Question 879 of 749
PL-300 Model the data Practice Question
A Power BI developer has a fact table that contains sales data at the transaction level. The table includes columns: TransactionID, ProductID, CustomerID, DateKey, Quantity, UnitPrice, Discount, and SalesAmount. The developer wants to create a measure for total sales after discount. Which approach is best for performance and accuracy?
⚠ Common exam trap
Candidates often assume a DAX measure using SUMX or a simple subtraction of aggregated columns is equivalent in performance, but the exam tests the understanding that pre-calculating row-level logic in Power Query (M) is the most performant approach for large fact tables, while also ensuring mathematical accuracy.
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
✓
Add a calculated column in Power Query: NetAmount = Quantity * UnitPrice - Discount, then create a measure: SUM(Sales[NetAmount])
It performs the net amount calculation at the row level in Power Query (M), which is computed during data refresh and stored in the table. This avoids runtime row-by-row iteration in DAX, making the measure SUM(Sales[NetAmount]) a simple, highly efficient aggregation. It ensures both performance and accuracy, as the discount is applied per transaction before aggregation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a measure: SUM(Sales[SalesAmount]) - SUM(Sales[Discount])
Why it's wrong here
This subtracts total discount from total sales, not per row.
- ✓
Add a calculated column in Power Query: NetAmount = Quantity * UnitPrice - Discount, then create a measure: SUM(Sales[NetAmount])
Why this is correct
Calculated columns are computed at refresh time, improving query performance.
- ✗
Create a measure: SUMX(Sales, Sales[Quantity] * Sales[UnitPrice] - Sales[Discount])
Why it's wrong here
SUMX iterates row by row, which can be slower than a calculated column.
- ✗
Create a measure: SUM(Sales[Quantity] * Sales[UnitPrice]) - SUM(Sales[Discount])
Why it's wrong here
This incorrectly aggregates before subtracting.
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Last reviewed: Jun 11, 2026
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