validating-database-integrity

# Data Validation Engine

This skill provides automated assistance for data validation engine tasks.

## Prerequisites

Before using this skill, ensure:
- Database connection credentials are available
- Appropriate database permissions for schema modifications
- Backup of production databases before applying constraints
- Understanding of existing data that may violate new constraints
- Access to database documentation for column specifications

## Instructions

### Step 1: Analyze Validation Requirements
1. Review database schema and identify columns requiring validation
2. Determine validation types needed (data type, range, format, referential)
3. Document existing data patterns that may conflict with new rules
4. Prioritize validation rules by business criticality

### Step 2: Define Validation Rules
1. Create validation rule definitions for each column
2. Specify data types, constraints, and acceptable ranges
3. Define regular expressions for format validation
4. Map foreign key relationships for referential integrity
5. Document business rule logic for complex validations

### Step 3: Implement Database Constraints
1. Generate SQL constraints for data type validation
2. Add CHECK constraints for range and format validation
3. Create foreign key constraints for referential integrity
4. Implement triggers for complex business rule validation
5. Test constraints with valid and invalid sample data

### Step 4: Validate Existing Data
1. Query existing data to identify constraint violations
2. Generate reports of data that would fail new constraints
3. Create data cleanup scripts to fix violations
4. Execute cleanup scripts in staging environment first
5. Re-validate cleaned data before applying constraints

### Step 5: Apply Validation Rules
1. Apply constraints to staging database first
2. Monitor for any application errors or failures
3. Validate that legitimate operations still function
4. Apply constraints to production database during maintenance window
5. Mon