Developed a high-fidelity, two-page Power BI intelligence suite to analyze $899.90M in US retail revenue. The project transitioned raw transactional data into an interactive executive tool focused on identifying regional profit leakage and optimizing product mix. Key Contributions: AI-Driven Root Cause Identification: Implemented a Decomposition Tree to allow stakeholders to drill down from total sales ($899M) into specific regions, retailers, and product categories to find performance drivers. Advanced Spatial Analytics: Leveraged Bubble Maps to visualize market density across US cities, identifying top-performing states and regional sales clusters. Custom Financial Engineering: Authored complex DAX measures for Operating Margin %, Profit per Unit, and Sales Velocity to assess merchandising efficiency at a granular level. Glass UI/UX Design: Engineered a dark-themed, app-style interface featuring synced cross-page navigation and conditional formatting (Data Bars) to reduce cognitive load for executive users. Technical Stack: Power BI Desktop, DAX (Data Analysis Expressions), Data Modeling, Advanced Visualization, Retail Strategy Analysis.