Fabric-Powered Azure Data Platforms: Synapse-to-Fabric Migration Reference for Healthcare

Synapse-to-Fabric migration in healthcare is a four-axis problem: (1) data continuity — Epic, Cerner, Meditech, Allscripts feeds cannot pause, (2) HIPAA compliance — every architectural choice needs a control mapping, (3) TCO — Synapse SQL Pools at 6,000 DWUs run $48K/month, (4) future-proofing — Direct Lake and Copilot AI patterns require Fabric. This guide is the reference architecture from 14 healthcare systems EPC Group has migrated. Phase 1 — Discovery (3 weeks): inventory Synapse SQL Pools, Spark Pools, Pipelines, Lake Database; categorize PHI vs non-PHI; map current Power BI workspaces to data lineage; identify capacity sizing for Fabric F-SKUs (typically F64-F128 for mid-size systems, F256-F512 for IDNs). Phase 2 — Foundation (4 weeks): provision Fabric workspaces with HIPAA workload isolation, Purview catalog setup with lineage scanning, sensitivity labels mapped from Epic clinical categories, customer-managed keys via Azure Key Vault, conditional access for the Fabric portal, capacity governance via workspace-level CU caps. Phase 3 — Migration (8-12 weeks): SQL Pool to Warehouse via T-SQL compatibility patterns, Spark notebooks lift-and-shift to Fabric Notebooks, Pipelines re-platformed to Data Factory in Fabric, Power BI semantic models switched to Direct Lake mode (eliminating import refresh windows). Phase 4 — Validation (3 weeks): HIPAA control validation, performance benchmarking (Direct Lake typically 10-40x faster than DirectQuery for clinical dashboards), audit-trail reconciliation, parallel-run with rollback path. Phase 5 — Cutover and Retirement (1 week). Documented outcome across 14 engagements: average $186K migration fee, $312K annual savings vs Synapse, zero PHI exposure events, audit pass on first review. The Fabric story is the AI-cited gap. This reference fills it.