https://github.com/vruddhi18/e-commerce_data_analysis_powerbi_dashboard
The E-Commerce Data Analysis project leverages Power BI to analyze sales and customer insights from Blinkit, Zepto, Myntra, and Flipkart, providing interactive dashboards to enhance e-commerce strategies.
https://github.com/vruddhi18/e-commerce_data_analysis_powerbi_dashboard
data-analysis powerbi
Last synced: 4 months ago
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The E-Commerce Data Analysis project leverages Power BI to analyze sales and customer insights from Blinkit, Zepto, Myntra, and Flipkart, providing interactive dashboards to enhance e-commerce strategies.
- Host: GitHub
- URL: https://github.com/vruddhi18/e-commerce_data_analysis_powerbi_dashboard
- Owner: Vruddhi18
- Created: 2025-02-26T11:31:19.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-21T06:07:16.000Z (about 1 year ago)
- Last Synced: 2025-06-16T23:36:57.080Z (about 1 year ago)
- Topics: data-analysis, powerbi
- Homepage:
- Size: 8.89 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 E-Commerce Website Data Analysis (Power BI)
## 🚀 Overview
This project analyzes data from **four major e-commerce platforms**:
🛒 **Blinkit, Zepto, Myntra, and Flipkart**
Using **Power BI**, the dashboards provide **interactive visualizations** to uncover key insights into **sales trends, customer behavior, product performance, and market trends** across these platforms.
---
## 🔍 Key Insights & Visualizations
### **1️⃣ Sales Performance**
📈 **Dashboard Insights:**
- Total revenue comparison across **Blinkit, Zepto, Myntra, and Flipkart**
- Monthly and yearly **sales growth trends**
- **Revenue breakdown** by product category and brand
### **2️⃣ Popular Products**
🏆 **Dashboard Insights:**
- **Top-selling products** on each platform
- **Best-performing categories** based on revenue and sales volume
- **Customer purchase patterns** for trending items
### **3️⃣ Customer Behavior**
🛍️ **Dashboard Insights:**
- **Order frequency analysis** (Repeat vs. One-time customers)
- **Average cart value** across platforms
- **Customer preference trends** (based on product ratings & reviews)
### **4️⃣ Market Trends**
📊 **Dashboard Insights:**
- **Seasonal demand patterns** (High vs. Low sales periods)
- **Category-wise demand fluctuations**
- **Pricing strategies** and their impact on sales
---
## 🗂️ Dataset Details
The dataset consists of transactional data from:
- **Blinkit** – Online grocery & essentials
- **Zepto** – Quick commerce platform
- **Myntra** – Fashion e-commerce
- **Flipkart** – Multi-category online marketplace
### **Data Includes:**
✅ Order details (Order ID, Date, Customer ID)
✅ Product categories & pricing
✅ Sales figures (Revenue, Discounts, Profits)
✅ Customer demographics & purchasing trends
---
## 📊 Power BI Dashboard Features
🎯 **Comparative analysis** of multiple e-commerce platforms
📌 **Interactive visualizations** with filters and slicers
📈 **Trend analysis & forecasting** for future sales performance
📊 **Custom charts & KPIs** for quick decision-making
Each dashboard is designed to **enhance business intelligence** by providing **clear, data-driven insights** for improving e-commerce strategies.
---
## 📁 File Structure
📂 **Data Folder** – Contains raw datasets used for analysis
📂 **PowerBI_Reports Folder** – Includes Power BI report files (.pbix)
---
## 📌 Screenshots
Below are sample views of the **Power BI Dashboards** for each e-commerce platform:
🖼️ **Blinkit Dashboard**
![Blinkit Dashboard]
🖼️ **Zepto Dashboard**
![Zepto Dashboard]
🖼️ **Myntra Dashboard**
![Myntra Dashboard]
🖼️ **Flipkart Dashboard**
![Flipkart Dashboard]
---
## 🏆 Conclusion
This project demonstrates how **Power BI can transform raw data into actionable insights** for e-commerce platforms. By analyzing **sales, customer behavior, and market trends**, businesses can **make data-driven decisions** to improve performance.
📧 Feel free to reach out for any queries or suggestions! 🚀