#data-ops

Build an automated data quality monitoring system. Checks to implement: 1. Completeness (null percentage per column). 2. Uniqueness (duplicate detection). 3. Validity (regex patterns, range checks). 4. Timeliness (data freshness alerts). 5. Consistency (cross-table referential integrity). Create a dashboard showing quality scores over time with alerting for threshold breaches. Use Great Expectations or custom Python validators.