Retail SQL Analytics

This project is a complete SQL-based retail analytics system designed to analyze sales performance, customer behavior, and product demand using structured query techniques. It includes a normalized database schema, realistic transactional retail data, and analytical SQL queries that generate actionable business insights.

Project Structure :

schema.sql — Contains table definitions for Customers, Products, and Sales

sample_data.sql — Inserts realistic, real-world retail data

analysis_queries.sql — Contains business analysis queries (revenue, customer spending, city-wise sales, etc.)

Features : Fully normalized relational database (Customers, Products, Sales) Realistic retail dataset with 20+ transactions Multiple cities, customers, and product categories Analytical SQL queries including:

Revenue calculation

Customer-wise spending

Product performance

City-wise revenue

Daily revenue trends Easy to run on MySQL / PostgreSQL / Oracle / SQL Server

How to Run :

Execute schema.sql to create all tables

Execute sample_data.sql to populate the database

Run analysis_queries.sql to generate insights

Business Insights Generated :

Total store revenue

Top spending customers

Best-selling products

Revenue contribution from major cities

Daily revenue trends

Quantity and demand patterns

Skills Demonstrated :

SQL schema design

Joins, aggregations, subqueries

Data analysis & reporting

Problem-solving using SQL

Understanding of retail business logic

Why This Project Is Valuable This project demonstrates practical SQL skills that Accenture values highly — especially for roles in Data Engineering, Analytics, Business Consulting, and Application Development.