This talk addresses the essential role of data models in analytics, especially for lean teams. It caters to a broad audience, from beginners creating reports to those integrating diverse datasets for advanced analytics and KPI development. A robust data model is crucial for rapidly scaling analytics efforts, allowing for the inclusion of varied data sources such as research awards and proposals, HR data (Gender, ranks, titles, ethnicity etc.), teaching loads, and external datasets like the HERD Survey. We will cover data modeling basics, then explore advanced analytics with the Microsoft Analytics Stack, focusing on Power BI Desktop, emphasizing its accessibility and capability for comprehensive insights. Including an introduction to Microsoft Data Analysis Expressions (DAX) and Time Intelligence Functions. Discover how effective data models enhance analytics capabilities, enabling teams to achieve significant research outcomes.