DP-203 Design and implement data storage Practice Question
You need to design a storage solution for streaming data from IoT devices. The solution must support real-time analytics and long-term storage for historical analysis. Which combination of Azure services should you use?
⚠ Common exam trap
Watch out — candidates often confuse Azure IoT Hub with Event Hubs, assuming IoT Hub is the primary streaming ingestion service, but IoT Hub is for device management and control, not high-throughput event streaming, making Event Hubs the correct choice for this scenario.
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 and Azure Data Lake Storage Gen2
Azure Event Hubs is designed for high-throughput, low-latency ingestion of streaming data from IoT devices, supporting real-time analytics via integration with Azure Stream Analytics. Azure Data Lake Storage Gen2 provides hierarchical namespace and POSIX-compliant access for long-term storage, enabling efficient historical analysis with tools like Azure Synapse Analytics or Spark. This combination meets both real-time and historical requirements without the limitations of other options.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Queue Storage and Azure Cosmos DB
Why it's wrong here
Queue Storage is for asynchronous messaging, not real-time streaming.
- ✗
Azure Event Hubs and Azure Blob Storage
Why it's wrong here
Blob Storage lacks the hierarchical namespace and optimizations for analytics that Data Lake Storage provides.
- ✗
Azure IoT Hub and Azure SQL Database
Why it's wrong here
Azure SQL Database is not designed for real-time streaming analytics and can be expensive for large volumes.
- ✓
Azure Event Hubs and Azure Data Lake Storage Gen2
Why this is correct
Event Hubs ingests streaming data, and Data Lake Storage stores it for analytics.
Go deeper
Related to this question
Learn chapter
Introduction to Azure Data Engineering
Key term
Azure Data Lake Gen2
Azure Data Lake Gen2 is a cloud-based data storage service that combines the scalability and performance of a data lake with the hierarchical file system and security of a data warehouse, designed for big data analytics.
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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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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