📊 Superstore SQL Analysis

Project Overview

This project analyzes the Superstore sales dataset using MySQL. The objective is to answer business questions and extract meaningful insights using SQL.

Tools Used

• MySQL Workbench
• SQL
• GitHub

Database

• Database: "superstore"
• Table: "superstore_data"

Business Questions Solved

• Total Sales
• Total Profit
• Top 10 Products by Sales
• Top 10 Customers by Sales
• Most Profitable State
• Average Sales by Region
• Least Profitable Products
• Most Profitable Products
• Top 10 Cities by Sales
• Top 10 Sub Categories by Sales
• Customers with the Most Orders
• Category with Highest Average Profit

SQL Concepts Used

• SELECT
• WHERE
• GROUP BY
• ORDER BY
• LIMIT
• SUM()
• AVG()
• COUNT()

Key Insights

• California generated the highest total profit.
• Technology had the highest average profit.
• Phones was the top-selling sub-category.
• New York generated the highest sales among cities.
• Sean Miller was the highest-value customer by sales.
• William Brown placed the most orders.

Author

Devansh Srivastava