A comprehensive SQL project designed to analyze and manage e-commerce business data. This repository demonstrates database design, SQL query optimization, joins, aggregations, subqueries, and analytical reporting techniques commonly used in real-world e-commerce systems.
The project simulates an e-commerce order processing system and provides SQL queries to extract valuable business insights from customer, order, payment, product, and employee data.
The objective is to showcase practical SQL skills through solving business problems and generating analytical reports.
- Customer information management
- Customer loyalty analysis
- Customer rewards tracking
- Order processing and management
- Invoice generation
- Order lookup and tracking
- Product inventory management
- Stock availability monitoring
- Popular product analysis
- Payment tracking
- Payment method analysis
- Invoice payment summaries
- Employee hierarchy management
- Reporting structure analysis
- Salary analytics
- SELECT Statements
- WHERE Clause
- ORDER BY
- GROUP BY
- HAVING Clause
- Aggregate Functions
- INNER JOIN
- LEFT JOIN
- Self Join
- Subqueries
- Common Table Expressions (CTEs)
- CASE Statements
- Date Functions
- Database Creation and Data Insertion
This project includes SQL solutions for:
- Customer Loyalty Status
- Customer Rewards Analysis
- Find Orders by Customer ID
- Most Popular Product
- Stock Availability Check
- Inventory Monitoring
- Total Payment Per Invoice
- Payments by Date Range
- Payment Method Analysis
- List Employees with Managers
- Employees Reporting to Specific Managers
- Direct Report Count
- Highest Paid Employee by Office
- Average Salary by Office
- Total Salary Expense by Office
- Total Sales by Month
- Discount Analysis Based on Invoice Amount
- Top Clients by Total Payments
├── Create_database_table_insert.sql ├── Customer Loyalty Status.sql ├── Customer Rewards.sql ├── Most popular product.sql ├── Payment.sql ├── StockCheck.sql ├── Total Sales by month.sql ├── Top 5 Clients by Total Payments.sql ├── Calculate Average Salary by Office.sql ├── Calculate Total Salary Expense by Office.sql ├── README.md
- SQL
- MySQL
Through this project, you will learn:
- Database schema design
- Writing complex SQL queries
- Data aggregation and reporting
- Business intelligence reporting
- Relational database concepts
- Real-world e-commerce analytics
Helly Diyora
LinkedIn: www.linkedin.com/in/helly-diyora
GitHub: https://github.com/hellydiyora
This project is intended for educational and portfolio purposes.