DEA-C01 Data Ingestion and Transformation Practice Question
A company is using AWS Glue to catalog data in Amazon S3. The data is in CSV format with varying schemas. The Data Engineering team wants to ensure the Glue Data Catalog is updated automatically when new partitions are added to S3. Which TWO actions should be taken? (Choose two.)
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
✓
Enable partition indexing on the Glue Data Catalog.
A is correct because enabling partition indexing in the Glue Data Catalog allows partition pruning and automatic updates. C is correct because configuring a Glue crawler with a schedule will automatically discover new partitions. B is wrong because setting up an S3 event notification to trigger Lambda for manual updates is not as efficient as crawler scheduling. D is wrong because using AWS Glue ETL jobs to update the catalog is not automatic. E is wrong because Amazon Athena does not update the catalog.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable partition indexing on the Glue Data Catalog.
Why this is correct
Partition indexing enables automatic updates and efficient querying of new partitions.
- ✗
Set up an S3 event notification to trigger a Lambda function that updates the Glue Data Catalog.
Why it's wrong here
This is manual and not as scalable as scheduled crawling.
- ✓
Configure a scheduled AWS Glue crawler to run on a regular basis.
Why this is correct
Scheduled crawlers automatically discover new data and update the catalog.
- ✗
Run Amazon Athena queries with MSCK REPAIR TABLE to add partitions.
Why it's wrong here
MSCK REPAIR TABLE requires manual execution and is not automatic.
- ✗
Use AWS Glue ETL jobs to write data and update the catalog simultaneously.
Why it's wrong here
ETL jobs do not automatically update the catalog for new partitions.
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 by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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