A practical primer, checklist, and assessment templates to compare synthetic data, anonymization and differential privacy approaches and their trade-offs for safe sharing and model training.
A practical primer that explains types of synthetic data and common privacy-preserving approaches, compares their trade-offs, and provides a decision checklist and an assessment template teams can use to evaluate privacy risk and analytical utility before sharing or using synthetic datasets.
Interactive checklist and evaluation form to determine whether synthetic or other privacy-preserving approaches are appropriate, document selected privacy metrics, capture empirical utility tests, and record governance, release controls, and known limitations.
An interactive decision and risk-assessment template teams can use to decide when synthetic data or other privacy-preserving techniques are appropriate, document trade-offs, record validation tasks, and produce an actionable implementation and monitoring plan.
Interactive assessment to evaluate privacy risk, analytic fidelity, operational needs, and decision trade-offs when choosing synthetic data, anonymization, or hybrid approaches.