- A
Amazon Athena CTAS query
Why wrong: Athena is for querying, not for continuous transformation of incoming data.
- B
AWS Glue ETL job triggered by S3 event
Glue can be triggered by S3 events (via Lambda or EventBridge) and perform the conversion and partitioning.
- C
AWS Lambda function triggered by S3 event
Lambda can perform the conversion and write to partitioned S3 paths.
- D
Amazon EMR with Spark job
Why wrong: EMR involves cluster management, increasing operational overhead.
- E
Amazon Kinesis Data Firehose with Parquet conversion
Why wrong: Firehose can convert to Parquet but does not support custom partitioning like year/month/day without additional Lambda.
Question 472 of 1,786
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 company ingests IoT data into an S3 bucket using AWS IoT Core rules. The data is in JSON format, and each record is about 500 bytes. The data volume is 5 GB per day. The company wants to convert the data to Parquet format and partition it by year/month/day. Which TWO AWS services can be used together to achieve this with minimal 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
✓
AWS Glue ETL job triggered by S3 event
Option B (AWS Glue ETL job triggered by S3 event) is correct because it provides a serverless, fully managed ETL solution that can convert JSON to Parquet and partition by year/month/day with minimal operational overhead. The S3 event trigger automatically invokes the Glue job when new data arrives, eliminating the need for manual scheduling or infrastructure management.
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.
- ✗
Amazon Athena CTAS query
Why it's wrong here
Athena is for querying, not for continuous transformation of incoming data.
- ✓
AWS Glue ETL job triggered by S3 event
Why this is correct
Glue can be triggered by S3 events (via Lambda or EventBridge) and perform the conversion and partitioning.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
AWS Lambda function triggered by S3 event
Why this is correct
Lambda can perform the conversion and write to partitioned S3 paths.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon EMR with Spark job
Why it's wrong here
EMR involves cluster management, increasing operational overhead.
- ✗
Amazon Kinesis Data Firehose with Parquet conversion
Why it's wrong here
Firehose can convert to Parquet but does not support custom partitioning like year/month/day without additional Lambda.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Amazon Kinesis Data Firehose (Option E) thinking it's the simplest for Parquet conversion, but it is designed for streaming data, not for batch processing of S3-uploaded files, and it lacks native S3 event-driven partitioning for historical data.
Detailed technical explanation
How to think about this question
AWS Glue ETL jobs use Apache Spark under the hood, allowing efficient conversion of JSON to columnar Parquet format, which reduces storage and improves query performance. The S3 event notification triggers the Glue job via an SQS queue or Lambda intermediary, ensuring exactly-once or at-least-once processing semantics. Partitioning by year/month/day is achieved by dynamically deriving partition keys from the event timestamp or object key, which Glue's DynamicFrame handles natively.
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
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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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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: AWS Glue ETL job triggered by S3 event — Option B (AWS Glue ETL job triggered by S3 event) is correct because it provides a serverless, fully managed ETL solution that can convert JSON to Parquet and partition by year/month/day with minimal operational overhead. The S3 event trigger automatically invokes the Glue job when new data arrives, eliminating the need for manual scheduling or infrastructure management.
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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