- A
Azure Cosmos DB
Why wrong: Cosmos DB is designed for transactional workloads with low latency; it is expensive for large volumes of historical data.
- B
Azure Table Storage
Why wrong: Table Storage is cheaper but lacks powerful querying and analytics capabilities needed for historical analysis.
- C
Azure SQL Database
Why wrong: Azure SQL Database is costly for massive IoT data and not optimized for append-only workloads.
- D
Azure Data Lake Storage Gen2
ADLS Gen2 provides cost-effective storage for large datasets and integrates with analytics services like Synapse and Databricks.
Quick Answer
Azure Data Lake Storage Gen2 is the correct choice because it provides a cost-effective, scalable solution for storing high-volume, append-only IoT sensor data that must be retained for long-term analytics. Its hierarchical namespace organizes data into directories, enabling efficient querying and fine-grained access control, while the underlying Azure Blob Storage ensures low-cost storage for rarely updated historical logs. On the DP-900 exam, this scenario tests your understanding of when to choose Data Lake Storage over options like Azure Blob Storage or Azure SQL Database—a common trap is selecting Blob Storage alone, which lacks the hierarchical structure needed for performant analytics with tools like Azure Synapse. Remember that Data Lake Storage Gen2 is essentially Blob Storage with a file-system layer, making it ideal for append-heavy workloads like IoT telemetry. A helpful memory tip: think of a lake—data flows in (append-only) and sits there for years, ready for deep analysis without expensive updates.
DP-900 Describe core data concepts Practice Question
This DP-900 practice question tests your understanding of describe core data concepts. 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.
Your company is designing a data solution for IoT sensor data that arrives in high volume and must be stored for long-term analytics. The data is append-only and rarely updated. You need to choose a storage solution that balances cost and query performance for historical analysis. Which Azure data store 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
Azure Data Lake Storage Gen2
Azure Data Lake Storage Gen2 is the correct choice because it combines a hierarchical namespace with Azure Blob Storage, offering scalable, cost-effective storage for high-volume append-only data like IoT sensor logs. It supports both structured and unstructured data, integrates with analytics engines like Azure Synapse and Spark, and provides POSIX-compliant access control, making it ideal for long-term historical analysis at low cost.
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
Why it's wrong here
Cosmos DB is designed for transactional workloads with low latency; it is expensive for large volumes of historical data.
- ✗
Azure Table Storage
Why it's wrong here
Table Storage is cheaper but lacks powerful querying and analytics capabilities needed for historical analysis.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is costly for massive IoT data and not optimized for append-only workloads.
- ✓
Azure Data Lake Storage Gen2
Why this is correct
ADLS Gen2 provides cost-effective storage for large datasets and integrates with analytics services like Synapse and Databricks.
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 Cosmos DB's low-latency capabilities with suitability for high-volume historical analytics, overlooking its cost model and lack of native file-system semantics for append-only workloads.
Detailed technical explanation
How to think about this question
Azure Data Lake Storage Gen2 uses a hierarchical namespace to organize blobs into directories, enabling efficient rename and delete operations without full object scans, which is critical for managing large IoT datasets. It supports the ABFS (Azure Blob File System) driver for Hadoop-compatible access, allowing tools like Apache Spark to perform parallel reads with O(1) metadata operations, and its tiered storage (hot, cool, archive) lets you automatically move older data to cheaper tiers, reducing costs for long-term analytics.
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.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Describe core data concepts — study guide chapter
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe core data concepts — This question tests Describe core data concepts — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Data Lake Storage Gen2 — Azure Data Lake Storage Gen2 is the correct choice because it combines a hierarchical namespace with Azure Blob Storage, offering scalable, cost-effective storage for high-volume append-only data like IoT sensor logs. It supports both structured and unstructured data, integrates with analytics engines like Azure Synapse and Spark, and provides POSIX-compliant access control, making it ideal for long-term historical analysis at low cost.
What should I do if I get this DP-900 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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Last reviewed: Jun 24, 2026
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