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Fake Data Generator creates realistic test data for development and testing—names, emails, addresses, phone numbers, dates, and lorem ipsum text. I use this constantly when seeding development databases, creating demo accounts for presentations, testing form validation, and building UI mockups with realistic content instead of 'test test test'. Generate single entries or bulk data (up to 1000 records) in JSON, CSV, or SQL INSERT format. Configure locales (US, UK, Europe, Asia) for region-specific formats (phone numbers, postal codes, addresses). The tool uses Faker.js patterns—generated data looks real but is completely fictional with no PII concerns.
Tips & Best Practices
**Development workflows**: Use JSON output for API mocking or frontend fixtures, CSV for spreadsheet imports or database seeders, SQL for direct database population. Always add 'test_' prefix or special markers to fake emails (test_john@example.com) to prevent accidental real-user notifications. Common scenarios: testing pagination with 100+ records, validating email uniqueness constraints, stress-testing search with varied names/addresses, and creating privacy-safe screenshots for documentation. Remember: generated data is random but deterministic per session—refresh for new data. Don't use for security testing (passwords are weak) or performance benchmarks (data distribution isn't production-realistic). For large datasets (10k+ records), use command-line Faker.js with custom scripts for better performance and control.