Power BI Row-Level Security: How to Control Data Access Effectively
Managing access to data is a non-negotiable for organisations working with sensitive information or multiple stakeholders. In Power BI, one of the most effective tools for achieving this is Row-Level Security (RLS). It allows you to control which data users can see based on their identity—without having to create separate reports or datasets for each audience.
Let’s unpack how RLS works, why it’s important, and how to implement it properly to protect your data while keeping reports user-friendly and efficient.
What Is Row-Level Security in Power BI?
Row-Level Security (RLS) is a feature in Power BI that restricts access to data at the row level. Instead of everyone seeing the same dataset in a report, users only see the data that they’re authorised to view.
For example, if your business operates across multiple regions, you may want your NSW manager to see data only for NSW, while your VIC manager sees only VIC data. With RLS, both users can use the same report but will automatically be shown data relevant to their roles.
This setup is especially useful for:
National sales teams
Multi-brand organisations
Department-specific dashboards
Sensitive data like financials or HR
Why Row-Level Security Matters
Beyond the obvious need for confidentiality, RLS helps streamline report development and governance:
✅ Efficiency
No need to duplicate reports for each user group. One report, one dataset – customised views for each user.
✅ Data Integrity
By limiting data exposure, you reduce the risk of accidental (or intentional) data misuse.
✅ Governance & Compliance
RLS supports compliance efforts, particularly for industries with strict data protection requirements such as healthcare, finance, or government sectors in Australia.
Implementing Row-Level Security: A Step-by-Step Guide
There are two main ways to implement RLS in Power BI:
1. Static RLS
This is where rules are hardcoded into the model. For instance, you manually assign users or roles to specific filters. It’s a good option if access doesn’t change often.
How to set up Static RLS:
In Power BI Desktop, go to Model View
Click Manage Roles
Create a new role, e.g. "State Manager"
Select a table and apply a DAX filter (e.g. [State] = "NSW")
After publishing to Power BI Service, assign users to roles via the dataset settings
Static RLS is simple and effective for small teams or fixed access requirements.
2. Dynamic RLS
Dynamic RLS is more scalable. It allows role filtering based on the logged-in user's credentials, referencing a user access table within your model.
Basic setup for Dynamic RLS:
Create a user table with usernames/emails and access rights (e.g. [Email], [State])
Relate this table to your fact table
Use USERPRINCIPALNAME() in your DAX filter to dynamically apply filters:
[Email] = USERPRINCIPALNAME()
This way, when a user opens the report, the filter applies based on their login – no manual role assignments needed.
Best Practices for Managing RLS
Test Before Deploying: Use the “View As Role” feature in Power BI Desktop to simulate user views and confirm filters are working as expected.
Minimise Model Complexity: Keep your user access tables clean and well-maintained. Avoid circular relationships or overly complex DAX expressions.
Use UPN (User Principal Name): Stick with email/UPN fields for user identification to align with Azure Active Directory.
Document Access Rules: Keep a clear record of who has access to what, especially if you're using dynamic RLS—this is essential for audits or troubleshooting.
Common Pitfalls to Avoid
🔒 RLS Doesn’t Apply to Dataset Owners: If you're the report owner, you’ll see everything—even when RLS is in place. Test with non-admin accounts to verify access properly.
🔗 Not Syncing RLS with Workspace Permissions: Even with RLS, users need access to the report in Power BI Service. RLS controls what they see, not if they can access the report.
⚙️ Overcomplicating the Setup: Start with static RLS if your scenario is simple. You can always scale up to dynamic as needs evolve.
Row-Level Security in Power BI is a must-have for organisations that need to manage sensitive or role-based data access. Whether you opt for a static or dynamic approach, implementing RLS allows you to consolidate reporting while protecting critical information.
For businesses in Australia, particularly those with regional operations or compliance needs, RLS can be a game-changer—not just for data security, but for operational efficiency.
If you’re not sure where to start, or if your current setup could use a tidy-up, we can help you design, implement, and optimise RLS in your Power BI environment.