Migration from Power BI Premium (Capacity/PPU) → Fabric Assessment Checklist

This article provides key Fabric migration assessment from Power BI Premium. These include pre-migration assessment, readiness & planning , migration execution, post migration & adoption as well as key benefits and known limitations.

1. Pre-Migration Assessment

• Inventory Reports & Datasets

  • Identify all reports, datasets, and apps currently hosted on Premium or PPU.

  • Categorize by size, refresh frequency, and user adoption.

• Data Sources

  • Document all sources (SQL, Dataflows, Lakehouse, etc.).

  • Confirm Fabric connector support.

• Licensing Model Review

  • Compare current Premium Capacity/PPU with Fabric F SKUs (Fabric capacity-based).

  • Estimate cost differences.

• Feature Usage

  • Check for features that may behave differently in Fabric (e.g., Gen2 Dataflows, DirectLake).

  • Document dependencies on AI, paginated reports, or APIs.

• Security & Governance

  • Export current workspace roles, RLS/OLS, and sensitivity labels.

  • Plan to re-apply or enhance in Fabric.

2. Readiness & Planning

• Capacity Sizing

  • Map Premium capacity SKU (e.g., P1, P2, P3) to equivalent Fabric SKU (F64, F128, etc.).

  • Assess workloads (semantic models, dataflows, paginated, AI) for concurrency.

• Workload Alignment

  • Decide whether to shift to new Fabric-native workloads (Lakehouse, Warehouse, Real-Time Analytics).

  • Plan phased adoption (start with BI reports, then modernize pipelines).

• Migration Strategy

  • Lift-and-shift reports/datasets first.

  • Re-architect into Fabric workloads where beneficial.

• Dataflow Migration

  • Validate Dataflow Gen1 → Gen2 migration readiness.

• Access Control & Governance

  • Align with Fabric workspace roles, Entra ID groups, Purview policies.

3. Migration Execution

• Assign Fabric Capacity

  • Move existing workspaces from Premium/PPU to Fabric capacity.

• Dataset Migration

  • Validate refresh schedules, gateways, and performance post-migration.

• Report Migration

  • Re-publish PBIX if needed for compatibility.

• Security Validation

  • Test RLS/OLS, sensitivity labels, and DLP policies.

• User Testing

  • Ensure report outputs and performance are consistent or improved.

4. Post-Migration & Adoption

• Decommission Old Premium Capacity/PPU (if fully migrated).

• Training & Change Management

  • Educate users on Fabric features, workspace navigation, and new workloads.

• Monitoring & Optimization

  • Use Fabric Admin metrics to track capacity usage and optimize workloads.

• Governance Alignment

  • Apply unified Fabric governance (Purview, auditing, sensitivity labeling).

🌟 Key Benefits of Migrating to Fabric

• Single SaaS Platform: Eliminates siloed Premium vs PPU; all workloads under Fabric.

• Future-Proof: Fabric capacity enables new workloads (Lakehouse, Data Warehouse, Real-Time Analytics, AI).

• Cost Optimization: Fabric capacities are elastic and can be scaled up/down, unlike fixed Premium SKUs.

• DirectLake Mode: Faster, storage-efficient access for large datasets.

• Advanced Features: Built-in AI, Copilot for report building, integration with Microsoft 365.

• Governance & Security: Unified Purview policies, DLP, and central capacity monitoring.

⚠️ Known Limitations & Considerations

• Feature Gaps

  • Some advanced Premium features (e.g., XMLA endpoints, Paginated Reports scaling) may behave differently.

• Licensing Shift

  • Fabric is purely capacity-based; PPU users lose per-user premium licensing model.

• Migration Overhead

  • Dataflows Gen1 require migration to Gen2.

• Hybrid Data Connectivity

  • On-premises sources still need a properly configured Data Gateway.

• Learning Curve

  • Users must adapt from Premium/PPU concepts to Fabric capacities and workloads.

• Capacity Management

  • Fabric introduces a new way of monitoring and controlling workloads—admins must learn to tune and prioritize.