E-Commerce Sales Analysis

End-to-end data analysis project using SQL, Python, and Tableau to analyze e-commerce

Tools Used

• SQL (MySQL)

• Python (Pandas, Matplotlib)

• Tableau

  Dashboard Preview

Project Goals

• Analyze sales trends
• Identify top performing categories
• Understand order status distribution
• Visualize revenue across regions

Dataset

E-commerce sales dataset containing:

• Order ID
• Category
• Revenue
• Order Status
• Ship State
• Date

Analysis Steps

SQL

• Revenue by category
• Revenue by state
• Monthly revenue
• Rolling average revenue

Python

• Data cleaning
• Exploratory data analysis
• Visualization

Tableau Dashboard

The dashboard includes:

• Sales over time

• Revenue by category

• Revenue map by state

• Order status distribution

• Sales by state

• Key Insights

• Set category generated the highest revenue

• Maharashtra produced the largest share of total sales

• Most orders were successfully shipped

• Revenue peaked in April before declining slightly

Repository Structure

ecommerce-sales-analysis │ ├── clean_sales.csv.zip ├── SQL_queries.sql ├── data_cleaning.ipynb ├── tableau_dashboard.png └── README.md

Author

Alfred Quenum Data analysis project using SQL, Python, and Tableau.