Data Modeling & Ontology Design

Structure Your Organization's Knowledge for AI Readiness

Bridge the gap between raw data and organizational wisdom in this transformative session that combines theoretical foundations with immediate practical application. Building on our Data Catalog experience, we discover how formal data modeling creates the structured representations that both humans and AI systems need to interpret information consistently. 

Learn how ontology design - the architectural blueprint of knowledge systems - enables organizations to move beyond simple data storage to creating interconnected knowledge ecosystems where relationships between entities become as valuable as the data itself.

Through practical exercises, we'll identify the key entities in our business domain, define their essential attributes, establish meaningful hierarchies, map complex relationships, and implement constraints that maintain data integrity. 

The session transitions seamlessly from conceptual learning into a hands-on modeling workshop where we'll apply these principles to create a knowledge graph representing our organizational domain, laying the groundwork for advanced AI applications that can reason with business knowledge.

Essential for leaders who recognize that tomorrow's competitive advantage comes not just from collecting data, but from structuring it in ways that unlock its full potential.

• Outline
• Data Modeling Fundamentals
• Ontology Design: Modeling Knowledge Graphs
• Entities
• Attributes
• Hierarchy
• Relationships
• Constrains

• Format
• This is a mixed session. It starts as a lecture to introduce the relevant background, and then we move to a hands-on data modeling lab.

• Level
• Intermediate

• Prerequisite Knowledge
• Data Governance
• Governing Data with a Data Catalog

• Learning Outcomes
• Knowledge of data modeling principles. Experience in ontology design.