Exploratory Data Analysis (EDA) with SQL

Project Overview

This project showcases the use of SQL to perform Exploratory Data Analysis (EDA) on a sales dataset.

The aim is to clean, explore, and analyze data to uncover patterns, trends, and business insights that support better decision-making.

️ Tools & Technologies

SQL (T-SQL)

Relational Database (SQL Server)

Dataset: Customers, Products, Sales

Key Steps in Analysis

Database Exploration → Listing tables, schemas, and columns.

Dimensions Exploration → Extracting unique categories, products, and customer demographics.

Date Range Exploration → Finding first/last orders, total sales duration, and customer ages.

Measures & Metrics → Total sales, quantity, orders, average price, number of products and customers.

Magnitude Analysis → Revenue by category, customers by country/gender, revenue per customer.

Ranking Analysis → Top/Bottom products, top customers, least active customers.

Insights & Results

Identified top-performing products and low-performing products.

Highlighted top 10 customers driving revenue.

Revealed sales trends by category and country.

Discovered average costs per category and customer distribution.