Secure, monitor, and optimize data storage and data processing →mediumMultiple ChoiceObjective-mapped
DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are designing a data processing solution in Azure Synapse Analytics. The solution must process streaming data from IoT devices and store it in a dedicated SQL pool for reporting. The data volume is high (millions of events per hour), and you need to optimize for both ingestion speed and query performance. You also need to ensure that the data can be partitioned by date for efficient maintenance. Which architecture should you recommend?
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
✓
Use Event Hubs Capture to store data in Avro files in Blob Storage and then query with external tables.
The correct architecture. Event Hubs Capture automatically captures streaming data into Avro files in Blob Storage, which can be organized by date in folder structures. External tables in Azure Synapse can query these files with partition elimination, providing good query performance. This approach handles high-volume ingestion efficiently without impacting the streaming pipeline. Option A is incorrect because PolyBase in Azure Synapse does not natively support the Delta format (it supports Parquet, ORC, etc.), so loading Delta format using PolyBase is not feasible. Option B is incorrect because direct writes from Stream Analytics to a dedicated SQL pool are not efficient for millions of events per hour due to batch constraints and potential bottlenecks. Option C is incorrect because Azure SQL Database with elastic scaling is intended for online transaction processing (OLTP) workloads, not large-scale analytical processing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ingest data to Azure Data Lake Storage Gen2 in Delta format, then use PolyBase to load into a dedicated SQL pool partitioned by date.
Why it's wrong here
Incorrect because PolyBase in Azure Synapse does not support the Delta format; it supports Parquet, ORC, etc. Therefore, loading Delta files via PolyBase is not feasible.
- ✗
Use Azure Stream Analytics to write directly to a dedicated SQL pool with a time-based window.
Why it's wrong here
Incorrect because writing directly from Azure Stream Analytics to a dedicated SQL pool is not efficient for high-volume streaming data; it can cause performance bottlenecks.
- ✗
Store data in Azure SQL Database with elastic scaling and use linked server queries.
Why it's wrong here
Incorrect because Azure SQL Database with elastic scaling is not designed for large-scale analytics workloads.
- ✓
Use Event Hubs Capture to store data in Avro files in Blob Storage and then query with external tables.
Why this is correct
Correct. Event Hubs Capture efficiently stores streaming data in Avro format organized by date. External tables in Synapse allow querying with partition elimination, optimizing both ingestion and query performance.
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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.