Data governance is about the convergence of data quality, data management, data policies, business process management, and risk management around the handling of data within an organization. Data governance can create great value for the entire organization as it generates more transparency, availability, and security in the decision-making process. To achieve this, it is crucial to understand how the vast amounts of data available can be stored, managed, and protected properly.

In the program, we will focus on data governance and its importance in an organization, both from a theoretical and a practical perspective.

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

• Demonstrate an understanding of hardware and software and their place in management information systems.
• Recognize the primary benefits of information systems in organizations including the application of customer relationship management (CRM), enterprise resource planning (ERP), and enterprise application integration (EAI).
• To assess the quality of data and be aware of any benefits and challenges.
• Gain insight into the role of data security
• Understand the strategic potential of data governance.
• Understand the threats and opportunities and learn to protect data in the most effective way.
• Demonstrate an understanding of the crucial role information security management plays within organizations and its role most MIS activities.

CONTENT

Foundations of Data Governance

• Drivers of Data Governance
• Data as an Asset
• Data Governance and Data Management
• Data Quality and Risk
• Data Governance Organization and Structures
• Data Governance Frameworks
• Data Governance Implementation

Foundations of Data Security

• Introduction: Creating Awareness through Examples of Real-Life Security Incidents
• Types of (Cyber) Attacks (e.g. Social Engineering, Phishing, Denial of Service, Web-Based Attacks)
• Protection of Confidential Information
• Basic Concepts of Cryptographic Methods and Applications
• Basic Concepts of Access Control

Data Governance from the Viewpoint of Public Administration

• Data Strategy – including Showcase: Data Excellence Strategy of the City of Vienna
• Organizational and Technical Implementation
• Data Governance Organization
• Data Governance Framework
• Data Governance Maturity Model
• Benefits and Challenges

Trends in Data Governance: Enterprise Perspective

• Data Governance in Enterprises

• Challenges in Enterprise Data Management
• Importance of Data Quality Management
• Introduction to Metadata Management
• What is Semantic Data Management?
• What is a Knowledge Graph?
• Applications and Use Cases based on Semantic AI

Training Methodology

The training methodology combines lectures, discussions, group exercises and illustrations. Participants will gain both theoretical and practical knowledge of the topics. The emphasis is on the practical application of the topics and as a result participant will go back to the workplace with both the ability and the confidence to apply the techniques learned to their duties.