DEA-C01 Data Ingestion and Transformation Practice Question
An e-commerce company wants to capture clickstream data from its website and store it in Amazon S3 for analytics. The data arrives continuously and the company needs near-real-time processing. Which solution is most appropriate?
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
Amazon Kinesis Data Firehose is the most appropriate solution because it is a fully managed service designed to ingest streaming data and deliver it to destinations like Amazon S3 with near-real-time latency. The company needs continuous clickstream capture and near-real-time processing, which Firehose provides. Option A (AWS Data Pipeline) is for batch processing, not streaming. Option B (AWS Snowball Edge) is for offline data transfer, not real-time. Option D (S3 Transfer Acceleration) improves upload speed but is not a streaming ingestion service.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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AWS Data Pipeline
Why it's wrong here
AWS Data Pipeline is a batch-oriented orchestration service that runs scheduled jobs on data at rest; it cannot ingest a continuous clickstream or deliver near-real-time processing. It suits periodic ETL between data stores. Kinesis Data Firehose is designed for continuous streaming ingestion with buffering straight into Amazon S3.
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AWS Snowball Edge
Why it's wrong here
Snowball Edge is a physical edge device for bulk offline data transfer and local compute, not continuous ingestion; clickstream arrives as a live stream requiring Kinesis or Firehose into S3. It would be correct for migrating terabytes from a site with no reliable network bandwidth.
- ✓
Amazon Kinesis Data Firehose
Why this is correct
Amazon Kinesis Data Firehose ingests streaming clickstream data continuously and delivers it into Amazon S3 with near-real-time buffering, satisfying the stem's continuous-arrival and near-real-time requirements without custom consumer code. It handles scaling and delivery automatically, unlike batch uploads or query-based approaches.
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Amazon S3 Transfer Acceleration
Why it's wrong here
Transfer Acceleration speeds up uploads over long distances using edge locations, but it is a transport optimisation, not an ingestion service; it does not capture clickstream events or process them in near-real-time. It suits accelerating large file transfers to an existing bucket, whereas Kinesis Data Firehose buffers and delivers streaming records 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.