Fake Data Generator
Generate rows of realistic-looking but entirely made up test data (name, email, address, phone number, and company) for populating a database, testing a form, or building a UI demo without using real people's information. Pick which fields to include, how many rows you need, and optionally a numeric seed so the same dataset can be regenerated later for repeatable tests. Export as CSV or JSON. Everything runs in your browser with a seeded pseudo-random generator, so nothing gets uploaded.
Reviewed by Vincenzo Manto, Founder & Lead Developer · Last updated September 27, 2026
How it works
- 1
Check the fields you want included: Name, Email, Address, Phone, Company.
- 2
Set how many rows to generate (up to 5000).
- 3
Optionally set a numeric seed so the same settings always regenerate the exact same dataset.
- 4
Choose CSV or JSON output, then copy or download the generated data.
Why generate fake data instead of using real records
Testing forms, database imports, or UI demos with real customer names, emails, and addresses risks privacy violations and looks unprofessional in a demo. Fake but realistically formatted data lets you exercise the same code paths, like validation, column widths, sorting, and pagination, without exposing anyone's real information.
Reproducible test fixtures with a seed
Randomly generated test data is fine for a one-off manual test, but automated test suites often need the exact same fixture data on every run. This generator's optional seed uses a small deterministic pseudo-random generator (mulberry32), so the same seed, row count, and field selection always reproduce identical rows.
Frequently asked questions
Is this real personal data?
No. Every name, email, address, phone number, and company is assembled from fixed word lists using a pseudo-random generator. None of it corresponds to a real person, business, or place, though addresses and phone numbers are formatted to look plausible.
What does the seed field do?
By default, each generation uses fresh randomness so the dataset changes every time. Setting a seed switches to a deterministic pseudo-random generator: the same seed with the same row count and field selection always produces identical output, which is useful for reproducible test fixtures.
Are the generated emails linked to the generated names?
Yes, each row's email is derived from that row's generated first and last name (e.g. [email protected]), so the fields stay consistent within a row.
Can I use this to seed a database for development?
Yes, that's a common use. Generate a CSV or JSON file of realistic-shaped rows, then import it into your dev database or test fixtures instead of using real customer data.
Is any of this data sent to a server?
No. Generation happens entirely in your browser with JavaScript; nothing is uploaded or logged.