How Bad Data Models Can Sabotage Your Reports

In this episode, Brick and Caleb discuss the critical role of good data models in making business intelligence tools like Power BI efficient and scalable. They cover the pitfalls of poor data models, including delayed reporting and data category issues, and offer insights into designing flexible, transactional-level data models that can grow with your business needs.
Key Moments:
1:20 - Example of a Bad Data Model
3:31 - The Benefits of Transactional-Level Data
5:17 - Why Developers Take Shortcuts
7:18 - Common Data Model Mistakes
Blue Margin increases enterprise value for PE-backed, mid-market companies by serving as their fractional data team. We advise on, build, and manage data platforms. Our strategy, proven with over 300 companies to-date, expands multiples through data transformation, as presented in our book, The Dashboard Effect.
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[@kappasigGSU]

Love it guys. Would also like to see a future talk on what makes a good semantic model from a business user perspective rather than just performance. How should a semantic dataset differ from a Gold lakehouse for instance? And do you get the business involved in designing the data model?