Retail Sales Analysis – SQL + Tableau

Project Overview

This project analyzes retail sales data to uncover insights into customer behavior, product performance, and store revenue.
I used SQL to clean, join, and prepare the dataset, and Tableau to build an interactive dashboard for data visualization.

The dataset contains four tables:

• Customers – customer demographics and join dates
• Stores – store details including city and region
• Products – product categories, unit price, and cost price
• Transactions – sales transactions with quantities purchased
• The raw dataset downloaded from Kaggle

Key SQL Steps

• Performed multiple joins between customers, stores, products, and transactions
• Calculated Net Sales = quantity * unitprice
• Calculated Profit = (unitprice - costprice) * quantity
• Aggregated metrics by region, city, product category, and customer segment

Tableau Dashboard

The Tableau dashboard provides:

• Sales by Region and City
• Top Customers by Revenue
• Product Category Performance
• Trend Analysis over Time

👉 -check it out in Tableau Portfolio

Tools Used

• SQL (joins, aggregations, profit/revenue calculations)
• Tableau (interactive dashboard, KPIs, maps, trend analysis)
• Excel (data source cleaning and prep)

Key Insights

• Top-performing regions and cities driving sales
• Most profitable product categories
• Identification of high-value customers
• Clear gap between revenue and profit margins

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