DP-203 Design and implement data storage Practice Question
You are designing a data storage solution for a retail company that needs to store semi-structured JSON data from IoT sensors. The data is ingested continuously and must support both real-time analytics and batch processing. Which Azure data store should you recommend?
⚠ Common exam trap
A common mix-up: candidates choose Azure Cosmos DB (Option D) because it natively supports JSON and real-time access, but they overlook the requirement for batch processing and cost-effective storage at scale, which ADLS Gen2 is designed for as a data lake solution.
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 (ADLS Gen2) is the correct choice because it combines a hierarchical file system with the scalability and low cost of Azure Blob Storage, making it ideal for storing semi-structured JSON data from IoT sensors. It supports both real-time analytics (via services like Azure Stream Analytics or Apache Spark) and batch processing (via tools like Azure Data Factory or PolyBase) without data movement, and it natively handles JSON files with schema-on-read capabilities.
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 Data Lake Storage Gen2
Why this is correct
ADLS Gen2 combines Blob Storage with a hierarchical namespace and is designed for big data analytics.
- ✗
Azure Blob Storage
Why it's wrong here
Blob Storage lacks a hierarchical namespace and integrated analytics optimizations.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is relational and not ideal for storing semi-structured JSON at large scale for analytics.
- ✗
Azure Cosmos DB
Why it's wrong here
Cosmos DB is a NoSQL database optimized for low-latency transactional workloads, not for analytics at scale.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Introduction to Azure Data Engineering
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.
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.