Best Practice for Editing Semantic Model

When working with Power BI semantic models, here are some best practices to consider:

1. Edit in Power BI Service: Since you cannot edit the model directly in Power BI Desktop when it’s not in import mode, you should use the Power BI service to make your changes. The Power BI service now allows you to edit data models directly, including modifying data types, creating calculated columns, and adding measures1.

2. Minimal Transformations in Power BI Service: It’s generally a good idea to perform minimal transformations in the Power BI service. Focus on essential changes like data type adjustments and creating necessary calculated columns and measures. This approach helps maintain model performance and manageability2.

3. Create a Copy of the Original Model: Before making significant changes, create a copy of the original semantic model. This ensures you have a backup in case you need to revert to the original state2.

4. Use Descriptive Naming Conventions: Make your model easily understandable by using clear and consistent naming conventions for tables, columns, and measures3.

5. Document Your Model: Maintain clear documentation of your model, including relationships and calculations. This will facilitate future updates and collaboration3.

By following these practices, you can effectively manage and optimize your Power BI semantic model. If you have any more questions or need further assistance, feel free to ask!

Edit data models in the Power BI service (preview) - Power BI | Microsoft Learn

Mastering Power BI Semantic Models: A Beginner's Guide to Building Data-Driven Insights - Datum Discovery

Semantic models in the Power BI service - Power BI | Microsoft Learn

Hi Anonymous 

It’s important to clarify whether your semantic model is using DirectQuery or Import mode, as the capabilities and best practices differ between the two:

DirectQuery Mode:

1. Limitations:

   • You cannot edit data types or add calculated columns in Power Query or Desktop.
   • Your transformations are limited to creating measures (DAX) in Power BI Desktop.

2. Recommendations:

   • Use DAX in Power BI Desktop to create measures.
   • If changes to data types or columns are necessary, make them in the source system (e.g., Power Apps or SharePoint).
   • DirectQuery is useful for near real-time updates, but it comes at the cost of flexibility and performance.

Import Mode:

1. Advantages:

   • You can fully utilize Power Query for data transformations, such as changing data types or creating calculated columns.
   • Once the data is imported, performance in Power BI is generally better because queries are run against the imported data instead of the source.

2. Recommendations:

   • If real-time updates are not essential, consider switching to Import mode for more control and better performance.
   • After switching to Import, you can:
     • Use Power Query for data transformations.
     • Add calculated columns and measures in Desktop.

General Best Practices:

• Power BI Desktop:

  • Perform all modeling tasks, including data transformations and creating calculated columns or measures.
  • Use it for detailed development and testing.

• Power BI Service:

  • Use primarily for publishing, managing, and sharing your reports.
  • While model editing capabilities in Power BI Service have improved, they are still limited compared to Power BI Desktop.

If your scenario permits, I recommend using Import mode, as it allows greater flexibility for transformations and better performance for most use cases. However, if you need real-time data, DirectQuery remains a valid option, with the trade-offs outlined above