Mohmmed-Ibrahem11/Uber-Data-Warehouse-Pipeline

An enterprise-grade End-to-End Data Warehouse and Analytics pipeline for Uber operations in Egypt using SQL Server and Power BI. # 🚖 Uber End-to-End Data Warehouse & Analytics Pipeline ## 🌟 Project Overview An enterprise-grade Data Warehouse project simulating Uber ride-sharing operations in Egypt. Developed a complete pipeline from a 3NF normalized ERD system into a highly optimized Star Schema using SQL Server and Power BI to uncover operational insights and track driver fraud. ## 🏗️ Architecture & Modeling - **Source Database Schema (`Work_In_Uber`):** 3NF normalized transactional database capturing raw application data (Drivers, Customers, Vehicles, Locations, and Trips). - **Analytics Schema (`Analytics_In_Uber`):** Dimensional model (Star Schema) optimized for fast analytical queries and corporate reporting. - **SCD Type 2 Implementation:** Tracked driver history and vehicle modifications dynamically over time using automated row validity dates (`Row_Start_Date`, `Row_End_Date`). - **Junk Dimension:** Consolidated low-cardinality trip statuses and cancellation reasons into a centralized `Dim_Trip_Status_Junk` table for cleaner storage. ## 🛠️ Tech Stack & Skills Demonstrated - **Database Architecture:** Advanced SQL Server (SSMS), schemas isolation, constraints enforcement, and explicit IDENTITY processing. - **Data Modeling:** Star Schema design, Junk Dimensions, Role-Playing Dimensions (Date variations). - **ETL Pipelines:** Programmatic and dynamic data movement, conditional flagging for driver price violations, and peak hours classification. - **BI & Analytics:** Power BI semantic layer linking, advanced DAX measures, dynamic dashboard visualization, and custom branding templates. ## 📊 Analytical Insights & Advanced DAX - **Total Revenue & Trips:** Monitored baseline platform performance across different regions. - **Driver Price Violations Flag 🚩:** Created custom logic to instantly catch and flag active price fraud where actual fare exceeded estimated boundaries. - **Peak Operational Hours Analysis:** Programmed business hours logic to classify peak operational efficiency withi …