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%)
   --> Optimize model performance
      --> Identify poorly performing measures, relationships, and visuals by using 
          Performance Analyzer and DAX query view

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

You run Performance Analyzer on a report page and notice that a visual has a very high DAX Query duration but a low Visual Display duration. What is the most likely cause?

A. The visual contains too many fields
B. The measure used by the visual is inefficient
C. The report page has too many visuals
D. The dataset refresh frequency is too high

✅ Correct Answer: B

Explanation:
A high DAX Query time indicates that the bottleneck occurs during DAX execution, which typically points to inefficient measures, complex calculations, or inefficient filter context.

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Question 2

Which Power BI tool allows you to view and execute DAX queries generated by report visuals?

A. Model View
B. Performance Analyzer
C. DAX Query View
D. Power Query Editor

✅ Correct Answer: C

Explanation:
DAX Query View enables analysts to inspect and test DAX queries independently of visuals, making it ideal for diagnosing measure-level performance issues.

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Question 3

You observe that multiple visuals across different report pages are slow, even though they use different visual types. What is the most likely root cause?

A. A complex report theme
B. Inefficient shared measures
C. Excessive visual formatting
D. Dataset refresh settings

✅ Correct Answer: B

Explanation:
If multiple visuals are slow across pages, the issue is often a shared measure or relationship rather than a visual-specific configuration.

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Question 4

Which Performance Analyzer metric helps you determine whether slowness is caused by rendering rather than DAX?

A. Total Load Time
B. DAX Query
C. Other
D. Visual Display

✅ Correct Answer: D

Explanation:
High Visual Display time indicates the visual itself (layout, formatting, or rendering complexity) is the primary performance bottleneck.

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Question 5

Which relationship configuration is most likely to negatively impact model performance?

A. One-to-many with single direction
B. Many-to-many with bi-directional filtering
C. One-to-one with single direction
D. Inactive relationship

✅ Correct Answer: B

Explanation:
Many-to-many relationships combined with bi-directional filtering significantly increase filter propagation complexity and often degrade performance.

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Question 6

You copy a DAX query from Performance Analyzer and run it in DAX Query View. Why is this useful?

A. To change the visual’s formatting
B. To validate data refresh schedules
C. To isolate and analyze query performance
D. To modify relationships automatically

✅ Correct Answer: C

Explanation:
Running queries in DAX Query View helps isolate performance issues at the DAX level, independent of visual rendering.

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Question 7

A table visual renders slowly, but Performance Analyzer shows low DAX Query time. What should you investigate next?

A. Measure logic
B. Data model relationships
C. Visual complexity and row count
D. Dataset size on disk

✅ Correct Answer: C

Explanation:
Low DAX time but slow rendering suggests the issue is visual-related—such as high row counts, many columns, or heavy formatting.

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Question 8

Which DAX pattern is most commonly associated with poor performance when overused?

A. Simple aggregations like SUM
B. Iterators such as SUMX and FILTER
C. Implicit measures
D. Column sorting

✅ Correct Answer: B

Explanation:
Iterator functions evaluate row by row and can significantly slow down DAX queries when used excessively or unnecessarily.

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Question 9

Why can unnecessary bi-directional relationships negatively affect report performance?

A. They increase dataset size
B. They prevent refresh from completing
C. They increase filter propagation complexity
D. They disable query folding

✅ Correct Answer: C

Explanation:
Bi-directional filtering increases the number of filter paths Power BI must resolve, often leading to slower query execution.

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Question 10

What is the primary purpose of Performance Analyzer in Power BI Desktop?

A. Optimize dataset refresh times
B. Rewrite inefficient DAX automatically
C. Identify which visuals are slow and why
D. Monitor gateway performance

✅ Correct Answer: C

Explanation:
Performance Analyzer helps identify slow visuals and breaks down execution time, allowing analysts to pinpoint whether the issue lies in DAX, rendering, or other overhead.

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Key Exam Takeaways

• Performance Analyzer identifies where time is spent
• DAX Query View helps analyze why queries are slow
• High DAX Query time → measure or relationship issue
• High Visual Display time → visual design issue
• Bi-directional and many-to-many relationships are frequent performance culprits

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