The answer is that the measure is suffering from a SUMX aggregation granularity error, because it aggregates each column separately before multiplying. When you use SUM(Sales[Discount]) * SUM(Sales[Quantity]) * SUM(Sales[UnitPrice]), Power BI first totals all discounts, all quantities, and all unit prices across the entire filter context, then multiplies those three large numbers together. This produces a wildly inflated result whenever multiple discount percentages exist, as it fails to compute the discount per individual transaction. On the PL-300 exam, this scenario tests your understanding of row context versus filter context, and the correct fix is to replace the three SUM functions with a single SUMX that iterates over each row of the Sales table, calculating Discount * Quantity * UnitPrice row by row before summing. A common trap is assuming that multiplying aggregated values is safe, but it only works when there is a single value per column in the filter context. Memory tip: “SUMX walks the rows; SUM skips the rows.”
PL-300 Model the data Practice Question
This PL-300 practice question tests your understanding of model the data. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are building a data model for a retail company. The 'Sales' fact table has a column 'Discount' that is a percentage (0 to 1). You create a measure 'Total Discount Amount' = SUM(Sales[Discount]) * SUM(Sales[Quantity]) * SUM(Sales[UnitPrice]). However, the measure returns incorrect results when multiple discount percentages exist in the same filter context. What is the issue?
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 performing aggregations at the wrong granularity; it should use SUMX to iterate over each row.
The measure uses SUM on each column individually, which aggregates all values in the filter context before multiplying. When multiple discount percentages exist, this incorrectly multiplies the total of all discounts by the total of all quantities and total of all unit prices, rather than computing discount per row. The correct approach is to use SUMX to iterate over each row of the Sales table, calculating Discount * Quantity * UnitPrice per row and then summing those row-level results, ensuring accurate granularity.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 measure contains a circular dependency.
Why it's wrong here
No circular dependency exists.
✓
The measure is performing aggregations at the wrong granularity; it should use SUMX to iterate over each row.
Why this is correct
SUMX ensures row-by-row calculation before summing.
Related concept
Read the scenario before looking for a memorised answer.
✗
The measure is referencing columns from different tables without proper relationships.
Why it's wrong here
All columns are in the same table.
✗
The Discount column should be of type Decimal instead of Percentage.
Why it's wrong here
Data type is not the core issue.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume SUM works correctly for all multiplicative measures, overlooking that SUM aggregates before multiplication, while SUMX is required for row-by-row calculations in DAX.
Detailed technical explanation
How to think about this question
Under the hood, SUM operates on the entire column in the current filter context, collapsing all rows into a single scalar before multiplication. In contrast, SUMX iterates row-by-row, evaluating the expression for each row and then summing the results. This distinction is critical in DAX when dealing with row-level calculations, such as applying a discount percentage per line item. A real-world scenario: if one sale has a 10% discount and another 20%, SUM incorrectly computes (0.10+0.20) * (Qty1+Qty2) * (Price1+Price2), while SUMX correctly computes (0.10*Qty1*Price1) + (0.20*Qty2*Price2).
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Model the data — This question tests Model the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The measure is performing aggregations at the wrong granularity; it should use SUMX to iterate over each row. — The measure uses SUM on each column individually, which aggregates all values in the filter context before multiplying. When multiple discount percentages exist, this incorrectly multiplies the total of all discounts by the total of all quantities and total of all unit prices, rather than computing discount per row. The correct approach is to use SUMX to iterate over each row of the Sales table, calculating Discount * Quantity * UnitPrice per row and then summing those row-level results, ensuring accurate granularity.
What should I do if I get this PL-300 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
This PL-300 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PL-300 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.