Sales Analytics & Management System

This project is a comprehensive Sales Analytics and Management System designed to streamline sales data analysis, reporting, and management for businesses. It combines a modern Python-based analytics backend with a user-friendly Streamlit dashboard and a Windows Forms (C#) desktop application for sales operations.

Features

• Data Integration:

  • Loads and merges sales, customer, product, and order data from CSV and PKL files.
  • Connects to SQL databases for robust data management.

• Analytics & Visualization:

  • Interactive dashboards and reports using Streamlit and Altair/Plotly.
  • Key metrics: sales trends, product performance, customer segmentation, and more.

• Desktop Application:

  • Windows Forms (C#) app for managing categories, cities, customers, products, and sales orders.
  • Real-time dashboard and reporting features.

• Extensible & Modular:

  • Easily add new data sources or analytics modules.
  • Clean separation between data, analytics, and UI layers.

Project Structure

• streamlit_app.py — Main Streamlit dashboard for analytics and visualization.
• load_data.py, connect_db.py — Data loading and database connection utilities.
• analysis.ipynb, DataMerge.ipynb — Jupyter notebooks for data exploration and merging.
• SalesSystemApp/ — C# Windows Forms application for sales management.
• data/ — Source data files (CSV, PKL).
• requirements.txt — Python dependencies.
• .gitignore — Excludes venv, cache, and other unnecessary files.

Getting Started

1. Clone the Repository

git clone https://github.com/<your-username>/<your-repo>.git
cd SalesAnalytics

2. Set Up Python Environment

python -m venv venv
venv\Scripts\activate  # On Windows
pip install -r requirements.txt

3. Run the Streamlit Dashboard

streamlit run streamlit_app.py

4. Run the Desktop Application

• Open SalesSystemApp/SalesSystemApp.sln in Visual Studio and build/run the solution.

Data Sources

• Place your CSV/PKL data files in the data/ directory.
• Update database connection settings in connect_db.py as needed.

Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License.