Reviewed by Aditya Kumar · Last reviewed 2026-03-24
Architectural logic: Fabric = unified analytics (engineering, warehouse, science, BI). Data integration: Fabric Pipelines (ADF-based), Dataflows Gen2 (Power Query), OneLake. Use case: Ingest SAP → Dataflows transform → Warehouse → Power BI. Why: Single platform for...
Architectural logic: Fabric = unified analytics (engineering, warehouse, science, BI). Data integration: Fabric Pipelines (ADF-based), Dataflows Gen2 (Power Query), OneLake. Use case: Ingest SAP → Dataflows transform → Warehouse → Power BI. Why: Single platform for Microsoft-centric analytics; shortcuts for virtual consolidation. Trade-off: Fabric vs standalone ADF—Fabric for end-to-end; ADF for hybrid/multi-cloud. Best practice: Use shortcuts; Fabric capacities for compute; evaluate licensing.
Red Flag: Recommending Fabric without understanding OneLake vs ADLS differences. Pro-Move: 'We use Fabric for Microsoft stack—shortcuts to ADLS and Sharepoint; single capacity for compute—reduced sprawl.'
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