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Microsoft DP-600 Exam - Topic 3 Question 53 Discussion

You have a Fabric workspace that contains a DirectQuery semantic model. The model queries a data source that has 500 million rows.You have a Microsoft Power Bl report named Report1 that uses the model. Report! contains visuals on multiple pages.You need to reduce the query execution time for the visuals on all the pages.What are two features that you can use? Each correct answer presents a complete solution.NOTE: Each correct answer is worth one point.
C) query caching and D) OneLake integration
A) user-defined aggregations
B) automatic aggregation

Microsoft DP-600 Exam - Topic 3 Question 53 Discussion

Actual exam question for Microsoft's DP-600 exam
Question #: 53
Topic #: 3
[All DP-600 Questions]

You have a Fabric workspace that contains a DirectQuery semantic model. The model queries a data source that has 500 million rows.

You have a Microsoft Power Bl report named Report1 that uses the model. Report! contains visuals on multiple pages.

You need to reduce the query execution time for the visuals on all the pages.

What are two features that you can use? Each correct answer presents a complete solution.

NOTE: Each correct answer is worth one point.

Show Suggested Answer Hide Answer
Suggested Answer: C, D

User-defined aggregations (A) and query caching (C) are two features that can help reduce query execution time. User-defined aggregations allow precalculation of large datasets, and query caching stores the results of queries temporarily to speed up future queries. Reference = Microsoft Power BI documentation on performance optimization offers in-depth knowledge on these features.


by Cecilia at Jun 20, 2026, 05:10 AM

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Youlanda
13 hours ago
OneLake integration? I don't think that would help with query execution time. It feels more like a storage solution than a performance feature.
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Mindy
6 days ago
Query caching seems like a good choice too, but I can't recall if it applies to DirectQuery models specifically.
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Marsha
11 days ago
I'm not entirely sure, but I feel like automatic aggregation might be another option. It sounds familiar from our practice questions.
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Rosalyn
16 days ago
I think user-defined aggregations could be one of the answers. I remember something about them helping with performance in large datasets.
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