PL-300 Visualize and analyze the data Practice Question
A Power BI report contains a table visual that displays employee names and their total sales. The data model includes an Employee table with columns: EmployeeID, Name, Department, and HireDate. The Sales table has columns: SaleID, EmployeeID, Amount, and SaleDate. The relationship between Employee and Sales is one-to-many. The user wants to see only employees who have made at least one sale. However, the table shows all employees, including those with no sales (blank Amount). What is the most likely reason?
⚠ Common exam trap
A common mix-up: candidates assume a one-to-many relationship will automatically hide employees without related sales, but Power BI does not apply implicit row-level security or auto-filtering for missing related records; you must explicitly filter out blank values.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
There is no visual-level filter to exclude blank values.
The table visual is showing all employees due to the absence of a visual-level filter to exclude blank or zero sales amounts. In Power BI, a one-to-many relationship between Employee and Sales means that employees without sales will still appear in the visual unless explicitly filtered out, as the relationship does not automatically suppress rows from the 'one' side when there are no matching rows on the 'many' side.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The EmployeeID column in the Employee table is hidden.
Why it's wrong here
Hiding the EmployeeID column in the Employee table only removes it from the report field list and canvas; it does not alter the underlying data model, relationship behavior, or filter propagation. The Employee Name column remains visible and unaffected, so hiding a key column used for the relationship cannot cause employees with no sales to appear in the table visual. Hidden columns are a presentation-layer change, not a data or filtering change.
- ✗
The relationship is many-to-one, not one-to-many.
Why it's wrong here
The relationship cardinality described as one-to-many (Employee to Sales) is correctly configured for a dimension-to-fact relationship. If it were many-to-one (Sales to Employee), the filter flow would still work in the same direction from Employee to Sales, so employees with no matching sales would still appear unless a filter excludes blanks. Cardinality defines uniqueness and matching rules, but it does not determine whether rows with no related records are displayed; that is controlled by filter context, not by the cardinality label.
- ✗
The relationship direction is set to Single from Employee to Sales.
Why it's wrong here
Setting the relationship direction to Single from Employee to Sales means that filters applied on the Employee table propagate to the Sales table, which is the standard and correct configuration for this scenario. A single-direction filter does not cause employees with no sales to appear; rather, it ensures that filtering by an employee limits the sales shown. The appearance of all employees, including those with zero corresponding sales rows, is a result of the absence of a filter on the Amount field, not the relationship direction.
- ✓
There is no visual-level filter to exclude blank values.
Why this is correct
To show only employees who have at least one sales record, a visual-level filter must be applied on the Amount field to exclude blank values (e.g., 'Amount is not blank' or 'Amount > 0'). Without such a filter, the table visual displays every row from the Employee dimension, even those without any related Sales rows, because Power BI's default behavior is to show all dimension rows unless a filter explicitly removes them. A visual-level filter on a measure or column from the fact table is the standard technique to restrict the visual to only employees with sales.
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