Forum Discussion

Awesomedev's avatar
Awesomedev
New Member
6 months ago
Solved

Lakehouse Data Modeling Tips in Fabric

Hello Fabric Community, I’m currently preparing for the DP-600 exam and working through Microsoft Learn modules. I’ve started creating a Lakehouse workspace in Microsoft Fabric and want to make sure...
  • cengizhanarslan's avatar
    6 months ago

    1) Separate Layers

    Use a layered approach inside the Lakehouse:

    • Bronze → Raw ingestion (no business logic)

    • Silver → Cleaned & transformed tables

    • Gold → Analytics-ready tables (star schema)

    For reporting efficiency, Power BI should ideally connect to the Gold layer.

     

    2) Always Model as a Star Schema

    Even in Lakehouse.

    Use:

    • Fact tables (transactions, events, metrics)

    • Dimension tables (Date, Customer, Product, Region, etc.)

    Avoid:

    • Snowflake schema unless necessary

    • Fact-to-fact relationships

    • Many-to-many unless unavoidable

    • Bi-directional unless justified

     

    3) Use Surrogate Keys (Not Natural Keys)

    In your Gold layer:

    • Create integer surrogate keys for dimensions

    • Avoid joining on text columns

    • Avoid GUID joins if possible

    This reduces storage size and improves relationship performance.

     

    4) Watch Cardinality

    High-cardinality columns:

    • Transaction IDs

    • Timestamps at second-level

    • Free-text descriptions

    Keep them out of dimensions and visuals if not needed.