This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Visualize and analyze the data (25–30%)
   --> Create reports
      --> Select an appropriate visual

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 to compare total sales across multiple product categories. Each category has a single aggregated value.
Which visual is most appropriate?

A. Line chart
B. Scatter chart
C. Column chart
D. Card

Correct Answer: C

Explanation:
Column (or bar) charts are best for comparing values across discrete categories. Line charts are better for trends over time, and cards only show a single value.

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Question 2

A business user wants to see how revenue changes month over month for the last three years.
Which visual should you choose?

A. Area chart
B. Line chart
C. Pie chart
D. Treemap

Correct Answer: B

Explanation:
Line charts are ideal for showing trends over time and are the standard choice for time-series analysis in Power BI.

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Question 3

You want to show the percentage contribution of each region to total sales, with only four regions.
Which visual is most appropriate?

A. Table
B. Scatter chart
C. Pie chart
D. Waterfall chart

Correct Answer: C

Explanation:
Pie charts are appropriate for part-to-whole comparisons when there are only a few categories. With many categories, they become difficult to interpret.

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Question 4

A report needs to highlight a single KPI: Total Revenue for the current year.
Which visual should you use?

A. Gauge
B. Card
C. Column chart
D. Matrix

Correct Answer: B

Explanation:
A card visual is designed to display a single aggregated value clearly and prominently.

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Question 5

You want to analyze the relationship between advertising spend and total sales to see if higher spend correlates with higher sales.
Which visual is best?

A. Line chart
B. Scatter chart
C. Stacked column chart
D. Treemap

Correct Answer: B

Explanation:
Scatter charts are used to analyze relationships between two numerical measures and are ideal for identifying correlations and outliers.

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Question 6

A user wants to see how total sales break down by category and subcategory in a hierarchical way.
Which visual should you choose?

A. Pie chart
B. Table
C. Treemap
D. Line chart

Correct Answer: C

Explanation:
Treemaps are designed to display hierarchical data and part-to-whole relationships at multiple levels.

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Question 7

You want to compare actual sales versus target sales across multiple regions.
Which visual is most appropriate?

A. Stacked bar chart
B. Scatter chart
C. Line chart
D. Card

Correct Answer: A

Explanation:
A stacked bar (or column) chart allows easy comparison between actual and target values across categories.

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Question 8

A report must show the distribution of order values to identify outliers.
Which visual best supports this requirement?

A. Line chart
B. Pie chart
C. Histogram
D. Card

Correct Answer: C

Explanation:
Histograms are used to show the distribution of numeric data and are effective for spotting skewness and outliers.

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Question 9

You want to display sales trends for multiple regions side-by-side without cluttering a single chart.
Which Power BI feature or visual approach is most appropriate?

A. Pie charts
B. Small multiples
C. KPI visuals
D. Gauge charts

Correct Answer: B

Explanation:
Small multiples allow you to repeat the same visual across categories, making comparisons easier without overcrowding a single chart.

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Question 10

Which of the following is the most important factor when selecting a visual in Power BI?

A. The number of available visuals
B. The visual that looks the most impressive
C. The business question being answered
D. The amount of data in the model

Correct Answer: C

Explanation:
Visual selection should always be driven by the business question and the insight you want to communicate, not by aesthetics or volume of data.

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