Training course

Overview

Data Security for Professionals is a comprehensive five-day professional training course designed to equip information technology, cybersecurity, data management, compliance, audit, and business professionals with the knowledge and practical capabilities required to protect organizational data throughout its lifecycle. The course provides a structured understanding of data security principles, threats, vulnerabilities, risk management, identity and access management, encryption, data classification, secure data handling, monitoring, incident response, privacy, and security governance. Participants will explore how modern organizations can establish effective data protection controls across databases, cloud platforms, applications, endpoints, networks, analytics environments, and third-party services.

The course develops practical expertise in identifying sensitive and critical information, assessing data-related risks, implementing appropriate access controls, applying encryption and masking techniques, and establishing secure data handling procedures. Participants will work with professional security practices and tools such as identity and access management platforms, multi-factor authentication, role-based access control, data loss prevention solutions, vulnerability scanners, security information and event management platforms, database activity monitoring, cloud security controls, and security assessment techniques. Practical exercises and realistic scenarios help participants translate security concepts into operational controls that can be applied within their own organizations.

Data Security for Professionals also introduces internationally recognized standards and frameworks used to establish, assess, and continuously improve data security programs. Participants will examine ISO/IEC 27001, ISO/IEC 27002, the NIST Cybersecurity Framework, NIST security and privacy guidance, CIS Controls, COBIT, Zero Trust principles, and relevant privacy and data protection requirements. Through case studies, risk assessments, control-mapping exercises, incident simulations, and security design activities, participants will learn how to align technical safeguards with governance, regulatory, business continuity, and enterprise risk requirements.

By the end of this professional data security training course, participants will be able to contribute effectively to the design, implementation, assessment, and continuous improvement of organizational data security programs. The course progresses from foundational concepts to advanced professional practices, including threat modeling, identity governance, cryptographic protection, cloud data security, data loss prevention, security monitoring, incident response, privacy engineering, third-party risk, security metrics, and Zero Trust. A final practical capstone scenario enables participants to integrate the techniques, standards, tools, and best practices covered throughout the five-day program into a comprehensive professional data security approach.

Course Duration

5 Days (40 Hours)

Target Participants

This course is suitable for:

• Data security professionals and cybersecurity practitioners

• Information security officers and security analysts

• Data protection and privacy professionals

• Database administrators and data engineers

• IT professionals responsible for data platforms and infrastructure

• Systems, network, and cloud security professionals

• Risk, compliance, audit, and governance professionals

• Data managers and information governance specialists

• Application and software professionals responsible for protecting organizational data

• Professionals responsible for security monitoring, incident response, and vulnerability management

• IT managers and technical team leaders who require advanced practical data security knowledge

Course Objectives

By the end of the training, participants will be able to:

• Explain core data security principles, threats, vulnerabilities, attack surfaces, and security objectives

• Classify organizational data according to sensitivity, criticality, business value, and protection requirements

• Conduct practical data security risk assessments and identify appropriate security controls

• Apply identity and access management principles including least privilege, RBAC, ABAC, MFA, and privileged access management

• Select and apply appropriate encryption, hashing, tokenization, masking, and pseudonymization techniques

• Protect databases, applications, endpoints, networks, cloud platforms, and analytical data environments

• Apply ISO/IEC 27001, ISO/IEC 27002, NIST Cybersecurity Framework, CIS Controls, COBIT, and Zero Trust principles to data security programs

• Implement practical data loss prevention, monitoring, vulnerability management, and security detection practices

• Participate effectively in data security incident response, investigation, containment, recovery, and lessons-learned activities

• Strengthen data privacy, retention, resilience, third-party security, and regulatory compliance practices

• Develop security metrics, control assessments, improvement plans, and professional data security roadmaps

• Apply advanced data security practices through realistic case studies, exercises, simulations, and a final capstone scenario

Course Content

Day 1: Data Security Foundations, Risk, Threats, and Data Classification

Module: Professional Data Security Foundations and Risk Management

Topics

1. Introduction to Professional Data Security and the Data Protection Lifecycle
2. Data Security Principles: Confidentiality, Integrity, Availability, Authenticity, and Accountability
3. Data Assets, Data Owners, Custodians, Users, and Security Responsibilities
4. Data Classification and Handling Requirements for Sensitive and Critical Information
5. Data Security Threats, Vulnerabilities, Attack Surfaces, and Common Attack Techniques
6. Data Security Risk Assessment, Risk Identification, Analysis, Treatment, and Acceptance
7. Security Controls: Preventive, Detective, Corrective, Compensating, and Recovery Controls
8. Applying ISO/IEC 27001, ISO/IEC 27002, NIST Cybersecurity Framework, CIS Controls, and COBIT
9. Practical Data Security Risk Assessment Exercise and Control-Mapping Workshop
10. Case Study: Assessing Data Security Risks Across a Modern Enterprise Environment

Day 2: Identity, Access Control, Encryption, and Secure Data Handling

Module: Professional Data Protection and Access Management

Topics

1. Identity and Access Management Fundamentals for Data Protection
2. Authentication, Multi-Factor Authentication, Password Security, and Adaptive Access
3. Authorization, Least Privilege, Role-Based Access Control, and Attribute-Based Access Control
4. Privileged Access Management, Service Accounts, Secrets, and Administrative Access
5. Encryption Fundamentals: Symmetric, Asymmetric, Hybrid Cryptography, and Key Management
6. Data at Rest, Data in Transit, and Data in Use Protection Techniques
7. Hashing, Digital Signatures, Tokenization, Masking, and Pseudonymization
8. Secure Data Handling, Data Transfer, Backup Protection, Retention, and Secure Disposal
9. Practical Exercise: Designing Access Controls and Cryptographic Protection for Sensitive Data
10. Case Study: Investigating Excessive Privileges and Unauthorized Access to Critical Data

Day 3: Database, Cloud, Application, Endpoint, and Network Data Security

Module: Professional Security Controls Across Modern Data Environments

Topics

1. Database Security Architecture and Protection of Structured and Unstructured Data
2. Database Authentication, Authorization, Auditing, Activity Monitoring, and Security Hardening
3. Application and API Data Security, Secure Development Practices, and Input Validation
4. Cloud Data Security Across Infrastructure, Platforms, Software Services, and Storage
5. Cloud Identity, Encryption, Key Management, Security Configurations, and Shared Responsibility
6. Endpoint and Network Controls for Protecting Data Access and Data Movement
7. Data Security in Data Warehouses, Data Lakes, Analytics Platforms, and Business Intelligence Systems
8. Vulnerability Management, Security Configuration Assessment, Patch Management, and Secure Baselines
9. Practical Exercise: Performing a Security Assessment of a Database and Cloud Data Environment
10. Case Study: Securing a Hybrid Data Environment Following a Configuration Vulnerability

Day 4: Monitoring, Data Loss Prevention, Incident Response, Privacy, and Resilience

Module: Professional Data Security Operations and Incident Management

Topics

1. Security Monitoring, Logging, Alerting, and Data Security Visibility
2. Security Information and Event Management, Database Activity Monitoring, and Threat Detection
3. Data Loss Prevention, Insider Risk, Unauthorized Data Movement, and Exfiltration Controls
4. Security Vulnerability Monitoring, Threat Intelligence, and Continuous Control Assessment
5. Data Security Incident Identification, Triage, Classification, and Escalation
6. Incident Response: Containment, Eradication, Recovery, and Post-Incident Improvement
7. Digital Evidence, Investigation, Documentation, and Security Incident Reporting
8. Data Privacy, Data Protection Principles, Retention, Minimization, and Regulatory Requirements
9. Business Continuity, Backup Security, Disaster Recovery, Ransomware Resilience, and Recovery Testing
10. Incident Response Simulation: Detecting, Containing, and Recovering from a Sensitive Data Breach

Day 5: Advanced Data Security Governance, Zero Trust, and Professional Capstone

Module: Advanced Data Security Strategy, Governance, and Continuous Improvement

Topics

1. Advanced Data Security Governance, Policies, Standards, Procedures, and Control Ownership
2. Zero Trust Security Principles and Data-Centric Security Architecture
3. Advanced Threat Modeling, Security Architecture Review, and Protection of Critical Data
4. Third-Party, Supplier, Cloud Service Provider, and Data Supply Chain Security
5. Security Automation, Continuous Control Monitoring, Security Orchestration, and Response
6. Advanced Data Security for Artificial Intelligence, Machine Learning, and Emerging Technologies
7. Security Metrics, Key Risk Indicators, Key Performance Indicators, and Executive Reporting
8. Data Security Maturity Assessment, Gap Analysis, Security Improvement Planning, and Roadmaps
9. Practical Capstone Exercise: Designing an Enterprise Data Security Program Using NIST, ISO/IEC 27001, CIS Controls, and Zero Trust Principles
10. Final Case Study and Professional Simulation: Responding to a Multi-Stage Data Security Incident and Presenting a Comprehensive Security Improvement Plan