Fabric is a good candidate when the team understands its governance, capacity, lifecycle and integration implications. It is not automatically better than a well-run SQL, Power BI or Databricks architecture.
What problem should Fabric solve?
Clarify whether the goal is simpler data movement, lakehouse adoption, workspace consolidation, Power BI integration, governance or cost control. A vague modernization goal is not enough.
Who will operate the capacity?
Capacity planning, monitoring and cost accountability need owners. Without that, platform convenience can become a budget and performance surprise.
How mature is the semantic layer?
Fabric does not remove the need for shared definitions. If KPI ownership and model standards are weak, Fabric may simply move confusion into a newer platform.
Where does Databricks still fit?
Some engineering and advanced analytics scenarios may still justify Databricks. The right question is not which tool wins, but which layer should own which responsibility.
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