SQL for QA Testing

A comprehensive SQL query collection focused on data quality validation and bug detection in databases. This project demonstrates real-world QA skills: finding data anomalies, validating integrity, and detecting broken relationships.

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🎯 Project Purpose

This repository showcases SQL skills from a QA Engineer perspective:

• ✅ Detecting invalid data (negative values, nulls, zeros)
• ✅ Finding duplicates and inconsistencies
• ✅ Validating data integrity and relationships
• ✅ Identifying orphaned records and broken references

This is NOT about writing complex queries to show off.
This IS about writing clear, focused queries that find real bugs.

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🗄️ Database Schema

Simple e-commerce database with intentional bugs for QA practice:

Tables:

• users - Customer accounts
• products - Product catalog
• orders - Purchase orders

Relationships:

orders.user_id    → users.id
orders.product_id → products.id

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🐛 Intentional Bugs in Dataset

The seed data contains real-world bugs that QA engineers encounter:

Data Quality Issues:

• Negative totals and prices
• Zero prices and quantities
• Invalid/future dates
• Empty/null required fields

Duplicates:

• Duplicate emails in users
• Potential duplicate orders

Data Integrity:

• Orphaned orders (user doesn't exist)
• Broken references (product doesn't exist)
• Totals that don't match calculations

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📂 Query Organization

Queries are organized by validation type:

queries/
├── 01_basic_validation/      # List, filter, order data
├── 02_data_quality/          # Find invalid data
├── 03_duplicates/            # Detect duplicates
└── 04_data_integrity/        # Validate relationships

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🚀 Getting Started

Prerequisites

• MySQL 8.0+
• MySQL Workbench (or any SQL client)

Setup

1. Clone the repository:

   git clone https://github.com/your-username/sql-for-qa-testing.git
   cd sql-for-qa-testing

2. Create database:

   CREATE DATABASE sql_qa_testing;
   USE sql_qa_testing;

3. Run schema:

   mysql -u root -p sql_qa_testing < database/schema.sql

4. Load seed data:

   mysql -u root -p sql_qa_testing < database/seed_data.sql

5. Verify setup:

   SELECT COUNT(*) FROM users;    -- Should return 10
   SELECT COUNT(*) FROM products; -- Should return 10
   SELECT COUNT(*) FROM orders;   -- Should return 15

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🧪 Running Queries

Each query file is standalone and can be executed independently:

-- Example: Find negative prices
source queries/02_data_quality/find_negative_totals.sql

Or open in MySQL Workbench and execute.

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📊 What You'll Learn

As a QA Engineer:

• How to validate data quality systematically
• Writing queries that detect real bugs
• Understanding data relationships and integrity
• Identifying edge cases in datasets

Technical Skills:

• SQL SELECT with filters and joins
• Aggregate functions for validation
• Subqueries for data verification
• NULL handling and data anomalies

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🎓 Query Philosophy

Good QA SQL queries are:

• ✅ Clear - Easy to understand what's being checked
• ✅ Focused - One validation per query
• ✅ Documented - Comments explain the bug being detected
• ✅ Actionable - Results can be directly reported

Avoid:

• ❌ Overly complex queries that are hard to maintain
• ❌ Multiple validations in one query
• ❌ Queries without clear purpose

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📊 Project Status

Category	Status	Queries
Basic Validation	✅ Complete	3/3
Data Quality	✅ Complete	4/4
Duplicates	✅ Complete	3/3
Data Integrity	✅ Complete	3/3

Total: 13 professional QA queries

🐛 Bugs Found

This project successfully detected:

• 3 orders with invalid totals (negative/zero)
• 2 records with future dates
• 3 products with zero/negative prices
• 1 user with empty name
• 2 duplicate emails (4 users affected)
• 1 orphaned order (user doesn't exist)
• 1 broken reference (product doesn't exist)

Data Integrity: 86.67% (13 out of 15 orders are valid)

🤝 Contributing

This is a personal learning project, but suggestions are welcome!

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👤 Author

• GitHub: https://github.com/ChandeDeVargas
• LinkedIn: https://www.linkedin.com/in/chande-de-vargas-b8a51838a/

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📄 License

This project is open source and available under the MIT License.

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⭐ If this project helps you learn SQL for QA, give it a star!