DEA-C01 Data Ingestion and Transformation Practice Question
A startup is building a data pipeline to ingest user activity logs from a mobile app. The logs are sent in real-time via HTTP POST requests. The data volume is low (a few hundred requests per second) but can spike to a few thousand during promotions. The team wants to store the logs in Amazon S3 for analysis. They also need to be able to query the data using Amazon Athena with minimal latency. The data must be transformed from JSON to Parquet and partitioned by date. The team is considering using Amazon API Gateway with AWS Lambda to receive the logs and write to S3. However, they are concerned about Lambda cold starts and the complexity of handling spikes. Which alternative solution should they choose?
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
✓
Use Amazon Kinesis Data Firehose with a HTTP endpoint as source, enable Parquet conversion, and deliver to S3 with dynamic partitioning
Amazon Kinesis Data Firehose is the best choice because it can directly receive HTTP POST requests (via its HTTP endpoint or integrated with API Gateway), automatically buffer incoming data, convert JSON to Parquet, and deliver to S3 with dynamic partitioning by date. This handles traffic spikes without custom code or Lambda cold starts, meeting all requirements with minimal operational overhead. Option A (API Gateway + Lambda → SQS → Lambda) adds complexity and still involves Lambda cold starts. Option C (Kinesis Data Streams + Lambda) also requires Lambda and cold start management. Option D (EMR Spark Streaming) is overkill for this low-volume use case.
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 Amazon API Gateway with AWS Lambda that sends logs to Amazon SQS, then a separate Lambda reads from SQS and writes to S3
Why it's wrong here
Adds unnecessary complexity; still relies on Lambda for transformation.
- ✓
Use Amazon Kinesis Data Firehose with a HTTP endpoint as source, enable Parquet conversion, and deliver to S3 with dynamic partitioning
Why this is correct
Firehose handles ingestion, transformation, and partitioning with automatic scaling.
- ✗
Use Amazon Kinesis Data Streams with AWS Lambda to process and write to S3
Why it's wrong here
Kinesis Data Streams introduces a mandatory consumer processing model that adds latency and operational overhead for a low-volume pipeline; the team’s requirement for minimal query latency is undermined because Lambda must poll the stream, process batches, and write Parquet partitions, which delays data availability in S3 compared to a direct ingestion service. This option is tempting because Kinesis excels at buffering and scaling for high-throughput streaming workloads, and it would be the correct choice if the startup needed durable, ordered replay of millions of events per second or real-time stream processing with multiple consumers.
- ✗
Use Amazon EMR with Spark Streaming to ingest logs from a custom endpoint
Why it's wrong here
Overly complex and costly for low-volume data.
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
About these practice questions
This DEA-C01 question is part of Courseiva's 1,711-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.