Azure Synapse to Microsoft Fabric Migration
Softree modernized an Azure Synapse environment by migrating data workloads, pipelines, Spark notebooks, OneLake, and Power BI dependencies to Microsoft Fabric.
Business Process Challenges
The client operated an Azure Synapse Analytics environment supporting data warehousing, data integration, Spark-based processing, and business intelligence. Over time, the environment expanded across dedicated SQL pools, pipelines, notebooks, lake storage, and Power BI reporting.
The separate components created operational complexity, with dependencies across data movement, orchestration, transformation, warehousing, and reporting that needed to be understood before migration.
Key challenges included:
- Assessing compatibility of existing warehouse objects and SQL logic.
- Migrating Synapse pipelines with their linked services, parameters, schedules, and dependencies.
- Updating Spark notebooks, libraries, configurations, and data-access patterns.
- Defining an appropriate OneLake strategy for existing lake data.
- Validating Power BI semantic models, reports, refreshes, and security.
- Minimizing business disruption during cutover.
Our Strategic Approach
Softree followed a workload-by-workload migration approach to move the existing Azure Synapse environment toward a Microsoft Fabric-based data platform.
Assess & Prioritize
Softree inventoried Synapse workspaces, SQL pools, schemas, tables, views, stored procedures, pipelines, triggers, notebooks, Spark dependencies, lake paths, and Power BI assets. Workloads were assessed based on complexity, business criticality, dependencies, data volume, and execution patterns.
Modernize the Data Warehouse
Dedicated SQL pool workloads were assessed for Fabric Warehouse compatibility. Schemas, tables, views, stored procedures, data types, SQL syntax, and performance patterns were reviewed before migration. Data and business measures were reconciled against the source environment.
Migrate Data Pipelines
Synapse pipelines were reviewed activity by activity and upgraded or recreated using Fabric Data Factory. Connections, parameters, dependencies, triggers, retry behavior, logging, and failure handling were validated as part of the migration.
Migrate Spark Workloads
Spark notebooks were reviewed for runtime compatibility, libraries, packages, storage paths, APIs, and external dependencies. Notebook outputs, schemas, record counts, and business calculations were validated against representative data.
Establish the OneLake Foundation
OneLake was established as the target data foundation, with migration decisions made around copying, reusing, or using shortcuts for existing lake data. Workspace boundaries, permissions, naming, lineage, and data ownership were also considered.
Integrate Power BI
Power BI semantic models and reports were mapped to the target Fabric data structures. Relationships, measures, refresh settings, security rules, permissions, filters, drill paths, and key business metrics were validated.
Test & Cut Over
Softree performed functional testing, data reconciliation, performance benchmarking, and user acceptance testing before a controlled production cutover. Pipeline runs, notebook failures, refresh history, capacity consumption, and user-reported issues were monitored during stabilization.
Our Engineering & Delivery Process
Our structured project delivery approach takes you from discovery and planning to development, testing, and deployment, ensuring quality, transparency, and predictable outcomes at every stage.
Discovery & Architecture
Deep-dive technical audit of existing systems, security baselines, API mapping, and comprehensive cloud target blueprinting.
UX & System Prototyping
Role-based user journeys, wireframing, high-fidelity clickable Figma prototypes, and API contract specifications prior to build.
Agile Sprint Engineering
Modular development sprints delivering clean, shippable code with automated CI/CD pipelines and continuous testing.
QA & Security Hardening
End-to-end regression suites, cross-device verification, load stress audits, and penetration testing for enterprise resilience.
Production Launch & Scale
Zero-downtime blue-green production deployment, real-time telemetry, administrator training runbooks, and ongoing SLA support.
Explore the Solution Through visuals
What changed for the client.
The migration established a structured path toward a more integrated Microsoft Fabric data engineering and analytics environment.
The expected impact areas included:
- Platform simplification through a more integrated Fabric experience.
- Improved operational visibility through centralized monitoring and clearer workload ownership.
- Greater data trust through documented reconciliation and validation of key business measures.
- Analytics continuity through validated Power BI models, reports, refreshes, and access controls.
- Reduced migration risk through workload assessment, phased deployment, acceptance criteria, and rollback planning.
- Measured performance and cost visibility through comparison of workload performance and Fabric capacity consumption.
The numbers behind the rollout.
The full integration layer.
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