Fabric Environment Design Advice

Hi michaelgambling ,

I agree with the point raised by Taylor Amy. In scenarios where the source data is highly fragmented across multiple tables and requires additional calculated columns or transformations, relying solely on views can introduce performance and maintainability challenges.

A more robust approach in Microsoft Fabric is to introduce a lightweight transformation layer (Silver) using notebooks or dataflows. While this does introduce some level of data duplication, it allows you to pre-join and structure the data once, enabling semantic models to operate efficiently with Direct Lake without falling back to DirectQuery.
This pattern generally provides better performance, improved stability for reporting workloads, and clearer separation between ingestion, transformation, and consumption layers. For complex legacy schemas, a small ETL layer often ends up being the most sustainable option.

Hope this helps.
Thank you.