By now, many of us are familiar with the general tenets of data governance: inventorying what data lies where, controlling data access, protecting sensitive data, and documenting all of it. But in the context of machine learning (ML) and artificial intelligence (AI), new governance requirements arise.
Beyond identifying sensitive data, we must determine whether it can be analyzed in aggregate and discover if the aggregated data can be de-anonymized. Beyond securing datasets, we must determine who can build ML models on them. In addition to cataloging datasets, we need to monitor changes in them, then alert data scientists to retrain models based on those changes, or do so automatically based on policy.
These are just a few examples of AI-specific data governance concerns. To learn more, join us for this free 1-hour webinar from GigaOm Research. The Webinar features GigaOm analyst Andrew Brust and special guest, Will Nowak from Dataiku, an Enterprise AI and machine learning platform.
In this 1-hour webinar, you will discover:
- Governance âcheckpointsâ for data scientists
- The relationship between data regulations, ethics, and AI
- Making ML models compliant, both with government regulations and corporate policy
Register now to join GigaOm Research and Dataiku for this free expert webinar.
Who Should Attend:
- Chief Data Officers
- Data Stewards
- Data Scientists
- Machine Learning Engineers
- Data Engineers
- Business Analysts