Description: Information loss in the context of data anonymization refers to the reduction in the quality or utility of data due to the techniques employed to protect individuals’ privacy. When anonymization methods are applied, such as the removal of personal identifiers or data generalization, the aim is to prevent the re-identification of individuals from the information. However, these techniques can compromise the richness of the data, making it less accurate or useful for subsequent analyses. For instance, by removing specific data, the ability to conduct detailed analyses that could be crucial for research or decision-making may be lost. Information loss is a critical aspect to consider in data management, as it involves a delicate balance between privacy and the utility of information. In a world where data is increasingly valuable, understanding and managing information loss becomes essential for organizations seeking to protect user privacy without sacrificing the quality of the data they use.
