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 stored as CSV files and is updated daily. The engineer wants to load only new data each day without duplicating existing records. Which AWS service or feature should the engineer use to automate this process?
⚠ Common exam trap
The trap here is assuming that Redshift Spectrum or DMS can automatically handle incremental loads from S3 without additional 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 Glue with job bookmarks enabled to track processed files.
AWS Glue job bookmarks are designed to track processed data across job runs, enabling incremental processing. For daily loads from S3 to Redshift, a Glue ETL job with bookmarks ensures only new files are processed each day, preventing duplication. This automates the process and integrates with Redshift via the COPY command. Other options do not provide automatic incremental load tracking for S3 files.
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 Spectrum to query S3 data directly and insert new records.
Why it's wrong here
Redshift Spectrum allows querying data in S3 directly from Redshift, but it does not automatically load data into Redshift tables. To insert new records, the engineer would need to write custom SQL to select from Spectrum and insert into a Redshift table, which is manual and does not track processed files. This approach does not automate the incremental load and could lead to duplication if not carefully managed.
- ✗
Amazon Kinesis Data Firehose to stream S3 data to Redshift.
Why it's wrong here
Kinesis Data Firehose can deliver streaming data to Redshift, but it is designed for real-time streaming sources, not for batch loading from existing S3 files. Firehose does not track processed files or support incremental batch loads from S3. Using Firehose for this scenario would require setting up a stream and would not automatically handle daily updates without duplication.
- ✓
AWS Glue with job bookmarks enabled to track processed files.
Why this is correct
AWS Glue job bookmarks track the state of data processed in previous runs, allowing the job to process only new or changed files in subsequent runs. This is ideal for daily incremental loads from S3 to Redshift, as it prevents reprocessing and duplication. The engineer can create a Glue ETL job that reads from S3, applies transformations, and writes to Redshift using the COPY command. This automates the incremental load process efficiently.
- ✗
AWS Database Migration Service (DMS) with ongoing replication from S3 to Redshift.
Why it's wrong here
AWS DMS is designed for migrating databases and replicating ongoing changes from database sources, not for loading files from S3. While DMS can read from S3 as a source, it does not natively track which files have been processed for incremental loads in the same way Glue job bookmarks do. Using DMS for this purpose would be overcomplicated and not the intended use case.
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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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
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