Comparison
AnonymisationvsPseudonymisation
Anonymisation
you removed the id entirely and aggregated to groups of at least fifty, so no row can be traced back to a person even with the other tables.
Transforming data so that no individual can be re-identified, including by combining it with anything else. The bar is much higher than dropping the name column: quasi-identifiers like postcode, birth date and employer re-identify people with alarming reliability, so genuine anonymisation usually means aggregation or suppression. Claiming it when you have only pseudonymised is a common and consequential mistake.
Full entry →Pseudonymisation
the user id is replaced with a hash so you can still count sessions per person, and rejoining it to a name is a deliberate act with a key.
Replacing identifiers with consistent substitutes so behaviour can still be linked per person without the person being named. It preserves the analytical joins that matter while removing the direct identifier. Most privacy regimes treat it as still personal data, because the mapping exists — which is the distinction people most often get wrong when they claim a dataset has been anonymised.
Full entry →