A fast pipeline is worthless if it delivers wrong data. Data quality must be checked automatically, on every load, and not discovered by the user in the report.
Checks that pay off
- Completeness: required columns without nulls.
- Uniqueness: keys without duplicates.
- Ranges: values within the expected bounds.
- Referential integrity between tables.
When a check fails, the pipeline should stop and alert, never silently publish suspicious data.
