DEA-C01 Data Ingestion and Transformation Practice Question
Which THREE factors should be considered when selecting a data ingestion service for a high-volume, real-time streaming pipeline that requires exactly-once processing semantics? (Choose 3.)
⚠ Common exam trap
The DEA-C01 exam often tests the misconception that schema evolution or in-flight transformation are required for exactly-once semantics, when in fact they are unrelated to delivery guarantees and instead belong to data quality or processing domains.
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
✓
Ability to replay records from a checkpoint
In high-volume streaming pipelines, the ability to replay records from a checkpoint is essential for achieving exactly-once processing semantics. Services like Amazon Kinesis Data Streams and Apache Kafka allow consumers to reset to a specific sequence number or offset, enabling reprocessing of unacknowledged records after a failure without data loss or duplication.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Ability to replay records from a checkpoint
Why this is correct
Replay allows recovery without duplication.
- ✓
Support for idempotent record processing
Why this is correct
Idempotency is required for exactly-once semantics.
- ✓
Integration with Amazon S3 for checkpoint storage
Why this is correct
Checkpoints enable exactly-once processing by tracking progress.
- ✗
Support for schema evolution
Why it's wrong here
Schema evolution is not directly related to exactly-once semantics.
- ✗
Ability to transform data in-flight
Why it's wrong here
Transformation is not required for exactly-once semantics.
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