When accessing sensitive data in Amazon Redshift, what should be properly managed?

When accessing sensitive data in Amazon Redshift, proper management of column-level permissions is essential for ensuring data security and compliance. Column-level permissions allow administrators to define who can see specific columns in a database. This granular control is vital when dealing with sensitive information, such as personally identifiable information (PII) or financial data. By restricting access at the column level, you can ensure that users only view data they are authorized to see, thereby minimizing the risk of unauthorized access.

This level of control is particularly important in environments where different users have varying roles and responsibilities. By managing permissions effectively, organizations can enhance data security, adhere to regulatory requirements, and reduce the likelihood of data breaches.

The other options, while relevant to overall database management, do not specifically address the security of sensitive data in the same way. For instance, database size limitations pertain to performance and capacity rather than security; data retention policies focus on how long data should be stored; and log export frequencies relate to monitoring and auditing rather than direct data access controls.