Power biBest Practices for Centralized Row-Level Security (RLS) Integration with Power BI

[Prajwal9]

Hello Power BI Community,

We are exploring ways to streamline the implementation of Row-Level Security (RLS) in Power BI and are seeking insights on the best practices for managing RLS across multiple reports.

Specifically, we would like to:

✅ Create and define RLS once in the data lake.
✅ Automatically apply this RLS across all Power BI reports (PBIX files) without having to configure it individually for each report.

Is it possible to set up RLS centrally in the data lake and have it seamlessly applied to Power BI reports? If not, what is the next best approach to achieve consistent and efficient RLS management across all reports?

Any guidance or suggestions on how to best manage RLS for scalability and efficiency would be greatly appreciated!

[Prajwal9]

Your advice has been most helpful — thank you!

[rohit1991 · Accepted solution]

Unfortunately, Power BI does not natively support centralizing Row-Level Security (RLS) in a data lake or directly applying it across multiple reports automatically. However, here are the best practices to achieve consistency and efficiency:

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1. Use a Centralized Dataset (Recommended Approach)

• Create a centralized Power BI dataset in the Power BI Service.
• Define RLS in this dataset (once) using roles and DAX expressions.
• Connect multiple reports (PBIX files) to this single dataset.
• This way, RLS is managed in one place and applies consistently across all reports that use the shared dataset.

2. Leverage Azure Analysis Services (AAS) or Power BI Premium

• If you're using Azure Analysis Services or Power BI Premium, you can define RLS in a centralized model (e.g., AAS or Tabular Models).
• Multiple Power BI reports can connect to this model, and RLS will automatically apply.

3. Automate RLS Configuration with Deployment Pipelines

• Use deployment pipelines to replicate RLS configurations from one environment (like Dev) to others (Test/Prod).
• This reduces manual work when deploying multiple reports.

Summary: To streamline RLS, define it once in a centralized dataset or use Azure Analysis Services. All connected reports will inherit the RLS automatically. Avoid duplicating RLS definitions across individual reports.

[Prajwal9]

Thanks for the great insights on centralized RLS management! I have a follow-up question regarding a scenario where my report is connected to two different semantic models.

If my Power BI report is connected to two separate semantic models, each potentially with its own RLS configuration, how would RLS be applied in this case? Would I need to manage RLS separately for each model, or is there a way to handle this more seamlessly?

I’d appreciate any further guidance on how to manage RLS in this multi-model setup.

Thanks again for your help!