Titus for Data Classification Course Overview

To ensure a successful learning experience in the Titus for Data Classification course, participants should have the following minimum prerequisites:

• Basic understanding of data management principles and concepts.
• Familiarity with information security and data protection best practices.
• Knowledge of compliance and privacy regulations relevant to data security (e.g., GDPR, HIPAA, etc.).
• Experience with using computers and navigating software applications.
• Comfortable with operating in a Windows-based environment, as many data classification tools, including Titus, are often demonstrated in this context.
• Ability to understand and follow written and spoken instructions in English.

Please note that while prior experience in data classification is beneficial, it is not a strict requirement for this course. The program is designed to guide participants through the foundational aspects and build up to more advanced topics.

Target Audience for Titus for Data Classification

1. The Titus for Data Classification course equips professionals with strategies and policies for effective data management and security.

   
   

2. Target audience for the course includes:

   
   

• IT Security Managers
• Data Protection Officers
• Compliance Officers
• Risk Managers
• Information Security Analysts
• System Administrators
• Network Administrators
• IT Consultants
• Security Architects
• Data Governance Experts
• CIOs/CTOs and IT Executives
• IT Auditors
• Cybersecurity Professionals
• Data Analysts
• Software Developers (focused on security solutions)
• Database Administrators
• Cloud Security Specialists
• Legal Professionals (interested in data privacy and compliance)

Learning Objectives - What you will Learn in this Titus for Data Classification?

Introduction to the Course's Learning Outcomes

The Titus for Data Classification course equips learners with in-depth knowledge and practical skills for implementing effective data classification strategies using the Titus platform, enhancing data security, and ensuring compliance.

Learning Objectives and Outcomes

• Gain a comprehensive understanding of the Titus Data Classification Platform, its architecture, and security features.
• Learn the benefits and processes of data classification, as well as deployment strategies and best practices using Titus.
• Understand different types of data classification, their strategies, techniques, and the role of machine learning in automating these processes.
• Develop the ability to establish, implement, and manage robust data classification policies and rules that align with organizational data governance.
• Master the creation of automated data classification workflows, leveraging machine learning to optimize data classification and governance.
• Acquire skills for monitoring, auditing, and reporting on data classification compliance, addressing challenges, and ensuring data privacy and security.
• Enhance knowledge about data classification tools, techniques, and their integration with other security solutions to protect sensitive information.
• Learn to manage data classification at various levels and categories, understanding the implications for risk management and regulatory compliance.
• Understand the advanced features and capabilities of the Titus platform, including advanced data protection strategies and troubleshooting.
• Prepare for real-world application with best practices for automating data classification for compliance requirements, data loss prevention, and data governance.