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Retail Inventory Management and Forecasting

A comprehensive web-based application designed to manage retail inventory efficiently and forecast future demand trends. This project leverages advanced data analytics and a user-friendly interface to streamline inventory processes for retailers.

Features

  • Inventory Management: Track stock levels, update inventory details, and monitor stock movements.
  • Forecasting: Predict future inventory needs based on historical sales data using advanced algorithms.
  • Interactive Dashboard: Visualize inventory and forecasting insights through an intuitive interface.
  • Multi-user Support: Secure login system for multiple users with role-based access.
  • Dynamic Visualizations: Integrated Power BI reports for in-depth data analysis.

Technologies Used

  • Backend: Python (Flask framework)
  • Frontend: HTML, CSS, JavaScript
  • Forecasting: Machine learning libraries in Python
  • Data Visualization: Power BI for interactive dashboards
  • Database: SQLite (or specify your database if different)

Installation and Setup

  1. Clone the repository:

    git clone https://github.com/your-repository-link.git
    cd retail-inventory-management
  2. Set up a virtual environment:

    python -m venv env
    source env/bin/activate  # For Windows: env\Scripts\activate
  3. Install dependencies:

    pip install -r requirements.txt
  4. Run the application:

    python app.py
  5. Access the application: Open your browser and navigate to http://127.0.0.1:5000.

Power BI Dashboard

Explore the interactive dashboard here: Retail Inventory Dashboard

image

Future Enhancements

  • Integration with external APIs for real-time sales data.
  • Advanced forecasting models using deep learning.
  • Mobile app version for on-the-go inventory management.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes.

License

This project is licensed under the MIT License.