Authors: Ajay Kumar Kota
Abstract: In the pharmaceutical industry, data complexity and fragmentation pose significant challenges to delivering unified, actionable insights. Traditional single-fact table models in Power BI often fall short when integrating data from multiple domains such as sales, prescriptions, marketing, and clinical operations. This article explores the strategy and implementation of multi-fact table modeling in Power BI, a powerful approach to unify diverse datasets while preserving analytical integrity and granularity. We examine the architecture of multi-fact models, the challenges of schema design and granularity alignment, and the importance of shared dimensions and bridge tables. The article also delves into advanced DAX techniques for managing filter contexts, optimizing performance, and delivering accurate KPIs across disparate data sources. A real-world pharmaceutical case study is included to illustrate practical applications and business impact.
DOI: https://doi.org/10.5281/zenodo.16024582
