The correct answer is to use Amazon Kinesis Data Firehose to ingest the streaming data, buffer it, and deliver it to S3, then run an AWS Glue job to convert the files to Parquet. This approach is the most cost-effective and scalable because Kinesis Firehose is a fully managed service designed for high-throughput ingestion with no payload limits, unlike Lambda, and it automatically batches data before writing to S3, reducing costs. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of choosing the right serverless ingestion tool for high-volume streaming data, with a common trap being to select Lambda due to its familiarity—but Lambda’s 6 MB payload limit and per-invocation cost make it unsuitable for millions of small files. Remember the memory tip: “Firehose for the flow, Glue for the glow”—Firehose handles the streaming ingestion, and Glue transforms the data into query-friendly Parquet format.
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 engineering team is designing a data ingestion pipeline that will receive millions of small JSON files per hour from external partners via API. The files should be stored in Amazon S3 and then transformed into Parquet for querying. Which approach is MOST cost-effective and scalable?
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 to buffer and deliver data to S3, then use AWS Glue to convert to Parquet.
Option C is correct because Kinesis Firehose can ingest streaming data, buffer it, and deliver in batches to S3, and then a Glue job can convert to Parquet. Option A is wrong because Lambda has a payload limit and is not cost-effective for millions of files. Option B is wrong because Direct Connect is for dedicated network, not for API ingestion. Option D is wrong because EMR is overkill and more expensive.
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 Amazon Kinesis Data Firehose to buffer and deliver data to S3, then use AWS Glue to convert to Parquet.
Why this is correct
Firehose can ingest high throughput, buffer, and deliver to S3; Glue can run scheduled conversions.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use AWS Lambda to process each file as it arrives and write to S3.
Why it's wrong here
Lambda has a concurrency limit and may not handle millions of files per hour cost-effectively.
✗
Use AWS Direct Connect to establish a dedicated network for file uploads.
Why it's wrong here
Direct Connect is for network connectivity, not for data ingestion at the application layer.
✗
Use Amazon EMR to process the files as they arrive in S3.
Why it's wrong here
EMR requires cluster management and may be more expensive than serverless options.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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.
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 Amazon Kinesis Data Firehose to buffer and deliver data to S3, then use AWS Glue to convert to Parquet. — Option C is correct because Kinesis Firehose can ingest streaming data, buffer it, and deliver in batches to S3, and then a Glue job can convert to Parquet. Option A is wrong because Lambda has a payload limit and is not cost-effective for millions of files. Option B is wrong because Direct Connect is for dedicated network, not for API ingestion. Option D is wrong because EMR is overkill and more expensive.
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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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 thousands of IoT devices into AWS. The data is JSON-formatted and must be stored in Amazon S3 for long-term analytics. Which service is most appropriate for real-time ingestion and routing to S3?
easy
A.Amazon SQS
✓ B.Amazon Kinesis Data Firehose
C.Amazon Kinesis Data Streams
D.AWS Glue
Why B: Amazon Kinesis Data Firehose is the easiest way to load streaming data into S3. Kinesis Data Streams requires custom consumers; AWS Glue is batch ETL; Amazon SQS is not designed for direct S3 delivery.
Variation 2. A data engineering team is ingesting streaming data from IoT devices into Amazon Kinesis Data Streams. The data must be transformed in real-time and then loaded into an Amazon S3 bucket for long-term storage. Which AWS service should be used to perform the transformation and delivery to S3 with minimal operational overhead?
easy
✓ A.Amazon Kinesis Data Firehose
B.AWS Glue
C.Amazon EMR
D.Amazon Kinesis Data Analytics
Why A: Option B is correct because Kinesis Data Firehose can subscribe to a Kinesis Data Stream, transform data using Lambda or its built-in transformations, and automatically deliver to S3 with no code required for delivery. Option A is wrong because Kinesis Data Analytics is for real-time analytics, not direct delivery to S3. Option C is wrong because AWS Glue is a batch ETL service, not real-time. Option D is wrong because Amazon EMR is a managed Hadoop cluster that requires significant overhead.
Variation 3. A data pipeline ingests streaming data from thousands of IoT devices into Kinesis Data Streams. The data must be transformed using a simple field mapping before being stored in S3. Which service should be used to perform the transformation with minimal operational overhead?
easy
A.AWS Lambda function invoked by the Kinesis stream
B.AWS Glue ETL job
C.Kinesis Data Analytics
✓ D.Kinesis Data Firehose with a Lambda transformation
Why D: Option C is correct because Kinesis Data Firehose can perform simple transformations using Lambda functions before delivering data to S3. Option A is wrong because Glue ETL is better for complex batch transformations. Option B is wrong because Kinesis Data Analytics is for real-time analytics, not simple field mapping. Option D is wrong because Lambda alone would require managing the delivery to S3.
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.