DEA-C01 Data Ingestion and Transformation Practice Question
A company uses Amazon S3 to store raw data and needs to transform it into Parquet format for analytics. The transformation job runs daily on a schedule. Which AWS service is BEST suited for this task?
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
AWS Glue is a fully managed, serverless ETL service that can automatically convert data formats (e.g., from CSV to Parquet) and run on a schedule (e.g., daily). It is ideal for this use case because it is purpose-built for ETL transformations and handles schema discovery, data cataloging, and job scheduling without managing infrastructure. Option A (Amazon Redshift) is wrong because Redshift is a data warehouse for querying, not a transformation service; it could load Parquet but not convert raw data to Parquet directly. Option B (Amazon EMR) is wrong because EMR requires provisioning and managing clusters, adding operational overhead. Option C (AWS Lambda) is wrong because Lambda has a maximum execution timeout of 15 minutes, which is too short for daily large-scale data transformation jobs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is for querying and storing data, not for converting file formats.
- ✗
Amazon EMR
Why it's wrong here
Amazon EMR is unsuitable because the requirement is a scheduled daily transformation of S3 data into Parquet, which is a batch ETL workload that AWS Glue handles natively with its serverless, schedule-triggered crawlers and jobs; EMR requires provisioning and managing a Hadoop cluster even for transient use, adding operational overhead. It is tempting because EMR excels at large-scale distributed data processing using frameworks like Spark or Hive, and would be correct if the transformation involved complex, custom analytics requiring fine-grained control over cluster configuration and resource tuning.
- ✗
AWS Lambda
Why it's wrong here
Lambda has a maximum execution timeout of 15 minutes, not suitable for large data transformations.
- ✓
AWS Glue
Why this is correct
Glue is serverless, supports Parquet, and can be scheduled with triggers.
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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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-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 DEA-C01 exam.