version: "1.0.0" name: test-data-management description: "Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios." category: specialized-testing priority: high tokenEstimate: 1000 agents: [qe-test-data-architect, qe-test-executor, qe-security-scanner] implementation_status: optimized optimization_version: 1.0 last_optimized: 2025-12-02 dependencies: [] quick_reference_card: true tags: [test-data, faker, synthetic, gdpr, pii, anonymization, factories] trust_tier: 3 validation: schema_path: schemas/output.json validator_path: scripts/validate-config.json eval_path: evals/test-data-management.yaml

Test Data Management

<default_to_action> When creating or managing test data:

1. NEVER use production PII directly
2. GENERATE synthetic data with faker libraries
3. ANONYMIZE production data if used (mask, hash)
4. ISOLATE test data (transactions, per-test cleanup)
5. SCALE with batch generation (10k+ records/sec)

Quick Data Strategy:

• Unit tests: Minimal data (just enough)
• Integration: Realistic data (full complexity)
• Performance: Volume data (10k+ records)

Critical Success Factors:

• 40% of test failures from inadequate data
• GDPR fines up to €20M for PII violations
• Never store production PII in test environments

</default_to_action>

Quick Reference Card

When to Use

• Creating test datasets
• Handling sensitive data
• Performance testing with volume
• GDPR/CCPA compliance

Data Strategies

Data Anonymization

// Masking
function maskEmail(email) {
  const [user, domain] = email.split('@');
  return `${user[0]}***@${domain}`;
}
// john@example.com → j***@example.com
function maskCreditCard(cc) {
  return `****-****-****-${cc.slice(-4)}`;
}
// 4242424242424242 → ****-****-****-4242
// Anonymize production data
const anonymizedUsers = prodUsers.map(user => ({
  id: user.id, // Keep ID for relationships
  email: `user-${user.id}@example.com`, // Fake email
  firstName: faker.person.firstName(), // Generated
  phone: null, // Remove PII
  createdAt: user.createdAt // Keep non-PII
}));

Database Transaction Isolation

// Best practice: use transactions for cleanup
beforeEach(async () => {
  await db.beginTransaction();
});
afterEach(async () => {
  await db.rollbackTransaction(); // Auto cleanup!
});
test('user registration', async () => {
  const user = await userService.register({
    email: 'test@example.com'
  });
  expect(user.id).toBeDefined();
  // Automatic rollback after test - no cleanup needed
});

Agent-Driven Data Generation

// High-speed generation with constraints
await Task("Generate Test Data", {
  schema: 'ecommerce',
  count: { users: 10000, products: 500, orders: 5000 },
  preserveReferentialIntegrity: true,
  constraints: {
    age: { min: 18, max: 90 },
    roles: ['customer', 'admin']
  }
}, "qe-test-data-architect");
// GDPR-compliant anonymization
await Task("Anonymize Production Data", {
  source: 'production-snapshot',
  piiFields: ['email', 'phone', 'ssn'],
  method: 'pseudonymization',
  retainStructure: true
}, "qe-test-data-architect");

Agent Coordination Hints

Memory Namespace

aqe/test-data-management/
├── schemas/*            - Data schemas
├── generators/*         - Generator configs
├── anonymization/*      - PII handling rules
└── fixtures/*           - Reusable fixtures

Fleet Coordination

const dataFleet = await FleetManager.coordinate({
  strategy: 'test-data-generation',
  agents: [
    'qe-test-data-architect',  // Generate data
    'qe-test-executor',        // Execute with data
    'qe-security-scanner'      // Validate no PII exposure
  ],
  topology: 'sequential'
});

Related Skills

• database-testing - Schema and integrity testing
• compliance-testing - GDPR/CCPA compliance
• performance-testing - Volume data for perf tests

Remember

Never use production PII directly. Always use synthetic data or properly anonymized production snapshots.

With Agents: qe-test-data-architect generates 10k+ records/sec with realistic patterns, relationships, and constraints. Agents ensure GDPR/CCPA compliance automatically and eliminate test data bottlenecks.