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Why is data quality testing essential in a big data pipeline?

  1. A Silent quality failures propagate wrong numbers into decisions without any job failing
  2. B It is required by regulation
  3. C It speeds up processing
  4. D It reduces storage costs
Answer

Silent quality failures propagate wrong numbers into decisions without any job failing

Row count checks, null rate thresholds and referential integrity tests catch what a successful job status does not reveal.

All Big data MCQs

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