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Anonymization and pseudonymization of data

Behind the Mask

Article from ADMIN 86/2025

By Daniel Richey

Data anonymization and pseudonymization are two key techniques that ensure privacy while enabling the use of data for analysis and decision making; the two methods offer different approaches that vary as a function of use case.

Data anonymization and pseudonymization are not just technical approaches but should be key factors in every organization's data protection strategy. Whereas anonymization aims to modify personal data such that the data subject cannot be identified, pseudonymization aims to make identification more difficult by replacing identifiers with pseudonyms. These techniques are particularly relevant in the context of Europe's General Data Protection Regulation (GDPR), which stipulates strict requirements for the handling of personal data, requiring businesses to implement robust mechanisms that ensure both data integrity and data protection.

Implementing anonymization and pseudonymization techniques is technically demanding and poses numerous challenges, including ensuring data quality and usefulness after anonymization and providing protection against re-identification risks. At the same time, these techniques offer immense opportunities, particularly with a view to leveraging big data and machine learning without violating data protection regulations. Choosing the right technology and implementing it requires a deep understanding of the existing data structures, the legal framework, and the potential risks. Various technical processes play a role and are discussed in detail in this article.

Different Ways for Different Plays

Anonymization and pseudonymization differ fundamentally in their application and objectives and depend on the industry and use case. Anonymization involves modifying personal data to remove identifiability irreversibly. Direct and indirect identifiers are removed or modified. After complete anonymization, it is no longer possible to draw conclusions about individual people, which puts the data firmly outside the scope of the strict requirements that apply under data protection law. Once anonymized, data can no longer be traced back to the original subject, which makes this

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