The correct choice is to use AWS Glue ETL jobs for complex JSON transformations to Redshift, because Glue provides a fully managed Apache Spark environment that excels at flattening nested structures and handling evolving transformation logic through code-based flexibility. This approach directly addresses the need for a pipeline that can adapt to frequent changes without infrastructure overhead, unlike alternatives such as Athena for query-only tasks, Lambda with its 15-minute execution limit, or Redshift COPY which lacks transformation capabilities. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of when to choose Glue over simpler services, often trapping candidates who overlook Lambda’s scalability constraints or Athena’s lack of ETL support. A strong memory tip is “Glue for complex, code-driven ETL; COPY for raw loads; Lambda for lightweight transforms only.”
DEA-C01 Data Ingestion and Transformation Practice Question
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 data engineer is designing a data ingestion pipeline for JSON files landing in an Amazon S3 bucket. The pipeline must transform the data (e.g., flatten nested structures) and load it into Amazon Redshift. The transformation logic is complex and may evolve frequently. Which approach provides the MOST flexibility and ease of maintenance?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use AWS Glue ETL jobs to transform the data and load into Redshift.
Option A is correct because Glue ETL (Apache Spark) provides a flexible, code-based environment for complex transformations. Option B is incorrect because Athena is for querying, not ETL. Option C is incorrect because Lambda is limited by execution time and memory for large files. Option D is incorrect because Redshift COPY does not transform.
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 AWS Lambda functions to transform each file and load into Redshift.
Why it's wrong here
Lambda has limits on execution time and memory for large files.
✗
Use the Amazon Redshift COPY command to load raw JSON directly.
Why it's wrong here
COPY does not transform data.
✓
Use AWS Glue ETL jobs to transform the data and load into Redshift.
Why this is correct
Glue ETL supports complex transformations and is easy to maintain.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use Amazon Athena to query the raw data and insert into Redshift.
Why it's wrong here
Athena is not designed for ETL 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 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
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 AWS Glue ETL jobs to transform the data and load into Redshift. — Option A is correct because Glue ETL (Apache Spark) provides a flexible, code-based environment for complex transformations. Option B is incorrect because Athena is for querying, not ETL. Option C is incorrect because Lambda is limited by execution time and memory for large files. Option D is incorrect because Redshift COPY does not transform.
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.
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Question Discussion
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