📊 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.

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🗂️ 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.

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🧰 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)

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🔍 Key Analysis Performed

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

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📊 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.

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🚀 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