This is an end-to-end SQL project, from dataset creation and seeding to problem statement creation and data analysis through SQL. We created a fake database in MySQL consisting of 4 tables (sales, customers, suppliers, and products). The data was auto-populated randomly through AI, and then we conducted a sales and customer insights analysis.

This project consists of four tables.: Sales, Customers, Suppliers, Products

Sales Table

• transaction_id (Primary Key)
• customer_id (Foreign Key to Customers table)
• product_id (Foreign Key to Products table)
• supplier_id (Foreign Key to Suppliers table)

Customers Table

• customer_id (Primary Key)

Products Table

• product_id (Primary Key)
• supplier_id (Foreign Key to Suppliers table)

Suppliers Table

• supplier_id (Primary Key)

SQL results:

Top Product Categories

Top Suppliers

Profitable customer's Demographics

Product Category Distribution

Monthly Sales trend

Top Suppliers

• Main Revenue Sources: Electronics and Accessories are the top product categories.
• Seasonal Trends: Higher sales in the first quarter of the year.
• Top Suppliers: Our top 3 suppliers are Gadgets4U, ElectronicsRUs, and FashionTrends.

• Gender Distribution: Sales distribution is 50/50 between genders.
• Profitable Customer Demographics: Profitable customers (3-5 purchases) are aged between 28-40 years old.