DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is ingesting streaming data from an IoT fleet into Amazon S3 using Amazon Kinesis Data Firehose. The data arrives as JSON, but the downstream analytics require Parquet format. Which Firehose transformation should the engineer configure?
⚠ Common exam trap
Many candidates confuse S3 lifecycle policies or Batch Operations as viable transformation tools, overlooking that Firehose's Lambda integration is the only option that performs real-time, record-level format conversion within the streaming pipeline.
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
✓
Configure a Lambda function as a data transformation in Firehose to convert JSON to Parquet.
Amazon Kinesis Data Firehose can invoke an AWS Lambda function as a data transformation step to convert incoming JSON records to Parquet format before delivery to S3. This is the native, serverless way to perform record-level format conversion within the Firehose delivery stream, ensuring downstream analytics tools can directly query the Parquet data without additional processing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use an S3 lifecycle policy to convert JSON to Parquet.
Why it's wrong here
Lifecycle policies only manage object transitions, not format conversion.
- ✓
Configure a Lambda function as a data transformation in Firehose to convert JSON to Parquet.
Why this is correct
Lambda can transform data format during delivery.
- ✗
Use S3 Batch Operations to convert existing JSON objects to Parquet.
Why it's wrong here
Batch Operations are for bulk processing, not stream ingestion.
- ✗
Use Kinesis Data Analytics to convert the stream to Parquet before writing to S3.
Why it's wrong here
Kinesis Data Analytics does not output Parquet directly to S3.
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.