This project focuses on transforming raw sales data into a meaningful and interactive dashboard using Python for cleaning and Power BI for visualization. It provides a comprehensive overview of sales performance, customer behavior, regional trends, and product/channel performance.
- Source: Excel file with 6 sheets
- importing necessary libs
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- Combined 4 sheets into a single dataset
- Cleaned nulls, renamed columns, standardized formats
- Feature engineered fields (Profit Margin %, Revenue per Order etc) 1image alt
- EDA for insights(some the many are shown below)
- Exported cleaned file
Created an interactive 4-page dashboard:
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Page 1 – Summary (Home) Overview of dashboard sections with navigation
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Page 2 – Executive Overview Key KPIs: Revenue, Orders, Profit Margin %, RPO Monthly trends, top/bottom products, region-wise sales
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Page 3 – Product & Channel Performance Deep dive into product performance and sales by channel
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Page 4 – Customer & Region Analysis Customer count, behavior, and map-based regional sales insights
Raw Excel Data (6 sheets)
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Python (Pandas) Cleaning & Merging
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EDA + Export Cleaned File
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Power BI Dashboard (4 Pages)
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Download the Repository
- Clone the repo or download as ZIP
- Locate the Power BI file:
SalesDashboard.pbix
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Open in Power BI Desktop
- Double-click
.pbixfile - Wait for visuals to load
- Double-click
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(Optional) Run Python Script
- Python script
/scriptsfolder - It reads the 4 Excel sheets → cleans → merges → outputs
- Python script
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Interact with the Dashboard
- Filter by Region, Channel, Month, Year
- Navigate across 4 dashboard pages
- Python (pandas, matplotlib)
- Power BI
- Excel
Created by \Nikhil Chauhan as part of a portfolio project. Inspired by real-world sales dashboard use cases
MIT License – free to use with attribution.