FREE ON-DEMAND WEBINAR
AI/ML to Classify and Build Data Intelligence – Design and Approaches
March 2, 2022
About this event:
With the exponential growth incorporate data, there is an increasing need to ensure all sensitive, personal, and business information is properly identified and secured. But it has become difficult for organizations to keep up with this growth in enterprise data and utilize its full potential.
Only AI and machine learning technologies offer the ability to detect, map, and categorize sensitive data at an organizational level. However, mapping sensitive information at an enterprise scale requires a solution that is scalable and accurate.
Reasons to Watch:
- Get acquainted with the types of data classification
- Know how to properly scope and plan for such an effort
- Learn about the capabilities and limitations of such an AI/ML model and how to incorporate appropriate manual controls for successful execution
Key Themes:
- The current state of data classification – an overview into types of classification
- Starting a classification project: planning
- Challenges with auto-classification
- Active vs. passive approaches to classifying documents
- Classification project outcomes
- Synthetic data and its use in solving data classification problems
Webinar Highlights
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About the Facilitators:
Priya Keshav
Founder & CEO | Meru Data LLC
Priya Keshav is the Founder and CEO of Meru Data LLC, a company focused on building solutions to simplify and sustain privacy and information governance programs for customers worldwide. At Meru, Priya helps leading companies identify and proactively manage privacy and security risks around data. Prior to this Priya Keshav was the Managing Director of KPMG’s Forensic Technology Services practice in the Southwest U.S. She has more than twenty years of consulting experience in risk management, cyber-crime response, technology investigations, regulatory response, Information governance and forensics investigations. Priya’s work has been published in various business publications and she is a frequent speaker on privacy and information governance.
Maura R. Grossman
Research Professor
Maura R. Grossman is a Research Professor in the School of Computer Science at the University of Waterloo, an Adjunct Professor at Osgoode Hall Law School, and an affiliate faculty member of the Vector Institute, all in Ontario, Canada, as well as an eDiscovery attorney and consultant in Buffalo, New York. Previously, she was Of Counsel at Wachtell, Lipton, Rosen & Katz, where for 17 years, she represented Fortune 100 companies and major financial institutions in civil litigation and white-collar criminal and regulatory investigations, and advised the firm’s lawyers and clients on legal, technical, and strategic issues involving eDiscovery and information governance, both domestically and abroad. Maura’s scholarly work on TAR, most notably, Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review, published in the Richmond Journal of Law & Technology in 2011, has been widely cited in case laws, both in the U.S. and abroad.
