A credible Fabric engagement should connect platform decisions to the organization’s data sources, reporting needs, security model, operating maturity, and future AI plans.
Architecture before migration
Define domains, workspaces, lakehouse and warehouse patterns, environments, ownership, and release controls before moving workloads.
Pipelines need observability
Ingestion should include validation, failure handling, reconciliation, logging, and clear operational ownership.
Consumption shapes the platform
Semantic models, Power BI, data science, and AI requirements should influence how data is organized and governed.
Questions to answer before the initiative begins
- Which domains and use cases should move first?
- How will environments, workspaces, security, and releases be governed?
- What quality, reconciliation, and observability must pipelines provide?
- How will Fabric support BI, analytics, automation, and AI consumers?
A practical way to move forward
Begin with one important operating outcome and make the surrounding ownership visible. Document the decision, workflow, users, source information, controls, exceptions, and adoption requirements. Then choose the architecture and delivery sequence that can prove value without creating a disconnected pilot.
The first implementation should establish patterns the organization can reuse: clear definitions, testable behavior, responsible ownership, and a feedback loop for improvement.