Assess your Data Estate for Microsoft Fabric

Before migrating data solutions to Microsoft Fabric, it's essential to assess the current data estate. Unlike infrastructure migrations to Azure, no one is migrating from Microsoft Fabric, but rather to it — often from traditional data warehouses, data lakes, or reporting solutions like Power BI, SQL Server, or other on-premises and cloud-based data services.

The goal of this phase is to evaluate the readiness and suitability of data sources, models, and workloads for Microsoft Fabric adoption.

Why Assess?

High-level planning (like digital estate rationalization) provides only rough guidance. To build a viable Fabric migration strategy, you must dig deeper:

• Can your current workloads benefit from Fabric's unified SaaS model?
• Are your data pipelines suitable for event-based ingestion, OneLake storage, or Direct Lake datasets?
• Can your reporting needs be enhanced by Fabric's real-time or semantic modeling capabilities?

If you skip this phase, you risk:

• Failing workloads during deployment,
• Unexpected costs due to inefficient data movement,
• Security gaps or policy violations,
• Inconsistent architecture that does not align with Microsoft Fabric best practices.

Assessment Checklist

Activity	Description	Responsible roles
Classify data workloads	Assess data sensitivity (e.g. PII, regulated data) and business criticality. Identify where Fabric's capabilities are applicable.	Fabric Solution Architect Data Governance Lead
Evaluate workload readiness	Identify existing pipelines, storage formats, ingestion patterns (batch vs. real-time), and dependencies (e.g., Power BI, Synapse, Data Factory). Document blockers (e.g., unsupported connectors, missing APIs).	Fabric Solution Architect Data Engineers
Architect for Fabric	Design target workloads using Fabric architecture. Define Lakehouse, Warehouse, KQL Database, and Eventstream usage. Estimate capacity units (CU), workspaces, and deployment automation.	Fabric Solution Architect Workload Owner Landing Zone Architect
Tag workloads for migration waves	Use tagging strategy to define readiness state, target Fabric workload type, and migration wave.	Cloud Strategy Team Fabric Platform Admin

Recommended Tools

• Microsoft Purview – to classify and discover your data
• Power BI Service and Workspace Inventory scripts
• OneLake / Lakehouse workload profilers
• Custom tagging frameworks and migration backlog tooling
• Azure DevOps or GitHub Projects to track assessment outcomes

Continue to the next section: Architect Fabric workloads.