Automating Data Quality in Dev Environments

Data quality is the backbone of successful AI, yet most leaders lack quality standards they can automate in production. This course teaches you how to create quality standards for the data in your domains, then automate those standards in production environments.

Most organizations produce and ingest more data than they can effectively manage, with insufficient standards to measure quality. As leaders face increasing pressure to leverage AI, companies that don't adopt and implement better standards will fall behind. Instructor Lauren Maffeo explains how to define data quality standards per domain, who should set these quality standards, which tools you should use to scale and automate these standards, and how to ensure that any new data is measured against these standards. Gain an understanding of the people, processes, and tools needed to know what data quality looks like and integrate those standards into your data architecture.