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Modernize your Data Estate

Modernization is when you enhance workloads and the processes that support those workloads. It’s all about maximizing value and adopting cloud technologies that unlock more benefits of the cloud. The goal of modernization is to make the cloud work for you. It can improve operational efficiency, reduce management overhead, and optimize costs. Modernization allows your organization to be more productive with less. Efficiency at this scale should be a priority.

We recommend modernizing in two phases:

Phase 1: Business Alignment​

In phase one of modernization, you identify your business goals and create a modernization roadmap to reach those goals. The roadmap should list the workloads you need to modernize and the strategies you’ll apply. Use this phase to evaluate current data estate pain points, align stakeholders, and ensure the value of modernization is clearly communicated and measurable.

This business alignment consists of:

  • Envisioning: Define your goals, KPIs, and transformation outcomes.
  • Evaluating: Assess readiness, current tooling, and skills.
  • Committing: Secure sponsorship and allocate funding to initiatives.

Phase 2: Modernization Strategies​

In phase two, you implement modernization strategies. This is where technical change happens. You’ll adopt new methodologies and technologies to enhance your processes, applications, and data platforms.

Process Modernization​

Adopt a DevOps or DataOps methodology. This will help accelerate delivery and reduce total cost of ownership (TCO). Automation, CI/CD pipelines for Fabric notebooks and dataflows, and IaC for Fabric environments should be prerequisites for any scalable modernization effort.

Application and Database Modernization​

For Microsoft Fabric environments, focus on transitioning from legacy ETL tools to Fabric-native PaaS components:

  • Replace SSIS with Fabric Data Pipelines.
  • Replace legacy scheduling with Fabric Data Activator and Eventstreams.
  • Use Fabric Notebooks instead of server-bound scripts.

For database workloads:

  • Migrate SQL workloads to Fabric Lakehouses or Warehouses depending on query performance, concurrency, and integration needs.
  • Consider using Direct Lake mode to avoid duplication and improve latency.
  • Leverage OneLake as a single, governed data lake.

PaaS-based solutions like these improve scalability, governance, cost transparency, and reduce operational overhead.

Resources​

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