Augmented data quality uses AI and ML to fasten effective ways of improving data quality and minimizing the interference of data stewards.
An organization requires an assessment to understand its current state of data quality and a clear picture of what AI and ML can do for it. AI does automate many data quality processes but not entirely. The AI models are trained to understand what good or bad data looks like and how corrections were made; the data stewards supervise this. Data Governance becomes the foundation for effective ML models.
Xenonstack Glossary
