How does Data Cloud support data governance and privacy?

How does Data Cloud support data governance and privacy?

• A. Data capture without consent.
• B. Role-based access, data masking, field-level encryption, consent management, data retention policies, and audit logs.
• C. Deleting data after 30 days automatically.
• D. Anonymous data sharing with no controls.

Answer: (B)

Managing data governance and privacy relies on layered controls that protect who can access data, how data is protected, and how long it is kept. Role-based access limits visibility to what a user needs for their role, ensuring only authorized people see sensitive information. Data masking hides sensitive values in outputs so analysts can work with data without exposing secrets. Field-level encryption protects specific sensitive fields, so even if the dataset is exposed, those values remain unreadable. Consent management tracks user preferences and supports updating or revoking permissions to stay aligned with privacy laws. Data retention policies govern how long data stays in the system and when it must be purged, helping meet legal and organizational requirements. Audit logs provide an immutable trail of who accessed or changed data, enabling accountability and compliance reporting. Together, these features form a robust governance and privacy framework in Data Cloud. Capturing data without consent undermines privacy safeguards. A fixed automatic deletion rule rarely satisfies governance needs because it ignores consent, accessibility, and auditing requirements. Anonymous data sharing with no controls eliminates governance and traceability.

Managing data governance and privacy relies on layered controls that protect who can access data, how data is protected, and how long it is kept. Role-based access limits visibility to what a user needs for their role, ensuring only authorized people see sensitive information. Data masking hides sensitive values in outputs so analysts can work with data without exposing secrets. Field-level encryption protects specific sensitive fields, so even if the dataset is exposed, those values remain unreadable. Consent management tracks user preferences and supports updating or revoking permissions to stay aligned with privacy laws. Data retention policies govern how long data stays in the system and when it must be purged, helping meet legal and organizational requirements. Audit logs provide an immutable trail of who accessed or changed data, enabling accountability and compliance reporting. Together, these features form a robust governance and privacy framework in Data Cloud.

Capturing data without consent undermines privacy safeguards. A fixed automatic deletion rule rarely satisfies governance needs because it ignores consent, accessibility, and auditing requirements. Anonymous data sharing with no controls eliminates governance and traceability.