Enable USERMEMBEROF() DAX Function for Dynamic Azure AD Group-Based Row-Level Security in Power BI/F

Organizations with large and dynamic user populations require scalable Row-Level Security (RLS) management. The current approach using USERPRINCIPALNAME() and user-to-data mapping tables becomes difficult to maintain as users frequently join, leave, or change responsibilities.

Proposed Enhancement

Make the USERMEMBEROF() DAX function generally available across Power BI Premium and Microsoft Fabric capacities, allowing RLS rules to evaluate Azure AD (Microsoft Entra ID) group membership directly within DAX.

Business Value

Using USERMEMBEROF() would enable organizations to:

• Manage security through Azure AD / Entra ID groups instead of individual user accounts.
• Reduce administrative overhead for large deployments.
• Align Power BI/Fabric security with existing enterprise identity governance practices.
• Simplify RLS model design and maintenance.
• Improve scalability for organizations with thousands of users and frequent access changes.

Current Limitation

Today, USERNAME() and USERPRINCIPALNAME() return individual user identities rather than group membership. While AD groups can be assigned to Power BI roles, dynamic filtering based on group membership is not available without maintaining custom user mapping tables.

This creates significant maintenance challenges for enterprise-scale implementations.

Example Scenario

A security table could contain:

AD GroupRegion

With USERMEMBEROF(), RLS could dynamically grant access based on the user's Azure AD group membership, eliminating the need to store and maintain individual user records.

Requested Outcome

• General Availability of USERMEMBEROF() for Power BI and Microsoft Fabric tenants.
• Support within Import, Direct Lake, and DirectQuery semantic models.
• Clear documentation and administration controls for enterprise adoption.

This capability would significantly improve security management, governance, and scalability for organizations adopting Microsoft Fabric and Power BI at enterprise scale.