Synthetic Data Governance refers to the policies and operational controls used to manage how synthetic data is generated, validated, versioned, distributed, and used. Its purpose is to maintain quality, traceability, and consistency in synthetic-first environments.
Frequently asked questions
What is synthetic data generation?
Creating new records that preserve the statistical structure of real data without copying real individuals, so AI can train on realistic data that carries no real personal information.
How does synthetic data generation protect privacy?
When the generation process applies differential privacy, the output carries a formal guarantee that no individual record can be recovered from it.
When should you use synthetic data generation?
When real data is restricted, imbalanced, or too small: to expand coverage and unblock AI work without exposing source records.