DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is designing a data ingestion pipeline to load data from an on-premises Oracle database to Amazon S3. The pipeline should capture changes in near real-time (within minutes) and minimize impact on the source database. The source table has a 'last_modified' timestamp column. Which service combination would meet these requirements?
⚠ Common exam trap
Many candidates assume a 'last_modified' timestamp column enables easy CDC via polling (options B, D), but the question tests that true near real-time CDC with minimal source impact requires reading database redo logs, not querying the table, and that services like Kinesis or Glue cannot perform log-based CDC without additional custom logic.
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 DMS with a replication task in CDC mode, writing to S3 in Parquet format.
AWS DMS with a replication task in CDC (Change Data Capture) mode is the correct choice because it continuously reads the Oracle redo logs to capture near real-time changes (within seconds to minutes) with minimal impact on the source database. It can directly write to S3 in Parquet format, meeting the requirement for low-latency ingestion without full table scans.
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 DMS with a replication task in CDC mode, writing to S3 in Parquet format.
Why this is correct
DMS change data capture reads the Oracle redo logs continuously, applying minimal query load on the source, and delivers near-real-time changes to S3. Writing Parquet reduces storage and query cost, satisfying the minutes-level latency and low source impact constraints.
- ✗
Amazon Kinesis Data Firehose with a Lambda function that queries Oracle.
Why it's wrong here
Firehose cannot query Oracle; it ingests streaming records pushed to it, so a Lambda would need to poll the database itself, and Lambda's 15-minute ceiling plus connection overhead makes sustained Oracle polling impractical. Firehose is correct for consuming existing streams into S3, not sourcing from relational databases.
- ✗
AWS Data Pipeline with a periodic SQL query activity to copy full table snapshots.
Why it's wrong here
Periodic full-table snapshots re-read the entire table each run, imposing heavy load on the Oracle source and delivering batch latency rather than near real-time change capture. AWS Data Pipeline suits scheduled bulk movement, not incremental replication; the last_modified column would be wasted since no delta filtering occurs.
- ✗
AWS Glue with a JDBC connection to Oracle, running a crawler every 5 minutes.
Why it's wrong here
A Glue crawler only infers schema and populates the Data Catalog; it does not extract rows, so no data reaches S3. Glue with JDBC suits scheduled batch ETL jobs, but crawler frequency does not create incremental ingestion, and repeated full reads would still burden Oracle.
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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Same concept, more angles
1 more way this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data engineer needs to ingest data from a relational database (MySQL) into Amazon S3 for analytics. The database is 500 GB and the job must run daily with incremental updates. Which AWS service is BEST suited for this task?
easy- A.Amazon EMR with Apache Sqoop.
- B.Amazon Kinesis Data Firehose with a database source.
- ✓ C.AWS Database Migration Service (DMS) with a replication task.
- D.AWS Glue ETL job with a JDBC connection.
Why C: AWS DMS with a replication task is the best choice because it is specifically designed for continuous, incremental data replication from relational databases like MySQL to Amazon S3. DMS supports ongoing replication (change data capture) to capture incremental changes without custom scripting, and it can handle the initial 500 GB load efficiently. Other services either lack native incremental support or require additional configuration for this use case.
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.