An end-to-end Power BI analytics solution designed to optimize the middle mile for logistics providers.
The project integrates 17 operational data sources to deliver a unified view of fleet performance, operating costs, and customer profitability, enabling data-driven decisions across operations, finance, and commercial teams.
Logistics organizations often lack a consolidated view of how fuel, maintenance, asset utilization, and customer contracts interact to drive true profitability.
This project addresses that gap by connecting operational and financial data into a single analytical model.
Which trucks are high-cost and underutilized, and should be considered for retirement?
Which customers and routes generate high volume but low margin?
How does fuel efficiency (MPG) vary across trucks and drivers?
Where do maintenance costs indicate potential reliability risks?
Executive dashboard for revenue, cost, and profitability monitoring
Quadrant analysis using Cost per Mile vs. Revenue per Mile
Dynamic fleet-wide benchmarks to identify operational outliers
Asset-level analysis combining fuel, maintenance, and utilization data
Star schema data model (6 fact tables, 11 dimension tables)
Power Query (M) for modular, parameter-driven data ingestion
Advanced DAX for KPI calculation and dynamic benchmarking
Optimized for performance and analytical flexibility
An end-to-end Power BI business intelligence solution transforming raw "Adventure Works" data into actionable executive insights.
This project features a dual-Page interactive report designed for regional performance tracking and deep-dive customer segmentation
Segment Value: Which customer occupations provide the highest average revenue?
Regional Disparity: Why are specific territories underperforming in margin despite meeting sales targets?
High-Value Risk: Which of our top 10 revenue-generating customers are currently our lowest margin performers?
Star schema Optimization: Designing a high-performance normalized data model for enterprise scalability.
Portable ETL (M-Query): Decoupling transformation logic via parameters and standalone scripts for easier deployment.
Contextual Drill-Through: Engineering seamless navigation paths between high-level maps and detail pages.
Management by Exception: Using conditional formatting and top/bottom rankings to highlight business risks.
Mobile-Responsive Design: Building a dedicated, thumb-optimized layout specifically for on-the-go leadership.
Senior-level Power BI suite for commercial profitability.
Features dynamic pricing simulations (What-If), Pareto 80/20 analysis, and Star Schema modeling to identify margin leakage and support strategic decision-making
Product Concentration: Which 20% of our products generate 80% of our total profit?
Profitability Leakage: Where is high sales volume failing to convert into net margin due to costs or discounts?
Pricing Impact: How will a 5% price adjustment impact our bottom-line profit?
Growth Quality: Is our year-over-year revenue growth being driven by new or returning customers?
Discount Effectiveness: At what specific threshold does discounting start to destroy product value rather than drive volume?
Pareto (80/20) Modeling: DAX ranking and cumulative totals to identify high-value products.
What-If Parameters: Dynamic scenario planning for price and discount simulations.
Time-Intelligence: YoY and YTD growth calculations using customer Calendar logic.
Statistical Segmentation: Identifying New vs. Returning customer revenue streams.
Complex DAX Iterators: Utilizing SUMX and CALCULATETABLE for granular commercial logic.
Each project in this portfolio is designed with a real business stakeholder in mind - focusing not only on insights, but on decisions and actions