Fake Data Generator
Generate realistic fake data for testing and development
About the Fake Data Generator
This fake data generator produces realistic but entirely fictional records — names, emails, addresses, companies and phone numbers — for seeding a development database or filling a demo environment without touching real customer data.
A fake data generator exists mainly so production data does not have to be copied into development. Copying real records is the easy option and the wrong one: it spreads personal data into environments with weaker access control, and under GDPR and similar regimes that is a reportable problem waiting to happen.
Generated records are realistic enough to be useful. A demo populated with plausible names and companies looks like a working product, while one full of "test test" and "[email protected]" undermines whatever you are demonstrating.
Realistic data also stresses the interface honestly — long company names, names with apostrophes, international addresses. Nothing here corresponds to a real person; values are assembled from component lists rather than sampled from any dataset.
How to use the Fake Data Generator
- Choose the record shape. Pick which fields each record should include.
- Set the record count. Choose how many records to generate.
- Generate. Fictional records are produced in your browser.
- Copy the records. Take the data for your seed script or demo environment.
Fake Data Generator features
- Person, company, address, contact and card record types
- Generate a whole record set or one field type
- Choose how many records to produce
- Values assembled from component lists, not sampled from real data
- Copy the generated records
- Runs in your browser; nothing is sent anywhere
Frequently asked questions
Could any of this data belong to a real person?
Not by design. Records are assembled by combining values from component lists — a first name with an unrelated surname, street and city — rather than drawn from any real dataset. Coincidental matches to a real name are possible, as they are with any generator, but nothing is copied from real records.
Why not just copy production data into development?
Because it spreads personal data into environments with weaker access control and no retention policy, which under GDPR and similar regimes is a reportable problem waiting to happen. Generated data gives you realistic records with none of that exposure.
Are the generated card numbers usable?
They are formatted to look like card numbers for filling a form or a demo screen. They are not valid payment instruments and will not authorise against any processor.
Why does realistic data matter for a demo?
Because a demo populated with plausible names and companies looks like a working product, while one full of test test and [email protected] undermines whatever you are showing. Realistic values also stress the interface honestly — long company names, apostrophes in surnames, international addresses.
How do I get the records into my database?
Copy them and paste into a seed script or fixture file. There is no direct database connection, which is deliberate — a tool that writes to your database is a much larger thing to trust.