As data volume and complexity grow in an organization, sound decision making and high-quality AI products depend on having a robust approach to maintaining data health. In this talk, Anna Swigart will outline a framework for how to invest in preventative health for data, including choosing the right “data vitals” to measure, how to keep bad data from propagating through systems, early detection of anomalies using ML-driven tools like Luminaire, and being systematic about cleaning up data clutter.
