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 are designing a data storage solution for a retail company that expects high volumes of small, time-series sensor data from thousands of IoT devices. The data must be stored cost-effectively and queried by time range with low latency. Which Azure data store should you recommend?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Data Explorer (ADX)
Azure Data Explorer (ADX) is optimized for high-volume, time-series data ingestion and low-latency queries over time ranges. It uses a columnar storage engine and automatic indexing, making it cost-effective for sensor data from thousands of IoT devices.
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 Cosmos DB with analytical store
Why it's wrong here
Cosmos DB is optimized for low-latency transactions, not high-throughput time-series analytics.
✗
Azure SQL Database with columnstore indexes
Why it's wrong here
SQL Database is not cost-effective for massive IoT data and lacks native time-series partitioning.
✗
Azure Blob Storage with Azure Data Lake Storage Gen2
Why it's wrong here
Blob Storage lacks native time-series querying and would require external compute, increasing latency and cost.
✓
Azure Data Explorer (ADX)
Why this is correct
ADX is designed for high-speed ingestion and real-time analytics on time-series data with built-in optimization.
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 choose Azure Blob Storage with Data Lake Storage Gen2 because it is cheap for storage, but they overlook that it lacks native query capabilities for low-latency time-series queries, requiring additional compute layers.
Detailed technical explanation
How to think about this question
Azure Data Explorer uses a Kusto Query Language (KQL) that natively supports time-series functions like bin(), series_decompose(), and make-series for aggregating and analyzing sensor data over time. Its ingestion pipeline can handle millions of events per second via Event Hubs or IoT Hub, and data is automatically partitioned by ingestion time, enabling sub-second query responses for time-range filters without manual tuning.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 Data Explorer (ADX) — Azure Data Explorer (ADX) is optimized for high-volume, time-series data ingestion and low-latency queries over time ranges. It uses a columnar storage engine and automatic indexing, making it cost-effective for sensor data from thousands of IoT devices.
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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