- A
Create nonclustered indexes on all columns of the target table
Why wrong: Indexes slow down data loading.
- B
Use ROUND_ROBIN distribution for the staging table
Round-robin distributes data evenly, speeding up loads.
- C
Set the row group size to 100,000 rows for optimal compression
Why wrong: Optimal row group size is 1M rows; smaller sizes degrade compression.
- D
Enable change tracking on the target table
Why wrong: Change tracking adds overhead during loads.
- E
Use CREATE TABLE AS SELECT (CTAS) with partition switching
CTAS minimizes logging and partition switching avoids data movement.
Question 96 of 851
Optimize Data Loading in Dedicated SQL Pool
This DP-203 practice question tests your understanding of develop 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.
Which TWO actions can you take to optimize the performance of a dedicated SQL pool in Azure Synapse Analytics when loading large volumes of data?
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 ROUND_ROBIN distribution for the staging table
Option B is correct because using ROUND_ROBIN distribution for a staging table ensures that data is evenly distributed across all distributions without any data movement, which is the fastest way to load data into a dedicated SQL pool. This distribution type is ideal for staging tables because it minimizes load time and avoids the overhead of hash distribution key computation during the initial data ingestion phase.
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.
- ✗
Create nonclustered indexes on all columns of the target table
Why it's wrong here
Indexes slow down data loading.
- ✓
Use ROUND_ROBIN distribution for the staging table
Why this is correct
Round-robin distributes data evenly, speeding up loads.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Set the row group size to 100,000 rows for optimal compression
Why it's wrong here
Optimal row group size is 1M rows; smaller sizes degrade compression.
- ✗
Enable change tracking on the target table
Why it's wrong here
Change tracking adds overhead during loads.
- ✓
Use CREATE TABLE AS SELECT (CTAS) with partition switching
Why this is correct
CTAS minimizes logging and partition switching avoids data movement.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the purpose of indexes and distribution types, mistakenly thinking that adding indexes on all columns will speed up loading, when in fact it degrades performance, and they overlook that ROUND_ROBIN is specifically designed for fast staging loads, not for query performance.
Detailed technical explanation
How to think about this question
Under the hood, ROUND_ROBIN distribution distributes rows across all distributions in a round-robin fashion without any hash computation, making it the most efficient distribution for staging tables where the primary goal is fast ingestion. When combined with CTAS and partition switching (Option E), you can load data into a staging table, then switch the partition into the target table as a metadata-only operation, avoiding costly data movement and index maintenance. This pattern is commonly used in real-world scenarios for large-scale ETL pipelines to achieve near-instantaneous data availability.
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.
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
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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Develop data processing — study guide chapter
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FAQ
Questions learners often ask
What does this DP-203 question test?
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use ROUND_ROBIN distribution for the staging table — Option B is correct because using ROUND_ROBIN distribution for a staging table ensures that data is evenly distributed across all distributions without any data movement, which is the fastest way to load data into a dedicated SQL pool. This distribution type is ideal for staging tables because it minimizes load time and avoids the overhead of hash distribution key computation during the initial data ingestion phase.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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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. Which TWO actions should you take to optimize performance of a dedicated SQL pool in Azure Synapse Analytics when loading large volumes of data?
medium- A.Disable index on the target table after loading.
- ✓ B.Use a large batch size (e.g., 100 MB) for each copy operation.
- ✓ C.Use round-robin distribution for the staging table.
- D.Use a small batch size (e.g., 1 MB) for each copy operation.
- E.Use clustered columnstore index on the target table during load.
Why B: Option B is correct because using a large batch size (e.g., 100 MB) for each copy operation minimizes the number of round trips and transaction commits, which significantly improves throughput when loading large volumes of data into a dedicated SQL pool. The PolyBase or COPY statement in Azure Synapse performs best when batches are large enough to leverage parallel processing and reduce overhead from frequent small writes.
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Last reviewed: Jul 4, 2026
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