DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are monitoring an Azure Synapse Analytics dedicated SQL pool. You notice that queries are occasionally queued due to concurrency limits. You need to reduce the impact of concurrency limits on query performance. What should you do?
⚠ Common exam trap
The trap here is assuming that scaling up DWUs or changing data distribution will solve concurrency issues, when the real solution is workload management to control resource allocation and concurrency.
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
✓
Implement workload management with workload groups and classifier functions to allocate resources and control concurrency.
Workload management in Azure Synapse Analytics dedicated SQL pools enables you to create workload groups, define resource allocation, and set concurrency limits. By using classifier functions to route queries to appropriate groups, you can ensure that critical queries get resources and are not blocked by concurrency limits. This is the most effective way to manage concurrency and resource allocation.
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 a new dedicated SQL pool and move half of the tables to it.
Why it's wrong here
Creating a new pool would distribute the load but does not address concurrency limits within a single pool. It also introduces additional cost and complexity. The requirement is to reduce the impact of concurrency limits on query performance, which can be achieved more efficiently with workload management within the existing pool.
- ✓
Implement workload management with workload groups and classifier functions to allocate resources and control concurrency.
Why this is correct
Workload management allows you to create workload groups, assign resources, and set concurrency limits per group. By classifying queries into different groups, you can isolate workloads and prevent one workload from consuming all concurrency slots. This directly addresses concurrency limits by managing resource allocation and concurrency.
- ✗
Increase the number of data warehouse units (DWUs) for the dedicated SQL pool.
Why it's wrong here
Increasing DWUs scales compute resources and can improve query performance, but it does not directly increase the concurrency limits. Concurrency limits are determined by the service level and resource class. While more DWUs may allow more queries to run concurrently, the primary factor is the resource class and workload management configuration.
- ✗
Change the distribution of the largest tables to round-robin.
Why it's wrong here
Changing distribution can affect query performance but does not influence concurrency limits. Concurrency is about the number of queries that can run simultaneously, not about data distribution. Round-robin distribution may even degrade performance for large fact tables, as it can lead to more data movement during joins.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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