DEA-C01 Data Ingestion and Transformation Practice Question
A company uses Amazon Kinesis Data Firehose to deliver data to Amazon S3. The data engineer needs to transform the data before delivery. Which THREE options can be used to perform the transformation?
⚠ Common exam trap
Watch out — candidates often confuse AWS Glue ETL jobs (which are separate, batch-oriented) with the Glue Data Catalog schema used by Firehose's built-in format conversion, leading them to incorrectly select Glue ETL as a valid Firehose transformation option.
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
✓
Amazon Kinesis Data Firehose data format conversion (e.g., JSON to Parquet)
Amazon Kinesis Data Firehose can transform data natively using data format conversion (e.g., converting JSON to Parquet or ORC) without requiring external services. This is a built-in capability that applies schema-based conversion using AWS Glue tables, enabling efficient storage and querying in Amazon S3.
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 Athena queries
Why it's wrong here
Athena queries data after delivery.
- ✗
AWS Glue ETL job
Why it's wrong here
Glue jobs are not directly invoked by Firehose.
- ✓
Amazon Kinesis Data Firehose data format conversion (e.g., JSON to Parquet)
Why this is correct
Firehose can convert data formats natively.
- ✓
AWS Lambda function
Why this is correct
Firehose can invoke a Lambda function to transform records.
- ✓
Amazon Kinesis Data Firehose dynamic partitioning with Lambda
Why this is correct
Firehose can use Lambda for dynamic 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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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.