Ensuring Data Privacy in Practice

Learn about industry solutions to ensure data privacy, and how synthetic data and federated learning can be used to handle data privacy.

Theoretical approaches carry value, but this lesson will cover some of the more common techniques and tools used in the real world to ensure data privacy and minimize reidentification and leakage risks.

Synthetic twins

Synthetic data can create high-fidelity, fake “copies” of a dataset that doesn’t contain any of the PII (the protected classes) of the original set. Recall that in earlier lessons, we’ve discussed sourcing data synthetically. Here, we generate new synthetic sources from an existing dataset that retains all of the original properties but removes all of the PII.

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