Dimensional Modeling Fundamentals

The name Kimball is synonymous with dimensional modeling. For decades, the Kimball methodology has provided the vocabulary, principles, and best practices for designing analytical data warehouses and business intelligence solutions. Today, these concepts continue to underpin modern cloud data platforms, semantic models, and analytics applications.

An effective dimensional model—or star schema—is the foundation of successful reporting, dashboards, self-service analytics, and performance management. Well-designed dimensional models simplify complex business processes, improve query performance, and provide business users with an intuitive and consistent view of enterprise data.

This half-day learning lab provides a practical introduction to dimensional modeling, covering the complete design process from identifying business processes and defining business metrics to designing fact tables, dimension tables, and star schemas. The session combines foundational concepts with hands-on modeling exercises to explore the core building blocks of dimensional design—including conformed dimensions and slowly changing dimensions—and demonstrates how these techniques can be applied to create scalable, business-friendly analytical models.

Why attend

Attendees will learn:

• The role of dimensional modeling in data warehousing and business intelligence
• Core concepts and terminology of the Kimball dimensional modeling methodology
• How to identify business processes, measures, facts, and dimensions
• Best practices for designing fact tables
• Techniques for designing effective dimension tables
• The purpose and design of conformed dimensions across multiple business processes
• How to model slowly changing dimensions to preserve historical information
• Practical modeling techniques that can be immediately applied to reporting, dashboards, semantic models, and business intelligence solutions