Certified Secure Software Lifecycle Professional Practice

Anonymization in the context of data management specifically refers to the process of removing personal identifiers from data sets. This action is crucial for protecting individual privacy by ensuring that the information can no longer be tied back to a specific individual. The primary goal of anonymization is to allow data analysis and processing while safeguarding the identities of the data subjects. When personal identifiers are removed, the data can be analyzed without compromising the privacy of individuals, making it especially important in industries that handle sensitive information, such as healthcare and finance. By anonymizing data, organizations can comply with privacy regulations and ethical standards, thus fostering trust with users and stakeholders. In contrast, the other options do not accurately represent the concept of anonymization. Converting data into machine-readable formats does not necessarily involve the removal of personal identifiers. Increasing data storage efficiency pertains to optimizing space and performance, which is unrelated to the privacy concerns addressed by anonymization. Finally, backing up data without encryption focuses on the security of data storage rather than the privacy aspect linked to the removal of identifiers. This clarification highlights why option B is the most appropriate choice regarding the definition of anonymization in data management.