Microsoft Fabric Migration (Contract)

Microsoft Fabric Migration - Lift & Shift (Best Practice Approach)
Project Duration: Mid-February - June (4 Months)

Scope of Work
Source System Migration

• Transition of all relevant datasets from Azure SQL Server (EDP) to the Fabric Data Warehouse and Lakehouse (OneLake).

• Validate schema alignment, metadata consistency, and cross-platform compatibility.

Data Pipeline Migration

• Migrate Azure Data Factory (ADF) pipelines to Fabric Data Factory, retaining transformation logic, triggers, dependencies, and parameterization.

• Re-platform Synapse pipelines to ensure operational equivalence and orchestration continuity.

Reporting & Analytics Modernization

• Migrate Power BI datasets and reports to capacity-enabled fabric workspaces.
• Update dataset connections to utilize Fabric Data Warehouse/Lakehouse.
• Optimize refresh performance and align with governance requirements.

Azure Analysis Services Migration

• Convert Azure Analysis Services (AAS) cube models to Fabric Semantic Models.
• Rebuild measures, KPIs, partitions, incremental refresh policies, and security roles (RLS).

• Conduct business validation to ensure functional equivalency.

Storage Migration

• Migrate structured and unstructured data assets from Azure Blob/ADLS to OneLake.
• Align migrated data with recommended architectural zones (Bronze, Silver, Gold).

Database Object Migration

• Recreate all required tables, views, and stored procedures within the Fabric Data Warehouse.

• Remediate SQL incompatibilities specific to Fabric's SQL endpoint.
• Validate object behavior across development, test, and production environments.

Fabric Environment Setup

• Configure Fabric Workspaces, Lakehouses, Warehouses, and Data Factory pipelines.

• Integrate Git/DevOps for deployment automation and version control.
• Implement workspace security, governance standards, and role assignments.

Data Validation

• Perform table-level, column-level, and aggregation-level validations across all migrated assets.

• Execute historical and incremental load validation.
• Reconcile outputs between:

o EDP → Fabric Data Warehouse/Lakehouse
o ADF/Synapse → Fabric Data Factory
o AAS → Fabric Semantic Models
Cutover Planning & Go-Live

• Develop and coordinate a comprehensive cutover strategy, including freeze periods and final sync.

• Execute last-mile data movement, update credentials, and repoint production workloads.

• Support the go-live process, with post-migration hypercare for performance and stability.

Deliverables
Migration Deliverables

• Fully operational Fabric Data Warehouse and Lakehouse environments.
• All ADF and Synapse pipelines migrated and validated in Fabric Data Factory.
• Azure Analysis Services models replaced with fully functional Fabric Semantic Models.

• Power BI datasets connected to Fabric sources and optimized for capacity performance.

• OneLake storage structures implemented with aligned data layers.
• Complete migration of database objects (tables, views, stored procedures).

Documentation Deliverables

• End-to-end migration inventory and mapping documentation.
• Architecture and deployment configuration documentation.
• Data validation logs and reconciliation results.
• Comprehensive cutover and transition plan.
• Post-migration operational runbook and support guide.

Project Timeline (4-Month Execution Window)
Assessment & Planning

• Inventory of current assets, architectural review, and migration sequencing.
• Environment preparation and dependency assessment.

Environment Setup

• Configuration of Fabric Workspaces, Data Warehouse, Lakehouse, governance, and DevOps integration.

Database & Storage Migration

• Migration of tables, views, stored procedures, and Blob/ADLS assets to Fabric and OneLake.

Pipeline Migration

• Rebuild and validate ADF pipelines in Fabric Data Factory.
• Migrate Synapse pipelines and confirm operational fidelity.

Semantic Model Migration

• Conversion of AAS cubes to Fabric Semantic Models.
• Business validation and performance tuning.

Power BI Migration

• Rebinding datasets and reports, enabling optimized refresh and workspace alignment.

Validation & Testing

• Full functional, data, and system validation across all migrated components.

Cutover & Hypercare

• Go-live execution, final synchronization, stabilization, and operational handoff