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%)
   --> Identify patterns and trends
      --> Use grouping, binning, and clustering

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 want to combine several individual product SKUs into higher-level product families that reflect business-defined categories. Which feature should you use?

A. Binning
B. Clustering
C. Grouping
D. Calculated columns

Correct Answer: C

Explanation:
Grouping is designed to manually combine categorical values based on business logic. Binning is for numeric ranges, and clustering is AI-driven.

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Question 2

You are analyzing customer ages and want to see how many customers fall into ranges of 10 years (0–9, 10–19, 20–29, etc.). What is the best approach?

A. Grouping
B. Binning
C. Clustering
D. Sorting

Correct Answer: B

Explanation:
Binning groups continuous numeric values into ranges, making it ideal for age distributions and histogram-style analysis.

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Question 3

Which type of data is required to create bins in Power BI?

A. Text data
B. Date data only
C. Numeric data
D. Any data type

Correct Answer: C

Explanation:
Binning works only with numeric columns, such as integers or decimals.

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Question 4

You want Power BI to automatically segment customers based on similarity using multiple numeric fields such as revenue, order count, and profit. Which feature should you use?

A. Grouping
B. Binning
C. Clustering
D. Conditional formatting

Correct Answer: C

Explanation:
Clustering uses machine learning to automatically group data points based on similarity across multiple numeric dimensions.

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Question 5

Which statement best describes clustering in Power BI?

A. It requires predefined rules
B. It only works with categorical fields
C. It is AI-driven and exploratory
D. It replaces DAX calculations

Correct Answer: C

Explanation:
Clustering is an AI-driven exploratory feature that does not require predefined logic and works with numeric data.

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Question 6

You want to reduce the number of categories shown in a bar chart by combining smaller values into an “Other” category. Which feature supports this?

A. Binning
B. Grouping
C. Clustering
D. Drill-through

Correct Answer: B

Explanation:
Grouping allows you to manually create groups and optionally include an “Other” category to simplify visuals.

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Question 7

Which visual type commonly supports clustering in Power BI?

A. Table
B. Card
C. Scatter chart
D. Gauge

Correct Answer: C

Explanation:
Clustering is most commonly used in scatter charts, where multiple numeric dimensions define similarity.

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Question 8

What happens when you create a group, bin, or cluster in Power BI?

A. The source data is permanently changed
B. A new field is added to the model
C. The original column is deleted
D. A calculated measure is created

Correct Answer: B

Explanation:
Power BI creates a new field while leaving the original data unchanged.

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Question 9

When should you choose binning over grouping?

A. When combining text values
B. When using AI-based segmentation
C. When analyzing numeric value distributions
D. When creating drill-through pages

Correct Answer: C

Explanation:
Binning is best for numeric distributions, while grouping is best for categorical data.

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Question 10

Which of the following is a limitation of clustering in Power BI?

A. It cannot be edited
B. It requires clean, well-scaled numeric data
C. It only works in Power BI Desktop
D. It replaces grouping and binning

Correct Answer: B

Explanation:
Clustering results depend heavily on data quality and scale, and poor data can lead to misleading segments.

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Exam Readiness Summary

For the PL-300 exam, remember:

• Grouping → manual, categorical, business logic
• Binning → numeric ranges, distributions
• Clustering → AI-driven, multi-variable similarity
• All three create new fields, not source changes

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