DEA-C01 Data Ingestion and Transformation Practice Question
A company uses Amazon Kinesis Data Firehose to deliver streaming data to an S3 bucket. The data must be transformed from JSON to Parquet format before delivery. Which approach should be used?
⚠ Common exam trap
A common mix-up: candidates think they need a separate ETL service like Glue or EMR for format conversion, but Firehose's built-in Lambda integration is the simplest and most cost-effective way to transform data in-flight before delivery.
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 Kinesis Data Firehose to invoke a Lambda function for data transformation.
Kinesis Data Firehose can invoke a Lambda function as a transformation step before data is delivered to S3. This allows you to convert JSON records to Parquet format inline, without needing an intermediate storage or separate processing pipeline. The Lambda function receives batches of records, transforms them (e.g., using PyArrow or similar libraries), and returns them to Firehose for delivery.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure Kinesis Data Firehose to invoke a Lambda function for data transformation.
Why this is correct
Firehose can call a Lambda function to transform records, including converting JSON to Parquet.
- ✗
Use an AWS Glue ETL job to read from S3 and write Parquet back to S3.
Why it's wrong here
This works but adds latency; Firehose can do it in-stream with Lambda.
- ✗
Use Amazon EMR to process the data and output Parquet.
Why it's wrong here
EMR is for large-scale batch processing, not real-time streaming.
- ✗
Use Kinesis Data Analytics to convert the data to Parquet.
Why it's wrong here
Kinesis Data Analytics processes streaming data but is not the primary tool for format conversion in Firehose.
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 |
Go deeper
Related to this question
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Same concept, more angles
1 more way this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company is ingesting streaming data from IoT devices into Amazon Kinesis Data Streams. The data must be transformed into Parquet format and stored in Amazon S3. Which AWS service can perform the transformation in near real-time with minimal operational overhead?
easy- A.Amazon EMR cluster running Spark Streaming
- B.AWS Glue ETL job triggered by Kinesis stream
- ✓ C.Amazon Kinesis Data Firehose with a transformation Lambda function
- D.Amazon Kinesis Data Analytics for Apache Flink
Why C: Amazon Kinesis Data Firehose is the fully managed service designed to load streaming data into S3 with built-in data format conversion. By attaching a Lambda transformation function, you can convert incoming records to Parquet format in near real-time without managing any infrastructure, making it the lowest-operational-overhead choice for this task.
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.