PL-300 · Question #307
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…
The correct answer is A. Yes. Power BI allows only one active relationship between two tables at a time, but supports multiple inactive relationships. The correct pattern for multiple date role-playing dimensions is: create one active relationship (e.g., Order Date → Date) and additional inactive…
Question
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a Power BI report that imports a date table and a sales table from an Azure SQL database data source. The sales table has the following date foreign keys:
- Due Date
- Order Date
- Delivery Date
You need to support the analysis of sales over time based on all the date foreign keys. Solution: For each date foreign key, you add inactive relationships between the sales table and the date table. Does this meet the goal?
Options
- AYes
- BNo
How the community answered
(46 responses)- A76% (35)
- B24% (11)
Explanation
Power BI allows only one active relationship between two tables at a time, but supports multiple inactive relationships. The correct pattern for multiple date role-playing dimensions is: create one active relationship (e.g., Order Date → Date) and additional inactive relationships for Due Date and Delivery Date. DAX measures can then activate a specific inactive relationship on demand using the USERELATIONSHIP() function (e.g., CALCULATE([Total Sales], USERELATIONSHIP(Sales[Due Date], Date[DateID]))). This enables independent time-based analysis for all three date keys without duplicating the date table. The proposed solution in the question is therefore valid - the answer is Yes.
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