Description: Anonymization is the process of removing personally identifiable information from data so that individuals to whom the data refers cannot be identified, either directly or indirectly. This process is fundamental in the field of data privacy, as it allows the use of valuable information for analysis and studies without compromising individuals’ identities. Anonymization can be achieved through various techniques, such as data suppression, generalization, and perturbation, which alter the original data in a way that preserves its utility for analysis while eliminating any trace that could link it to a specific individual. The relevance of anonymization has grown in the digital age, where massive data collection poses serious challenges to privacy and data protection. Additionally, it is a key component in compliance with regulations such as the GDPR in Europe, which mandates strict measures to protect personal information. In summary, anonymization is not only a technical technique but also an ethical pillar in data management, allowing a balance between innovation and privacy.
