Why RLS protects sensitive data in Power BI - Dashboard Impact

Dashboard Mode - Why RLS protects sensitive data

Business Question

How does Row-Level Security (RLS) protect sensitive data by restricting what each user can see in a sales report?

Sample Data

Salesperson	Region	Sales Amount
Alice	North	1000
Bob	South	1500
Charlie	East	1200
Diana	West	1300
Eva	North	1100
Frank	South	1400

Dashboard Components

• KPI Card: Total Sales
  Formula: Total Sales = SUM('Sales'[Sales Amount])
  Result: 7500
• Bar Chart: Sales by Region
  Shows total sales grouped by Region:
  North: 2100, South: 2900, East: 1200, West: 1300
• Table: Salesperson Details
  Shows Salesperson, Region, and Sales Amount rows filtered by RLS
• RLS Rule: Users see only rows where Region = LOOKUPVALUE('UserRegion'[Region], 'UserRegion'[User], USERPRINCIPALNAME())
  Example: User assigned to 'North' sees only North region rows

Dashboard Layout

+----------------------+----------------------+
|      Total Sales      |   Sales by Region    |
|      (KPI Card)       |     (Bar Chart)      |
+----------------------+----------------------+
|          Salesperson Details Table           |
|                (Filtered by RLS)             |
+----------------------------------------------+

Interactivity

The RLS filter automatically limits data shown in all components based on the logged-in user's assigned region. No manual filter needed. When a user logs in, Power BI applies the RLS rule to show only rows matching their region. This updates the KPI, bar chart, and table to show only their allowed data.

Self Check

If you add a filter for Region = 'South', which components update?

• The KPI Card will show total sales only for South region (2900).
• The Bar Chart will update to show sales only for South region.
• The Salesperson Details Table will show only salespeople from South region.
• If RLS is active and user is assigned to 'North', no data will show because South region is outside their allowed data.

Key Result

Dashboard shows how RLS restricts sales data by region to protect sensitive information.

Practice

1. What is the main purpose of Row-Level Security (RLS) in Power BI?

easy

A. To speed up data refresh times

B. To change the visual design of the report for each user

C. To create new calculated columns automatically

D. To restrict data access by filtering rows based on the user's identity

Solution

1. Step 1: Understand RLS functionality

   RLS filters data rows so users only see data they are allowed to access.

2. Step 2: Compare options

   Speeding up refresh times, changing visual design, and creating calculated columns describe unrelated features; only restricting data access by filtering rows based on user identity matches RLS purpose.

3. Final Answer:

   To restrict data access by filtering rows based on the user's identity -> Option D

4. Quick Check:

   RLS filters rows by user identity = C [OK]

Hint: RLS controls data visibility per user, not report design [OK]

Common Mistakes:

• Confusing RLS with report formatting
• Thinking RLS speeds up data refresh
• Believing RLS creates new columns

2. Which of the following is the correct way to define a filter in a Power BI RLS role?

easy

A. FILTER('Sales', 'Sales'[Region] = "USERNAME()")

B. FILTER('Sales', 'Sales'[Region] == USERNAME())

C. FILTER('Sales', 'Sales'[Region] = USERPRINCIPALNAME())

D. FILTER('Sales', 'Sales'[Region] = USERNAME())

Solution

1. Step 1: Identify correct DAX function for user identity

   USERPRINCIPALNAME() returns the logged-in user's full username, commonly used in RLS filters.

2. Step 2: Check syntax correctness

   FILTER('Sales', 'Sales'[Region] = USERPRINCIPALNAME()) uses correct syntax and function. Using double equals (==), treating the function as a string, or using USERNAME() instead misuses syntax or less preferred function.

3. Final Answer:

   FILTER('Sales', 'Sales'[Region] = USERPRINCIPALNAME()) -> Option C

4. Quick Check:

   Use USERPRINCIPALNAME() for RLS filters = A [OK]

Hint: Use USERPRINCIPALNAME() for user-based filters in RLS [OK]

Common Mistakes:

• Using USERNAME() instead of USERPRINCIPALNAME()
• Using double equals (==) in DAX
• Putting USERNAME() inside quotes

3. Given this RLS filter on the 'Sales' table:
FILTER('Sales', 'Sales'[Salesperson] = USERPRINCIPALNAME())
If the logged-in user is '[e-mail]', what data will Alice see?

medium

A. All sales data regardless of salesperson

B. Only sales where 'Salesperson' equals '[e-mail]'

C. No data because USERPRINCIPALNAME() is invalid

D. Sales data for all salespersons except '[e-mail]'

Solution

1. Step 1: Understand the filter condition

   The filter keeps rows where 'Salesperson' matches the logged-in user's email.

2. Step 2: Apply the filter for user '[e-mail]'

   Only rows with 'Salesperson' = '[e-mail]' remain visible to Alice.

3. Final Answer:

   Only sales where 'Salesperson' equals '[e-mail]' -> Option B

4. Quick Check:

   RLS shows user-specific rows = B [OK]

Hint: RLS filters rows matching logged-in user exactly [OK]

Common Mistakes:

• Assuming all data is visible
• Thinking USERPRINCIPALNAME() is invalid
• Believing data for other users is shown

4. You created this RLS role filter:
FILTER('Orders', 'Orders'[Country] = USERNAME())
But users report seeing no data. What is the most likely issue?

medium

A. USERNAME() returns only the username, not the country name

B. FILTER function is not supported in RLS roles

C. The table name 'Orders' is misspelled

D. RLS roles cannot filter by text columns

Solution

1. Step 1: Understand USERNAME() output

   USERNAME() returns the user's login name, not a country name.

2. Step 2: Compare USERNAME() with 'Country' column

   Since 'Country' contains country names, the filter never matches, so no data shows.

3. Final Answer:

   USERNAME() returns only the username, not the country name -> Option A

4. Quick Check:

   Mismatch between USERNAME() and column values = A [OK]

Hint: Match USERPRINCIPALNAME() or correct user info to column values [OK]

Common Mistakes:

• Assuming USERNAME() returns country
• Thinking FILTER is unsupported in RLS
• Ignoring case sensitivity in filters

5. You want to protect sensitive sales data so that each regional manager sees only their region's data. Which approach best uses RLS to achieve this?

hard

A. Create a role with filter 'Sales'[Region] = LOOKUPVALUE('Managers'[Region], 'Managers'[Email], USERPRINCIPALNAME()) and assign managers by email

B. Do not use RLS; instead, create separate reports for each region

C. Create a role with filter 'Sales'[Region] = "Region1" and assign all managers to this role

D. Create a role with filter 'Sales'[Region] = USERPRINCIPALNAME() and assign managers their email as region

Solution

1. Step 1: Understand the need for dynamic filtering

   Each manager should see data for their assigned region, which may differ from their username.

2. Step 2: Use LOOKUPVALUE to map manager email to region

   Create a role with filter 'Sales'[Region] = LOOKUPVALUE('Managers'[Region], 'Managers'[Email], USERPRINCIPALNAME()) and assign managers by email uses LOOKUPVALUE to find the manager's region from a 'Managers' table, enabling correct filtering.

3. Step 3: Evaluate other options

   Create a role with filter 'Sales'[Region] = USERPRINCIPALNAME() and assign managers their email as region incorrectly assumes email equals region; C assigns all managers to one region; B avoids RLS and is less efficient.

4. Final Answer:

   Create a role with filter 'Sales'[Region] = LOOKUPVALUE('Managers'[Region], 'Managers'[Email], USERPRINCIPALNAME()) and assign managers by email -> Option A

5. Quick Check:

   Use LOOKUPVALUE for dynamic RLS filtering = D [OK]

Hint: Use LOOKUPVALUE to map users to their data dynamically [OK]

Common Mistakes:

• Assuming username equals region directly
• Assigning all users to one static region
• Avoiding RLS and duplicating reports