DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are running an Azure Stream Analytics job that reads from an Event Hub and writes to a Power BI dataset. The job is falling behind and processing latency is increasing. What should you do to improve performance?
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 number of Streaming Units (SUs) allocated to the job.
Increasing the number of Streaming Units (SUs) allocates more compute resources to the Azure Stream Analytics job, directly improving throughput and reducing processing latency. Option B (use reference data) does not address throughput; it is used for enriching streams with static data. Option C (change output to Blob Storage) avoids Power BI throughput limits but does not fix the job's compute performance. Option D (decrease event size) is not typically under the control of the job configuration and may not be feasible.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the number of Streaming Units (SUs) allocated to the job.
Why this is correct
More SUs increase processing capacity.
- ✗
Use a reference data input to filter events.
Why it's wrong here
Reference data doesn't improve throughput.
- ✗
Change the output to Azure Blob Storage instead of Power BI.
Why it's wrong here
This changes the output but may not be acceptable.
- ✗
Decrease the size of events sent to the Event Hub.
Why it's wrong here
Not under your control and may not help.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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