A complete end-to-end Excel Data Analysis Project designed for Global E-Commerce Inc.
This project covers Business Understanding → Data Cleaning → KPI Analysis → Dashboard Development → Insights → Final Report.
This repository includes the *Interactive Excel Dashboard, **Business Problem Document, and the *Final Project Report PDF.
Global E-Commerce Inc. is experiencing challenges in understanding overall business performance across
regions, product categories, customer segments, and payment methods. Management wants clarity on:
- Why profit margins vary across categories
- Which regions generate the most profit
- How discount strategies are influencing profitability
- Customer purchasing behavior and preferred payment modes
- Delivery performance and operational efficiency
To address these issues, the company requires an interactive Excel dashboard capable of providing actionable insights for data-driven decisions.
📄 The “Business Problem” PDF is included in this repository.
- Total Sales
- Total Profit
- Total Orders
- Average Discount
- Average Delivery Days
- Region
- Category
- Month
- Payment Method
- Customer Segment
- Monthly Sales Trend
- Profit by Region
- Sales vs Profit by Category
- Customer Segment Share
- Payment Method Share
- Profit vs Discount Analysis
- Top 10 Products by Sales
- 💰 Total Sales: ₹6,66,606.21
- 📈 Total Profit: ₹1,33,862.72
- 📦 Total Orders: 500
- 💸 Average Discount: 8.13%
- 🚚 Average Delivery Days: 4.13 Days
- 🏆 South Region generates the *highest profit, followed by the *East.
- 💼 Technology and Furniture categories lead in revenue & profit.
- 🧑💼 Home Office (42%) is the most profitable customer segment.
- 💳 Most customers prefer Cash (27%) and PayPal (24%) payments.
- 🛒 Laptops, Chairs, and Pens dominate the Top 10 product sales.
- 📉 Discounts between 5–10% result in the best profit margins.
| File Name | Description |
|---|---|
| Ecommerce_Raw_Data.xlsx | Original dataset used for cleaning & analysis |
| Global_Ecommerce_Sales_Analysis.xlsx | Final interactive Excel dashboard |
| Dashboard_Screenshot.png | Dashboard preview image |
| Business Problem.pdf | Detailed business problem statement |
| Global E-Commerce Sales Analysis Report.pdf | Full project analysis report (PDF) |
| README.md | Project documentation |
The PDF report includes:
✔ Business Problem
✔ Dataset Overview
✔ Data Cleaning Steps
✔ Exploratory Data Analysis
✔ KPI Interpretation
✔ Dashboard Results
✔ Final Insights & Recommendations
📄 The full project report is included in the repository.
- Microsoft Excel
- Pivot Tables
- Pivot Charts
- Slicers & Timeline
- Data Cleaning
- SUMIFS, IF, VLOOKUP, COUNTIF, etc.
- Conditional Formatting
- Download the Excel files from the repository.
- Open Global_Ecommerce_Sales_Analysis.xlsx.
- Use slicers to explore sales across regions, months, categories, and segments.
- Read the Business Problem and Final Report for complete understanding.
This project demonstrates how Excel can be used to:
- Track and analyze sales performance
- Identify profitable categories & regions
- Optimize discount strategies
- Understand customer behavior
- Improve business decision-making
An excellent portfolio project for Data Analyst, Business Analyst, and BI roles.
👤 Harsh Belekar
📍 Data Analyst | Python | SQL | Power BI | Excel | Data Visualization
📬 LinkedIn | 🔗GitHub
⭐ If you found this project helpful, feel free to star the repo and connect with me for collaboration!