DP-203 Design and implement data storage Practice Question
This DP-203 practice question tests your understanding of design and implement data storage. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that 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.
Detailed technical explanation
How to think about this question
Event Hubs uses AMQP 1.0 and HTTPS for ingestion, supporting up to 1 MB per event and auto-inflate throughput units, while Data Lake Storage Gen2 builds on Azure Blob Storage with a hierarchical namespace that enables directory-level operations and atomic metadata updates. In a real-world scenario, IoT devices emitting sensor data at 10,000 events per second can be ingested via Event Hubs, processed in real-time with Stream Analytics, and partitioned into Data Lake Storage Gen2 for year-over-year trend analysis using PolyBase or Spark.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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