📌 Today's e-commerce giants operate with large and complex data structures.
In this project, I analyzed the data models of Amazon, Trendyol, and HepsiBurada, and developed an optimized, scalable, and unified relational database model.
✅ Analysis of Existing Systems – Reviewed the data requirements of Amazon, Trendyol, and HepsiBurada, identifying common and platform-specific features.
✅ EER Diagrams – Created detailed Entity-Relationship (EER) models for each platform.
✅ Unified and Optimized Model – Merged shared data structures into a scalable and modular unified model.
✅ SQL Implementation – Developed the final model as a relational database schema using DDL (Data Definition Language) scripts.
✅ Testing and Sample Data – Added sample datasets and executed queries for realistic testing scenarios.
Main components identified through detailed analysis for each platform:
- 👥 Users (Customers & Sellers)
- 🛍️ Product & Inventory Management
- 🛒 Shopping Cart System
- 📦 Orders & Order Items
- 💳 Payments & Promotions
- 🚚 Shipping & Logistics Management
- ⭐ Reviews & Ratings
Separate EER diagrams were created for each platform:
All Tables PDF
🔍 Goal: Analyze similarities and differences in the data models of each platform.
Common features from Amazon, Trendyol, and HepsiBurada were combined into a single unified model.
Unique structures were preserved to create a flexible and scalable design.
📄 Fully Integrated Model: ECommerceCombined_EER.pdf
The EER model was converted into a relational database schema and coded using DDL commands.
📜 SQL Scripts:
- 🏗️ Create Tables → Contains table definitions and constraints.
- 📊 Insert Sample Data → Provides sample data for testing.
📄 📘 Database Report → Detailed explanation of design process, decision-making, and optimizations.
📄 📑 EER-to-Relational Mapping Steps → Step-by-step guide for mapping EER models to relational schemas.
This project provides an integrated and optimized database model for large-scale e-commerce systems.
The model simplifies cross-platform data management while ensuring scalability and efficiency.
📌 You can explore all details through the documentation and SQL script files linked above.