This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Create single aggregation measures

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

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Practice Questions

Question 1

You need a measure that calculates total sales amount and responds to report slicers. Which DAX expression should you use?

A. Total Sales = Sales[SalesAmount]
B. Total Sales = SUM(Sales[SalesAmount])
C. Total Sales = CALCULATE(Sales[SalesAmount])
D. Total Sales = SUMX(Sales, Sales[SalesAmount])

✅ Correct Answer: B

Explanation:
SUM() is the correct single aggregation function for adding numeric values in a column. It automatically responds to filter context. SUMX() is unnecessary for simple aggregations.

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Question 2

Which function should you use to count the total number of rows in a fact table?

A. COUNT()
B. COUNTA()
C. COUNTROWS()
D. SUM()

✅ Correct Answer: C

Explanation:
COUNTROWS() counts rows in a table regardless of column values and is the preferred approach for counting records in fact tables.

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Question 3

A column contains text values and blanks. You want to count the number of non-blank entries. Which function should you use?

A. COUNT()
B. COUNTA()
C. COUNTROWS()
D. SUM()

✅ Correct Answer: B

Explanation:
COUNTA() counts non-blank values across all data types, including text, making it ideal for this scenario.

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Question 4

Why should aggregation logic typically be implemented as a measure rather than a calculated column?

A. Measures consume more memory
B. Measures are evaluated at data refresh
C. Measures respond to filter context
D. Calculated columns are faster at query time

✅ Correct Answer: C

Explanation:
Measures are evaluated at query time and dynamically respond to slicers, filters, and visuals. Calculated columns are static and do not react to user interaction.

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Question 5

Which aggregation function returns the arithmetic mean of a numeric column?

A. SUM()
B. AVERAGEX()
C. AVERAGE()
D. COUNT()

✅ Correct Answer: C

Explanation:
AVERAGE() performs a simple mean over a single column. AVERAGEX() is an iterator and is unnecessary for basic aggregations.

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Question 6

You drag a numeric column into a visual and Power BI automatically creates a sum. What type of measure is this?

A. Calculated measure
B. Explicit measure
C. Implicit measure
D. Calculated column

✅ Correct Answer: C

Explanation:
Implicit measures are automatically generated by Power BI when a field is placed in a visual. The PL-300 exam favors explicit measures created with DAX.

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Question 7

Which DAX expression correctly counts the number of orders in a Sales table?

A. Order Count = COUNT(Sales)
B. Order Count = COUNT(Sales[OrderID])
C. Order Count = COUNTROWS(Sales)
D. Order Count = COUNTA(Sales)

✅ Correct Answer: C

Explanation:
COUNTROWS() is the safest and most reliable method for counting records in a table. COUNT() requires a numeric column and may produce misleading results.

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Question 8

What happens to a single aggregation measure when a slicer is applied?

A. The value remains unchanged
B. The measure recalculates based on filter context
C. The measure recalculates only at refresh
D. The measure stops working

✅ Correct Answer: B

Explanation:
Measures automatically recalculate based on the current filter context created by slicers, filters, and visuals.

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Question 9

Which function returns the earliest date in a filtered context?

A. FIRSTDATE()
B. MIN()
C. EARLIEST()
D. STARTDATE()

✅ Correct Answer: B

Explanation:
MIN() returns the smallest value in a column and works correctly with dates and filter context. It is a valid single aggregation function.

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Question 10

Which of the following is the best practice when creating aggregation measures for PL-300?

A. Use calculated columns whenever possible
B. Use implicit measures to save time
C. Use explicit measures with clear naming
D. Avoid formatting measures

✅ Correct Answer: C

Explanation:
Explicit measures with clear, business-friendly names are reusable, easier to maintain, and strongly aligned with PL-300 expectations.

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Final Exam Tips 💡

• Expect COUNT vs COUNTROWS vs COUNTA questions
• Prefer SUM over SUMX for simple totals
• Measures always respect filter context
• Avoid calculated columns for aggregations
• Clear naming and formatting matter

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