CDPSE Exam Information and Outline
Certified Data Privacy Solutions Engineer
CDPSE Exam Syllabus & Study Guide
Before you start practicing with our exam simulator, it is essential to understand the official CDPSE exam objectives. This course outline serves as your roadmap, breaking down exactly which technical domains and skills will be tested. By reviewing the syllabus, you can identify your strengths and focus your study time on the areas where you need the most improvement.
The information below reflects the latest 2026 course contents as defined by ISACA. We provide this detailed breakdown to help you align your preparation with the actual exam format, ensuring there are no surprises on test day. Use this outline as a checklist to track your progress as you move through our practice question banks.
Below are complete topics detail with latest syllabus and course outline, that will help you good knowledge about exam objectives and topics that you have to prepare. These contents are covered in questions and answers pool of exam.
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