DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
A company uses Azure Stream Analytics to process real-time data from IoT devices. They need to ensure that the output to Azure Synapse Analytics is optimized for high throughput and low latency. What should they configure in the Stream Analytics job?
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
✓
Partition the output by a key and use a columnstore index in the target table.
Partitioning the output by a key enables parallel writes to Azure Synapse Analytics, significantly improving throughput, and using a columnstore index optimizes the target table for large data loads, reducing latency. Option A is incorrect because the question specifically requires Azure Synapse Analytics output, not Azure SQL Database. Option C is wrong because a single partition serializes writes, reducing throughput. Option D is incorrect because disabling batching increases the number of write transactions, leading to higher latency and reduced throughput.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure SQL Database output instead of Azure Synapse Analytics.
Why it's wrong here
The question specifies Azure Synapse Analytics; changing the target is not a configuration.
- ✓
Partition the output by a key and use a columnstore index in the target table.
Why this is correct
Partitioning parallelizes writes and columnstore indexes are optimized for analytics.
- ✗
Use a single partition for the output to simplify processing.
Why it's wrong here
Single partition can become a bottleneck; multiple partitions improve throughput.
- ✗
Disable batching to reduce latency.
Why it's wrong here
Disabling batching may increase the number of write operations and reduce throughput.
Go deeper
Related to this question
Learn chapter
Introduction to Azure Data Engineering
Key term
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based data integration, warehousing, and analytics service that brings together big data and data warehouse capabilities under one platform.
Key term
Azure Stream Analytics
Azure Stream Analytics is a fully managed, real-time data processing service that analyzes and transforms high volumes of streaming data from various sources to deliver low-latency insights and trigger actions.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.