CDPSE - Certified Data Privacy Solutions Engineer

The Certified Data Privacy Solutions Engineer (CDPSE) course is a comprehensive program designed to provide learners with the skills necessary to implement effective privacy solutions and manage data protection within their organizations. The course is structured into three key modules:

1. Module 1: Privacy Governance

   • This module covers the fundamentals of personal data management, focusing on various privacy laws, documentation, consent processes, and data governance responsibilities. It emphasizes the importance of privacy training, vendor management, risk assessment, and incident management.

2. Module 2: Privacy Architecture

   • Learners are introduced to the technical aspects of data protection, including secure technology stacks, cloud services, system hardening, and privacy-focused development practices. Topics such as encryption, identity management, and monitoring's critical role in maintaining privacy are thoroughly explored.

3. Module 3: Data Cycle

   • This module addresses the entire lifecycle of data within an organization. It covers everything from data inventory and classification to quality management and data destruction, ensuring that data is protected at every stage of its journey.

By mastering these areas, participants will be well-equipped to support and enhance their organization's data privacy frameworks, ensuring alignment with global standards and regulations.

Course Prerequisites

To ensure a successful learning experience in the CDPSE course, the following prerequisites are recommended:

• Basic IT Concepts:

  • Understanding of IT terminology, particularly in relation to data handling and information systems.

• Familiarity with Data Protection and Privacy Principles:

  • Awareness of personal data's sensitivity and general principles of data protection.

• Knowledge of Privacy Laws and Regulations:

  • Understanding key privacy laws such as GDPR, CCPA, or other relevant regional privacy frameworks.

• Exposure to Information Security Principles:

  • Familiarity with risk management processes and basic information security practices.

• Understanding of Data Subject Rights:

  • Awareness of legal requirements for handling personal data, including data subject rights.

• Technical Understanding:

  • Foundational knowledge of IT systems, cloud services, endpoints, and secure development practices.

• Critical Thinking and Analytical Skills:

  • Ability to apply privacy governance concepts to practical scenarios.

While prior knowledge in these areas is beneficial, the CDPSE course is designed to build upon foundational concepts and guide learners through more advanced topics in data privacy solutions engineering.

Target Audience for CDPSE

The CDPSE course is aimed at professionals seeking to develop essential skills in privacy governance, architecture, and data lifecycle management. The target audience includes:

• Data Privacy Officers

• Compliance Officers and Lawyers specializing in data privacy

• Information Security Analysts

• IT Managers and Consultants

• Risk Assessment Professionals

• Data Protection Managers

• Cybersecurity Professionals

• Systems and Network Administrators

• Software Developers with a focus on privacy

• Cloud Security Specialists

• Data Governance and Quality Managers

• Privacy and Security Architects

• IT Auditors involved in privacy audits

• Corporate Training Professionals specializing in privacy and compliance

• Government Officials dealing with data protection regulations

• HR Professionals overseeing employee data privacy

• Marketing Managers who handle customer data

• Product Managers incorporating privacy into product design

• Business Analysts involved in data-sensitive projects

Learning Objectives - What You Will Learn in this CDPSE Course

The CDPSE course aims to equip learners with robust skills in privacy governance, architecture, and data lifecycle management to ensure compliance and effective data protection. The key learning objectives include:

• Privacy Governance:

  • Understand different types of personal data and their significance in privacy governance.

  • Gain knowledge of global privacy laws and standards, and learn how to apply them across various jurisdictions.

  • Develop and implement privacy documentation such as policies and guidelines.

  • Comprehend legal requirements for data processing, including consent and legitimate interest.

  • Manage data subject rights and understand responsibilities associated with various data-related roles.

  • Learn to manage privacy risks and conduct effective Privacy Impact Assessments (PIAs).

• Privacy Architecture:

  • Acquire knowledge on privacy architecture, including secure technology stacks, cloud services, and system hardening.

  • Master principles of secure development, including Privacy by Design, and learn to harden applications and software.

• Data Lifecycle Management:

  • Manage the data lifecycle, ensuring data quality, minimization, retention, and secure destruction practices are in place.

Course Outline:

Domain 1: Privacy Governance (34%)
A. Governance

1. Personal Data and Information

2. Privacy Laws and Standards across Jurisdictions

3. Privacy Documentation (e.g., Policies, Guidelines)

4. Legal Purpose, Consent, and Legitimate Interest

5. Data Subject Rights

B. Management

1. Roles and Responsibilities related to Data

2. Privacy Training and Awareness

3. Vendor and Third-Party Management

4. Audit Process

5. Privacy Incident Management

C. Risk Management

1. Risk Management Process

2. Privacy Impact Assessment (PIA)

3. Threats, Attacks, and Vulnerabilities related to Privacy

Domain 2: Privacy Architecture (36%)
A. Infrastructure

1. Technology Stacks

2. Cloud-based Services

3. Endpoints

4. Remote Access

5. System Hardening

B. Applications and Software

1. Secure Development Lifecycle (e.g., Privacy by Design)

2. Applications and Software Hardening

3. APIs and Services

4. Tracking Technologies

C. Technical Privacy Controls

1. Communication and Transport Protocols

2. Encryption, Hashing, and De-identification

3. Key Management

4. Monitoring and Logging

5. Identity and Access Management

Domain 3: Data Cycle (30%)
A. Data Purpose

1. Data Inventory and Classification (e.g., Tagging, Tracking, SOR)

2. Data Quality and Accuracy

3. Dataflow and Usage Diagrams

4. Data Use Limitation

5. Data Analytics (e.g., Aggregation, AI, Machine Learning, Big Data)

B. Data Persistence

1. Data Minimization (e.g., De-identification, Anonymization)

2. Data Migration

3. Data Storage

4. Data Warehousing (e.g., Data Lake)

5. Data Retention and Archiving

6. Data Destruction