- A
Create materialized views on frequently queried tables.
Why wrong: Materialized views precompute aggregations for repeated queries, but a nightly batch job typically runs unique queries, offering little benefit. They also require storage and maintenance.
- B
Increase the service level objective (DWU) of the dedicated SQL pool.
Correct. Increasing DWU directly accelerates compute-heavy operations. Because runtime decreases, total cost stays the same or even drops, meeting the 'no cost increase' requirement.
- C
Implement workload management to prioritize the job.
Why wrong: Workload management prioritizes the job for resources, but it does not increase the total compute capacity. It may help with concurrency but won't significantly reduce runtime for a single large job.
- D
Enable result-set caching on the dedicated SQL pool.
Why wrong: Result-set caching stores results of repeated queries. A nightly batch job often involves different queries each run, so caching provides negligible speedup. It is designed for interactive, repeated queries.
DP-203 Dedicated SQL pool scaling (DWU) Practice Question
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. A key principle to apply: dedicated SQL pool scaling (DWU). 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.
Your company uses Azure Synapse Analytics to run a large-scale batch processing job every night. The job currently runs on a dedicated SQL pool and takes 4 hours. Management wants to reduce the runtime to under 2 hours without increasing cost. The job involves heavy compute operations with no data movement limitations. What should you do?
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
Increase the service level objective (DWU) of the dedicated SQL pool.
Increasing the service level objective (DWU) of the dedicated SQL pool provides more compute resources, directly reducing the runtime of compute-heavy batch jobs. Since the pool runs for fewer hours, the total cost (DWU × hours) may remain the same or even decrease, meeting the requirement to reduce runtime without increasing cost. Materialized views (A) and result-set caching (D) benefit repeated queries, not a unique nightly job. Workload management (C) only prioritizes resources, without increasing overall compute power.
Key principle: Dedicated SQL pool scaling (DWU)
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 materialized views on frequently queried tables.
Why it's wrong here
Materialized views precompute aggregations for repeated queries, but a nightly batch job typically runs unique queries, offering little benefit. They also require storage and maintenance.
- ✓
Increase the service level objective (DWU) of the dedicated SQL pool.
Why this is correct
Correct. Increasing DWU directly accelerates compute-heavy operations. Because runtime decreases, total cost stays the same or even drops, meeting the 'no cost increase' requirement.
Related concept
Dedicated SQL pool scaling (DWU)
- ✗
Implement workload management to prioritize the job.
Why it's wrong here
Workload management prioritizes the job for resources, but it does not increase the total compute capacity. It may help with concurrency but won't significantly reduce runtime for a single large job.
- ✗
Enable result-set caching on the dedicated SQL pool.
Why it's wrong here
Result-set caching stores results of repeated queries. A nightly batch job often involves different queries each run, so caching provides negligible speedup. It is designed for interactive, repeated queries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates often assume that increasing DWU always increases cost, but total cost can remain constant when runtime decreases proportionally. They may also mistakenly believe materialized views or result-set caching can significantly speed up a large, non-repetitive batch job.
Detailed technical explanation
How to think about this question
Result-set caching works by storing the output of a query (up to 1 TB per cache) in a dedicated SSD cache on the compute nodes; subsequent identical queries bypass the compute engine and read directly from cache, reducing latency to milliseconds. However, the cache is invalidated automatically when data in the underlying tables changes, so for nightly batch jobs that run on static or snapshotted data, the cache remains valid across runs, maximizing the benefit. In real-world scenarios, this is particularly effective for dashboards or recurring ETL validation queries where the same aggregations are computed repeatedly.
KKey Concepts to Remember
- Dedicated SQL pool scaling (DWU)
- Cost equilibrium with scaling
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
Dedicated SQL pool scaling (DWU)
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Review dedicated SQL pool scaling (DWU), 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?
Develop data processing — This question tests Develop data processing — Dedicated SQL pool scaling (DWU).
What is the correct answer to this question?
The correct answer is: Increase the service level objective (DWU) of the dedicated SQL pool. — Increasing the service level objective (DWU) of the dedicated SQL pool provides more compute resources, directly reducing the runtime of compute-heavy batch jobs. Since the pool runs for fewer hours, the total cost (DWU × hours) may remain the same or even decrease, meeting the requirement to reduce runtime without increasing cost. Materialized views (A) and result-set caching (D) benefit repeated queries, not a unique nightly job. Workload management (C) only prioritizes resources, without increasing overall compute power.
What should I do if I get this DP-203 question wrong?
Review dedicated SQL pool scaling (DWU), then practise related DP-203 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Dedicated SQL pool scaling (DWU)
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Last reviewed: Jul 4, 2026
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