Solving the issue of "The UseRelationship() and CrossFilter() function may not be used when querying 'Table' because it is constrained by row-level security."

 Solving the issue of "The UseRelationship() and CrossFilter() function may not be used when querying 'Table' because it is constrained by row-level security."


Error Statement, Problem, and Solution:

Error Statement: The error faced in the original scenario was related to the usage of USERELATIONSHIP function within row-level security constraints, leading to the error "The UseRelationship() and CrossFilter() function may not be used when querying 'Table' because it is constrained by row-level security."

Problem: The error prevented the usage of USERELATIONSHIP within row-level security constraints, impacting the ability to establish relationships between tables for filtering purposes in certain contexts.

Solution: To overcome the error and achieve the desired filtering based on dates without relying on USERELATIONSHIP, the DAX expression utilizes the TREATAS function along with ALL('Date'). This approach establishes a virtual relationship between the 'Date' table and the SalesHeader table, enabling filtering based on dates without encountering the row-level security constraint error.

Dax Formulae:

SalesAmount = CALCULATE(
SUM(Sales[SalesAmount]), 
ALL('Date'),
TREATAS(VALUES('Date'[Date]),Sales[STAGE_START_DATE])
)

Dax Explanation:

Purpose: The expression helps us understand how much money was made from sales transactions within a specific timeframe.

Sales Amount Calculation: It first adds up all the sales amounts to get the total sales value.

Date Filtering: Then, it uses a clever method to connect the sales data with dates. This ensures that only sales made within certain dates are counted.

ALL('Date'): This part makes sure that all the dates are considered, even if some dates don't have any sales. It's like looking at a calendar to see all the days, regardless of what's happening on each day.

TREATAS(VALUES('Date'[Date]), Sales[STAGE_START_DATE]): This part connects the sales data with the dates. It's like matching up each sale with the date it happened, so we can see how sales perform over time.

Conclusion:

This DAX expression helps us analyze sales performance over time by considering the relationship between sales data and dates. It ensures that we accurately count sales within specific date ranges, even when dealing with complex data relationships.

Feel free to ask any questions about Power BI. I am here to help you.

Happy Learning! 😊

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