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DP-203 Columnstore indexes Practice Question
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.
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.
- ✗
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.
- ✓
Enable result-set caching.
Why this is correct
Result-set caching returns cached results for repeated queries, improving performance.
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Same concept, more angles
1 more way this is tested on DP-203
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which TWO actions can you take to optimize the performance of an Azure Synapse Analytics dedicated SQL pool? (Choose two.)
medium- A.Scale up the SQL pool to a higher DWU.
- ✓ B.Replicate small dimension tables.
- C.Use heap indexes for fact tables.
- D.Use round-robin distribution for all large fact tables.
- ✓ E.Use hash distribution on a column used in joins and aggregations.
Why B: Replicating small dimension tables across all distributions reduces data movement during joins and improves query performance. Option E is correct because hash distribution on a column used in joins and aggregations ensures that rows with the same key are colocated on the same distribution, minimizing data shuffling. Option A is incorrect: scaling up increases resources but is not a targeted performance optimization and may not address underlying distribution or indexing issues. Option C is incorrect: heap indexes are generally not optimal for fact tables because they lack compression and indexing benefits; clustered columnstore indexes are recommended. Option D is incorrect: round-robin distribution distributes data evenly but does not reduce data movement for joins and aggregations, often leading to poor query performance.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.