DEA-C01 Data Store Management Practice Question
A data engineer is designing a data pipeline that ingests streaming data from IoT devices into Amazon S3 using Amazon Kinesis Data Firehose. The data must be transformed from JSON to Parquet format before storage. Which TWO actions should the data engineer take to achieve this?
⚠ Common exam trap
The DEA-C01 exam often tests the misconception that Firehose can automatically convert to Parquet without a schema definition, leading candidates to select Option A, but in reality, Firehose requires an explicit schema (via Glue or Lambda) for Parquet conversion.
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
✓
Create a Glue Data Catalog table defining the schema and configure Firehose to use the table for Parquet conversion.
Amazon Kinesis Data Firehose can directly convert incoming JSON data to Parquet format by referencing a table schema defined in the AWS Glue Data Catalog. This allows Firehose to perform the schema-aware conversion without custom code, leveraging the Glue table's column definitions and SerDe for Parquet serialization.
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 Firehose's built-in Parquet conversion without any additional configuration.
Why it's wrong here
Firehose requires a schema (Glue Data Catalog) for Parquet conversion.
- ✗
Use Amazon Kinesis Data Analytics to convert the data format.
Why it's wrong here
Kinesis Data Analytics is for analytics, not format conversion.
- ✗
Configure Firehose to convert the data to Apache Avro format.
Why it's wrong here
Avro conversion requires a schema, and Firehose does not support Avro natively.
- ✓
Create a Glue Data Catalog table defining the schema and configure Firehose to use the table for Parquet conversion.
Why this is correct
Firehose can use the schema from Glue Data Catalog to convert to Parquet.
- ✓
Create an AWS Lambda function to transform the data to Parquet and use it as a Firehose transformation.
Why this is correct
Lambda can convert JSON to Parquet and Firehose can invoke the transformation.
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 by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.