Which privacy-preserving techniques should be reflected in Clarity data models?

Which privacy-preserving techniques should be reflected in Clarity data models?

• A. Consent management is optional; data sharing is unrestricted
• B. Data masking/pseudonymization, minimization, role-based access control, consent management, and de-identification where required
• C. Encryption at rest is the only requirement
• D. No need to track user consent

Answer: (B)

Designing privacy-preserving data models means building layered protections that cover data from collection through sharing and storage. Data minimization keeps only what’s necessary, reducing exposure. Masking or pseudonymizing data preserves usefulness while protecting identities, and de-identification is applied where sharing or analysis requires even less identifiable detail. Role-based access control ensures that only the right people can view sensitive information. Tracking and honoring user consent is essential so data use and sharing align with user choices and regulatory requirements. Encryption at rest protects stored data, and you should also consider protections for data in transit and during processing. Together, these techniques provide a comprehensive approach to privacy and governance. Options that suggest consent management is optional or that data sharing is unrestricted bypass important controls. Relying on encryption at rest alone misses access controls, data in use, and consent considerations. Claiming there’s no need to track consent ignores privacy rights and regulatory obligations.

Designing privacy-preserving data models means building layered protections that cover data from collection through sharing and storage. Data minimization keeps only what’s necessary, reducing exposure. Masking or pseudonymizing data preserves usefulness while protecting identities, and de-identification is applied where sharing or analysis requires even less identifiable detail. Role-based access control ensures that only the right people can view sensitive information. Tracking and honoring user consent is essential so data use and sharing align with user choices and regulatory requirements. Encryption at rest protects stored data, and you should also consider protections for data in transit and during processing. Together, these techniques provide a comprehensive approach to privacy and governance.

Options that suggest consent management is optional or that data sharing is unrestricted bypass important controls. Relying on encryption at rest alone misses access controls, data in use, and consent considerations. Claiming there’s no need to track consent ignores privacy rights and regulatory obligations.