Migrate to Microsoft Fabric: Your Step-by-Step Path to the Unified Platform
Azure Synapse dedicated SQL pools, on-premises SQL Server warehouses, ADF pipelines, ADLS storage — they all have a clear migration path to Fabric. The question isn't whether to move. It's how to execute the migration without breaking production workloads or losing 6 months to rework.
Migration Assessment
Inventory your current stack, map dependencies, identify the Fabric migration path
Architecture Design
Workspace topology, OneLake structure, lakehouse vs warehouse decisions
Phased Execution
Parallel-run migration with rollback plans and zero-downtime cutover
Validation & Optimization
Data reconciliation, performance tuning, and post-migration cost optimization
Fabric migration isn't lift-and-shift. It's a re-architecture opportunity.
The biggest mistake organizations make when migrating to Fabric is treating it like a one-to-one copy of their existing Azure services. Fabric isn't Synapse with a new name — it's a unified platform with different architectural patterns, different performance characteristics, and different cost models.
Synapse dedicated SQL pools → Fabric warehouse seems straightforward, but the compute model, distribution strategy, and query optimization are different. ADF → Fabric pipelines looks like a rename, but Dataflows Gen2 and Fabric notebooks open new patterns. ADLS Gen2 → OneLake is the simplest migration — until you need to design workspace boundaries, shortcut strategies, and governance policies for multi-team access.
Xylity matches Fabric migration specialists who understand both sides of the move — your current Azure architecture and the optimal Fabric target architecture. Our Fabric consulting practice covers the full migration lifecycle from assessment through post-migration optimization.
Where are you migrating from?
Each source platform has a specific migration path to Fabric. We match specialists with experience on your exact source-to-Fabric journey.
Azure Synapse → Fabric
Dedicated SQL pools to Fabric warehouse. Synapse Spark to Fabric notebooks. Synapse pipelines to Fabric pipelines. ADLS Gen2 integration through OneLake shortcuts. The most common Fabric migration — and the one with the most architectural nuance.
On-Prem SQL Server → Fabric
SQL Server data warehouses and SSIS packages to Fabric lakehouse/warehouse and Fabric pipelines. Schema conversion, stored procedure migration, and SSIS package re-architecture for cloud-native Fabric patterns.
See cloud migration →ADF → Fabric Pipelines
Azure Data Factory pipelines to Fabric data pipelines and Dataflows Gen2. Linked services, integration runtimes, and trigger reconfiguration. Leveraging Fabric-native features: notebook activities, OneLake shortcuts, and Spark transforms.
Power BI Import → Direct Lake
Converting traditional Power BI import models to Direct Lake semantic models. V-Order optimization, framing configuration, and performance tuning. Eliminating the import/refresh cycle for near-real-time analytics at lakehouse scale.
See Fabric analytics →ADLS Gen2 → OneLake
Data lake reorganization from ADLS containers to OneLake workspace structure. Shortcut configuration, permission mapping, and governance redesign for Fabric's unified storage layer.
Azure HDInsight → Fabric Spark
Hadoop and Spark workloads migrating from HDInsight to Fabric's managed Spark environment. Job conversion, cluster configuration mapping, and performance benchmarking against Fabric Spark pools.
Step-by-step Fabric migration process
Assessment & Inventory
Complete inventory of your current Azure data estate: Synapse pools, ADF pipelines, ADLS storage, Power BI datasets, and downstream dependencies. Gap analysis between current architecture and optimal Fabric target state.
Target Architecture Design
Fabric workspace topology, OneLake structure, lakehouse vs warehouse decisions, pipeline strategy, and governance framework. Designed for your specific workloads — not a generic template.
Phased Migration
Parallel-run execution: source and target running simultaneously. Schema migration, data transfer, pipeline conversion, and semantic model migration. Each phase validated before proceeding to the next.
Validate & Optimize
Row-count reconciliation, performance benchmarking, cost comparison, and user acceptance testing. Cutover only after validation confirms parity — with rollback plans if issues emerge.
Fabric migration for enterprises and IT services companies
Ready for Fabric but need architects who've completed the migration before?
Fabric migration is a re-architecture opportunity — not a lift-and-shift. Xylity matches migration architects who understand both your current Azure data estate and the optimal Fabric target architecture. Our consulting-led approach starts with assessment, designs the target state, and executes the migration with zero-downtime strategies.
Start a Consulting Engagement →Client committed to Fabric migration but your team lacks migration experience?
Fabric migration requires specific experience: Synapse-to-Fabric mapping, ADF-to-Fabric pipeline conversion, and Direct Lake semantic model migration. When your bench doesn't have production Fabric migration experience, Xylity delivers curated migration specialist profiles from our 200+ partner network. First profiles in an average of 4.3 days.
Scale Your Migration Delivery →Fabric migration — answered
Your Fabric migration deserves architects
who've completed it before.
Tell us about your current Azure data estate and Fabric migration goals. We'll match specialists who've navigated the exact migration path you need.