Cross Filtering and Cross Highlighting in Power BI control how visuals interact with each other. Cross Filtering replaces the data in connected visuals based on the selection, while Cross Highlighting emphasizes the selected portion while keeping the rest visible for comparison. Mastering these interactions helps create insightful, interactive dashboards.
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What is the main purpose of Cross Filtering in Power BI?
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Question 2 of 15
2. Question
What does Cross Highlighting do in Power BI?
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Question 3 of 15
3. Question
In which menu can you modify Cross Filter and Cross Highlight settings?
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Question 4 of 15
4. Question
What icon represents Cross Filtering when editing interactions?
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Question 5 of 15
5. Question
What icon represents Cross Highlighting when editing interactions?
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Question 6 of 15
6. Question
Can a visual in Power BI be set to neither filter nor highlight others?
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Question 7 of 15
7. Question
Which interaction type is more suitable for comparing selected data with the overall context?
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Question 8 of 15
8. Question
Which interaction type completely removes unrelated data from connected visuals?
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Question 9 of 15
9. Question
When selecting a bar in a bar chart, other visuals highlight partial bars — this is an example of:
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Question 10 of 15
10. Question
Which feature ensures that multiple visuals stay in sync with the same filter selection?
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Question 11 of 15
11. Question
Can Cross Highlighting be used in map visuals?
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Question 12 of 15
12. Question
How does Cross Filtering affect performance in large datasets?
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Question 13 of 15
13. Question
Which is the default interaction between visuals in Power BI?
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Question 14 of 15
14. Question
How can you completely disable all interactions for a visual?
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Question 15 of 15
15. Question
Which is better for showing a narrow focus without distraction from unrelated data?
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Summary
This quiz on Cross Filtering and Cross Highlighting in Power BI helps you understand how visuals interact to refine insights. By mastering these interaction types, you can create dashboards that are both interactive and user-friendly, allowing clear data focus or contextual comparison as needed.
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