Data quality monitoring for a production warehouse

Project Description

We find out our data is wrong when someone notices a dashboard looks odd, usually days later. We want automated checks — freshness, row counts, nulls in columns that should never be null, referential integrity between marts — that alert before a human notices. The design constraint is alert fatigue. A check that cries wolf twice a week will be muted within a month, so thresholds need thought rather than defaults.

Skills Required