Top 10: Data Cleaning Tools for AI

Enterprises are discovering that the success of AI deployments hinges less on model sophistication and more on the quality of data feeding those models.
An estimated 60% of AI projects fail before reaching production due to data quality issues, according to industry research.
As organisations move from pilot programmes to production-scale machine learning (ML) systems, the infrastructure required to profile, cleanse and govern data has become critical.

The platforms below are some of the top tools addressing this challenge, handling everything from basic data validation to complex governance frameworks across hybrid cloud environments.