Read up on differential privacy and k-anonymization. There are commonly implemented best practices for measuring and preserving anonymity in a dataset in non-reversible ways. It usually involves aggregating clusters of data and dropping clusters with too few unique contributions.

These techniques have a long track record in the private sector and with public entities such as the US Census, with a lot of formal research to back it up.