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Unleash the Future: Migrate from Legacy System to Cloud

A cloud connected to wires

Are you ready to embrace the future of data management? Discover why the migration from legacy on-premises systems to Cloud is becoming the go-to strategy for companies worldwide.


70% of businesses report slower time-to-market and hindered innovation due to outdated data management solutions according to a study by VMware and Professor Feng Li. Imagine unlocking the full potential of your data with the agility and scalability of the cloud. This blog post is your roadmap to leaving those legacy burdens behind and embracing a future-proof data strategy.


Let’s decode the power of cloud-based data integration platforms like the Intelligent Data Management Cloud (IDMC). We'll unveil the key features that make Cloud the clear champion and equip you with a strategic roadmap for a smooth and successful migration. Get ready to say goodbye to limitations and hello to a world of data-driven insights!

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Everything's Fine, Why Migrate to a Cloud System?

Cloud-native integration platforms offer several features which make it a better choice for data integration:


  • Microservices architecture: The Cloud offers all-in-one functionality, allowing developers to have everything in one place rather than opening multiple applications for different tasks. For example, IDMC is built on a microservices architecture, which makes it more scalable and resilient than PowerCenter. IDMC combines data integration, application integration, and data management into a unified platform, resulting in better cross-team collaboration and management of the developed assets. PowerCenter needs the deployment of multiple applications, whereas all the components are a click away in IDMC.

  • Enhanced Agility: Cloud offers a range of pre-built connectors and templates that expedite integration workflows, enabling faster development cycles and quicker time-to-market for new data initiatives. For example, Informatica’s Cloud Data management allows the usage and integration of assets from different services. One can create an address verifier in CDQ (Cloud Data Quality) and use it in CDI under a mapping, whereas the same functionality is not available in PowerCenter. 

  • Intelligent Data Integration: The cloud leverages AI-driven automation to optimize data integration tasks. Intelligent recommendations, error detection, and self-tuning processes empower data engineers to focus on high-value tasks. The Intelligent aspect of the Cloud allows a developer to focus more on the final product than on fixing minor bugs.

  • Advanced Data Quality and Governance: Cloud has many new features when it comes to Data Quality and Governance. By implementing inherent data quality rules and lineage tracking within cloud-based solutions, organizations can secure the accuracy and compliance of their data. This ensures more confident decision-making and mitigates business risks effectively.

  • Accessibility: Cloud architecture offers the convenience of accessing it from anywhere, making it more user-friendly. With your work on the cloud, you don require access to specific tools to work on your tasks, unlike on-premises systems.

The table below shows some key differences between Cloud and On-premises systems, taking Informatica Data Management Cloud & Informatica PowerCenter as examples:

Chart showing difference between IDMC and Informatica's PowerCenter Clouds

The features mentioned above merely scratch the surface of the extensive list of benefits Cloud could offer, adding to the list are automatic updates, pay for what you use among other benefits.

While it might initially seem complex, a well-structured roadmap can lead to a successful migration.


The Roadmap: From Legacy to Cloud:

  • Assessment and Planning: The first step is to assess your current data integration environment, identify dependencies and potential challenges, prioritize the integrations, and find out-of-scope assets, and areas of enhancements. 

  • Data Profiling and Cleansing: Prioritize data quality by profiling and cleansing data before migration, setting the foundation for accurate data management in the Cloud. As the saying goes, Clean Data, Happy Data!

  • Migration and Validation: Testing and Validating the migrated integrations in lower environments and then gradually moving to upper environments is the best approach. The functionalities of Cloud-native Integration tools might not be similar to what on-premises systems offer; hence a thorough validation is equally important.

By following a well-defined migration roadmap and embracing the benefits of the Cloud, any organization can transition smoothly and embark on a data integration journey poised for success.

At Fluidata Analytics, we are happy to walk hand in hand with you throughout your migration journey, providing support and guidance and leveraging our deep expertise in Cloud to your assistance.


Reach out to us at hello@fluidata.co

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