Which Lakehouse table feature improves query performance by allowing the query engine to skip reading entire groups of data that do not match the query's filter conditions?

Data skipping via Z-order indexing

Which pipeline optimization technique reduces the amount of data transferred by filtering data at the source before it is loaded into the destination?

Partitioning the destination table

Pushdown of filters and projections

Increasing the number of retries

A Spark job processes a large dataset and writes results to a Lakehouse table. The job is slow due to excessive shuffling. The engineer identifies that the data is skewed on a join key. What should you do to reduce the impact of skew?

Increase the number of partitions in the shuffle.

Use a sort-merge join instead of a hash join.

Use a broadcast join hint for the skewed table.

Apply salting to the join key to distribute data more evenly.

Microsoft Certified:Fabric Data Engineer Associate

Domain 3Objective 3

Optimize Performance DP-700 Practice Questions (Page 6)

Part of the Monitor and optimize an analytics solution domain, which accounts for 30–35% of the DP-700 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~12–23 in this domain), expect 4–8 from this objective — we provide 30 practice questions to prepare you well beyond it. (estimate)

30questions here

6free pages

7concepts

30–35%of the exam

Questions 26–30

26foundation · easy
Which Lakehouse table feature improves query performance by allowing the query engine to skip reading entire groups of data that do not match the query's filter conditions?
Select an answer first
27foundation · easy
Which data warehouse optimization technique involves pre-computing and storing aggregated results to speed up queries that repeatedly summarize large fact tables?
Select an answer first
28foundation · easy
Which pipeline optimization technique reduces the amount of data transferred by filtering data at the source before it is loaded into the destination?
Select an answer first
29application · medium
A Spark job processes a large dataset and writes results to a Lakehouse table. The job is slow due to excessive shuffling. The engineer identifies that the data is skewed on a join key. What should you do to reduce the impact of skew?
Select an answer first
30foundation · easy
Which data warehouse design practice can improve query performance by physically dividing a large table into smaller, more manageable segments based on a column value?
Select an answer first

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Optimize Performance DP-700 Practice Questions (Page 6)

Questions 26–30

Which Lakehouse table feature improves query performance by allowing the query engine to skip reading entire groups of data that do not match the query's filter conditions?

Which data warehouse optimization technique involves pre-computing and storing aggregated results to speed up queries that repeatedly summarize large fact tables?

Which pipeline optimization technique reduces the amount of data transferred by filtering data at the source before it is loaded into the destination?

A Spark job processes a large dataset and writes results to a Lakehouse table. The job is slow due to excessive shuffling. The engineer identifies that the data is skewed on a join key. What should you do to reduce the impact of skew?

Which data warehouse design practice can improve query performance by physically dividing a large table into smaller, more manageable segments based on a column value?

Keep studying — Monitor and optimize an analytics solution