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CDPSE exam Format | CDPSE Course Contents | CDPSE Course Outline | CDPSE exam Syllabus | CDPSE exam Objectives

Number of Questions: 120 multiple-choice questions.

Duration: 3.5 hours (210 minutes).

Passing Score: Scaled score of 450 or higher (on a scale of 200-800).

Language: English.

Delivery Method: Computer-based testing (CBT) at authorized testing centers or online proctored exam.



- PRIVACY GOVERNANCE

- Personal Information

- Privacy Principles

- Privacy by Design

- Consent

- Transparency

- Privacy Laws and Regulations

- Privacy Documentation

- Policies

- Guidelines



- PRIVACY OPERATIONS

- Organizational Culture, Structure, and Responsibilities

- Vendor and Supply Chain Management

- Incident Management

- Data Subject Rights, Requests, and Notification



- PRIVACY RISK MANAGEMENT AND COMPLIANCE

- Risk Management Process and Policies

- Privacy-Focused Assessment

- Privacy Impact Assessment (PIA)

- Privacy Training and Awareness

- Threats and Vulnerabilities

- Risk Response



- COMPLIANCE

- Privacy Frameworks

- Evidence and Artifacts

- Program Monitoring and Metrics



- DATA LIFE CYCLE MANAGEMENT

- DATA COLLECTION AND PROCESSING

- Data Inventory, Dataflow Diagram, and Classification

- Data Quality (e.g. Accuracy)

- Data Use Limitation

- Data Analytics

- Aggregation

- AI

- Data Warehouse



- DATA PERSISTENCE AND DESTRUCTION

- Data Minimization

- Data Disclosure and Transfer

- Data Storage, Retention, and Archiving

- Data Destruction



- PRIVACY ENGINEERING

- TECHNOLOGY STACKS

- Infrastructure and Platform Technology

- legacy

- cloud computing

- Devices and Endpoints

- Connectivity

- Secure Development Life Cycle

- APIs and Cloud-Native Services



- PRIVACY RELATED SECURITY CONTROLS

- Asset Management

- Identity and Access Management

- Patch Management and Hardening

- Communication and Transport Protocols

- Encryption and Hashing

- Monitoring and Logging



- PRIVACY CONTROLS

- Consent Tagging

- Tracking Technologies

- cookie management

- Anonymization and Pseudonymization

- Privacy Enhancing Technologies (PETs)

- AI/Machine Learning (ML) Considerations

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