retail-sales-analytics

🛒 Retail Sales Analytics Pipeline

A comprehensive end-to-end data analytics pipeline processing 475,000+ retail transactions using Python, SQL, and interactive web technologies.

🌐 Live Demo

👉 View Interactive Dashboard

✨ Features

• 📊 Data Generation: Creates 500K+ realistic retail transactions
• 🔄 ETL Pipeline: Automated data cleaning and transformation
• 💾 Database: SQLite with optimized indexes
• 🧮 SQL Analytics: CTEs, window functions, complex joins
• 📈 Visualizations: 8 professional charts (Matplotlib/Seaborn)
• 🌐 Interactive Dashboard: Web-based dashboard with Plotly.js
• 💼 Power BI Ready: Pre-processed export files

🚀 Quick Start

# Clone the repository
git clone https://github.com/Jin02420/retail-sales-analytics.git
cd retail-sales-analytics

# Install dependencies
pip install -r requirements.txt

# Run the pipeline
run_pipeline.bat

# Open dashboard.html in your browser

📊 Tech Stack

• Python 3.12 - Core language
• Pandas & NumPy - Data manipulation
• SQLite - Database management
• Matplotlib & Seaborn - Static visualizations
• Plotly.js - Interactive charts
• Faker - Synthetic data generation

📈 Project Highlights

• 💰 Total Revenue: $322.9M analyzed
• 📊 Total Profit: $112.8M calculated
• 📉 Profit Margin: 34.9% average
• 🛒 Transactions: 475,352 processed
• 👥 Customers: 50,000 unique
• 📦 Products: 1,000 items

🎯 Skills Demonstrated

• Python programming & scripting
• SQL database design & optimization
• ETL pipeline development
• Data analysis & visualization
• Business intelligence
• Web development (HTML/CSS/JavaScript)
• Version control with Git

📁 Project Structure

src/ ├── 01_data_generation.py # Generate synthetic data ├── 02_etl_pipeline.py # ETL processes ├── 03_sql_analytics.py # SQL analysis ├── 04_visualization.py # Create charts └── 05_power_bi_export.py # Export for Power BI

👤 Author

Jin02420 - GitHub Profile

📄 License

MIT License

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