Anonymisation does not work. A few quasi-identifiers can unmask people in an anonymous dataset, and pooling sensitive data centrally builds a target. So why move the data at all? This session works through federated learning, differential privacy and synthetic data, with live code. For each, what it protects, what it costs, where it breaks. It draws on my published architecture, which cut data exposure by 99.2 per cent. You will leave able to pick the right method for your threat model.