You need to ensure that the authors can see only their respective sales data. How should you complete the statement? To answer, drag the appropriate values the correct targets. Each value may be…

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Explanation

This question tests your ability to implement Row-Level Security (RLS) so that each author can only see their own sales records. The correct approach involves constructing a DAX filter expression or security predicate that matches the logged-in user's identity to a column in the data.

Approach. To restrict each author to only their own sales data, you implement Row-Level Security using a DAX expression such as [Author] = USERPRINCIPALNAME() (in Power BI) or [Author] = USERNAME(). This expression is applied as a role filter on the Sales table, so when a user logs in, the engine dynamically evaluates their identity and returns only rows where the Author column matches their account. In SQL Server RLS, the equivalent involves a security predicate function using SYSTEM_USER or USER_NAME() tied to a CREATE SECURITY POLICY statement. The key principle is: compare a user-identifying column in the table to a built-in identity function so the filter is dynamic and automatic per user.

Concept tested. Row-Level Security (RLS) - dynamically filtering data at the row level based on the authenticated user's identity, using DAX expressions (Power BI/Analysis Services) or security predicate functions (SQL Server). The core function pairing is a table column (e.g., [Author] or [SalesPerson]) with an identity function (USERPRINCIPALNAME(), USERNAME(), or SYSTEM_USER).

Reference. Microsoft Learn - Row-level security (RLS) with Power BI / SQL Server Row-Level Security documentation

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