What does data minimization refer to?

Data minimization is a key principle in data protection and privacy regulation. It refers to the practice whereby organizations are only allowed to collect personal data that is adequate, relevant, and limited to what is necessary for achieving their specific purpose. This principle is designed to ensure that only essential information is gathered, thereby reducing the risk of misuse, unnecessary exposure, or data breaches.

By adhering to data minimization, organizations protect individuals' privacy by not collecting excessive information that is not required for their services. This aligns with the broader goals of ensuring transparency and accountability in data handling practices and promoting people's trust in how their personal information is managed.

The other choices refer to different aspects of data management and protection but do not specifically define data minimization. Maintaining accurate personal data pertains to data quality, analyzing large datasets deals with data analysis, and demonstrating consent focuses on legal compliance regarding the processing of personal data. These are important components of overall data governance but do not encapsulate the concept of data minimization itself.