Why do we actually care about AI Frontend Dev right now?
With AI becoming part of almost every tool we use — Figma, Canva, Adobe, and beyond — the urgency to understand where it adds real value (and where it doesn’t) has never been greater.
And instead of leaving it at theory, we did what engineers do best: we tested it.
Two of our engineers, Anton Herasymenko and Ivan Datsunov, set up an internal experiment. The goal was clear: assess how far AI can go in converting static designs into functioning code without much manual input.
The setup was intentionally simple. We took a set of Figma screens — representing the client’s idea for a new application — and gave them to a coding assistant. No database, no APIs, no fully mapped-out logic. Just the design and the challenge: Can we generate meaningful front-end code with minimal developer effort using AI tools?
The intention wasn’t to build a production-ready app. Instead, we wanted to understand the boundaries. Where does AI help? Where does it fail? And more importantly — how can we use this insight to work smarter?
IIt didn’t take long to see where AI tools like Cursor and similar developer assistants could genuinely accelerate progress.
The models handled basic layout structure well. Things like forms, buttons, standard input flows, and container components were generated with a fair degree of accuracy. In terms of raw speed, this was impressive. What would normally take half a day of repetitive coding now took a few minutes.
This is where AI frontend dev shows real promise — accelerating routine UI generation and giving teams a faster starting point. More importantly, these auto-generated components served as a working base for further development. Developers could quickly modify or refine what was generated instead of starting from scratch. That kind of head start is valuable in MVP stages or fast iterations.
As Ivan Datsunov explained during the debrief, “If it’s a straightforward UI, AI can absolutely help you move faster. It won’t get it perfect, but it’ll get you 70–80% of the way. And that’s already a win.”
The moment we moved beyond the visual layer, things became more complicated.
Any time the application needed to reflect non-standard behavior, custom workflows, or domain-specific logic, the AI struggled. It lacked the context to interpret what the business actually needed. And the effort it took to prompt and re-prompt the model into doing the right thing quickly outweighed the benefit of using it at all.
As Ivan pointed out, "You start spending more time trying to explain what you want than if you just wrote the code manually."
This aligned perfectly with our corporate statement: AI doesn’t magically increase productivity just because it’s there. It only helps if you’re solving the right problem in the right way.
This experiment wasn’t just about exploring a cool feature. It was a direct response to an open question within our team. It was also a proof of how we approach new technologies at Opinov8, not with blind enthusiasm, but with curiosity, structure, and a focus on real outcomes.
Christian Aaen, our co-founder, framed it well: “AI won’t solve everything. But if we learn where it fits, it will absolutely change the way we work.”
He also raised an idea that might shape our next experiment: Can we improve AI output by training it on our existing codebase? If a model could learn our architecture and coding conventions, would its suggestions become more useful? That’s a conversation we plan to continue.
We’re now preparing a similar experiment on the backend side — where logic, performance, and structure are even more critical. Following our AI Frontend Dev test, where we focused on generating UI components, the next step is to see how AI performs when it comes to state management, authentication, API handling, and more.
This is part of a larger, ongoing effort across Opinov8 to understand how AI should fit into our delivery pipeline — at every stage, from discovery and design to deployment and scale.
And as always, we believe the best insights come not from reading whitepapers, but from building things ourselves.
AI Frontend Dev refers to the use of AI-powered tools to automate parts of frontend development — like generating layout, components, or boilerplate code from design files.
AI tools can generate basic UI components and structure from Figma designs. However, they often fall short when it comes to complex logic, data flow, or domain-specific requirements.
No, the goal wasn’t to launch a production-ready app. The experiment focused on understanding where AI adds value in the early stages of frontend development.
AI tools are helpful for speeding up repetitive tasks and scaffolding UIs. But they struggle with custom logic and need close developer supervision.
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Choosing the right data platform is a key step in building a scalable, intelligent, and future-ready organization. The volume and variety of data continue to grow — along with the demand for faster insights, tighter compliance, and support for both analytics and machine learning.
From financial services to logistics and life sciences, the pressure is the same — connect diverse data sources, ensure compliance, and enable smarter decisions through automation and analytics.
Outdated stacks slow teams down. Disconnected tools increase risks. Choosing a platform with the right balance of flexibility, performance, and governance helps unlock your data’s potential across departments — from reporting to real-time automation.
This guide is built for decision-makers who want clarity. Whether you're upgrading legacy systems or designing a new stack, the playbook outlines a practical path forward — based on real experience and industry benchmarks.
Many businesses begin their data transformation without fully defining their needs. Choosing the right data platform means understanding how your teams use data today — and how they’ll need to use it tomorrow.
Before committing to a solution, ask:
These questions are part of the framework included in the downloadable guide. Use them to clarify your priorities, avoid unnecessary complexity, and align your technology with your business goals.
Cloud consulting has long passed the point of being a buzzword. Today, it's the engine powering enterprise scalability, digital transformation, and cost efficiency. But for C-level decision-makers at companies like Booking, Reno, or any enterprise operating across borders, there’s a new question on the table:
“Do we really need our cloud consulting partner to be nearby?”
In this article, we’ll unpack why nearshoring your cloud consulting services isn't just about convenience — it’s a strategic business move that accelerates project delivery, increases collaboration, and reduces risk.
Before we dive into location, let’s quickly address the “why cloud consulting” question for 2025. With AWS Cloud, Azure, and Google Cloud driving 90% of enterprise IT innovation, cloud is not an infrastructure choice — it’s a business imperative.
Yet many organizations still face:
Cloud consulting companies help enterprises migrate, optimize, and secure their cloud environments. But here’s the twist: not all consultants are created equal, and not all locations are strategic.
Nearshoring is the choice to work with a cloud consulting company based in a nearby region — often within the same time zone or just one over. Unlike offshoring, where teams are located on distant continents, nearshoring supports real-time communication, better cultural fit, and greater efficiency in cost and talent use.
For example, a Netherlands-based enterprise might partner with a cloud consulting team in Eastern Europe or Egypt. A U.S. East Coast company might look toward Latin America. The result? Faster feedback loops, real-time collaboration, and fewer delays in critical AWS cloud deployments or modernization projects.
Let’s break down the core reasons why proximity matters when choosing a cloud consulting partner:
When you’re rolling out an AWS cloud migration or restructuring your cloud infrastructure, waiting 24 hours for a response is not sustainable. Nearshoring ensures overlapping working hours, which means:
Local norms matter. Whether it’s GDPR compliance in Europe or HIPAA alignment in the U.S., working with cloud consulting companies that understand the regulatory landscape in your region reduces friction and legal exposure.
Proximity allows for easier site visits, real-time code reviews, and stronger governance. Many companies feel more confident scaling their AWS cloud environment when their consulting team is just a short flight away.
Working with a partner who “gets” your business hours, team structure, and delivery cadence improves strategic alignment. It’s the difference between reactive troubleshooting and proactive scaling.
If you're looking for where this approach shines most, here are a few standout examples:
When shortlisting partners, ask the following:
| Question | Why It Matters |
| Do they have AWS, Azure, or GCP certifications? | Validates expertise and access to cloud-native resources |
| Are they experienced with companies in your industry? | Domain expertise accelerates value delivery |
| Can they provide references from similar-scale enterprises? | Proof of capability and reliability |
| Do they offer hybrid/remote collaboration models? | Ensures flexibility without sacrificing speed |
| Are they nearshoring or offshoring their services? | Impacts communication, speed, and security |
If you’re searching for reliable cloud consulting companies near you, consider partners with proven enterprise experience — like Opinov8.
At Opinov8, we support mid-to-large enterprises with nearshore digital delivery centers and tailored cloud services. Our two flagship offerings include:
We simplify your move to the AWS cloud, Azure, or GCP by identifying what’s ready and what needs preparation. Our risk-focused approach helps manage costs, prevent downtime, and guide you with a custom migration roadmap.
Already in the cloud? We evaluate your setup and provide actionable insights to boost performance, security, and cost efficiency.
Need help deciding what’s next? Get in touch with our cloud experts
What does a cloud consulting company do?
Cloud consulting companies assess your infrastructure, design migration strategies, implement cloud-native solutions, and optimize security, cost, and performance.
Is nearshoring more expensive than offshoring?
Not necessarily. Nearshore partners often offer a better balance between cost savings and operational efficiency, with reduced risk of delays or miscommunication.
Can I work with an AWS-certified consultant near me?
Yes. Many cloud consulting companies specialize in AWS Cloud and operate in nearby regions — giving you access to top-tier talent without the time zone or language barriers.
Choosing a cloud consulting partner near you is about more than convenience. It's about velocity, visibility, and value. For C-level executives navigating multi-region cloud deployments or modernization efforts, nearshoring offers the sweet spot between cost and control.
At Opinov8, our nearshore teams across Europe, Egypt, and Latin America support enterprise clients in migrating, scaling, and optimizing their cloud operations — with AWS-certified experts and real-time collaboration baked in.
If you’re searching for “cloud consulting near me,” you’re already thinking strategically. Let’s make it actionable. Schedule a free consultation with our enterprise cloud experts and see how we can move your roadmap forward — faster.
In the world of life sciences, time isn’t just money — it’s lives. For nearly five decades, one industry leader has been helping pharmaceutical companies get critical treatments to patients faster and more safely. With a 50+ team of experts, they’ve earned their reputation through robust consulting across Real-World Evidence, Market Access, Advanced Market Research, and HCP engagement.
But even leaders hit a point where legacy tools can no longer keep up with modern demands.
As pharmaceutical clients pushed for faster, deeper insights — often in near real-time — this life sciences consultancy found itself facing a mounting challenge:
How do you efficiently manage and process massive, varied, and fast-growing data sources?
They needed more than a patchwork of solutions. They needed a modern, scalable foundation capable of:
That’s when they partnered with Opinov8.
As a trusted Databricks partner, our team brought both platform expertise and a deep understanding of data architecture. We guided the client through the development of a robust, scalable platform built on Databricks and structured around the medallion architecture (bronze, silver, and gold layers).
Here’s how we made it happen:
We built ingestion pipelines that pulled data from multiple sources — SFTP, REST APIs, CSVs — into the bronze layer, using Databricks best practices.
Then came transformation in the silver layer, where our team applied PySpark and Delta Lake to cleanse, validate, and combine datasets.
In the gold layer, analytics-ready data was made available for dashboards, advanced market research, and machine learning.
We developed and deployed 100+ daily workflows, supporting both batch and streaming data needs.
Our modular approach meant that workflows could be reused and scaled across different business domains — improving both agility and maintenance.
By integrating MLflow, we enabled seamless model experimentation, tracking, and deployment.
Models are now reproducible across environments, moving effortlessly from notebook to production pipeline.
The platform processes hundreds of gigabytes of data per day, with elasticity built in. As data volume and use cases grow, the platform scales without breaking a sweat.
With their new Databricks-based platform, the client has turned a technical overhaul into a business advantage:
This transformation marks more than a technological leap — it’s a strategic move toward continuous innovation in a mission-critical industry. With Opinov8 and Databricks by their side, our client is well-positioned to stay ahead of market demands while keeping patients at the heart of everything they do.
In life sciences, data saves lives. And we’re proud to be building the platforms that make that possible.
Slow systems kill conversions, frustrate users, and spike cloud costs. But the fix isn't always more compute — it’s smarter delivery.
You’ve invested in a high-availability architecture. Your cloud bill reflects that. Yet the experience? Still not fast enough. When milliseconds impact user retention and search rankings, scaling blindly isn’t a sustainable strategy.
Caching changes the game — not by doing more, but by doing less but smarter.
Let’s skip the jargon. Here’s what caching unlocks for your platform at scale:
Data your users need most is served in-memory, instantly — no need to query databases over and over.
Your backend breathes easier. Fewer repetitive calls, fewer performance bottlenecks, better stability during traffic spikes.
Serving cached content from memory is significantly cheaper than scaling databases or compute on-demand.
Whether your users are in Berlin or Buenos Aires, caching keeps the experience snappy and consistent.
Caching isn't a bolt-on. It's a strategic layer that fits across multiple touchpoints:
AWS ElastiCache (backed by Redis, Valkey or Memcached) is built for this job. It’s:
You don’t have to re-architect. You just need to insert ElastiCache where latency matters most.
Traditionally, you could either go fast or go cheap — not both. Caching breaks that rule.
By offloading hot data to memory, you reduce compute cycles and storage IOPS, which means:
It’s the rare optimization that hits speed, scale, and spend at the same time.
Book a performance audit with our AWS-certified experts.
We’ll pinpoint the high-latency zones, model the impact of ElastiCache, and outline a caching plan tailored to your AWS architecture.
Because in the cloud, performance isn’t just a feature — it’s a competitive edge.
Data runs the world. But the way you store and manage it can either boost your business or slow it down. Some companies stick to on-premises servers because they believe they offer better control. Others move to the cloud, looking for scalability and cost savings. There is no one-size-fits-all answer. It all depends on your business needs, growth plans, and budget.
Let’s break it down and see which option makes the most sense.
For years, companies have used on-premises infrastructure to store and manage data. With servers and hardware on-site, businesses have full control over their IT environment. This setup works well for industries that deal with strict security regulations, such as finance, healthcare, or government agencies.
But managing on-prem infrastructure is not easy. Hardware needs constant upgrades, IT teams must handle security, and scaling up requires heavy investment. It’s a traditional model that still works, but it comes with serious challenges.
Cloud computing changed the game. Instead of running everything on local servers, businesses can store and process data on remote data centers, managed by providers like AWS, Microsoft Azure, or Google Cloud.
With cloud solutions, you don’t need to worry about hardware maintenance or security updates — your provider takes care of that. Scaling is also much easier. Need more storage? Just upgrade your plan.
Many companies prefer the cloud because it allows them to focus on growth instead of managing infrastructure.
Many companies don’t want to be tied to a single provider, so they choose a multi-cloud strategy. This allows businesses to distribute workloads across multiple platforms like AWS, Azure, and Google Cloud. It reduces dependency on a single vendor and improves reliability and flexibility.
A multi-cloud approach also gives companies more control over costs, performance, and security. Some workloads run better on AWS, while others perform better on Azure or Google Cloud. Having multiple options makes it easier to adapt and scale as needed.
For businesses working with large amounts of data, Databricks provides a Lakehouse platform that blends the flexibility of data lakes with the reliability of data warehouses. It allows companies to process, analyze, and manage data across multiple cloud providers, including AWS, Azure, and Google Cloud, without vendor lock-in.
Both cloud and on-prem have their place. The right choice depends on your business model, security needs, and future plans.
Many businesses now use a hybrid model — keeping critical data on-prem while using cloud solutions like Databricks for analytics and AI. This reduces infrastructure costs while maintaining control over sensitive information.
More businesses are moving towards data-driven decision-making, and cloud solutions are leading the way. On-prem infrastructure still has its role, but the flexibility of cloud and hybrid models is hard to ignore.
A multi-cloud strategy provides even more flexibility, helping businesses optimize performance, reduce risk, and manage costs effectively. Databricks helps companies integrate and manage data across multiple cloud environments, making it easier to handle large-scale analytics and AI development.
If you’re unsure which model is right for you, let’s discuss your data strategy and find the best solution for your business.
Every second counts when it comes to website performance. Slow-loading pages frustrate users, hurt SEO, and impact conversions. That’s where AWS CloudFront comes in. This powerful Content Delivery Network (CDN) helps businesses deliver content faster, no matter where their users are.
CloudFront caches and distributes your content across a global network of edge locations. This means users get faster load times, improved performance, and a seamless browsing experience.
CloudFront uses edge locations worldwide to deliver content quickly. When a user requests a file, CloudFront serves it from the nearest cached location. If it’s not cached, CloudFront retrieves it from the origin server, caches it, and delivers it — making future requests faster.
Implementing CloudFront is simple but requires smart configurations for optimal performance.
Analyze traffic patterns to optimize data transfer costs. Consider using regional price class selections based on where your audience is located.
CloudFront does more than just speed up websites. Businesses that implement it effectively typically see:
CloudFront isn’t just a “set it and forget it” tool. Continuous tweaks and refinements unlock its full potential.
Identify which assets benefit most from edge caching. Classify content by type, update frequency, and impact on performance.
Configure caching strategies based on content type. Set longer cache durations for static assets like images and CSS. Adjust TTLs for dynamic content.
Use multiple origin servers for different content types. Implement origin failover for high-availability applications.
Secure sensitive data with field-level encryption. Use signed URLs or cookies to control access. Enable AWS Shield to mitigate DDoS attacks.
New features and improvements roll out regularly, bringing more speed, security, and efficiency. Keeping up with updates ensures you make the most of what CloudFront has to offer.
A well-optimized CDN can transform how your website handles traffic, improves reliability, and protects against threats. Our AWS-certified team can help you configure CloudFront to match your specific needs.
Let’s fine-tune your content delivery for better performance and a seamless user experience.
In this AI for Businesses Guide, created by AWS and Opinov8, you’ll gain access to:
📈 Key trends and emerging AI technologies shaping digital transformation in 2025.
💻 The essential role of AI-powered cloud-based solutions in accelerating innovation and business efficiency.
🌐 How AI and cloud computing are reshaping business operations, enabling scalability, and fostering productivity.
Agile in software development is a way of managing software projects that focuses on flexibility, collaboration, and customer feedback. It breaks agile into small and manageable parts. Instead of planning everything upfront, teams work in short cycles, adapting as they go.
Traditional software development followed a strict step-by-step process. Developers planned everything, built the product, and then tested it. This took months or even years. If something went wrong, fixing it was slow and expensive.
Agile methods solve this problem. Teams deliver small, working parts of software regularly. They get feedback early, make changes quickly, and improve the product step by step.
Using Agile in software development allows teams to stay aligned with customer needs and market changes.
The Software Development Life Cycle (SDLC) is the process of planning, creating, testing, and deploying software. It includes several stages:
Agile transforms these stages. Instead of doing them once in order, Agile teams repeat them in short cycles called sprints.
Several Agile frameworks help teams work efficiently. Here are the most popular ones:
Scrum organizes work into sprints, usually lasting 1-4 weeks. Teams hold daily stand-up meetings to discuss progress and challenges. At the end of each sprint, they review their work and plan the next one.
Applying Agile in software development enhances communication and collaboration between team members.
Agile promotes continuous improvement, ensuring that development processes evolve.
Implementing Agile in software development helps teams react to changes in requirements quickly.
Kanban uses a visual board to track tasks. Teams move tasks from "To Do" to "In Progress" to "Done." This method helps manage workflow and avoid bottlenecks.
XP focuses on high-quality code. It encourages frequent testing, pair programming (two developers coding together), and continuous feedback.
Inspired by manufacturing, Lean aims to reduce waste and maximize value. It eliminates unnecessary work and focuses only on what the customer needs.
FDD breaks the project into features. Developers deliver features one by one, ensuring constant progress.
Agile is still the go-to in software development. But it's not standing still. In 2025, it's getting a serious tech upgrade.
AI tools now help teams plan better and fix problems before they happen. They spot bottlenecks, suggest priorities, and even review code. Less guessing, more smart decisions.
CI/CD isn’t optional anymore. It’s a must. Developers don’t waste time on manual builds or tests. Tools take care of it, so updates roll out faster and with fewer bugs.
Most teams build apps straight for the cloud. They use containers, serverless tools, and auto-scaling. It makes launching and updating apps quicker—and way easier to manage.
Big companies don’t keep Agile inside one team anymore. They scale it across the whole business. Frameworks like SAFe help them keep everyone aligned without losing speed.
Design thinking blends into Agile now. Teams test ideas with real users early on. This means fewer bad surprises later and more products that people actually want.
Agile emphasizes the importance of team collaboration and accountability.
Agile methods reshape the SDLC by making it more adaptive and efficient.
With Agile in software development, teams can focus on delivering value to customers incrementally.
Agile allows for more frequent releases, which can lead to higher customer satisfaction.
Agile has many benefits, but it also has challenges:
Agile works best for projects that require flexibility and quick delivery. It suits startups, software products with evolving requirements, and teams that work closely with users.
However, for highly regulated industries or projects with strict deadlines and fixed scopes, traditional SDLC models may still be better.
Agile methods in software development have changed the way teams build software. By breaking work into small cycles, Agile improves speed, quality, and adaptability. It reshapes the software development life cycle stages, making the process more flexible and user-focused.
If your team needs faster results, better collaboration, and continuous improvement, Agile might be the right choice.
Nevertheless, understanding when to apply agile in software development is crucial for achieving desired outcomes.
In conclusion, Agile in software development reshapes traditional approaches, prioritizing customer feedback and adaptability.
What do Netflix, Amazon, and Google Cloud have in common? They’ve mastered the art of resilience, ensuring their services are always up and running. Downtime isn’t just an inconvenience; it’s lost revenue and damaged trust. That’s why businesses today must prioritize cloud resilience.
In simple terms, high availability means your system is always accessible, while reliability ensures it performs consistently. These two principles are the backbone of any cloud-based service, helping businesses stay operational, even in unexpected scenarios.
Building a cloud solution that never fails? Almost impossible. But minimizing downtime? That’s achievable. The key principles include:
Think of redundancy as an insurance policy for your cloud setup. If one server goes down, another takes over seamlessly. Failover mechanisms ensure traffic is redirected instantly, so users don’t even notice a hiccup.
Not all load balancers are created equal. You can choose from:
Load balancers distribute incoming traffic across multiple servers, ensuring no single server gets overwhelmed. The result? Faster response times, improved fault tolerance, and higher availability.
A fault-tolerant system isn’t just about backups. It’s about smart design. Here’s what makes a system resilient:
Disruptions happen. The question is: Are you prepared? A well-structured disaster recovery (DR) plan ensures your business keeps running, no matter what.
You can’t fix what you can’t see. That’s why monitoring tools are crucial:
Testing isn’t optional—it’s essential. Key testing types include:
Without security, availability doesn’t matter. A cyberattack can take down even the most resilient system. Prioritizing security is non-negotiable.
Resilient cloud solutions require a mix of high availability, fault tolerance, and security. The key takeaways?
Downtime is expensive, and users don’t have patience for unreliable services. By adopting the right strategies, businesses can ensure their cloud solutions remain resilient, no matter what challenges arise.
High availability ensures minimal downtime by using redundant systems, while fault tolerance allows systems to continue functioning even if a component fails.
Load balancing distributes traffic across multiple servers, preventing overloads and improving system performance and availability.
Popular monitoring tools include Prometheus, Datadog, and AWS CloudWatch, which help track performance and detect issues.
Disaster recovery ensures that businesses can quickly recover from disruptions, reducing downtime and data loss.
Regular testing, including load, failover, and chaos testing, should be integrated into the development cycle to maintain reliability.
Modernization is redefining how enterprises operate. Traditional industries like HealthTech, Logistics, Retail, Maritime are overcoming challenges like outdated systems and siloed data to scale effectively and innovate.
Our new Enterprise Modernization Report offers practical insights from real-world successes, highlighting strategies that drive measurable results. It’s a guide for organizations ready to embrace change and thrive.
This report dives into the most pressing modernization challenges facing enterprises today, including:
Fill in the form below and get the insights, strategies, and real-world examples that will guide your modernization journey.
With the proliferation of data breaches and increasing public awareness of personal information security, businesses must prioritize compliance with data privacy regulations, especially in the context of security and compliance. This article will explore the implications of various data privacy regulations for tech companies and offer insights into navigating the complex landscape of compliance.
As business owners, understanding the current legal framework surrounding data privacy and the overarching theme of security and compliance is crucial not only for safeguarding customer information but also for sustaining operational integrity and trust. With regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) shaping the way data is handled globally, tech companies must adapt and implement robust compliance strategies. This article will delve into key regulations, compliance challenges, and best practices for navigating the evolving data privacy landscape.
Tech companies face numerous challenges in achieving compliance with data privacy regulations and ensuring Security and Compliance. The complexity of varying laws across different jurisdictions can create confusion, especially for organizations operating globally. Companies must navigate differences in consent requirements, data subject rights, and penalties for non-compliance, which can vary significantly between regulations.
Additionally, the rapid pace of technological advancement can complicate compliance efforts. New technologies such as artificial intelligence and machine learning can lead to unforeseen data usage and privacy implications, necessitating ongoing legal and technical assessments. This dynamic environment requires tech companies to be proactive and adaptable in their compliance strategies.
Non-compliance with data privacy regulations can have severe financial implications for tech companies. Beyond the potential for substantial fines, businesses may face legal costs associated with defending against lawsuits, civil penalties, and damages resulting from data breaches. These costs can escalate quickly, particularly in cases involving large-scale data breaches that impact thousands or millions of individuals.
Moreover, the reputational damage resulting from non-compliance can lead to decreased customer trust and loss of business. Tech companies that fail to prioritize data privacy may find it challenging to attract and retain customers, ultimately impacting their bottom line. Therefore, understanding the financial stakes is crucial for business owners when developing compliance frameworks.
The need for compliance with data privacy regulations can significantly impact a company's operational framework and strategic planning. As organizations strive to ensure compliance, they may need to invest in new technologies, hire compliance officers, and develop robust data governance policies. This shift can lead to increased operational costs but is essential for long-term sustainability.
Furthermore, compliance efforts can drive innovation within organizations. By focusing on data privacy and security, tech companies can develop new products and services that prioritize consumer trust. This alignment with data privacy principles can serve as a competitive advantage, attracting customers who value their privacy and security.
The first step in developing a compliance framework is conducting a thorough assessment of current data practices. Companies must evaluate how they collect, process, and store personal data, identifying areas of risk and non-compliance. This assessment should include documentation of data flows, data classification, and third-party data sharing practices.
Employing tools such as data mapping and risk assessments can help uncover weaknesses in data management processes. Understanding where data resides and how it moves within the organization is critical in mitigating risks associated with data breaches and regulatory violations.
Once current data practices are assessed, tech companies must develop and implement comprehensive data governance policies. These policies should outline the organization’s approach to data management, including data collection, usage, sharing, and retention. Key components of a data governance policy may include data classification, access controls, and procedures for responding to data subject requests.
Effective data governance not only ensures compliance with legal requirements but also fosters a culture of accountability within the organization. By establishing clear guidelines and responsibilities related to data handling, companies can enhance transparency and trust with customers.
Employee training is a critical element of a successful compliance framework. All employees, regardless of their role, should receive training on data privacy principles, company policies, and specific regulatory requirements. This training should include practical scenarios and case studies to illustrate the importance of data protection in everyday operations.
Regular training sessions can help reinforce a culture of compliance and ensure that employees are equipped to recognize and respond to potential data privacy issues. Additionally, fostering an environment where employees feel comfortable reporting concerns can further enhance data protection efforts.
Investment in the right tools and software is essential for tech companies to achieve compliance with data privacy regulations. Data management platforms can facilitate the collection, storage, and processing of personal data while ensuring compliance with relevant laws. These tools can also automate processes such as data subject requests and breach notifications, reducing the risk of human error.
Cloud-based solutions often provide scalability and flexibility, making it easier for companies to adapt to changing compliance requirements. By leveraging technology, organizations can enhance their data management capabilities and streamline compliance efforts, allowing them to focus on their core business objectives.
Artificial Intelligence (AI) can play a transformative role in aiding compliance efforts. AI-driven solutions can analyze vast amounts of data to identify risks and anomalies, helping organizations detect potential compliance breaches before they occur. Machine learning algorithms can also assist in automating data classification and management processes, improving efficiency and accuracy.
Furthermore, AI can enhance data security measures by providing advanced threat detection and response capabilities. By adopting AI technologies, companies can strengthen their compliance frameworks and proactively address data privacy challenges.
Implementing best practices for data security is paramount for tech companies seeking to comply with data privacy regulations. This includes establishing robust access controls, encrypting sensitive data, and regularly conducting security audits and assessments. Companies should also implement multifactor authentication and ensure that data is stored securely.
Regularly updating software and systems is critical to protecting against emerging threats. Additionally, fostering a culture of security awareness among employees can further enhance data protection. By adopting a holistic approach to data security, tech companies can significantly reduce the risk of data breaches and ensure compliance with relevant regulations.
The landscape of data privacy regulations is constantly evolving, with emerging trends indicating a shift toward stricter requirements. Governments worldwide are becoming increasingly aware of the importance of data protection, leading to the introduction of new regulations and amendments to existing laws. Businesses must stay informed about these developments to remain compliant and competitive.
One notable trend is the growing emphasis on consumer rights, including the right to data portability and the right to be forgotten. As public awareness of data privacy issues continues to rise, businesses can expect to encounter more stringent regulations that prioritize consumer protections.
To prepare for future regulatory landscapes, tech companies must adopt a proactive approach to data privacy compliance. This includes staying informed about emerging regulations, participating in industry discussions, and engaging with legal experts to understand potential impacts on their operations.
Additionally, fostering a culture of compliance within the organization can help ensure that data privacy remains a priority across all levels. By investing in ongoing education and training, companies can equip their teams to navigate the complexities of evolving regulations effectively.
In conclusion, data privacy regulations such as the GDPR, CCPA, and HIPAA represent critical frameworks that tech companies must navigate to protect consumer data and achieve compliance. The implications of these regulations extend beyond legal compliance, influencing financial stability, business operations, and customer trust.
Developing a comprehensive compliance framework that includes assessing current data practices, implementing data governance policies, and leveraging technology is essential for organizations seeking to thrive in the digital landscape. As regulations continue to evolve, adaptability and proactive engagement will be key to navigating future challenges in data privacy.
The primary goals of data privacy regulations are to protect individuals' personal information, enhance transparency regarding data collection and usage, and empower consumers with rights over their data.
Tech companies can ensure compliance by conducting comprehensive assessments of their data practices, implementing standardized data governance policies, and staying informed about regulatory changes across jurisdictions.
Consequences of non-compliance can include substantial financial penalties, legal fees, loss of customer trust, and reputational damage that can ultimately impact business performance.
Employee training is crucial as it ensures that all staff members understand their responsibilities regarding data protection, helps identify potential risks, and promotes a culture of compliance within the organization.
Technology plays a vital role by providing tools for data management, automating compliance processes, enhancing data security, and facilitating the analysis of data privacy risks and compliance obligations.
When businesses in the U.S. consider nearshore software development, Colombia often stands out as a top choice. With its strategic location, thriving tech ecosystem, and highly skilled talent pool, Colombia has positioned itself as a vital hub for companies seeking reliable and cost-effective solutions. Colombia software development offers a unique blend of quality, innovation, and proximity, making it an ideal partner for U.S.-based organizations. Let's explore why this vibrant country is becoming a go-to destination for U.S.-based organizations.
One of Colombia's greatest assets is its proximity to the U.S., both geographically and in terms of time zones. For U.S. companies, this translates to easier communication, smoother collaboration, and real-time problem-solving. Flight times from Miami to Bogotá average about 3.5 hours, further simplifying travel and enabling stronger business relationships. Whether you're on the East Coast or West Coast, overlapping work hours make project management seamless, fostering an agile workflow.
Moreover, the alignment of time zones minimizes delays in communication and allows for real-time updates and adjustments, which are crucial in agile development methodologies. This accessibility makes Colombia an ideal choice for companies that value efficiency and responsiveness in their projects.
Colombia boasts over 150,000 IT professionals. The country ranks highly in global IT assessments, particularly in problem-solving and mathematics skills, making it an attractive destination for companies seeking quality engineering talent. These professionals not only bring technical expertise but also cultural alignment, enhancing collaboration with U.S.-based teams.
The diversity within Colombia's talent pool is another significant advantage. Developers and engineers in Colombia are accustomed to working on a variety of projects across industries, from fintech and healthcare to logistics and e-commerce. This adaptability ensures that they can meet the unique needs of each client, regardless of the project's complexity.
Colombia’s tech industry has seen tremendous growth over the past decade. Cities like Bogotа and Medellin are becoming major tech hubs. Bogota is recognized as the largest IT hotspot, with numerous startups and global tech companies establishing operations there. Medellin, once known for its industrial prowess, is now gaining traction as a center for innovation and technology development. Events like Medellin’s Innovation Week and the rise of startup accelerators underline the country's commitment to staying ahead in the digital age. Colombia software development is increasingly driven by the innovation coming out of these dynamic cities, attracting businesses worldwide.
In addition to these hubs, smaller cities like Cali and Barranquilla are emerging as noteworthy players in the tech scene. These cities are home to growing communities of developers and offer untapped potential for businesses looking to expand their operations in Colombia. With government-backed initiatives and increased foreign investment, Colombia’s tech ecosystem continues to thrive, making it a powerhouse for innovation in Latin America.
Colombian software developers, along with their counterparts in Argentina and other Latin American countries, earn approximately 2.5 to 3 times less than developers in the U.S., according to Gross Annual Salary data on Glassdoor. This significant wage difference allows U.S. businesses to optimize their budgets without sacrificing quality. The lower cost of living in these regions further enhances the affordability of hiring top-tier talent, making Colombia an especially attractive destination for outsourcing. This cost-effectiveness empowers companies to allocate savings toward innovation, expansion, or other strategic priorities.
Furthermore, the cost savings extend beyond salaries. Reduced travel expenses, minimal time zone challenges, and efficient workflows contribute to an overall lower project cost, enabling companies to reinvest these savings into other areas of growth.
The Colombian government actively promotes the digitalization of the economy and supports the tech industry through initiatives like Misión TIC, which aims to train an additional 100,000 programmers. Tax incentives, free trade agreements, and streamlined processes for international companies further enhance the business-friendly environment. These efforts have solidified Colombia software development as a key contributor to the region’s economic and technological growth, attracting global businesses seeking top-tier talent.
Additionally, Colombia’s emphasis on education and skill development has created a robust pipeline of future talent. Programs in universities and technical institutes are tailored to meet the demands of the global tech industry, ensuring that graduates are job-ready and equipped with the latest skills.
The Colombian software development industry is projected to grow significantly, with estimates suggesting it could reach a market size of $35 billion by 2028. Increasing foreign investment, coupled with a robust ecosystem that encourages startups and innovation, positions Colombia as a key player in the global software development landscape.
This growth is also fueled by Colombia’s strategic partnerships with multinational companies. As more businesses recognize the country’s potential, the influx of projects and collaborations will further elevate its standing in the global tech community. The government’s continued focus on building digital infrastructure and fostering innovation will play a pivotal role in sustaining this momentum.
At Opinov8, we recognized Colombia’s potential early on and established a development center in Bogota. Our Colombian team exemplifies the excellence and innovation that make the country a standout destination for software development. We use Opinov8’s expertise and Colombia’s strengths to deliver world-class solutions to our U.S. clients. This approach ensures smooth teamwork and outstanding results.
From fintech solutions to enterprise applications, Opinov8’s Colombian development center has consistently delivered projects that exceed client expectations. We're dedicated to creating a collaborative and innovative space where Colombia's tech ecosystem can truly thrive.
Colombia is an excellent nearshore option for the U.S. companies. But also it’s a strategic partner for growth. So does Opinov8. If you’re looking for a reliable partner with strong local expertise, our team in Colombia is here to help. Let’s discuss how we can support your business goals.
Сhoosing the right system architecture is crucial for scalable, efficient, and maintainable digital products. Modular architecture has emerged as a versatile approach, blending the strengths of traditional monoliths and microservices. By organizing software into independent modules, teams can achieve greater agility and prepare for future growth without unnecessary complexity. Let's delve into how monolith can revolutionize product & platform development.
Modular monolith architecture is a software design principle that structures applications into self-contained modules. Each module manages a specific business function, enabling better maintainability, and adaptability. This approach bridges the gap between monolithic and microservices architectures, offering flexibility without the overhead of managing distributed systems.
Modular systems allow teams to work independently on specific components without affecting the entire application. This reduces bottlenecks, accelerates delivery, and minimizes conflicts.
Testing efforts focus on individual modules rather than the entire application. This modular testing approach leads to faster debugging and maintenance cycles.
With fewer infrastructure requirements compared to microservices, modular architecture reduces operational costs while still enabling long-term scalability.
| Feature | Monolith | Microservices | Modular Monolith |
| Deployment Complexity | Low | High | Moderate |
| Scalability | Limited | High | Moderate |
| Maintenance | Difficult | Moderate | Easy |
| Transition Flexibility | Limited | Moderate | High |
Overly interconnected modules defeat the purpose of modularity. Using well-defined interfaces and communication protocols mitigates this risk.
Distributed systems often face challenges with data synchronization. Employing patterns like the Saga or Outbox ensures consistency across modules.
While modular designs are simpler than microservices, they can grow complex with mismanagement. Continuous code reviews and adherence to design principles are key.
Modular monolith architecture empowers tech teams to innovate, adapt, and evolve their digital products with agility. It offers a balanced approach that combines the simplicity of monoliths with the scalability of microservices. Whether you're building a startup's MVP or optimizing enterprise platforms, modular architecture provides the flexibility to meet today’s demands while preparing for tomorrow's challenges.
The technology industry is in a race against time. New frameworks, languages, and tools emerge rapidly. This creates endless opportunities but highlights the growing need for AI upskilling in tech teams to bridge the gap. Without effective solutions, tech teams struggle to keep pace as the divide between what they know and what they need to know widens. For many companies, this gap determines whether they succeed or fall behind.
Traditional training methods often fail. Generic online courses or week-long workshops rarely address the specific and immediate needs of developers under tight deadlines. The challenge is not just about learning new skills but doing it quickly and seamlessly without disrupting critical work. This is where artificial intelligence steps in.
At Opinov8, we lead the way in using AI to bridge this gap. Our experiments and insights show how AI reshapes how teams learn, adapt, and thrive in today’s fast-paced environment.
The skills gap poses a critical challenge for organizations, affecting productivity and delaying innovation. According to our colleagues from UST, 76% of companies report a severe shortage of AI professionals, leaving teams ill-equipped to harness the potential of emerging technologies.
The skills gap remains a significant challenge in 2025, reflecting trends from previous years. The Digital Leadership Report for 2023 highlighted that 67% of tech leaders attributed their struggles to keep up with industry trends to a lack of skills within their teams. This issue persists, as we observe similar challenges in our conversations with clients today.
Organizations continue to grapple with a shortage of expertise in critical areas like AI and cloud technologies. Without addressing these gaps, teams face mounting pressure. This shortage strains teams already balancing demanding projects. Without intervention, companies face slower timelines, rising costs, and missed opportunities to innovate — challenges that weaken their competitive position in fast-changing markets.
AI offers a targeted and efficient way to close the skills gap, addressing the unique needs of individual developers and entire teams. By integrating AI tools into learning processes, companies can achieve faster, more effective upskilling.
Unlike traditional training, which often delivers the same content to everyone, AI creates tailored learning experiences. By analyzing an individual’s strengths, weaknesses, and career goals, AI recommends specific courses, modules, or resources. For example, a front-end developer needing to master React might receive a custom path with focused exercises and hands-on projects, while a junior engineer could start with foundational JavaScript. This personalized approach ensures that learning efforts are relevant and immediately applicable, saving time and boosting engagement.
AI-driven tools like Cursor enhance learning by integrating into developers’ daily work. Cursor provides real-time coding suggestions, identifies potential errors, and explains best practices as developers write code. This approach allows team members to learn while solving real-world problems, blending training with productivity. This approach was validated during an AI Snap Talk, an internal Opinov8 initiative, where developers highlighted how Cursor turned repetitive debugging tasks into meaningful learning opportunities. By embedding training into day-to-day tasks, tools like this make upskilling a natural part of the work process.
AI also automates repetitive tasks, freeing up valuable time for skill development. For instance, AI can generate boilerplate code, suggest optimized algorithms, or even convert design files into functional front-end components. This eliminates manual drudgery, enabling developers to spend more time learning advanced techniques or experimenting with new technologies.
At Opinov8, we once explored how AI could streamline development by feeding Figma design files into an AI tool to prototype an application. The AI swiftly generated basic UI components, significantly cutting down on manual work. This freed our developers to focus on refining complex business logic, transforming a routine task into an opportunity to tackle more strategic challenges and grow their skills.
This experiment was one of many use cases discussed during our AI Snap Talks, where teams share insights on leveraging AI tools to enhance workflows and skill development. From simplifying debugging with Cursor to automating design-to-code transitions, these discussions underline AI's versatility in transforming how teams learn and deliver results. Such initiatives showcase the power of AI to make upskilling a seamless part of the development process while boosting overall productivity.
The power of AI also transforms how teams collaborate and share knowledge. By standardizing workflows and creating shared platforms for innovation, AI enhances teamwork and fosters a culture of continuous improvement.
AI simplifies complex processes, enabling teams to work more cohesively. It automates repetitive tasks, leaving developers with more bandwidth to focus on creative problem-solving. For instance, AI tools can provide real-time suggestions or corrections in code, ensuring consistency across team projects. Opinov8 developers frequently discuss how AI tools improve alignment by providing shared insights into workflows, helping teams work together more effectively. Yes, AI is a huge assistance for individuals, but it builds bridges between team members by creating a common foundation of knowledge as well.
Collaboration thrives when teams share experiences and insights. Platforms where members discuss use cases, tools, and best practices amplify the benefits of AI. Opinov8’s AI Snap Talks exemplify this approach. These internal sessions bring developers and engineers together to exchange real-world applications of AI, from automating debugging tasks to streamlining design-to-code workflows. Such discussions not only help teams adopt new tools but also spark ideas for applying AI to solve challenges specific to their projects.
Our AI Snap Talks are just one example of how we promote community-driven learning. Teams looking to adopt similar initiatives could explore other formats, such as regular workshops focused on emerging AI technologies, which provide hands-on experience and practical knowledge. Internal collaboration platforms are another option, encouraging continuous learning by enabling teams to share tutorials, insights, and new discoveries in real time. These approaches ensure that team members not only grow individually but also contribute to the collective expertise of their organization.
While AI has the potential to revolutionize upskilling, its adoption isn’t without obstacles. Skepticism, technical limitations, security concerns, and the need for balance between technology and human input are key challenges that organizations must address.
One of the most common hurdles is resistance to change. Some team members fear that AI tools may replace their roles, while others doubt AI’s ability to deliver meaningful results. At Opinov8, we tackle this by emphasizing AI as a supportive partner, not a replacement. Through initiatives like AI Snap Talks, we demonstrate practical use cases, showing how AI tools simplify repetitive tasks and enhance learning without disrupting workflows. By engaging teams in open discussions and hands-on sessions, we build trust and confidence in the technology.
A critical consideration when using AI tools is cybersecurity. Many organizations hesitate to adopt generative AI due to concerns over data privacy and the risk of exposing sensitive information. Opinov8 ensures that no sensitive client data ever enters generative AI tools or systems where external entities could access it. Our teams operate within strict data governance frameworks, using secure, on-premise, or trusted cloud solutions tailored to each client’s requirements. By safeguarding data, we maintain the trust of our clients while enabling teams to leverage AI effectively.
AI tools, while powerful, have their limits. They excel at automating repetitive tasks and providing recommendations but struggle with complex, nuanced logic. For instance, AI can generate boilerplate code or suggest debugging fixes, but it often requires human intervention for workflows involving intricate business-specific rules. Additionally, biases in training data can affect AI’s accuracy and relevance, potentially leading to inconsistent outputs.
Opinov8 addresses these issues by carefully evaluating and testing AI tools before implementation. We ensure that our teams understand AI’s strengths and limitations, using it where it delivers clear value while recognizing where human expertise is indispensable.
The most effective approach to upskilling combines AI tools with human mentorship. AI can handle repetitive tasks, analyze individual skill gaps, and offer tailored recommendations, but human mentors provide context, guidance, and a deeper understanding of complex problems. At Opinov8, we advocate for this hybrid model. AI tools enhance efficiency and provide personalized support, while mentorship ensures that knowledge is applied effectively. This synergy enables teams to grow their skills while delivering real-world results.
By addressing resistance, ensuring cybersecurity, acknowledging limitations, and adopting a balanced approach, Opinov8 ensures that AI becomes an enabler of growth, not a barrier to progress.
The future of upskilling is deeply tied to the unexplored potential of AI, as highlighted in our very first AI Snap Talk. Christian Aaen captured this sentiment by pointing out the current duality of AI: “If you read the news, some claim AI will fix everything, while others fear it will make us obsolete. The truth lies somewhere in between.” While AI can be transformative, its real value comes from addressing specific needs rather than applying it universally. AI, though expensive and still underexplored in many areas, is already proving effective when targeted thoughtfully.
One of these areas is adaptive learning. AI systems capable of understanding individual workflows and coding styles could revolutionize how developers upskill. For example, instead of generic lessons, developers would receive context-aware feedback tailored to their unique projects and team standards. This would not only enhance learning but also drive efficiency across teams.
Opinov8 shares this forward-thinking approach. By continuously experimenting with AI tools and engaging teams through initiatives, we aim to lead the charge in bridging the skills gap. The goal is clear: to prepare tech teams for the future by enabling smarter, faster, and more meaningful upskilling solutions
Curious how we can help your organization unlock its full potential?
The significance of technology cannot be overstated. Among the most revolutionary advancements is edge computing, a paradigm that is transforming how businesses interact with the Internet of Things (IoT). Edge computing decentralizes data processing, bringing it closer to the source of data generation, which enhances real-time decision-making and operational efficiency. This article delves into five pivotal ways in which edge computing is reshaping IoT for businesses, driving them toward greater efficiency and innovation.
Latency can be a silent killer in the realm of IoT. When devices communicate with centralized cloud servers, delays can occur due to the distance data must travel. Edge computing addresses this issue by processing data closer to its source, significantly reducing latency. This proximity enables near-instantaneous data processing and analysis, allowing businesses to make quick, data-driven decisions.
For instance, in a manufacturing setting, edge computing can facilitate real-time monitoring of machinery. Sensors can send data to local edge devices that analyze performance metrics on-site, detecting anomalies or inefficiencies almost immediately. This rapid response time not only enhances operational efficiency but also reduces costs associated with downtime.
Consider a smart city equipped with edge computing capabilities. Traffic management systems can instantly adjust traffic signals based on real-time data collected from vehicles and pedestrians, effectively reducing congestion and improving safety. Similarly, in agriculture, farmers are utilizing edge computing to monitor soil moisture levels and optimize irrigation systems, resulting in better crop yields and resource conservation.
These scenarios illustrate how businesses across various sectors are leveraging edge computing to enhance decision-making speed, ultimately leading to improved service delivery and customer satisfaction.
Data security is a paramount concern for any business operating in the digital age. The rise of IoT devices has increased the number of potential entry points for cyber threats. Edge computing mitigates these risks by processing sensitive data locally rather than transmitting it to a centralized cloud, thus reducing exposure to potential attacks. By keeping data closer to its source, edge computing lowers the risk of interception during transmission.
Moreover, implementing localized security measures at the edge can further enhance data protection. Businesses can deploy firewalls, encryption, and authentication protocols directly on edge devices, allowing for a more robust defense against cyber threats.
To maximize the security benefits of edge computing, businesses should adopt best practices such as regularly updating software and firmware on edge devices, conducting vulnerability assessments, and training employees on cybersecurity awareness. Additionally, implementing multi-factor authentication can significantly reduce the risk of unauthorized access to critical data.
By prioritizing data security at the edge, businesses can protect sensitive information while still reaping the benefits of real-time data processing and analysis.
As the number of connected IoT devices continues to rise, so does the demand for bandwidth. Network congestion can lead to slower data transmission, affecting the performance of IoT applications. Edge computing alleviates this issue by processing and filtering data locally, thus reducing the volume of data that needs to be sent back to centralized servers.
By only transmitting relevant information, businesses can significantly reduce the strain on their network infrastructure. This efficiency not only improves the performance of IoT applications but also lowers operational costs associated with bandwidth consumption.
To further enhance bandwidth efficiency, businesses can implement strategies such as data compression techniques, real-time analytics at the edge, and selective data transmission. For instance, instead of sending raw data continuously, a system might transmit only the results of critical analyses or alerts, conserving bandwidth and ensuring that essential information reaches decision-makers quickly.
By optimizing bandwidth usage, organizations can maintain smooth operations while accommodating the growing number of IoT devices and applications.
Operational resilience is crucial for businesses, especially in industries where downtime can lead to significant financial losses. Edge computing enhances system robustness by localizing processing and reducing reliance on centralized cloud servers. This decentralized approach allows businesses to continue functioning even in the event of network outages or cloud service disruptions.
In addition, edge computing supports redundancy and failover systems. If one edge device fails, others can seamlessly take over its functions, ensuring uninterrupted service and minimizing potential risks associated with system failures.
Several companies have successfully implemented edge computing to bolster their operational resilience. For instance, in the energy sector, utilities leverage edge computing to monitor and manage grid operations, allowing for real-time adjustments and maintenance without downtime. Similarly, retail chains use edge computing to manage inventory systems, ensuring they can continue operating smoothly even during high-traffic periods or system failures.
These examples underline how embracing edge computing can lead to greater operational resilience, enabling businesses to navigate challenges while maintaining high levels of service continuity.
Investing in edge computing can lead to substantial cost savings for businesses. By reducing latency, enhancing data security, and optimizing bandwidth usage, organizations can significantly lower their operational costs. Moreover, edge computing reduces the need for expensive cloud storage and processing capacity by enabling localized data management.
Additionally, the ability to make faster decisions can translate into better resource allocation, reduced waste, and improved customer satisfaction, all of which contribute positively to a company's bottom line.
While the initial investment in edge computing technologies may seem high, the long-term return on investment (ROI) is often justified by the ongoing savings and operational efficiencies achieved. Businesses can expect continued benefits as IoT technology evolves and becomes even more integrated into daily operations.
Ultimately, the strategic implementation of edge computing not only enhances operational efficiency but also drives long-term growth and profitability for businesses across various sectors.
Edge computing is revolutionizing how businesses leverage IoT technologies, providing significant advantages in terms of reduced latency, enhanced security, improved bandwidth efficiency, operational resilience, and cost savings. As organizations continue to navigate an increasingly digital landscape, investing in edge computing solutions will be crucial for maintaining a competitive edge and fostering innovation.
Embracing these advancements ensures businesses can harness the full potential of IoT, paving the way for improved service delivery, operational excellence, and sustained growth in the future.
What is edge computing?
Edge computing refers to a distributed computing model that brings processing and data storage closer to the location where it is needed, rather than relying solely on centralized cloud servers. This reduces latency and improves response times for IoT devices.
How does edge computing enhance data security?
By processing data locally, edge computing minimizes the transmission of sensitive information over networks, reducing exposure to cyber threats. Businesses can also implement localized security measures to further protect data.
What are some real-world applications of edge computing in IoT?
Applications include smart traffic management systems, industrial IoT for manufacturing, smart agriculture for optimizing irrigation, and energy management in utility sectors.
Can edge computing help reduce operational costs?
Yes, by improving efficiency, reducing latency, and optimizing bandwidth usage, edge computing can lead to lower operational costs and better ROI for businesses.
Why is operational resilience important for businesses?
Operational resilience ensures that businesses can continue functioning during disruptions, minimizing downtime and maintaining service levels, which is essential for customer satisfaction and financial stability.
Cloud technology keeps changing fast. Want to stay ahead? Know cloud computing trends in 2025. This guide breaks down the biggest trends shaping the future of cloud computing.
In this guide, you will gain insight into the cloud technologies that matter in 2025.
📈 Key trends and emerging cloud computing technologies driving the digital transformation in 2025.
💻 The essential role of cloud-based software development services in accelerating innovation and efficiency.
🌐 How cloud computing is reshaping business operations, enabling scalability, and fostering productivity.
Cloud adoption goes beyond keeping up — it helps businesses stay ahead. Companies that use the latest cloud innovations cut costs, strengthen security, and open new opportunities. AI-driven automation and sustainable cloud solutions are shaping the future right now.
This guide gives you a straightforward look at where cloud computing is going, with industry insights and real-world examples. Whether you lead a tech team, run a business, or plan IT strategy, you’ll find clear and practical ideas to stay ahead.
Artificial intelligence powers today’s most successful e-commerce businesses. From personalized shopping experiences to real-time inventory management, AI in e-commerce has become a cornerstone of competitive strategy. Yet, the true potential lies in its nuanced applications, from generative AI in e-commerce content creation to advanced customer behavior analytics.
In this article, we’ll explore how AI is used in e-commerce. We’ll provide real-world use cases and actionable insights. Additionally, we’ll answer the most pressing questions about its role in driving digital transformation.
At its core, AI in e-commerce refers to leveraging artificial intelligence and machine learning technologies. These tools optimize and automate processes, enhance user experience, and maximize revenue. Businesses are using them in innovative ways. They help manage massive datasets, predict customer needs, and make data-driven decisions faster than ever before.
But using AI in e-commerce is also about elevating the experience. Here's where it gets interesting.
Some businesses hesitate, asking: "Do we really need this level of innovation?" The short answer: Yes. The long-term ROI from using AI in e-commerce often outweighs the initial investment. Here’s why:
While the benefits of AI in e-commerce are undeniable, businesses must navigate several challenges to ensure successful implementation. Below are some of the key hurdles:
AI systems rely on vast amounts of high-quality data to function effectively. However, collecting, cleaning, and managing this data can be a daunting task for e-commerce businesses. Ensuring compliance with data privacy regulations like GDPR and CCPA adds another layer of complexity.
Handling sensitive customer data brings significant privacy and security risks. Robust measures are essential to protect against data breaches, which can lead to severe legal penalties and damage to a company’s reputation.
Many e-commerce platforms operate on outdated legacy systems. Integrating AI into these infrastructures can be complex and often requires costly upgrades or complete overhauls, posing a significant challenge for businesses.
The financial investment needed to implement AI technologies can be substantial, especially for smaller businesses. Costs include hiring skilled personnel, acquiring hardware, and developing or licensing AI models.
There is a global shortage of skilled professionals capable of designing, implementing, and managing AI systems. This talent gap can slow the adoption of advanced AI solutions, especially for companies without extensive resources.
While AI can enhance personalization, poor implementation can lead to a frustrating user experience. Overreliance on AI risks losing the human touch, which remains a critical component of customer service in many interactions.
As businesses grow, their AI systems need to scale alongside them. Adapting technological infrastructure and algorithms to handle increased data volumes and interactions can present significant challenges.
AI implementation brings ethical concerns, such as bias in algorithms and compliance with region-specific regulations. Failing to address these issues can erode customer trust and expose businesses to legal risks.
As AI adoption becomes more widespread in the e-commerce sector, the competition grows fiercer. Businesses must continuously innovate to maintain a competitive edge in a rapidly evolving market.
Measuring the return on investment (ROI) for AI initiatives can be difficult. The results often take time to materialize, making it challenging for businesses to justify the upfront costs involved.
The transformative power of AI in e-commerce is best understood through real-world applications. Leading brands across various industries have successfully integrated AI technologies to enhance customer experience, streamline operations, and drive growth. Here are some notable examples:
Amazon is a trailblazer in using AI in e-commerce to personalize shopping experiences. By analyzing customer browsing and purchase histories, it delivers tailored product recommendations that drive sales and engagement. Beyond personalization, Amazon employs AI in logistics to optimize inventory management and delivery processes, ensuring efficiency and reliability.
eBay leverages conversational AI in e-commerce through chatbots and virtual assistants to handle customer inquiries and manage order processing. These AI tools significantly improve response times and enhance the overall shopping experience, creating a seamless interaction between the platform and its users.
Alibaba has implemented AI applications in e-commerce to safeguard transactions. By analyzing vast amounts of transaction data, its algorithms detect suspicious patterns, reducing fraud risks and providing a secure environment for both customers and sellers.
Walmart utilizes AI and machine learning in e-commerce to enable dynamic pricing strategies. By analyzing market trends, competitor prices, and customer behaviors in real time, Walmart adjusts its prices to maximize profitability while maintaining competitiveness.
Zara employs AI in e-commerce to forecast demand and optimize inventory management. This approach minimizes stockouts and overstock situations, ensuring that the right products are available at the right time, improving operational efficiency.
Sephora has embraced AI applications in e-commerce with tools like Virtual Artist, which allows customers to virtually try on makeup products. Its Color IQ technology further personalizes the experience by matching products to customers' unique skin tones, boosting confidence in online purchases.
ASOS uses AI applications in e-commerce to introduce visual search functionality. Customers can upload images of clothing they like, and the system identifies similar products available on the platform. This feature enhances user engagement and simplifies the product discovery process.
SHEIN applies AI in e-commerce for personalized product recommendations. By analyzing user browsing behaviors, it tailors suggestions to individual preferences, improving engagement and boosting conversion rates.
Pinterest incorporates image recognition into its search capabilities, allowing users to find products based on uploaded photos. This innovative use of AI in e-commerce simplifies the shopping journey by connecting consumers with visually similar items.
While the benefits are clear, the implementation requires a strategic approach. Here’s how Opinov8 can help:
Are you ready to harness the transformative power of AI in e-commerce? Let Opinov8 guide you through every stage, from identifying AI use cases in e-commerce to creating practical solutions that drive results.
Code review is a cornerstone of maintaining project health, providing a structured way to ensure quality and identify potential issues in your codebase. But while reviews focus on spotting errors and improving standards, they work best when combined with another essential practice: refactoring. Refactoring — restructuring existing code without altering its functionality — is the unsung hero that keeps your projects on track. But what makes it so critical, and how can it transform your development processes? Let’s break it down.
Think of your codebase as a house. Over time, small fixes, quick solutions, and outdated practices add layers of technical debt, akin to clutter in a living space. Refactoring acts like a renovation: it clears the mess, strengthens the foundation, and makes room for future enhancements.
Without regular refactoring, even well-functioning systems become brittle, harder to scale, and increasingly prone to bugs. This isn't just a technical challenge; it’s a business risk. Poor project health leads to higher maintenance costs, slower time-to-market, and frustrated development teams.
Failing to refactor regularly compounds technical debt. Small inefficiencies add up, leading to:
In contrast, a commitment to consistent refactoring fosters a culture of quality and innovation, boosting team morale and long-term project viability.
Clear, concise code improves onboarding for new team members and reduces cognitive load for existing ones. A refactored codebase is easier to understand, modify, and expand.
A cleaner codebase encourages productive code reviews. Developers can focus on functionality and logic rather than untangling messy structures.
Refactoring eliminates bottlenecks. Developers spend less time debugging and more time innovating, reducing overall lead time.
Modern AI code review solutions rely on clean, well-structured code to deliver actionable insights. Refactored code ensures compatibility with advanced tools, leveraging AI for faster, smarter reviews.
Optimizing algorithms and removing redundant processes during refactoring can directly improve application speed and resource usage. This is especially critical for applications with high user loads or complex operations.
Refactoring helps align technical capabilities with business needs. By maintaining a flexible and robust codebase, teams can quickly adapt to market demands or integrate new features, ensuring competitive advantage.
Integrate code review best practices into your workflow. Use code review tools like SonarQube or GitHub's built-in review system to identify areas for improvement.
Not all code is created equal. Focus on critical sections that affect performance, user experience, or scalability. This targeted approach maximizes ROI on refactoring efforts.
Avoid trying to overhaul the entire codebase at once. Break it down into manageable chunks and tackle them during sprint cycles.
Incorporate tools that support refactoring and quality checks. Explore code review solutions that integrate seamlessly into your CI/CD pipelines. These tools can identify potential problems automatically, reducing manual effort.
Track key metrics like code complexity and dependency cycles. Prioritize refactoring for modules with the highest debt.
Make refactoring a regular part of your sprint planning. Treat it as a deliverable, ensuring that it receives the time and resources it deserves.
AI code review solutions can identify subtle issues in your codebase, offering suggestions for improvements that even experienced developers might miss. This is particularly useful for large teams or projects with extensive legacy code.
Legacy systems often present the biggest challenge. These systems may lack documentation, making it difficult to refactor without introducing errors. The solution? Start small, document changes meticulously, and use automated testing to validate updates.
One of the most common objections to refactoring is time. Teams often feel they can’t afford to refactor when deadlines loom. However, neglecting refactoring can lead to delays down the road. Treat refactoring as a time-saver, not a time-waster.
Stakeholders may question the value of investing in something that doesn’t immediately impact the end-user experience. Bridge the gap by explaining how refactoring reduces long-term costs, improves scalability, and accelerates feature delivery.
At Opinov8, we don’t just refactor; we elevate your entire development process. With decades of experience working with large technology companies, we know how to align technical improvements with your business goals.
Here’s how we can support your team:
Our proven approach combines cutting-edge tools and best practices to ensure your codebase is always a step ahead.
Artificial intelligence (AI) and machine learning (ML) are no longer just innovations but essential tools for growth and competitiveness. Opinov8, a digital and engineering solutions leader, is at the forefront of helping these industries adopt AI and ML in practical, impactful ways. This article explores how AI and ML are transforming manufacturing, construction, retail, energy, and finance — industries once considered "traditional" but now ready for a digital future.
First of all, AI and ML aren’t about replacing jobs. They focus on improving efficiency, enhancing customer experiences, and unlocking valuable insights that were previously inaccessible. With the right technology and strategies, we help businesses maximize these technologies' potential, unlocking new levels of productivity and profitability.
In healthcare, AI is revolutionizing diagnostics, enabling faster and more accurate identification of diseases. Machine learning algorithms analyze complex medical data, from imaging results to genetic information, making it possible to detect conditions like cancer or cardiovascular disease with unprecedented precision.
Hospitals using AI for diagnostic imaging can reduce false positives by up to 40%, improving patient outcomes and streamlining the treatment process. With personalized treatment plans, healthcare providers can tailor therapies to each patient’s unique genetic and lifestyle factors, creating a more patient-centered approach.
Beyond direct patient care, AI and ML are reshaping healthcare operations by optimizing resource allocation and workflow management. By analyzing historical data, machine learning models can predict patient flow patterns, ensuring that healthcare facilities are neither overstaffed nor under-resourced. This proactive approach improves patient care and significantly reduces operational costs, which is critical in today’s healthcare landscape.
Logistics is an industry that thrives on efficiency, and AI-driven route optimization is making this easier than ever. With machine learning models that analyze traffic patterns, weather data, and delivery timelines, logistics companies can optimize routes in real time, cutting down delivery times and fuel costs.
A logistics provider using AI-based route optimization could theoretically reduce delivery times by up to 20% and fuel costs by around 15%. With real-time tracking, transparency is enhanced as customers gain the ability to monitor their shipments live. This also empowers logistics teams to adjust routes on the fly, potentially reducing delays and improving overall customer satisfaction.
AI-powered demand forecasting helps logistics companies maintain optimal inventory levels and avoid stock shortages. By analyzing past sales data, seasonality, and external factors, machine learning models enable logistics providers to anticipate demand and manage stock levels effectively.
With AI-driven inventory management, logistics companies can better align their stock with customer demand, minimizing warehousing costs and reducing waste. This data-driven approach ensures that products are available when and where they’re needed, strengthening the entire supply chain and enhancing customer trust.
In manufacturing, AI and ML applications like predictive maintenance have revolutionized maintenance processes. Traditionally, manufacturers used preventive maintenance schedules to avoid breakdowns. However, this approach often leads to unnecessary checks and replacements.
Imagine a manufacturing company implementing an AI-driven predictive maintenance system that monitors equipment conditions in real time. This system could anticipate mechanical issues weeks in advance, minimizing unexpected downtime and potentially reducing repair costs by over 20%.
AI-based vision systems now allow manufacturers to automatically detect product defects and quality issues on the assembly line, supporting enhanced quality & risk services. This enables higher precision in real time.
Machine learning algorithms analyze images of products and can identify imperfections that are invisible to the human eye. By integrating these algorithms, manufacturers can ensure consistency and meet high-quality standards with less waste.
Construction projects are complex and prone to delays. AI’s project management capabilities can help predict risks, optimize scheduling, and improve decision-making.
Imagine a construction company implementing an AI-based project management solution that analyzes weather data, supply chain factors, and labor availability. By forecasting potential delays, this solution could help the company reduce project overruns by 15%, potentially saving millions in labor costs.
In construction, every project relies heavily on the efficient use of resources. Machine learning algorithms analyze historical project data to optimize material procurement and usage.
ML models help identify patterns in resource consumption. This allows project managers to forecast material needs more accurately and reduce waste. The result is both environmental and financial benefits.
AI in retail goes beyond basic customer segmentation. Through machine learning, retailers can now track customer behaviors, preferences, and buying patterns, offering personalized experiences that keep customers engaged.
Imagine a global fashion brand deploying AI algorithms that segment customers based on browsing and purchase data. This system could recommend products tailored to individual preferences and seasonal trends, potentially increasing conversion rates by 18% and boosting customer satisfaction.
Managing inventory in retail has traditionally involved guesswork, often leading to overstock or understock situations. AI can accurately forecast demand by analyzing various factors, including past sales data, social trends, and even weather patterns.
A major retail chain implements an ML-based predictive analytics solution to dynamically adjust inventory levels. This real-time approach helps the retailer reduce surplus stock by 25% while keeping shelves stocked with in-demand items.
Energy providers are increasingly adopting AI to better match supply with demand, ensuring that resources are utilized more efficiently. Accurate demand forecasting is essential for reducing waste and minimizing environmental impact.
In a recent project, a utility company deployed machine learning models to predict electricity usage based on variables like weather forecasts, historical demand data, and peak usage hours. This approach improved forecasting accuracy by 30%, enabling the company to optimize production and reduce energy waste.
Renewable energy sources like wind and solar are inherently variable. AI helps in optimizing their usage by predicting output based on factors like weather patterns, sunlight hours, and wind speeds.
Machine learning algorithms analyze these variables in real time, allowing energy companies to efficiently allocate resources and stabilize output.
AI has become indispensable in the financial sector for real-time fraud detection. Traditional methods relied on rule-based systems, which were less effective in recognizing novel fraud tactics.
From our experience, implementing a machine learning model to analyze transaction patterns, device locations, and user behavior can result in significantly improved fraud detection. This approach can reduce false positives by up to 40%, creating a safer and more reliable banking experience.
Financial institutions face increasingly complex regulatory standards, with compliance requiring constant oversight and detailed transaction monitoring. AI now plays a critical role in automating these compliance checks by swiftly processing vast amounts of transaction data to ensure alignment with evolving regulations. With an AI-powered risk assessment tool, financial institutions can proactively identify patterns that signal potential risks and compliance gaps, allowing teams to address issues before they escalate. This proactive approach not only reduces the frequency of regulatory breaches but also saves time and minimizes exposure to costly penalties, providing a reliable safeguard for institutions navigating stringent industry requirements.
Opinov8 is a global leader in digital and engineering solutions, offering deep expertise in AI and ML technologies. With our extensive industry knowledge, we help businesses in traditional sectors adopt AI and ML strategies tailored to their specific challenges and goals.
We understand that each industry has unique needs and that adopting AI requires a clear strategy and the right technology stack. Our proven track record in delivering customized solutions for clients globally shows our commitment to driving meaningful digital transformations.
Fill out our feedback form to connect with an Opinov8 expert for a personalized consultation.
Imagine this: your systems go down. Operations stall. Clients are left hanging. And the clock starts ticking — every minute costs you money, trust, and momentum.
In that moment, the question is simple: how fast can you bounce back?
Enter Disaster Recovery as a Service (DRaaS) — the enterprise-ready answer to unplanned downtime. It’s not just about backing up your data. It’s about making sure your entire IT environment is ready to recover at speed.
Disaster Recovery as a Service (DRaaS) is a cloud-based solution that replicates your entire IT infrastructure — not just your data — and keeps it ready to launch in the event of a failure. Unlike traditional backup systems that just store information, DRaaS solutions offer instant failover, enabling you to switch to a live replica of your systems within minutes.
That means zero scrambling, zero delays, and business continuity by design.
| Feature | Traditional Cloud Backup | Disaster Recovery as a Service |
|---|---|---|
| Focus | Data storage | Full system recovery |
| Speed | Slow (manual restore) | Instant (automated failover) |
| Automation | Minimal | High (failover/failback) |
| Business Continuity | Not guaranteed | Designed for it |
DRaaS isn’t a luxury anymore. It’s a core layer of resilience in modern IT strategy. Here’s how it delivers in real-world scenarios:
When evaluating a DRaaS partner, look beyond the tech stack. Consider:
More remote teams. More cyberattacks. More systems in the cloud. Today’s IT environments are more fragile — and more critical — than ever. That’s why DRaaS adoption is accelerating across industries. It’s a proactive defense, a continuity plan, and an operational advantage rolled into one.
Start by reviewing your current backup and recovery setup. Are you relying on storage alone? Are your RTOs realistic?
At Opinov8, we help enterprises and service centers modernize their disaster recovery strategy — from assessment to implementation. Let’s make sure your business keeps moving, no matter what.
Downtime is expensive — but so is the time your team spends manually managing outdated recovery plans. DRaaS not only reduces the risk of disruption but also frees up your internal IT team to focus on innovation instead of maintenance. By automating disaster recovery and removing infrastructure overhead, enterprises gain predictable performance, simplified compliance, and measurable cost savings. It’s not just an insurance policy — it’s a strategic investment in agility and uptime.
Traditional backup stores data for recovery but doesn’t guarantee fast system restoration. DRaaS replicates your entire infrastructure, allowing near-instant failover to keep operations running with minimal disruption.
Not at all. While enterprises often benefit most, mid-sized companies and service centers also use DRaaS to protect critical systems and meet compliance requirements.
Top providers offer RTOs and RPOs measured in minutes — much faster than traditional recovery methods, which may take hours or days.
Yes. Leading DRaaS solutions are cloud-agnostic and support complex infrastructures across AWS, Azure, Google Cloud, and private clouds.
Regular testing is a key feature of DRaaS. Providers typically offer automated and scheduled failover tests to ensure your recovery plan works when it’s needed most.
Yes. DRaaS providers follow strict compliance standards such as GDPR, HIPAA, ISO/IEC 27001, and others, depending on your industry and location.
Look for providers with clearly defined SLAs, global data center reach, automated testing, multi-cloud support, and a track record in your industry.
Third-party dependencies in web development have become essential components that facilitate rapid innovation and functionality enhancement. These dependencies — libraries, frameworks, and services — allow developers to leverage existing solutions rather than reinventing the wheel. However, while they offer numerous advantages, they also pose significant challenges that need to be effectively managed. This article seeks to explore the intricate landscape of third-party dependencies in web development, identifying their benefits, risks, and best practices for effective management.
Third-party dependencies in web development refer to external libraries, frameworks, or services that developers utilize in their projects to perform specific tasks or functions. Common examples include JavaScript libraries like React or jQuery, CSS frameworks such as Bootstrap, and API services like Stripe for payment processing. These tools save time and effort, allowing developers to focus on building unique features rather than underlying functionalities.
The integration of third-party dependencies in web development can significantly impact development processes. On one hand, they can accelerate project timelines, increasing agility and responsiveness to market demands. On the other hand, reliance on external code introduces complexities related to version control, compatibility, and long-term maintainability. Understanding both sides is crucial for making informed decisions about their use.
One of the foremost advantages of utilizing third-party dependencies is the speed at which developers can innovate. By incorporating pre-built solutions, teams can reduce development time, enabling them to bring products to market faster. This agility can be particularly beneficial in a competitive landscape where the ability to rapidly adapt can determine success.
Third-party dependencies in web development often come with robust functionalities that can enhance the overall performance of an application. By leveraging established tools, developers can integrate features such as user authentication, data visualization, and responsive design without delving into the complexities of building these functions from scratch. This enhancement not only elevates user experience but also allows for a more sophisticated product offering.
Integrating third-party solutions can also lead to significant cost savings. Rather than allocating resources to develop every aspect of an application, companies can invest in existing libraries or services, reducing both time and labor costs. In many cases, the long-term maintenance and support for these dependencies are also less expensive compared to building and maintaining custom solutions.
| Criteria | Third-Party Dependencies | Custom Development |
|---|---|---|
| Speed of Implementation | Fast | Slower |
| Cost | Lower upfront | Higher upfront |
| Control & Flexibility | Limited | Full control |
| Maintenance | Outsourced to library maintainers | Your team is responsible |
| Security Risk | Depends on third party | More controllable |
Despite their benefits, third-party dependencies often introduce security vulnerabilities. Since these external libraries can be written by anyone and may not undergo rigorous scrutiny, malicious code can easily find its way into applications. This risk necessitates regular security audits and careful selection of dependencies to mitigate potential threats.
Compatibility is another significant challenge that arises from the use of third-party dependencies. As libraries evolve, they may introduce breaking changes that can disrupt an application. Developers must stay vigilant by monitoring updates and ensuring that their codebase remains compatible with the latest versions of the dependencies they use.
Managing dependencies can become a complex task, particularly in larger projects with numerous third-party libraries. Issues such as dependency hell, where multiple libraries depend on different versions of the same package, can lead to conflicts and increased maintenance overhead. Effective dependency management strategies are therefore crucial for maintaining a healthy codebase.
Before integrating any third-party dependency in web development, conducting thorough research is vital. This includes evaluating the library's popularity, community support, maintenance status, and security history. A well-supported library with a robust community is often less risky than a niche alternative with little backing.
Regular updates to dependencies are essential for maintaining security and functionality. Developers should establish a routine for reviewing and updating libraries, ensuring that they benefit from the latest features and security patches. Automated tools can assist in monitoring updates, making this process more efficient.
Employing dependency management tools such as npm for JavaScript or Composer for PHP can simplify the process of managing libraries. These tools help in tracking versions, resolving conflicts, and ensuring that all dependencies are correctly installed and up-to-date. They also facilitate the process of rolling back to prior versions if necessary.
Clear communication among team members regarding the use of third-party dependencies is essential. Teams should document why specific libraries are chosen, their intended use cases, and any potential risks. This transparency ensures all members are on the same page and can contribute to decisions regarding dependency management.
Conducting regular security audits is necessary to identify and resolve vulnerabilities. Tools like Snyk or npm audit can help automate this process, scanning for known vulnerabilities in dependencies. Establishing a culture of security within the development team can further enhance the integrity of the application.
For service centers that handle multiple projects, streamlining processes around dependency management is crucial. Standardizing the selection and integration of third-party libraries can reduce inconsistencies and improve efficiency. This uniform approach can also facilitate training and onboarding of new developers.
When outsourcing development tasks, it is vital to maintain clear guidelines regarding the use of third-party dependencies. Establishing a framework that outlines acceptable libraries and ensures compliance with security and performance standards can mitigate risks associated with outsourcing. Regular check-ins and code reviews can also enhance collaboration and alignment.
Implementing monitoring and reporting mechanisms can provide insights into the health of third-party dependencies in use. Analytics tools can track performance metrics, detect anomalies, and report on the overall status of dependencies. This proactive approach allows teams to respond quickly to any issues that arise.
Adopting a modular design approach can significantly mitigate the risks associated with third-party dependencies in web development. By creating self-contained modules that can be independently managed and updated, developers can isolate changes and reduce the impact of dependency updates on the entire system. This strategy enhances maintainability and adaptability in the long run.
Keeping abreast of industry trends and emerging technologies can help developers make informed decisions about third-party libraries. Attending conferences, participating in forums, and following relevant publications can provide valuable insights into which dependencies are likely to remain relevant and secure in the future.
Continually investing in training and development for team members ensures that they remain knowledgeable about best practices in dependency management. Workshops, online courses, and internal training sessions can equip developers with the tools they need to effectively navigate the complexities of third-party dependencies and make strategic choices.
In summary, managing third-party dependencies in web development requires a careful balance of leveraging their benefits while mitigating associated risks. Implementing best practices such as thorough research, regular updates, the use of dependency management tools, and security audits can lead to more robust and secure applications. Additionally, maintaining clear communication and adopting a modular design approach will further enhance the sustainability of projects.
The integration of third-party dependencies is a double-edged sword. While they provide avenues for accelerated development and enhanced functionality, they also introduce potential vulnerabilities and compatibility challenges. By adhering to best practices and fostering a culture of security and collaboration, developers can navigate this landscape successfully and future-proof their projects against the evolving demands of technology.
Third-party dependencies are external libraries, frameworks, or services integrated into a project to provide specific functionalities or features. They can streamline development efforts and enhance application capabilities.
The primary risks include security vulnerabilities, compatibility issues, and challenges in dependency management. These risks can impact the stability and security of an application.
To ensure security, regularly update dependencies, conduct security audits, and choose well-maintained libraries with good community support. Utilizing automated tools can further aid in monitoring vulnerabilities.
Some popular tools include npm for JavaScript, Composer for PHP, and Bundler for Ruby. These tools assist in tracking versions and managing library installations.
Embracing modular design, staying informed on industry trends, and investing in ongoing training for your team can help future-proof your projects against risks associated with third-party dependencies.
In today’s interconnected world, web applications are the backbone of many businesses. But with great digital presence comes great responsibility. Is your web application really secure? If you’ve never conducted a comprehensive web application security assessment, your app could be vulnerable to attacks that you’re not even aware of. Here’s why this process is crucial and how it helps protect your business from costly breaches.
A web application security assessment involves a deep dive into the security measures of your web applications. It uncovers vulnerabilities that hackers could exploit, helping you mitigate risks before they become full-blown attacks. Unlike traditional security testing, this assessment is tailored to web apps, focusing on their unique risks and weaknesses. From application security testing to security risk analysis, this process leaves no stone unturned.
With cyberattacks on the rise, application security is no longer optional. Hackers continuously evolve, making security testing a critical element of any business strategy. But why is application security testing so important?
For one, web applications handle sensitive data—whether it's user credentials, financial information, or corporate secrets. Without proper security, you risk exposing this information to malicious actors. Worse yet, a breach can not only result in financial loss but also irreparable damage to your brand’s reputation.
Many companies assume their apps are secure because they haven’t been breached yet. Unfortunately, this is a dangerous misconception. The absence of visible attacks doesn’t mean vulnerabilities aren’t present. Here’s where security testing in software testing and vulnerability management tools come into play. These tools scan your app for weaknesses, including:
Conducting regular vulnerability management solutions is the only way to stay ahead of threats. These systems continuously monitor and assess your web application’s defenses, giving you the peace of mind that your data is secure.
A thorough security risk assessment will cover the following critical areas:
One of the most effective defenses against cyber threats is a robust vulnerability management platform. These platforms provide continuous oversight of your app’s security, ensuring that risks are detected early. They integrate with network vulnerability management tools and endpoint vulnerability management systems to provide a holistic view of your security landscape.
The best part? These platforms are scalable, so whether you’re a small business or a large corporation, you can benefit from a vulnerability management solution tailored to your needs.
AppSec (short for application security) goes beyond simply securing your code. It involves the application security management of all processes related to app development and deployment. A strong application security program includes:
Your application security providers should be well-versed in both application data security and cybersecurity testing, ensuring that every aspect of your web app is fortified against attacks.
If you’re new to web application security testing, the process might seem overwhelming. However, with the right approach, you can ensure your application is secure without disrupting operations. Here’s a quick overview of how to get started:
Web application security isn’t something you can afford to overlook. A comprehensive web app security assessment is your best defense against the unknown risks lurking in your systems. At Opinov8, we specialize in providing cutting-edge application security solutions to help businesses safeguard their most valuable assets.
Ready to secure your web applications? Fill out our feedback form today and get a free consultation on how to protect your web apps from the latest cyber threats. Our experts will guide you through the assessment process and ensure your business is ready to face whatever comes next.
Application security involves a set of practices, tools, and processes that safeguard applications against threats during their entire lifecycle. Whether you're dealing with web or mobile apps, application security is critical to ensuring data integrity and privacy.
An IT security assessment evaluates the security posture of an organization’s IT infrastructure, including its applications and networks. It helps identify weaknesses that could be exploited by cyber attackers and provides a roadmap for strengthening defenses.
A vulnerability manager is a tool or software solution that helps identify, classify, and manage vulnerabilities across an organization’s applications and systems. It is an essential part of any robust vulnerability management system.
A security risk assessment analyzes the potential risks and vulnerabilities within your web application and broader IT infrastructure. The assessment allows businesses to prioritize critical issues and implement measures to reduce the risk of cyberattacks. Regular information security risk assessments ensure your defenses remain up to date.
Testing the security of a website involves conducting web security testing through methods like penetration testing and vulnerability scans. You can also use web app security testing tools to detect specific weaknesses such as SQL injections or cross-site scripting vulnerabilities.
Security testing in software testing refers to evaluating the security features of an application to ensure that data remains protected from external threats. This process includes testing for vulnerabilities that could compromise the app’s security.
Application level security focuses on securing applications at the code level, ensuring that every layer of the application, from the user interface to backend databases, is protected against attacks. Implementing application security management is crucial for securing web apps.
Application security vendors are companies that provide solutions, tools, and services to help secure web and mobile applications. These vendors offer services like application security programs and security testing software to help protect your systems.
Vulnerability management tools scan applications and systems to detect security weaknesses, allowing businesses to address vulnerabilities before they can be exploited. These tools are a core component of any effective vulnerability management solution.
A network security risk assessment evaluates potential vulnerabilities in a company’s network infrastructure. This includes both internal and external networks, ensuring that sensitive data is safeguarded against unauthorized access.
There are several types of application security testing, including penetration testing, vulnerability scanning, and dynamic application security testing (DAST). Each method serves to identify different kinds of vulnerabilities, helping to fortify your app’s defenses.
Vulnerability remediation tools help businesses resolve vulnerabilities by providing detailed instructions or automated fixes for identified weaknesses. This ensures that vulnerabilities are properly addressed before attackers can exploit them.
A security assessment is an in-depth analysis of an organization’s overall security posture. It covers areas such as application security, network security, and data protection to ensure that all vulnerabilities are identified and addressed.
To perform a security risk assessment, start by identifying potential threats, evaluating the likelihood of these threats, and determining the potential impact on your business. The first step is to conduct an IT security risk assessment to evaluate existing vulnerabilities and security gaps.
A security risk assessment methodology is a structured approach for identifying, assessing, and managing risks within an organization’s IT and web application infrastructure. This methodology helps ensure that vulnerabilities are addressed in a systematic manner.
Vulnerability management solutions companies offer specialized services that help businesses identify, manage, and remediate security vulnerabilities. These companies typically provide vulnerability management platforms and other tools to ensure comprehensive security coverage.
To test web server security, use web server security test tools to evaluate vulnerabilities like open ports, insecure protocols, and misconfigurations. These tools will help identify potential entry points for hackers.
The best vulnerability management software is one that integrates seamlessly with your existing systems, provides real-time updates on vulnerabilities, and includes tools for automated remediation. Look for platforms that offer comprehensive coverage, from vulnerability tracking to remediation.
Effective cloud cost management goes beyond reducing expenses. It provides enterprises with greater control, visibility, and the ability to make informed decisions, leading to:
Understanding how your cloud resources are utilized is the foundation of cost management. Enterprises should regularly review usage patterns to pinpoint peak demand periods and underutilized resources. By identifying these trends, organizations can make data-driven decisions that enhance efficiency.
One of the most effective ways to reduce unnecessary cloud expenditures is by leveraging autoscaling. This feature dynamically adjusts resources based on real-time demand, ensuring that you only pay for the resources you actually use. It eliminates the need to maintain fixed resources during periods of low demand.
Rightsizing involves continuously reviewing and adjusting your resource allocations to match actual demand. Many enterprises over-provision resources, leading to inflated costs. By rightsizing, businesses ensure that they only pay for what they need, similar to adjusting operational capacity based on current workloads.
Advanced cloud cost management tools provide a detailed overview of your cloud spending, forecast future costs, and offer actionable recommendations for optimization. These tools are essential for enterprises managing multi-cloud environments and offer insights into how to allocate resources more effectively.
Enterprises must carefully evaluate the pricing models offered by cloud providers. On-demand pricing offers flexibility, but reserved or spot instances can provide significant cost savings when planned effectively. Choosing the right model ensures that the organization’s needs are met without overspending.
Data transfer between cloud services can lead to substantial costs if not closely monitored. Techniques such as data compression and caching can reduce the volume of data being transferred, minimizing these expenses.
Not all cloud resources need to be running 24/7. By scheduling fixed uptime and downtime periods, enterprises can ensure they are only billed for resources during active operational hours. This strategy helps reduce unnecessary costs without impacting performance.
Many enterprises benefit from adopting a multi-cloud strategy, leveraging different providers to optimize pricing and service offerings. However, this approach also introduces complexity. Organizations should ensure they have the right tools and processes in place before expanding into multi-cloud environments.
While optimizing cloud costs, enterprises often encounter a few common challenges:
We recommend the following cloud cost management tools for enterprises looking to enhance cost visibility and efficiency:
For enterprises, cloud cost management is essential to maintaining operational efficiency and controlling costs in a rapidly evolving digital landscape. By adopting these strategies, businesses can ensure they are optimizing cloud usage while avoiding unnecessary expenditures.
This topic was originally covered on Moqod's blog.
Cyberattacks occur 2,220 times every day, or about once every 39 seconds. In 2023 more than 3,200 data breaches impacted over 350 million people globally. The larger the corporations, the higher the stakes. Secure code writing is critical to maintaining operational integrity and protecting sensitive data.
Secure code is designed to prevent exploitation by cybercriminals. It safeguards applications against vulnerabilities and is critical at every stage of development. Implementing secure coding practices and staff training can significantly reduce your company's exposure to risk.
Here’s how you can elevate your secure coding practices to protect your business and its reputation.
Before writing any code, conduct a comprehensive threat model. For large systems, this involves mapping out every interaction within your architecture and identifying potential vulnerabilities. Focus on critical areas, such as data entry points, APIs, and login systems.
Ensure your team is aware of common threats like SQL injection and cross-site scripting (XSS). These attacks, often targeting input fields or exposed APIs, can have devastating consequences if left unchecked.
Security cannot be an afterthought. By integrating security checks into your development cycle from the very start — what’s known as shift-left security — you’ll catch issues before they become bigger problems. Utilize automated vulnerability scanners and static code analysis tools after each code commit to ensure security is baked into your process.
Implement role-based access control (RBAC) and the principle of least privilege. Ensure that each user or system has access only to the data and tools they need. This limits the potential damage in case of a breach and minimizes the avenues for an attacker to exploit.
Enterprises often deal with massive amounts of user input, from forms to APIs. Input validation ensures that data entered into your system is screened and sanitized before being processed. By enforcing strict validation, you reduce the likelihood of malicious data causing a breach.
Data encryption is critical for any sensitive information, whether it's customer passwords, financial transactions, or intellectual property. Ensure data is encrypted both at rest and in transit using robust encryption standards such as AES-256 and TLS 1.3. This ensures that even if attackers gain access to your data, they can’t exploit it without the encryption keys.
Large corporations should adopt a continuous testing strategy that includes both static and dynamic code analysis. Static analysis reviews your code for potential flaws before deployment, while dynamic analysis simulates real-world attacks in runtime environments. Combining these with penetration testing (ethical hacking) helps identify and resolve weak points before they become critical.
In large enterprises, speed and scale often collide with security. By integrating security tools into your CI/CD pipeline, you ensure that each code change undergoes automated security testing. This guarantees that vulnerabilities are identified and addressed quickly, even in rapid deployment environments.
With complex systems come dependencies. Third-party libraries and open-source components often become targets for attackers due to outdated code. Implement a rigorous patching and update schedule to ensure you’re not vulnerable through external software. Automate dependency management tools to keep track of and update libraries without manual intervention.
No security strategy is complete without regular training. Your developers and technical staff must stay current on emerging threats and best practices. Regular training sessions ensure your team knows how to spot vulnerabilities and avoid common coding mistakes that can lead to breaches.
Once your system is live, implement robust logging and monitoring solutions. However, be cautious: logs can expose sensitive information if not handled properly. Regularly review logs for anomalies and suspicious behavior. Advanced enterprises should invest in automated threat detection systems that use machine learning to identify patterns of malicious activity.
At Opinov8, we understand the complexities of secure code development for enterprise-level systems. From comprehensive threat modeling to advanced automated security testing, our team ensures your code stays secure from inception to deployment. Let us handle the complexities of security so you can focus on innovation and business growth.
Secure code writing is the practice of developing software with security in mind from the start. It involves techniques that help prevent vulnerabilities like injection attacks, data leaks, and unauthorized access.
Enterprises handle vast amounts of sensitive data. Secure code writing reduces the risk of data breaches, ensures compliance with regulations, and protects brand reputation.
Key principles include input validation, least privilege access, encryption, regular testing, and continuous monitoring. These help eliminate common attack vectors in enterprise systems.
Popular tools include static code analyzers (e.g., SonarQube), dependency scanners (e.g., OWASP Dependency-Check), and CI/CD security integrations like GitHub Actions or GitLab Secure.
Yes. Outdated or vulnerable dependencies are a common attack vector. Use automated tools to monitor and update libraries regularly.
Web and app accessibility has emerged as a critical concern for investors, developers, and policymakers alike. It is about creating technology that everyone can use, including people with disabilities: visual, hearing, and cognitive impairments.
Accessibility goes beyond legal requirements. With the global trend toward accessible and inclusive products, customers are naturally choosing compliant businesses over those that aren't. In the near future, this shift will drive companies to adopt accessibility from the ground up. We can help you to prepare for this change.
While we at Opinov8 are committed to helping businesses stay ahead in this evolving landscape, understanding the key regulations and best practices around accessibility is essential for all. This article breaks down the rules, risks of non-compliance, and what investors should look for when navigating web and app accessibility.
The Americans with Disabilities Act (ADA) has set a precedent for accessibility standards in the United States. The ADA was enacted in 1990 to prohibit discrimination against individuals with disabilities. It covers all areas of public life, including jobs, schools, transportation, and both public and private places open to the general public. Although the ADA does not explicitly mention web accessibility, various court rulings have interpreted it to include websites and mobile applications as places of public accommodation. This has led to increased scrutiny and legal action against companies whose digital platforms do not meet accessibility standards.
The implications of the ADA are significant for investors as companies face legal challenges that can result in hefty fines and operational changes. Recognizing the importance of ADA compliance can guide investment decisions. Firms that prioritize accessibility may reduce risks related to lawsuits and improve their reputation with consumers.
Section 508 of the Rehabilitation Act mandates that federal agencies ensure their electronic and information technology is accessible to people with disabilities. This section requires that any software, websites, or applications developed or procured by the federal government comply with established accessibility standards. The guidelines outlined in Section 508 have become a benchmark for organizations striving for inclusivity in their digital offerings.
Investors should pay attention to Section 508 when evaluating companies that have federal contracts. Compliance can signal a company’s commitment to accessibility and could be a competitive advantage.
The Web Content Accessibility Guidelines (WCAG) are recognized as the primary international standard for web accessibility. Developed by the World Wide Web Consortium (W3C) in 1999, these guidelines have been continuously updated to reflect advancements in digital technology and accessibility needs. WCAG is not a law, but it is widely adopted across various jurisdictions as the benchmark for ensuring web and mobile applications are accessible to individuals with disabilities. Many countries, including those in the European Union, the United States, Canada, and others, reference WCAG in their national accessibility laws and policies.
WCAG outlines four core principles: content must be perceivable, operable, understandable, and robust (often referred to as POUR), which form the foundation for accessible web development. These principles ensure that websites and applications can be used by people with a range of disabilities, including visual, auditory, physical, and cognitive impairments.
Meeting WCAG standards is essential to improve user experience. Accessible websites also tend to have better SEO and customer engagement, which is good for business.
In addition to the ADA and Section 508, various states and local governments have enacted their own accessibility laws, which can further complicate compliance. For instance, the California Unruh Civil Rights Act and the New York City Administrative Code both address digital accessibility. These regulations can impose additional obligations on businesses, increasing the complexity of navigating legal requirements.
Navigating these laws can be complex, but businesses that stay ahead of the curve can reduce risks and expand their audience.
As accessibility regulations evolve worldwide, businesses face both challenges and opportunities. Different regions, including Europe, Canada, and the Asia-Pacific, are implementing their own accessibility laws, creating a global landscape that requires attention. Beyond legal compliance, companies that embrace accessibility can tap into new markets and gain a competitive edge by meeting the needs of millions of users with disabilities. This section explores key international standards and the potential for growth in accessible digital products and services.
The European Accessibility Act aims to improve the accessibility of products and services across the European Union. Enacted in 2019, this legislation mandates that certain products and services, including websites and mobile apps, meet accessibility requirements. It serves not only to protect the rights of individuals with disabilities but also to create a level playing field for businesses operating within the EU.
The Act signifies a growing market for accessible technology. Companies that invest in compliance and innovation in this area can tap into a wider audience, including the over 80 million people with disabilities in Europe, thus presenting a lucrative opportunity for growth.
Canada has made significant strides in promoting digital accessibility through the Accessible Canada Act, which aims to create a barrier-free Canada by 2040. This legislation provides a framework for improving accessibility across various sectors, including information and communications technology. A key aspect of the act is its emphasis on proactive compliance measures, encouraging businesses to address accessibility issues before they lead to complaints or legal challenges.
Understanding Canadian accessibility laws is essential, especially for companies operating in this region. While accessibility is a critical factor, it should be considered alongside other key investment criteria, such as business plans, ROI potential, and market positioning. Prioritizing accessibility can enhance a company’s reputation and expand its customer base, but it must align with broader business strategies to ensure a balanced, holistic investment decision.
Across the Asia-Pacific region, countries like Australia and Japan are also working toward enhancing digital accessibility. The Australian Government has adopted the National Disability Strategy, which includes commitments to accessibility in digital services. In Japan, the Act on the Elimination of Discrimination against Persons with Disabilities emphasizes the importance of accessible technology in improving the quality of life for individuals with disabilities.
Across the Asia-Pacific region, countries like Australia and Japan are taking significant steps to enhance digital accessibility. The Australian Government has adopted the National Disability Strategy, which outlines various commitments, including improving accessibility in digital services. Similarly, Japan’s Act on the Elimination of Discrimination against Persons with Disabilities places a strong emphasis on accessible technology, recognizing its vital role in improving the quality of life for individuals with disabilities.
In these regions, businesses that view accessibility as part of their core strategy — not just a legal requirement — are positioned for growth. Investors can find opportunities in companies that lead the way in accessibility innovation.
The financial implications of failing to comply with accessibility regulations can be severe, particularly in regions where penalties are enforced. Non-compliance can lead to significant fines, legal fees, and remediation costs, potentially straining a company's financial resources. For example, settlements from ADA lawsuits in the U.S. can range from thousands to millions of dollars, depending on the severity of the violation and the size of the company. However, it’s important to note that in some regions, such as the European Union, governmental bodies often prioritize providing businesses with guidance over issuing fines, focusing on improving accessibility rather than immediate punishment.
In certain sectors, such as airlines, companies that fail to comply with accessibility standards may also lose revenue due to legal actions and customer dissatisfaction. However, accessibility is not just about avoiding penalties. Implementing best practices can offer strategic advantages online, such as improving SEO rankings. Well-organized, accessible content enhances a website’s usability, which search engines reward, leading to better visibility and potentially driving more traffic.
While the risk of financial penalties is a factor to consider, it’s equally important to recognize that companies that prioritize accessibility can benefit from long-term operational gains, better customer engagement, and enhanced market positioning.
Non-compliance can lead to lawsuits from private individuals or advocacy groups, disrupting business operations and damaging a company’s reputation. Legal battles can drain financial resources and scare off potential investors or partners.
It’s also about brand trust. Customers are more likely to choose companies that show a commitment to inclusivity. Negative publicity resulting from accessibility failures can lead to a decline in customer trust and loyalty, ultimately affecting sales and market share.
In the near future, this shift in consumer preferences is expected to drive significant change across industries. To stay ahead of the curve, we encourage businesses to take proactive steps — schedule your accessibility audit and ensure compliance.
As an investor, assessing a company's accessibility policies is critical before making investment decisions. Companies should have clear, documented procedures for maintaining compliance with accessibility standards. This includes regular audits of their digital platforms and ongoing training for staff to ensure they understand best practices for accessibility.
Before investing in a company, check if they have all these documents and regulations. Also, ask them how they collect feedback from users with disabilities. Answers to these questions can provide insights into the company’s commitment to accessibility and its long-term potential.
Another avenue for investors is to seek out technologies and startups that focus on improving accessibility. This growing sector encompasses a variety of innovations, from assistive devices to AI-driven accessibility solutions. Companies that prioritize accessibility in their products and services are poised to capture a significant share of a market that includes millions of potential users.
Investing in accessible technologies positions investors for financial returns and aligns with ethical and social responsibility goals. Companies that lead in this area often experience increased brand loyalty and customer satisfaction, further enhancing their market position.
Companies that embrace inclusive design consider the needs of all users from the start. Investing in firms that embrace inclusive design methodologies can also lead to a more sustainable business model. These companies are less likely to face legal challenges and are better positioned to adapt to changing regulations and consumer expectations.
Web and app accessibility isn’t just a legal requirement; it’s a business opportunity. Investors who prioritize companies with strong accessibility practices are setting themselves up for long-term growth. Understanding key regulations like the ADA, Section 508, and WCAG helps minimize risks, while investing in accessible technologies can lead to innovation and a broader customer base.
If you’re an investor looking to support inclusive, forward-thinking companies, accessibility should be a top priority.
1. What is web accessibility?
Web accessibility is the practice of making websites and applications usable for people with disabilities, ensuring that all individuals can access and interact with digital content without barriers.
2. Why is accessibility important for businesses?
Accessibility is crucial for businesses as it fosters inclusivity, expands potential customer bases, complies with legal standards, and enhances brand reputation.
3. What are the consequences of not being accessible?
Consequences can include financial penalties, legal actions, and damage to brand reputation, ultimately affecting a company's profitability and market position.
4. How can investors evaluate a company's accessibility?
Investors can evaluate a company's accessibility by reviewing their policies, asking about compliance measures, and assessing the user experience of their digital platforms.
5. What role does inclusive design play in accessibility?
Inclusive design ensures that products and services are developed with diverse user needs in mind. It enhances usability for all individuals, thereby expanding market reach and fostering customer loyalty.
In today's dynamic landscape, remote work has emerged as a transformative force, reshaping how businesses operate and collaborate, reflecting diverse strategies across the IT industry. At Opinov8, we recognize the profound impact of distant work in breaking down geographical barriers, enabling us to tap into a global pool of talent and deliver exceptional results to clients worldwide. Let's explore how working remotely fosters talent acquisition, supports client needs, promotes diversity and inclusion, and harnesses insights from our team members.
Remote work empowers companies to recruit the best experts regardless of location. This is particularly beneficial for IT companies, where the demand for specialized knowledge often outstrips local supply.
At Opinov8, this approach allows us to identify individuals with specific skills and exact experiences that align with the project requirements, ensuring that we have the right expert for a particular task. By casting a wider net, we can assemble diverse teams with varied perspectives and backgrounds.
Embracing remote work benefits internal operations and also enhances the ability to serve clients around the world. With a global team distributed across different time zones, you can provide around-the-clock support and agile response to client needs. This flexibility ensures seamless collaboration and timely project delivery.
Opinov8's remote work model enables us to tap into a global network of experts and deliver effective digital and engineering services. By leveraging our international team's strengths, we offer solutions that adapt to the evolving digital market and unique client challenges.
Distant work promotes diversity and inclusion by providing equal opportunities for individuals from diverse backgrounds and points of view. Here, at Opinov8, we celebrate the unique perspectives and contributions of our global workforce. By fostering an inclusive environment where every voice is valued, we cultivate creativity, empathy, and mutual respect, enabling us to deliver innovative solutions that resonate with clients and end-users alike.
One significant advantage of distant work is the ability to embrace diverse cultures and backgrounds within a company. At Opinov8, we take pride in our global workforce, collaborating with experts worldwide, including teammates from Colombia, Egypt, Ukraine, the UK, and the USA. This international collaboration brings unique viewpoints and diverse skill sets to our projects, enhancing our ability to innovate and solve complex problems.
Working remotely is adopted in various countries and cultures, each with a unique experience. In Colombia, it connects professionals to the global IT market. In Egypt, it provides flexibility for balancing professional responsibilities with family commitments. Ukrainian team members have shown remarkable resilience and dedication working under challenging circumstances. At the same time, those in the USA and the UK appreciate the flexibility and improved work-life balance remote work offers. We also have teammates from various other regions and locations, enriching our team with a wide range of perspectives.
Our teammates enjoy integrating their cultural practices and personal preferences into their daily routines. This cultural richness enhances individual performance and fosters a more inclusive and collaborative work environment.
To provide a well-rounded perspective, we gathered insights from our Opinov8 team members about the advantages of working remotely:
The Talent Acquisition (TA) team notes: "Offering remote IT jobs has significantly expanded our talent pool, allowing us to attract professionals worldwide with unique skill sets. This strategy enriches our team with various expertise and ensures that we can deliver the best solutions to our clients no matter where they are based."
The Human Resource (HR) team observes: "As a remote-first organization, we hire and collaborate with talents all over the world. Having this in mind, we always strive to maximize our knowledge and communication. Our strategy focuses on building geographically balanced teams driven by innovative solutions, advanced technologies, and quality engineering delivered worldwide."
Our Project Management (PM) team highlights: "Remote work has transformed our approach to project delivery, enhancing efficiency through cross-cultural and cross-time zones collaboration. Diverse backgrounds and experiences have driven more creative solutions and innovative project outcomes, significantly improving our team's results."
The Learning & Development (L&D) team shares: "Remote work has enhanced our diversity and inclusion efforts. Leveraging a global network, we've implemented mentorship programs that bridge cultural gaps and foster hard and soft skill development. This enriches our team with diverse perspectives and ensures continuous personal and professional growth for all members."
As we navigate the evolving landscape of remote work, Opinov8 is committed to harnessing its potential to drive growth, success, and excellence. Leveraging a global talent pool allows us to deliver exceptional services, address diverse challenges, and stay competitive in the digital market. By fostering diversity and inclusion, we enrich our teams with varied perspectives, leading to creative and effective outcomes.
Picture your company as a stronghold, guarding invaluable assets. Consider a vigilant team, committed to securing each access point and maintaining an impenetrable defense. This comparison reflects how InfoSec (Information Security) companies reinforce businesses against digital threats.
What exactly are InfoSec companies? They are specialized entities equipped with an arsenal of tools and strategies to shield sensitive data, systems, and networks from digital marauders. Their primary goal? To prevent unauthorized access, breaches, and cyber threats from compromising your company's digital assets.
Now, let's delve into the core services provided by these InfoSec companies. They perform risk assessments to identify potential vulnerabilities in your digital fortress. Think of it as a team of experts conducting thorough inspections to fortify weak spots. Next, they offer advice and guidance (like seasoned generals) on how to strengthen your defenses, recommending proactive measures tailored to your company's needs.
What makes these InfoSec companies even more formidable are the advanced technologies they employ — think of these as powerful shields and sophisticated sensors. Data science and machine learning for infosec are like the magic behind these shields. They help analyze enormous amounts of data, identifying unusual patterns that could signal an impending attack. By predicting potential threats and automating responses in real-time, these technologies bolster your defenses, keeping your digital fortress secure.
It's all about safeguarding digital treasures — your company's sensitive data and critical systems — from harm. This includes ensuring information remains confidential, maintaining its integrity, and guaranteeing its availability when needed. Think of it as the guardian of your digital realm.
The digital battlefield is more active than ever. In recent years, we've seen a dramatic escalation in cyber threats — from sophisticated phishing campaigns to AI-powered malware. For many companies, especially those handling large volumes of sensitive data, it's not a question of if an attack will happen but when. That’s why InfoSec companies have become mission-critical partners, not optional vendors.
Governments and regulators are also tightening compliance requirements. Frameworks like GDPR, HIPAA, and the EU’s AI Act impose strict controls on data handling and security infrastructure. Non-compliance isn’t just a legal risk — it’s a financial one. A single breach can result in fines, lawsuits, reputational damage, and loss of customer trust.
Moreover, hybrid work and cloud transformation have widened the attack surface. Your digital perimeter is no longer just your office network — it’s every employee’s device, every cloud-based app, and every third-party integration. InfoSec companies provide the tools and intelligence to monitor, manage, and protect this expanding landscape in real time.
Simply put, cybersecurity can no longer be reactive. Businesses must take a proactive stance — and that’s where IT security providers step in as indispensable guardians of your digital assets.
Now, let's peek into the toolbox of InfoSec solutions. These encompass various protective measures — like setting up security perimeters, securing individual access points, encrypting sensitive information, and continuously monitoring for any suspicious activities. Each tool serves as a shield, fortifying your digital fortress against potential attacks.
Security InfoSec takes this defense a step further. It's the integration of all these security measures across your entire digital landscape. Imagine an interconnected web of shields enveloping every aspect of your digital domain — this is Security InfoSec in action.
In summary, IT security providers are the vigilant guardians of your digital fortress. They offer specialized services, employ cutting-edge technologies, and implement comprehensive solutions to keep your company's digital assets safe from evolving cyber threats.
For teams seeking to bolster their company's InfoSec strategies, Opinov8 emerges as a reputable IT service company. Renowned for our top-notch security services and innovative solutions, Opinov8 stands ready to fortify your organization's cybersecurity posture.
InfoSec companies (short for information security companies) are specialized providers that help organizations protect their digital assets from cyber threats. They offer services such as risk assessment, data protection, network security, compliance management, and real-time threat detection.
With the growing number of cyberattacks and regulatory demands, businesses need InfoSec companies to ensure their data is secure, their operations are compliant, and their systems are resilient. These companies bring expertise, tools, and technologies that most in-house teams can’t easily replicate.
Most InfoSec companies offer services like penetration testing, vulnerability management, cloud security, identity and access management, incident response, and cybersecurity consulting tailored to the client’s industry and risk level.
Advanced InfoSec companies use AI and machine learning to detect anomalies in real-time, predict potential threats, and automate responses. These technologies enhance threat intelligence and reduce response times during incidents.
Look for InfoSec companies with experience in your industry, proven success stories, compliance knowledge (e.g., GDPR, ISO 27001), and scalable solutions. A good partner will also offer continuous monitoring and support, not just one-time audits.
The Web Summit, an unparalleled gathering of tech enthusiasts and industry pioneers, once again proved to be an enlightening experience for us at Opinov8. Our participation was not just about networking and showcasing our expertise; it was about diving deep into the pulse of emerging technologies, particularly the discussions revolving around the development and integration of Artificial Intelligence (AI) and Machine Learning (ML) into business operations.
One prevailing theme that echoed throughout the summit was the immense potential of these technologies to revolutionize businesses across diverse sectors. However, amidst the enthusiasm and buzz, a glaring reality stood out - the stumbling block for many companies in adopting these transformative technologies lies within their own data infrastructure.
The challenges associated with AI adoption often stem from disorganized, fragmented, or siloed data repositories within a company's ecosystem. Without a solid foundation of clean, accessible, and well-organized data, the implementation of AI/ML technologies becomes a lofty ambition, seemingly out of reach.
It is imperative for businesses to recognize that the bedrock of successful AI/ML integration begins with efficient data organization. No matter how groundbreaking these technologies are, overlooking the basics can impede progress and hinder the potential for innovation.
In alignment with our observations at the Web Summit, recent research conducted by Cisco in their "Cisco AI Readiness Index" strongly reinforces the significance of high-quality, accessible, and well-organized data for the successful adoption of AI technologies.
The study reveals that 81% of organizations struggle with data silos, hindering seamless AI integration. While around 60% practice consistent data preprocessing, a significant gap remains in understanding and implementing effective strategies.
Additionally, the report emphasizes the essential link between data analytics tools and AI, with 74% facing challenges in integrating these tools with data sources and AI platforms. Managing external data quality for AI models emerges as a pressing challenge, urging the need for better data lineage tracking. Overall, the study underscores the imperative of comprehensive data organization and quality assurance for businesses to fully leverage AI's transformative potential.
Organizing data for AI/ML adoption involves several critical steps. Firstly, companies need to conduct a comprehensive audit of their existing data assets. This audit should identify data sources, assess data quality, and streamline data governance protocols. Subsequently, data cleansing and normalization processes become pivotal, ensuring that data is consistent, accurate, and free from redundancies or inconsistencies.
Furthermore, establishing a robust data infrastructure is fundamental. Scalable storage solutions, efficient data pipelines, and advanced analytics capabilities are prerequisites for handling vast amounts of data necessary for AI/ML algorithms to learn and derive meaningful insights.
However, the requirements for an effective data infrastructure can be complex and demanding. It necessitates expertise in data architecture, database management, and a thorough understanding of AI/ML algorithms.
At Opinov8, we comprehend the significance of laying a strong foundation for AI/ML integration. With our expertise in data engineering, analytics, and AI solutions, we offer tailored strategies to help companies navigate the complexities of data organization. Our team collaborates closely with clients to assess their data landscape, devise data governance frameworks, and architect scalable infrastructures that align with their AI/ML aspirations.
Through our proven methodologies and cutting-edge technologies, we empower businesses to transform their data chaos into structured assets ready for AI/ML implementation.
Strategic expansion and resourceful collaboration have become pivotal for companies seeking to push the boundaries of technological innovation. Opinov8, a forward-thinking tech firm, has strategically positioned itself at the nexus of this pursuit by establishing a robust developer center in Egypt. This move isn’t just about geographical expansion but also represents a strategic leap towards enhancing its services for our European partners.
Egypt offers a cost-effective yet highly skilled tech labor force. Leveraging the lower operational costs in Egypt, Opinov8 can offer competitive pricing for its services. This is beneficial for German, Netherlands and European businesses looking for high-quality services at higher than 60% cost savings.
Egypt is nurturing a growing pool of tech talent with strong educational backgrounds in STEM fields. Opinov8, with its developer center in Egypt, gains access to this talent pool, providing diverse skill sets and innovative perspectives that benefit European customers seeking cutting-edge solutions.
Egypt's time zone is advantageous for real-time collaboration with Europe, offering overlapping working hours. This synchronization ensures swift communication, minimizing delays, and enabling more efficient project management.
Egypt's government is actively supporting the tech industry by investing in infrastructure and education. This support enhances the technological capabilities and fosters a conducive environment for innovation, benefiting Opinov8's offerings to European customers.
Egypt's geographical location makes it a bridge between continents, resulting in diverse perspectives and expertise. It positions Opinov8's Egyptian center as an ideal place for knowledge sharing and innovation, which directly benefits the solutions offered to our clients.
The burgeoning tech ecosystem in Egypt provides ample growth opportunities. As a result, Opinov8 is at the forefront of emerging technologies and methodologies, offering our clients access to the latest tech advancements for their projects.
Keep reading: Meet Meena, Manual QA Engineer at Opinov8's Egypt Hub.
Egypt's emphasis on language education means that a significant part of the workforce is proficient in multiple languages. This linguistic diversity can facilitate smoother interactions and project execution between Opinov8's Egyptian developers and our European clients.
May interest you: Opinov8 is a top IT Services Company accordingly to Clutch.
Contact us now! Our commitment lies in being more than just a service provider. We aim to be your strategic partner in navigating the dynamic world of technology, helping you not just meet but exceed your organizational goals. Through cost-efficiency, accelerated time-to-market, and a dedicated approach tailored to your needs, we stand ready to be the catalyst for your organization's success.
Enter containerization, the transformative technology that has revolutionized the very essence of how businesses deliver IT services and deploy applications. Its importance lies in its ability to streamline operations, enhance security, and accelerate time-to-market, making it a fundamental tool for companies striving to remain competitive in the fast-paced world of modern business.
Containerization is a transformative approach to software development and deployment. It helps IT service providers to make things run smoother, beef up security, and speed up the time it takes to get a product to market. At its heart, containerization is all about bundling up apps and all the stuff they need into these nifty, lightweight containers. These containers basically wrap up the app, its settings, and all the tools it needs, ensuring it works the same way everywhere it goes.
Unmatched Portability
One big plus with containerization is how portable it is. Containers can easily run on different setups, whether it's your dev machine, your live server, or even in the cloud. This portability eliminates the "it works on my machine" dilemma that plagues software development teams. By ensuring that applications run consistently across different environments, businesses can significantly reduce deployment-related issues and save valuable time and resources.
Resource Efficiency
Containers are all about being lightweight and smart. Unlike those old virtual machines (VMs), which demand a full operating system for each app, containers are like good roommates — they share the host's operating system kernel. This savvy sharing means you can fit more containers on a single host, getting the most out of your resources while cutting down on those hefty infrastructure bills.
Isolation and Security
Containerization provides a high degree of isolation between applications. Each container operates independently, with its own filesystem and processes. This isolation enhances security by minimizing the attack surface and reducing the risk of one application affecting another. It also simplifies application updates and patching, as changes made to one container do not impact others.
May interest you: Kubernetes Professional Services | Opinov8
Scalability and Flexibility
Containerization plays perfectly into the world of modern microservices. It's like having building blocks for your applications. You can break down your apps into smaller, super-flexible pieces, and when things get busy, you just scale up these containers as needed. This agility is a real lifesaver for handling the ups and downs of user traffic and making sure your apps stay snappy and dependable.
DevOps and CI/CD Integration
As an IT service company, we understand the importance of streamlining development and deployment processes. Containerization plays a pivotal role in DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines. Containers enable automated testing, rapid deployment, and efficient rollback, facilitating faster release cycles and improved collaboration between development and operations teams.
Containerization is supported by a robust ecosystem of tools and services, including:
Docker popularized containerization. It offers a user-friendly platform for creating, managing, and sharing containers, making it an industry standard.
Kubernetes is the leading container orchestration platform. It automates container deployment, scaling, and management, with extensive capabilities for load balancing and updates.
Amazon Web Services (AWS) App2Container streamlines application containerization, simplifying the process of migrating existing applications to containers on AWS.
Microsoft Azure Container Service (AKS) is a managed Kubernetes service, ideal for deploying, managing, and scaling containerized apps in Azure.
Google Kubernetes Engine (GKE) offers a managed Kubernetes service with advanced features for deploying containerized apps on Google Cloud.
These are just a few of the many tools and services available in the containerization ecosystem. You can choose the tech and platforms that best match your business goals.
At Opinov8, containerization is one of the core elements of our expertise. Our skilled professionals have extensive experience in container orchestration platforms like Kubernetes, which enables us to manage efficiently and scale containers in production environments. We tailor containerization solutions to the unique needs of each client, ensuring that they harness the full potential of this technology to drive business growth.
DevOps has taken center stage in modern IT operations. It revolutionizes how development and operations teams collaborate to deliver software faster and more reliably. At the core of this transformative approach, DevOps alerting tools are pivotal in ensuring the smooth functioning of DevOps processes, including essential components like DevSecOps services.
Effective alerting is the backbone of any successful DevOps operation. These tools act as the early warning system, instantly notifying teams about irregularities or issues within the software development and deployment pipeline. With real-time alerts, DevOps teams can proactively address issues, reducing downtime and minimizing the impact on end-users. This rapid response is crucial for maintaining the speed and efficiency that DevOps promises.
With proper alerting tools, DevOps processes can become smooth and active. Issues may only be noticed once they escalate, leading to costly downtimes and frustrated customers. Inefficient alerting can also result in alert fatigue, where the constant noise of false alarms desensitizes teams, causing them to overlook critical alerts. Investing in the right DevOps alerting tools is essential to avoid these pitfalls.
They streamline incident management by providing real-time notifications and comprehensive incident reports. This accelerates the identification of root causes and facilitates faster resolutions, minimizing the impact on operations. The result is improved service reliability and customer satisfaction.
DevOps is all about collaboration, and alerting tools are pivotal in fostering teamwork. These tools centralize incident information, enabling cross-functional teams to work cohesively, whether they are on-call engineers, developers, or operations staff. This collaboration ensures that issues are resolved efficiently, promoting a culture of continuous improvement.
DevOps alerting tools contribute significantly to the overall reliability of systems and applications. By monitoring key performance metrics and providing insights into system behavior, these tools empower organizations to proactively address potential issues, preventing them from escalating into critical failures. This proactive approach is vital for maintaining high availability and ensuring a positive user experience.
May interest you: IT Staff Augmentation Services.
DevOps is a journey, not a destination. Continuous monitoring and optimization are crucial for staying ahead of evolving challenges. DevOps tools enable organizations to track performance over time, identify trends, and fine-tune processes for maximum efficiency.
To prevent alert fatigue, it's essential to configure alerts thoughtfully. DevOps alerting tools allow for customization, enabling teams to set up alerts based on specific criteria and thresholds. This ensures that only relevant and actionable alerts are generated, reducing noise and preventing burnout among team members.
Feedback loops are essential in DevOps, and alerting tools are no exception. Regularly review alerting configurations and incident responses, seeking feedback from the teams involved. This iterative process helps refine alerting strategies, making them more effective and efficient.
Ensure the smooth operation of your IT infrastructure!
In the dynamic world of DevOps, alerting tools are indispensable for maintaining the speed, reliability, and collaboration that define successful DevOps practices. As a DevOps services company, Opinov8 is dedicated to helping you make the most of DevOps alerting tools and other vital DevOps services.
In a competitive business environment, staying ahead of the curve requires a strategic approach to IT staffing. Companies often face challenges in finding the right talent for their technology projects, and that's where IT staff augmentation services come into play.
At its core, IT staff augmentation is a strategic approach to staffing where companies hire skilled IT professionals temporarily to fill specific roles or skill gaps within their existing teams. This practice offers businesses unparalleled flexibility and scalability, allowing them to adapt quickly to changing project requirements and market demands. The excellence of IT staff augmentation lies in its ability to provide expert resources when and where you need them.
IT staff augmentation services are all about addressing your IT workforce needs efficiently and effectively. Whether you require a team of developers for a short-term project or a single IT specialist to enhance your existing team, this service caters to various requirements within the tech realm.
The advantages of IT team augmentation services are abundant. Firstly, it leads to substantial cost savings. Companies can eliminate the expenses associated with long-term hiring, such as salaries, benefits, and training, while still gaining access to top-tier talent. Additionally, by tapping into a diverse pool of IT experts, businesses can access specialized skills that might not be readily available in-house. This diversity of skills empowers companies to tackle complex projects and innovate more effectively.
Another significant benefit is the expedited project delivery. With IT team augmentation, you can quickly assemble a team of experts tailored to your project's needs, accelerating the development process and ensuring timely delivery.
Selecting the right IT staff augmentation firm is crucial to the success of your projects. To make an informed choice, consider factors such as the company's experience in the industry, expertise in various technologies, and its ability to align with your corporate culture and values. Ensure that they have a proven track record of successfully augmenting IT teams and delivering on their promises.
Choosing the right IT augmentation services can make all the difference in the success of your projects. By conducting thorough research and due diligence, you can establish a partnership that adds real value to your organization.
While both IT development outsourcing and IT staff augmentation are viable strategies for addressing IT needs, they serve different purposes. IT development outsourcing involves handing over the entire project to an external vendor, while IT staff augmentation allows you to maintain control over your project while leveraging external talent.
Each approach has its merits, and the choice between them should be based on your specific project requirements and business goals. Outsourcing IT development can be ideal for large-scale projects with well-defined scopes, while IT staff augmentation shines in situations where flexibility and control are paramount.
However, many businesses are increasingly turning to outsourcing IT services as well as IT staff aug to streamline their operations and reduce costs.
Keep reading: DevOps vs. Traditional IT support: The difference.
It's essential to differentiate between outstaffing and IT outsourcing company. Outstaffing involves hiring external professionals who work directly under your management and follow your project's objectives. On the other hand, outsourcing entails delegating the entire project or specific tasks to an external company.
When deciding between outstaffing and outsourcing, consider your project's complexity and your level of involvement. Outstaffing is beneficial when you need full control over the project, while outsourcing can be a more hands-off approach.
Contact us today to learn more about how Opinov8 can elevate your IT capabilities and help you achieve your business goals.
Cloud infrastructure has become the backbone of modern businesses. The flexibility, scalability, and cost-efficiency offered by the cloud have transformed the way organizations operate. However, with great power comes great responsibility. Managing cloud resources can be a challenging endeavor, and this is where cloud infrastructure monitoring tools come to the rescue.
The world has witnessed a monumental shift towards cloud computing in recent years. Organizations are migrating their applications and data to the cloud to leverage its numerous advantages. The cloud provides a competitive edge from cost savings and agility to global scalability.
While the cloud brings many benefits, it also introduces new challenges. Managing cloud infrastructure can be complex, with an array of services, configurations, and dependencies to oversee. Ensuring optimal performance, availability, and security in this dynamic environment can be daunting. Additionally, private cloud monitoring adds another layer of complexity, making it crucial to have a comprehensive strategy in place.
May interest you: Kubernetes Professional Services.
To effectively monitor cloud infrastructure, it's crucial to keep an eye on key performance metrics:
Monitoring these metrics provides insights into the health and performance of your cloud resources. It enables you to identify bottlenecks, potential failures, and opportunities for optimization.
Keep reading: UX, Infrastructure and Cloud Readiness Assessments
To master cloud infrastructure monitoring and ensure the seamless operation of your cloud resources, it's essential to leverage the right tools. However, monitoring can be complex, and Opinov8 offers an excellent cloud infrastructure monitoring service. Our experts can help you implement the most suitable monitoring tools for your specific needs, set up effective alerting, and ensure your cloud infrastructure is optimized for performance, cost, and security. Don't wait for issues to disrupt your operations; take proactive steps toward effective cloud-based infrastructure monitoring with Opinov8.
Keep reading:
Proxy trends in 2025 on Designrush.com.
Businesses that embrace the cloud must be especially vigilant in safeguarding their assets. Azure Kubernetes Service (AKS) offers a powerful solution for managing containerized applications, but without proper security measures, vulnerabilities can arise. In this article, we'll delve into the world of AKS security services and explore the best practices provided by Opinov8 to ensure your cloud environment remains resilient and protected.
Understanding AKS security best practices and their significance is the first step in fortifying your Azure Kubernetes Service environment. Businesses store sensitive data, valuable applications, and critical processes in the cloud. Without robust AKS security services, these assets are at risk. Imagine a scenario where unauthorized access or a breach compromises customer data or disrupts operations – the consequences could be devastating.
Opinov8 emphasizes that proactive security measures are paramount. It's not just about defense; it's about maintaining data integrity and ensuring business continuity through Azure Kubernetes security best practices. By adhering to these practices, you not only mitigate risks but also build trust with your customers and stakeholders.
Opinov8 recognizes the importance of securing the network environment surrounding your Azure Kubernetes Service cluster. Implementing Azure AKS networking best practices is instrumental in preventing unauthorized access and thwarting potential threats:
May interest you: Top Azure Partner and Azure Advisor.
Proactive security doesn't stop at prevention – it extends to monitoring and swift incident response. Opinov8 recommends these steps for adequate Azure Kubernetes service security:
Keep reading: Opinov8 is a top Azure Advisor according to Clutch.
In today's digitally interconnected world, the security of your Azure Kubernetes Service cannot be taken lightly. By understanding the significance of AKS container security and implementing Opinov8's Azure Kubernetes security best practices, you empower your business to thrive securely in the cloud. Remember, safeguarding your assets goes beyond compliance; it's about ensuring trust, customer satisfaction, and sustained growth.
Are you ready to fortify your Azure Kubernetes Service against potential threats? Opinov8's expertise in AKS security services can guide you toward a robust cloud environment. Contact us today to take your security measures to the next level and build a resilient future for your business. Your data and operations deserve nothing less than the best protection.
GCP DevOps Service has emerged as a transformative approach that bridges the gap between development and operations, promoting teamwork and boosting productivity. At the forefront of this paradigm shift is Google Cloud Platform (GCP), a formidable toolkit that helps organizations unlock the full power of DevOps. Let's explore how GCP cloud services establish the foundation for a seamless implementation of GPC DevOps Service and transform the way we develop, deploy, and manage software.
GCP's vast ecosystem is a treasure trove of services designed to elevate DevOps practices. From Google Compute Engine, which delivers virtual machines with unparalleled speed, to Google Cloud SQL, which offers managed MySQL and PostgreSQL databases, GCP provides a comprehensive suite of tools tailored to fuel innovation.
GCP's reputation for scalability, performance, and security is unparalleled. With a global network of data centers and robust infrastructure, including the highly secure GCP Virtual Private Cloud, applications scale seamlessly to meet demand while maintaining stringent security measures. This reliability empowers DevOps teams to focus on what truly matters: delivering value to end-users.
Keep reading: How to Choose the Right DevOps Tools?
GCP's DevOps arsenal, complemented by its powerful Google Cloud database services, is a testament to its commitment to facilitating collaboration and automation:
Container orchestration is made simple. GKE streamlines the deployment, management, and scaling of containerized applications, allowing DevOps teams to focus on code rather than complex infrastructure.
Revolutionizing CI/CD pipelines, Cloud Build automates the build, test, and deployment stages of development, accelerating the release cycle and enhancing code quality.
Monitoring and logging reimagined. Stackdriver provides real-time insights into application performance, ensuring issues are detected and resolved promptly to maintain optimal user experiences.
Infrastructures as code made easy. DevOps teams can define and manage cloud resources using declarative templates, promoting consistency and traceability.
Version control at your fingertips. Cloud Source Repositories offer secure, scalable hosting of private Git repositories, fostering collaboration and efficient code management.
Speaking of startups, GCP doesn't just provide a toolbox; it offers a tailored ecosystem with the Google Cloud Platform for Startups program. With cost-effective solutions and an array of services designed to accelerate growth, startups find a supportive partner in GCP.
Each GCP service seamlessly integrates into the DevOps workflow, fostering collaboration between development and operations teams. GKE's dynamic scaling ensures applications meet demand spikes, while Cloud Build's automation expedites the delivery process. Stackdriver's insights enhance reliability, and Deployment Manager's infrastructure automation minimizes manual errors. Cloud Source Repositories facilitate efficient code sharing, making collaboration a breeze.
Amid this, Google Cloud pricing ensures budget optimization, while the robust Google Cloud infrastructure provides a resilient foundation. From virtual machines via Google Compute Engine to managed databases like Google Cloud SQL, this infrastructure streamlines operations, letting DevOps focus on innovation.
May interest you: Opinov8 is a Top Development Company accordingly to Clutch.
Amidst evolving DevOps landscape, embracing GCP's capabilities is strategic for startups and enterprises. Opinov8's GCP DevOps expertise guides streamlined development, including hosting React apps on Google Cloud for performance and scalability.
In conclusion, Google Cloud Platform isn't just another cloud provider; it's a powerhouse that fuels the DevOps revolution. With diverse services, scalable infrastructure, and strong security, GCP enables collaborative, automated, agile software development. Embrace the GCP advantage with Opinov8, and let DevOps drive your success story. Contact us now and talk for free to a GCP expert:
Business is now driven by digital transformation, and the healthcare sector is no exception. Adopting innovative technologies has become essential for healthcare facilities to optimize their operations and enhance patient care. One such popular solution is healthcare cloud-managed services. This article explores the evolution, advantages, data security, and compliance of healthcare cloud services, highlighting how they are transforming the healthcare landscape.
Over the years, cloud computing in healthcare has undergone significant advancements. It effectively tackles critical challenges that healthcare facilities encounter, such as data security, scalability, and interoperability. Cloud services revolutionize healthcare IT, enabling seamless access to patient records, images, and real-time data across diverse settings, including storage. This accessibility has fostered improved collaboration among healthcare professionals, allowing them to store and access patient data and medical records effortlessly and securely. As a result, healthcare providers can make timely and informed decisions, ultimately elevating patient care and enhancing health outcomes.
Healthcare cloud-managed services offer a myriad of benefits for healthcare organizations. One of the primary advantages is cost savings. By moving to the cloud, healthcare facilities can significantly reduce their infrastructure costs, as they no longer need to invest heavily in on-premises hardware and maintenance. Additionally, the cloud's pay-as-you-go model allows for better cost management and resource allocation.
Another key advantage is increased flexibility. Healthcare providers can easily scale their cloud resources based on fluctuating demands, ensuring they have the necessary infrastructure to support peak times and high-volume data processing. This scalability is particularly beneficial for healthcare organizations that experience seasonal fluctuations or rapid growth.
Healthcare cloud solutions also enable healthcare providers to enhance data analytics capabilities. Healthcare facilities can tap into the potential of big data and advanced analytics tools to gain meaningful information about patient trends, treatment outcomes, and operational efficiencies. This approach, based on data analysis, supports informed decision-making, ultimately contributing to improved patient outcomes.
Additionally, cloud-based solutions are instrumental in facilitating telemedicine, remote patient monitoring, and telehealth services, bringing convenience and accessibility to healthcare delivery. Through medical cloud computing, healthcare providers can reach patients in remote areas, offer virtual consultations, and monitor patients' health remotely. This increased reach fosters accessibility to healthcare services and enhances patient engagement.
One of the most critical concerns surrounding healthcare cloud services is data security and patient privacy. Reputable cloud service providers, such as AWS Healthcare and Microsoft Cloud for Healthcare, address these concerns through robust security measures. These providers follow industry standards and compliance regulations, such as HIPAA (Health Insurance Portability and Accountability Act) and GDPR (General Data Protection Regulation), ensuring that patient information remains confidential and protected from unauthorized access.
HIPAA-compliant cloud storage in 2022 is a crucial requirement for healthcare organizations dealing with sensitive patient data. The AWS healthcare-managed services and other cloud service providers offer robust encryption, access controls, and regular audits to ensure data integrity and compliance with regulatory standards.
As the healthcare industry continues to evolve, embracing cloud technology is becoming essential for healthcare facilities. Healthcare cloud-managed services offer a host of benefits, including cost savings, increased flexibility, improved data analytics, and expanded access to patient care. However, ensuring data security and compliance with industry regulations remains a top priority.
For expert guidance in adopting and implementing healthcare cloud-managed services tailored to your specific needs, consider reaching out to Opinov8. We empower healthcare providers with innovative cloud solutions, helping them navigate the digital transformation journey, and delivering exceptional patient care.
Discover how our healthcare cloud solutions can revolutionize your healthcare facility's operations and patient outcomes. Our team of experts will provide a detailed analysis to calculate customized health cloud pricing, ensuring cost-effectiveness and optimal resource allocation.
Every business is seeking efficient and scalable infrastructure solutions to stay competitive. This is where a cloud managed platform come into play, enabling organizations to harness the power of the cloud while optimizing their IT operations. In this article, we will explore the concept of cloud-managed platforms, their benefits, and how Opinov8 can help you to meet your business needs.
A cloud-managed platform is a modern IT infrastructure model that replaces traditional on-premises systems with a cloud-based approach. It offers a comprehensive suite of tools, services, and resources to streamline and optimize IT operations. Unlike conventional models, cloud-managed platforms provide flexibility and scalability, allowing businesses to adapt to changing demands and scale their infrastructure.
With the best multi-cloud management platforms, such as those listed in Gartner's Magic Quadrant, businesses gain access to a comprehensive suite of tools and services. This enables them to streamline and optimize their IT operations across multiple cloud environments, including AWS and Azure.
Looking to optimize your cloud operations and unlock the full potential of AWS and Azure? Discover the power of managed services for AWS and Azure with Opinov8. As a leading provider of cloud solutions, Opinov8 offers expert AWS fully managed services and Azure management services tailored to your business needs. Maximize the efficiency and scalability of your cloud infrastructure while benefiting from Opinov8's industry-leading expertise. Experience seamless cloud management with Opinov8 and take your AWS and managed services for Azure.
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Cost savings are a significant advantage of cloud-managed platforms. These platforms eliminate the need for expensive hardware investments and maintenance costs. By leveraging the cloud's resources, businesses can reduce their capital expenses and operate on a pay-as-you-go model, optimizing costs while maintaining performance. Additionally, implementing cloud cost management software enhances cost optimization even further, providing businesses with the tools and insights to manage and control their cloud spending effectively.
Cloud-managed platforms implement robust security measures to safeguard data and applications. Providers prioritize data encryption, access controls, and proactive monitoring to ensure the highest levels of security. This allows businesses to protect their sensitive information and comply with industry regulations. As an additional layer of protection, businesses can also benefit from utilizing cloud backup solutions. These solutions offer automated backups and data replication to secure cloud storage, providing an extra level of data protection and disaster recovery capabilities.
With cloud-managed platforms, businesses can enjoy reliable and high-performance infrastructure. Providers leverage cutting-edge technologies and best practices to optimize network speeds, minimize latency, and ensure maximum uptime. This translates into improved user experiences and enhanced productivity.
Cloud-managed platforms streamline IT operations by centralizing control and monitoring. They offer intuitive dashboards, automation capabilities, and comprehensive reporting, empowering businesses to manage their cloud resources efficiently. This simplified management reduces the burden on IT teams and frees up valuable time and resources while ensuring data protection and disaster recovery. The cloud backup server acts as a central hub for securely storing and accessing backup data, simplifying the management and retrieval process.
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Opinov8 meets all these requirements and goes above and beyond, offering a comprehensive suite of cloud-managed platform services backed by a proven track record, robust security protocols, seamless scalability options, and exceptional customer support, ensuring a successful implementation tailored to your business needs.
Evaluate the provider's track record, uptime guarantees, and service level agreements to ensure reliable performance. Also, look for reputable cloud hosting providers with a proven track record of maintaining high availability and uptime.
Assess the provider's security protocols, including data encryption, access controls, and compliance certifications, to protect your data.
Look for a provider with scalability options to meet your business's evolving needs. Consider their ability to handle peak workloads and seamlessly accommodate growth. They advise you on the best cloud hosting to ensure that your infrastructure can seamlessly adapt to changing demands.
Determine the level of customer support offered by the provider. Responsive and knowledgeable support teams are invaluable in addressing issues promptly and minimizing downtime.
If you're ready to harness the power of cloud-managed platforms, contact Opinov8, a leading provider of Cloud Managed Platform services. Our expert team will guide you through the process, ensuring a seamless and successful transition to the cloud.
DevOps as a Service is essential in the era of digital transformation, as companies always strive to achieve efficient software delivery, optimize operational processes, and outperform their competitors. That’s why managed services software development is popular.
DevOps is the process of automate software development life cycle starting from planning until continuous integration and deployment of solutions and software across different platforms, a transformative approach emphasizing collaboration, automation, and continuous delivery. However, the challenges of implementing and sustaining modern DevOps practices internally should not be underestimated. It demands specialized skills, substantial resources, and a cultural transformation within the organization. Thankfully, there is a solution: DevOps as a managed service. This approach harnesses the power of external expertise, scalability, and cost-effectiveness.
Implementing modern DevOps as a service practices brings numerous benefits to organizations, including faster software delivery cycles that enable businesses to respond swiftly to market demands and customer needs. By incorporating automated processes, organizations can effectively reduce human error and enhance the overall software quality.
While the benefits of DevOps as a service are compelling, implementing and managing DevOps practices internally can be challenging. Cultural barriers, resistance to change, and a lack of expertise often hinder successful adoption. Additionally, integrating diverse technologies, tools, and platforms can pose technical complexities, requiring specialized knowledge across various domains.
DevOps as a managed service offers organizations a strategic solution to overcome the challenges associated with in-house implementation. As one of the well-known partners in the region Opinov8 support customer to eliminate applying DevOps challenges including not limited to cultural barriers, resistance to change, and a lack of expertise often hinder successful adoption. Additionally, facilitating integration between diverse technologies, tools, and platforms which can pose technical complexities, requiring specialized knowledge across various domains.
Opinov8 is your DevOps reliable partner that will brings to you several advantages.
First, we significantly reduce upfront investment, as organizations can leverage our existing infrastructure and tools.
Second, the implementation process is accelerated, enabling organizations to start reaping the benefits of DevOps swiftly. Moreover, partnering with a trusted managed service provider ensures access to a highly skilled team that possesses in-depth expertise across different aspects of DevOps, including AWS DevOps, Azure DevOps Server, incident management in DevOps, and modern DevOps practices. This expertise translates into improved operational efficiency, enhanced security, and compliance.
We typically offer a comprehensive range of services covering the entire DevOps lifecycle. These services encompass strategy and planning, architecture design, infrastructure provisioning, automation, continuous integration and delivery, monitoring, and ongoing support.
By tailoring our offerings to the specific needs of each client, we help organizations navigate the complexities of DevOps while aligning with our customers business objectives. With our expertise and experience, we enable business owners to streamline their software life cycle, optimize software delivery, and achieve operational excellence.
This comprehensive guide shows the intersection of technology and healthcare, shining a spotlight on the Healthtech trends in Germany. It highlights the transformative impact of Opinov8's innovative software development services on the HealthTech industry, driving revolutionary changes in patient care, operational efficiency, and transformative growth. With their pioneering approach, Opinov8 is at the forefront of shaping the future of healthcare in Germany, ushering in a new era of possibilities.
📈 Key trends and emerging technologies shaping the HealthTech sector in Germany.
💻 The vital significance of Software Development services in driving healthcare innovation in Germany.
🌐 How HealthTech solutions in Germany are elevating patient outcomes and experiences.
🔍 Illustrative case studies demonstrating real-world implementations in the German HealthTech landscape.
Discover the compelling reasons to dive into this enlightening publication. Uncover invaluable knowledge regarding the dynamic evolution of the HealthTech realm in Germany, while remaining updated on the groundbreaking solutions that propel transformative shifts. Embrace this chance to proactively stay at the forefront of the German HealthTech industry.
You might find it intriguing to note that Clutch acknowledges Opinov8 as a leading software development firm.
Uncover the groundbreaking transformation occurring at Weld Health as they harness the power of microservices on AWS to reshape their system architecture. Witness Weld Health as they architect microservices on the AWS platform, pushing the boundaries of what's possible.
So what is TaaS? In tech industry, where cloud computing and distributed systems are shaping the way businesses operate, the "anything as a service" (XaaS) acronyms have become the hottest trends. From SaaS (software as a service) to IaaS (infrastructure as a service) and PaaS (platform as a service), these acronyms represent the fundamental shift towards adopting cloud-based solutions. One of the more recent additions to the XaaS family is TaaS, or testing as a service, which offers significant benefits for businesses looking to enhance their testing processes.
TaaS meaning: Testing as a Service (TaaS) involves outsourcing testing to specialized firms that excel in recreating real-world scenarios to assess the functionality, performance, and security of applications or websites. Understanding its various types can help businesses leverage this service effectively.
Functional testing involves testing the front-facing parts of an application or website — including the User Interface (UI) and Graphical User Interface (GUI) — to see how potential customers will interact with it. This helps companies to see if their application is intuitive, as well as functional, and helps identify potential bugs that are likely to be among the most visible.
Keep reading: What is User Experience (UX) and Why Is It Important?
The second type of TaaS is performance testing. TaaS firms will stress-test an application’s ability to handle multiple users, creating virtual users to see how the application performs under load. This can provide invaluable information for a company looking to ensure their application or website can scale and grow as needed.
Quickly becoming one of the most important aspects of this, security testing scans and probes your application or website for any vulnerabilities. With more and more legislation putting additional burdens on companies to protect user data, security testing provides an added layer of accountability.
Related content: WHAT IS QUALITY ASSURANCE (QA)? | Opinov8
TaaS offers a number of significant benefits to development firms and projects.
1. Speed. Because TaaS firms specialize in testing, they are often able to test and find issues much more efficiently than in-house development teams.
2. Perspective. Developers and development teams can sometimes develop tunnel vision, only looking at their product from a specific point of view. Outside firms may approach an application or website from a completely new point of view that enables them to see things that would otherwise be missed.
3. Accountability. Especially in the realm of security, accountability is king. Having an outside firm test and verify the security of an application or website can go a long way toward reducing liability if there is an unfortunate breach.
Without a doubt, TaaS is quickly becoming an invaluable part of many companies’ development efforts. In the years to come, this service will continue to take a more dominant role among the XaaS acronyms.
Kubernetes, an open-source container orchestration platform, has emerged as a powerful tool for managing and scaling applications. However, implementing and managing Kubernetes on Google Cloud, AWS, and Azure can be complex and challenging without the right expertise. This is where Opinov8, a leading provider of Kubernetes professional services, comes into play. With its exceptional services and expertise, Opinov8 empowers businesses to harness the full potential of Kubernetes.
Opinov8 recognizes the transformative power of Kubernetes and its ability to streamline application deployment, scalability, and management. As a provider of Kubernetes professional services, Opinov8 offers comprehensive solutions to help organizations effectively leverage this technology.
Opinov8 stands out as a leading provider of Kubernetes professional services, empowering businesses to harness the full potential of this powerful technology. Contact us and talk with a Kubernetes Professional Services Expert:
This comprehensive white paper delves deep into the intersection of technology and healthcare, shining a spotlight on the Healthtech trends in Switzerland. It highlights the transformative impact of Opinov8's innovative software development services on the HealthTech industry, driving revolutionary changes in patient care, operational efficiency, and transformative growth. With their pioneering approach, Opinov8 is at the forefront of shaping the future of healthcare in Switzerland, ushering in a new era of possibilities.
Gain valuable insights into the advancements shaping the HealthTech landscape in Switzerland and stay informed about the innovative solutions driving transformative changes. Don't miss out on this opportunity to stay ahead of the curve in the Swiss HealthTech sector.
May interest you: Opinov8 is a Top Software Development Company accordingly to Clutch.
Discover how Weld Health is revolutionizing their system architecture by leveraging microservices on AWS. This captivating case study showcases the remarkable advancements and outcomes achieved through their innovative approach.
Weld Health, architecting microservices on AWS.
This comprehensive white paper delves deep into the intersection of technology and healthcare in the United States, revealing the Healthtech trends in the USA. This document highlights the transformative impact of Opinov8's innovative software development services on the HealthTech industry. By revolutionizing patient care, enhancing operational efficiency, and driving transformative growth, Opinov8 is at the forefront of shaping the future of healthcare.
Whether you're a healthcare professional, a technology enthusiast, or an industry leader, this document is an invaluable resource for gaining a comprehensive understanding of the dynamic landscape of healthcare and the transformative power of Software Development services for the HealthTech industry.
May interest you: Opinov8 is a Top Software Development Company accordingly to Clutch.
Explore the remarkable journey of Weld Health as they revolutionize their system architecture by leveraging microservices on the AWS platform.
Case Study: Weld Health, architecting microservices on AWS.
One of the most time-consuming and laborious projects that can come to a digital development company is an enterprise product to build from scratch or redesign. Each of these projects presents serious challenges ranging from complex workflows to diverse user roles. So, creating effective solutions that will satisfy users' and business needs can be a rather tough task. And that is the work of an enterprise designer.
In this article, we will explore the importance of UX design in enterprise projects and how it can help to achieve business goals, including employee productivity improvement, efficiency increase, and general experience enhancement.
Before diving deeper into the subject, let’s define what we call enterprise design and why it differs from the consumer field of UX. Enterprise design is a field of UX design focused on building software for large organizations and companies. These solutions can vary from internal systems used by the company's employees to products distributed commercially.
The key difference between enterprise design and other forms of UX design is that enterprise design takes into consideration the whole organization with all its professional end business challenges. This involves understanding large and complicated workflows and systems, adjusting these systems for diverse user roles, and establishing consistent communication between different departments of one enterprise ecosystem.
The main goal of enterprise design is to improve the usability and efficiency of an enterprise product. Just as important, the realization requires covering both users’ and business needs. Enterprise design helps to cope with this task and achieve the primary goal in a complex way.
One of the primary benefits of enterprise design is maximizing ROI. Usually, when clients come to a development company with their project, they have requirements and a general idea of how the final product should work. However, as practice shows, nearly half of all original requirements will bring minimal value for the product in the initial stages. Here takes place rule 80/20 or the Pareto principle: approximately 20% of all features will bring 80% of product value and success. In order not to waste any efforts and recourses on the less-profitable features, enterprise designers collect the owner’s requirements and users' suggestions, analyze them surreally, and then prioritize. In such a way, the development resources are allocated to the most valuable and profitable 20% of features, maximizing ROI.
Another key benefit is improving efficiency. An enterprise product essentially is a software tool that is created for different user roles to help accomplish their tasks and goals. Enterprise designers discover the main professional needs and pain points of each role and, in the final, tailor each part of the enterprise system to the specific needs of the corresponding role. When the instrument is created considering the requirements of all users who interact with it, then it results in efficiency and productivity increase, which, in its turn, leads to substantial time and cost savings in the long run.
Enterprise products often are complicated systems that can be used by different departments and include separate modules or even applications. All products should follow the same design language to decrease users’ efforts in learning alternative patterns, improve usability in general and reduce confusion. When users are familiar with a design language and can anticipate how different applications and tools work, they can complete tasks faster and more accurately. Visual consistency is also a main principle in brand recognition and loyalty. When users observe the same stylistic language and usability patterns across all touchpoints, they are more likely to feel trust. This will result in better customer engagement over time.
As with any professional working tool, enterprise software requires instructions on how to use it. Time and effort-consuming training are the potential sources of negative user experience and low productivity levels. When enterprise designers create intuitive software tools, organizations can reduce the time and resources required to train new employees and, in this way, reduce the learning curve. The most important thing here is to design solutions that are based on the users’ previous professional experience with similar tools and that are easy to learn and use.
We have hands-on expertise in various enterprise domains, including logistics, medicine, project and resource management. In each case, we have provided an individual approach, but that is based on the best enterprise design practices:
Despite the common belief that in enterprise design, the traditional user-centric approach takes a back seat, we can tell for sure that enterprise designers cannot ignore the main principles of UX design because complex systems require being user-friendly and intuitive even more than design for consumers. Enterprise designers should always prioritize the needs and goals of the end users because this is the only way to create an intuitive and effective interface.
Conducting user research is essential for gaining insight into the requirements and objectives of users. In our practice, the most preferable way to collect necessary data is by conducting user interviews. Communication with real users, studying their workflow, and gathering feedback provide the development team with the data that allows further feature prioritization and functional specification. In case of tight time or human resource limits, we also can suggest conducting user surveys. While surveys are typically used as part of comprehensive user research alongside interviews to gather more data that is later refined through live interviews, they can also serve as the primary means of gathering information about users in certain situations.
After conducting usability research, all gathered information is analyzed, structured, and grouped. The development team gets it in the form of user persona portraits, user experience maps, and user research reports. It helps to align all the team over the same issues that should be in focus during the development process.
Designing a software tool is not just building screens with some required data and features. It is a complex process of understanding users, defining problems, ideating solutions, and testing designs on real users to ensure that developed solutions meet users’ needs. Each project should start with users and end with users. First, we get acquainted with users, learn their needs and problems via research, and then test ideas, prototypes, or completed projects on those users. By conducting usability testing, we can find areas of confusion, make adjustments and improve user experience, and in such a way, provide a better product.
What is more important, conducting usability testing early in the design process can help identify issues before the product is released, saving time and money on costly redesigns later on.
It often happens that numerous workflows with various paths and interaction points bring much confusion in the development process. This mass has rather painful consequences. Some intermediate features can be forgotten, so in some use cases, users can face errors and lose the ability to fulfill their tasks. To avoid such a scenario, designers first build maps that can guide the rest of the development team across all systems. User flow is a perfect variant of how designers can anticipate all possible variants of interaction with a product and visualize it in the form of a diagram that consists of different screens, interactions, and decisions that users should make. It is not only a guarantee that all UI states will be worked over. It is also a way to discover touchpoints where users may become confused or frustrated.
Usually, enterprise products have a rather long lifecycle. During this lifecycle organization will grow, the number of user roles can change, and the workflow can become more complicated. Consequently, software solutions should scale in accordance with the business. So, scalability is a key consideration when planning and executing these types of projects. This requires careful planning and building an information architecture that will allow adding new features and functionality without disrupting the existing system. For this, the best way to facilitate all enhancements is to build modular and flexible design systems and use universal usability patterns that can be adapted to new use cases and business requirements.
Often happens, that project starts as a desktop application, but in a year or two, the concept changes, and a requirement comes to create a mobile application for this product. If scalability wasn't taken into consideration in the initial stages, then developing a mobile application will require much more time and effort.
Following these practices helps us to achieve all those benefits for which enterprise design is appreciated. We try to break the stereotype that enterprise products should always have monstrous and complicated interfaces where users can get lost without precise training. These software tools can be user-friendly, easy to navigate, and use. As mediators between the world of users, business, and development teams, enterprise designers do not set a goal to create a Swiss knife but put compromise between the expectations of all sides as a top priority. The modern, well-designed corporate product should serve as an instrument to solve tasks without extra effort and time spent.
However, there we do not insist that it is mandatory to start projects always with user Interviews and surveys, validate each idea on end-users, work out meticulous user flows and app maps, or build comprehensive cross-platform design systems. Each project requires a case-by-case approach to achieve business goals and solve professional tasks. However, to get maximum results with minimum expense, we highly recommend not ignoring enterprise design with all its principles and approaches. Nobody but users know better what will influence their productivity and efficiency improvement. Investment in enterprise design is an investment in product success.
Our team of experts is available to assess your current operations and determine where we can provide assistance.
In today's fast-paced digital landscape, it's essential to stay ahead of the curve when it comes to creating exceptional digital products and platforms. That's where Opinov8 comes in. We, as a leader in digital solutions, dedicate ourselves to assisting businesses in achieving their goals and streamlining their IT ecosystems.
If you're reading this article, it's likely that you're in charge of a company, and you understand how crucial it is to offer your clients an excellent user experience. Additionally, it's crucial to allocate workloads efficiently, enabling your team to concentrate on other critical tasks. Furthermore, implementing best practices in your IT ecosystem is equally important.
If you're unsure about the answers to any of these topics, we encourage you to keep reading. Opinov8 designed different assessments to help your business achieve exceptional results and develop outstanding digital products and platforms.
We designed the User Experience assessment with the goal of ensuring that your clients have a seamless experience when using your applications and digital products. Moreover, our assessment will identify areas where we can make improvements to enhance the overall user experience. This, in turn, can lead to higher customer satisfaction rates and increased revenue for your business.
The Cloud Readiness assessment will help you determine if you have allocated your workloads in the most efficient place. We'll analyze your current infrastructure and identify opportunities to migrate to the cloud, which can reduce costs and improve performance.
We created our Infrastructure assessment to optimize the performance and security of your IT ecosystem. We'll assess your infrastructure, suggest improvements for data security and system efficiency.
Keep reading: Opinov8 is recognized as a leading software development company according to Clutch.
At Opinov8, we're committed to helping businesses succeed in the ever-changing digital landscape. Through critical assessments, we equip you with tools and expertise to achieve goals and stay competitive.
Our team of experts is available to assess your current operations and determine where we can provide assistance.
We are here to provide comprehensive assistance tailored to your specific needs. Whether you require support in cloud computing, data management, software development, quality assurance, or risk management, our dedicated team is ready to assist you every step of the way.
As part of our commitment to excellence, we offer complimentary assessments in various critical areas, including Cloud Readiness, Infrastructure, User Experience, Data Management, and Modernization. Rest assured, our expertise and resources are at your disposal to ensure your success.
The maritime industry has always been complex, involving numerous stakeholders such as charterers, shipowners, and operators. This complexity makes operational efficiency critical, with even small optimizations translating into savings worth five or six digits in direct costs. The increasing pressure of sustainability and environmental regulations adds another layer of urgency for modernization and smarter decision-making.
Big data analytics in maritime industry is transforming operations. It helps companies lower costs, improve efficiency, and stay compliant with strict regulations. The maritime sector generates huge amounts of data daily — from vessels, sensors, and logistics systems. Managing and using this data effectively is now essential. Opinov8 develops advanced platforms that turn this complex data into clear insights, enabling businesses to make smarter, more informed decisions.
Fuel accounts for up to 60% of a vessel's operating expenses. Big data analytics can track fuel usage in real time, providing insights into consumption patterns and inefficiencies. For instance, using maritime data analytics, operators can optimize routes based on historical weather patterns and current sea conditions. Predictive analytics helps identify when to switch between slower speeds or alternative routes to save fuel without compromising delivery schedules.
The integration of vessel data analytics allows operators to monitor KPIs like engine performance, hull condition, and energy efficiency. By analyzing sensor data, potential breakdowns or maintenance needs can be predicted and addressed before they occur, reducing downtime and maintenance costs. For example, marine data analytics can detect patterns in vibration and noise levels, alerting operators to engine misalignments or wear and tear.
Stricter environmental regulations, such as the IMO 2023 targets for reducing greenhouse gas emissions, demand innovative solutions. Maritime predictive analytics helps monitor emissions in real time and suggests strategies for meeting compliance targets. This includes optimizing fuel types, leveraging renewable energy sources, and implementing retrofitting solutions.
The Role of Big Data Analytics in Maritime Industry
One of the biggest hurdles in the maritime sector is managing fragmented data sources. Information is collected from various stakeholders, including shipping companies, port authorities, and logistics providers. Without proper integration, this data remains siloed and underutilized.
Big data analytics in maritime industry bridges this gap by unifying disparate datasets into a centralized platform. Opinov8’s solutions ensure seamless data integration, delivering actionable insights to decision-makers across the value chain.
Data quality is paramount in ensuring reliable analytics. Inconsistent or incomplete data can lead to poor decision-making. Opinov8 employs medallion architecture, a tiered system that cleans and categorizes data at different stages. This ensures that only high-quality, actionable insights are delivered to decision-makers.
In an industry where conditions change rapidly, real-time data processing is critical. Opinov8’s cloud-based solutions on Azure enable the processing of millions of sensor readings daily. For instance, live data from vessel telemetry can be used to adjust routes dynamically in response to unexpected weather or port delays.
Check out Opinov8, a leading advisor and partner for Azure services.
The adoption of cloud technologies like Azure has been a game changer for the maritime industry. By migrating legacy systems to the cloud, Opinov8 helps businesses scale their data processing capabilities. This allows for handling vast datasets generated by maritime big data systems without compromising speed or accuracy.
Machine learning models are used to predict maintenance needs, optimize fuel consumption, and even forecast market trends. For example, Opinov8’s machine learning engine analyzes historical data to predict vessel performance under various conditions, enabling proactive adjustments.
To make these innovations possible, maritime companies rely on a powerful tech stack. Here's a breakdown of core technologies and how Opinov8 implements them:
IoT sensors on vessels collect data ranging from engine performance to environmental conditions. When integrated with maritime data analysis platforms, this data provides a comprehensive view of operations, enabling real-time decision-making.
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A leading maritime operator faced issues with fragmented data systems and inconsistent analytics. Their existing platform lacked the scalability to handle growing data volumes and failed to provide actionable insights.
Opinov8 conducted Discovery Workshops to understand the client’s challenges and goals. We implemented a cloud-based solution using Azure, focusing on:
The new platform processes 7 million sensor readings daily, providing real-time insights for operational efficiency. Key achievements include:
Explore how Opinov8 transforms logistics with cutting-edge digital solutions.
The future of maritime analytics lies in predictive capabilities — a key advantage of Big Data Analytics in Maritime. By analyzing historical data, machine learning models can forecast equipment failures and recommend maintenance schedules in advance, helping operators minimize downtime and reduce operational costs.
Digital twin technology creates a virtual replica of a vessel, enabling operators to simulate different scenarios. This helps in testing fuel optimization strategies, assessing retrofitting options, and planning efficient routes.
With the growing importance of maritime business intelligence, ensuring data security is critical. Blockchain technology offers a decentralized way to store and share data securely, reducing the risk of cyberattacks.
Opinov8 works with maritime businesses to turn big data into real results through big data analytics in maritime. We build cloud-based platforms, apply machine learning, and unify complex data systems into a single, streamlined process. Our solutions help improve operations, reduce costs, and support sustainability goals. Want to see it in action? Explore our logistics transformation case study or get in touch to learn how we apply Big Data Analytics in Maritime to solve real-world challenges.
It refers to the use of advanced technologies to collect, process, and analyze large-scale data from vessels, ports, and sensors to improve efficiency and compliance.
It analyzes consumption patterns, weather data, and routes to optimize travel plans, helping operators reduce fuel use by up to 15%.
Cloud computing (like Azure), IoT sensors, machine learning, and medallion architecture all support real-time, reliable analytics.
Take a look at Opinov8 Technology Services' Clutch profile.
The logistics industry is a complex ecosystem that involves the movement of goods and services from one point to another. With a multitude of factors to consider, such as transportation costs, labor, and infrastructure, logistics providers are always looking for ways to improve efficiency and reduce costs. One way they can achieve this is by understanding the difference between OPEX and CAPEX and how software technologies can help.
OPEX, or operational expenditures, refers to the day-to-day costs associated with running a logistics operation. This can include expenses like wages, fuel costs, and maintenance fees. On the other hand, CAPEX, or capital expenditures, refers to investments in physical assets like trucks, warehouses, and IT infrastructure.
While both types of expenditures are important for logistics providers, there are key differences between the two. OPEX is more flexible and can be adjusted in response to changes in demand or market conditions. CAPEX, on the other hand, is a long-term investment that requires careful planning and management.
The logistics industry can benefit from shifting from a capital expenditure (CAPEX) model to an operating expenditure (OPEX) model in several ways. Here are some ways IT can pass from a CAPEX model to an OPEX model in the logistics industry:
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These days, in the ever-evolving landscape of technology, it can often feel overwhelming with the sheer number of tech companies vying for attention, each claiming to be the next disruptor in their respective industries. With such a saturation of companies and claims, it becomes crucial to develop the ability to discern which companies are truly capable of delivering on their promises. In the realm of software development, where innovation and potential go hand in hand, it is essential to have a framework for evaluating the worth and potential of a software development company. To aid you in this process, it is imperative to seek answers to a set of five fundamental questions that delve into various aspects of the company's operations.
A software development company's leadership team plays a pivotal role in shaping its trajectory. Effective leadership demands a unique blend of technical expertise, visionary thinking, and operational acumen. While it is rare to find a single individual who excels in all three areas, it is crucial to identify these essential characteristics within the company's leadership team. Additionally, pay attention to the chemistry and synergy among team members. A harmonious leadership team fosters an environment where talented minds collaborate seamlessly toward a common goal, driving the company's success.
Might interest you: IT Outsourcing: everything you need to know.
Understanding a software development company's revenue model is vital to assess its financial sustainability. Various revenue models exist, ranging from advertisement-based revenue to service fees and subscriptions. Each model has its nuances and impacts the company's profitability differently. For instance, a company leveraging data to deliver targeted advertisements may generate higher profits compared to a company displaying generic ads. On the other hand, a company subsidizing its service fees to attract a wider user base might initially sacrifice short-term profitability for long-term growth and customer loyalty.
Determining the current value of a software development company involves applying established valuation techniques similar to any other company. Three commonly employed approaches are the cost approach, the market approach, and the intrinsic value approach. Depending on the company's unique circumstances, one of these approaches will provide a more accurate assessment of its worth. Remember that software development companies are no exception to the principles of valuation and should be evaluated accordingly.
Unlike real estate, where metrics like the cost to own and rent play crucial roles in predicting growth, software development companies require a more nuanced approach. Identifying the key metrics that influence growth within a particular field is essential. For example, a rideshare company might closely monitor metrics such as the percentage of the driving-age population that owns a car and the overall satisfaction with public transportation. These metrics reflect the dynamics of the industry and can serve as indicators of the company's potential for growth.
Once the relevant metrics impacting growth have been identified, it is crucial to analyze their historical behavior over the past few years. This analysis provides a baseline understanding of the market's dynamics and sheds light on whether the current economic landscape supports the company's growth trajectory. By studying these metrics' trends and patterns, one can gain valuable insights into the market conditions and anticipate potential challenges or opportunities for the software development company.
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In the simplest terms, DevOps is a culture that brings together developers and operations/support staff. This can mean cooperating, bridging the gap, or even full integration. That’s in contrast to traditional IT set-ups that keep the two completely separate. Promoters of the DevOps support approach argue that it can cut costs, reduce risks, and make an IT operation more responsive.
Some of the more heated debates over DevOps stem from differing definitions of the term and associated concepts. You’ll occasionally see “DevOps” used to refer to a specific development operations team or department that exists alongside a traditional IT department. It’s up to every company to define their own structure and departments, but this situation isn’t the one that DevOps supporters are talking about.
DevOps as a concept is a counter to the traditional IT support philosophy. That’s where an organization has a dedicated development team responsible for producing software, systems, and solutions. A separate IT business operations team is responsible for keeping things running: managing networks, fixing bugs, maintaining hardware, and dealing with any software problems.
In contrast, DevOps brings these two together. How this works administratively isn’t as important as the principle that development and operations work closely together for best results, and apply the best practices of continuous integration and continuous delivery (ci cd).
Most commonly, traditional IT setups involve department or teams based on a particular activity, be that software development, configuration management, testing, implementation, support or maintenance.
DevOps allows for a merged department that brings together the people who possess these various skills; the communed team is now united by a specific project such as developing an application.
May interest you: DevOps as a Service.
The traditional set-up is more likely to have a new application go through a lengthy development process, passing through different departments in sequence. It’s designed to finish with a “complete” release that’s as near to perfect as possible.
DevOps is more suited to a faster, more agile development process with more frequent releases. The logic is that although bug fixes or feature improvements may be needed more often, DevOps teams can cope with incident management more quickly. Indeed, there’s more scope for holding back a new feature to test it fully, without delaying the entire project.
Opinov8 is a Top Software Development Company, accordingly to Clutch.
The way departments think and operate under different set-ups is something of a subjective point. DevOps supporters criticize traditional IT operations as being too driven by a desire to minimize the risk of failure and too defined by a culture where individual staff or teams concentrate solely on achieving their specific siloed tasks.
In contrast, the argument goes that the DevOps approach accepts that failures will happen and that it’s best if they happen early and on a smaller scale, so the damage is limited, and the fixes are more viable. DevOps can also mean people performing different tasks will pay more attention to the overall success of a project rather than only caring about their specific responsibilities.
Companies that adopt DevOps principles report an average of 45% higher customer satisfaction, 43% higher employee productivity, 41% improvement on defect rates, and 38% less IT-related costs. To keep your understanding of DevOps relevant, stay updated with the latest trends and statistics related to DevOps support.
Microsoft Azure is a powerful cloud computing platform that offers a broad range of services to businesses worldwide. Its flexibility, scalability, and security make it a popular choice for businesses of all sizes. However, implementing and managing Azure can be challenging, and that's where Azure Partner, Opinov8, comes in.
Azure partners are certified and trained by Microsoft to provide Azure solutions and services to businesses. These partners offer various services, including Azure deployment, consultation, management, and optimization, making it easier for businesses to leverage Azure's full potential. The Azure partner ecosystem includes Azure Expert MSPs, Azure Advisors, Azure Consulting Partners, Azure Resellers, and Microsoft Cloud Solution Providers (CSPs).
Might interest you: Opinov8 is a top Azure Partner and advisor according to Clutch.
Keep reading: 5 Things every project manager should know about cloud migration.
Opinov8 is an Azure Consulting Partner and Advisor that specializes in delivering Azure solutions to businesses. We have a team of certified experts who are proficient in designing and implementing Azure solutions that cater to a business's unique requirements. Opinov8's Azure services include Azure migration, deployment, management, and optimization. Opinov8 helps businesses leverage Azure's capabilities and functionalities to increase efficiency, reduce costs, and enhance their overall business performance. With Opinov8's expertise in Azure, businesses can trust that their Azure journey will be smooth and successful.
Speak to one of our Azure experts and discuss your project requirements and challenges. Our experts can help you identify the right Azure solutions that best meet your needs and provide you with a tailored plan to help you get started with Azure. Contact us today to set up a free consultation.
In today's ever-evolving business landscape, companies need to stay ahead of the game and remain competitive in their respective markets. One way to achieve this is through outsourcing Information Technology (IT) services that involve hiring third-party IT service providers to handle various functions, allowing businesses to focus on their core competencies.
IT services can be outsourced in a variety of ways:
Overall, outsourcing IT, services can provide numerous benefits to businesses. It can reduce costs, improve efficiency, and allow businesses to focus on their core competencies. Outsourced IT support services with Opinov8 also ensure that businesses have access to the latest technology and IT expertise.
Embark on a technology journey with Opinov8, a partner who puts humans first - contact us to choose our human-centered approach!
Opinov8 is a leading IT outsourcing company that specializes in project-based software development services. Our focus is on providing comprehensive business solutions, and we are committed to delivering exceptional outcomes to our clients throughout the full project life-cycle.
At Opinov8, we understand that project management can be a daunting task. Therefore, we take responsibility for managing all the risks related to project management on our side. Our team of experts has the skills and expertise to handle all aspects of project management, from planning and implementation to monitoring and control.
We also provide managed IT support services tailored to meet the needs of modern businesses. Our services are backed by Service Level Agreements (SLAs) that ensure we remain fully accountable for the quality and reliability of the IT solutions we provide. We believe that technological innovation is the key to success in today's dynamic business landscape. As a result, we strive to be a technology innovation partner for our clients, engaging with them at any stage in their product engineering and software development pipeline.
Are you looking to unlock the potential of the ultimate cloud computing platform? With AWS Cloud Solutions, your business can experience reliable, secure, and flexible services that can take your operations to the next level. Find out why an AWS Consulting Service is essential and the advantages that Opinov8 can provide - so you can make the most of your cloud computing experience!
At Opinov8, we want to highlight some of the ways AWS can help organizations get the most out of their cloud infrastructure. If your company use AWS Cloud Solutions, you can reap a host of incredible benefits! From cost savings to increased resilience in the face of higher traffic demands in special seasons like Black Friday, to high availability of workloads and secure data storage for your customers.
1. Scalability: Businesses can quickly scale up or down to meet the changing needs of their applications and traffic. Consequently, organizations can easily adjust capacity to meet customer demand, while only paying for the storage that is used.
2. Cost Savings: In addition, AWS provides businesses with a cost-effective way to run their applications. Moreover, by using the cloud, businesses can significantly reduce their capital expenditure on hardware and software.
3. Flexibility: AWS provides businesses with the flexibility to choose the services and infrastructure that best fit their applications. This enables organizations to experiment with different architectures and customize their applications for their specific needs.
4. Reliable Performance: With AWS, businesses can be assured of reliable performance for their applications. AWS’s automated scaling capabilities ensure that businesses can quickly respond to customer demand.
5. Security: AWS provides businesses with secure solutions that allow companies to admin their own workloads and sensitive information through AWS shared responsibility policy.
It may be of interest to you: Best AWS Services for Building a Powerful Cloud Computing Platform.
AWS consulting companies are third-party firms that offer AWS consulting services to businesses. Despite AWS offers a user-friendly platform, many businesses need assistance in using it to its fullest potential. This is where Opinov8, an AWS consulting company, comes in. We will provide you with expertise in AWS architecture, best practices, security, and optimization. AWS consultants such as us will help your business in planning, designing, implementing, and managing your AWS infrastructure or to migrate your current infrastructure to AWS Cloud.
Check out Opinov8's success case: Renault: ERP Solution Migration to AWS Cloud.
Yes, throughout this service we will help your company leverage the full potential of AWS. Opinov8’s AWS cloud consulting services include cloud strategy, cloud migration, cloud security, and cloud optimization. Opinov8 will help businesses identify the right AWS services and solutions that match their business needs and goals.
Opinov8 will be a partner in your cloud journey through AWS consultancy. Our human-centered approach will help your business plan, design, and implement AWS solutions. Moreover, we provide AWS support and management services, ensuring that businesses get the most out of their AWS investment. Additionally, our experienced AWS consultants are available to help with any questions or issues you may have.
Discover the power of cloud computing with Amazon Web Services (AWS) consulting partner Opinov8!
In software development, building your solution correctly is crucial for success. But who ensures this – your project management team or your QA lead? Let’s explore these roles and how each of two skills contribute to your project to make informed decisions and resource optimization.
Understanding the balance between project management and quality assurance is crucial for delivering high-quality, reliable products. This approach, known as QA project management, maintains stakeholder trust, optimizes resources, fosters team collaboration, mitigates risks, and drives continuous improvement and innovation. This knowledge leads to successful project outcomes and positions your organization as a leader in the competitive technology landscape.
Quality assurance (QA) in project management aims to produce a high-quality product. The project management team defines the project scope, sets schedules, and oversees the process. The QA lead tests the product, identifies bugs, and ensures it meets the required standards.
The project management team plays a vital role in software development. They facilitate the process and oversee its scope. Their main tasks include:
The QA lead ensures the product's quality. They check various aspects of the development process to ensure thorough testing. Their main tasks include:
We think you might be interested in this: What is Quality Assurance (QA)? - Opinov8
Quality assurance in project management involves balancing both roles. The project manager oversees the work to completion, while the QA lead verifies it’s done correctly. This balance can lead to conflicts, especially when QA finds issues that expand the project's scope. However, both roles working together is ideal.
To integrate quality assurance in project management successfully, consider these strategies:
In a DevOps team, the real winner between project management and the QA lead is the product. Agile teams and IT operations work together, breaking down silos and encouraging transparency. Automation tools speed up development and QA testing. By making the project accountable to the entire team, developers can ensure the product is feature-complete, bug-free, and ready for market.
We're here to help! Fill out our form, and our team of experts will be in touch to discuss your needs and find the perfect match for your project. With our skilled professionals on your side, you can rest assured that your development process will be optimized for success.
When it comes to generating a new project, service, product, or feature, you need to know that in today’s world, a good idea and execution aren’t enough. Your idea needs to rest on a solid foundation and is desirable for users, technically feasible, and commercially viable to help companies reduce any problems that might be occurring down the road.
Almost any design cycle starts with a discovery phase, which is instrumental in setting the project off in the right direction. The UX discovery phase is a key factor in every project that involves product development.
This is a critical part of Opinov8’s UX/UI design services that helps us to provide a flawless user experience. In this article, we will share key details about the UX discovery phase and feature ideation during our development of an advanced electric scooter rental app for City Ride.
The key concept idea was to create an app for renting electric scooters, but with the additional condition that the app should be useful, interactive, and enjoyable. We decided to begin with a Discovery stage to fulfill an outstanding user experience and ideate a functionality to make the target audience users switch to our application.
To develop the optimal scooter rental app, our team first conducted market research and competitor analysis to determine this niche market’s general trends and features. Most apps in this space are focused exclusively on rental and payment tasks. None of the competitive apps offered additional features or innovations. This omission provided a golden opportunity for City Ride’s app to stand out functionally from the rest of the market by introducing advanced features while maintaining the app’s usefulness and simplicity. Another key theme was to encourage tourists to rent scooters. Cycling tourism is already well established, enabling renters to visit tourist attractions or become better acquainted with a city along their selected routes. Although still in the developmental stage, electric scooter tourism is growing.
After studying the market in greater detail, our team concluded that the tourism concept offered enough advantages to succeed. Every big city has notable sights, but it often takes a lot of time to travel between them. Taxis are not affordable for everyone, and bus tours operate on set schedules and can be crowded. Electric scooter rentals provide a perfect solution, empowering independent tourism by offering speed, freedom, and accessibility.
Keep reading: What is User Experience and why is it important
To develop this concept, we conducted user interviews to discover how potential customers use similar apps in real life. During the focus group interviews, we uncovered key pain points and brainstormed potential solutions to develop a unique set of functionalities that would enable the app to meet all the basic rental requirements as well as enhance the renter’s user experience.
“We must understand for whom we were creating this product to make it as relevant as possible to the audience’s needs and not create unnecessary difficulties for them.” — Olga Shepelenko, UX/UI designer.
Based on our interviews, we found that when using a rental application, many users switch away from the rental app to their phone’s map app for navigation purposes. We proposed embedding a navigator in the City Ride rental app that would guide users without this inconvenience. When a user selects a destination on the app’s map, the app determines the best route. The user can place the phone in a holder attached to the steering wheel. This novel feature enables users to follow their route on the app’s map.
But we did not stop there. We added an option to choose an audio sightseeing tour on the route, taking into consideration both distance and planned time. We also included a section with bonuses and promotional codes to enhance client retention and loyalty. Users can collect points for specific achievements, such as the number of kilometers traveled, reporting a malfunction, or recommending the application to friends.
“When working with functionality, it is important to clarify that we have a list of necessary functions that are inherent in all applications in this niche, without which the application could not fulfill its main goal, as well as a list of recommended functions that could improve and improve our application.” — Yuliya Guseva UX Designer.
We created a concept that would correspond to the conditions in which the user would access it. To deal with this task, we decided to use a light theme with contrasting colors. This decision is justified by the fact that when using the application outdoors in sunlight, the visibility of the screen can be significantly reduced, and due to the light background and the contrast of the elements, the user would not have problems with the visibility of the interface.
One of our innovations in the interface of the electric scooter rental application is the screen during the trip in 2 modes. One of them displays the user's position on the map and his movement. And the second mode is presented as a real-time trip, where the person can check the route by following the image and the guiding arrows on the screen. These solutions are, at the same time, quite perceptible and allow the user to explore different possibilities.
When designing the app, we included both essential rental and payment functionality and killer features to distinguish it from competitors in the electric scooter rental market. Our UX research identified weaknesses in competing applications, and we analyzed user experience to identify functional problems and opportunities to add novel features. Our solution makes it possible to attract new users to the application — both locals using scooters for daily transportation as well as tourists and other visitors. With this in mind, City Ride would stand out from the competition and be in high demand. We also ensured that the proposed ideas would be easy to implement, enhancing further development and speeding up time to market.
May interest you: City Ride | Nominated to UX Design Awards
Have you ever wondered how it is so easy to navigate between some websites while with others, it's challenging even to identify the provided action items? Just think about your experience with Amazon, Apple, or Google products. What makes these websites or products stand out?
The answer to all these questions is better User Experience (UX) Design. What they did was change the way we interact with these products, making them easy to use. Such first-rate companies invest millions of dollars in the user experience of their products, contributing to sales and revenue growth.
Most of us have heard about user experience, but some are still confused about what it is. The good news is that there's never been a better time to learn about it. In this article, you will learn what UX Design is and how to create a good UX strategy to make our digital products stand out.
User Experience (UX) refers to a person's overall experience when interacting with a digital product, such as a website, app, or software. UX design involves creating user-centered designs that meet the needs and goals of the users while also considering the technical and business requirements of the product. It encompasses all user interaction aspects, including visual design, ease of use, accessibility, functionality, and user satisfaction.
UX for websites and apps is critical to the overall design and development process. It can significantly impact the user's experience and overall satisfaction with the product having an incidence in metrics such as NPS (Net Promoter Score).
UX strategy is an integral part of product design. It involves defining and guiding the overall vision and approach to UX design within an organization through the following steps:
You can engage an expert vendor if your company seeks UX expertise to design from scratch or assess an existing digital product. Opinov8 specializes in designing user interfaces and user experiences for various products and has UX consultants to help organizations improve their product experiences by providing expert advice and recommendations.
Contact an Opinov8 Customer Experience & UX/UI expert to develop new ideas for your business together.
Creating products that convert, engage, and receive rave reviews in the digital world is no easy feat. That's why User Experience (UX) and User Interface (UI) design have become the holy grail of digital success, bolstering your Net Promoter Score (NPS) and driving actual results. And if you're ready to take your UX/UI game to the next level, buckle up! We've got the top ten best practices that will take you from "meh" to magnificent in no time.
In today's highly competitive digital landscape, companies that invest in good UX design can differentiate themselves from their competitors and increase user base and engagement. And the least but not least – a thought-through UX design can help reduce development costs by identifying usability issues early in the design process, which can prevent costly rework later on.
Overall, these ten best UX practices are important because they help to create a positive user experience, which is crucial for the success of any product or service. By incorporating these practices into the design process, you can create a product or service that is easy to use, engaging, and meets the needs of your users, leading to increased user satisfaction, engagement, and, ultimately, business success.
At Opinov8, we will help your company to incorporate these practices into the design and development process, aiming that your company create products that are user-friendly, accessible, and provide a positive experience for the end-user. Ready to talk, or do you need help with a project? Contact our UX Experts.
In today's rapidly evolving digital world, software usability plays a crucial role in the success of businesses. Software has become the backbone of many organizations, from websites to mobile apps. In this article, one of our QA will explain what quality assurance is and its importance during the Software Developing Process.
Given the business criticality of software, it's vital that the developed software is protected from vulnerabilities, performs predictably and meets the needs of the end users. This is where QA and testing come into play.
Quality assurance is critical in software development because it ensures that the software product meets the end-users expectations and functions as intended. Quality assurance helps identify software defects and bugs early in the development cycle. That saves time and resources by catching issues before they become more complex and costly to fix.
A proper QA testing approach also ensures that the software meets the quality standards set by the organization and industry regulations. It helps to ensure that the software is reliable, secure, and performs well. This ultimately leads to customer satisfaction and increased business value.
Software testing and quality assurance are two important software development life cycle aspects. While they are related, they serve different purposes.
Software testing is evaluating a software application or system to identify defects or errors that could affect its functionality or performance. It involves executing the software to find bugs and verify that it meets the specified requirements. Testing can be done manually or through automated tools.
Quality assurance, on the other hand, is the process of ensuring that a software product or system meets the required quality standards and customer expectations. It involves creating and implementing processes and procedures to ensure that the software is developed and delivered according to the desired level of quality. This includes verifying that the software meets the required functional and non-functional requirements, as well as assessing its usability, reliability, and performance.
What is Quality assurance in software testing? It involves using a systematic and structured approach to testing software products. This involves establishing quality standards for creating test plans and test cases, executing tests, and reporting defects. The quality assurance process helps to ensure that the software is of high quality.
There are several key approaches to software quality assurance, including:
It's a must for specialized QA companies or software companies with QA teams involved to be responsible for ensuring that the software products developed by a company meet the quality standards.
Commonly companies specializing in QA services provide these types of software testing services:
At Opinov8, we follow the global gold testing standard and have three types of automated tests: unit, integration, and end-to-end tests. The test approach is agreed upon with the client and specifies the required test coverage and depth for each type of test. The team plans for the necessary scope of automated tests during the planning stage. Unit tests check the program units, integration tests check the integration between different system modules or components, and end-to-end tests perform an extended validation of the user flows. Smoke tests act as a quality gate during active development, and regression tests check all system components and features. The tests are automatically triggered with each code commit or system build, and some tests are triggered manually within increment finalization activities.
Opinov8 recommends using both Manual and Automated testing together to increase system reliability and avoid potential pitfalls. Projects benefit from the synergy of these two approaches as automated testing requires low time to perform, while manual testing allows a human mind to check cases that might be missed by an automated testing program.
At Opinov8, we are experts in Software Quality Assurance Testing Services. If you need help with your projects, please contact us.
Scalable product development requires more than smart code or a sleek design. It’s about aligning your roadmap, architecture, and user experience with long-term growth goals. From choosing the right tech stack to integrating measurement points from day one, this article walks through the key decisions that set your product up for scale and investment.
When you start conceptualizing your product, it is good to let the imagination run wild. Still, it is essential to add a bit of pragmatism to your product roadmap - you can’t be everything to everybody.
Assuming that you have a good grasp of the competitive landscape, you need to identify exactly what makes your product or service unique and tie that into an understanding of your expected revenue streams e.g. having fancy and comprehensive admin functionality is not directly providing tangible benefits and value to users (in a b2c offering). Needless to say, the features and functions you plan to build in your product must support the prioritization of the revenue streams.
Once you have your product roadmap, you have indeed challenged yourself by applying some limitations. You should take an additional view of the product ecosystem to which your product belongs. That will provide a better perspective and validation of the roadmap but will also provide input for 2 further important considerations:
Use the product roadmap to inform the direction of your product architecture and infrastructure.
From the product roadmap, it is possible to elicit what I tend to call ‘Architectural drivers’ - the critical part here is that you do not want to ‘over-dimension’ or ‘under-dimension’ your technical approach.
CX or customer experience is vital. Switching costs from SaaS products are not very high, so you will have to be on your toes with regards to providing a superior user experience… and don’t forget that the user experience starts from your website/in the app store and extends all the way to problems/issues resolution (customer service).
Translating your roadmap into wireframes is usually the way to go about it. Suppose you have the opportunity to create a clickable prototype to show early investors, FFF friends, family & fools. In that case, you can get some potentially great feedback and increase investor interest.
Nothing particularly new here, right?
However, one element that often gets overlooked in scalable product development is tangible measurement of how your product is being used — where users drop off, which features are ignored, and what causes friction. Too often, teams default to “we’ll apply Google Analytics” and move on. But simply knowing your number of conversions or purchases isn’t enough.
We’d argue that event mapping — the structured analysis based on your wireframes and designs— is just as critical as a solid technical architecture. In the context of scalable product development, it’s essential to set up key measurement points from the start and include them in your “definition of done.” You should also define early on which tools will support your data collection and analysis strategy. This often-overlooked step is foundational to both user experience and growth.
For the sake of happier users, efficiency of future product development, and to satisfy investor questions, you must be very well versed in the fancy abbreviations of the general product metrics of SaaS products. You must be able to back that up with real data.
Always consider CAPEX vs. OPEX; what does that mean in reality?
Only invest CAPEX in areas that are a differentiator for your product, i.e., IP. Don’t spend cash on reinventing the wheel e.g., custom build components and services that can be consumed natively from a commercial cloud (as there obviously is no product edge in that) - on the contrary, the edge is to fully understand what’s available and use that in our architecture (increase speed of getting to market, reduce CAPEX and only pay when you have usage of your product (OPEX)
And regarding reducing OPEX - make sure that you fully understand the various startup accelerator packages that the commercial clouds offer.
Don’t go for exotic frameworks or languages unless it is absolutely necessary for building your product.
Point: When you need to scale and increase your engineering team, you would want to be able to dive into a larger pool of specialists for the following reasons 1) cost, 2) reduce keyman dependencies, and typically it will also reduce the cost of ongoing maintenance.
Scalable product development doesn’t end at launch. Once your product is live, ongoing operations become critical — both for stability and long-term growth. This includes performance monitoring, uptime management, release pipelines, and user support infrastructure.
As you scale, regulatory compliance (e.g., GDPR, HIPAA) becomes a requirement, not an option. Proper documentation of your architecture, data flows, and APIs isn’t just for audits — it enables faster onboarding of engineers, smoother integrations, and clearer stakeholder communication.
Leverage cloud-native services not just for speed-to-market, but also for built-in resilience, security, and observability. Managed services reduce operational burden and allow your team to focus on building product differentiators instead of maintaining commodity infrastructure.
If you apply the principles above, your approach to scalable product development will empower you to:
Let’s talk about how we can help you build smart, scale fast, and stay investment-ready.
Most business leaders agree that big data has become crucial to developing a viable business model in today’s marketplace. But big data alone isn’t enough. Being able to effectively analyze and act on a massive store of data is almost more important than collecting it in the first place. Data scientists are the ones who sort through that data, discovering actionable trends and insights that can take your business strategies to the next level.
Making big data actionable is a complex process that involves communication between data scientists (the ones who analyze the data) and engineers (the ones tasked with putting their ideas and insights into production). This divide is where problems commonly arise. Getting the most value out of your data means making sure data scientists and engineers can communicate and work together effectively. With that in mind, here are a few tips to ensure a smoother, more coordinated development process.
A shared language and terminology are essential for strong communication and collaboration. Cross-training is one of the simplest methods for achieving that shared language and breaking down the divide between data scientists and engineers. For data scientists, this might mean learning the basics of production languages. For engineers, it might mean studying the fundamentals of data analysis.
Assigning employees a partner from the other division can help facilitate the learning process, while also helping both departments recognize what changes they could make to help the other team and make their work easier. For instance, engineers might communicate to data scientists that a more organized code would expedite the production process.
As we’ve seen, communication is key. One of the best ways to facilitate communication is by emphasizing the importance of clean code. For data scientists, analyzing big data can sometimes be a messy, experimental process, resulting in preliminary code that can be difficult to understand for engineers. If engineers begin to work from the substandard code, their model software will likely run into problems, including instability and overall efficiency.
Implementing standardization protocols that consider security parameters, data access patterns, and other factors can keep both sides of the development team happy and expedite the development process. If your data scientists can consistently produce code that performs well within your engineers’ development framework without sacrificing any of the functionality the data scientists need to continue their work, the entire process will run more smoothly.
Once you’ve established a system for consistently producing clean code, it’s time to productize it. Think of this approach as a way of segmenting features (or independent variables in the data), curating them, and storing them in a centralized location. The intent is better information sharing. Data scientists can retrieve these features when they’re working on a project, and they can be confident the features are reliable and tested. This approach also produces analysis benefits. A features store is essentially a data management layer that uses machine-learning algorithms to analyze raw data and filter it into easily recognizable features.
Once your teams speak the same language and your data is structured for reuse, the next step is to operationalize that collaboration through shared pipelines. Instead of treating data science and engineering as two separate workflows, align them under a unified CI/CD (Continuous Integration / Continuous Deployment) framework tailored for machine learning and analytics.
This means:
With shared pipelines in place, data scientists can push models that engineers can immediately implement — without custom translation work. It also makes experimentation safer and faster: if something breaks, you know where, why, and how to fix it.
Automation doesn't just save time. It builds trust. And in a data-driven environment, trust between teams is what turns prototypes into products.
Big data refers to large and complex data sets that traditional data processing tools cannot handle efficiently. It's important because it enables businesses to uncover patterns, trends, and insights that support better decision-making and innovation.
Data scientists focus on analyzing big data to uncover insights, while engineers are responsible for building and maintaining the systems that make those insights usable in production environments.
Without strong collaboration, insights generated by data scientists may never make it into production, and engineers may lack the context to build optimal solutions. Bridging this gap ensures that big data becomes actionable.
Tools like Databricks, MLflow, Airflow, and feature store platforms such as Feast support collaboration by standardizing workflows, sharing artifacts, and maintaining traceability across teams.
Choosing the right DevOps Tools is a bit more complicated than just looking at a list of top-rated services. That’s because different tools are better suited for specific jobs. Additionally, tools alone don’t make DevOps work, but the right tools can make it much easier to be successful. The following tips cover what you need to know when evaluating DevOps tools for your business.
Before you start looking at DevOps tools, it helps to establish a collaboration strategy for development, QA, and operations. Understanding how these groups work together and how they address problems gives you insight into what your tools need to do. The collaboration strategy won’t point you to specific tools to use but will clarify what you need those tools to do for you. Before making a decision, you’ll need to examine how well tools work with an organization of your size and how much of a learning curve those tools require. Always keep in mind that a tool you don’t need is not the right DevOps tool.
The right tool depends on your organization, but you’ll need to find communication and planning tools for your team. These tools include collaboration, workload management, instant messaging, ticketing, and documentation. Some tools handle more than one of the previously listed jobs. With many of these tools, you’ll need to use them to see if they work for your teams, so take advantage of free trials. Your organization might find tools like Slack, Jira, Confluence, Trello, InMotion, Dovetail, and others useful.
DevOps tools aim to eliminate as much of the human element from the workload as possible, which means the right DevOps tools should accomplish this goal. You should look into monitoring tools to track problems and look for potential improvements. Automated testing speeds up the development process. Acceptance testing prevents bad code from reaching production. Automation tools help with Continuous Integration, making it easier to properly test code several times a day as it’s submitted from early bug detection.
When your teams aren’t sharing resources, they may end up working against each other instead of with each other. The tools you use should enable development and operations teams to hand off tasks to each other in a loop. The goal is to avoid using multiple tools for the same purpose across different teams. It’s also important to identify how well a tool works within your DevOps workflow. A tool that is excellent in one workplace workflow may be counterintuitive for another business.
Avoid tools that only work in production because they step outside of the feedback loop. Feedback is an essential part of the DevOps process. These tools disrupt this valuable source of information.
Ultimately, it’s up to your organization to determine the right DevOps tools to use. However, a strong understanding of how your organization collaborates, what tools should be doing for your organization, and how to identify which tools work best will point you to the right decisions.
Ultimately, it’s up to your organization to determine the right DevOps tools to use. But success starts with understanding your workflows, collaboration patterns, and automation needs. Choose tools that make work easier, not more complex. And remember: the best tool is the one your team will actually use — consistently and confidently.
Let our DevOps experts help you build the right toolkit for your business.
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The microservice architectural style creates a wealth of opportunities for development teams to evolve their DevOps pipelines. Microservices make it practical to break apart larger applications so work pipelines focus on smaller, independently operating services instead of the entire application at once.
DevOps teams can work in broken-out repositories for each microservice instead of needing to stick with the larger workflow. In short, microservice updates work independently of the entire application.
Whether you’re building a new application or retrofitting an existing application, your DevOps teams will need to either design with several microservices in mind from the ground up or break up a monolithic application into smaller, independent segments. Structure microservices so they function independently of each other. The microservices communicate with each other to exchange information but don’t overlap in actual work. Containerize each microservice and avoid using shared libraries you will be modifying.
The microservice architectural style untangles services from the entire application, which substantially simplifies the process for relationship mapping. Relationship mapping updates stay contained within the microservice instead of affecting the relationships between microservices. When you’re working with containerized code, you won’t need to worry about an update changing how a different microservice works or breaking the larger application.
Microservices make it easier to manage relevant code, which means it’s easier to keep track of what already exists. Improved code management can be a significant boost to your building processes because it’s easier to build reusable code when you’re only concerned with the immediate microservice instead of the entire application. When you’re working with less code, it's much easier to keep track of what’s already done, so you can avoid repeating code. Reusable, nonrepeated code is faster to update, which will help streamline the pipeline.
Microservices can significantly evolve the deployment part of a DevOps pipeline. DevOps teams can stay focused on updates within the microservice instead of being distracted by those concerning the application as a whole. This makes them easier to keep track of and eliminates the need to wait on other parts of the application to update. Fixes and enhancements come faster with microservices. It’s much easier to manage versions with microservices because each microservice has independent versioning. This model is easier to manage and requires less work if you need to revert to an older version because you only need to revert the microservice.
Adopting microservices goes hand-in-hand with evolving DevOps pipelines. One of the biggest mistakes you can make when working with microservices is to stick with the same old pipelines. Take advantage of the new opportunities for a better workflow with microservices.
Why cloud server security should be your top priority? In a world where data breaches and ransomware attacks are more sophisticated than ever, cloud server security is essential. Private cloud environments, often used by enterprises for regulatory or performance reasons, offer greater control than public clouds. But with that control comes responsibility.
So how do you stay ahead of evolving threats? By using the right tools to detect, assess, and close security gaps before they’re exploited.
Here are the top tools for identifying vulnerabilities in your private cloud, categorized by risk type:
Top tool: IBM Security Guardium
Data is the crown jewel — and attackers know it. Misconfigured databases, outdated software, or exposed endpoints can open the door to serious breaches.
IBM Security Guardium scans your cloud databases, data lakes, and file systems for vulnerabilities, unpatched software, and misconfigurations. It automatically generates compliance-ready reports and alerts you to suspicious access patterns before they escalate.
Alternatives to consider:
Top tool: Okta Identity Cloud
Most breaches involve compromised credentials. That’s why secure identity management is foundational for any cloud server security strategy.
Okta provides centralized identity and access management, complete with single sign-on (SSO), adaptive multi-factor authentication (MFA), and role-based permissions. This ensures only the right people access sensitive systems, with zero trust baked in.
Also effective:
Top tool: CrowdStrike Falcon
Private clouds aren’t immune to ransomware or advanced persistent threats (APTs). Malware can move laterally across virtual machines and containers, often undetected.
CrowdStrike Falcon uses AI-powered threat detection to spot anomalies in real time. It integrates with endpoints, email servers, and cloud workloads to block malicious files, scripts, and behaviors — before damage is done.
Other top players:
Cloud server security is no longer about firewalls and passwords. Attack surfaces have expanded, and hybrid work environments mean more entry points than ever. Organizations using private clouds must continuously monitor and test their infrastructure — because static defenses are outdated the moment they’re deployed.
✅ Regular vulnerability scanning
✅ Identity and access management with MFA
✅ Malware detection and response tools
✅ Compliance auditing and reporting
✅ Real-time alerts for unusual activity
Most breaches in private cloud environments don’t happen overnight. They start small — an overlooked patch, a misconfigured access rule, an unmonitored virtual machine. That’s why proactive monitoring is one of the most underrated yet powerful elements of effective cloud server security.
Proactive security turns your private cloud into a moving target — making it harder for malicious actors to find an entry point and increasing your confidence in operational resilience.
Because private clouds often handle sensitive data and custom configurations, they require tailored security tools to identify and mitigate risks like malware, misconfigurations, and unauthorized access.
Ideally, continuous scanning is best. At minimum, perform weekly automated scans and manual audits after every major update or configuration change.
Some tools are designed for both, but private cloud environments may require more customization. Always check if a tool supports your architecture and compliance needs.
Working with a combination of private and public cloud services in a hybrid cloud solution presents a wide range of challenges with keeping data safe and making sure all of your applications can communicate efficiently. The path to building a versatile, secure hybrid cloud infrastructure involves developing a standardized, tracked, and validated configuration.
The different parts of your hybrid cloud need to allow applications and databases to communicate with each other. Individual cloud providers keep configuration data under control, but this is a bit more of a challenge with a hybrid cloud because data doesn’t live inside a singular enclosed service. How you organize configuration information makes a difference in both performance and maintainability.
The closer you can keep your organization’s hybrid cloud configuration to a standardized model, the easier it will be to manage it. A standardized or normalized system is easier to maintain than one built under several layers of ad hoc adjustments.
Avoid changing how you manage computing resources between different cloud and application providers. The configuration should handle cloud services like Azure and AWS the same way. Write your code and configuration data as portable as possible.
Expert tip:
Use declarative infrastructure tools like Terraform or Pulumi to build reusable modules for all environments.
Machine learning and performance testing tools are invaluable assets you can have on your side when developing a standardization strategy. These tools can identify configuration patterns and which configurations offer the best performance.
Keeping detailed logs of all configuration changes is part of high-performing hybrid cloud infrastructure. Like with an application’s code, maintain a version history log of the configuration. You need to know who changed what, when they changed it, and why they changed it.
Although standardization is the ultimate goal, it isn’t always realistic to expect the same code and configuration to work in all instances. It’s necessary to track deviations between applications.
Tracking changes is easier said than done when working with multiple teams. You’ll need to account for teams updating different parts of the configuration at the same time. Implementing a role-based access control system helps keep things orderly.
You’ll also want to run configuration data through a validation process. Run configuration changes through QA like you would with application code updates. Your organization will need to establish how strict it will be with enforcing standards because more freedom to deviate from the standards requires more validation. Additionally, validation checks will scale as more people can access the configuration.
As part of the validation process, you’ll want to maintain snapshots across versions. Machine learning can also help out in this part of the process.
The concept of data governance complicates the hybrid cloud infrastructure because it imposes specific rules and requirements for different regions. Local laws may require that your organization stores information in specific places or entities.
Your organization is legally required to follow data governance requirements, but don’t let those requirements break your other good habits. The best practice is to build with portability in mind so applications can connect to different databases in a similar, standardized manner.
Building a versatile hybrid cloud infrastructure is an ongoing process. It doesn’t end with a single configuration. It requires continuous development and enforcement of standardization, tracking, validation, and data governance practices.
To manage hybrid environments effectively, real-time visibility into performance, cost, and security posture is non-negotiable.
Recommended stack:
Expert tip:
Standardize tagging across cloud resources to improve traceability and analytics across all environments.
Automation is key to maintaining agility in hybrid architectures. Use:
Advanced organizations also leverage AI to detect configuration drift, recommend changes, and optimize resource allocation over time.
A hybrid cloud environment expands the attack surface.
Checklist for cloud security:
Security must be baked into your hybrid cloud strategy — not bolted on.
Standardize infrastructure code and configuration
✔️Track and log every change across teams
✔️ Validate infrastructure like software code
✔️ Stay compliant with evolving data governance
✔️ Implement centralized observability and security
✔️ Leverage automation and AI to scale reliably
Building a versatile hybrid cloud infrastructure is not a one-time project. It’s a continuous process of standardization, validation, tracking, and adaptation. As AI search and cloud-native technologies evolve, so too must your infrastructure practices.
Opinov8 is a fast-growing company, and we, Opino8rs, are proud of it! We are always thinking about our future, our growth, and our customers — how could we provide the best service? Obviously, to achieve these goals, we must build strong and scalable processes. Requirements testing is one of them.
Today, we are going to talk with Vadym, Opinov8 QA Practice Lead. Vadym will tell us about one of the processes implemented in Opinov8 — requirements testing. This is a basic and mandatory process for all our projects.
As you know, requirements are the foundation for any development project. Projects start with documentation (requirements) and end with it. One of the most vital processes for us is requirements testing. In Opinov8 (for a project with SDLC based on Scrum), we created a few rules when implemented this approach:
We need to test the requirements exactly before these requirements are added to the sprint backlog. On the other hand, it is not necessary to perform these actions at a very early stage because there is a possibility that these requirements will lose their relevance.
As a result, we can significantly reduce the cost of the project (or sprint, since we are talking about testing requirements as a sprint activity).
Our Business Analysts use a requirements approach based on the INVEST mnemonics described here. However, from the QA practice side, when we do Requirements Testing, we also stick to the following aspects:
All statements must be correct, truthful, and make sense. Testing a system for incorrect requirements is a waste of time, money, and effort. How correct is your requirement? Is this really what is required of the system?
Can be traced back to the business problem or business need that triggers it. Does this really cover the needs of the business?
The requirement should contain all the information needed by the developers and everyone else who uses it to do their job. The requirement must include all the details necessary to express the needs of the users.
Requirements must not conflict with other requirements. Are all buttons or error messages in the same style?
There must be a way to check if the implementation meets the requirements. Can the requirements be verified? How do you do this, and what data and tools do you need?
Is it possible to develop the described functions, we do not have blockers and restrictions?
Anyone who reads the requirement must come to a common interpretation.
Is the requirement unambiguously defined so that it can be unambiguously referred to?
Are all scenarios covered in the requirements?
Requirements testing is a top priority to help you get your developing project to a really good level. Timely use of these activities can save the development team time and money.
Be curious and driven to explore new horizons and technology areas with us. Let's innov8 together!
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Until recently, if your company needed to hire an outside contractor for a project, that contractor would likely work onsite rather than as part of a remote team. The digital revolution, however, has changed that, thanks to the fact that communication and sharing documents is now simple. Today, it is just as common to hire teams who are offsite — and sometimes even overseas — for a project. When it comes to your own business’ project delivery method, keep the following considerations in mind when deciding between an onsite or offshore contractor.
Reduced cost is a big advantage of hiring an offshore team. Your company can lower expenses, such as for real estate, supplies, equipment and utilities with an offshore contractor. With an onsite team, you’ll need to find extra space in the office for the new team members and potentially cover expenses related to equipment and supplies. Not only that but if you opt for an offshore project delivery method then you may be able to take advantage of overseas talent at a cost that is lower than what is available to you locally.
Both onsite and offshore project delivery models have their respective advantages and disadvantages when it comes to communication. With an onsite team, you benefit from face-to-face communication, which makes scheduling last-minute meetings and communicating about minor issues much easier. You may also find that face-to-face communication gives you more control over the direction of the project. However, offshore communication is more seamless today thanks to technology. Scheduling online meetings and sending important documents is usually straightforward, especially if you have a contractor that prioritizes communication and transparency.
For many businesses, the most important consideration when hiring a contractor is finding the very best one. Whether the best contractor for your project is an onsite or offshore one is impossible to guarantee. It’s possible that a contractor that is able to send its team to your premises will also be the one best able to deliver the very best expertise. However, when your business is open to the possibility of an offshore remote team, you have significantly more options to choose from. When you’re willing to look nationally or even globally for a contractor, then you can be more selective about who you hire — and potentially have an easier time finding a contractor that is the very best in the business.
Significant benefits exist for both onsite and offshore project delivery methods. The ultimate decision of which one is best for you will depend on your project’s goals, timeline, budget and whether you prefer to work with a remote team.
Platform development requires careful consideration of various factors to ensure success. There's a lot for a business to consider when deciding between developing a product or a platform. In short, a product is a consumable or usable piece of software you sell or offer, while a platform is a system that enables a product to work or communicate with another product. Products can stand alone or exist on platforms. The following five considerations can help your business decide which path is correct for your organization at the time, as well as the idealized implementation of what you're creating.
Creating a platform before creating a product carries a lot more risk than building the product first. In the platform vs product debate, it's important to note that products tend to be less work than platforms. However, platforms can't be converted into products. Since products tend to be less work than platforms, it's much better to have a product that doesn't work over a platform that doesn't work.
The scope of the development process is important: it is much harder to build a platform first. Your organization might be looking to build a platform in the future, but currently only has the resources to develop a product. Once having a successful product in the marketplace generating revenue, a business can work on turning it into a platform.
How you approach a problem or solution in development can vary depending on the context of the program's value. In this case, a platform creates its value through interactions while a product creates value by selling a feature. In platform development, the focus is on building a system that facilitates seamless interactions and integrations. Some ideas work very well as a product or platform, but not both.
Some great products have very long lifespans; however, not every product does. It's okay if a product is only intended for temporary or short-term use. However, any platform designed without long-term sustainability is problematic. Platforms should be deeply integrated into the business or customer infrastructure. A platform needs to stick around for a long time, preferably indefinitely. For example, a computer is a product built to last the user for several years. However, the user will use many programs, or products, throughout the lifespan of the device.
With a platform, you're developing software that needs to be easily updated. It needs to be flexible so you can make changes and improvements quickly and easily over time. While it's a better development practice to design software that's easy to maintain, it is less important with a product that doesn't need to be constantly updated. Your organization should lean towards a product if it doesn't have the capacity to provide a constant update stream.
The decision to develop a platform vs product highly depends on the resources available to your organization and the desired business case. When making the choice, go with the option that makes the most sense from a business standpoint.
Our team of tech experts is here to help you succeed! Whether you need assistance with software development, product design, or platform optimization, we've got you covered.
Check out our collection of related articles! We've curated a selection of informative, insightful pieces that can help you explore various topics such as benefits of the AWS Cloud, Quality Assurance or User Experience.
Amazon Web Services (AWS services) is the world’s leading cloud computing platform. Trusted by millions of customers ranging from NASA to Netflix, AWS makes it simple for companies to build powerful solutions using tried-and-true technology.
Offering nearly 200 different services that power a broad range of cloud solutions, AWS provides many different flexible, reliable, and purpose-built functionalities to help businesses deliver the ideal solution for any customer.
Here are five of the best AWS services to build a powerful cloud computing solution:
The reliable, secure, and scalable computing infrastructure of Amazon Elastic Cloud Compute (EC2) serves as the backbone of many cloud computing solutions. Through its wide range of highly customizable virtual machines, Amazon EC2 eliminates the need to invest in physical computing equipment and provides flexible, on-demand computing power that enables organizations to build powerful applications in the cloud.
As a powerful, scalable, and easy-to-use database solution, the Amazon Relational Database Service (RDS) delivers a user-friendly database platform that incorporates a high degree of administrative automation. Delivering a wide variety of highly optimized cloud databases, dedicated Amazon RDS instances are powered by some of the world’s most popular database engines, including Amazon Aurora, MySQL, and PostgreSQL.
Built to store and retrieve any amount of data from anywhere, the Amazon Simple Storage Service (S3) provides highly secure, flexible, and redundant file storage. Relied upon to power cloud-native applications, disaster recovery solutions, and big data analytics, Amazon S3 is engineered for high durability and is the trusted data storage solution for millions of applications.
To deploy information across the internet with speed, scale, and security, the Amazon CloudFront fast content delivery network (CDN) is an ideal choice to deliver data, applications, and video with low latency. Trusted by such brands as Canon, Condé Nast, and Hulu, CloudFront’s asset caching, streaming media options, and seamless security make it simple to efficiently distribute dynamic content and software across the globe.
Delivering a full virtual networking environment, Amazon Virtual Private Cloud (VPC) provides simple, secure, and highly customizable network security. From secure web hosting to corporate VPN (virtual private network) access, Amazon VPC delivers an isolated IT infrastructure with highly customizable networking configurations.
Taken together, Amazon EC2, RDS, S3, CloudFront, and VPC provide some of the most powerful cloud infrastructure capabilities for leading brands around the world. With more than 175 services available in global data centers, AWS makes it possible for any organization to build the cloud computing platform that best meets its needs.
AWS offers nearly 200 services, but the most widely used include Amazon EC2, Amazon RDS, Amazon S3, Amazon CloudFront, and Amazon VPC.
Amazon EC2 is the go-to service for scalable computing power, offering customizable virtual machines on demand.
Amazon RDS automates common administrative tasks like backups, patching, and scaling, while supporting multiple popular database engines.
Amazon S3 is used for secure, redundant storage of any data type, often powering cloud apps, backups, and big data analytics.
Amazon CloudFront delivers content with low latency and high transfer speeds, making it ideal for streaming, websites, and dynamic applications.
Amazon VPC allows you to launch AWS resources in a logically isolated virtual network, enhancing control over security and traffic flow.
AWS vs Azure — the cloud question startups and enterprises alike are asking, especially when every dollar counts. With VC funding tightening and operational efficiency in the spotlight, the platform you build on can either stretch your runway or shrink it.
While both Amazon Web Services (AWS) and Microsoft Azure offer similar capabilities in compute, storage, and networking, budget-conscious builds demand a sharper lens. It’s not just about pricing. It’s about picking the cloud platform that aligns with your architecture, scale, compliance, and ecosystem — without bleeding your budget.
Let’s break it down.
When building lean, it’s tempting to chase what looks cheapest. But short-term savings can mean long-term pain.
Tip: Start by identifying your most critical workloads before evaluating plans.
Need to keep part of your infrastructure on-prem for compliance? Azure’s hybrid legacy gives it an edge.
Tip: If your solution touches sensitive data or regulated industries, evaluate hybrid architecture needs upfront.
Your team’s existing workflows matter.
Tip: Map your current stack and identify where integrations could save development hours.
AWS vs Azure isn't about picking a winner — it’s about choosing the platform that matches your build priorities. For some, that’s granular control and open tools. For others, it's seamless integration with Microsoft products and enterprise governance.
AWS offers more granular billing and flexibility, which can benefit startups with unpredictable workloads. Azure may offer discounts if you already use Microsoft products.
Azure leads in hybrid cloud support due to its enterprise software roots, while AWS has recently improved but still lags slightly in this area.
Yes, migrating between platforms can involve high data transfer, reconfiguration, and compliance validation costs. Choosing right from the start saves money.
AWS offers more configurable GPU options and pay-as-you-go flexibility, making it a strong choice for budget-conscious ML development.
AWS is generally better for open-source, offering stronger Linux and GitHub integrations. Azure is stronger if your team uses Microsoft products.
Yes, many organizations adopt a multi-cloud approach to avoid vendor lock-in, leverage the strengths of both platforms, and improve resilience. However, it requires careful planning to manage costs, integration, and security across environments.
Innovation tools for teams are essential — because innovation doesn’t happen overnight. Breakthrough concepts and technologies are often the results of painstaking work carried out after a countless number of empty coffee cups, late work sessions and sleepless nights.
Becoming a driver of innovation also isn’t as easy as flipping a switch. Organizations that successfully embrace the creative process to produce new, exciting ideas and products must empower their employees to be as efficient and effective as possible.
To take your organization to the next level, here are some tools that can help your team drive innovation faster.
No innovation tool will work if your team doesn’t feel safe to speak up. Creativity is messy — it comes with trial, error, and risk. That’s why the foundation of any innovation effort is a culture where people feel heard and secure.
Tools that help:
These systems create transparency, trust, and the freedom to experiment.
Ideas grow faster when they’re shared easily. Whether you're brainstorming or iterating on a prototype, frictionless communication is critical.
Top collaboration tools:
Modern innovation demands fast, cross-functional feedback. These tools remove silos and boost team agility.
Micromanagement kills innovation. Teams move faster when they’re trusted to own their work, take risks, and explore new ideas without constant approval loops.
But autonomy doesn’t mean chaos. It means structured freedom.
How to support it:
When your team has space to think independently and systems to stay aligned, innovation flows naturally.
You don’t need to reinvent the wheel to innovate — but you do need the right setup. With the right innovation tools for teams, you’ll empower creativity, speed up execution, and deliver real results.
Looking to build a more innovative digital team?
Let’s talk about the tools and frameworks that can get you there.
Some of the top innovation tools for teams include Slack for communication, Miro for brainstorming, Notion for documentation, and Asana or ClickUp for project tracking. These tools support faster collaboration, transparency, and idea execution.
Innovation tools streamline communication, reduce friction in collaboration, and give teams the autonomy to explore ideas without micromanagement. They create a structured environment where creativity can thrive.
While all innovation tools enable collaboration, not all collaboration tools are built for innovation. Innovation tools are designed to support ideation, experimentation, and iteration — not just communication.
Yes, especially if your team is scaling or working across departments. The right tools can reduce time-to-market, improve employee engagement, and drive measurable outcomes from creative efforts.
In the IT world, many experts today are tossing around the terms “DevOps” and “CloudOps” as if they are synonymous. Nothing could be further from the truth. Both models share similar attributes; however, users, partners, clients and teams need to get on the same page when it comes to understanding the differences and the varying factors in choosing what works best for your organization.
Development and Operations (DevOps) is a system that optimizes the best parts of IT and development teams. It focuses on continuous advancement of processes and tools and empowers team members to collaborate more effectively across the collective group.
One of the DevOps principles is automation – delivering agile, repeatable processes to maximize the power of the final product or solution. It fuels an evolving cascade of operational improvement.
Cloud Operations (CloudOps) is simply a different way of “doing” DevOps. Rather than relying on any one set of on-site network server assets, CloudOps leverages powerful cloud-computing tools such as AWS, GCP and Azure, including multi cloud environments. CloudOps is basically the next logical extension of DevOps and both focus on continuous operations, a process that has emerged from DevOps practices into the world of Cloud Ops.
It may be of interest to you: What are the key benefits of using AWS cloud?
Since companies have several choices among cloud-based platforms, CloudOps providers are motivated to compete on quality and price. Rather than worrying about maintaining an expensive network architecture on site, teams can optimize resource contracting with a cloud service to provide all networking/server needs including maintenance, monitoring and expansion of capacity – all at a more affordable price point to manage infrastructure and applications.
CloudOps providers offer virtually unlimited storage and processing power that can be expanded or contracted based on your company’s needs to easily manage cloud resources.
Thanks to the enhanced expandability and scalability of cloud computing, DevOps processes can leverage cloud tech to reduce latency issues and errors. Cloud infrastructure is not specific to any one location (stateless) and manage cloud implies the facility to move from one server to another to avoid processing problems.
It’s both/and, not either/or: CloudOps is simply a different way of doing DevOps. It complements the process rather than replacing it. Empowering your DevOps system with the powerful tools CloudOps offers can bring together two robust paradigms into one – the product-success/customer focus of DevOps with the speed and scalability of CloudOps. DevOps targets process improvement. CloudOps seeks to enhance technology and services.
Platform agnosticism: When marrying DevOps functionality with CloudOps, it’s the “job” of the cloud platform to abstract the foundational infrastructure and flexibly adapt to virtually any type of system. Cloud systems - be it AWS, Azure or Google – must follow the DevOps infrastructure rather than lead the process, letting each organization to manage its cloud governance.
Every organization is different: Yes, that seems obvious. However, many organizations sometimes assume they need to invest in CloudOps Solution X or Y because it’s “the next Big Thing.” Often they fail to ask fundamental questions about their specific needs. Are there reasons to avoid CloudOps? Perhaps your company has unique security concerns that require internal server structure. Are there legal issues that may inhibit deployment of a specific cloud platform? Most importantly, are there underlying factors that could result in CloudOps hurting rather than helping your DevOps system? Generally, the answer is “no” since there is such a diverse array of CloudOps solutions available. However, it’s a question worth consideration.
It’s all about the product: No matter how “gee-whiz/cool” CloudOps may be; no matter how awesome the scalable, affordable tools may be, your organization must always keep your collective eye on the prize. Focus on the product. Focus on what steps must be taken to always optimize the release and support for the customer. There’s an old saying: “Keep the main thing the main thing.” CloudOps can certainly augment your DevOps system, but never lose sight of the product forest for the cloud-app trees.
Do your homework: Major CloudOps providers employ major sales forces. That means, their sales reps are experts at – well, getting that sale. That also means, your team may be susceptible to a suave, fast-talking salesperson who promises the pinnacle of CloudOps excellence in their product but fails to deliver after-sale.
Take a look at this: Cloud architecture review
You can defend against an overly aggressive sales process by arming your team with data – tech specs, reviews, recommendations and an almost-encyclopedic knowledge of competing CloudOps providers. “Knowledge is power” may be an old cliché. It’s an old cliché because it’s a fundamental truth. Cloud governance is on your hands.
Going forward, the word “CloudOps” will likely disappear as a useful term in the future as more organizations integrate these tools into their DevOps and its presence will be a foregone assumption built into every system. Until then, it’s vital to educate your team, your clients and yourself to gain "visibility into cloud".
Contact us today to schedule a consultation with our experts! Discover how you can optimize IT services in the cloud and achieve greater agility.
When embarking on the development of a minimum viable product (MVP), it is essential to make informed decisions about what features to include and, equally important, what to exclude. The success of an MVP lies in its ability to deliver a streamlined version of the product that captures the interest and feedback of early adopters. In this article, we explore three key elements that should be avoided when creating an MVP, ensuring its effectiveness in gathering insights and aligning with your overall product strategy.
One of the primary challenges in developing an MVP is determining which features are truly essential. In the early stages, it is common for stakeholders to view all suggested features as "must-haves." To overcome this bias, it is crucial to engage in ruthless prioritization. Begin by crafting a one-line description of your product's core functionality and unique selling point. This description serves as a guiding principle to assess whether a feature directly aligns with the MVP's purpose. If a feature does not contribute directly to the core description, it is best to exclude it from the MVP. By focusing on the must-have features, you create a more refined and attractive MVP that resonates with early adopters.
May interest you: 5 Questions to evaluate a software development company.
An MVP is an opportunity to validate your product's concept and value proposition. However, it is not the appropriate stage to test the fundamental viability of underlying technologies. Before releasing your MVP, it is vital to conduct thorough testing and ensure the reliability and functionality of the foundational technology. Neglecting this crucial step can result in a negative user experience and compromise the integrity of your MVP. By addressing any technical uncertainties prior to the MVP stage, you can confidently test the concept's market appeal and user acceptance.
Always remember that though an MVP is a stage in a process for you, it’s an end destination for early adopters who buy it. That means you shouldn’t include a feature that plugs a gap to make the MVP “ready” when you know you’ll remove or replace that feature in the final product.
A good way to think of this is a common analogy. If your final product is a car, an MVP of simply four wheels and a chassis is useless: It’s a logical developmental stage, but it’s not a functional product.
Some uses of this analogy suggest a bicycle would be a suitable MVP because it’s a more primitive form of transport. However, a bike not only misses fundamental features of a car (goes long distances without stopping; carries an entire family), but it has features that won’t be in the finished car (works without fuel; works on cycling paths.)
The software equivalent is straightforward: Don’t include anything in an MVP that fundamentally changes what your intended product is or what it does. Doing so completely undermines the benefits of getting feedback from early adopters.
Keep reading: IT Outsourcing: Everything you need to know.
Designing a high-quality user interface and engineering a positive user experience are two of the most important components to consider in software development. Intuitive interfaces that allow users to carry out their desired tasks with ease and speed can enable them to get the most out of an application.
Of course, not all users are alike, which poses a challenge for developers seeking to reach the broadest audience possible. That’s especially true for Generation Z, the first cohort of digital natives who were not raised in a pre-Internet world. To members of Gen Z, applications and devices aren’t new tools to help them get things done: they’re common aspects of everyday life.
Here’s how to approach UX/UI designs that are mindful of GenZ.
Unlike previous generations, Gen Z wasn’t raised in an age of dial-up where slow speeds were once tolerable because they were, at the time, cutting edge. Instead, high-speed wireless internet and mobile devices were the normal ways to access information online.
As such, Gen Z doesn’t waste time worrying about the distinction between “desktop” and “mobile” — they just want it to work. UI/UX for applications and websites must take these considerations in mind and strive for the fast, mobile-optimized experiences Gen Z has come to expect as table stakes.
The digital natives of Gen Z already know how to navigate tech platforms with ease and sophistication. There’s no need to hold their hand through lengthy tutorials, help pages, or other basic introductions to how a website or application works. They already get it.
Intuitive UI/UX design for Gen Z should be built with discoverability and explorability in mind. Gen Z is happy to poke around apps and websites to discover which functions and features are living where, and don’t need the entire experience spelled out for them.
Gen Z knows how to stay connected through different types of content across a variety of platforms. Whether it’s via an emoji in a text or a video posted to Snapchat, Gen Z users are eager to highlight new purchases, unique experiences, and high-quality content.
Apps and websites should be designed to capture Gen Z’s attention and make it easy to share experiences with others. Even if an app isn’t inherently “social,” UI/UX designers should incorporate features that allow Gen Z users to share information and stay connected to their peers.
Software is everywhere, and everything is connected. Whether system or application software, there are lines of code — probably trillions of lines of code — right at this moment that are affecting your life (your home, car, job, school, hospital, city, streetlights … you name it). Anywhere and everywhere, above and below the ground and up in the air, software runs in the background for all of us.
Testing all of that software is not only obviously mandatory, but it’s a time- and cost-gobbler. So, as humans do, we’ve developed more and more efficient and effective processes to develop and test software throughout its engineering life cycle. One of these strategies is TaaS (Testing as a Service).
TaaS was developed as a process around 2009 by a Danish software and services company, and once IBM adopted it, it became widely applied. A cloud-based outsourcing model where a service provider (rather than in-house teams) performs testing activities by simulating client-specified real-world testing environments, TaaS has proven demonstrably to effect significant benefits over traditional testing, particularly in cost-savings.
TaaS can be used throughout the life cycle of software testing, for functional testing (GUI Testing, integration testing (SIT), regression testing and UAT testing); performance and benchmark testing (multiple users access the application simultaneously to determine its threshold point); load and stress testing (where ‘real-world’ / virtual users place an app under load and stress test); and security testing (executing vulnerability scans on apps and sites).
Performing these tests in-house (requiring hundreds of hours of manual QA or real-user monitoring) has become inefficient and costly. It’s a time drain on teams and network systems. The high security for this in-house is internal stress, and the complexity and variability of software makes each approach functionally a new project. TaaS solves a lot of this to achieve scaling, minimize costs and improve the processes and services, while lessening risk and achieving higher ROI.
1. TaaS is a highly scalable model. It’s a cloud-based delivery model, so companies do not need to dedicate internal servers to the testing activities.
2. Pay according to what you use only. You can segment testing processes and re-test, avoiding the need to unnecessarily run parts of a test.
3. Licensing benefits. Systems, tools, hardware, and app licenses for tests are all cloud-managed.
4. Standardization. By improving efficiency and quality, cost savings are built-in to improved results (often a 10-20% cost decrease).
5. Data centralization. The efficiency of having all information and projects stored centrally is time- and cost-saving and allows easy remote access.
6. Learning curve. Processes for testing are always advancing. This stress on internal teams is avoided using an outsourcing model.
The challenge to invent new and ever more complex software is enough for any internal team. Testing is a necessity throughout the life cycle. Choose wisely how your company best makes use of the intelligence of your engineers. If the testing piece can be made efficient in a cloud-based environment through the use of standard tools and processes, then internal teams can devote their energy and creativity to their core competency: inventing new and exciting software.
User Interface and User Experience design trends face the uphill task of keeping online content optimized alongside changes in technology. What makes it difficult is that the changes must also retain functionality for older devices. UI and UX designers need to keep pace with technology evolution to insure their audiences have a good experience with their content. The following five trends in UI and UX are set to shape development and design in the near future.
Designers and developers often find themselves working with computers, tablets, and smartphones that offer them better performance than most users who consume their content. If a website or application looks beautiful, but takes forever to load and offers sluggish performance on less powerful devices, the audience is going to stop using the product. Since UX is heavily invested in "how" a website works, UX designers are looking into concepts like load times, time to interactivity, and first paint in simulated environments. A site may run well on an iPhone XS on a fiber WiFi connection, but an iPhone 7 user on a slower 4G connection may have a sub-par experience.
UX and UI are poised to work with content to better tell a story. This isn't just for articles or actual stories, but also involves marketing campaigns and sales pitches. Some of the ways UX is assisting in better telling stories is to use imagery and white space to break up content for easier consumption. UI is working with functional animations and using other visual effects to work alongside content.
UX and UI designers have previously ignored the time between actions and page loads as empty space that exists because of technical limitations. However, with the development of new CSS capabilities, single-page web applications, and PWAs, that's really not the case anymore. UI designers can make a more visually appealing experience out of what was previously considered unusable space. As far as UX is concerned, load transitions improve the user experience by letting the user know the next page/option is loading with a visual cue.
More recently released desktop monitors, laptop screens, and mobile device displays are more likely to feature better contrast ratios and more visible space, which make vibrant colors more appealing. On older, lower contrast displays, vibrant colors didn't make as much of a strong visual impression, so UI designers would ignore them and stick with established web-safe colors. The newer screens let UI designers create better artistic experiences.
Device agnostic design is the next evolution in responsive design. Responsive design emerged to let web developers create a single site for every device class instead of having to build three sites to house exactly the same content. However, responsive design trends used to assume that users on a smaller display would be using touchscreen controls and users on larger displays would be using mouse-based controls. With touchscreen laptops like the Microsoft Surface and tablets with "stylus" input like the iPad Pro, designers can no longer make that assumption. All screen sizes need to be designed with touch capabilities in mind and interactions like mouseover/hover won't be used for necessary interactions. It's essential for website and application designers to keep up with UI and UX trends to find ways to improve their content. Both UI and UX are developing on-going practices that constantly offer ways to improve content presentation.
Innovation as a Service gives you the creativity you’d find in an agile, hungry start-up but without drawbacks such as financial risk or scale constraints. Whether you’re bringing outside consultants into your organization or outsourcing innovation to labs, hackspaces, and focus groups, look for these five key characteristics in a service offering.
You may be familiar with the “wisdom of crowds” theory best demonstrated by the example of a crowd at a county fair trying to guess the weight of a cow or the number of jelly beans in a jar. It’s rare any individual will get the exact answer, but the average of all guesses is often remarkably accurate.
It’s not just the number game that makes this work: that the crowd brings a range of backgrounds and characteristics and thus different approaches and insights to the task, which get combined in the average guess. If you asked 100 architects or 100 elementary school kids to each guess, there’s a good shot almost everyone in the group would be wrong in the same direction. With Innovation as a Service, you don’t just want the largest possible group of skilled people working on your ideas — you want a service that harnesses people of diverse backgrounds, experiences, and specialisms to get as broad a range of inputs as possible.
To effectively develop ideas for your organization, whether internally or externally, an innovative provider will often need access and insight to your operations. That means you need absolute trust that they won’t compromise your company’s confidentiality.
Ideas and innovations tend to be a bit fuzzy, but a truly innovative provider should make things clear. Look for one who is willing and able to explain their work and results in a way you can understand. Those who hide behind waffle and unnecessary jargon may be trying to exaggerate their abilities and results.
Make sure you’re clear about who owns the intellectual property for any ideas, processes or inventions created. This isn’t just about whether you are able to use the innovations without further financial or legal obligations. It’s also about where anyone involved in the process gets rights that could later be used in competition to you.
A good provider will have a clearly defined process to make sure their work serves your needs. This can be as simple as a two-step process: coming up with ideas then selecting, refining, and focusing those ideas to solve your problems. The process could be more complex and detailed. Either way, be certain that their particular take on Innovation as a Service achieves your actionable goals.
Doing many Proof of Concepts, or Rapid Prototyping to achieve decision making in digital products and then “graduating “ these to MVP is a fast way to disrupt your own organization. Allowing for the process to flow and ideation being the initiator, this will allow for Innovation to take hold in your business.
Craig Wilson
Co-Founder, Chief Commercial Officer
Great minds might think alike, but they don’t necessarily innovate together. Whether your business is in the early stages of onboarding individuals or is an established company seeking to join forces with another company, connecting with the right partner can help you best achieve your innovation goals. The key principle in finding a strong partner for innovation is this: You and your company’s strengths are likely to be different from the partners with whom you will innovate best.
Think about it. If you both have the exact same strengths and weaknesses, you are more likely to conjure projects that you could have produced all by yourself. When your partner possesses strengths that you do not, you can bridge your combined knowledge, leading to new and better ways of solving customer pain points. Here’s how to find potential partners who are best suited to you and your company:
Understand that having different strengths is not the same as being polar opposites with your partner. The best partner for your company shares your company’s core values. If one partner sees only technical knowledge as valuable, and the other partner only views comprehension of human behavior as valuable, partners may be disrespectful toward each other’s differences in intelligence. Partners who similarly weight respect, work ethic, communication, and collaboration tend to be good partners in general.
Once you believe you have a compatible partner, you can decide whether the partner will facilitate innovation. Typically, when strong candidates for innovation come into a partnership with you, the expertise between you becomes more liminal. One partner might be proficient in video streaming, where the other partner’s strength is audio streaming. Together, they can build bigger, faster, better streaming platforms. This proficiency at the intersection of different fields (e.g. AI and economics, art and software development, etc.) often creates an environment where elements of those seemingly separate fields fit together to create new services or products. It breeds innovation.
It’s common for people to go out of their way to add potential partners to their network. If you’re looking for a partner with a very specific skillset, seek out and network with companies, researchers, conferences, and social media groups that specialize in that field. When pursuing a more general variety of abilities, announcing to members of your network—through email, social media posts, or regularly scheduled meetings—that you’re looking for a partner with particular proficiencies is helpful in finding a strong partner. Regardless of the method you use, always be sure to clearly articulate the capabilities that the partner should have so that your time is well spent evaluating only the most qualified candidates.
Craig Wilson
Co-Founder, Chief Commercial Officer
A "Most Valuable Player" (MVP) on the football field is a player who has proven their worth and the team considers them the ultimate prize during a season. Similarly, in the realm of product development, an Minimun Viable Product (MVP) aims to achieve a similar status but requires time to evolve and reach its full potential.
To gain a comprehensive understanding of the concept of a minimum viable product (MVP), it is important to delve into the realms of Agile, Lean, and Lean Startup methodologies.
In the world of Information Technology (IT), Agile is a project development approach that emphasizes prioritizing high-value functions and conducting ongoing tests with users throughout the development process. By other side, Lean is a manufacturing methodology focused on minimizing waste. Originally pioneered in Japan by W. Edwards Deming for Toyota, Lean is a manufacturing methodology focused on minimizing waste. It involves designing a simple system, measuring all aspects of the process, and continuously improving efficiency. This iterative approach allows for the early identification and correction of errors.
Lean Startup combines the principles of Agile and Lean, integrating customer development into the mix. While Agile tests the product against users, Lean Startup takes it a step further by testing the product against the market. The goal of Agile is to avoid creating a product that won't work, while Lean Startup aims to prevent the development of a product that people don't actually need.
Keep reading: Minimum Viable Product (MVP): 3 Things to avoid.
Frank Robinson coined and defined the concept of the MVP, or Minimum Viable Product, and Eric Ries popularized it in his book "The Lean Startup." It emphasizes the importance of learning in new product development. The underlying premise of the MVP is to create an actual product that can be offered to customers, allowing their real behavior with the product or service to be observed. This approach proves to be much more reliable than simply asking people what they would do in hypothetical scenarios.
However, there are common misconceptions and misunderstandings surrounding MVPs that can lead to trouble. It's essential to address these misconceptions.
An MVP should accomplish three main things: have just enough features; satisfy early customers; and enable feedback for future development. But, confusion and miss-projections about MVPs can get you into trouble. The five big misconceptions are:
May interest you: Product vs. Platform development: 5 things to consider.
Developing a minimum product allows gauging its demand. If the initial response is not promising and the idea struggles, it becomes an opportunity for change and pivoting. The MVP concept empowers entrepreneurs to make informed decisions and navigate product development.
At Opinov8, we prioritize a human approach and provide tailored solutions to meet the unique needs of your company. Our goal is to establish a personal connection with our clients and deliver customized tech solutions that address their specific requirements.
RegTech (regulatory technology) is still a new field within the financial services industry, but some already have said it’s the new FinTech. It utilizes information technology “to provide nimble, configurable, easy to integrate, reliable, secure and cost effective regulatory solutions,” according to Deloitte.
U.S. SEC Commissioner Michael Piwowar adds that RegTech “also refers to the use of technology by regulated entities to streamline their compliance efforts and reduce legal and regulatory costs,” such as using blockchain and AI tools to “allow the easy and secure transfer of critical regulatory data to multiple federal agencies.”
Growth in the number of RegTech firms shows that the past seven years have been robust in this new arena. The industry has seen a 23 percent increase in the number of RegTech firms in regulatory compliance and risk management alone. Other areas where segments showed a jump in growth of these firms include financial crime (13 percent), identity management (7 percent) and compliance support (6 percent).
Various other factors exist in the financial industry that should drive RegTech startups to continue a trajectory momentum:
1. Nasdaq acquired Sybenetix, which makes a behavioral analytics app that tracks people in financial institutions. It monitors unusual or suspicious behavior that could be a sign of misconduct. Banks, hedge funds and regulators can also use this technology.
2. AlgoDynamix is a “risk analytics company focusing on financially disruptive events” using algorithms to predict price movements in advance. “Its customers include investment banks and asset managers such as hedge funds, CTAs and family offices. The deep data algorithms underpinning the AlgoDynamix analytics engine use primary data sources (the world’s global financial exchanges) and proprietary unsupervised machine learning technology. The analytics engine detects market anomalies and anticipates directional price movements hours or days in advance of the event. Unlike competitive solutions, Alodynamix’s real-time analysis does not rely on historical data or previous disruptive events.”
3. Suade helps banks run analyses of their own practices, but also then adjust them in compliance with changing regulatory requirements, with a focus on flexibility. With the UK leaving the EU in 2019, concern is high about the future of financial regulation as a result, which could involve multiple regulatory swings. Startups like Suade provide technology that is adaptable in a quickly changing environment. “RegTech is all about minimizing uncertainty,” Suade co-founder Diana Paredes says.
Why do we struggle so much to get things done in the way that best sorts out the task, solves the problem, creates the new widget or accomplishes the goal? We can blame it on something outside ourselves, something monolithic like: Society made me not do it. It’s true. Society today is a lot about consumption, and access to all that consuming is not only on every corner, but constantly at our fingertips through our phones. Maybe we’re not as agile at envisioning something new as we once were 75 or 100 years ago, planning how to bring it about, then building it to completion. Now, we just make a call, and a little drone delivers a fully conceived and developed product within hours to our door. Society made us not do it because we engineered things to free us from the struggles of our forebearers. So … oops? That’s okay. We’re mighty smart, and we have developed methodologies to help retrain us to be creators, accomplishers and finishers so that we can just do it.
The most popular of these methodologies is Agile, an approach to software development through self-organizing and cross-functional collaboration. In 2007, another monolithic entity, Oracle, acquired Agile Software Corporation and rebranded it as a product lifecycle management (PLM) software. At its roots, Agile is an adaptable process that drives people and software projects to the most desirable solutions. (Its manifesto is enviably simplistic.)
Unlike project management (PM) processes that tend to be more defined and linear, Agile is an empirical and iterative process where teams use data gathered, working in iteration, to build on what’s been done, introducing or changing elements during the process, developing in phases, to create the best end result.
Agile is considered an incremental model, so instead of just one final delivery phase, it divides the project up into increments, each with its own set of stages (requirements, design, development, testing and delivery) before moving on to the next phase. This iterative strategy begins with developing basic features, then, once tested, moves on to the next phase, adding more and more advanced features incrementally with each iteration.
This process strategy is designed to deliver the highest priority items first, satisfying client needs and confidence. Critically, feedback is gathered from stakeholders at each iteration so new ideas can be folded into the next iteration, building a product that has the brightest hope for solving challenges, being the most innovative and ground-breaking.
The bigger question is, will Agile solve all your software development problems? The answer is not entirely. It’s your job to first assess if there is a block somewhere, a juggernaut that needs work first. For example.
Have you established an alignment between your business objectives and IT, where values, resources (human and budget) and goals are all in sync? Without this, you can incorporate a process like Agile, but you won’t fully engage its potential.
Is your staff fully supported in their adaptation to the Agile process? That might require bringing new talent on board or training or realigning the great talent you already have on your team.
Are your teams empowered, and are they allowed to self-select, self-drive and self-commit to the work being done? This embodies and produces responsibility and accountability.
Perfectly calculated steps, flexible and seamless collaboration, highest value requirements. It's Agile. It's innovation.Agile is not merely PM — it will force you to consider your entire business culture, and what needs to change about that so your team can be fully empowered for productivity and innovation.
Robotic process automation (RPA) tools make it easy for organizations to automate typical workflows. Analyzing a user’s movements through an application’s graphical user interface, RPA tools can faithfully recreate the same workflow that an active employee would be required to carry out on their own. The result is a solution that can automate a wide range of tasks and services, freeing up employees from performing repetitive work and enabling them to focus on more valuable tasks.
While most RPA tools are designed for similar purposes, the market for RPA tools is ripe with different options. Determining the best choice for an organization is often a matter of considering the number of applications the RPA toolset supports, the ease of deployment and its ease of use.
Here are some popular RPA tools that your team should be using:
UiPath is one of the leading RPA tools for automating desktop and web-based applications. It is available as a comprehensive enterprise platform and as a free community edition. Users can design, deploy and control fully automated workforces that are able to completely mimic a human’s behavior. Built with a simple drag-and-drop interface for easy usability, UiPath offers one of the lowest barriers of entry to building a robotic workforce.
Blue Prism’s enterprise software robots are an intelligent, scalable, adaptive and secure set of RPA tools. Built upon the Microsoft .NET Framework, Blue Prism can automate applications across a wide variety of platforms, including mainframes, terminal emulators and web services. Blue Prism provides incredible amounts of visibility and control over digital workers, allowing organizations to get real-time feedback into the performance of any specific workflow or task.
Also available in free and enterprise editions, WorkFusion offers everything from self-service RPA tools to a comprehensive AI-powered enterprise automation platform. RPA Express, WorkFusion’s free platform, enables teams to deploy robotic workers without the need to code. For enterprise users, WorkFusion’s Enterprise Smart Process Automation (SPA) uses AI to digitize operations with the help of machine learning bots and smart analytics.
Trusted by financial institutions, healthcare organizations and logistics operations, Automation Everywhere makes it possible to deploy anywhere from 10 to 5,000 automated bots. Built with business users in mind, Automation Everywhere offers tools to create, deploy, and monitor bots across the enterprise that are backed up with detailed analytics. Automation Anywhere’s solutions also offer advanced security and audit tools for compliance with regulations like the European Union’s GDPR.
Rapid adaptability has become increasingly crucial for companies in order to maintain their relevance and competitiveness in the ever-evolving business landscape of today. Across various industries, those organizations that have successfully adopted Agile methods have reported significant improvements in their overall performance. However, despite its proven benefits, a successful Agile adoption remains a challenge for many organizations, often resulting in demotivation and hesitation towards adopting it.
When companies embark on the journey of adopting Agile, they commonly encounter five main challenges that hinder their progress and effectiveness.
The first challenge is the lack of buy-in from management. Executives and higher-level decision-makers may find themselves feeling challenged by Agile's iterative development approach. These individuals are accustomed to seeing project plans laid out in detail from start to finish, and the idea of embracing a new, evolutionary framework can be met with resistance.
Solution: Run a pilot project that demonstrates the core tenets of Agile, such as improved speed to market, increased ability to tackle unforeseen challenges, and rapid innovation. This practical demonstration can help ease the process of management buy-in by showcasing the tangible business value that Agile can bring.
May interest you: Product vs. Platform development: 5 things to consider.
The second challenge organizations face is the misalignment of Agile with their existing organizational culture. In many cases, organizational structures do not inherently foster collaboration among cross-functional teams. Moreover, the top-down structure prevalent in such organizations reinforces operational silos, making it difficult for Agile principles to thrive.
Solution: Recognize that Agile is not just a technical framework but also an embodiment of organizational change management. It is necessary to evaluate the corporate culture and create a tailored Agile solution that aligns with the organization's core practices, facilitating a cultural shift that supports Agile principles.
Inadequate resource planning poses another challenge for organizations adopting Agile. Agile methodologies require quick access to necessary resources such as funding, talent, and technology to ensure timely value delivery. Yet, traditional resource planning approaches, rooted in the waterfall model, offer more structure and early visibility into the project.
Solution: Organizations should focus on providing support for Agile adoption by integrating Agile into core management processes such as staffing, procurement, and IT. This not only aids product development but also ingrains Agile into the organization's DNA, making it easier to scale Agile practices effectively.
The fourth challenge is the inexperience of organizations with Agile methodologies. For traditional companies attempting Agile for the first time, the lack of experience presents a catch-22 situation. How does one introduce Agile without any prior knowledge? Even after the team has adopted Agile, they may face numerous roadblocks and struggle to resolve issues efficiently due to their limited experience.
Solution: It is highly recommended to seek the guidance of an Agile coach who has experience in a similar industry or an internal resource who has successfully worked on another Agile team. This coach or internal resource can provide invaluable support in helping the new Agile team implement their Agile strategy effectively. Furthermore, they can continue to work with the team to tackle any challenges that arise throughout the Agile journey.
Keep reading: DevOps vs. Traditional IT Support.
The final challenge organizations encounter during Agile adoption is the preservation of legacy systems. Many organizations find themselves constrained by outdated systems and processes that they are reluctant to abandon. However, the successful adoption of Agile can be hindered by the dogmatic preservation of legacy systems, as Agile primarily focuses on delivering value rather than adhering to cumbersome processes. To overcome this challenge, organizations need to identify the critical dependencies of their Agile teams on legacy systems. They can then introduce technological tools that either eliminate these dependencies or establish effective liaisons between the Agile practices and the legacy systems, ensuring smoother and more accessible data flow.
Agile, at its core, accelerates product delivery by using empowered, self-organizing teams. Nevertheless, missteps made during the transitions can derail the transformational journey and lead to Agile being written off. To avoid such scenarios, organizations should take a measured approach toward Agile. By carefully engineering their Agile adoption, organizations can defy business uncertainty and achieve the best possible outcomes.
Just when you thought it was safe to come back out after the recent ‘Great AI Uprising’ against the humans, now the robots are coming for us again. But it’s okay. They are here to benefit your business with their scalability and adaptability. Even better, they are actually going to save your business time and money, all while boosting productivity and improving accuracy, service levels and agility.
Bandying about discussion related to artificial intelligence (AI) these days is this idea of RPA: Robotic Process Automation. To tamp down any notion of a cyborg-like war against humanity, RPA does not involve physical or mechanical robots. Instead, it is software running on a physical or virtual machine — very much part of any other business process automation, but, in this case, it follows a defined set of instructions. So, for example, RPA can be programmed for first-level customer support executions to run queries and lay in data from one system to another for invoicing, expenses or refunds.
As we’ve experienced with chatbots, robots are capable of imitating most human-computer interactions to conduct error-free tasks speedily and at high volume. Effectively, RPA automates repetitive computer-based tasks and processes that are otherwise slow and expensive for humans to perform, thereby boosting efficiency for businesses and organizations. Also, RPA, like any other form of machine learning, can be trained to make predictive judgments relating to production. It can beneficially, non-intrusively integrate within existing infrastructures without causing disruption to systems already in place.
How can RPA save businesses and organizations time and money? Consider when staff is used, especially for a considerable amount of their work day, for repetitive tasks that require little-to-no decision making. Replacing some of that lost time with RPA software will certainly make better use of the humans in question. They can then devote more time to higher-level processes that do require decision-making skills that software cannot replace. And RPA can free up time your developers spend on automatable tasks (such as scripting). Here are five places to test robotic process automation in your business:
Accounting: RPA is a cost-effective alternative to managing financial processes. It boosts financial data accuracy by 95 percent, makes the transfer of financial data time from invoices and receipts three to four times faster, and provides overall costs savings of up to 80 percent.
Internal Communications: Walmart, AT&T and Walgreens are using RPA for employee matters. CIO of Walmart Clay Johnson says they use “RPA bots to automate pretty much anything from answering employee questions to retrieving useful information from audit documents.”
Administrative Tasks: David Thompson, CIO of American Express Global Business Travel, says they “implement the use of RPA to automate the process for canceling an airline ticket and issuing refunds.” Also, Thompson is “looking to use RPA to facilitate automatic rebooking recommendations.”
IT Services: RPA can run software testing when it involves multiple applications and monotonous work.
eCommerce: COO at Eggplant, Anthony Edwards, uses RPA for processing returns online.
RPA (robotic process automation) tools are great solutions for automating boring, expensive and repetitive workflows. Built to follow a pattern of user interactions, an RPA can free up valuable human resources by allowing software to carry out tedious tasks related to business processes or software testing. In essence, RPA gives an organization the capability to build a virtual workforce that can run around-the-clock, continuously performing tasks without needing to take a coffee break.
Integrating an RPA into a company’s existing set of tools begins by identifying workflows that involve significant amounts of human effort to carry out multiple, repeatable tasks. Whether it’s data entry, report generation or QA testing, these processes should be easily replicated through repetitive sequences. Once the workflow is identified, the RPA tool can be used to build a sequence that allows for the automated completion of the task.
Take the example of customer relationship management (CRM) software. Relied upon throughout the world by businesses and other large organizations, a comprehensive CRM makes it possible to keep track of customer information and interactions. Traditionally, CRM tools have relied on manual data entry that is prone to human error. When linked to a database, an RPA can streamline the data entry process by logging information into the CRM on a user’s behalf, accurately placing information in the correct fields and solving for common human mistakes like typos.
RPA tools can be integrated into any application workflow that follows a pattern that’s able to be re-created. In the arena of software testing, for example, RPA tools can be deployed to execute a series of user interactions to fully vet an application before its release. Even if the application is brand new, the RPA can ensure it’s completely functional while bypassing the steps where human software testers would traditionally carry out the tedious task of checking every possible workflow.
It’s worth noting that an RPA is only as powerful as your applications. If there is a slow, cumbersome piece of proprietary software within a particular workflow, the RPA can still be programmed to follow any number of given tasks, but it won’t be able to speed up the application itself. But the process, of course, can still be run without human interaction.
For organizations seeking to incorporate RPA capabilities, any workflow that’s repeatable across any number of applications can be ready for disruption. As soon as a tedious task requiring the same sequence of monotonous clicks is automated with a robot that’s happy to do the job, companies often wonder how they ever lived without incorporating RPA.
AI-powered DevOps automation is redefining how modern tech teams manage software delivery. By combining artificial intelligence and machine learning with the core principles of DevOps, businesses can finally move beyond reactive workflows toward predictive, autonomous operations.
Since 2009, DevOps has helped break down the silos between development and IT operations. It promised faster releases, continuous improvement, and scalable collaboration. Yet more than a decade later, many teams still struggle with fragmented tooling, data overload, and persistent security risks. AI and ML are here to fix that.
One of the biggest challenges in DevOps today is keeping up with the constant monitoring demands of live systems. As data volumes grow, manual monitoring becomes unrealistic—especially for enterprise-scale applications.
AI thrives in these data-heavy environments. It quickly processes massive datasets, identifies patterns, pinpoints anomalies, and surfaces actionable insights. This allows DevOps teams to focus on resolution, not detection.
Key benefits of integrating AI into DevOps workflows:
In short, AI doesn’t just help DevOps teams keep up—it enables them to stay ahead.
ML gives AI its learning capability—enabling systems to adapt and improve without explicit programming. Instead of relying on static rules, ML algorithms continuously evolve based on the data they receive.
Why this matters for DevOps:
The more ML is embedded into your DevOps stack, the more intelligent—and autonomous—your delivery pipeline becomes.
Implementing AI-powered DevOps automation doesn’t require a complete overhaul of your existing infrastructure. In fact, the most effective approach is often incremental. Here’s how to get started:
1. Identify high-friction areas in your pipeline
Begin by analyzing stages of your CI/CD pipeline where delays, errors, or manual tasks slow down progress. These are prime candidates for intelligent automation.
2. Integrate AI-enhanced monitoring tools
Start with tools that apply AI to log analysis, performance monitoring, or incident response. These tools offer immediate ROI by reducing alert fatigue and speeding up root cause analysis.
3. Introduce ML for predictive insights
Once monitoring is stabilized, apply machine learning models to predict system failures, optimize resource usage, and forecast release impacts.
4. Use AIOps platforms
Consider deploying AIOps solutions that bring together observability, analytics, and automation. These platforms centralize insights across environments and scale AI-powered decision-making.
5. Focus on collaboration and culture
Successful AI-powered DevOps automation is not just about tech—it’s about mindset. Educate your teams, align processes, and promote a culture of trust in AI-assisted workflows.
DevOps alone improves delivery speed. AI-powered DevOps automation takes that speed and adds intelligence, context, and adaptability.
Companies that implement AI and ML into their DevOps strategy are already experiencing:
As the digital landscape becomes more complex, the ability to automate smartly and respond instantly becomes a competitive advantage. DevOps powered by AI and ML is not just a possibility—it’s the path forward.
At Opinov8, we help enterprise teams integrate intelligent automation into their DevOps pipelines. Let’s talk about how AI-powered DevOps automation can give you the speed and resilience your business needs.
RPA tools are becoming increasingly vital in software development, especially in one of the most important — and time-consuming — tasks: software testing. To ensure a product functions properly before being released to the public, developers must carry out several different rounds of test execution, validation and reporting to highlight any areas that need repair or improvement.
Throughout the history of software development, test automation tools have existed to execute common workflows and assist developers in ironing out the kinks of their product. However, these tools have often been cumbersome and expensive, requiring a deep knowledge of coding that makes them difficult to set up. Additionally, many test automation tools necessitate a certain amount of manual testing, turning a seemingly automated process into a task that still requires human intervention.
The introduction of robotic process automation (RPA) tools has revolutionized software testing, making it easier and more efficient than ever before. Built to follow an automated workflow, RPA tools can be set to automatically carry out software testing on a wide scale without the need for human intervention. Using RPA tools helps teams greatly reduce the time spent on boring and repetitive tasks, which can ultimately lead to human error. By following a structured, rules-based workflow, RPA tools can execute automation testing with greater efficiency than human beings, freeing up employees to focus on high-value tasks.
RPA tools typically require no programming skills, making it easy for non-technical users to establish a workflow for a digital worker to follow. When testing a user interface or API, users equipped with RPA tools can simply build a workflow that doesn’t require additional work to carry out the automation. With the help of detailed analytics and reporting, these tools can be analyzed and adjusted to ensure testing is occurring thoroughly and accurately.
RPA are incredibly useful for testing because they can be deployed across a wide range of platforms. Instead of having to find specific automation tools for particular operating systems or devices, RPA tools are often flexible and platform-independent, supporting web-based, desktop, and legacy application testing. Virtual machines through RPA tools also make it possible to scale testing at any time, saving resources while speeding up the testing process.
Many new automation software are beginning to employ artificial intelligence capabilities that can continuously improve upon their workflows. Rather than having to manually adjust specific tasks, smart tools can refine their behavior over time, making testing an automatic process that can be trusted to run without additional supervision. This advancement not only increases efficiency but also ensures a higher level of accuracy and reliability in testing results.
Healthcare organizations manage vast amounts of data on a daily basis. From electronic health records to data analytics, the cloud offers healthcare organizations the chance to store, process and analyze healthcare data with greater accuracy at a lower cost.
Here’s a look at how the migration to cloud solutions continues to transform the healthcare industry:
Digital healthcare solutions make it possible to set up automated workflows in the cloud, freeing up resources across the organization. Automated cloud-based data entry, for instance, can reliably and accurately ensure that patient information is correct and secure. Online appointment scheduling enables patients to manage their healthcare needs without the need for human interaction.
Many cloud-based services don’t require an expensive investment in new hardware and software licensing. Because most cloud tools are easily accessible through a web browser, healthcare organizations can run their desired applications on basic systems that don’t require cutting edge processing power. By being able to run on existing devices or new hardware that doesn’t require all the latest bells and whistles, healthcare organizations can save money on costly new equipment like servers. Following a subscription revenue model, most cloud solutions also offer a fixed recurring cost that’s easy to budget for.
Moving healthcare information into the cloud makes it easier to gain new insights as soon as data is collected. While healthcare data has previously existed in its own siloed existence , cloud solutions make it possible to share information with ease across a wide variety of applications. New and comprehensive data, like health information collected from a wearable device, can further paint a picture of a user’s habits and statistics. The result is patient care that’s easier to monitor, maintain and manage in real time.
Hardware and software in the healthcare industry have traditionally seen a slow upgrade cycle. Because many devices and systems are often relied upon for many daily, critical tasks, installing a new device or improving an existing solution could lead to serious downtime that put patients’ lives at risk.
Cloud solutions have changed this equation by placing web-based technologies at the fingertips of healthcare providers. Through the SaaS model, software can be continuously maintained and updated on the back end without the need for any intervention from the end user. Bug fixes and enhanced capabilities could be pushed out overnight, allowing healthcare providers to take full advantage of new technology the moment it becomes available.
Financial Technology and Regulatory Technology are so closely associated that the two are practically " built in" to each other, but they are not the same. The intersection between FinTech and RegTech necessitates parallel development, which can make blur the line between the two.
FinTech improves and automates financial functionality, while RegTech handles compliance insurance, risk assessment and activity monitoring. RegTech is concerned with all FinTech, but FinTech is not concerned with all RegTech. Understanding how the two are related is important to understand how they are different.
The reason that some people confuse the two stems from the fact that RegTech exists because of FinTech. RegTech actually began as a subgroup of FinTech, but it has grown into something that extends beyond that original scope. FinTech is exclusive to the banking and financial industries, but RegTech is not. However, RegTech exists because it is necessary for holding FinTech accountable. New technology that collects massive amounts of information has created a wide range of new applications for RegTech.
Because RegTech needs to keep up with changes in FinTech to do its job, it makes sense to develop both at the same time. And because RegTech started as an offshoot of FinTech, it makes practical sense for FinTech to incorporate RegTech in the development process. Additionally, both technologies have a vested interest in protecting information.
At the core, the reason the two are not the same is RegTech can be applied to more than just the financial industry. This might seem unusual because RegTech started because of FinTech but grew into something more. The overlap stems from both regulators and businesses using RegTech to ensure compliance. While RegTech needs to keep up with FinTech changes, it also needs to keep up with other information technology changes to maintain successful regulation.
Though this was not the original intent, RegTech applications extend to other types of data management, including personal information. RegTech's move beyond the financial industry makes sense because governments are regulating how businesses store personal information — like financial information — in regards to privacy, security and use. RegTech is important for security firms and any business concerned with regulatory compliance. Additionally, businesses can use RegTech concepts to interpret and analyze the information they collect to make projections akin to what the financial industry does.
Businesses that work in the financial industry can benefit from the help of experts in both FinTech and RegTech to improve operations and make sure they're keeping up with the law. Businesses outside of the financial industry have much to learn about how to utilize RegTech by looking at its relationship with FinTech.
The Agile development technique is attractive because teams using it help push new features to the customer, and bugs are addressed much faster compared to the waterfall method. However, adopting an Agile development environment isn't flipping a switch: It involves changing both culture and program structure to reap the benefits of more frequent updates. Therefore, leaders will find switching to Agile easier if they embrace it as a gradual process.
Immediately making every project an Agile project is a recipe for failure. Instead, leaders should start with converting a single project to Agile and — from there — expand one project at a time. Leaders need to learn how to convert a project, so running a prototype or a pilot project will help them understand the conversion process and learn the differences in how these projects need to be managed.
Leaders should organize their team differently to thrive in an Agile environment. Keeping track of who is working on what needs to receive more attention because it's going to change more frequently. Leaders may discover that tools like boards and ticketing systems help keep staff organized and on track. It is also important to avoid micromanaging in an Agile environment. If a developer misses something, you will have the opportunity to address it in the near future.
Program code should also be structured differently to work well with Agile development. It is easier for Agile teams to work with applications that have been branched out and segmented to minimize how much code gets blocked off when making updates; this means you avoid preventing other developers from working on another update. Code compartmentalization is more important than ever.
Agile development needs to keep its moving parts in motion to succeed, so leaders need to promote a culture where developers get in the habit of minimizing the amount of time they need to block off code from the rest of the team. Encourage employees to finish what they have started since letting code sit unfished can prevent developers from attending to other important fixes. Developers should branch off the code they need to work on, make the changes, and immediately restore that code to the trunk.
Leaders should also accept that while you have the pressure to push new features and updates faster without spending as much time debugging and testing, you also have the capability to push fixes faster too in the event that you do make a mistake. Don't avoid pushing updates that are ready to go because you're waiting for another unrelated part of the program to finish. Shift to incremental improvements, but realize sometimes you will need larger overhauls. Leaders should look into automated testing tools to streamline this process.
Leaders don't want to create an environment that is just "waterfall, but more frequent." If your business is looking to switch its development from the waterfall method to Agile, a gradual, organized transition will yield the best results.
In the financial services industry, FinTech apps is the combination of mobile apps, processes, products and business models provided online, comprised of complementary financial services. The apps, in particular, have become very popular in order for more consumers to do exactly what their behaviors are leading them to do naturally: complete electronic transactions.
About 12 years ago, some of the first FinTech startups were founded to respond to the challenge of making financial systems more accessible and efficient. FinTech apps include that for financial education, retail banking and lending, peer-to-peer money transfer, investment, cryptocurrency and others.
So is there data yet in these early years to suggest whether consumer confidence is there? Possibly.
According to a Juniper Research report, there will be more than 2 billion mobile banking app users by 2020. That number will grow exponentially as reliance on mobile tech continues to advance.
According to Wilson Kerr, vice president of business development and sales at Unbound Commerce, “Apps can harness trusted phone features like Apple Pay to reduce checkout friction. [They] can tap into loyalty programs and reward customers for patronage ... Banking apps drive deep engagement and deliver real value, which is why so many consumers love them.”
The reality that there is such a rise of banking apps shows that consumers are becoming increasingly comfortable using their mobile devices for storing financial data and making purchases with them. So retailers can feel buoyed to target consumers for their own e-commerce solutions.
“Smart retailers will look to the meteoric rise of banking apps as a signal that they should begin the process of asking themselves how an app could help them solve a problem for their customers, while adding retail sales to their bottom line,” Kerr said. “For example, apps can allow a furniture retailer to offer virtual show rooms and the ability to place images of furniture for sale into homes.”
There remains a lack of confidence, a “lingering distrust in [traditional] banks,” since the financial crisis of 2008. As a result, FinTech startups have flourished in the wake of what most industries see as dark days to put behind them. And it’s millennials (the largest consumer bloc at the moment) who were growing into adulthood and influenced emotionally during the crisis.
“What that underscored for people is that banks can’t be trusted, and your money is only as safe as the government allows you to believe,” said Fundstrat founder and managing partner Tom Lee [3], who worked at J.P. Morgan in 2008. “That’s why millennials today have so little trust in banks, because of what their parents went through.”
“The younger generation will gravitate toward brands that provide the best user experience, the best value, and ultimately, can help them reach their financial goals,” said JMP Securities’ Devin Ryan.
Cloud migration is changing the way retailers operate to the benefit of businesses and customer alike. At its core, "the cloud" is a massive off-site data repository that provides convenient information access and incredible data leverage potential. Retailers who make the transition to the cloud are constantly finding new ways to enhance customer relationships.
Businesses migrating to cloud-based services are typically moving away from storing information in a data center. Cloud servers offer a wealth of benefits compared with data centers, including streamlined, more affordable server capability scaling. Retailers making the switch to the cloud are blurring the line between physical and retail stores: It's helping retailers treat both parts of their business as a single entity rather than two competing storefronts.
Retailers can leverage the cloud to link Point-of-Sale platforms between online and physical stores. Merged POS helps track everything a customer buys across different physical locations and online sales. This helps retailers create continuity between all their locations, which creates a better picture of customer buying habits for analysis and streamlined customer service.
The customer benefits with improved returns and exchanges experiences. Retailers can access sale information for customers from any location regardless of where the customer made the purchase. Therefore, customers can bring a return to any location. The retailer may even track down proof of purchase if the customer lost their receipt. If a customer bought the wrong size clothing online, they can easily return it and get the correct size at a physical location.
Keeping all your customer data in the cloud makes it possible to better understand and predict customer behavior. The scope of the cloud-based platform means a retailer can analyze customer behavior en masse or on an individual level. This can help retailers more accurately stock their stores and order products for warehouses.
While sometimes a customer just needs to talk to another human being when resolving an issue, cloud services streamline data access so AI-based customer service can handle tasks like automating returns and checking up on orders.
Retailers can use cloud servers to tailor marketing behavior as deep as the individual customer level. Instead of creating ads and suggested purchases based on the history of all customers, retailers can use an individual's purchasing history to create unique suggestions and offers. Retailers can identify a product a customer regularly purchases and send that customer a discount offer if they have stopped buying that product to entice the customer to come back.
Additionally, retailers can create an interconnected shopping experience between online and retail by using "beacons" at physical locations to provide app-based services that mirror customer-specific online suggestions and deals in a retail setting.
If your business is looking to leverage its customer data by combining online and physical store experiences, cloud migration will transform the way you work.
Robotic Process Automation (RPA) is already revolutionizing productivity and accuracy in the workplace. However, the amount any business should invest in the technology is contingent on the nature of the business and the limits of RPA. How much a business should invest in RPA comes down to how much work is compatible with automation and how much automation the business can afford to manage.
RPA technology works best with simple, repetitive actions. Right from the beginning, there are obvious limitations to what RPA technology can do for businesses. The objective of RPA is to remove talent from boring, simple practices so they can be reallocated to higher-value work that can't be performed by a machine.
A business should invest as much as it can in automatic simple, practical processes. The technology excels at data-entry tasks, increases data-processing speed, cuts down on errors and simplifies auditing-related compliance. Don't look to RPA to handle complex analysis — that's what employees are for. The actual amount a business should invest depends on how much work can be automated, which can vary wildly from company to company.
While RPA is great at reducing payroll costs for simple tasks, implementing the technology means your business will need to pay people to manage and evaluate automation work. Hypothetically speaking, the RPA software might reduce existing payroll by $500,000 — but it may require paying people $100,000 to handle upkeep and make sure things are working correctly.
Additionally, by being able to process simple tasks faster, your business might find itself with more opportunities to hire additional staff to work, because data entry is no longer a work bottleneck. Therefore, a business needs to consider managing RPA as a cost. Larger operations working with larger amounts of data tend to see a greater return than smaller counterparts.
RPA technology has an excellent ROI potential for businesses, but that potential will eventually suffer from diminishing returns. There is a limit to what RPA can do. It can reduce payroll costs and generate more projects employees can work on. However, at some point, your business will hit a limit regarding how much the technology has to offer.
Consider this hypothetical example using low numbers for ease of understanding: Investing $10 in RPA might save you $40, but investing $15 in RPA might only save you $50. Eventually, your investment in RPA won't be saving your company money — so finding that point is essential in determining how much you should invest.
If your business is looking to start investing or further invest in RPA, finding the right partners can make all the difference in both identifying the ideal jobs for automation and getting that automation running. RPA offers exciting opportunities for businesses to run better.
Cloud migration refers to the process of transferring data, applications, and other business elements from on-premises computers to the cloud. It involves leveraging cloud computing, which entails storing and accessing data and programs over the Internet rather than on local hard drives.
This concept of cloud computing can be visualized as a virtual cloud, symbolizing a vast server infrastructure that handles connections and delivers information. Beyond storage, cloud migration also encompasses communications. Cloud communications integrate various modalities such as voice, email, chat, and video, enabling seamless collaboration and connectivity.
However, satisfaction levels with cloud migration experiences have been relatively low, with only 27 percent reporting satisfaction. To address this, having a skilled project manager (PM) becomes pivotal in planning and implementing a smooth cloud migration. A competent PM should possess specific skills related to cloud computing, including pricing and ROI analysis, understanding of enterprise architecture, and vendor contract negotiation.
The Cloud Industry Forum recommends using these eight criteria to select your provider:
valuate your existing workloads and prioritize which elements should be migrated first based on their characteristics and requirements.
May interest you: Opinov8 offers UX, Infrastructure And Cloud Readiness Assesments.
Consider these important factors:
Think through factors that impact your company’s specific environment such as disaster recovery and related security issues, backups, stability issues and of course budget directives to cover all this.
You’ve planned the migration including budget considerations. Now you need to create a timeline that suits your needs for migrating, deploying and testing.
Get in touch with us today! We provide customized solutions for your business, leveraging our extensive expertise in leading cloud platforms such as Azure Cloud, AWS Cloud, and Google Cloud.
There are few among us so inspired they truly change the world. In 1955, Dartmouth math professor and computer and cognitive scientist John McCarthy did exactly that when he introduced the notion of artificial intelligence (AI). Since then, AI has popped its head up and down, almost in mythic fashion. We’ve experienced it culturally in science fiction to the point that it has nearly become something more magical than real. Yet it happened — it became a true business value. Then it had legs and could freely cross the human landscape in ways that, thanks to Dr. McCarthy, have irretrievably changed everything.
If for no other reason, it’s arguably now the key difference in economic development across the world. PriceWaterhouseCoopers estimated that “artificial intelligence technologies could increase global GDP by $15.7 trillion, a full 14%, by 2030.”
At this point, it's no surprise that AI has come to revolutionize industries such as healthcare (faster, improved health services by mining medical records); automobiles (driverless cars); manufacturing (AI coupled with automation); e-commerce and marketing (chatbots, predictive sales, recommendation engines, warehouse automation); and financial services (algorithmic trading), among others. The innovation it’s causing is breathtaking, as AI is capable of analyzing massive amounts of data to predict quite specific outcomes. The precise strategy that AI offers a growing number of industries is to be expected. Or so you thought ...
A McKinsey AI report revealed a diverse trend in adoption rates of AI by industries. Technology and communications (32 percent), automotive manufacturing (29 percent), financial services (28 percent) — these make sense. But impressive adoptions rates were also on the rise in media and entertainment (22 percent), education (17 percent) and even travel and tourism (11 percent).
So discovering these five areas where AI is about to shake things up is surprising in ways, but the tea leaves were already predicting this.
One groundbreaking software program is using data to improve wildlife research. “Wildbook blends structured wildlife research with artificial intelligence, citizen science and computer vision to speed population analysis and develop new insights to help fight extinction,” according to its website.
Through its Project Maven, [4] the American military is deploying AI “to sift through the massive troves of data and video captured by surveillance and then alert human analysts of patterns or when there is abnormal or suspicious activity.”
Travel websites use AI to help individuals plan trips, including via chatbot travel AI concierges that do the planning directly.
Drones with AI, available in far greater numbers than first responders, are flying over natural disasters to navigate areas and assess danger.
AI communications strategist Jason Behrmann says agriculture is a sector hit hard by labor shortages. “We estimate that Canada will suffer from a deficiency in 100,000 farm workers soon. Adopting AI and related automation technologies is a matter of survival for the agriculture industry,” he said.
Technology makes it possible to communicate and collaborate faster than ever before, but human bottlenecks can still grind any team to a halt. Whether due to disorganization or poor coordination, teams left with meetings that don’t start on time or lack ample preparation can turn a well-oiled machine into a sinking ship.
Many of today’s AI-enhanced collaboration tools are seeking to change the equation. By increasing the amount of time-consuming or confusing clerical work that can be automated, teams can collaborate freely without having to worry about simple tasks that can slow things down. The result is an AI-assisted workforce that’s able to stay focused on their top priorities.
Here are some ways AI is helping teams get more done faster than ever before.
One of the most frustrating and common pain points for any collaborative team is meeting coordination. Juggling an entire team’s worth of calendar entries, appointments and vacation days can make it downright frustrating to find a single time to meet that works for all team members — even if it’s just five minutes to check in. Worse, a last-minute change can topple a carefully scheduled meeting like a house of cards, creating even more confusion and inefficiency.
AI-based interview scheduling tools are transforming meeting scheduling by automatically drawing from each team member’s availability. Rather than having to email team members to determine available times, AI-based scheduling assistants can coordinate and reschedule meetings on a team’s behalf.
Working as a team member frequently means exchanging ideas using many different types of documents, software tools and communication methods. But within many organizations, different teams may speak entirely different languages by using completely different toolsets.
The marketing team’s Slack and Google Docs operation may look completely different from the accounting department’s Skype and Office workflow. When preparing documents or meetings, this mish-mash of different technologies can slow down cross-team collaboration and increase the possibility of distractions, meaning people waste valuable time on tasks that have nothing to do with the actual tasks at hand.
AI is enhancing this experience through enhanced collaboration tools that work anywhere and everywhere. For an increasingly remote workforce, this includes building easy-to-use communications tools that bring everyone together into the same virtual workspace. Tools like real-time language translation and voice control can help teams naturally communicate, reducing potential confusion.
When organizations streamline digital clutter and make it easy for teams to access and communicate in a single space, collaboration becomes more powerful and focused than ever before.
DevOps has already gone far to change IT culture. An agile technology combining software development (Dev) and software operation (Ops), it accelerates everything related to software and services, focusing on the concepts of monitoring and automation from integration to testing to post-deployment management. Yet, DevOps as a Service (DaaS) takes DevOps even farther.
DaaS is a delivery model for the suite of tools that advance collaboration between software development and operations teams. Effectively, a DaaS provider improves on the idea of the toolchain (discrete, distinct software development tools linked or chained together within specific stages). Instead, DaaS sweeps in and forms into one efficient unit those divergent tools that make up the overall software development and delivery process.
DaaS aims to ensure every step in the delivery of software is tracked (along with associated ongoing feedback) so desired outcomes are achieved while successfully hiding complexities of data and information flow management. In this way, teams can use intuitive interfaces to more effortlessly call on the tools they require in order to best deliver the ultimate business value.
Here are the top 10 words and abbreviations you need to know about DaaS.
These terms are helpful in understanding how, by integrating DevOps tool suites into a unified system, DaaS does improve DevOps goals by coexisting with traditional development and deployment processes — and so, ensuring collaboration, monitoring, management and reporting, while enabling the adoption of more flexible approaches in the changing marketplace.
The big players — Amazon, Apple, Facebook, Netflix, among others — are now devotees worshipping at the altar of DevOps. We know 81 percent of enterprises and 70 percent of SMBs are adopting DevOps, and this 2019 report indicates trends are only continuing on the upswing.
Organizations are stressed in new ways these days, thanks to the explosion of cloud-based applications. The need to deploy software releases to manage end-user needs regarding security, bugs, new features or unusual activity means that software and operations teams are stretched to their limits, creating internal struggles and strife. This child of Agile — DevOps — is far more than merely the latest flash-in-the-pan … It’s become a critical solution for this collaboration.
Combining software development (Dev) and software operations (Ops) is a practice little more than a decade old in software engineering. It’s underscored most strategically by monitoring and automation at every step of the process — from integration to testing, all the way to post-deployment management. Undeniably, the three main goals of DevOps are speed, cybersecurity and collaboration. Supporting all of this is automation.
The 2018 State of DevOps Report illustrates how organizations are benefiting from DevOps in ways that include lower change failure rates and less time dealing with security challenges, rework and unplanned work. At the same time, DevOps is vastly improving failure recovery, customer satisfaction and operational efficiency.
However, sufficient automation is required throughout the DevOps process to make these benefits come to life. Speed is the backbone of DevOps, and maintaining a steady sprint is all about automation done well. In this way, you can effectively manage things such as:
As more companies seek to create a leaner org table by right-sizing staff, the role of a dynamic consulting business has never been more vital and attractive across so many industry sectors.
The “toolkit” consultants used 10 or 5 (or even 2) years ago can’t fully address the needs of today’s client base.
The modern toolkit for consultants is agile, tech-facing and adaptable to sudden sea changes in market trends. Here are some of today's most respected tools.
Most consulting businesses tend to be smaller shops — perhaps 5 to 10 employees. With such a limited team, marketing automation optimizes hundreds of hours of “grunt work,” allowing employees to focus on more strategic tasks. Digitization and automation of business processes and customer engagement processes launches your consulting business to the head of the pack when it comes to attracting, developing and retaining new clients.
When seeking a new marketing automation solution, look for a provider with extensive CRM agency reach. Providers using cutting-edge tools such as Adobe Campaign Manager can optimize your marketing process by 10X.
As you build out your client base, your efforts focus externally on relational contact and solution selling. Few consultants have the time or expertise to develop a game-changing user-design experience. Deploying a vibrant UX solution requires a tool that powers usability, visual design and interaction/data architecture to guarantee a satisfying experience for your clients.
The quest for an optimized data-analytics platform is moving at the speed of thought. To position your consulting business as a thought leader within your sector, you must adopt an analytics strategy that maximizes the latest tech in the fields of Artificial Intelligence and Machine Learning. Your quest begins with the gathering of relevant data, followed by establishing a data-needs baseline and finally the creation of a robust, predictive analysis platform to solve problems.
Partnering with a provider that can access multiple APIs to streamline this process is essential to your success. Fueling a crystal-clear vision, strategy and tactical model for handling and maximizing data is a passion for quality providers.
All the tools at your disposal as a consultant mean nothing to your client if they cannot depend on your firm to shepherd data in a secure manner.
Cybercrime — as well as cyber warfare — is a disease that’s not likely to leave the world stage any time soon. Consulting businesses are often tasked with protecting highly confidential client information, sometimes with legal or even political ramifications. Ensure your IT systems are armed with the most vigorous architectural design and integration available — solutions such as BiModal platforms that utilize effective DevOps practices.
At the end of it all, your consulting business will only survive (and ultimately thrive) based on your commitment to investigating, obtaining and deploying the best of the best in tech-facing tools.
The pace of change in technology is growing. Companies have countless options to improve their technology infrastructure. Consumers take less time than ever to adopt new technologies as well. It’s difficult to identify the best solutions for your company.
Opinov8 puts a finger to the pulse of these changes. We keep our partners abreast of the latest developments. Innovation drives our mindset and services. This enables us to help partners adapt to these changes.
Our experts have identified 8 key technology trends for the year. Consider how these developments will affect your company. Then, connect with us to learn how we can improve your technology infrastructure.
Consumers and B2B customers have heightened eCommerce expectations. They expect the best experiences on all eCommerce websites. Companies need specialized services to keep ahead of the curve.
Headless commerce is a trend worth noting. It allows developers to deliver any type of eCommerce solution. They use application program interfaces (API) to deliver to any type of device as well. It “adds another layer of data for analysis,” says Forbes. These features allow for proactive improvements to customer experiences.
Marketing automation is critical to modern business. It drives great omnichannel experiences. It transforms the entire customer journey as well. Expect more sophisticated solutions in 2020.
Still, marketing automation is a challenge for most companies. It can alienate customers when done incorrectly. Opinov8 works with partners to lower marketing costs through automation of business processes. We improve customer engagement processes as well.
Companies need rapid responses to changing customer expectations. Custom software engineering solutions help with this process. Agile methodologies are a popular approach.
But these best practices are changing. Developers must move beyond Agile for more complex software development. Opinov8 has embraced other methods to improve outcomes for our partners.
Most companies lack critical security features. That’s why data breaches have become more common. Bad actors target companies of all sizes. Nobody is immune to the damage they can cause.
Companies need partners who administer rigorous controls and testing. Opinov8 provides effective code management. We support both manual and testing environments as well. Our proactive relationships help clients stay ahead of security concerns.
Traditional analytics are no longer enough. Companies need automated business intelligence. But many companies lack the infrastructure to support this.
The right partnerships support unique and dynamic analytics models. They automate key processes as well. This allows employees to focus on adding value rather than processing information. Companies who master this in 2020 will have an immediate advantage over their competitors.
Internet of Things (IoT) adoption is spanning industries. These solutions create ecosystems between products and platforms. But adapting cloud platforms to accommodate these systems is complicated. This is especially true as companies try to accomplish more with IoT.
In 2020, companies will launch IoT on 5G networks. This will add new capabilities and make IoT investments more desirable. Companies need the right development resources to make them effective.
Blockchain uses a public ledger to manage transactions. It grew in popularity with the growth of cryptocurrencies. Companies across industries are finding more business applications as well.
Blockchain recently fell out of popularity, Gartner reports. But analysts predict it will become a core technology to future digital business functions. IT leaders must be prepared to use Blockchain to achieve competitive advantages.
Companies need to think progressively about new technologies. With this in mind, they will turn more and more to skilled technology service providers.
At Opinov8, we engage with our clients at all stages of technology development. We take a collaborative approach to our client’s success. Let’s start a discussion about innovation solutions for your company. Connect with an Opinov8 expert today.
In technology, the concept of a monolith runs the gamut — from application monoliths (single large application with many dependencies); database-driven monoliths (multiple applications or services coupled to the same database, challenging to change); monolithic builds (a continuous integration build for the purpose of getting a new version of any component); monolithic releases (bundled components); and several others.
Organizations can increase their capability by dividing old monolithic systems into manageable chunks according to business requirements for safer, more expedient changes — ergo, backend microservice architecture.
In addition to the issue of poorly planned decoupled systems where the decoupling had not taken into account how the process affects teams (and not merely technology), there also needs to be a focus on how backend microservices impact complex frontends.
A micro-frontend solution is what happens when your newly decoupled backend is now weighed down inconsistently with your business services because of a monolithic frontend (in one app). So, the idea is quite similar to building backend microservices, but it’s about modifying it for client-side development.
A micro frontend mirrors the backend microservice by business domain enabling the frontend to have more concurrent systems for testing, speed and systems in the mind of how the new backend architecture is imagined. The benefits of a newly structured micro frontend may serve your needs.
If you have a team problem: If your teams need to separate for the business services cycle, then they are weighed down by a frontend monolith, which denies them the ability to deploy their unit work separate from the built-in single release.
If you have a scale problem: Micro frontends best serve an organization where the frontend monolith has made it impossible for a team to provide accessible solutions because it’s just grown like a weed that is now cumbersome and confusing.
If you lack flexibility: There are always new systems, tech, apps and processes that could very well influence growth in your organization or product. Micro frontends allow your team to experiment without dragging the entire system down — or, for that matter, deny experimentation because a unified business cycle won’t allow more flexibility.
Today's websites are shifting to feature more dynamic content that parallels experiences users expect from mobile applications. Libraries like React.js are available to alleviate the challenges that come with developing highly interactive websites.
React.js is a JavaScript library built to address the unique needs of a dynamic user interface for a website. It provides a wealth of performance and ease-of-use benefits for developers. Facebook initially introduced the library to the programming community, which now is largely responsible for maintaining and documenting it as an open source project.
Websites naturally split up into several interface components such as the navigation, a sidebar and main content. React.js embraces this concept and splits the page into individual components that can be reused and manipulated as needed. React.js employs templates for each component, and these are easy to build and convenient to reuse.
To make it easier to create the templates, the library uses JSX to allow the developer to write HTML in-line with JavaScript code. Using JSX is much easier than constructing complex HTML through JavaScript's standard capabilities. This can be very useful for actions such as changing a sidebar between holding some advertisements, a messaging client or user settings without having to load a new page.
React.js utilizes a Virtual DOM to work around the need for the browser to re-evaluate the entire page whenever a component is updated through component isolation. Limiting how much work the browser needs to do helps pages run faster.
Additionally, the library makes it easy to run UI updates without having to make an HTTP/HTTPS call. The virtual DOM reduces dependency on the server calls to make page content adjustments.
Finally, component isolation means changes to one component won't have adverse effects on the others. The downward flow ensures changes to child components won't impact parent components that could break the page's layout.
The virtual DOM makes it easy to pass data between components. With other methods such as AJAX, it can be very easy for important variables and values to get lost between the page construction, the first update call and subsequent updates.
However, with a Virtual DOM, these values stay in the browser's memory and are ready to be used again without requiring the developers to work with complex variable value-passing methods.
React.js can make projects easier to manage and faster to operate. Additionally, React.js can be used for single-page/mobile web applications and has a native application framework for iOS and Android apps. The library simplifies the transition toward parity between mobile web and native applications.
If your website would benefit from implementing any of the React.js features, the library is worth checking out.
In his May I/O 2017 keynote, Google CEO Sundar Pichai addressed an “important shift,” their sea change, from “searching and organizing the world’s information to artificial intelligence (AI) and machine learning (ML).” In his 2016 Founder’s Letter, Pichai laid out his vision: “The next big step will be for the very concept of the 'device' to fade away. Over time, the computer itself — whatever its form factor — will be an intelligent assistant helping you through your day. We will move from mobile first to an AI first world.”
Recently, Pichai made good on that promise by backing a group of startups that use AI in healthcare technology. One uses voice recognition commands for record-keeping, team collaboration and other administrative tasks, reportedly saving doctors 10 hours a week. Others use the technology for early diagnosis of sepsis, assistance for people with mobility trouble and construction of a platform for wearables.
Google is just the first of the giants to step into the fray.
When it comes to investing in AI, a great deal has changed over the years.
2007 saw 31 new deals take place. By 2016, the number skyrocketed to 322 deals, with a total of $3.6 billion invested. For all healthcare IT companies, venture capital funding during first nine months of 2017 alone passed the total for 2016, which was
Today, AI works best through perception and cognition using voice and image recognition and ML — learning without humans explicitly programming them to perform that process. AI in health care uses algorithms (a process for problem-solving) to analyze medical data, especially prevention or treatments that could impact patient outcomes. AI programs are working most effectively in fields like personalized medicine/genetics; drug discovery and development; and disease identification and management.
“Putting real-time data in the hands of providers helps them better help patients,” says Deborah Muro, CIO for El Camino Hospital in California, like by developing an algorithm to analyze patients at high risk of falls. Gathering certain types of information, such as how frequently patients leave their beds or use their call lights, can be used to alert nurses to check on patients in order to prevent potential falls, she says.
Both now and on the horizon, AI innovations in health care are more exciting than ever. Consider these technologies:
• Chatbots can take “patient inquiries via phone, e-mail or live chat.”
• Virtual assistants “enable conversational dialogues and pre-built capabilities that automate clinical workflows.” Some can to even detect depression through subtle clues in speech or gesture.
• Robot "doctors" are conversational robots that explain lab results.
• Surgery consultants support workflow and build predictive modeling.
• AI prosthetics refers to when a “bionic hand is fitted with a camera which instantaneously takes a picture of the object in front of it, assesses its shape and size and triggers a series of movements in the hand” in response.
• Disease detectors can “identify tuberculosis on chest X-rays,” and some can highlight “areas that might indicate the potential presence of cerebral bleeds.”
By virtue of design, AI and ML solutions for health care will keep getting better. You can expect these technologies to enhance diagnosis and prevention of diseases, help researchers get more out of the data they collect and even empower labs to produce drugs tailored to a person’s DNA. For AI in health care, the future certainly looks bright.
SaaS has become a transformative technology solution and
over 20 percent growth, making it a $46.3B industry. During the last 10 years, companies like Salesforce, Dropbox and LogMeIn have become incredibly successful B2B organizations and even household names. As startups continue to enter the space in search of a piece of this growing market, these businesses can learn a few lessons from the successes of existing SaaS companies.
Just as we throw around acronyms like “IBM,” it’s easy to use SaaS as a word and not remember its origins. SaaS stands for “Software as a Service” — but many newcomers in the SaaS space will start as a Software as Many Services. Many businesses that do so will fail, as being a jack of all trades but a master of none is an ineffective way to carve out a niche in the market.
Before LogMeIn offered meeting services and remote customer support, the company did one thing: allowed users to get to their computer from anywhere. Similarly, Dropbox has now integrated with Windows, iOS and Linux and can be used for enterprise cloud storage, but its origins were far simpler: allow a user to save files to the cloud from any device. Instead of taking on the world, successful SaaS companies have found a single need, addressed it and then built from there.
When a SaaS company launches, it is easy to focus on the here and now — what needs to happen to stay afloat this quarter, or even this month. However, as companies find success, this mindset must change. It’s crucial to have a growth strategy relevant to the level of success achieved. If a SaaS company a year after launching doesn’t have a plan for the following year, the company can easily become too shortsighted and fail.
The freemium strategy has worked for businesses like Spotify, Dropbox and Slack, which saw incredible growth as users tried them at no cost and later converted to paying customers. However, offering a product for free and hoping it will spread like wildfire isn’t a marketing strategy. If no one knows about your product, how will they know where to find it or what it does? Even if the product’s functionality may speak for itself, people can’t try it if they haven’t heard about it.
As much success as freemium strategies have brought certain businesses, SaaS companies cannot sustain themselves if all users focus on the “free” part of freemium. In fact, it may be best to limit the number of freemium users until there have been enough conversions to continue supporting free use of the product. Simply put, if sales cannot support the number of free users, your SaaS company won’t last.
Gaming companies have been promising players that soon they’ll be able to open and play their games on any device at any time. These organizations are making the shift from delivering betting games via fixed machines to cloud-based systems. With cloud storage, casinos and makers of betting games can target new audiences and keep current players engaged in ways they never could before. So far, they've seen considerable success; by the end of 2016, the global online gambling market was worth over $45 billion. Experts expect it to reach nearly $100 billion by the end of 2024, growing at a rate of over 10% each year.
Here are a few reasons why they’re making the jump.
Traditionally, in order to stay on top of the market, a game needs to launch across a number of platforms. This requires the game to be coded for various platforms, which takes time and money.
Not only does this make these games more cost-effective for the company to produce, but it also makes it more likely a player will play, due to greater accessibility. So far, this accessibility appears to have contributed to its growth as well, with the UK, Malta and the Asia Pacific region being the primary contributors to the industry's rapid growth. 3 states in the USA had legalized online gambling as of March 2017, and more are expected to follow suit by 2020, which is likely to accelerate its geographical expansion.
Game companies of all types are looking more often at micro-transactions to extend the life cycle of releases. Under this model,
rather than all at once. By managing these releases from the cloud, these smaller updates can be made available instantly on a scheduled cycle, keeping players engaged and excited about new content. While some may worry about the security risks of frequent updates, experts say that the extensive verification processes used in cloud and other forms of online gambling actually make it more secure than gambling at many physical casinos.
What is more, if a particular game isn’t getting much play in a casino, cloud storage allows for the game to be easily swapped out for another. This isn’t possible with traditional one-game machines, which can lead to dead space on the casino floor.
Engaged players are repeat players — and repeat players spend more money. With cloud gaming,
These easy in-app transactions encourage players to continue playing where previously they may have instead simply stopped and walked away.
With streaming and cloud services becoming the norm for movies and television, it’s no surprise that gaming is next. As networks expand and data transfers become faster and more stable, the reason why gaming companies want to take advantage is clear. While cloud gaming may not be the entire future of gambling, it will certainly play a large part in casinos and other aspects of the industry for years to come.
The future looks bright for Internet of Things technology going into 2019. But the industry will likely have to jump a few hurdles along the way. With major corporate security breaches frequently appearing in the news, it's clear to customers they need to be careful about whom they trust with their personal information. Businesses will continue to push new IoT concepts while improving upon existing ones, which have the potential to revolutionize daily life.
As of 2018, the biggest security issue with IoT device is how hackers can exploit lax security on the devices to create botnets for malicious uses. A hacker can seize control of watches, thermostats and hundreds of other smart devices to overwhelm and disable a site or service. Vulnerability means device creators and users alike will shift security focus to all endpoints.
Changes may include forcing users to change default passwords and implementing blockchain to stop unauthorized changes. To combat security issues for small and large businesses, managed services providers will likely start offering IoT-related services as well.
As exciting as constant innovation can be, the IoT industry has to accept that some smart devices are far more useful than others. The number of smart devices jumped from 20.35 billion in 2017 to 23.14 billion in 2018. The public will likely see many new device types appear on the market. Some will succeed, and others will fail.
Healthcare and manufacturing will lead the charge toward IoT adoption by using devices that vastly improve monitoring, recordkeeping, efficiency, downtime reduction and inventory management. Biometrics will likely expand in use, but people may hesitate to use it because they don't like being constantly tracked. However, people will likely embrace RFID-based devices.
As technology improves and prices drop, IoT devices will handle much more of the data processing locally rather than relying on the cloud to do all the heavy lifting. Running most of the data processing closer to the data generation source is known as "edge computing." However, the cloud will still be essential for data management and analysis. Having the devices do more of the work will minimize how much data has to travel to the cloud which is good for both security improvements and traffic reduction.
Implementing 5G Internet access will make it more practical to run IoT devices over cellular networks. This change could lead telecoms to get more invested in IoT and connected cars becoming more prevalent. Additionally, " smart cities" that use IoT devices to handle traffic systems, waste management and other operational elements will likely emerge. However, it's only a matter of time before a " smart city" finds itself on the losing end of a cyber-attack.
If your business is looking to invest in IoT devices to improve the workplace, it's best to take a preemptive approach to security and consider which devices are right for your unique needs.
Business has been using Artificial Intelligence for quite some time, but there’s been significant growth in the last few years because of advances in areas like machine learning and natural language processing. No other sector is as poised to leverage the rapid advances in AI as the travel and hospitality industry where consumer satisfaction is crucial to beating your competition.
Travel companies now possess a wealth of information about customers, including traveler profiles, behavioral history, and personal preferences. Applying machine learning to travel data opens up a wealth of opportunities to improve the traveler experience. This makes the travel and hospitality sector well suited to ride the next wave of AI in order to build intelligent applications that take the customer experience to new levels of personalization and comfort.
Since its introduction to the sector, AI’s influence has spread to almost every aspect of the travel and hospitality industry experience.
while delivering traveler journeys, hospitality, service, and loyalty programs.
Let’s examine the major use cases where AI technology is currently being utilized to dramatically change travel and hospitality products and services.
‘Chatbots’ have emerged as highly visible examples of machine learning at work in the travel and hotel-booking experience. Their sophistication is constantly improving as the machines keep learning to simulate human conversation using NLP (neuro-linguistic programming) techniques. Lufthansa and Kayak are notable examples of the successful use of chatbot-based automation bringing convenience and efficiency to customers.
Travel agencies and aggregators use machine learning and predictive data analytics to forecast and dynamically optimize their revenue management systems. Algorithms to dynamically identify matching properties, sentiment analysis to identify optimum room rates and real-time segmentation to assure hotel bookings are optimized for the right customer at the right time and price.
Consumers are expected to make
percent of all digital booking via mobile devices by 2019. By automating transactions that don’t add value for both companies and travelers, automation will save valuable man hours and resources. Airline companies use AI to give unprecedented options to manage all aspects of the physical travel experience — like providing real-time updates and support to travelers in case of disruptions.
The ability of AI to personalize the delivery of content, services, customer support and loyalty programs could potentially transform how the industry markets and delivers services. For instance, innovations like Hilton’s Connie, the first true AI-powered concierge robot, is capable of adapting recommendations of local attractions and activities for each guest.
A recent McKinsey study found that
The travel and hospitality sector has the opportunity to retain and delight customers, and propel growth with new AI-based services for better customer engagement, experience personalization, and AI-powered customer service.
Organizations across the globe are increasingly turning to DevOps in order to speed up delivery of software and services. This agile technology is changing everything — and no one better understands that the "The Godfather of DevOps," Patric Debois, who created the movement.
“The cultural aspect of collaboration gives everyone an equal seat at the table; both Dev and Ops are important," Debois said in a recent interview. "The biggest advantage is the insight that we work in a system. We have to optimize for the whole system and not just for the silo. By optimizing for the whole, we are improving for the business, not just for IT.”
In a nutshell, this combination of software development (Dev) and software operation (Ops) is a relatively new practice in the world of software engineering. It centres on the concepts of monitoring and automation, every step of the way — from integration to testing, all the way to post-deployment management.
The DevOps culture brings with it numerous benefits associated with acceleration, including briefer development cycles and more frequent deployment. For organizations seeking change, DevOps is one disruptor that can help them reap rewards.
Essentially, DevOps can be boiled down to three critical ingredients.
First, it focuses on speed. “The goal of DevOps is to create a working environment in which building, testing and deploying software can occur rapidly, frequently and reliably," wrote tech journalist Jason Hiner in a recent article.
Another advantage centers on improved cybersecurity. In a world where breaches make headlines on a near-daily basis, DevOps empowers organizations to better find and fix their vulnerabilities. It also simplifies the process of providing patches and security updates and helps prevent unwanted intruders.
Finally, DevOps helps IT departments collaborate better. While many professionals focus on a single specialty or skill, this new culture encourages them to put their heads together — a practice vital for success in virtually any organisation.
The key to DevOps is improving delivery of applications and services. The secret weapon is speed, especially as a business tackles the migration of data, communications and services to the cloud.
“Digital transformation strategies are evolving because there are so many technology changes, so you have to react fast," Kamal Anand from Tech Pro Research told ZDNet in an interview.
Companies across the world are embracing artificial intelligence (AI) capabilities at a rapid pace,
and today’s leading technology companies — Amazon, Apple, Facebook and Google — are no
exception.
Here’s a look at how the big four tech firms are currently using AI:
AI is behind many of Amazon’s most popular efforts. Alexa, its voice-powered virtual assistant, uses natural language processing and machine learning to process user queries and carry out actions like ordering products or controlling smart home devices. In Amazon Go convenience stores, machine vision and algorithms make it possible to track when customers pick up items to make purchases without human cashiers. And as one of Amazon’s longtime AI flagships, its product recommendation technology analyzes user purchases to suggest items that customers may wish to purchase in the future.
Apple’s embrace of AI makes it easier for developers to create apps that can harness machine learning on Apple devices. Through Core ML, developers get access to machine learning tools for common tasks like image recognition. In 2018, Apple introduced Create ML, a toolkit that makes it possible for developers to learn the basics of how to build machine learning models.
With the introduction of the iPhone X, Apple added a neural engine to its A11 processor to accelerate AI-specific tasks. Combined with developer tools, new and experienced developers alike can easily build applications that take full advantage of machine learning capabilities and AI-focused hardware.
Facebook uses machine learning to make predictions about a user’s interests . Analyzing the likes, the likes of friends and location information, Facebook takes that information to determine content a user may enjoy through features like Facebook Watch. The extent of these prediction capabilities can also predict other future behavior, like what products a user may purchase, that can be shared with advertisers.
Google’s commitment to AI stems from its interest in deep learning, where artificial neural networks mimic the way the human brain processes information. The company’s interest in deep learning became public in 2011 through its Google Brain project, a neural network designed for image recognition. Google cemented its commitment to deep learning through the acquisition of Deep Mind, the machine learning company behind the Alpha Go, an algorithm-based digital competitor for the board game Go.
Across Google services, deep learning is used in everything from to natural language processing to providing user recommendations. Its open source TensorFlow machine learning programming platform enables users to develop their own neural network solutions. AI is also at the core of Google’s self-driving car efforts, incorporating deep learning algorithms into its autonomous vehicles.
FinTechs are embracing social media to tell their stories, engage consumers, and leverage influence. Long-established brands like American Express as well as newcomers such as Clark and solarisBank – and their BaaP (Banking as a Platform) software – are employing creative FinTech banks face a promising but complicated future as economies evolve into cashless societies and banking transactions go mobile. Traditionally, the public’s perception of a bank was that of a strong concrete or brick-and-mortar building filled with trusted, well-dressed professionals, security guards, and a hushed atmosphere that conveyed a serious financial environment. Banking through a mobile smartphone, however, is a completely different experience. And there is no better way to brand that experience than through social media.
American Express, which spent 2.35 billion on advertising in 2015 is harnessing the power of Instagram influencers as #AmexAmbassadors to promote the brand’s Platinum Card to consumers. In the age of mobile platforms, brands like American Express are leveraging social media to sell their products and services through an aspirational narrative crafted by experts and celebrities in fields ranging from food and fashion to travel and photography. The American Express #AmexAmbassador marketing strategy employs a variety of such influencers, from NBA icon Shaquille O’Neal with millions of followers to “micro-influencers” and bloggers who have leveraged their niche expertise in a spectrum of categories, such as interior design and lifestyle management.
Meanwhile, the Instagram account for solarisBank offers brand-building narratives featuring beautiful views from the company’s headquarters in Berlin, Germany, including rooftop yoga and brainstorming sessions alongside images of homemade pizza and industry events. This focus on community is extended across solarisBank’s other social media channels as well. On Twitter, solarisBank solicits the help of customers in testing the brand’s “consumer lending product” alongside other tweets featuring staff at conferences and recent accolades. SolarisBank blends these narratives on its LinkedIn page with other corporate initiatives, such as promoting open positions and thought leadership assets – all designed to create and leverage the power of influence.
Whether applying for a loan, depositing a paycheck, or transferring money into a savings account, most customers want a quick, easy experience – especially online. FinTech brands know firsthand that social media channels are deeply integrated into everyday transactions, both professional and personal, placing them in the middle of a digitally oriented cultural shift. Clark, which provides low-cost customized insurance coverage, is at the front line of using social media to promote its seamless, integrated financial platform. Clark is an app similar to the popular money-transfer app Venmo, except that the self-proclaimed “insurance robo-advisor” uses algorithms so that customers can easily manage and purchase a spectrum of insurance products based on their online information. Not surprisingly, Clark uses Facebook, Instagram, LinkedIn, and Twitter to promote its services and brand.
In addition to creating front-of-mind marketing campaigns, FinTech brands are leveraging social media to monitor and increase customer satisfaction. In a seamless global culture, social media is an extension of a customer’s valuable thoughts, suggestions, and complaints. FinTech brands like American Express, solarisBank, and Clark use social media as an interactive, real-time focus group that provides critical information about the effectiveness, usability, and popularity of their products and services. By tagging FinTech brands with a direct @handle or #hashtag, customers – especially disgruntled customers – will typically receive a follow-up from a customer service representative with hours, if not sooner.
The challenge for many FinTech brands is that their products and services are generally intangible and can’t be pulled off of a store shelf or set on a windowsill and photographed. Social media, however, is often visual, so FinTech brands must stretch their creativity. Savvy FinTech businesses utilize photos and short, accessible videos from events such as conferences and in-house talent at celebrations to contextualize their expertise and industry leadership. Add to these assets social media influencers and effective customer service protocols, and they have a winning visually based strategy. Just think of those colorful and creative American Express cards, intentionally designed to be photographed and shared on Instagram. Yours could be the next sensation.
As machines begin transacting with machines, traditional blockchain models hit a wall. High fees, scalability issues, and energy use limit real-world adoption.
With IOTA, a lightweight, feeless alternative built for machine-to-machine (M2M) transactions, we’re entering a new phase of decentralized infrastructure — one that fits the needs of modern industries embracing IoT.
Many things in the digital world 37 feel connected, and they all should. Devices are connected to many other devices. Our homes, cars, banks, businesses, schools, hospitals, municipalities — all connected, thanks to the Internet of Things (IoT). Even our behaviors are connected to how information is captured and used to refer back to us new information, all based on those behaviors. So, it should not seem alien to start thinking that ideas are all connected too, and as new ideas develop — especially in technology — they evolve from other ideas that barely have taken flight before the other emerges. That’s the case with blockchain and IOTA. In this case, an “iota of a difference” is, in fact, a very meaningful thing.
You’ve probably heard the term “blockchain,” especially of late (even though its inventor, Satoshi Nakamoto, developed it in 2008). Perhaps you even know what it means in relation to the cryptocurrency revolution. Essentially, a blockchain is a digital and decentralized ledger in which transactions made with Bitcoin or other cryptocurrencies are recorded chronologically and publicly, verified by “miners” to avoid duplications through a complex mathematical “proof-of-work” based algorithms. The beauty of Nakamoto’s design of blockchain for Bitcoin is that is solved the double-spending problem without the need for a centralized server.
That’s not just remarkable, it’s revolutionary.
The great promise of blockchain was decentralization. It does not run using a standard database on just one computer. Instead, it is managed autonomously using a peer-to-peer network. Distributed processing nodes jointly run it collaboratively, and each node can hold a full copy of this special database. As a result, the database and its contents are more secure since it is near impossible to tamper with it without being found out by others in the network.
Even though it was created for use in tracking cryptocurrencies, think about the possibilities of other uses — any kind of record-tracking and storing of data. It can be used not only in FinTech for borrowing money or buying cryptocurrencies, but also smart contracts, voting, securing property rights in real estate, tracking shipments, managing a database of patient information for health care provider access, more secure shopping, and other potentially groundbreaking applications.
However, blockchain does have its limitations and problems — namely scalability and the transaction fees associated with it. So as it started to feel like it needed expansion, a new idea came about.
IOTA has gone beyond blockchain — one could argue it’s the next step in blockchain’s evolution. First and foremost, it’s scalable and feeless. Without the necessity for a distinct group of miners (who must be compensated), there aren’t the fees with IOTA that plague blockchain. This is part of what’s at the heart of the IoT-loving IOTA. The feeless system fosters exactly the kind of microtransaction environment friendly to the burgeoning machine-to-machine (M2M) economy — one arguably impossible or quite clunky with Bitcoin.
IOTA is also decentralized like blockchain, but in a more authentic, efficient and secure way. It’s the first open-source distributed ledger, thanks to the blockless Tangle — more a web of transactions than a linear block. Tangle works with a quantum-resistant Directed Acyclic Graph (DAG) and grows through its transactors, not the miners, so it bypasses blockchain’s current major challenge: its lean toward becoming centralized.
Rather than use the sequential chains of blocks in blockchain, the Tangle is a stream of individual transactions entangled together. To participate, one need only perform a bit of computational work which then verifies two previous transactions — a pay-it-forward system of validations. And the “more activity in ‘the Tangle,’ the faster transactions can be confirmed,” giving it another one-up on blockchain, which slows down as transactions increase.
IOTA is the perfect fit for the emerging IoT’s M2M economy of scalable, fee-free, decentralization where data integrity and micropayments are highly prized. And that seems to be proving itself today.
In 2024, IOTA rolled out its Stardust upgrade, unlocking smart contract capabilities and native assets — moving closer to true enterprise-grade utility.
Meanwhile, initiatives like Project Alvarium (in collaboration with Dell Technologies) explore how IOTA nodes can support trusted data pipelines across distributed systems — from factories to smart cities.
Nasdaq says of IOTA that it’s “one of the most prominent blockchain alternatives” and that the IoT “could benefit enormously from a network able to complete high volumes of minute transactions,” which opens up new economic possibilities.
With an IOTA node, machines gain the ability to transact with other machines, manage all economic transactions on their own, making them “economically independent.” And that’s exciting. Soon, a smart device could “pay its assembly, its maintenance, its energy and also for its liability insurance by giving data, computing power, storage or physical services to other machines.”
One day quite soon amidst those connections in the IoT, IOTA’s Tangle may well serve to completely reshape how all those things interact, what they can do to transform entire industries desperate for fast, efficient, trustless systems.
As AI and automation reshape industries, innovation leaders are looking for infrastructure that can handle high-volume, low-latency, trustless interactions.
With IOTA, companies can build decentralized ecosystems where devices trade value, verify data, and operate autonomously — at scale, and without costly intermediaries.
For CTOs and CIOs seeking scalable solutions in IoT-heavy industries, IOTA presents a real opportunity to lead the next infrastructure leap.
The combination of new technology, a shift in hacking targets and legislation will likely lead DevSecOps to further emphasize data privacy in 2019. The attitude shift will stem from both necessity and a general change in vulnerability awareness. Larger businesses and major device platforms have shifted toward bolstering security over the last few years. This likely will drive DevSecOps to "catch up" platforms and organizations that have been left behind.
The "security through obscurity" mindset is no longer relevant. In order to keep up with the need for better data privacy, DevSecOps will further emphasize automation and push the notion that everyone in an organization is responsible for security.
The many high-profile breaches over the last few years are leading businesses to stress data privacy through security more than ever. Businesses will take a proactive approach to protect data by improving security testing. Organizations are poised to leverage Artificial Intelligence and Machine Learning techniques in 2019 to test for vulnerabilities far faster than what's possible through human testing alone.
The general shift toward rapid development in software necessitates embracing automatic testing integration. Additionally, more development teams will implement Interactive Application Security Testing to streamline and improve testing.
Data privacy emphasis will lead smaller businesses and platforms to invest more in DevSecOps. As larger businesses observed the financial damage and embarrassment other companies endured in major security breaches, they buckled down and enhanced security to avoid finding their company name in the headlines too. Because larger businesses are no longer easy targets, hackers are shifting their attention to smaller businesses and platforms, which are more appealing now. Smaller businesses and platforms can no longer hide behind larger entities.
The proliferation of IoT devices means they will become an even bigger target for hackers. To make matters worse, IoT security is known to be very weak compared with that of other devices. Additionally, mobile users will also find themselves in the targeting scope as mobile use eclipses desktop use.
In 2019, legislation will push a greater emphasis on data privacy in DevSecOps through compliance and anticipation. Major legislation in 2018 propelled data privacy to the legal forefront, but the legal effects will spill over into the following years. Because the web is a worldwide market, the laws in the EU's General Data Protection Regulation and the UK's Data Protection Act will force international businesses to get serious about protecting personal and sensitive information. While the law doesn't apply to U.S. companies, it is reasonable to anticipate businesses will opt in to comply with the laws anyway in anticipation of future legislation.
If your business isn't already taking DevSecOps seriously, there's no better time to start than the present. If your business is already deeply invested in security, staying in that mindset involves keeping up with all the latest trends and closing vulnerabilities before hackers find them.
Think back on a time when software was released after long, drawn-out waits. From 2007 to 2016, Microsoft released versions of Office every three years. Now, software releases are fast and frequent. But are they better? Those three-year gaps allowed Microsoft to painstakingly QA test their software for months, if not years. However, Office has now gone the path of other apps, which seem to release new versions weekly, if not more often.
If there's a bug in the code, the solution seems to be simply rolling out another version and hoping it fixes it (and doesn't break anything else). But in this fast-paced SDLC world, organizations must make time for QA testing as part of the software pipeline.
If your organization would like to test the validity or build quality of a new product or a significant redesign before it hits the market, consider a beta release. Invite fellow coders and power users to test a piece of software while it's still in the pipeline in order to get UX, UI and general feedback on the product.
This seems to be a logical option, but for many developers, this is easier said than done. It can be easy to say, "Let's just add this one more item before we beta test this," which quickly turns into "Wait, what if we added these three other items?" Planning a beta test following a specific sprint is incredibly important at the onset of the project's roadmap. Don't think that it will happen organically — it probably won't.
With many organizations investing significant time and resources into digital transformations, automation and artificial intelligence are no longer "the next big thing" — because they're here. Even simple apps incorporate predictive technology and predictive algorithms. As a result, testing must follow suit. This is where AI can assist testing in the software pipeline.
AI and predictive technology can run tests far faster than any single person or team could, finding software flaws in minutes rather than days, weeks or months. Exposing these flaws quickly can help developers resolve them before the next iteration, ensuring weekly updates go out with far fewer flaws. This allows the software pipeline to move quickly and smoothly without requiring teams to fix what's broken before moving on to new implementations.
Recent advancements in AI are making chatbots smarter and more human-like than ever before. As a result, customers are warming up to the idea of interacting with chatbots with 44% of respondents of the Aspect survey claiming that they would prefer to communicate with a chatbot instead of a human company representative.
As AI chatbot solutions become more available, early adoption of the chatbot technology becomes a source of competitive advantage and brand value. This article describes ways in which chatbot technology can benefit your sales via a “conversational commerce” approach.
If your company is selling products or services online, you can entrust the entire sales process -- from the initial quote to closing a deal with a customer — to a chatbot. In 2015, Chris Messina, then Developer Experience Lead at Uber, defined such an approach to e-commerce as conversational commerce.
These days, companies can integrate conversational commerce into their chatbot applications simply that excels in sales. As messenger apps are becoming more popular than social networks, integrating sales into them will expose your business to billions of users worldwide. (see the figure).
Once the AI-enabled sales chatbot is installed, it can help customers purchase items with fewer steps than ever before. To speed up the sales process, a chatbot can mine user preferences in conversation history or refer to the user profile to get information about the customer’s location, gender or hobbies. Unlike a human expert who would have to learn this information manually, a chatbot can process user data in milliseconds, ensuring a seamless buying experience for the customer and a perfectly-matched product to his/her needs.
Thanks to these smart features, conversational commerce to your customers. Early adoption of chatbot technology will help you build a data-driven and innovative company that values the time of consumers and employees. And if you’re running a small company, don’t worry: with the rapid advancements in AI, chatbot solutions have become more affordable for a company of any size.
RegTech, short for regulation technology, is an emerging industry that combines technology and financial services to help organizations comply with regulations. It focuses on utilizing automation and innovative solutions to simplify regulatory monitoring and reporting processes. By leveraging RegTech solutions, companies can avoid costly mistakes and ensure adherence to the numerous financial regulations in force worldwide. This industry has experienced significant growth and is expected to continue expanding in the coming years. Here are five key Regtech trends to watch for in this dynamic field.
In the first half of 2018, the RegTech industry received $1.37 billion in investments, surpassing the total investments made in 2017. This surge in funding demonstrates the increasing recognition of RegTech as a major industry in its own right, separate from its parent industry, FinTech. As RegTech continues to mature, it will attract even more corporate interest and substantial investments, further solidifying its position as a prominent sector.
Managing risks is a critical aspect of any business, particularly in the financial services industry. RegTech plays a pivotal role in risk management by significantly reducing the time required for regulatory compliance checks. This streamlines the onboarding process for new companies and facilitates ongoing compliance for existing organizations. RegTech solutions help identify potential risks, automate compliance procedures, and provide real-time monitoring, empowering companies to proactively address regulatory challenges.
The growing demand for RegTech solutions has spurred the development of industry-specific conferences and platforms. These gatherings provide regulators, thought leaders, and industry experts with opportunities to collaborate, share best practices, and devise innovative solutions. Collaboration and transparency in the RegTech community will drive sector advancements, fostering a vibrant ecosystem of knowledge exchange and support.
The General Data Protection Regulation (GDPR), implemented in 2018 by the European Union, has become one of the world's most stringent data protection and privacy regulations. Non-compliant companies face severe fines that can jeopardize their long-term viability. While GDPR is an EU regulation, its extraterritorial scope means that international companies operating within EU borders must also comply with its policies. As a result, there has been a heightened demand for RegTech solutions that assist organizations in achieving and maintaining GDPR compliance. RegTech platforms offer tools for data privacy management, consent tracking, breach notification, and other essential aspects of GDPR compliance.
May interest you: Testing as a Service (TaaS) explained.
GDPR is not the only data protection regulation in the world. As more countries introduce their own data protection laws, such as the California Consumer Privacy Act (CCPA) and Brazil's General Data Protection Law (LGPD), the demand for RegTech solutions will continue to grow. RegTech providers are adapting their offerings to meet the compliance needs of these evolving regulatory landscapes. They help organizations navigate the complexities of multiple regulatory frameworks, streamline compliance processes, and ensure data protection across borders.
These trends illustrate the expanding role of RegTech in the financial industry and other regulated sectors. Through technological innovation and automation, RegTech offers companies the means to effectively manage compliance, reduce risks, and stay ahead of evolving regulatory landscapes. As the industry continues to mature, we can expect further advancements in RegTech solutions, fostering a culture of compliance, efficiency, and trust in the business world.
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For more than 60 years, artificial intelligence (AI) has been the white whale of technology promises. Dartmouth math professor John McCarthy coined the term in 1955, and ever since, one phenomenal claim after another has been tossed onto the discard pile. Finally, AI has found its niche in digital commerce. Giants like Amazon and Google have been its champions, but companies of all sizes can and should employ AI immediately.
AI’s great gift is machine learning (ML) — learning without being explicitly programmed in that process by humans. Recently, ML has improved, becoming far more accessible. This is a key improvement because the more learning that happens, the more intelligent the process.
Two major areas where AI has taken hold is in “perception and cognition.” This includes a wide array of problem-solving, and voice and image recognition that consumers use daily (e.g., Siri, Alexa, Google Assistant for voice, and Facebook for tagging faces in images). According to the Harvard Business Review, companies employ “ML to optimize inventory and improve product recommendations, [to] predict whether a user would click on a particular ad, [and] to improve customers’ search and discovery process at a Brazilian online retailer. The first system increased advertising ROI threefold, and the second resulted in a $125 million increase in annual revenue.” These are serious results that every company needs to pay attention to.
Improved searches: ML studies each new interaction to better understand what a customer is searching, delivering more relevant results.
Personalization and recommendations: By gathering data (e.g., a social media post), AI makes specific recommendations based on that content.
Improved customer interactions and relations: Rather than blasting annoying, irrelevant advertising, AI customizes what and how often customers want to hear about their preferred brands. Through voice recognition, CRM systems answer customer questions, problem solve, and report leads to sales teams.
Dynamic pricing: AI can tweak pricing in real time, depending on the market and consumer behavior.
Targeting potential customers: With 33% of marketing leads left without follow-up potential conversions are lost. With facial recognition on-site (in store), AI gathers data about an individual’s potential product interest.
Driving localization: Through AI’s natural language capabilities, businesses can drive local recommendations.
Managing fake reviews: 86% of purchases are adversely influenced by negative reviews; some of these bad reviews are planted by a company’s competition (astroturfing). ML boosts verified customer purchase reviews while giving preference to those marked as helpful by other users.
It’s easy to build the right AI engine for a company’s digital commerce needs. Making the technological investment today could make your solutions work far better tomorrow.
The future of healthcare is in our DNA. It always has been. Every doctor's visit, every blood test, and every x-ray ever conducted is about one key element: data. Without data, there is no information, no diagnosis, and no recommendations for treatment or recovery. Without medical data about our DNA, we—our minds, hearts, and our bodies—are eternal mysteries to science.
Modern technologies and IoT are not only changing our relationships with our doctors, but also our healthcare plans, and access to medicines and treatments, and more importantly, our relationship with ourselves.
changing the world of data. Never in the history of mankind have people had more access to what is going on inside their own bodies than right now.
Historically, visits to the doctor's office entailed a litany of questions designed to mine patients for important data regarding their calorie intake, exercise routines, sex life, smoking and drinking habits, and general lifestyles. The process was a very personal and intimate experience for patients, as they answered—often inaccurately—probing questions about their health. The truth is that people are very self-conscious about how they live and often lie about how they truly behave because revealing such personal information is, for most people, an uncomfortable experience.
IoT, however, is changing this dynamic. Data doesn't lie. Nor does it judge you for your decisions. Now that wearable technologies are commonplace, people have become accustomed to their vital signs being constantly monitored by digital technologies. In fact, today, people are more inclined to self-supervise their bodies and health decisions, instead of waiting for something to go wrong and then heading to the doctor's office. IoT has created a significant cultural shift regarding the idea of personal responsibility. More and more people are monitoring their own habits and behaviors and changing their lives based on the data in front of them, which presents undeniable truths about their health.
What began with those wearable technologies and digital devices that counted our steps and measured our heart rates has now evolved into interactive pillboxes, ingestible sensors, and even smart tattoos with special ink that changes colors based on blood sugar and dehydration levels. This next generation
With these devices, technology is now able to motivate and monitor patient’s ability to incorporate healthy routines into their lifestyles. The sad truth has been that, whether recovering from a heart attack or maintaining proper blood pressure levels, millions of patients every year fail to follow their doctor’s instructions. The consequences can be fatal. However, adherence technology could potentially save countless lives by simplifying and clarifying complex directions and providing real-time monitoring that signals the patient, and even the doctor, when a deviation from those routines requires immediate medical attention.
For decades a major inconvenience and inefficiency in healthcare management have been the siloed collection, analysis, and distribution of information. Because a person’s medical records are private information, that information remains in files that are not shared effectively throughout a patient’s lifetime, or even among various doctors and specialists throughout the course of a particular disease or affliction. The results of these outdated processes are at best frustrating, and at worst a threat to one’s health.
However, IoT and monitoring technologies collect health data in real-time, making it instantly available to both patients and doctors and easily transferable as digital data to anyone, anywhere, in the world. And with new blockchain technology—yes, the same technology that renders bitcoin transactions impervious to hacking
No longer must their condition be documented by a doctor’s illegible handwriting and ferried away in a folder into a massive file cabinet. We live in an age of unprecedented connectivity, thankfully. Life is short and IoT helps us optimize the most precious thing we all have: time.
Getting your software ready for market means taking the time to make sure it works properly.
This statement might sound obvious, but it’s serious business: Reports have shown IT departments can spend up to 35 percent of an organization’s IT budget on quality assurance and testing alone. Through DevOps and agile development, being able to find and squash bugs as quickly as possible is becoming essential in order to stay on pace toward delivering the next sprint.
But when following DevOps best practices, things can change very quickly — and the role of QA and product testing becomes more important than ever before.
When an organization chooses not to perform thorough product testing, they’re putting their product at risk and potentially losing customers and income down the line. If a company creates a poor user experience, users may simply elect not to experience a product altogether. And by cutting corners by carrying out less testing, organizations can also put themselves at risk by missing critical security vulnerabilities that can potentially leave their data — and their customers' data — within a talented hacker’s reach.
One of the best ways to take care of your ongoing QA work is through Testing as a Service (TaaS). By handing off the testing work to a trusted technology service provider like Opinov8, organizations can save valuable time and money. Allowing a dedicated team of experts to take care of the heavy lifting frees up your developers so they can continue writing their code. Embracing TaaS puts your product in front of fresh sets of eyes and cutting-edge automated applications, ensuring no stone is left unturned throughout the QA process.
Opinov8 follows best DevOps practices to deliver applications quickly and reduce the risks of defective deployments. Through automated and manual testing environments, organizations can test out any feature, product or platform. As part of a DevOps structure, your organization will have a full view of the testing process, ensuring they understand what is being checked for quality, as well as how and why.
Taking advantage of Testing as a Service means putting quality control into the hands of professionals who know how to run, check and execute any software functions with the assistance of automated tools that speed up the entire process. The result is a product that’s run through a faster and more thorough QA process. This can help complete your product development cycle in less time than ever before.
As financial technology (FinTech) continues to advance at lightning speeds, experts are wondering if traditional banks could soon be going the way of the dinosaurs. We're already using our camera phones to deposit our cheques, moving money between accounts with our banking apps, and paying our friends, entrepreneurs, and freelancers with Paypal and Google Wallet to name a few.
The last great frontier in FinTech is loans. Many people still believe that they need to trudge to their bank to apply for a loan and then wait days, even weeks, to hear if they've been approved. But FinTech is already making tremendous strides in changing the future of loans, especially with the growing public popularity of P2P loans. Keep reading to learn all about P2P loans, how they're breaking down borders created by traditional banks, and why that's a good thing.
A peer-to-peer (P2P) loan is granted without a bank's involvement. Instead, borrowers are matched with lenders over an online platform. Some of the most well-known P2P loan companies in FinTech are LendingClub, Prosper, Funding Circle, and Jimubox. The practice of P2P loans is sometimes referred to as social lending or crowdlending, too. This type of loan is most popular among small businesses and individuals looking for a personal loan.
FinTech loans boast a wide array of benefits to lenders and borrowers alike, which is why they're the second most funded sector in FinTech after payment companies. As of 2018, P2P loans are already gaining traction with millennials, but international citizens of all ages stand to benefit from these loans as well, whether they're looking to pay off a credit card, fund a medical surgery, or go back to school. So, let's break down the most valued aspects of P2P loans:
These are just some of the many, many benefits of FinTech loans. To see these P2P loans in action for yourself, try them out next time you're looking for a personal loan or extra funding for your small business.
There’s a fable told in one form or another, many times before, about “The Little Engine That Could.”
It was the end of 2017, and everyone everywhere was talking about virtual currency (cryptocurrency). Entire countries were creating their own tokens. Blockchain was the decentralized peer-to-peer technology that would be adapted well beyond the financial world for any kind of record-tracking and data storage — smart contracts, voting, securing property rights, tracking shipments, managing healthcare patient information and more secure shopping. And Bitcoin, the one crypto way out ahead of the pack in the race, reached an astounding value just under $20,000 for a single virtual coin.
Alas, the "little engine" was a little bubble. The market slumped. Bitcoin's value dropped to $5,000 (holding around $3,500 at this moment).
2018 saw the cryptocurrency market struggling on wobbly legs. Fraud and scams dominated the news and the mood. A new study revealed 80 percent of Initial Coin Offerings (ICOs) in 2017 were scams. And to boot, coin thefts from both wallets and exchanges marred further that bad reality. Adding salt on the wound, malware looks to be more and more a threat. Tough year, 2018.
Overall, the feeling among experts is encouraging. It’s less fable, more reality. Like anything that matures, lessons are learned. Hope finds new clothes, picks itself up and moves on. There is optimism:
What goes down, can go up, again — it’s about emotional investment. Declining prices and improved technologies have actually fostered some excitement out there for those looking to increase their crypto holdings.
Institutional forces are coming to the rescue. Governments are cracking down on ICOs. And Security Token Offerings (STOs) have been created. (STOs distribute tokens that actually represent a stake in a company's assets.) A lot of big money is pouring interest, especially in Bitcoin.
Cryptocurrency as a technology is advancing. For Bitcoin, growth on the Lightning Network advances. The Lightning Network is layered on top of blockchain, enabling fast transactions between participating nodes — possibly fixing the scalability problem. Ethereum also has improvements on the scalability of the platform with an update that will also improve processing times for developers and more. Justin Drake with the Ethereum foundation said of the Serenity update “[Serenity] contains various new radical ideas. Part of it is around a move from Proof of Stake (POS) away from POW. And the other big idea is sharding, so scalability — having a thousand shards compared to just one shard.”
Additionally, the acceptance has broken through of crypto in the power centers of the world. In projecting its focus on the global economy, the United Nations (UN) called cryptocurrency a “new frontier” in digital finance, noting that these digital assets and there foundational technologies such as blockchain will potentially revolutionize business and create remarkable new efficiencies.
And the UN has already dived in to IOTA to “explore how IOTA’s innovative technology — which provides an open-source distributed ledger for data management — can increase the efficiency of United Nations Office for Project Services (UNOPS) operations.” UNOPS is also keeping its eye on Ripple — a new payment protocol exciting the market at the moment.
“A sense of ethics must be innate” for anyone working in compliance, according to Anastasia Savvateeva, the Anti-Financial Crime and AML Compliance Officer for Deutsche Bank France.
In a recent interview, she mentioned she sometimes needs to explain to fledging compliance professionals the difference between compliance and ethics: “I try to explain it as simple as possible: I tell them to imagine they are cooking their favorite pumpkin soup. If they just follow the recipe — it is compliance. If they want to add something to make it better — it is ethics.”
Compliance officers (COs) ensure an organization complies with both its industry’s regulatory framework for corporate governance and its internal policies that mitigate risk, while keeping compliance costs down.
Reputation in the C-Suite will remain a cornerstone concern for all COs. In order to stay on top of the challenges they face, COs must meet the needs of success among the compliance community, as well as sustain the favor of the leaders they report to. Therefore, they must strive to meet the following goals:
Ten priorities identified for COs came out of Thomson Reuters's annual survey on the cost of compliance and the challenges financial services firms expect to face in the year ahead:
1. Stay current on skills: Assess skills tailored to all business activities.
2. Be aware of personal liability — because 48 percent of firms expect it to increase.
3. Manage conflicts of interest by reviewing governance and control arrangements.
4. Protect data both in terms of cyber resilience, hacking theft or other loss as well as with ongoing GDPR-related issues.
5. Review personal account dealing policies regarding conflicts of interest, market integrity, personal liability and financial crime.
6. Identify relevant product target markets, including cryptocurrencies, binary options and initial coin offerings.
7. Review anti-money laundering approach on all aspects of AML/CTF, bribery, corruption, fraud prevention and sanctions requirements.
8. Anticipate a regulatory investigation and ensure plans are in place.
9. Invest in RegTech, because successful deployment would drive up efficiency and effectiveness, allowing greater focus on value-added activities.
10. Focus on complaints handling regarding needs of vulnerable customers, changes to product governance expectations and the requirement for consistently good customer outcomes.
Christmas clock is ticking and people’s hearts are filled with excitement and an overwhelming desire to find out what presents they will get. No matter what someone’s hobbies or interests are, you still can think about the new gadget that will help to experience all the benefits of living in the age of technological innovations.
Here, we would like to provide you with the top 10 gadgets for Christmas that you should consider adding to your list.
Just imagine what a great present it would be for an avid reader if he could read everything he wanted without going to the bookstore or waiting for a book to be delivered by post for several days. With an e-book reader, you will save your priceless time and money. According to its characteristics, Kindle Oasis is considered to be one of the best e-readers on the market. It’s high-res, glare-free and pretty thin that will make you to enjoy the reading process.
Is Siri the only virtual assistant that is on top of things? Not really. Now you can ask Alexa to order lunch delivery, call your friend, keep track of news, check whether it’s warm enough for leaving your gloves at home and even more. Also instead of relying on third-party equipment, echo device can be connected to all smart home accessories and control it. It won’t just become your helping hand but also a stylish room accessory.
Gone are the days when it took two people to carry the projector and several months to buy it because of being pretty pricey. How about the portable and more importantly affordable Nebula Capsule Projector that will make your movie night with friends unforgettable? Considering its size, the projector provides good sound and color/image quality. However, there aren’t many alternatives on the market yet, you still can consider buying this Android built-in projector.
Is the digital photo better than the printed one? Not always. Unfortunately for most people, physical photos are the thing of the past. But sometimes we do think about hanging some memorable photos on the wall as subtle reminders of those precious and special moments of life. In this case, you should definitely consider buying a portable photo printer that can be easily connected to your smartphone with an app which in its turn will enable you to edit your photos before printing them out.
Indoor climate monitoring? Preventive Burglar light? Intrusion detection? Energy saving mode? Yes, it’s all about Anyware smart adaptor. If you were dreaming about having a smart living system in one product, then you are about to make the right choice. Isn’t it great to relax and stop worrying about your home even when you’re away? Once this portable device installed, you will be able to run various functions in your Anyware app that is designed to help you in everyday life.
Just imagine how many people are afraid of losing their keys, cameras, smartphones, bikes and how great it is that the solution is found. You can find literally everything you put the Tile on and check its last known location. It’s portable, nice and affordable. So next time when your things get lost Tile Mate is always there to help you.
With Xiaomi Vacuum Cleaner there is no need to worry about cleaning the house. With the powerful Laser Distance Sensor, the vacuum cleaner can scan the surroundings in 360 degrees and its scan rate is 1800 times per second which allows the system to build a clear path of motion and create an accurate map of the room. Mi Robot Vacuum Cleaner is equipped with a high-quality set of mechanisms to surprise you with cleanliness.
For those who are into capturing precious moments of life in a stylish square format, this camera is the best present. This camera combines the digital image capture and its film output. So it’s not just about photographing wherever you want but also about having an instant retro printed image in your hands.
Whistle 3 is on the market to track your pet’s location and activity. That’s the perfect present for the pet lovers who will know how many calories their pets burn and whether they need a longer or shorter walk on that day. All this information is based on personalized recommendations for their breed, age, and weight. What’s more, there is a money back guarantee on Whistle 3 Pet Tracker. So, in case you or your pet doesn’t like the device, there is no problem to give it back in 90 days with the full refund of the purchase price.
With the Nest Indoor Camera, you will always know what is going on at your home. Always means 24 hours a day, 7 days a week. All your recorded data is safely stored in the cloud, so there is no need to worry about privacy. Nest Cam has a built-in microphone and speaker. So you can not only see everything that happens there but also hear and speak. And yes, you can ask your pet to stop lying on a dinner table.
Brightpearl released some critical findings about cloud-based technology that should have retail brands doing a double-take. During the upcoming winter holidays, stubborn retailers that fail to embrace the newest technologies could cost themselves more than $300,000 in unnecessary expenditures. In their survey of 350 retail company heads, Brightpearl unearthed some astonishing trends that can help explain why. Retail brands and e-commerce need to migrate to the cloud to achieve cost optimization, scalability and bolster resilience during traffic surges such as Blak Friday or Holiday Season.
The survey indicated that rather than drafting a comprehensive plan to combat increased holiday demands, companies essentially throw money at the problem in a blind panic.
While temporary staff and a heightened product supply may still be helpful in combating demand surges, cloud technology makes it easy to formulate a clear, well-implemented company-wide strategy leading up to the holidays, which can play a major role in reducing unnecessary expenditures. No need for over-hiring or overstocking in hopes that the problem will simply go away.
Here are a few reasons joining the cloud could help your company fully capitalize on this year’s holiday season.
During holiday rushes, top-quality customer service is often the first thing to fall apart. Savvy retailers would do well take a page out of Apple’s book when it comes to efficiently dealing with customer transactions. At The Apple Store, all floor staff are armed with iPhones that use cloud-based technology to accept payments, complete returns and send electronic receipts. There’s no need for customers to wait in line at the cash register. The floor staff helps people find their desired product, and staff members are equipped to handle purchases without delay. With this model, Apple doesn’t need to recruit extra employees to work the register — even during the holiday rush.
Using a mobile point-of-sale device allows immediate changes to be made to a store’s cloud-based inventory. Your employees won’t be madly searching in the back for a product, because the cloud will alert them that the last unit has already been sold. In this way, businesses can reduce wasted time and allow employees to assist the next customer more quickly.
Additionally, minimizing the human error factor in store inventory decreases the odds of unnecessary overstocking. Because cloud-based technology can be accessed from anywhere in the world, you can maintain effortless communication between a store’s departments, the company branches, and even the suppliers as you enter the holiday season.
According to an IBM white paper titled Cloud Computing for Retail. In other words, a shocking 85 percent of this computing capacity is being wasted. Cloud technology turns this wasteful dynamic on its head, allowing retail brands to add and decrease incremental capacity depending on demand. Indeed, effectively using the cloud means lower installation, maintenance and IT charges for retail companies. Simply put, overall costs are consistently and reliably lower.
All in all, it’s clear that businesses would do well to join the 35 percent of retailers who are "very likely" invest in new technology. If Brightpearl’s figures are indeed accurate, retailers stand to save themselves $300,000 this holiday season — and avoid a great deal of stress in the process. Taking advantage of cloud technology now means retail companies will continue to thrive long after the holiday season comes and goes.
The future is now when it comes to cloud migration. Worldwide investment in cloud computing is predicted to double from almost $70 billion in 2015 to over $141 billion by 2019 according to a report by Forbes, so it's vital that rest of the world's companies keep pace.
Bringing your business into the cloud is an excellent move, which shows your commitment to continued growth as a company by embracing new technologies and offering a great array of services to your users. However, preparing for migration is a painstaking process that requires careful planning and strategizing. We'll show you how to avoid migration's pitfalls with this short guide.
The first step in beginning the migration process is choosing the best cloud provider for your business. With so many providers on the market, it's important to weigh your options carefully. While Amazon Web Services, Microsoft Azure, and Google Cloud Platform are the most popular options in 2017, these cloud providers aren't necessarily the best fit for your company's unique business model.
After you've selected your cloud provider, it's time to start strategizing. Migration isn't a process that happens overnight. Careful planning and strict followthrough are crucial to its success.
First, ensure your staff is ready to embrace the new cloud system. Schedule group training seminars, so everyone can learn together and ask questions in a comfortable learning environment. A certain level of downtime is expected during the migration process, but try to minimize it by preventing confusion among your employees and your users.
During this transition period, the business has to decide which applications and data should migrate first.
It's a good idea to start small by moving a few items into the cloud, and then pausing to troubleshoot for errors and to fully monitor your progress. Networks, servers, and applications don't always behave as expected post-migration. So, allow ample time to make any necessary changes, such as fixing code scripts and renegotiating bandwidth.
Remember that businesses often use different techniques to migrate everything over.
For instance, internet transfers aren't always feasible for large files. Check with your cloud provider to see if they offer alternative methods, such as shipping the physical drives by mail.
If everything goes to plan, your company's data migration should offer smooth sailing into the cloud. Once the migration is complete, be thorough and diligent in your final assessment. Your data should be fully migrated, working properly, and accessible to your employees and to your users.
Cloud migration has emerged as a game-changer for businesses of all sizes. The advantages it offers in terms of efficiency, scalability, flexibility, security, and cost reduction have made it a top priority for organizations seeking to stay competitive and agile. By transitioning from traditional on-site infrastructure to the cloud, companies can unlock a wealth of benefits that empower them to thrive in an increasingly interconnected world.
Cloud migration presents an opportunity to revolutionize the way businesses operate and manage their IT resources. With increased efficiency as one of its chief benefits, organizations can streamline their operations, focus on strategic initiatives, and alleviate the burden of managing complex on-premises infrastructure. By leveraging cloud technology, businesses can optimize their resource allocation, scaling up or down as needed without the significant costs associated with hardware and software upgrades.
Cloud computing, in essence, can be defined as the practice of storing and accessing data and programs over the Internet, instead of relying on the confines of your computer's local hard drive. As PC Mag explains, the term "cloud" serves as a metaphor for the vast Internet infrastructure, symbolized by a puffy, white cumulus cloud that effortlessly connects users and disseminates information. The cloud encompasses storage and communication, integrating voice, email, chat, and video services. Cloud migration involves transferring data, applications, or other business elements from local computers to the cloud.
Keep reading: Opinov8 offers AWS Consulting Services.
The adoption of cloud computing is reaching new heights, with Cisco Systems predicting that over 70 percent of U.S. organizations are already leveraging cloud computing models. According to the Dallas Business Journal, the impending wave of cloud migration is comparable to a tsunami. Regardless of your level of preparedness, your business will inevitably be carried along with it. Consequently, it becomes imperative to delve into the realm of cloud computing. What precisely does it entail? Why are businesses, particularly small enterprises, migrating en masse? And most importantly, what benefits await your company upon joining this transformative movement?
May interest you: Opinov8 is a Top Azure Partner and Azure Advisor.
The advantages of embracing the cloud are substantial, and it is crucial not to lag behind. Our Cloud experts (Azure, AWS, and Google) can ensure a smooth and successful transition, positioning your business for future growth and success.
Eighty-five percent of IT managers in the financial services sector say their biggest technology threat in 2018 is an online attack from cybercriminals — the most notable impact being on existing systems. Fraud incidents, alone, have increased more than 130 percent during the past year. In an October 2017 study on the cost of cyber crime conducted by the Ponemon Institute, as a direct result of cyber attacks,
“Whether managing incidents themselves or spending to recover from the disruption to the business and customers, organizations are investing on an unprecedented scale — but current spending priorities show that much of this is misdirected toward security capabilities that fail to deliver the greatest efficiency and effectiveness.” And, as attacks are on the rise, attackers are upping their game. “Criminals are evolving new business models, such as ransomware-as-a-service, which mean that attackers are finding it easier to scale cyber crime globally.”
And new threats are now. Since only after the new year, companies are scrambling with the latest warning “that hackers could take advantage of flaws discovered in chips made by Intel, AMD and ARM, which could affect nearly all computers and smartphones.”
There is no “one-size-fits-all” method for companies to follow to be cyber-secure, says Stephen Martin, director-general at the Institute of Directors in London.
He adds, “Shareholders are likely to interrogate boards more frequently on their cyber diligence and will hold them to account for failure.”
Key Findings of the Cost of Cyber Attacks:
Once data is evaluated and ranked, it is also important to know where the data lives and how it can be accessed. This might seem like common sense, but a recent EY study found that
And patching and updating protections to ward off ransomware will make a critical difference.
It’s impossible to completely prevent a breach from occurring, but proactively taking steps to ensure a company is prepared from the top-down to mitigate an attack and manage its impact is the key to reducing company-wide costs and stress.
Data protection and GDPR have taken center stage in global tech conversations — especially in the wake of the Facebook and Cambridge Analytica scandal, which exposed the personal data of at least 87 million users. On the eve of the EU’s General Data Protection Regulation (GDPR) coming into force, which introduces strict limits on how companies collect, store, and use personal data, DevOps professionals — responsible for bridging software development and IT operations—are facing a whirlwind of crisis and transformation. These teams now feel the pressure to rapidly evolve toward DevSecOps and embrace a “Security as Code” culture that embeds security practices directly into the development pipeline.
“By developing security as code, we will strive to create awesome products and services, provide insights directly to developers, and generally favor iteration over trying to always come up with the best answer before a deployment. We will operate like developers to make security and compliance available to be consumed as services. We will unlock and unblock new paths to help others see their ideas become a reality.”
DevOps, the first iteration in this evolutionary line, brought down the walls between development and operations, recognizing the necessity for a shift toward a new collaboration to give “everyone an equal seat at the table,” according to Patrick Debois, who created the movement. “The biggest advantage is the insight that we work in a system. We have to optimize for the whole system and not just for the silo. By optimizing for the whole, we are improving for the business, not just for IT.
Now, DevSecOps is in the second stage of this evolution where, seamlessly, IT security teams are immersed in these new software engineering processes, rather than outside of it. This creates a new culture where everyone is responsible for security in a continuous delivery environment. Given the present landscape of data breaches worldwide, this integration of security into DevOps — of bringing the sometimes at-odds IT security and operations teams together with a new philosophy where security is a constant in the entire operations process — serves best to “adapt our ways quickly and foster innovation to ensure data security and privacy issues are not left behind because we were too slow to change.
Ours is a new world, one where data protection and GDPR are not merely concerns for enterprises and high-value individuals. It’s now about everyone everywhere, and they’ve finally figured that out — well, at least the 2.2 billion users on Facebook. Those in data protection and GDPR compliance who are pushing DevOps teams to this precipice recognize that this perilous new world is a place where existing security models no longer work, and that a fundamental change must become systemic. “We will not wait for our organizations to fall victim to mistakes and attackers,” the manifesto says. “We will not settle for finding what is already known; instead, we will look for anomalies yet to be detected. We will strive to be a better partner by valuing what you value.”
There is no longer any doubt that data protection standards as they exist today — which have failed billions of individuals — must evolve in their processes, protocols and regulations, not only at the scale the EU’s GDPR envisions, but worldwide. At the World Economic Forum’s Annual Meeting in Davos this year, German Chancellor Angela Merkel challenged this reality within the framework of its immediacy concerning much larger social constructs. “The question ‘who owns that data?’ will decide whether democracy, the participatory social model, and economic prosperity can be combined,” she said.
Every two days, we generate as much data as we did from the dawn of time up to 2013, so the solutions will not come easy — and with every passing few days the complications become more and more manifold. Without a new cultural philosophy that tears down current divisions between software and IT security teams, these solutions cannot emerge. And as Merkel challenged, speaking to a global audience, this must be a global solution. The information age has all but eliminated the idea of silos. Populations of people may still live in countries with borders, varying cultures, values, beliefs and languages. However, information and related protection of data know no borders. This is truly international, and it demands a global effort. DevSecOps begins that work and Opinov8 Technology Services is providing a voice and opinion.
If your organization is ready to take action, fill in the form below and let’s explore how we can help you build secure, future-proof systems together.
A recent survey found that only 27% of 358 surveyed "IT and business decision makers" were satisfied with their cloud migration experience. While cloud computing is undoubtedly the way of the future, there are definitely pitfalls to be wary of along the path to applying a cloud-based model to your business. One smart way to improve your chances of a stress-free, successful migration is to properly train your employees beforehand. Read on to discover our favorite steps for ensuring that no one gets left behind during the big move to the cloud.
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Clear, precise communication now will go a long way toward minimizing confusion down the road. If you're planning to move your entire business to the cloud, your employees need to be aware of what "the cloud" means, how it stores company data, and the best ways to avoid security breaches during migration and into the future.
If your current employees aren't well-versed in cloud infrastructure, the impulse might be to simply hire new employees. However, hiring a handful of employees who understand the cloud, while the vast majority of your company does not, is a recipe for disaster. Instead,
who have demonstrated their loyalty to the company and a willingness to learn.
A 2016 survey by Softchoice calleAn image that says that 53% of IT leaders were struggling to attain the necessary cloud-centric skills for their team.d the "State of Cloud Readiness Study", in which they interviewed 500 business executives in North America, found that
This fraught workplace climate was largely attributed to an unwillingness by higher-ups to invest in training. When transitioning to the cloud, it is crucial that businesses create a positive work environment by offering thorough and professional cloud training from day one, either in-house or on an outsourced basis depending on your company's needs.
After fully training your existing employees, you may find there are still holes in your company's knowledge base. At this point,
Specialized employees, like cloud architects and cloud engineers, are currently in high demand. Be prepared to offer higher base salaries, bonuses, and other perks above your company's normal baseline when hiring for these roles. These experts can afford to be picky, but you can't afford to run a successful cloud-based business without them.
Remember, even after the cloud migration is complete, there is still work to be done. Business executives are advised to continue providing support and additional training to their employees during this transitional time. Always keep your employees aware of the company's plans for the cloud and assure them that they each play an integral, valued role inside this dynamic new sphere. A technology innovation partner like Opinov8 can help your company navigate this important transition — contact us to learn more.
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With 2018 peaking around the corner, it's prime time to make some predictions about the future of media and the entertainment industry. These innovative spheres have seen a lot of changes and growth in 2017, and now we're all set to examine which trends we should expect to evolve in the upcoming months. Keep reading to see if you agree, disagree, or want to make some wagers of your own.
With the drop in cable subscribers and TV watchers, film and television content is becoming far more curated. Of course, companies like Netflix, YouTube, and Amazon have been trailblazing this path for several years already. Indeed, 75% of Netflix's 109.25 million worldwide viewers select shows based on in-portal content suggestions.
Instead of a drive behind advertising, new episodes and movies now simply appear on our video streaming dashboard, tempting us into pressing "play.” With curated content, it's never been easier or faster to capture an audience's attention.
Consumers aren't just watching the newest episode of HBO's Game of Thrones. They're live-tweeting it, they're checking for relevant Facebook trends, and they're chatting about it afterward on Periscope. Watching television and film content at home in your pajamas isn't a solitary activity anymore. You're inviting the entire world into your living room. Entertainment providers like Netflix know this, hence they're all over social media too, interacting directly with their subscribers. For instance, check out Netflix US's Twitter account with its 3.86 million followers and you'll see they're launching polls, posting memes, and live tweeting alongside the rest of us. The goal for these providers is to stay relevant and actively involved with their multi-platform viewers.
A rising trend amongst media pitched at Millennials is "bite-sized" episodes, spanning less than 10 minutes in length. These mini-videos are being serialized on platforms like YouTube, so viewers can watch an episode during their coffee break at work. Media is conforming to our hectic lifestyles, instead of asking us to clear 30 to 60 minutes of a day to tune in.
As our last wager for 2018, expect to see more mixed reality media being launched. We can single-handedly thank Pokémon Go for this new entertainment craze. Pokémon Go launched to mass acclaim in July 2016, but as of April 2017, Business Insider reported that the game still attracted 65 million users per month. The game's continued success shows that consumers want to put themselves at the heart of the action, which mixed reality allows with its possibility to transform someone's everyday world into a dynamic gaming universe. Indeed, virtual reality (VR) is one of the fastest growing markets, according to Deloitte.
Of course, with the constant evolution of media and entertainment, we're bound to see some developments that surpass our wildest dreams. Stay tuned and keep watching! The innovations of 2018 are soon coming to an electronic screen near you.
