DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer needs to ingest streaming data from an Amazon Kinesis Data Stream into an Amazon S3 bucket. The data must be delivered in near real-time and stored in Parquet format for efficient querying. The engineer wants to minimize custom code. Which solution should the engineer use?
⚠ Common exam trap
The trap here is overlooking Firehose's built-in record format conversion feature and assuming that custom code is needed to convert JSON to Parquet.
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
✓
Use Amazon Kinesis Data Firehose to deliver the stream to S3, and enable record format conversion to Parquet using an AWS Glue table.
Kinesis Data Firehose provides a fully managed way to deliver streaming data from Kinesis Data Streams to S3. It supports automatic conversion to Parquet using a schema from the AWS Glue Data Catalog, requiring no custom code. This meets the near real-time and Parquet requirements while minimizing development effort, unlike solutions that require writing Lambda functions, Flink applications, or Glue scripts.
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 Amazon Kinesis Data Firehose to deliver the stream to S3, and enable record format conversion to Parquet using an AWS Glue table.
Why this is correct
Kinesis Data Firehose can read directly from a Kinesis Data Stream, buffer records, and deliver them to S3. It supports record format conversion from JSON to Parquet using a schema defined in the AWS Glue Data Catalog. This requires no custom code and provides near real-time delivery, meeting all requirements with minimal effort.
- ✗
Use Amazon Kinesis Data Analytics to process the stream and write Parquet to S3 using a Flink application.
Why it's wrong here
Kinesis Data Analytics (now Managed Service for Apache Flink) requires developing and managing a Flink application, which involves custom code and operational overhead. Although it can process and write Parquet to S3, it is not the simplest solution and does not minimize custom code compared to Firehose, which offers built-in format conversion.
- ✗
Use AWS Lambda to read from the Kinesis Data Stream and write Parquet files to S3 using the AWS SDK for pandas (awswrangler).
Why it's wrong here
This approach requires writing and maintaining Lambda code to poll the stream, convert records to Parquet, and write to S3. It also introduces complexity in handling checkpoints, error retries, and scaling. While it can work, it does not minimize custom code as effectively as a managed service like Firehose, which handles these concerns natively.
- ✗
Use AWS Glue streaming ETL job to read from the Kinesis Data Stream and write Parquet to S3.
Why it's wrong here
AWS Glue streaming ETL jobs require writing and maintaining Glue scripts, and while they can read from Kinesis and write Parquet, they involve more custom code and configuration than Firehose. Glue streaming is better suited for complex transformations, but for simple ingestion with format conversion, Firehose is the more managed and code-free option.
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.