Retail Sales Data Warehouse and Business Analytics Using SQL Server

Project Overview

This project focuses on building a retail sales data warehouse and performing business analytics using Microsoft SQL Server. Using the Central Superstore dataset, I designed a Star Schema data model to organize sales data and support efficient analytical queries.

The project includes the creation of five dimension and fact tables covering customers, products, locations, dates, and sales transactions. Data was loaded from the source dataset into the data warehouse using SQL queries and table relationships were established through primary and foreign keys.

Key Features

Designed a Star Schema data warehouse using SQL Server.

Transformed and loaded retail sales data into fact and dimension tables.

Used SQL joins, aggregations, subqueries, common table expressions, and CASE statements to analyze business performance.

Created a SQL view to summarize sales and profit by product category.

Developed a stored procedure to retrieve sales performance by city.

Implemented nonclustered indexes on key columns to support query performance.

Analyzed sales trends, product profitability, customer performance, regional sales, discounts, and shipping methods.

Project Objective

The main objective is to transform raw retail data into a structured analytical database that enables meaningful business insights, supports sales performance evaluation, and helps identify profitable products, valuable customers, and regional sales trends.

Tools and Technologies Microsoft SQL Server, T-SQL, Data Warehousing, Star Schema, Data Modeling, and Business Analytics.