- A
Use rowstore indexes instead of columnstore indexes.
Why wrong: Columnstore indexes are optimized for analytics; rowstore indexes are for OLTP.
- B
Partition large fact tables on a date column.
Partitioning enables partition elimination, reducing data scanned.
- C
Use round-robin distribution for all tables.
Why wrong: Round-robin may cause data shuffles; hash distribution is often better for large tables.
- D
Use replicated tables for small dimension tables.
Replicated tables avoid data movement during joins.
- E
Enable result-set caching.
Result-set caching returns cached results for repeated queries, improving performance.
Question 596 of 851
Secure, monitor, and optimize data storage and data processing →mediumMultiple SelectObjective-mapped
DP-203 Columnstore indexes Practice Question
This DP-203 practice question tests your understanding of secure, monitor, and optimize data storage and data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. A key principle to apply: columnstore indexes. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE actions can improve the performance of a dedicated SQL pool in Azure Synapse Analytics?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Partition large fact tables on a date column.
Options B, D, and E are correct. Partitioning large fact tables on a date column allows partition elimination, improving query performance. Using replicated tables for small dimension tables avoids data movement during joins. Enabling result-set caching stores query results for reuse, reducing compute load. Option A is incorrect because rowstore indexes are not optimal for analytics; columnstore indexes are preferred. Option C is incorrect because round-robin distribution is not suitable for all tables and can cause excessive data shuffling.
Key principle: Columnstore indexes
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use rowstore indexes instead of columnstore indexes.
Why it's wrong here
Columnstore indexes are optimized for analytics; rowstore indexes are for OLTP.
- ✓
Partition large fact tables on a date column.
Why this is correct
Partitioning enables partition elimination, reducing data scanned.
Related concept
Columnstore indexes
- ✗
Use round-robin distribution for all tables.
Why it's wrong here
Round-robin may cause data shuffles; hash distribution is often better for large tables.
- ✓
Use replicated tables for small dimension tables.
Why this is correct
Replicated tables avoid data movement during joins.
Related concept
Columnstore indexes
- ✓
Enable result-set caching.
Why this is correct
Result-set caching returns cached results for repeated queries, improving performance.
Related concept
Columnstore indexes
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Columnstore indexes
- Table distribution
- Partitioning
- Result-set caching
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Columnstore indexes
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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Review columnstore indexes, then practise related DP-203 questions on the same topic to reinforce the concept.
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FAQ
Questions learners often ask
What does this DP-203 question test?
Secure, monitor, and optimize data storage and data processing — This question tests Secure, monitor, and optimize data storage and data processing — Columnstore indexes.
What is the correct answer to this question?
The correct answer is: Partition large fact tables on a date column. — Options B, D, and E are correct. Partitioning large fact tables on a date column allows partition elimination, improving query performance. Using replicated tables for small dimension tables avoids data movement during joins. Enabling result-set caching stores query results for reuse, reducing compute load. Option A is incorrect because rowstore indexes are not optimal for analytics; columnstore indexes are preferred. Option C is incorrect because round-robin distribution is not suitable for all tables and can cause excessive data shuffling.
What should I do if I get this DP-203 question wrong?
Review columnstore indexes, then practise related DP-203 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Columnstore indexes
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Last reviewed: Jun 21, 2026
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