Microsoft Fabric brings data engineering, warehousing, real-time analytics, data science and Power BI into one software-as-a-service platform. For many Microsoft-centric organisations it's an attractive simplification. For others, it's a migration they don't need yet.
Here's how we help clients decide.
Where Fabric shines
- Power BI-heavy organisations. If most of your analytics already lives in Power BI, Fabric removes a lot of plumbing between your data and your reports.
- Lean platform teams. Capacity-based licensing and a managed platform mean less infrastructure to run, which suits teams without dedicated platform engineers.
- Open storage. OneLake stores data in the open Delta format, so you aren't locking your data into a proprietary store.
Where to be careful
- Capacity planning. Shared capacity is simple until a heavy workload slows everyone else down. Plan workloads and monitor usage from day one.
- DevOps maturity. Git integration and deployment pipelines have improved a lot, but teams used to mature CI/CD on other platforms should test their workflow early.
- Governance. It's easy to create workspaces and items quickly. Without clear standards, sprawl arrives just as quickly.
Five questions to ask before you commit
- How much of our analytics already runs on Power BI and the Microsoft stack?
- Do we have engineers with real Spark or lakehouse experience?
- Which workloads would we move first, and what would we retire?
- How will we manage capacity, cost and environments across teams?
- What does our governance model need to look like inside Fabric?
A sensible way to start
We usually recommend a time-boxed pilot: one valuable, well-understood workload, built end to end with proper source control, testing and monitoring. It shows you how Fabric behaves with your data and your team, at low risk, before you plan a wider migration.
If you'd like help scoping a pilot, see our data engineering services or book a consultation.