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

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.