Quick Answer
The answer is AWS Glue ETL job, as it is the service purpose-built for serverless data transformation at scale, including converting JSON to Parquet format with minimal effort. AWS Glue automatically infers schemas from JSON data in S3 and can write the output in columnar Parquet format, which optimizes query performance in Amazon Athena by reducing I/O and enabling predicate pushdown. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your ability to distinguish between services for batch ETL versus querying or streaming—a common trap is choosing Athena because it can query Parquet, but it cannot transform data formats. Remember that Glue’s built-in transform “Change Schema” or a simple Spark script handles the conversion natively. Memory tip: “Glue sticks JSON to Parquet” — think of Glue as the adhesive that binds your raw data to an optimized format for analytics.
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 stores IoT sensor data in S3 as JSON files. They need to convert the data to Parquet format for efficient querying with Amazon Athena. Which AWS service can perform this transformation with minimal effort?
Kinesis Data Firehose
Why wrong: Firehose is for streaming data.
Amazon Athena
Why wrong: Athena is for querying, not transforming data.
AWS Glue ETL job
Glue ETL can convert JSON to Parquet.
AWS Lambda
Why wrong: Lambda is for small-scale transformations, not large batch conversions.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
AWS Glue ETL job
Option B is correct because AWS Glue ETL can easily convert JSON to Parquet. Option A is wrong because Athena is a query engine, not a transformation service. Option C is wrong because Lambda is for small, event-driven transformations. Option D is wrong because Kinesis Data Firehose is for streaming data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Kinesis Data Firehose
Why it's wrong here
Firehose is for streaming data.
Amazon Athena
Why it's wrong here
Athena is for querying, not transforming data.
AWS Glue ETL job
Why this is correct
Glue ETL can convert JSON to Parquet.
Related concept
Read the scenario before looking for a memorised answer.
AWS Lambda
Why it's wrong here
Lambda is for small-scale transformations, not large batch conversions.
Common exam traps
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
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.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
What to study next
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 — study guide chapter
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FAQ
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
The correct answer is: AWS Glue ETL job — Option B is correct because AWS Glue ETL can easily convert JSON to Parquet. Option A is wrong because Athena is a query engine, not a transformation service. Option C is wrong because Lambda is for small, event-driven transformations. Option D is wrong because Kinesis Data Firehose is for streaming data.
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.
Read the scenario before looking for a memorised answer.
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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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