Description: Global Anonymization is a comprehensive approach to anonymizing data across multiple datasets, ensuring that sensitive information cannot be linked to specific individuals. This process involves the application of advanced anonymization techniques that allow for the removal or modification of personal data while maintaining the utility of the information for analysis and studies, without compromising individual privacy. Global Anonymization is distinguished by its ability to operate across different data sources, making it a valuable tool for organizations handling large volumes of information. This approach not only aims to protect individual identities but also to comply with privacy and data protection regulations, such as GDPR in Europe. By implementing Global Anonymization, organizations can share and analyze data more securely, fostering collaboration and innovation without the risk of exposing sensitive information. The main features of this approach include the removal of direct identifiers, data generalization, and value perturbation, allowing for the maintenance of dataset integrity while protecting the privacy of the individuals involved. In a world where concerns about data privacy are increasingly relevant, Global Anonymization presents an effective solution to balance the need for data analysis with the protection of personal information.
