What is the primary benefit of implementing incremental refresh in a semantic model?

It eliminates the need for scheduled refreshes

It reduces the amount of data that needs to be processed during each refresh

It increases the size of the semantic model

It allows the model to be used in Direct Lake mode

Which of the following is a recommended practice to improve query performance in a Fabric semantic model?

Using calculated columns for all derived values

Reducing the cardinality of columns used in relationships

Placing frequently filtered columns in the same table as the measures

Creating a star schema with dimension tables and fact tables

A Power BI report uses a Direct Lake semantic model with a large fact table. The report has a page with multiple visuals, including a matrix, a line chart, and a card. The page takes 10 seconds to load. The administrator wants to improve the visual performance. What should they do?

Change the visual's interaction to 'Cross-filter' instead of 'Cross-highlight' to reduce the amount of data processed.

Enable the 'Optimize for Direct Lake' setting on the report page.

Use the 'Performance Analyzer' in Power BI Desktop to identify which visual is causing the slow load, then optimize that visual's DAX or reduce its data.

Reduce the number of visuals on the page by combining the matrix and line chart into a single visual.

A Fabric semantic model imports a large sales table that grows by about 1 million rows per day. The table has a date column. You need to reduce the time and storage required for refreshes while ensuring that the most recent data is available. What should you configure?

Full refresh of the entire table every night.

Incremental refresh with a policy that refreshes only the last 30 days of data.

Use Direct Lake mode instead of Import mode.

Partition the table manually and refresh each partition separately.

In a Fabric semantic model, which technique is most directly aimed at reducing the amount of data scanned by queries?

Partitioning tables and setting appropriate query filters

Using a star schema design with proper relationships

Implementing row-level security (RLS) filters

Applying aggressive data compression to all columns

Microsoft Certified:Fabric Analytics Engineer Associate

Domain 3Objective 2

Optimize Enterprise-Scale Semantic Models DP-600 Practice Questions (Page 3)

Part of the Implement and manage semantic models domain, which accounts for 25–30% of the DP-600 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~10–20 in this domain), expect 5–10 from this objective — we provide 16 practice questions to prepare you well beyond it. (estimate)

16questions here

4free pages

6concepts

25–30%of the exam

Questions 11–15

11foundation · easy
What is the primary benefit of implementing incremental refresh in a semantic model?
Select an answer first
12foundation · easy
Which of the following is a recommended practice to improve query performance in a Fabric semantic model?
Select an answer first
13application · medium
A Power BI report uses a Direct Lake semantic model with a large fact table. The report has a page with multiple visuals, including a matrix, a line chart, and a card. The page takes 10 seconds to load. The administrator wants to improve the visual performance. What should they do?
Select an answer first
14application · medium
A Fabric semantic model imports a large sales table that grows by about 1 million rows per day. The table has a date column. You need to reduce the time and storage required for refreshes while ensuring that the most recent data is available. What should you configure?
Select an answer first
15foundation · easy
In a Fabric semantic model, which technique is most directly aimed at reducing the amount of data scanned by queries?
Select an answer first

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