Row-Level Security (RLS)

Row-Level Security (RLS) in Power BI is a feature that restricts data access at the row level based on user roles. It allows organizations to enforce access control policies so that users can only see data relevant to them. This is particularly useful in scenarios where different users, such as sales managers, regional heads, or department executives, need access to specific subsets of data without exposing the entire dataset.

By implementing RLS, organizations can:

Ensure data privacy and security.

Reduce the need to create multiple datasets for different users.

Improve report performance by handling access control at the data level.

Power BI provides two main approaches to RLS: Static RLS and Dynamic RLS.

Static vs. Dynamic RLS

Static Row-Level Security (RLS)

Static RLS is a straightforward approach where users are assigned fixed roles, and access is restricted based on predefined filter rules. This method requires manual configuration of security roles in Power BI Desktop.

Example:

Consider a sales dataset where data is divided by regions (North, South, East, West). If each regional manager should only see data for their respective region, you can define roles such as:

North_Region → Filter: Region = “North”

South_Region → Filter: Region = “South”

When a user is assigned to the North_Region role, they can only access records where Region = “North”. However, Static RLS requires manual updates if new regions or users are added.

Pros:

Simple to implement.

Works well for small datasets with fixed security rules.

Cons:

Requires manual maintenance for each role.

Not scalable for large organizations with dynamic user-role mappings.

Dynamic Row-Level Security (RLS)

Dynamic RLS uses user identity (e.g., email or username) to control data access dynamically. Instead of manually assigning users to roles, it relies on a security table that maps users to the data they can access.

Example:
A security table in your database might look like this:

UserEmail Region

john@company.com North

mary@company.com South

mike@company.com East

Then, in Power BI, a DAX filter is applied:

DAX

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[UserEmail] = USERPRINCIPALNAME()

When john@company.com logs in, Power BI filters the dataset to show only data where Region = “North”.

Pros:

Automatically scales for new users and changing assignments.

Easier to maintain compared to Static RLS.

More flexible and dynamic.

Cons:

Requires a user-role mapping table in the data model.

Can be complex to configure.

Configuring RLS in Power BI Desktop

Step 1: Define Roles in Power BI Desktop

Open Power BI Desktop and load your dataset.

Go to the Modeling tab and click Manage Roles.

Click Create and define a new role.

Apply a DAX filter based on the user’s role. For Static RLS, it might be:

DAX

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[Region] = “North”

For Dynamic RLS, use:

DAX
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[UserEmail] = USERPRINCIPALNAME()

Save and close the Manage Roles window.

Step 2: Test RLS in Power BI Desktop

Click View As Roles in the Modeling tab.

Select a role and verify if the data is correctly filtered.

You can also test as a specific user by entering an email.

Configuring RLS in Power BI Service

Step 1: Publish the Report to Power BI Service

Save and publish your Power BI file to Power BI Service.

Step 2: Assign Users to Roles

Open Power BI Service and navigate to your dataset.

Click on Security.

Select the role you created in Power BI Desktop.

Add users or security groups who should have access.

Step 3: Test RLS in Power BI Service

Click on the Ellipsis (⋮) > Test as role.

Enter a user’s email to verify if they see the correct filtered data.

Best Practices for Implementing RLS

Use Dynamic RLS for large organizations to avoid frequent manual updates.

Store security mappings in a separate security table.

Always test roles before deploying to production.

Avoid using multiple roles for the same user; instead, use hierarchical filtering.

Use Power BI Service Security Groups instead of individual users for easier management.

Conclusion

Row-Level Security (RLS) is a powerful feature in Power BI that ensures users only see relevant data based on their roles. While Static RLS is simpler for small datasets, Dynamic RLS offers greater flexibility and scalability. By correctly configuring RLS in Power BI Desktop and Power BI Service, organizations can enhance security, improve performance, and maintain better control over data access.Open Power BI Desktop and load your dataset.

UserEmail	Region
john@company.com	North
mary@company.com	South
mike@company.com	East

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Row-Level Security (RLS)

Configuring RLS in Power BI Service

Conclusion