DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is designing a data ingestion pipeline using Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. The data is in JSON format and must be converted to Apache Parquet before storage. The engineer wants to minimize costs and operational effort. Which two actions should the engineer take to meet these requirements? (Choose two.)
⚠ Common exam trap
The trap here is thinking that a Lambda function is needed for format conversion, but Firehose has native support using AWS Glue Data Catalog.
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
✓
Enable record format conversion in the Firehose delivery stream and select Apache Parquet as the output format.
To convert JSON to Parquet in Firehose with minimal effort, enable record format conversion and create an AWS Glue table defining the schema. These two actions allow Firehose to perform the conversion automatically. Other options either add overhead, do not address the conversion, or are supplementary but not required.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable compression on the Firehose delivery stream to reduce storage costs.
Why it's wrong here
Compression reduces storage costs but does not convert JSON to Parquet. Parquet is a columnar format that provides better query performance and compression, but enabling compression alone does not achieve the format conversion. It is not one of the two required actions.
- ✓
Enable record format conversion in the Firehose delivery stream and select Apache Parquet as the output format.
Why this is correct
Firehose supports record format conversion from JSON to Parquet using an AWS Glue table that defines the schema. This built-in feature eliminates the need for custom processing, reducing operational effort and cost. It is the recommended approach for format conversion in Firehose.
- ✓
Use AWS Glue to create a table in the AWS Glue Data Catalog that defines the schema of the JSON data for the Firehose stream to reference during conversion.
Why this is correct
Firehose record format conversion requires a reference to an AWS Glue table that specifies the source and target schemas. Creating this table is a necessary step to enable the conversion. It allows Firehose to understand the JSON structure and output Parquet.
- ✗
Configure the Firehose delivery stream to invoke an AWS Lambda function to convert each record from JSON to Parquet.
Why it's wrong here
Using Lambda for per-record conversion adds operational overhead and can be costly due to frequent invocations. It also requires managing the Lambda function and its dependencies. Firehose's built-in conversion is more efficient and cost-effective for this scenario.
- ✗
Set the Firehose buffer size to the maximum value to reduce the number of S3 PUT operations.
Why it's wrong here
Increasing buffer size can reduce S3 PUT costs but does not address the format conversion requirement. It also may increase latency. The question asks for actions to convert to Parquet with minimal cost and effort, so this alone is insufficient.
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 |
Go deeper
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.