These are the main prerequisites you need to address before starting the actual implementation of PDPL in your organization.
Legal and Compliance Framework
- Understanding PDPL and relevant regulations.
- Legal expertise for interpreting data protection laws.
- Data processing agreements (DPAs) with third parties.
Personal Data Protection Strategy
- Define goals and objectives for data protection.
- Develop a risk management plan.
- Establish data protection vision and mission.
Required Policies, Procedures, and Standards
- Develop data protection policies (e.g., data retention, access control).
- Define operational procedures for handling personal data.
- Ensure compliance with established standards.
Adequate IT Infrastructure (Tools, and Technologies)
- Implement data security tools (e.g., encryption, access control).
- Automate data protection tasks (e.g., consent management).
- Ensure systems support PDPL compliance (e.g., data minimization).
Skills and Competencies
- Legal and compliance expertise.
- Data governance and management skills.
- Risk and security management competencies.
- IT infrastructure and privacy by design knowledge.
- Operational process management skills.
- Training and awareness programs.
- Project and change management expertise.
Data Mapping and Classification
- Identify and classify personal data across the organization.
- Map data flows and understand where and how personal data is stored.
Vendor and Third-Party Management
- Identify third-party data processors and assess compliance.
- Ensure data processing agreements are in place.
Risk Assessment and Data Protection Impact Assessments (DPIAs)
- Conduct DPIAs for high-risk data processing activities.
- Breach Management and Response Plan
- Establish a clear process for handling data breaches.
- Set up breach notification procedures to comply with PDPL.
Employee Training and Awareness
- Train employees on PDPL compliance and data protection practices.
- Foster a data protection culture within the organization.
Recommended Resources
- Big Data vs. Traditional Data, Data Warehousing, AI, and Beyond
- Big Data Transformation Across Industries
- Big Data Security, Privacy, and Protection, & Addressing the Challenges of Big Data
- Designing Big Data Infrastructure and Modeling
- Leveraging Big Data through NoSQL Databases
- BDaaS (Big Data As-a-Service) – Data Governance Principles
- BDaaS (Big Data As-a-Service) – Compliance Features
- BDaaS (Big Data As-a-Service) – Data Governance Frameworks
- BDaaS (Big Data As-a-Service) – Real World Use Cases, and Scenarios
- BDaaS (Big Data As-a-Service) – General Activation Steps
- BDaaS (Big Data As-a-Service) – Enablement Methodology
- BDaaS (Big Data As-a-Service) – Challenges & Risks in BDaaS Implementation
- Data Strategy vs. Data Platform Strategy
- ABAC – Attribute-Based Access Control
- Consequences of Personal Data Breaches
- KSA PDPL (Personal Data Protection Law) – Initial Framework
- KSA PDPL – Consent Not Mandatory
- KSA PDPL Article 4, 5, 6, 7, 8, 9, 10, 11, & 12
- KSA PDPL Article 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, & 31
- KSA NDMO – Data Catalog and Metadata
- KSA NDMO – Personal Data Protection – Initial Assessment
- KSA NDMO – DG Artifacts Control – Data Management Issue Tracking Register
- KSA NDMO – Personal Data Protection – PDP Plan, & PDP Training, Data Breach Notification
- KSA NDMO – Classification Process, Data Breach Management, & Data Subject Rights
- KSA NDMO – Privacy Notice and Consent Management
- Enterprise Architecture Governance & TOGAF – Components
- Enterprise Architecture & Architecture Framework
- TOGAF – ADM (Architecture Development Method) vs. Enterprise Continuum
- TOGAF – Architecture Content Framework
- TOGAF – ADM Features & Phases
- Data Security Standards
- Data Steward – Stewardship Activities
- Data Modeling – Metrics and Checklist
- How to Measure the Value of Data
- What is Content and Content Management?
