Data Modeling in Power BI 101

Overview:

Unlike many traditional reporting tools, Microsoft Power BI is a model-driven platform. That means the quality of your reports depends heavily on how well you structure your data model.

To build effective reports, you need to understand your data—deciding which columns belong together in the same table and which should live in separate tables.

In this session, you’ll be introduced to the core concepts of data modeling and how they specifically apply in Power BI. We’ll cover tables and relationships, primary and foreign keys, normal forms, and dimensional modeling.

By the end, you’ll have a solid foundation in data modeling principles—and a practical starting point to design and build your own robust Power BI data models.

Why you should Attend:

Because without solid data modeling skills in Microsoft Power BI, you’re risking:

• Reports that break when new data is added
• Measures that return inconsistent or incorrect results
• Sluggish dashboards that frustrate stakeholders
• Duplicate logic scattered across visuals
• A semantic mess no one else can maintain
• Embarrassing “why doesn’t this total match?” moments in meetings

Bad modeling doesn’t just slow performance — it destroys trust in your numbers.

In this session, you’ll learn the fundamentals that prevent costly mistakes, rework, and credibility loss — before they become visible to your boss or your clients.

Don’t let weak data modeling silently sabotage your analytics.

Areas Covered in the Session:

• Tables
• Primary Keys
• Foreign Keys
• Normal forms
• Dimensional modelling
• Kimball, Inmon
• Anti-Patterns

Who Will Benefit:

• People who (start to) work with Power BI