MLS-C01 Data Engineering Practice Question
A company needs to build a data lake on AWS for analytics. The data includes structured, semi-structured, and unstructured data. The solution must support schema-on-read, provide fine-grained access control, and be cost-effective for storing rarely accessed data. Which THREE services should be used? (Choose THREE)
⚠ Common exam trap
A common mix-up: candidates confuse Amazon Redshift as a data lake storage layer due to its analytics capabilities, but it is a data warehouse with schema-on-write and higher costs for infrequently accessed data, making it unsuitable for the described requirements.
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
✓
AWS Glue Data Catalog for schema-on-read.
AWS Glue Data Catalog is correct because it provides a centralized metadata repository that enables schema-on-read for data stored in Amazon S3. It allows you to define table schemas and partitions without transforming the underlying data, so analytics tools like Amazon Athena and Amazon EMR can query the data with the schema applied at read time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
AWS Glue Data Catalog for schema-on-read.
Why this is correct
Glue enables schema-on-read for analytics.
- ✗
Amazon Redshift for data warehousing.
Why it's wrong here
Redshift is a warehouse, not a data lake.
- ✓
Amazon S3 as the primary storage layer.
Why this is correct
S3 is the foundation of a data lake.
- ✗
Amazon EMR for data processing.
Why it's wrong here
EMR is for processing, not storage.
- ✓
S3 Lifecycle policies to transition data to Glacier.
Why this is correct
Lifecycle policies reduce cost for old data.
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 |
Go deeper
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Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLS-C01 exam.