DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is designing a data transformation pipeline using AWS Glue. The source data is in Amazon S3 in Parquet format, and the transformed output must be written to another S3 bucket in Parquet format partitioned by year, month, day. The pipeline should handle incremental updates efficiently. Which three features should the engineer use? (Choose THREE.)
⚠ Common exam trap
Test-takers frequently confuse general-purpose tools like Spark SQL or monitoring concepts with the specific AWS Glue features designed for incremental processing and partitioning, leading them to select options that are technically possible but not the three required features.
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 job bookmarks to track processed data
AWS Glue job bookmarks track processed data by recording the state of previously processed files and partitions, enabling incremental processing of new or changed data in subsequent runs. This is essential for efficiently handling incremental updates without reprocessing the entire dataset.
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 job bookmarks to track processed data
Why this is correct
Enables incremental processing.
- ✗
Use AWS Glue JobWatch for monitoring job progress
Why it's wrong here
JobWatch is not an AWS service; CloudWatch is used.
- ✓
Use DynamicFrames instead of Spark DataFrames for schema handling
Why this is correct
DynamicFrames handle schema changes gracefully.
- ✓
Enable partition pruning in the Glue job
Why this is correct
Reduces data scanned by reading only relevant partitions.
- ✗
Use Spark SQL for transformations
Why it's wrong here
Not specific to incremental or partitioning.
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
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.