01
Rationalize reports and models
Identify duplicate dashboards, inconsistent measures, and stale datasets before rebuilding the Fabric estate.
Back to use cases
Microsoft Fabric migration
Modernize analytics workflows on Microsoft Fabric
Move reporting, data engineering, and semantic model work into a Fabric-centered operating model with better governance and less tool sprawl.
Best strategies
What makes this use case work
02
Design OneLake by domain
Organize data around business ownership, sensitivity, and consumption patterns instead of a one-size-fits-all folder structure.
03
Standardize semantic models
Create trusted measures and shared models so teams stop rebuilding the same logic in separate Power BI workspaces.
Showcase example
Showcase example: finance reporting consolidation
Scenario
A finance team consolidates spreadsheet refreshes and fragmented Power BI datasets into Fabric pipelines, OneLake storage, and shared semantic models.
Outcome
Monthly reporting becomes easier to govern, faster to refresh, and more consistent across leadership dashboards.
End-to-end process
How we move from strategy to production
Phase 01
Inventory reports, dataflows, warehouses, refresh jobs, and user groups.
Phase 02
Design Fabric workspaces, OneLake zones, security, and deployment paths.
Phase 03
Migrate priority datasets and rebuild pipelines with validation checks.
Phase 04
Publish certified semantic models and transition users in waves.