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dunn1373's avatar
dunn1373
Frequent Visitor
1 year ago
Solved

PowerBI data model Refresh hung up - 3 hour failure

We have a few data models we publish that contain the working elements that populate a number of reports.  All but one of them are under 1 GB.  The data model that is over 1GB is in a Premium workspa...
  • v-csrikanth's avatar
    1 year ago

    Hi dunn1373 

    To improve performance and ensure data consistency in your Power BI model, especially when working with bitemporal and snowflake schemas, consider the following strategies:

    1. Flatten your schema where possible using Power Query or SQL views to reduce complexity and avoid issues with inner joins.
    2. Use a bridge date table (e.g., BusinessDate) with TREATAS() for handling From_Date and To_Date across multiple tables. This helps apply time-based logic without expanding rows unnecessarily.
    3. Split data using composite models — import recent data for performance and use DirectQuery or summarized tables for older records.
    4. Manage relationships with DAX: Keep certain relationships inactive and use USERELATIONSHIP() when needed to control filter context safely.
    5. Avoid DAX in slicers: Instead, create a proper dimension table for filtering to ensure it works with visuals.

    These techniques help keep your model scalable and responsive, even with complex logic and large datasets.

    If the above information helps you, please give us a Kudos and marked the Accept as a solution.

    Best Regards,
    Community Support Team _ C Srikanth.