As organizations push to scale AI, access to high-quality, usable data remains a major barrier. This session explores how SAS Data Maker enables synthetic data generation to address challenges like limited access, privacy constraints, and data insufficiency—while preserving data characteristics for analytics use. You’ll see how the product fits into the broader analytics lifecycle, supporting use cases such as model development, validation, and scenario testing. The roadmap also highlights future directions, including tighter lifecycle integration, governance enhancements, and new capabilities for controlled, flexible synthetic data generation.
Presenter: Sundaresh Sankaran, SAS
Watch the recording
