- A
Use round-robin distribution on fact tables.
Why wrong: Round-robin causes data shuffling.
- B
Use hash distribution on dimension tables.
Why wrong: Hash on dimension tables causes unnecessary data movement.
- C
Use heap table structure for fact tables.
Why wrong: Columnstore index is better for analytics.
- D
Use replicated distribution on dimension tables.
Replicated tables avoid data movement.
- E
Use hash distribution on fact tables using the join key.
Hash distribution aligns data for joins.
Question 746 of 851
Optimize Star Join Queries in Azure Synapse Dedicated SQL Pool
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. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. 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.
You are optimizing an Azure Synapse Analytics dedicated SQL pool. The workload includes large fact tables and dimension tables. You need to improve query performance for star join queries. Which TWO actions should you take?
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
✓
Use replicated distribution on dimension tables.
The correct actions are D and E. For star join queries in Azure Synapse Analytics dedicated SQL pool, best practices are to use hash distribution on fact tables using the join key (option E) to distribute data across distributions efficiently, and use replicated distribution on dimension tables (option D) to avoid data movement. Option A is wrong because round-robin distribution is suitable for staging or temporary tables, not for large fact tables in star schemas. Option B is wrong because dimension tables should be replicated, not hash-distributed, to minimize shuffling. Option C is wrong because heap tables are not optimized for analytical queries; clustered columnstore index is the recommended table structure for fact tables.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 round-robin distribution on fact tables.
Why it's wrong here
Round-robin causes data shuffling.
- ✗
Use hash distribution on dimension tables.
Why it's wrong here
Hash on dimension tables causes unnecessary data movement.
- ✗
Use heap table structure for fact tables.
Why it's wrong here
Columnstore index is better for analytics.
- ✓
Use replicated distribution on dimension tables.
Why this is correct
Replicated tables avoid data movement.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Use hash distribution on fact tables using the join key.
Why this is correct
Hash distribution aligns data for joins.
Related concept
Read the scenario before looking for a memorised answer.
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
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Secure, monitor, and optimize data storage and data processing — study guide chapter
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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 — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use replicated distribution on dimension tables. — The correct actions are D and E. For star join queries in Azure Synapse Analytics dedicated SQL pool, best practices are to use hash distribution on fact tables using the join key (option E) to distribute data across distributions efficiently, and use replicated distribution on dimension tables (option D) to avoid data movement. Option A is wrong because round-robin distribution is suitable for staging or temporary tables, not for large fact tables in star schemas. Option B is wrong because dimension tables should be replicated, not hash-distributed, to minimize shuffling. Option C is wrong because heap tables are not optimized for analytical queries; clustered columnstore index is the recommended table structure for fact tables.
What should I do if I get this DP-203 question wrong?
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more ways 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. You are optimizing the performance of an Azure Synapse Analytics dedicated SQL pool. Which TWO actions can help reduce data movement during query execution?
hard- A.Use hash distribution on a column that is not used in joins.
- ✓ B.Use replicated tables for small dimension tables.
- C.Use round-robin distribution for large fact tables.
- D.Increase the resource class for the loading user.
- ✓ E.Distribute fact tables on the join key columns.
Why B: Options B and E are correct. Using replicated tables for small dimension tables avoids data movement during joins because the table is copied to all distributions. Distributing fact tables on the join key columns ensures that matching rows are co-located, reducing shuffling. Option A is incorrect: using hash distribution on a column not used in joins increases data movement because data is redistributed unnecessarily. Option C is incorrect: round-robin distribution distributes rows evenly but often requires data movement for joins. Option D is incorrect: increasing the resource class allocates more resources but does not directly reduce data movement.
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Last reviewed: Jun 21, 2026
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