DP-203 Design and implement data storage Practice Question
You are designing a data storage solution for real-time streaming data from IoT devices. The data must be stored in its original format for immediate processing and later transformed for analytics. Which Azure service should you use for raw data ingestion?
⚠ Common exam trap
Test-takers frequently confuse data ingestion (Event Hubs) with data storage (Data Lake Storage) or data processing (Stream Analytics), assuming a single service must handle both raw capture and transformation, when in fact the question explicitly asks for raw data ingestion only.
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
✓
Azure Event Hubs
Azure Event Hubs is a fully managed, real-time data ingestion service optimized for high-throughput streaming data from IoT devices. It can receive millions of events per second, store them in a partitioned, ordered log for immediate processing, and retain them for up to 7 days (or longer with Event Hubs Capture) for later transformation and analytics. This makes it the correct choice for raw data ingestion before any transformation occurs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Azure Data Lake Storage Gen2
Why it's wrong here
Azure Data Lake Storage Gen2 is designed for storing transformed, structured, or semi-structured data in a hierarchical namespace, not for ingesting raw, unmodified streaming payloads in real time. The scenario requires immediate capture of the original IoT data format without schema enforcement or transformation, which is a capability of Azure Event Hubs or Azure IoT Hub. It is tempting because Data Lake Storage Gen2 excels at large-scale analytics storage and would be the correct choice for the *transformed* data after processing, but it cannot serve as the initial ingestion point for raw streaming events.
- ✓
Azure Event Hubs
Why this is correct
Azure Event Hubs is a fully managed, real-time data ingestion service optimized for high-throughput streaming data from IoT devices. It can receive millions of events per second, store them in a partitioned, ordered log for immediate processing, and retain them for later transformation. This makes it the correct choice for raw data ingestion.
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Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics is a real-time analytics service that processes and transforms data in motion. It is used for processing data after ingestion, not for the initial raw data capture. Therefore, it is not the service for raw data ingestion.
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Azure Data Factory
Why it's wrong here
Data Factory runs scheduled or triggered batch pipelines with mapping data flows; it cannot ingest continuous IoT streams at low latency. It is tempting because it orchestrates movement and transformation across sources, which suits periodic ETL loads into a warehouse rather than real-time raw capture.
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Senior Network & Security Engineer · founder of Courseiva
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