HESHAM22155/Supply-Chain-Analysis-Depi

Supply Chain Data Analysis project developed as part of the Digital Egypt Pioneers Initiative (DEPI). The project analyzes supply chain data using Python and data visualization tools to generate insights about logistics performance, delivery efficiency, and product demand. # 📦 Supply Chain End-to-End Analytics > A comprehensive, multi-layer data analytics solution that transforms fragmented supply chain data into strategic business intelligence — from raw data engineering to executive-level dashboards and predictive insights. --- ## 🧠 Business Problem Modern supply chains generate vast amounts of transactional data across orders, shipments, customers, and products. Without a structured analytical framework, this data remains siloed and underutilized, leaving critical questions unanswered: - Which markets and customer segments are driving the most revenue? - Why are more than half of all deliveries arriving late? - Which product categories yield the highest profit margins? - Are revenue trends stable, growing, or declining over time? This project addresses these challenges by building a production-grade analytics pipeline — from a normalized star schema in SQL Server to Python-powered EDA. --- ## 🏗️ Project Architecture > **Workflow:** Raw Data → SQL Cleaning → Star Schema → Excel Dashboard → Power BI Insights → Python EDA | Layer | Tool | Audience | |---|---|---| | **1. Data Engineering** | SQL Server | Data Engineers / Architects | | **2. Operational Monitoring** | Excel | Operations Managers | | **3. Strategic Intelligence** | Power BI | Executives / Leadership | | **4. Advanced Analytics** | Python | Data Analysts / Scientists | --- ## 🗄️ 1. SQL Data Engineering Layer **🎯 Objective:** Design a scalable star schema data warehouse optimized for analytical queries. * **Work Done:** Data Cleaning (NULLs, duplicates), Star Schema Design, and ETL Preparation. * **📁 Source Code:** View SQL Queries & Scripts --- ## 📊 2. Excel Dashboard Layer **🎯 Objective:** Build an interactive operational dashboard for day-to-day KPI monitoring. * **Features:** Revenue analysis, Cost vs Profit tracking, and Delivery efficiency with Interactive filters. --- ## 📈 3. Power BI Dashboard Layer **🎯 Objective:** Deliver an executive-le …