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Section 1Privacy Governance (20%)Preview
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Summary
Privacy Governance sets direction and Privacy Operations makes it work: identify personal information and obligations, define principles/policies/roles, govern vendors, handle incidents, and operationalize data-subject rights.
Key Points
Privacy risk is broader than cybersecurity risk; secure processing can still create privacy harm.
Section 2Privacy Risk Management and Compliance (18%)Preview
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Summary
Risk Management asks what privacy problems processing can cause; Compliance proves obligations and controls remain effective. Think PIAs, threats/vulnerabilities, risk response, frameworks, evidence, monitoring, and metrics.
Key Points
Privacy risk can result from authorized processing.
Common Mistakes
Treating a penetration test as a privacy impact assessment.
Exam Tips
Privacy risk starts with processing.
Section 3Data Life Cycle Management (23%)Preview
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Summary
Data Life Cycle Management means know the data, control its use, preserve quality, minimize it, govern analytics/AI, control transfers, retain only as justified, and destroy it appropriately.
Key Points
Inventory = what/where/why/who; data-flow diagram = how data moves and changes.
Common Mistakes
Confusing processing purpose with a technical action.
Exam Tips
Map before control.
Section 4Privacy Engineering (39%)Preview
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Summary
Privacy Engineering is the technical center of CDPSE: design privacy into infrastructure, cloud, endpoints, APIs and SDLC; implement security controls; and engineer consent, tracking, de-identification, PETs, and AI/ML privacy safeguards.