DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer needs to ingest data from an Amazon S3 bucket into an Amazon Redshift cluster. The data is in CSV format and is updated daily. The engineer wants to use a fully managed service that can handle the load without managing infrastructure. Which AWS service should the engineer use?
⚠ Common exam trap
It's easy for candidates to confuse Redshift Spectrum with an ingestion service; Spectrum queries data in S3 but does not load it into Redshift, so it does not meet the ingestion requirement.
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 ETL service that can read CSV files from Amazon S3, apply transformations if needed, and load the data into Amazon Redshift. It handles the underlying infrastructure, scales automatically, and can be scheduled to run daily. This makes it the ideal choice for the scenario.
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
Why this is correct
AWS Glue is a fully managed extract, transform, and load (ETL) service that can read from S3 and write to Redshift. It handles provisioning and scaling of the underlying infrastructure. The engineer can create a Glue job to load the CSV data into Redshift on a schedule. This meets the requirement for a managed service without infrastructure management.
- ✗
AWS Database Migration Service (AWS DMS)
Why it's wrong here
AWS DMS is used to migrate databases, not to load files from S3 into Redshift. While DMS can replicate from S3 to Redshift, it is not a fully managed ETL service for file-based ingestion. It is better suited for ongoing replication of database changes. For daily CSV loads, a dedicated ETL service is more appropriate.
- ✗
Amazon Redshift Spectrum
Why it's wrong here
Redshift Spectrum allows querying data directly from S3 without loading, but it does not ingest data into Redshift. The requirement is to ingest data into the cluster. Spectrum is for external tables and does not provide ETL capabilities. It would not load the CSV data into Redshift tables.
- ✗
Amazon Kinesis Data Firehose
Why it's wrong here
Kinesis Data Firehose can deliver streaming data to Redshift, but it is designed for streaming data, not daily batch loads from S3. It requires a streaming source and does not directly read from S3. For daily CSV files, Firehose is not the appropriate service. It also does not perform complex transformations.
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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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.