SQL E-Commerce Portfolio Project

This project demonstrates core and advanced SQL skills through a simulated e-commerce dataset. It showcases the full data workflow—from schema creation to business analytics—designed to support real-world data analyst and entry-level data science roles.

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Project Structure

File	Description
01_create_schema.sql	Creates the database schema with Customers, Products, and Orders tables and inserts sample data
02_data_manipulation.sql	Demonstrates core SQL operations: SELECT, WHERE, JOIN, GROUP BY, ORDER BY, COUNT, and aggregations
03_advanced_joins.sql	Covers advanced joins: RIGHT JOIN, FULL OUTER JOIN (via UNION), SELF JOIN, and CROSS JOIN
04_business_analytics.sql	Business insight queries: top customers, sales trends, order behavior, category revenue, and customer segmentation

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Skills Demonstrated

• Relational database schema design
• Data querying and transformation with SQL
• INNER, LEFT, RIGHT, FULL OUTER, CROSS, and SELF joins
• Aggregation and filtering for analytics
• Business scenario modeling in SQL
• Use of aliases and readable SQL conventions

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Sample Business Questions Answered

• What is the monthly sales trend?
• Who are the most valuable customers?
• Which products are underperforming?
• What is the average order size?
• Which customers are repeat buyers?
• What categories generate the most revenue?

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Technologies Used

• MySQL (v9.3.0) via command-line
• Atom for SQL editing
• Git & GitHub for version control and publishing

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How to Run

1. Clone the repo:

   git clone https://github.com/your-username/sql-ecommerce.git
   cd sql-ecommerce

2. Log into MySQL and create a database:

   mysql -u root -p
   CREATE DATABASE sql_portfolio;
   exit;

3. Execute each script:

   mysql -u root -p sql_portfolio < 01_create_schema.sql
   mysql -u root -p sql_portfolio < 02_data_manipulation.sql
   mysql -u root -p sql_portfolio < 03_advanced_joins.sql
   mysql -u root -p sql_portfolio < 04_business_analytics.sql

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License

This project is open-source and available for reuse with attribution.

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About Me

I'm a data analyst and researcher transitioning into data science. This project is part of my portfolio to demonstrate practical SQL capability and insight generation. I'm open to feedback and collaboration—feel free to connect!