DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer needs to transform JSON data from a Kinesis Data Stream into Parquet format and store it in an S3 data lake. The transformation includes simple field mapping and data type conversions. Which AWS service is the most cost-effective for performing this transformation in near-real-time?
⚠ Common exam trap
Many candidates choose AWS Glue ETL jobs or Amazon EMR because they associate them with data transformation, but the question specifies 'near-real-time' and 'most cost-effective' for simple transformations, which points to the serverless, pay-per-use Lambda integration with Firehose rather than provisioned cluster-based solutions.
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 Lambda function triggered by Kinesis Data Firehose
AWS Lambda functions triggered by Kinesis Data Firehose are the most cost-effective solution for near-real-time transformations because Lambda allows you to perform lightweight field mapping and data type conversions on streaming data with a pay-per-invocation model, while Firehose handles buffering, compression, and direct delivery to S3 in Parquet format. This serverless approach avoids the overhead and cost of provisioning clusters or running continuous jobs, making it ideal for simple transformations on high-frequency, low-latency streams.
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 with CTAS (CREATE TABLE AS SELECT)
Why it's wrong here
Athena is for querying, not for streaming transformation.
- ✓
AWS Lambda function triggered by Kinesis Data Firehose
Why this is correct
Lambda can be invoked by Firehose for record transformation and can output Parquet; it is serverless and cost-effective for near-real-time.
- ✗
AWS Glue ETL job
Why it's wrong here
Glue is optimized for batch ETL, not streaming; it would introduce latency and cost.
- ✗
Amazon EMR with Spark Streaming
Why it's wrong here
EMR requires cluster management and is overkill for simple transformations.
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
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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.