DA0-002 Data Concepts and Environments Practice Question
A data engineer is designing a system to store raw sensor data from thousands of IoT devices. The data will be used later for various analytics projects, but the schema is not yet defined. Which storage solution is most appropriate?
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
✓
Data lake
A data lake stores raw data in its native format (e.g., S3, ADLS) without requiring a predefined schema, making it suitable for IoT data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Data lake
Why this is correct
Data lakes store raw data in any format and allow schema-on-read.
- ✗
Data mart
Why it's wrong here
Data marts are subject-specific subsets of a data warehouse, not for raw ingestion.
- ✗
Data warehouse
Why it's wrong here
Data warehouses store structured, processed data optimized for analytics, not raw data.
- ✗
Relational database
Why it's wrong here
Relational databases require a fixed schema; IoT data may be unstructured or semi-structured and schema is unknown.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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