🛒 Project: E-Commerce Metrics Platform

This project is a simplified simulation of an E-Commerce Metrics Platform, inspired by large-scale systems like Google Shopping. The platform ingests, processes, and analyzes e-commerce data to generate meaningful insights for merchants, such as sales trends, top-performing products, and customer feedback summaries.

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📖 Features

• Data Generation: Mock datasets for products, merchants, sales, and customer reviews.
• Data Ingestion: Loading data into a PostgreSQL database using Python.
• Data Processing: SQL pipelines for generating business-critical metrics.
• Metrics Examples:
  • Total sales per merchant.
  • Top-selling products.
  • Revenue trends over time.
  • Average product ratings.
• Scalability: Designed to handle large-scale data simulations.
• Future Plans:
  • Dashboard for visualizing metrics.
  • Advanced data pipelines with C++ for efficiency.
  • Integration with APIs for real-time metrics retrieval.

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🛠️ Technologies Used

• Languages: Python, SQL
• Database: PostgreSQL
• Libraries:
  • pandas: For data manipulation.
  • sqlalchemy: For database interaction.
  • Faker: For generating mock data.
• Tools:
  • Docker: For containerized database setup.
  • GitHub: For version control.

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📂 Directory Structure

ecommerce-metrics/
├── data/           # Contains generated mock datasets (CSV files)
├── scripts/        # Python scripts for data ingestion and processing
├── dashboard/      # Placeholder for visualization components
└── README.md       # Documentation for the project