Learning Objectives

Upon successful completion of this course, participants will be able to:

1. Fundamentals of Data Risk Management

• Understand the importance of data risk management in modern organizations.
• Identify key data assets and the risks associated with their collection, storage, and use.
• Learn the principles of data governance and risk frameworks (ISO 27005, NIST, COSO, GDPR, HIPAA).

2. Data Classification and Risk Assessment

• Categorize data based on sensitivity (public, internal, confidential, highly confidential).
• Perform risk assessments using methodologies like FAIR (Factor Analysis of Information Risk).
• Identify potential threats such as data breaches, unauthorized access, and insider threats.

3. Regulatory Compliance and Data Protection Laws

• Understand global and industry-specific regulations (GDPR, CCPA, HIPAA, PCI-DSS, SOX).
• Implement compliance policies to ensure proper data handling and security.
• Develop audit and reporting procedures to meet legal requirements.

4. Cybersecurity Threats and Data Protection Measures

• Recognize common cyber threats such as phishing, ransomware, data exfiltration, and insider risks.
• Implement encryption, access control, and authentication measures to protect data.
• Utilize endpoint protection, firewalls, and intrusion detection systems (IDS).

5. Data Loss Prevention (DLP) and Incident Response

• Implement DLP strategies to prevent unauthorized data access and leaks.
• Develop an incident response plan to mitigate data breaches and cyberattacks.
• Conduct forensic investigations and root cause analysis after security incidents.

6. Third-Party Risk Management and Vendor Compliance

• Assess risks associated with cloud providers, vendors, and third-party data processors.
• Implement Service Level Agreements (SLAs) and data processing agreements (DPAs).
• Monitor and audit third-party data security compliance.

7. Business Continuity and Disaster Recovery

• Develop a data backup and recovery strategy to ensure resilience.
• Implement redundancy and failover systems to maintain data availability.
• Test and validate disaster recovery plans for critical business data.

8. Emerging Trends and Future Risks in Data Security

• Explore the impact of AI, machine learning, and big data on risk management.
• Understand threats related to quantum computing and advanced cyberattacks.
• Develop proactive strategies to adapt to evolving data risks.

9. Case Studies and Practical Applications

• Analyze real-world data breaches and risk management failures.
• Participate in risk assessment and mitigation exercises.
• Develop a data risk management strategy tailored to organizational needs.

Target Audience

• IT and cybersecurity professionals
• Risk management and compliance officers
• Data protection officers (DPOs)
• Business leaders and executives handling sensitive data
• Auditors and governance professionals