WithPraxis
Data Quality: The Foundation Every AI Project Needs
Eighty percent of AI initiatives fail before reaching production. The culprit isn't model complexity – it's bad data. This article examines what proper data quality assessment looks like, how migration transforms messy data into AI-ready systems, and what governance means for mid-market distributors.