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PL-900 Practice Question: Describe the business value of Microsoft Power Platform

Exhibit

Refer to the exhibit.
```dax
Total Sales = SUMX(Sales, Sales[Quantity] * Sales[UnitPrice])
```

Refer to the exhibit. You are building a Power BI report to analyze sales performance. You create a measure named 'Total Sales' using the DAX expression shown. However, the measure returns a value that is much higher than expected. What is the most likely issue?

⚠ Common exam trap

A common mix-up: candidates assume a missing relationship (Option A) is the cause of incorrect totals, but the real issue is that SUMX without a filter context iterates over all rows, producing an inflated value, while a missing relationship would typically cause blanks or errors in time-intelligence functions, not a higher sum.

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

The measure is using SUMX without an appropriate filter context, leading to incorrect row iteration.

The DAX expression shown uses SUMX, which iterates over each row of the Sales table and sums the product of Quantity and Price. Without an appropriate filter context (e.g., from a Date table or slicer), SUMX may aggregate over the entire table, including rows that should be excluded, leading to a much higher total than expected. The issue is not a missing relationship but rather the lack of a proper filter context to restrict the rows being iterated.

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 Sales table lacks a relationship to the Date table, causing incorrect time-based calculations.

    Why it's wrong here

    Missing relationships would cause blanks or errors, not inflated values.

  • The measure is using SUMX without an appropriate filter context, leading to incorrect row iteration.

    Why this is correct

    SUMX iterates the Sales table; if the model has a many-to-many relationship or missing filters, it may sum incorrectly.

  • The measure is being filtered by a disconnected slicer, causing overfiltering.

    Why it's wrong here

    Overfiltering would reduce values, not increase them.

  • The measure should use DISTINCTCOUNT instead of SUMX to count sales.

    Why it's wrong here

    DISTINCTCOUNT counts unique values, not sums; not appropriate for total sales.

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