Which practice is critical for maintaining compliance with data protection regulations in the cloud?

Data minimization is a fundamental practice for maintaining compliance with data protection regulations in the cloud. This principle emphasizes the importance of collecting only the data that is necessary for a specific purpose and retaining it only for as long as needed. Many data protection regulations, such as the General Data Protection Regulation (GDPR), mandate that organizations limit data collection to what is strictly necessary, which aligns closely with the practice of data minimization.

By focusing on data minimization, organizations can reduce the risk of violating privacy laws and regulations, because they handle less personal data, thus lowering their exposure to potential data breaches and enhancing the overall security posture. This practice not only aids in compliance but also fosters trust with customers, as they feel more secure knowing that their data is being handled responsibly.

In contrast, practices such as data redundancy, data maximization, and data aggregation may not support compliance efforts effectively. Data redundancy generally pertains to creating copies of data for backup and recovery purposes rather than securing personal data. Data maximization, which involves collecting and retaining as much data as possible, would directly conflict with compliance regulations requiring minimal data collection. Data aggregation focuses on combining datasets for analysis, which can also lead to risks if it involves personal data without proper justification or consent.