Wednesday 27 December 2023

What does a SUMX function do calculated column ? Power BI interview questions and answers 154

 What does a SUMX function do calculated column ?

The SUMX function in Power BI calculates the sum of an expression evaluated for each row in a table, allowing for more complex and dynamic calculations compared to the standard SUM function. It's often used in calculated columns to create new measures that incorporate row-by-row calculations.

Here's how it works:


Code snippet

SUMX(<table>, <expression>)


  • table: The table containing the rows you want to iterate over.

  • expression: The expression to evaluate for each row, typically involving calculations or references to other columns in the same table.

Key Characteristics:

  • Iterative Calculation: SUMX processes each row individually, applying the expression to each row's values and accumulating the results.

  • Context Awareness: It respects filters and context within your data model, ensuring accurate calculations based on the current filtering state.

  • Complex Expressions: You can use a wide range of DAX functions and operators within the expression to perform sophisticated calculations.


Code snippet

Total Cost = SUMX(Sales, Sales[Quantity] * Sales[UnitPrice])

This calculated column calculates the total cost of items sold by multiplying the quantity and unit price for each row in the Sales table and summing the results.

Common Use Cases:

  • Calculating weighted averages.

  • Determining totals based on conditional logic.

  • Performing complex aggregations involving multiple columns.

  • Creating custom measures for specific analysis needs.

Performance Considerations:

  • SUMX is generally slower than SUM due to its iterative nature.

  • Optimize expressions for efficiency and consider using SUMMARIZE for aggregations where possible.

By mastering SUMX, you can unlock powerful analytical capabilities within your Power BI models, enabling you to create more sophisticated calculations and gain deeper insights from your data.

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