The answer is to implement dedicated SQL pool pause and resume. This is correct because Azure Synapse Analytics separates compute and storage, allowing you to stop compute billing entirely while your data remains intact in Azure Storage. For predictable nightly workloads, pausing the pool during idle daytime hours eliminates all compute costs, then resuming it just before the batch job runs ensures you only pay for active processing time. On the DP-900 exam, this scenario tests your understanding of cost optimization for scheduled, non-continuous workloads—a common trap is confusing scaling (which still incurs compute costs) with pausing (which stops compute billing entirely). Remember the memory tip: “Pause the price, not the data”—pausing stops compute charges but keeps your storage safe and ready.
DP-900 Describe an analytics workload on Azure Practice Question
This DP-900 practice question tests your understanding of describe an analytics workload on azure. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
A company uses Azure Synapse Analytics to run large-scale data transformations. They need to optimize costs for predictable workloads that run every night. Which Azure feature should they configure?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement dedicated SQL pool pause and resume
Azure Synapse Analytics dedicated SQL pool supports pause and resume, which stops compute billing while preserving data in storage. For predictable nightly workloads, pausing the pool during idle hours eliminates compute costs, then resuming it before the job runs. This directly optimizes cost for scheduled, non-continuous workloads.
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.
✓
Implement dedicated SQL pool pause and resume
Why this is correct
Pause/resume stops compute when not in use, ideal for scheduled workloads.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable always-on availability
Why it's wrong here
Always-on availability is for high availability, not cost optimization.
✗
Enable data compression on tables
Why it's wrong here
Data compression reduces storage cost, not compute cost.
✗
Configure auto-scale
Why it's wrong here
Auto-scale adjusts resources dynamically but may not be as cost-effective for predictable loads as pausing.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse auto-scale (which scales compute up/down while running) with pause/resume (which stops compute entirely), failing to recognize that predictable idle periods benefit from complete compute suspension rather than dynamic scaling.
Detailed technical explanation
How to think about this question
Pause and resume in Azure Synapse dedicated SQL pool works by deallocating the compute nodes and moving the metadata to a shared tier, so only storage costs (at ~$0.023/GB/month for blob storage) apply while paused. Resume re-provisions compute nodes from the service's warm pool, typically taking 1–5 minutes. This is ideal for batch ETL jobs that run for a few hours nightly, as it can reduce compute costs by up to 70% compared to running 24/7.
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 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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-900 question in full detail.
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Implement dedicated SQL pool pause and resume — Azure Synapse Analytics dedicated SQL pool supports pause and resume, which stops compute billing while preserving data in storage. For predictable nightly workloads, pausing the pool during idle hours eliminates compute costs, then resuming it before the job runs. This directly optimizes cost for scheduled, non-continuous workloads.
What should I do if I get this DP-900 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.
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Question Discussion
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