What does the term 'anonymization' mean in data privacy?

Anonymization in data privacy refers specifically to the process of removing identifiable information from data sets such that individuals cannot be re-identified from the data. This process is crucial for protecting personal information and ensuring compliance with privacy regulations, such as the GDPR, which require that personal data be handled in a manner that safeguards privacy.

By anonymizing data, organizations can utilize valuable information for analysis, research, or other purposes without risking the privacy of individuals involved. The goal is to create datasets that can be used for statistical and analytical purposes while minimizing the risk of exposing personal information. This allows for data-driven decision-making without compromising individual privacy rights.

The other options do not align with the definition of anonymization; they focus on different aspects of data handling and management, such as marketing practices, data summarization, or format conversion, rather than the specific goal of protecting the identity of individuals within a dataset.