- A
Use Kinesis Data Firehose with a Lambda transformation function
Firehose handles buffering, transformation via Lambda, and direct delivery to Redshift.
- B
Use AWS Glue ETL jobs running continuously
Why wrong: Glue is designed for batch processing, not real-time streams.
- C
Use Kinesis Client Library (KCL) to consume and transform data, then write to Redshift using COPY
Why wrong: KCL requires managing a consumer application, increasing operational overhead.
- D
Use AWS Direct Connect to stream data directly into Redshift
Why wrong: Direct Connect provides network connectivity, not data transformation.
Quick Answer
The correct choice is to use Kinesis Data Firehose with a Lambda transformation function. This solution minimizes operational overhead because Firehose natively handles buffering, batching, and direct loading into Redshift, while Lambda performs the real-time transformation of streaming data from Kinesis Data Streams without requiring you to manage any servers or custom consumers. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of managed ingestion pipelines versus custom application code—a common trap is choosing the Kinesis Client Library, which forces you to manage checkpointing and application scaling, or AWS Glue, which is batch-oriented and unsuitable for low-latency streaming. Remember that Firehose is the fully managed bridge for transform streaming data load to Redshift, and Lambda is its lightweight transformation engine. A helpful memory tip: think “Firehose for the hose, Lambda for the squeeze”—the hose delivers the stream, and Lambda squeezes the data into shape before it lands in Redshift.
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 data engineer is ingesting streaming data from an IoT fleet into Amazon Kinesis Data Streams. The data must be transformed in real-time and loaded into an Amazon Redshift cluster. Which solution minimizes operational overhead?
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 Kinesis Data Firehose with a Lambda transformation function
Option A is correct because Kinesis Data Firehose can buffer and batch incoming data, invoke a Lambda function for transformation, and load directly into Redshift. Option B is wrong because KCL requires custom application management. Option C is wrong because Glue is batch-oriented. Option D is wrong because Direct Connect is for dedicated network connections.
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.
- ✓
Use Kinesis Data Firehose with a Lambda transformation function
Why this is correct
Firehose handles buffering, transformation via Lambda, and direct delivery to Redshift.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use AWS Glue ETL jobs running continuously
Why it's wrong here
Glue is designed for batch processing, not real-time streams.
- ✗
Use Kinesis Client Library (KCL) to consume and transform data, then write to Redshift using COPY
Why it's wrong here
KCL requires managing a consumer application, increasing operational overhead.
- ✗
Use AWS Direct Connect to stream data directly into Redshift
Why it's wrong here
Direct Connect provides network connectivity, not data transformation.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
What to study next
Got this wrong? Here's your next step.
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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: Use Kinesis Data Firehose with a Lambda transformation function — Option A is correct because Kinesis Data Firehose can buffer and batch incoming data, invoke a Lambda function for transformation, and load directly into Redshift. Option B is wrong because KCL requires custom application management. Option C is wrong because Glue is batch-oriented. Option D is wrong because Direct Connect is for dedicated network connections.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Same concept, more angles
1 more ways 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 data engineer is ingesting streaming data from an IoT fleet into Amazon S3 using Amazon Kinesis Data Firehose. The data arrives as JSON, but the downstream analytics require Parquet format. Which Firehose transformation should the engineer configure?
easy- A.Use an S3 lifecycle policy to convert JSON to Parquet.
- ✓ B.Configure a Lambda function as a data transformation in Firehose to convert JSON to Parquet.
- C.Use S3 Batch Operations to convert existing JSON objects to Parquet.
- D.Use Kinesis Data Analytics to convert the stream to Parquet before writing to S3.
Why B: Option B is correct because Kinesis Data Firehose can convert JSON to Parquet using an AWS Lambda transformation. Option A is wrong because S3 lifecycle policies do not transform data format. Option C is wrong because Kinesis Data Analytics performs real-time analytics, not format conversion. Option D is wrong because S3 batch operations process existing objects, not streaming ingestion.
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Last reviewed: Jun 20, 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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