There’s a familiar tension in modern analytics: teams want data products that are easy to discover and safe to consume, but they also want to move fast—often faster than the governance model can tolerate.
In Microsoft Fabric, that tension frequently shows up as a perception of workspace sprawl. A “single product per workspace” model is clean on paper—strong boundaries, tidy ownership, straightforward promotion—but it can quickly turn into dozens (or hundreds) of workspaces to curate, secure, and operate.
This post proposes a different pattern—an advanced lakehouse approach that treats the lakehouse itself like a product factory:
- Shortcuts or schema shortcuts become the input layer (a clean, contract-aware “ingest without copying” boundary).
- A small-step transformation layer is implemented as a multi-step DAG using Materialized Lake Views (MLVs).
- A versioned, schema-based surface area becomes the data product contract you expose to consumers.
Then we connect that to OneLake security and Fabric domains, showing how you can expose left-shifted data products (usable earlier in the lifecycle) without letting workspaces multiply endlessly.
Continue reading “The Advanced Lakehouse Data Product: Shortcuts In, Materialized Views Through, Versioned Schemas Out”