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📊 Regional Sales Analysis using Python & Power BI

This project showcases end-to-end analysis of a Regional Sales Dataset, using Python for exploratory data analysis (EDA) and Power BI for building a professional business dashboard.

🗂️ Project Overview

The main objectives of this project are to:

  • Clean and analyze regional sales data using Python
  • Identify patterns and key performance metrics
  • Visualize insights using an interactive Power BI dashboard

This project demonstrates how Python and Power BI can work together to convert raw data into actionable business insights.

🧰 Tools & Technologies Used

  • Python (Google Colab / Jupyter Notebook)
    • Pandas for data manipulation
    • Matplotlib and Seaborn for data visualization
  • Power BI for dashboard creation
  • Dataset format: .xlsx (Excel)

🔍 Key Analysis Performed

  • 📅 Monthly and Regional Sales Trends
  • 🧾 Top Performing Products
  • 🧑‍🤝‍🧑 Customer Orders & Value Distribution
  • 📈 Channel & Distributor-wise Contribution
  • 📊 Revenue & Order Volume Correlation

📊 Power BI Dashboard

The dashboard built in Power BI contains:

  • Sales KPIs
  • Regional performance comparisons
  • Channel/distributor breakdowns
  • Visual trends and insights

📁 File: Regional_Sales_Dashboard.pbix (Upload this if not already done)

🧠 Note: The .pbix file can be opened with Power BI Desktop.

🚀 How to Use

  1. Open the notebook regional_sales_analysis.ipynb in Google Colab or Jupyter Notebook
  2. Upload the dataset: Regional Sales Dataset.xlsx
  3. Install any required packages (if needed): 
    !pip install pandas seaborn matplotlib openpyxl