Anonymiseerimise

Anonymiseerimise, often translated as anonymization, is the process of removing or modifying personal information from data so that it can no longer be associated with a specific individual. The primary goal of anonymization is to protect privacy while still allowing the data to be used for various purposes, such as research, analysis, or sharing.

There are several techniques used in anonymization. One common method is data aggregation, where individual data points are grouped together, making it impossible to identify specific individuals within the larger dataset. Another technique is generalization, which involves replacing specific values with broader categories. For example, an exact age might be replaced with an age range. Data suppression is another method, where certain sensitive data points are removed entirely. Pseudonymization is related, but it involves replacing identifying information with artificial identifiers or pseudonyms, which can be reversed if the key is available. True anonymization aims to prevent any possibility of re-identification.

The effectiveness of anonymization techniques can vary. It is important to consider the context and potential for re-identification, especially with the increasing availability of other datasets that could be linked to the anonymized data. Regulatory frameworks, such as GDPR, often mandate or encourage anonymization to ensure data privacy compliance. The process requires careful planning and execution to balance the need for data utility with the imperative of protecting individual privacy.