DEA-C01 Data Ingestion and Transformation Practice Question
A company uses Amazon Kinesis Data Streams to ingest real-time logs from thousands of applications. The data must be transformed and enriched with reference data from Amazon S3 before being stored in Amazon S3 in Parquet format. The transformation logic is stateful and requires exactly-once processing. Which AWS service should the data engineer use to perform the transformation?
⚠ Common exam trap
The trap here is assuming that AWS Glue streaming ETL or Lambda can handle stateful, exactly-once processing, when they are better suited for simpler transformations.
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
✓
Amazon Managed Service for Apache Flink (formerly Kinesis Data Analytics) with a Flink application.
The need for stateful processing, exactly-once semantics, and enrichment with reference data from S3 points to a stream processing framework. Amazon Managed Service for Apache Flink provides these capabilities with native support for state, exactly-once processing, and connectors to Kinesis and S3. Other services either lack stateful processing, exactly-once guarantees, or both.
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 Kinesis Data Firehose with AWS Lambda transformation.
Why it's wrong here
Kinesis Data Firehose can invoke Lambda for transformation, but it does not support stateful processing or exactly-once semantics. Firehose delivers data to destinations like S3, but it may duplicate records in failure scenarios, and Lambda transformations are stateless. It also cannot easily join with reference data from S3 for enrichment. This service is better for simple, stateless transformations and delivery.
- ✗
AWS Glue streaming ETL job.
Why it's wrong here
AWS Glue streaming ETL jobs can process data from Kinesis Data Streams and write to S3, but they are based on Apache Spark Structured Streaming and may not provide exactly-once semantics in all cases. They also may not support stateful operations as robustly as Flink. While Glue can enrich with reference data, it is less suited for low-latency, stateful processing with strict exactly-once guarantees.
- ✓
Amazon Managed Service for Apache Flink (formerly Kinesis Data Analytics) with a Flink application.
Why this is correct
Amazon Managed Service for Apache Flink supports stateful stream processing with exactly-once semantics. It can read from Kinesis Data Streams, enrich data by joining with reference data from S3 (using Flink's rich functions or async I/O), and write to S3 in Parquet format using the FileSystem connector. This service is designed for complex, stateful transformations and ensures exactly-once processing.
- ✗
AWS Lambda with Kinesis Data Streams event source mapping.
Why it's wrong here
AWS Lambda can process Kinesis records and write to S3, but it is stateless and does not support stateful processing or exactly-once semantics inherently. Lambda may retry on failure, leading to duplicate processing. Enriching with reference data from S3 would require loading the data on each invocation or using a cache, which is inefficient. This approach does not meet the stateful and exactly-once 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 |
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
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