Not every quality check should stop the pipeline

A medium Pipeline Design interview practice problem on DataDriven. Write and execute real pipeline design code with instant grading.

Domain

Pipeline Design

Difficulty

medium

Problem

Not every quality check should stop the pipeline. The section's rule is per-check: block when running is worse than not running, warn when running is better than not running but still imperfect. Five candidate checks sit on the canvas. A primary-key uniqueness violation, a required-column null spike above 5 percent, and a row count below 50 percent of baseline are blockers (downstream joins are now wrong; the consumer would be misled). A row count at 80 to 90 percent of average and a slight freshness drift are warnings. Pick warn or block by adding an authority annotation to each check's name and routing block-class checks to a paging destination.

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