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

Type	When	Size
Minimal	Unit tests	1-10 records
Realistic	Integration	100-1000 records
Volume	Performance	10k+ records
Edge cases	Boundary testing	Targeted

---

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!
});