When companies start using tools like Power BI for data analysis and dashboards, one important question usually comes up very quickly – who should be able to see which data?
In many organizations, not everyone should have access to everything. For example, a sales manager handling the North region should ideally see only North region data, not the entire company’s numbers. The same applies to financial reports, employee salary data, and internal performance metrics.
This is exactly where Row-Level Security (RLS) in Power BI becomes very useful.
RLS allows organizations to publish a single report for everyone while ensuring each user only sees the data they are authorized to access. In simple words, the report stays the same, but the data view changes depending on who is opening it.
In this guide, we’ll understand what Row-Level Security is, how it works in Power BI, different types of RLS, and some best practices to follow in 2026
What is Row-Level Security (RLS) in Power BI?
Row-Level Security, usually called RLS, is a feature in Power BI that restricts data access at the row level.
That simply means a user can only see the rows of data that they have permission to access.
For example, suppose a company has sales data like this:
| Region | Sales |
| North | ?2,00,000 |
| South | ?3,50,000 |
| West | ?1,80,000 |
Now, if RLS is implemented, a manager responsible for the North region will only see North region data in the report. Someone managing the South region will see only the South numbers.
So the report stays exactly the same, but the data changes depending on the user’s access.
This helps companies maintain data privacy and better data control.
Types of Row-Level Security in Power BI
In Power BI, there are mainly two ways to implement RLS.
Both methods work, but the choice usually depends on how big the organization is and how frequently access permissions change.
1. Static Row-Level Security
Static RLS is the simpler approach.
In this method, filters are manually defined for each role. Basically, you create roles and assign specific data filters to them.
For example, you can create a role called East Region Manager and apply a filter like:
[Region] = “East”
This means any user assigned to this role will only see East region data.
Advantages
- Easy to set up
- Good for small teams
- No additional tables required
Limitations
- Not very scalable
- If new departments or regions are added, you have to create more roles
- Managing permissions can become messy in large organizations
Because of this, static RLS usually works better in smaller companies or teams with fixed access levels.
2. Dynamic Row-Level Security
Dynamic RLS is a more flexible and scalable method.
Instead of creating multiple roles manually, this method uses a security table that maps users to the data they are allowed to access.
Power BI then automatically checks the logged-in user’s email and filters the data accordingly.
For example, a security table might look something like this:
| UserEmail | Region |
| sarah@company.com | North |
| james@company.com | South |
When Sarah opens the report, she will automatically see North region data, while James will see South region data.
Advantages
- Easier to manage in large organizations
- Automatically adapts when new users are added
- Only one role may be needed
Limitations
- Requires proper data modeling
- Some understanding of DAX functions is needed
Because of these benefits, dynamic RLS is generally preferred in modern Power BI solutions.
How to Implement Dynamic RLS in Power BI
Setting up dynamic RLS usually involves three basic steps.
Step 1: Create a Security Table
First, you need a table that maps users to their allowed data access.
Example:
| UserEmail | Region |
| sarah@company.com | North |
| james@company.com | South |
This table can come from Excel, a database, or another data source.
Step 2: Create a Role in Power BI
Next, open Power BI Desktop and go to:
Modeling ? Manage Roles
Create a new role, for example, UserAccess.
Then apply a filter using a DAX function like:
USERPRINCIPALNAME()
This function returns the email address of the user currently viewing the report in Power BI Service.
Power BI compares that email with the security table and automatically filters the data.
Step 3: Test and Assign Roles
Before publishing the report, it’s always a good idea to test the roles.
Power BI Desktop has a feature called “View As”, which lets you simulate what different users will see in the report.
After publishing the report to Power BI Service, you can assign users or Azure Active Directory groups to the role.
Using security groups is usually better than adding individual users.
Best Practices for Using RLS in 2026
When implementing Row-Level Security, a few best practices can make things smoother.
Avoid Complex Relationships
Bi-directional relationships in the data model can sometimes create unexpected filtering behavior. Keeping relationships simple usually works better.
Use Security Groups
Instead of adding hundreds of individual users to a role, it’s better to use Active Directory security groups and manage members there.
Combine RLS with Object-Level Security
If you also need to hide entire columns, such as salary data or profit margin, you can combine RLS with Object-Level Security (OLS).
Monitor Report Performance
Very complex RLS filters can sometimes slow down reports because they are evaluated every time visuals refresh.
Keeping your security logic simple helps maintain good report performance.
One Common Mistake People Make
One thing many Power BI users forget is that RLS does not apply to workspace admins or contributors.
If someone has permission to edit the report, they can still see all the data.
So when testing RLS, users should be assigned Viewer permissions only.
Final Thoughts
Row-Level Security is a very powerful feature in Power BI, especially for organizations that want to share dashboards with many teams but still control data access.
Instead of creating separate reports for every department, RLS allows businesses to maintain one single report while controlling which data each user can view.
Whether you implement Static RLS for small teams or Dynamic RLS for larger organizations, the main goal is always the same — secure data sharing with proper access control.
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