DEA-C01 Data Ingestion and Transformation Practice Question
A company has a nightly batch job that processes 100 GB of data from an Amazon S3 bucket and loads it into an Amazon Redshift table. The job currently runs on an Amazon EMR cluster. Which service would reduce operational overhead while providing similar functionality?
⚠ Common exam trap
The DEA-C01 exam often tests the distinction between query engines (Athena, Redshift Spectrum) and ETL services (Glue), where candidates mistakenly choose Athena or Spectrum because they can read from S3, but they lack the batch processing and data loading capabilities required for this use case.
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 serverless ETL service that can process 100 GB of data from S3 and load it into Redshift without managing any infrastructure. It provides built-in job scheduling, automatic retries, and a Spark-based engine that handles large-scale data transformations, directly replacing the EMR cluster's functionality while eliminating operational overhead.
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 Database Migration Service
Why it's wrong here
DMS is for database migration, not for file-based ETL from S3.
- ✓
AWS Glue
Why this is correct
Glue can run serverless ETL jobs on a schedule, reducing overhead.
- ✗
Amazon Redshift Spectrum
Why it's wrong here
Spectrum queries S3 directly but does not load data into Redshift tables.
- ✗
Amazon Athena
Why it's wrong here
Amazon Athena is unsuitable because its primary function is interactive querying of data directly in S3, not loading data into Amazon Redshift tables. The scenario explicitly requires a nightly batch job to *load* 100 GB into Redshift. Athena would be a strong choice for ad-hoc analysis or serverless querying of data residing in S3, offering significant operational overhead reduction compared to EMR for those specific use cases.
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
Related to this question
About these practice questions
This DEA-C01 question is part of Courseiva's 1,711-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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.