Legacy Application Migration

The Limitations Leading to The Need for EHR Migration Adherence to new regulatory standards Current EHR solutions, if outdated, may not align with the most recent healthcare and data processing regulations. In such cases, EHR migration to a compliant system becomes a viable solution. Request for modern, advanced EHR features For organizations wanting advanced EHR functionality, EHR data migration can be more effective than updating legacy systems. Healthcare acquisition facility When two healthcare organizations merge, the acquiring organization typically dictates operational standards. In these cases, your entity might need to undergo the EHR data migration process to synchronize with the larger provider and consolidate data into one unified system. "EHR transitions are remarkably expensive, laborious, personnel devouring, and time-consuming. Prudent planning may streamline EHR transitions and reduce expenses. Mitigating strategies, such as preservation of legacy data, managing expectations, and hiring consultants can overcome some of the greatest hurdles," National Library of Medicine, the US EHR Migration Services New Tech Stack Migration An organization may opt for application modernization through the upgrade of its tech stack instead of transitioning to the cloud. For instance, they may choose to shift from a legacy Electronic Health Records system to a modern, highly adaptable, and scalable system built on a different technology stack. This process may entail switching databases, programming languages, or other fundamental technologies. On-Premise EHR Migration to Cloud Healthcare organizations are increasingly favoring cloud-based EHR solutions because of their scalability, accessibility, and cost-effectiveness. In this case, they migrate existing data from a local server to a cloud-based EHR system. EHR migration to cloud actively improves data sharing and collaboration, reduces reliance on in-house IT infrastructure and support, and offers greater flexibility. Some might adopt a hybrid approach, keeping specific data on-site for immediate access while leveraging the cloud for other data. This strategy represents a practical compromise, combining the security and control of an on-premises system with with the benefits of a cloud solution. From Standalone to All-in-One EHR In certain situations, an organization may transition from a standalone EHR system to a comprehensive healthcare software that incorporates EHR as well as other functionalities, like practice management, billing, telehealth, and more. Such a transition could also entail the adoption of a new technology stack. Let's discuss your case! 5 Steps for Successful EHR Migration to the Cloud Having decided to migrate your EHR to the cloud, you might have concerns about potential risks. At Belitsoft, we follow a proven process ensuring secure, quick migration without interruptions. Step 1. Assessment and Planning ➤ Evaluate the current system We comprehensively assess your existing Electronic Health Record system. To achieve this, we delve into its architecture, conduct a thorough analysis of the patient data it handles, and pinpoint any customizations made over its lifespan. Such thorough scrutiny offers a detailed insight into the system's capabilities and constraints. ➤ Engage stakeholder groups Our process is inclusive. We consult your IT team to grasp technical specifications, interact with clinical staff to address workflow intricacies, and liaise with administrative personnel to understand their specific demands. This approach captures the comprehensive impact of migration. ➤ Role-based prioritization with business leaders Working closely with business leaders, we determine the priority for migrating roles. For example, we might prioritize migrating the 'account manager' role and all its related features. Once this role has been transitioned, we provide training to ensure they are well-acquainted and comfortable with the new system before progressing to the next role. ➤ Set clear objectives We define clear objectives for your EHR migration - whether it's cost savings, improved system performance, scalability, or enhanced security and compliance - to ensure everyone is on the same page. If, for instance, your current system faces compliance challenges, we'd emphasize achieving superior security and adherence to regulations. For that, we will focus on implementing data encryption, strict access controls, audit trails, training for staff, and vendor compliance. Step 2. Data Preparation ➤ EHR data cleaning Before migration, we meticulously review and refine your EHR data, eliminating inconsistencies and removing any duplicate entries or errors. This ensures a seamless transition with optimal data. ➤ EHR data mapping We determine how data from your current EHR will align with the new cloud-based EHR system. This may involve format changes or data transformation to ensure all data points align seamlessly. ➤ Datacenter location selection At this stage, we guide you in selecting a data center from providers like Amazon or Azure. It's essential to choose a center close to your business's physical location. This minimizes latency and maintains system responsiveness, especially when some functionalities are still desktop-based. Step 3. Choose the Right Cloud Provider ➤ Security and compliance We help choose a cloud provider that adheres to key healthcare regulations, like HIPAA, safeguarding EHR data and patient privacy. ➤ Scalability Anticipating future growth, we favor a cloud provider with scalable solutions. As your operations expand, your EHR system should scale effortlessly to accommodate the increased EHR data and demand. ➤ Post-Migration support and guaranteed SLAs Ensuring uninterrupted service post-migration is critical. Confirm that your chosen cloud provider offers favorable Service Level Agreements (SLAs) for responsive and efficient support, both during migration and in the long run. Step 4. Executing Migration ➤ Pilot testing During the pilot testing phase, data migration testing becomes a vital element. Here, we conduct simulations within the cloud environment using a select subset of data—patient records, medical practices and histories, treatment plans—to understand how the system behaves under various scenarios. It helps us detect potential challenges, from data integrity to system performance under load, and refine our approach before the full-scale migration. Each test, from accessing patient records to generating complex reports, entails replicating the data structure in the cloud and running various simulations. Testing also figures performance during high-use periods. Findings from this phase guide necessary refinements. ➤ Role-specific functionality migration with concurrent support We migrate functionalities based on prioritized roles while providing parallel support and training for employees. We train staff to navigate the new system for role transitions. Employee training sessions can be conducted in-person, online, or via a hybrid model, utilizing interactive modules to foster familiarity, confidence, and adeptness with the system. ➤ Data migration Data is first extracted from existing servers, ensuring its safety and completeness. This data is then transformed into a cloud-compatible format, which might include file type conversions or structure updates. Once the data is prepared, we load it into the cloud environment. We use healthcare data migration tools to automate the transfer, continuously checking for data consistency and ensuring a complete, accurate migration. ➤ Validation Post-migration, we apply a rigorous validation process to confirm data integrity. Using a sampling method, we select a subset of records and compare them to their original counterparts for accuracy. Automated scripts further scrutinize for inconsistencies, and any flagged discrepancies undergo manual review. As a result of the validation process, any necessary adjustments are made promptly, safeguarding data accuracy and completeness. Step 5. Training and Further Improvement ➤ Monitor and innovate We continuously monitor the system's performance to make requisite enhancements. Cloud deployment brings your EHR and data close to advanced tools like artificial intelligence, natural language processing, text analytics, and workflow analysis. ➤ Feedback loop We help to establish a robust feedback mechanism, setting up a channel for users to communicate challenges and suggest improvements, fostering enduring success. "Working with the right partners is key to achieving increased agility, security, innovation", HINA PATEL, Chief Growth Officer, US Health and Life Sciences, Microsoft Top Reasons for Migration from .NET to .NET Core The major reasons why you might want to consider migrating from .NET Framework to .NET Core. Faster Performance. Benchmarks show that .NET Core applications can be significantly faster than equivalent .NET Framework applications. Cross-Platform Support. NET Core is a cross-platform framework, supporting development and deployment on multiple operating systems, such as Windows, macOS, and Linux. Long-Term Support. While Microsoft declared .NET Framework 4.8 as its final major release, the focus has shifted to innovations on .NET Core and its successors, such as .NET 5 and .NET 6, which will receive continual enhancements and security updates. Cloud-Ready for Azure. .NET Core and Azure are both Microsoft technologies designed to work together seamlessly. Azure features tailored services, like Azure App Service, Azure Functions, Azure Container Instances, and Azure Kubernetes Service to streamline the deployment, management, and scaling of .NET Core applications. Future-Proof Features. .NET Core offers several advantages over the .NET Framework. Firstly, it embraces a microservices architecture, allowing for modular and scalable development. Its synergy with container tech like Docker and orchestration systems like Kubernetes ensures efficient app management and deployment. Additionally, .NET Core provides modern development tools such as command-line interface (CLI) tools and offers smooth integration with contemporary integrated development environments (IDEs) like Visual Studio Code, accessible across Windows, macOS, and Linux. Moreover, .NET Core stays up-to-date with the latest language features, ensuring developers can leverage the most recent advancements in their projects. Use Case: How Belitsoft Migrated EHR from .NET to .NET Core The US-based HeathTech company has been selling EHR solutions to healthcare organizations globally. To grow their sales and attract new clients, they needed EHR data migration experts to migrate the EHR from .NET Framework to .NET Core. This move, driven by .NET Core cross-platform capabilities, aimed to make their EHR accessible not only to Windows users but also to healthcare entities employing MacOS. Preparation Phase for EHR Data Migration Comprehensive review of the current application, its dependencies, code complexity, and tight integration with .NET Framework-specific features. Assessment of third-party and NuGet packages in the application to determine their compatibility with .NET Core or find suitable alternatives. Employment of tools like the .NET Portability Analyzer to generate a detailed report on how flexible the assemblies are. The EHR Data Migration Process Updating all NuGet packages to the most recent versions for enhanced compatibility with .NET Core. Targeting .NET Standard for maximum code reuse between .NET Framework, .NET Core, and Xamarin. Migrating the code, fixing build errors, replacing .NET Framework-specific code with .NET Core compatible equivalents. Replacing APIs that aren't available in .NET Core, with possible refactoring. Testing the application to ensure error-free builds. Deploying a new .NET Core application to a chosen environment (on-premises servers, Azure, Docker, etc.). Monitoring the app for any issues that may not have shown up during testing. Post-Migration Improvements Code refactoring to significantly improve application performance. Implementing asynchronous programming, which can help improve application performance by reducing blocking on I/O operations. Optimizing dependency injection to reduce tight coupling between classes and their dependencies, which improves code maintainability and testability. Updating libraries and packages, which might not have been compatible with the older .NET framework. Enhancing security by leveraging the built-in security features of .NET Core, such as identity and access control, clinical data protection, CORS support, and anti-forgery protection.

Belitsoft is a team of Azure migration and modernization experts with a proven track record and portfolio of projects to show for it. We offer comprehensive application modernization services, which include workload analysis, compatibility checks, and the creation of a sound migration strategy. Further, we will take all the necessary steps to ensure your successful transition to Azure cloud. Planning your migration to Azure is an important process as it involves choosing whether to rehost, refactor, rearchitect, or rebuild your applications. A laid-out Azure migration strategy helps put these decisions in perspective. Read on to find our step-by-step guide for the cloud migration process, plus a breakdown of key migration models. An investment in on-premises hosting and data centers can be a waste of money nowadays, because cloud technologies provide significant advantages, such as usage-based pricing and the capacity to easily scale up and down. In addition, your downtime risks will be near-zero in comparison with on-premises infrastructure. Migration to the cloud from the on-premises model requires time, so the earlier you start, the better. Dmitry Baraishuk Chief Innovation Officer at Belitsoft on Forbes.com Cloud Migration Process to Microsoft Azure We would like to share our recommended approach for migrating applications and workloads to Azure. It is based on Microsoft's guidelines and outlines the key steps of the Azure Migration process. 1. Strategize and plan your migration process The first thing you need to do to lay out a sound migration strategy is to identify and organize discussions among the key business stakeholders. They will need to document precise business outcomes expected from the migration process. The team is also required to understand and discover the underlying technical aspects of cloud adoption and factor them into the documented strategy. Next, you will need to come up with a strategic plan that will prioritize your goals and objectives and serve as a practical guide for cloud adoption. It begins with translating strategy into more tangible aspects like choosing which applications and workloads have higher priority for migration. You move on deeper into business and technical elements and document them into a plan used to forecast, budget, and implement your Azure migration strategy. In the end, you'll be able to calculate your total cost of ownership with Azure’s TCO calculator which is a handy tool for planning your savings and expenses for your migration project. 2. Evaluate workloads and prepare for migration After creating the migration plan you will need to assess your environment and categorize all of your servers, virtual machines, and application dependencies. You will need to look at such key components of your infrastructure as: Virtual Networks: Analyze your existing workloads for performance, security, and stability and make sure you match these metrics with equivalent resources in Azure cloud. This way you can have the same experience as with the on-premise data center. Evaluate whether you will need to run your own DNS via Active Directory and which parts of your application will require subnets. Storage Capacity: Select the right Azure storage services to support the required number of operations per second for virtual machines with intensive I/O workloads. You can prioritize usage based on the nature of the data and how often users access it. Rarely accessed (cold data) could be placed in slow storage solutions. Computing resources: Analyze how you can win by migrating to flexible Azure Virtual Machines. With Azure, you are no longer limited by your physical server’s capabilities and can dynamically scale your applications along with shifting performance requirements. Azure Autoscale service allows you to automatically distribute resources based on metrics and keeps you from wasting money on redundant computing power. To make life easier, Azure has created tools to streamline the assessment process: Azure Migrate is Microsoft’s current recommended solution and is an end-to-end tool that you can use to assess and migrate servers, virtual machines, infrastructure, applications, and data to Azure. It can be a bit overwhelming and requires you to transfer your data to Azure’s servers. Microsoft Assessment and Planning (MAP) toolkit can be a lighter solution for people who are just at the start of their cloud migration journey. It needs to be installed and stores data on-premise but is much simpler and gives a great picture of server compatibility with Azure and the required Azure VM sizes. Virtual Machine Readiness Assessment tool Is another great tool that guides the user all the way through the assessment with a series of questions. Besides the questions, it also provides additional information with regard to the question. In the end, it gives you a checklist for moving to the cloud. Create your migration landing zone. As a final step, before you move on to the migration process you need to prepare your Azure environment by creating a landing zone. A landing zone is a collection of cloud services used for hosting, operating, and governing workloads migrated to the cloud. Think of it as a blueprint for your future cloud setup which you can further scale to your requirements. 3. Migrate your applications to Azure Cloud  First of all, you can simply replace some of your applications with SaaS products hosted by Azure. For instance, you can move your email and communication-related workloads to Office 365 (Microsoft 365). Document management solutions can be replaced with Sharepoint. Finally, messaging, voice, and video-shared communications can step over to Microsoft Teams. For other workloads that are irreplaceable and need to be moved to the cloud, we recommend an iterative approach. Luckily, we can take advantage of Azure hybrid cloud solutions so there’s no need for a rapid transition to the cloud. Here are some tips for migrating to Azure: Start with a proof of concept: Choose a few applications that would be easiest to migrate, then conduct data migration testing on your migration plan and document your progress. Identifying any potential issues at an early stage is critical, as it allows you to fine-tune your strategy before proceeding. Collect insights and apply them when you move on to more complex workloads. Top choices for the first move include basic web apps and portals. Advance with more challenging workloads: Use the insights from the previous step to migrate workloads with a high business impact. These are often apps that record business transactions with high processing rates. They also include strongly regulated workloads. Approach most difficult applications last: These are high-value asset applications that support all business operations. They are usually not easily replaced or modernized, so they require a special approach, or in most cases - complete redesign and development. 4. Optimize performance in Azure cloud After you have successfully migrated your solutions to Azure, the next step is to look for ways to optimize their performance in the cloud. This includes revisions of the app’s design, tweaking chosen Azure services, configuring infrastructure, and managing subscription costs. This step also includes possible modifications when after you’ve rehosted your application, you decide to refactor and make it more compatible with the cloud. You may even want to completely rearchitect the solution with Azure cloud services. Besides this, some vital optimizations include: Monitoring resource usage and performance with tools like Azure Monitor and Azure Traffic Manager and providing an appropriate response to critical issues. Data protection using measures such as disaster recovery, encryption, and data back-ups. Maintaining high security standards by applying centralized security policies, eliminating exposure to threats with antivirus and malware protection, and responding to attacks using event management. Azure migration strategies The strategies for migrating to the Azure cloud depend on how much you are willing to modernize your applications. You can choose to rehost, refactor, rearchitect, or rebuild apps based on your business needs and goals. 1. Rehost or Lift and Shift strategy Rehosting means moving applications from on-premise to the cloud without any code or architecture design changes. This type of migration fits apps that need to be quickly moved to the cloud, as well as legacy software that supports key business operations. Choose this method if you don’t have much time to modernize your workload and plan on making the big changes after moving to the cloud. Advantages: Speedy migration with no risk of bugs and breakdown issues. Disadvantages: Azure cloud service usage may be limited by compatibility issues. 2. Refactor or repackaging strategy During refactoring, slight changes are made to the application so that it becomes more compatible with cloud infrastructure. This can be done if you want to avoid maintenance challenges and would like to take advantage of services like Azure SQL Managed Instance, Azure App Service, or Azure Kubernetes Service. Advantages: It’s a lot faster and easier than a complete redesign of architecture, allows to improve the application’s performance in the cloud, and to take advantage of advanced DevOps automation tools. Disadvantages: Less efficient than moving to improved design patterns like the transition to microservices from monolith architecture. 3. Rearchitect strategy Some legacy software may not be compatible with the Azure cloud environment. In this case, the application needs a complete redesign to a cloud-native architecture. It often involves migrating to microservices from the monolith and moving relational and nonrelational databases to a managed cloud storage solution. Advantages: Applications leverage the full power of Azure cloud with high performance, scalability, and flexibility. Disadvantages: Migrating may be tricky and pose challenges, including issues in the early stages like breakdowns and service disruptions. 4. Rebuild strategy The rebuild strategy takes things even further and involves taking apart the old application and developing a new one from scratch using Azure Platform as a service (PaaS) services. It allows taking advantage of cloud-native technologies like Azure Containers, Functions and Logic Apps to create the application layer and Azure SQL Database for the data tier. A cloud-native approach gives you complete freedom to use Azure’s extensive catalog of products to optimize your application’s performance. Advantages: Allows for business innovation by leveraging AI, blockchain, and IoT technologies. Disadvantages: A fully cloud-native approach may pose some limitations in features and functionality as compared to custom-built applications. Each modernization approach has pros and cons as well as different costs, risks and time frames. That is the essence of the risk-return principle, and you have to balance between less effort and risks but more value and outputs. The challenge is that as a business owner, especially without tech expertise, you don't know how to modernize legacy applications. Who's creating a modernization plan? Who's executing this plan? How do you find staff with the necessary experience or choose the right external partner? How much does legacy software modernization cost? Conducting business and technical audits helps you find your modernization path. Dmitry Baraishuk Chief Innovation Officer at Belitsoft on Forbes.com Professional support for your Azure migration Every migration process is unique and requires a personal approach. It is never a one-way street and there are a lot of nuances and challenges on the path to cloud adoption. Often, having an experienced migration partner can seriously simplify and accelerate your Azure cloud migration journey. Our Azure developers help you overcome cloud migration challenges through tailored planning, modernization expertise, and hands-on delivery. Let’s simplify your transition secure, efficient, and aligned with your business goals.

Why Belitsoft? With more than two decades devoted to .NET modernization, we’ve helped over 1,000 organizations achieve their technology goals - including the delivery of 200+ complex projects. After we deliver an MVP, nine out of ten customers choose to keep working with us. Our modernization work is a targeted intervention aligned with the dominant business driver in each vertical, which is why the resulting gains meet sector-specific needs. For finance - it's security and compliance, for e-commerce - it's latency under load, for healthcare - it's data integrity and privacy. The improvements after our migration and modernization efforts will be measurable - less manual work hours, lower page-load times, faster claim cycles, or higher orders per second. These KPIs are tracked before and after the cut-over, so the impact will be visible. With Belitsoft, you’ll gain cross-platform deployment, cloud scalability, and stronger security - each of which ties directly to a business advantage like lower costs, higher uptime, or audit readiness. Looking to modernize your legacy .NET applications? Belitsoft's dedicated .NET developers modernize legacy apps with minimal disruption, ensuring your systems are scalable, secure, and technologically up-to-date. Our .NET Migration Services We provide a full-spectrum offering - architecture consulting to future-proof the design, performance testing to validate speed under load, cloud deployment to land you in Azure or AWS with best-practice pipelines, and ongoing support. Every layer of the stack is covered by experts. If all you need is a tight, migration-only engagement, we’ll deliver it. Basic .NET Migration Services We specialize in straightforward "lift-and-shift" migrations that move your applications from older .NET Framework versions to the latest .NET releases (such as .NET 8 or .NET 9) with minimal code changes. We move your legacy software - whether it’s built on older versions of .NET - to the newest Microsoft .NET platform. The migration process is quick and cost-effective. We safeguard your data and keep downtime to a minimum. Our migration experts adjust each step to match your specific needs. As part of the process, we update project files, upgrade infrastructure components, such as IIS or cloud-based services, assess environment configurations, and modernize web app deployment settings, so everything aligns with current best practices.  Where data is involved, we migrate database schemas and stored procedures - whether you’re upgrading on-premises SQL Server or transitioning to Azure SQL - so your data layer remains fully compatible. The end result - once the migration is complete, your application just works, delivering the same functionality you rely on, now running on fully supported, modern technology. Enhanced .NET Modernization Services Beyond simply moving code, this type of migration elevates your application. We begin by upgrading the codebase to cross-platform .NET Core / .NET 8/9+ so you immediately benefit from the runtime’s performance and memory management gains - many organizations report 25-30% faster throughput after this step alone.  While the upgrade is underway, we profile the app, tune hot paths, and harden security: HTTPS is enforced by default, authorization is refactored using ASP.NET Core’s modern policy model, and known vulnerabilities are patched. If your legacy architecture limits agility, we refactor it - splitting monoliths into modular services or refreshing tiered designs - so the solution scales cleanly and is easier to maintain.  At the same time, we can integrate new features or UX improvements from your wish list, ensuring the product that emerges feels both familiar and unmistakably better. The result is an application that is faster, more secure, and cloud-ready - an upgrade in capability and value, not merely a change of runtime. .NET Migration Service Delivery Models We Offer Remote (Offshore) Team Our offshore delivery model lets you tap into a global pool of seasoned .NET engineers, giving you enterprise-grade expertise at a lower cost than exclusively onshore teams. To make sure distance never dilutes quality, we build in robust communication rhythms - daily stand-ups, shared sprint boards, and overlapping core hours - so questions are answered promptly and priorities stay aligned. Operating remotely also trims your overhead: you avoid extra office space and equipment costs while our teams handle the infrastructure. Throughout every sprint, collaborative tools and agile ceremonies keep progress transparent, pulling you into each decision loop and ensuring that "off-site" never feels out of sight. Time-Zone Alignment We can staff teams that work in your time zone, joining daily stand-ups and reacting to issues in real time. When using fully offshore talent for cost efficiency, we schedule guaranteed overlap windows. The result is a global team that feels local: quick hand-offs, instant feedback loops, and faster resolution of critical issues - no matter where the engineers are seated. Engagement Models Fixed-scope, one-off projects deliver a turnkey migration: we lock requirements, schedule, and price up front, then execute to meet the agreed-upon deadline and budget. This gives you maximum cost and timeline predictability while ensuring the application is fully migrated and ready for production on day one. Ongoing partnerships extend the relationship beyond the initial cutover. After go-live, our team stays embedded as a strategic extension of your IT organization - handling iterative modernization, performance tuning, future .NET upgrades, routine maintenance, and rapid troubleshooting. This continuous engagement keeps the software evergreen and lets you evolve features at the pace your business demands. Whether you need a single, predictable handoff or a long-term ally who shares your roadmap, we align our approach. Need a team fast?  We can spin up a dedicated, full-cycle team in just a few weeks, delivering approximately 170 hours per month of focused engineering capacity.  If you already have developers in place, we integrate seamlessly as team augmentation - powered by a high-velocity recruitment engine that provides certified experts exactly when you need them.  Engage us under an outsourcing model, and we take on the timeline and budget risk - freeing you to focus on the roadmap, not resourcing concerns. .NET Applications Types We Migrate Belitsoft offers end-to-end modernization across every part of a legacy application. User interfaces Desktop tools - whether WinForms, WPF, or console apps - are ported to the latest .NET so they run smoothly on Windows 11. If you have a VB.NET WinForms application, we can either move it intact onto .NET 8/9 to keep the familiar look and feel, or redesign the interface in WPF or Blazor for a more modern experience. Web-based systems We migrate classic ASP.NET Web Forms step by step into ASP.NET MVC or ASP.NET Core. Pages are replaced gradually, allowing the business to stay online during the process. If you want a new interface - React, Angular, or Blazor - we can add it on top of your existing logic, keeping functionality stable while improving the experience. The updated system runs on ASP.NET Core’s streamlined platform, giving you cleaner code, better performance, and room to scale in the cloud. Backends Legacy ASMX or WCF services are rebuilt as modern REST APIs or high-speed gRPC endpoints on .NET 8/9 and beyond. Background jobs that used to run as console or Windows services are migrated to .NET Worker Services - or Azure Functions, if you're moving to the cloud - to align with today’s DevOps and serverless models. Databases Whether you're upgrading an old SQL Server or switching to Azure SQL, we migrate your data and schema with full integrity checks. Mappings and stored procedures are updated and regression-tested, so your system picks up right where it left off - only faster, easier to maintain, and ready for what’s next. Our dedicated .NET developers deliver scalable, secure solutions handling everything from web app upgrades to cloud-ready service layers and database migrations. Let’s talk about your application migration project. .NET Migration Tools And Automation We Use Our migrations are driven by automation and repeatable tooling. When using a Code First approach, every database change is scripted as an Entity Framework Core migration, so the schema evolves incrementally, can be replayed in any environment, and never relies on manual SQL. In Database First scenarios, we work from the existing database structure and apply updates directly using specialized tools to ensure consistency and traceability. Before a single line is merged into "main", we run static code analyzers - the .NET Portability Analyzer, Roslyn-based rules, and custom security checks - to identify unsupported APIs, deprecated calls, or vulnerabilities. Changes then flow through a CI/CD pipeline in platforms such as Azure DevOps or GitHub Actions: each push triggers clean builds, automated tests, and deployment to a staging slot. That feedback loop catches integration issues or performance regressions within minutes. By the time we hand the project back, you get the fully automated build-and-release pipeline, which comes complete with green-to-green dashboards and one-click rollbacks. .NET Migration for Large Enterprises We deliver an end-to-end engagement that covers every phase - initial assessment, full-scale execution, and post-migration support - so you never manage multiple vendors. We begin with an application-portfolio assessment and a pilot migration, identifying quick wins and hidden risks, and validating tooling in a controlled setting before any large-scale cut-over. This diligence de-risks the roadmap for the most complex enterprise estates. Throughout execution, we coordinate tightly with your PMO and align to all internal compliance and security mandates, ensuring milestones, reporting, and governance dovetail with your existing processes. Because our bench spans databases, security, UI/UX, and cloud architecture, you get one-stop shopping - no need to stitch together separate specialists. As the project wraps, we provide structured knowledge transfer and training so your teams can operate, extend, and modernize the platform long after we step back.  .NET Migration for Cost-Conscious Organizations Our offshore delivery model makes large-scale migrations financially viable without compromising quality.  By tapping into global talent pools, we assign specialized .NET engineers to each task - often at significantly lower rates than fully onshore teams - and pass those savings directly to you.  Mature processes, overlapping work hours, and disciplined communication rhythms eliminate common offshore pitfalls, keeping progress fast and expectations clear.  This approach allows you to modernize mission-critical systems within tight budgets, rescuing projects that might otherwise have been shelved due to cost. .NET Migration for Internal Development Teams We serve as an on-demand extension of your engineering staff, stepping in wherever your migration hits a skills gap. Whether the sticking point is a VB6 module, an Entity Framework data layer, or a cloud uplift to Azure, our specialists plug directly into your workflow to tackle the hardest problems. Collaboration is hands-on: pair programming sessions, structured code reviews, and quick-fire whiteboard problem-solving all happen in real time. Along the way, we can mentor your developers - explaining design choices, demonstrating modern patterns, and sharing practical tips. By project close, you gain a fully modernized application and an upskilled in-house team equipped with the confidence and knowledge to own the codebase going forward. Book a free migration assessment or request a no-obligation cost estimate today.

Technical and Organizational Capabilities Required To migrate from Power BI Premium to Microsoft Fabric, companies need to build up both the tech skills and the organization’s muscle to handle the shift. Broad Technical Skill Set Fabric brings everything under one roof: data integration (Data Factory), engineering (Spark, notebooks), warehousing (Synapse SQL), and classic BI (Power BI). But with that comes a shift in expectations. Knowing Power BI isn’t enough anymore. Your team needs to be fluent in SQL, DAX, Python, Spark, Delta Lake. If they are coming from a dashboards-and-visuals world, this is a whole new ballgame. The learning curve is real, especially for teams without deep data engineering experience. Data Architecture & Planning Fabric is a greenfield environment, which means full flexibility, but zero guardrails. No out-of-the-box structure, no default best practices. That’s great if you’ve got strong data architects. If not, it’s a recipe for chaos. Building from scratch means you need to get it right early: workflows, pipelines, modeling. Think long-term from day one. Use of medallion architecture in OneLake is a good example of doing it right. In highly regulated sectors like healthcare and fintech, a BI consultant with domain knowledge can help define early architecture that supports compliance, governance, and long-term scalability from the ground up. Cross-Functional Collaboration Fabric brings everyone into the same space: data engineers, BI devs, data scientists. The roles that used to sit apart are now working side by side. That’s why it’s not just a platform shift, it’s a team shift. Companies need to start building cross-disciplinary teams and getting departments to actually collaborate; not just hand stuff off. In some cases, that means spinning up a central DataOps team or a center of excellence to keep things from drifting. Governance and Data Management Companies should have or develop capabilities in data governance, security, and compliance that span multiple services. Fabric doesn’t automatically centralize governance across its components, so skills with tools like Microsoft Purview for metadata management and lineage can help fill this gap. Role-based access controls, workspace management, and policies need to be enforced consistently across the unified environment. DevOps and Capacity Management Fabric isn’t set-it-and-forget-it. It runs on Azure capacities, and depending on how you set it up, you might be dealing with a pay-as-you-go model instead of fixed capacity. That means teams need to know how to monitor and tune resource usage: things like how capacity units get eaten up, when to scale, and how to schedule workloads so you are not burning money during off-hours. Without that visibility, performance takes a hit or costs spiral. A FinOps mindset helps here. Someone has got to keep an eye on the meter. Training and Change Management Teams used to Power BI will need training on new Fabric features (Spark notebooks, pipeline orchestration, OneLake, etc.). Given the multi-tool complexity of Fabric, investing in upskilling, workshops, or pilot projects will help the workforce adapt. Leadership support and clear communication of the benefits of Fabric will ease the transition for end-users as well as IT staff. Common Migration Challenges and Pitfalls Moving from Power BI Premium to Fabric isn’t always smooth. There are plenty of traps teams fall into early on. Knowing what can go wrong helps you plan around it and avoid wasting time (or budget) fixing preventable problems. Fabric introduces new tools, new architecture, and a different pricing model. That means new skills, planning effort, and real risk if teams go in blind. The pain comes when companies skip the preparation stage. Tooling Complexity & Skill Gaps One of the big hurdles with Fabric is the skill gap. It casts a wide net: no single person or team is likely to have it all from the start. You might have great Power BI and DAX folks, but little to no experience with Spark or Python. That slows things down and leads to underused features. Mastering Fabric requires expertise across a wide range of tools spanning data engineering, analytics, and BI. Without serious upskilling, teams risk falling back on old habits, like using the wrong tools for the job or missing what Fabric can actually do. Steep Learning Curve & Lack of Best Practices Fabric is still new, and the playbook is not fully written yet. Microsoft offers docs and templates (mostly lifted from Synapse and Data Factory) but there is no built-in framework for how to actually structure your projects. You are starting with a blank slate. That freedom can backfire if teams wing it without clear guidance. Without predefined standards, organizations have to create their own rules: workspace setup, naming conventions, data lake zones, all of it. And until that settles, most teams go through a trial-and-error phase that slows things down. Fragmented or Redundant Solutions Fabric gives you a few different ways to do the same thing, like loading data through Pipelines, Dataflows, or notebooks. That sounds flexible, but it often leads to confusion. Teams start using different tools for the same job, without talking to each other. That is how you end up with duplicate workflows and zero visibility. Unless you set clear rules on what to use and when, things drift fast. Capacity and Licensing Surprises Fabric doesn’t use fixed capacity like Power BI Premium. It runs on compute units: scale up, down, pause. You pay for usage. Sounds fine. Until you get the bill. Teams pick F32 to save money. But anything below F64 drops free viewing. Now every report needs a Pro license. Under Premium? Included. Under Fabric? Extra cost. And most teams don’t see it coming. Plenty of companies that switched to F32 thinking they were optimizing costs got hit later with Pro license expenses. Want the same viewer access as P1? You’ll need at least F64. That can cost 25–70% more, depending on setup. There are ways to manage it (annual reservations, Azure commit discounts) but only if you plan before migration. Not after. Data Refresh and Downtime Considerations The mechanics of migrating workspaces are straightforward (reassigning workspaces to the new capacity), but there are operational gotchas. When you migrate a workspace, any active refresh or query jobs are canceled and must be rerun, and scheduled jobs resume only after migration. If not carefully timed, this could disrupt data refresh schedules. Customers may need to “recreate scheduled jobs” or at least verify them post-migration to ensure continuity. Planning a hybrid migration (running old and new in parallel) can mitigate disruptions. Rely on Belitsoft technology experts to use their in-depth knowledge, broad expertise, and strategic thinking to assist you in legacy migration to Microsoft Fabric, while minimizing downtime and ensuring continuity. Resource Management Pitfalls Fabric lets you pause or scale capacity. Sounds like a good way to save money. But when a capacity is paused, nothing runs — not even imported datasets. Reports go dark. Companies with global teams or 24/7 access needs quickly learn: pausing overnight isn’t an option. There’s another catch: all workloads share the same compute pool. So if a heavy Spark job or dataflow kicks off, it can choke your BI reports unless you plan around it. Premium users didn’t have to think about this: those systems were separate. Now it’s on you to tune compute (CUs), schedule jobs smartly, and monitor usage in real time. Ignore that, and you’ll hit capacity walls: slow reports, failed jobs, or both. Pricing and Licensing Differences One of the biggest changes in moving to Fabric is the pricing and licensing model. Below is a comparison of key differences between Power BI Premium (per capacity) and Microsoft Fabric. Aspect Power BI Premium (P SKUs) Microsoft Fabric (F SKUs) Capacities and Scale Fixed capacity tiers P1–P5 (e.g. P1 = 8 v-cores). No smaller tier below P1. Scaling requires purchasing the next tier up. Flexible capacity sizes (F2, F4, F8, F32, F64, F128, …). Can choose much smaller units than old P1 if needed. Supports scaling out or pausing capacity in Azure portal. Included Workloads Analytics limited to Power BI (datasets, reports, dashboards, AI visuals, some dataflows). Other services (ETL, data science) require separate Azure products. All-in-one platform: Includes Power BI (equivalent to Premium features) plus Synapse (Spark, SQL), Data Factory, real-time analytics, OneLake, etc. Superset of data capabilities. User Access Model Unlimited report consumption by free users on content in a Premium workspace (no per-user license needed for viewers). Unlimited free-user consumption only on F64 and above. Smaller SKUs require Pro/PPU licenses for viewers. On-Premises Report Server Power BI Report Server (PBIRS) included with P1–P5 as dual-use right. PBIRS included with F64+ reserved capacity. Pay-as-you-go SKUs need separate license. Purchase & Billing Purchased via M365 admin center as subscription (monthly/annually). Fixed cost. Not counted toward Azure commitments. Purchased via Azure (Portal or subscription). Pay-as-you-go or reserved. Eligible for Azure Consumption Commitments (MACC). Cost Level (Capacity) P1 = $4,995/month. Higher SKUs scale linearly (P2 ~$10k, P3 ~$20k). F64 = ~$8,409.60/month pay-as-you-go. F32 = ~$4,204.80/month. More features included. Scaling and Pausing No dynamic scaling. Capacity is always running. No pause option. Can scale up/down or pause capacity in Azure. Pausing stops charges but also suspends access. Future Roadmap Power BI Premium per capacity is being phased out (no new purchases after 2024; sunset in 2025). Fabric is the future. All new features (Direct Lake, Copilot, OneLake) are in Fabric. Key takeaways on pricing/licensing Existing Power BI Premium customers will need to transition to an F SKU at their renewal (unless on a special agreement). In doing so, they should prepare for potential cost increases at equivalent capacity levels, although Fabric’s flexibility (smaller SKUs or scaling down) can offset some costs if used wisely. The benefits of Fabric’s model include more granular scaling, alignment with Azure billing (useful if you have Azure credits), and access to a broader set of tools under one price. The downsides include complexity in cost management and the need to adjust to Azure’s billing cycle. Careful analysis is recommended to choose the right capacity (F SKU) so that performance and user access needs are met without overspending. Use Cases and Success Stories of Fabric Migration Several organizations have already made the leap from Power BI Premium to Microsoft Fabric. These real-world case studies highlight the motivations for migration and the benefits achieved. Flora Food Group – Consolidation and Real-Time Insights Flora Food Group, a global plant-based food company, was juggling Synapse, Data Factory, and Power BI as separate tools. Too many moving parts. They decided to consolidate everything into Fabric. The move wasn’t rushed. They ran Fabric alongside their legacy stack and started with the big datasets. They used a medallion architecture (bronze-silver-gold) in OneLake to build a single source of truth. From there, the upside came fast: Unified setup — reporting, engineering, science, and security in one stack Better reporting — centralized semantic models made data reuse easy Direct Lake — killed the need for scheduled refreshes; reports now pull fresh data near real time Lower waste — idle compute from one workload now powers another Faster BI teams — integrated tools meant fewer handoffs and less prep time According to their Head of Data & Insight, the migration simplified their architecture and cut costs, while boosting capability. They see it as a strategic step toward what’s next: AI-powered analytics with Fabric Copilot. BDO Belgium – Scalable Analytics for Mergers & Acquisitions BDO Belgium was hitting walls with Power BI Premium, especially during M&A due diligence, where speed and clarity are non-negotiable. So they built a new analytics platform on Fabric. They called it Data Eyes. The shift paid off: Faster insights — better performance on large, complex datasets Self-service access — finance teams explored data without writing code One interface — familiar to users, powerful at scale Simpler backend — IT maintains one platform, not a patchwork Fabric gave them what Power BI alone couldn’t: a system that handles scale and puts data in the hands of non-technical users. For BDO, it wasn’t just an upgrade; it changed how the business works with data. Other Early Adopters Many organizations that were already invested in the Microsoft data stack find Fabric a natural progression.  Some companies reported that Fabric’s unified approach streamlined their data engineering pipelines and BI. They cite benefits like reducing data duplication (thanks to OneLake) and easier enforcement of security in one place rather than across multiple services.  Fabric’s integration of AI (Copilot for data analysis) is seen as an advantage.  The pattern is that companies migrating from Power BI Premium experience improvements in data freshness, collaboration, and total cost of ownership when they leverage the full Fabric ecosystem of tools. Value comes from utilizing Fabric’s broader capabilities rather than treating it as a like-for-like replacement of Power BI Premium.  Organizations that approach the migration as an opportunity to modernize their data architecture (as Flora did with medallion architecture and real-time data, or BDO did with an intuitive analytics app) tend to reap the most benefits. They achieve not just a seamless transition of existing reports, but also new insights and efficiencies that were previously difficult or impossible with the siloed tool approach. Implications of Not Migrating to Fabric Given Microsoft’s strategic direction, companies that choose not to migrate from Power BI Premium to Fabric face several implications in terms of features, support, and long-term viability. Feature Limitations Fabric isn’t just the next version of Power BI. It’s a superset. Staying on Power BI Premium means missing the features Microsoft is building for the future. No OneLake. No Direct Lake. No unified data layer. No Spark workloads. No Copilot. No built-in AI. Those are Fabric-only. If you stay on Premium, your analytics stack stays frozen. Fabric keeps evolving: with deeper integration, faster performance, and cloud-scale features. You can bolt on Azure services to replicate some of it, but that means extra setup, extra cost, and more moving parts. Support and Updates Microsoft is ending Power BI Premium per capacity SKUs. New purchases stop mid-2024. Renewals end in 2025. What that means: you’ll need to move to Fabric if you want to keep using the platform. There’s a temporary bridge: existing Premium customers can access some Fabric features inside their current capacity. But that’s a short-term patch. Not a strategy. Once your legacy agreement runs out, so does your support. No new features. No roadmap. Just a countdown to disruption. Fabric is the future. Microsoft’s made that clear.   Potential Cost of Inaction Delaying Fabric may seem easier in the short term, but the cost shifts elsewhere. Power BI Report Server won’t be bundled once Premium SKUs are retired. It will require separate licensing through SQL Server Enterprise + SA. Fabric also consolidates multiple tools (ETL, warehouse, reporting) into a single platform. Staying on the old stack means paying for them separately. Microsoft is offering 30 days of free Fabric capacity during transition. After that, migration gets more expensive and less flexible. Long-Term Roadmap Alignment After 2025, support for legacy Premium issues could slow down - because engineering focus will be on Fabric. Eventually, the Power BI Premium brand itself may disappear. Holdouts will face a bigger, messier migration later: with more change to absorb, less time to adapt. Early movers get the opposite: smoother transition, room to adjust, and a seat at the table. Microsoft is still shaping Fabric. Companies that migrate now can influence what comes next. Choosing not to migrate to Fabric is not a risk-free stance. In the immediate term (for those with existing Premium deployments), it means missing out on new capabilities and efficiencies. In the medium term (by 2025), it becomes a support risk as the old licensing model is phased out. While organizations can continue with Power BI Pro or Premium Per User for basic needs (these are not impacted by the capacity SKU retirement), larger scale analytics initiatives will increasingly require Fabric to stay on the cutting edge. Therefore, companies should weigh the cost of migration against the cost of stagnation. Most will find that a planned migration, even if challenging, is the prudent path to ensure they remain supported and competitive in their analytics capabilities. How Belitsoft can Help Fabric migration touches architecture, governance, training, and cost models. Experienced providers like Belitsoft have built services around it: assessment, design, workspace migration, policy setup, user onboarding. All mapped to Fabric’s structure. We use automation and phased rollout to reduce downtime and avoid rework. Engagements are flexible: fixed-price or T&M, depending on environment size and scope. With the right setup, you'll move faster and start using unified workloads, AI features, and performance gains. Fabric requires a diverse skill set spanning Power BI, SQL, Python, Spark, Delta Lake, and data engineering, far beyond traditional dashboard development. By outsourcing our BI development services, you get dedicated BI and data engineering experts with hands-on experience in Power BI modernization and migration to ensure a smooth transition, while introducing automated pipelines and AI-driven analytics. Contact for a consultation.

Why Financial Institutions Migrate Data Legacy systems are dragging them down Most migrations start because something old is now a blocker. Aging infrastructure no one wants to maintain, systems only one person understands (who just resigned), workarounds piled on top of workarounds. Eventually, the cost of not migrating becomes high. Compliance doesn’t wait New regulations show up, and old systems cannot cope. GDPR, SOX, PCI, local data residency rules. New audit requirements needing better lineage, access logs, encryption. If your platform cannot prove control, migration becomes the only way to stay in business. M&A forces the issue When banks merge or acquire, they inherit conflicting data structures, duplicate records, fragmented customer views. The only path forward is consolidation. You cannot serve a unified business on mismatched backends. Customer expectations got ahead of tech Customers want mobile-first services, real-time transactions and personalized insights. Legacy systems can’t provide that. They weren’t designed to talk to mobile apps, stream real-time data, or support ML-powered anything.  Analytics and AI hit a wall You can’t do real analytics if your data is trapped in ten different systems, full of gaps and duplicates, updated nightly via broken ETL jobs. Modern data platforms solve this. Migrations aim to centralize, clean, and connect data. Cost pressure from the board Everyone says "cloud saves money." That’s only half true. If you’re running old on-premises systems with physical data centers, licenses, no elasticity or automation …then yes, the CFO sees migration as a way to cut spending. However, smart teams don’t migrate for savings alone. They migrate to stop paying for dysfunction. Business wants agility. IT can’t deliver When the business says "launch a new product next quarter," and IT says "that will take 8 months because of system X," migration becomes a strategy conversation. Cloud-native platforms, modern APIs, and scalable infrastructure are enablers. But you can’t bolt them onto a fossil. Core system upgrades that can’t wait anymore This is the "we’ve waited long enough" scenario. A core banking system that can’t scale. A data warehouse from 2007. A finance platform with no support. It’s not a transformation project. It’s triage. You migrate because staying put means stagnation, or worse, failure, during a critical event. We combine automated tools and manual checks to find hidden risks early before they become problems through a discovery process, whether you’re consolidating systems or moving to the cloud. Database Migration Strategy Start by figuring out what you really have Inventory is what prevents a disaster later. Every system, every scheduled job, every API hook: it all needs to be accounted for. Yes, tools like Alation, Collibra, and Apache Atlas can speed it up, but they only show what is visible. The real blockers are always the things nobody flagged: Excel files with live connections, undocumented views, or internal tools with hard-coded credentials. Discovery is slow, but skipping it just means fixing production issues after cutover. Clean the data before you move it Bad data will survive the migration if you let it. Deduplication, classification, and data profiling must be done before the first trial run. Use whatever makes sense: Data Ladder, Spirion, Varonis. The tooling is not the hard part. The problem is always legacy data that does not fit the new model. Data that was fine when written is now inconsistent, partial, or unstructured. You cannot automate around that. You clean it, or you carry it forward. Make a real call on the strategy - not just the label Do not pick a migration method because a vendor recommends it. Big Bang works, but only if rollback is clean and the system is small enough that a short outage is acceptable. It fails hard if surprises show up mid-cutover. Phased is safer in complex environments where dependencies are well-mapped and rollout can be controlled. It adds overhead, but gives room to validate after each stage. Parallel (or pilot) makes sense when confidence is low and validation is a high-priority. You run both systems in sync and check results before switching over. It is resource-heavy, you are doubling effort temporarily, but it removes guesswork. Hybrid is a middle ground. Not always a cop-out, it can be deliberate, like migrating reference data first, then transactions. But it requires real planning, not just optimism. Incremental (trickle) migration is useful when zero downtime is required. You move data continuously in small pieces, with live sync. This works, but adds complexity around consistency, cutover logic, and dual writes. It only makes sense if the timeline is long. Strategy should reflect risk, not ambition. Moving a data warehouse is not the same as migrating a trading system. Choose based on what happens when something fails. Pilot migrations only matter if they are uncomfortable Run a subset through the full stack. Use masked data if needed, but match production volume. Break the process early. Most failures do not come from the bulk load. They come from data mismatches, dropped fields, schema conflicts, or edge cases the dev team did not flag. Pilot migrations are there to surface those, not to "prove readiness." The runbook is a plan, not a document If people are confused during execution, the runbook fails. It should say who does what, when, and what happens if it fails. All experts emphasize execution structure: defined rollback triggers, reconciliation scripts, hour-by-hour steps with timing buffers, a plan B that someone has actually tested. Do not rely on project managers to fill in gaps mid-flight. That is how migrations end up in the postmortem deck. Validation is part of the job, not the cleanup If you are validating data after the system goes live, you are already late. The validation logic must be scripted, repeatable, and integrated, not just "spot checked" by QA. This includes row counts, hashing, field-by-field matching, downstream application testing, and business-side confirmation that outputs are still trusted. Regression testing is the only way to tell if you broke something. Tools are fine, but they are not a strategy Yes, use DMS, Azure Data Factory, Informatica, Google DMS, SchemaSpy, etc. Just do not mistake that for planning. All of these tools fail quietly when misconfigured. They help only if the underlying migration plan is already clear, especially around transformation rules, sequence logic, and rollback strategy. The more you automate, the more you need to trust that your input logic is correct. Keep security and governance running in parallel Security is not post-migration cleanup. It is active throughout. Access must be scoped to migration-only roles PII must be masked in all non-prod runs Logging must be persistent and immutable Compliance checkpoints must be scheduled, not reactive Data lineage must be maintained, especially during partial cutovers This is not a regulatory overhead. These controls prevent downstream chaos when audit, finance, or support teams find data inconsistencies. Post-cutover is when you find what you missed No matter how well you planned, something will break under load: indexes will need tuning, latency will spike, some data will have landed wrong, even with validation in place, reconciliations will fail in edge cases and users will see mismatches between systems. You need active monitoring and fast intervention windows. That includes support coverage, open escalation channels, and pre-approved rollback windows for post-live fixes. Compliance, Risk, and Security During Migration Data migrations in finance are high-risk by default. Regulations do not pause during system changes. If a dataset is mishandled, access is left open, records go missing, the legal and financial exposure is immediate. Morgan Stanley was fined after failing to wipe disks post-migration. TSB’s failed core migration led to outages, regulatory fines, and a permanent hit to customer trust. Security and compliance are not post-migration concerns. They must be integrated from the first planning session. Regulatory pressure is increasing The EU’s DORA regulation, SEC cyber disclosure rules, and ongoing updates to GDPR, SOX, and PCI DSS raise the bar for how data is secured and governed.  Financial institutions are expected to show not just intent, but proof: encryption in transit and at rest, access logs, audit trails, and evidence that sensitive data was never exposed, even in testing. Tools like Data Ladder, Spirion, and Varonis track PII, verify addresses, and ensure that only necessary data is moved. Dynamic masking is expected when production data is copied into lower environments. Logging must be immutable. Governance must be embedded. Strategy choice directly affects your exposure The reason phased, parallel, or incremental migrations are used in finance has nothing to do with personal preference - it is about control. These strategies buy you space to validate, recover, and prove compliance while the system is still under supervision. Parallel systems let you check both outputs in real time. You see immediately if transactional records or balances do not match, and you have time to fix it before going live. Incremental migrations, with near-real-time sync, give you the option to monitor how well data moves, how consistently it lands, and how safely it can be cut over - without needing full downtime or heavy rollback. The point is not convenience. It is audit coverage. It is SLA protection. It is a legal defense. How you migrate determines how exposed you are to regulators, to customers, and to your own legal team when something goes wrong, and the logs get pulled. Security applies before, during, and after the move Data is not less sensitive just because it is moving. Testing environments are not immune to audit. Encryption is not optional - and access controls do not get a break. This means: Everything in transit is encrypted (TLS minimum) Storage must use strong encryption (AES-256 or equivalent) Access must be restricted by role, time-limited, logged, and reviewed Temporary credentials are created for migration phases only Any non-production environment gets masked data, not copies Belitsoft builds these controls into the migration path from the beginning - not as hardening after the fact. Access is scoped. Data is verified. Transfers are validated using hashes. There is no blind copy-and-paste between systems. Every step is logged and reversible. The principle is simple: do not treat migration data any differently than production data. It will not matter to regulators that it was "temporary" if it was also exposed. Rely on Belitsoft’s database migration engineers and data governance specialists to embed security, compliance, and auditability into every phase of your migration. We ensure your data remains protected, your operations stay uninterrupted, and your migration meets the highest regulatory standards. Reconciliation is the compliance checkpoint Regulators do not care that the migration was technically successful. They care whether the balances match, the records are complete, and nothing was lost or altered without explanation. Multiple sources emphasize the importance of field-level reconciliation, automated validation scripts, and audit-ready reports. During a multi-billion-record migration, your system should generate hundreds of real-time reconciliation reports. The mismatch rate should be in the double digits, not thousands, to prove that validation is baked into the process. Downtime and fallback are also compliance concerns Compliance includes operational continuity. If the system goes down during migration, customer access, trading, or payment flows can be interrupted. That triggers not just customer complaints, but SLA penalties, reputational risk, and regulator involvement. Several strategies are used to mitigate this: Maintaining parallel systems as fallback Scheduling cutovers during off-hours with tested recovery plans Keeping old systems in read-only mode post-cutover Practicing rollback in staging Governance must be present, not implied Regulators expect to see governance in action, not in policy, but in tooling and workflow: Data lineage tracking Governance workflows for approvals and overrides Real-time alerting for access anomalies Escalation paths for risk events Governance is not a separate track, it is built into the migration execution. Data migration teams do this as standard. Internal teams must match that discipline if they want to avoid regulatory scrutiny. No margin for "close enough" In financial migrations, there is no tolerance for partial compliance. You either maintained data integrity, access control, and legal retention, or you failed. Many case studies highlight the same elements: Drill for failure before go-live Reconcile at every step, not just at the end Encrypt everything, including backups and intermediate outputs Mask what you copy Log everything, then check the logs Anything less than that leaves a gap that regulators, or customers, will eventually notice. Database Migration Tools There is no single toolset for financial data migration. The stack shifts based on the systems involved, the state of the data, and how well the organization understands its own environment. Everyone wants a "platform" - what you get is a mix of open-source utilities, cloud-native services, vendor add-ons, and custom scripts taped together by the people who have to make it work. Discovery starts with catalogs Cataloging platforms like Alation, Collibra, and Apache Atlas help at the front. They give you visibility into data lineage, orphaned flows, and systems nobody thought were still running. But they’re only as good as what is registered. In every real migration, someone finds an undocumented Excel macro feeding critical reports. The tools help, but discovery still requires manual effort, especially when legacy platforms are undocumented. API surfaces get mapped separately. Teams usually rely on Postman or internal tools to enumerate endpoints, check integrations, and verify that contract mismatches won’t blow up downstream. If APIs are involved in the migration path, especially during partial cutovers or phased releases, this mapping happens early and gets reviewed constantly. Cleansing and preparation are where tools start to diverge You do not run a full migration without profiling. Tools like Data Ladder, Spirion, and Varonis get used to identify PII, address inconsistencies, run deduplication, and flag records that need review. These aren’t perfect: large datasets often require custom scripts or sampling to avoid performance issues. But the tooling gives structure to the cleansing phase, especially in regulated environments. If address verification or compliance flags are required, vendors like Data Ladder plug in early, especially in client record migrations where retention rules, formatting, or legal territories come into play. Most of the transformation logic ends up in NiFi, scripts, or something internal For format conversion and flow orchestration, Apache NiFi shows up often. It is used to move data across formats, route loads, and transform intermediate values. It is flexible enough to support hybrid environments, and visible enough to track where jobs break. SchemaSpy is commonly used during analysis because most legacy databases do not have clean schema documentation. You need visibility into field names, relationships, and data types before you can map anything. SchemaSpy gives you just enough to start tracing, but most of the logic still comes from someone familiar with the actual application. ETL tools show up once the mapping is complete. At this point, the tools depend on environment: AWS DMS, Google Cloud DMS, and Azure Data Factory get used in cloud-first migrations.AWS Schema Conversion Tool (SCT) helps when moving from Oracle or SQL Server to something modern and open. On-prem, SSIS still hangs around, especially when the dev team is already invested in it. In custom environments, SQL scripts do most of the heavy lifting — especially for field-level reconciliation and row-by-row validation. The tooling is functional, but it’s always tuned by hand. Governance tooling Platforms like Atlan promote unified control planes: metadata, access control, policy enforcement, all in one place. In theory, they give you a single view of governance. In practice, most companies have to bolt it on during migration, not before. That’s where the idea of a metadata lake house shows up: a consolidated view of lineage, transformations, and access rules. It is useful, especially in complex environments, but only works if maintained. Gartner’s guidance around embedded automation (for tagging, quality rules, and access controls) shows up in some projects, but not most. You can automate governance, but someone still has to define what that means. Migration engines Migration engines control ETL flows, validate datasets, and give a dashboard view for real-time status and reconciliation. That kind of tooling matters when you are moving billions of rows under audit conditions. AWS DMS and SCT show up more frequently in vendor-neutral projects, not because they are better, but because they support continuous replication, schema conversion, and zero-downtime scenarios. Google Cloud DMS and Azure Data Factory offer the same thing, just tied to their respective platforms. If real-time sync is required, in trickle or parallel strategies, then Change Data Capture tooling is added. Some use database-native CDC. Others build their own with Kafka, Debezium, or internal pipelines. Most validation is scripted. Most reconciliation is manual Even in well-funded migrations, reconciliation rarely comes from off-the-shelf tools. Companies use hash checks, row counts, and custom SQL joins to verify that data landed correctly. In some cases, database migration companies build hundreds of reconciliation reports to validate a billion-record migration. No generic tool gives you that level of coverage out of the box. Database migration vendors use internal frameworks. Their platforms support full validation and reconciliation tracking and their case studies cite reduced manual effort. Their approach is clearly script-heavy, format-flexible (CSV, XML, direct DB), and aimed at minimizing downtime.  The rest of the stack is coordination, not execution. During cutover, you are using Teams, Slack, Jira, Google Docs, and RAID logs in a shared folder. The runbook sits in Confluence or SharePoint. Monitoring dashboards are built on Prometheus, Datadog, or whatever the organization already uses.  What a Serious Database Migration Vendor Brings (If They’re Worth Paying) They ask the ugly questions upfront Before anyone moves a byte, they ask, What breaks if this fails? Who owns the schema? Which downstream systems are undocumented? Do you actually know where all your PII is? A real vendor runs a substance check first. If someone starts the engagement with "don’t worry, we’ve done this before," you’re already in danger. They design the process around risk, not speed You’re not migrating a blog. You’re moving financial records, customer identities, and possibly compliance exposure. A real firm will: Propose phased migration options, not a heroic "big bang" timeline Recommend dual-run validation where it matters Build rollback plans that actually work Push for pre-migration rehearsal, not just “test in staging and pray” They don’t promise zero downtime. They promise known risks with planned controls. They own the ETL, schema mapping, and data validation logic Real migration firms write: Custom ETL scripts for edge cases (because tools alone never cover 100%) Schema adapters when the target system doesn’t match the source Data validation logic - checksums, record counts, field-level audits They will not assume your data is clean. They will find and tell you when it’s not - and they’ll tell you what that means downstream. They build the runbooks, playbooks, and sanity checks This includes: What to do if latency spikes mid-transfer What to monitor during cutover How to trace a single transaction if someone can’t find it post-migration A go/no-go checklist the night before switch The good ones build a real migration ops guide, not a pretty deck with arrows and logos, but a document people use at 2AM. They deal with vendors, tools, and infrastructure, so you don’t have to They don’t just say "we’ll use AWS DMS." They provision it, configure it, test it, monitor it, and throw it away clean. If your organization is multi-cloud or has compliance constraints (data residency, encryption keys, etc.), they don’t guess; they pull the policies and build around them. They talk to your compliance team like adults Real vendors know: What GDPR, SOX, PCI actually require How to write access logs that hold up in an audit How to handle staging data without breaking laws How to prepare regulator notification packets if needed They bring technical project managers who can speak of "risk", not just "schema." So, What You’re Really Hiring You’re not hiring engineers to move data. You’re hiring process maturity, disaster recovery modeling, DevOps with guardrails and legal fluency. With 20+ years of database development and modernization expertise, Belitsoft owns the full technical execution of your migration - from building custom ETL pipelines to validating every transformation across formats and platforms. Contact our experts to get a secure transition, uninterrupted operations, and a future-proof data foundation aligned with the highest regulatory standards.

Business First Mindset before Migration to SaaS One of the key concepts here is having a business mindset first and a technical approach second. The move to SaaS begins with business strategy and goals. Do not let the technical aspects pressure you to rush with your SaaS migration process.  Your business needs have a definite influence on the path and the top priorities for your SaaS project migration.  When crafting your strategy, focus on the questions that unleash the most about what your future product will look like:  How can SaaS help us grow our business? Which segments are we targeting? What is the size and profile of these segments? What tiers will we need to support? What service experience are we targeting? What is our pricing and packaging strategy? Anyone who had previous experience with SaaS migration knows that most of the time answers to these questions influence the answers to technical questions such as: How do we isolate tenant data? How do we connect users to tenants? How do we avoid noisy neighbor conditions? How do we do A/B testing? How do we do based on tenant load? Which billing provider should we use? Introduce True SaaS Experience: Shared Services for Identity, Onboarding, Metrics, and Billing Management The key concept embraced by all SaaS solutions is having shared services surrounding your application. These services are used by SaaS business owners for identity, onboarding, metrics, and billing management. From the migration point of view, these services play a titular role.  You’ll need services to manage and monitor your SaaS solution centrally.  The general goal is to get your application running in a SaaS model with basic functionality. It allows you to improve the customers' experience instantly with ongoing updates based on incoming feedback. That’s why implementing these services should be at the forefront of your migration path. It allows you to present a true SaaS experience to your customers no matter what SaaS deployment architecture you choose.  You can make further modifications to your app and its architecture at a later stage. How much you modernize your application will vary based on the nature of your legacy environment, market needs, cost considerations, and so on.  Support your SaaS migration process Your team can handle the business aspects of your SaaS migration, but understanding the technical side may be challenging. Once you have planned a sound business strategy, the next step is to address the technical challenges. This involves assessing and adjusting your application and data for the new cloud environment. Integrating data migration testing into this phase is about identifying and resolving any data compatibility or performance issues before they impact your SaaS operation. Seek professional support from SaaS development company who have expertise in setting up the necessary shared services environment for your customers and ensuring a smooth and secure transition of your data to the cloud. STREAMLINE YOUR SAAS MIGRATION WITH A RELIABLE PARTNER