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Anatomy of a Modern Data Pipeline Quiz ​

Last Updated: September 12, 2026

  1. What must be checked before replaying Kafka offsets?
    • A) Whether the needed records remain after retention/compaction
    • B) Whether Kafka automatically deduplicates every external sink
    • C) Whether all batch inputs were deleted
    • D) Whether every event always remains forever
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Answer: A) Whether the needed records remain after retention/compaction

Replay requires retained input and consistent state recovery. End-to-end exactly-once also depends on sink transactions, idempotency and external effects.

  1. What distinguishes ETL from ELT?
    • A) Whether a lake is used
    • B) ETL transforms before destination load; ELT transforms after destination load
    • C) Whether Kafka is used
    • D) ELT is always exact and ETL always approximate
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Answer: B) ETL transforms before destination load; ELT transforms after destination load

Moving curated data into a warehouse does not by itself make the process ELT. Check the transformation order and destination.

  1. Which statement about batch and stream accuracy is correct?
    • A) Streaming is always approximate
    • B) Batch is always exact
    • C) It depends on late data, duplicates, state and output contracts; fast provisional results can be followed by finalization
    • D) Checkpoints automatically make external API effects exactly-once
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Answer: C) It depends on late data, duplicates, state and output contracts; fast provisional results can be followed by finalization

Design event time, watermarks, allowed lateness and sink semantics. Spark and Flink are not limited to one processing mode each.

  1. Which statement about Schema Registry compatibility checks is correct?
    • A) They automatically block every database DDL and semantic change
    • B) They validate the registration/serialization/CI paths where applied, and consumer tests are still needed
    • C) One registration automatically ensures transitive compatibility across every version
    • D) Compatibility rules remove the need for data-quality checks
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Answer: B) They validate the registration/serialization/CI paths where applied, and consumer tests are still needed

Bypass paths and business-semantic changes need separate validation. Check the scope of backward/forward and transitive settings.

Study material | Kafka quiz