We are building an open source Data Observability tool dqo.ai and we wondering what kind of data quality issues we should focus on. So far we are able to monitor timeliness (if the data is fresh), validity (values in columns not meeting requirements), consistency (anomalies how the number of rows is growing over time), uniqueness.
I will appreciate the feedback about the typical data quality issues that are worth continuous monitoring.
The code is open source on github: https://github.com/dqoai/dqo
Best answer by YuriGrinshteynView original