This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Prepare the data (25–30%)
   --> Transform and load the data
      --> Pivot, Unpivot, and Transpose Data

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

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Question 1

A dataset contains monthly sales stored in separate columns named Jan, Feb, Mar, and so on. You need to create a time-series visual that supports filtering by month. What should you do?

A. Pivot the Month columns
B. Unpivot the Month columns
C. Transpose the table
D. Create calculated columns in DAX

Correct Answer: B

Explanation:
Unpivoting converts repeated value columns into a single attribute–value pair, producing a normalized structure suitable for time-series analysis.

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Question 2

You want to convert unique values from a column into individual columns, displaying aggregated results per category. Which transformation should you use?

A. Unpivot Columns
B. Transpose Table
C. Pivot Columns
D. Group By

Correct Answer: C

Explanation:
Pivoting turns values from one column into multiple columns, often requiring an aggregation function such as Sum or Count.

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Question 3

Which transformation flips all rows into columns and columns into rows?

A. Pivot
B. Unpivot
C. Group By
D. Transpose

Correct Answer: D

Explanation:
Transpose rotates the entire table structure and is typically used when the table orientation is incorrect.

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Question 4

After transposing a table, the first row now contains the desired column headers. What should you do next?

A. Unpivot Columns
B. Rename columns manually
C. Promote the first row to headers
D. Create a calculated table

Correct Answer: C

Explanation:
Promoting the first row to headers finalizes the transformation after transposing data.

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Question 5

Which scenario best indicates that unpivoting is required?

A. Values in a column need to be summarized
B. Categories should become column headers
C. Repeating attribute columns must become rows
D. Data needs to be grouped by multiple keys

Correct Answer: C

Explanation:
Unpivoting is used to normalize data where multiple columns represent the same attribute (such as months or measures).

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Question 6

What is a potential negative impact of pivoting data in Power Query?

A. Increased DAX complexity
B. Reduced model performance due to many columns
C. Loss of relationships
D. Automatic removal of measures

Correct Answer: B

Explanation:
Pivoting can significantly increase the number of columns, bloating the model and negatively affecting performance.

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Question 7

You receive a dataset where column headers are stored in the first column instead of the first row. Which transformation is most appropriate?

A. Unpivot
B. Pivot
C. Transpose
D. Group By

Correct Answer: C

Explanation:
Transposing the table re-orients rows and columns so headers can be promoted correctly.

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Question 8

Which transformation often requires you to specify an aggregation function?

A. Transpose
B. Unpivot
C. Pivot
D. Remove Columns

Correct Answer: C

Explanation:
Pivoting may result in multiple values for a new column and therefore requires aggregation (Sum, Count, Average, etc.).

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Question 9

You want to keep identifier columns (such as ProductID and Region) while converting all other columns into rows. Which option is best?

A. Pivot Selected Columns
B. Unpivot Other Columns
C. Transpose Table
D. Group By

Correct Answer: B

Explanation:
Unpivot Other Columns preserves key identifier columns while normalizing all remaining columns.

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Question 10

Which statement reflects a PL-300 best practice for reshaping data?

A. Always pivot data before loading
B. Use transpose for large fact tables
C. Normalize data before modeling when possible
D. Avoid unpivoting to improve performance

Correct Answer: C

Explanation:
Normalized (unpivoted) data supports better filtering, relationships, and DAX flexibility, which aligns with PL-300 modeling principles.

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Final Exam Tips for This Topic

• Identify whether the data is wide or tall
• Pivot = rows → columns
• Unpivot = columns → rows
• Transpose = rotate entire table
• Watch for aggregation requirements when pivoting
• The exam emphasizes choosing the right transformation, not UI memorization

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