- A
AWS Glue ETL jobs scheduled every 5 minutes -> Redshift
Why wrong: Glue is batch, not real-time.
- B
S3 -> Lambda -> Redshift
Why wrong: S3 is not real-time; Lambda triggered by S3 events has latency.
- C
DynamoDB Streams -> Lambda -> Redshift
Why wrong: DynamoDB Streams is for DynamoDB changes, not clickstream.
- D
Kinesis Data Streams -> Kinesis Data Firehose -> Redshift
Provides real-time ingestion with transformation capability.
Question 564 of 1,786
Real-Time Ingestion to Redshift with Kinesis Data Streams and Firehose
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company needs to ingest real-time clickstream data from a web application into Amazon Redshift with minimal latency. The data volume is high and requires processing before loading. Which architecture 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
✓
Kinesis Data Streams -> Kinesis Data Firehose -> Redshift
D is correct because Kinesis Data Streams captures high-volume clickstream data in real time, and Kinesis Data Firehose can buffer, transform (e.g., with Lambda), and load the data directly into Amazon Redshift with near-zero latency. This architecture is purpose-built for streaming ingestion with minimal overhead, unlike batch or intermediary storage approaches.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Glue ETL jobs scheduled every 5 minutes -> Redshift
Why it's wrong here
Glue is batch, not real-time.
- ✗
S3 -> Lambda -> Redshift
Why it's wrong here
S3 is not real-time; Lambda triggered by S3 events has latency.
- ✗
DynamoDB Streams -> Lambda -> Redshift
Why it's wrong here
DynamoDB Streams is for DynamoDB changes, not clickstream.
- ✓
Kinesis Data Streams -> Kinesis Data Firehose -> Redshift
Why this is correct
Provides real-time ingestion with transformation capability.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'real-time' with 'near-real-time' and choose a batch option like Glue (A) or an indirect streaming path like S3 -> Lambda (B), failing to recognize that Kinesis Data Firehose is the only AWS service that natively integrates streaming ingestion with Redshift without additional latency or complexity.
Detailed technical explanation
How to think about this question
Kinesis Data Firehose uses a buffering mechanism (default 60 seconds or 1 MB) to batch records before writing to Redshift via the COPY command, which is optimized for bulk loads. Under the hood, Firehose can invoke a Lambda function for data transformation (e.g., JSON flattening or data enrichment) before delivery, ensuring processing happens in-stream without external orchestration. In real-world scenarios, this architecture can handle thousands of records per second with sub-minute end-to-end latency, making it ideal for clickstream analytics.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Data Ingestion and Transformation — study guide chapter
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Kinesis Data Streams -> Kinesis Data Firehose -> Redshift — D is correct because Kinesis Data Streams captures high-volume clickstream data in real time, and Kinesis Data Firehose can buffer, transform (e.g., with Lambda), and load the data directly into Amazon Redshift with near-zero latency. This architecture is purpose-built for streaming ingestion with minimal overhead, unlike batch or intermediary storage approaches.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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.
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