Random Data Generator
Generate bulk test data: names, emails, UUIDs, IPs and more
20 👤 Full Name records
About the Random Test Data Generator
This tool generates random test data — names, email addresses, UUIDs, phone numbers and dates — so you can fill a form or a fixture without inventing values. Everything is generated in your browser.
Random test data is the quickest fix for the moment you need a plausible name and email to test a form and find yourself typing "asdf" into every field. Generated values look realistic, which makes layout and validation problems visible in a way placeholder junk does not.
Realistic values also surface real bugs. A name containing an apostrophe, an address on two lines or an unusually long email are the inputs that break validation and column widths, and they only appear if the data resembles the real thing.
Everything generated here is fictional. Names and addresses are assembled from component lists rather than drawn from any real dataset, so nothing represents an actual person — which matters when test data ends up in shared environments or screenshots.
How to use the Random Test Data Generator
- Pick the field types. Choose names, emails, UUIDs, phone numbers or dates.
- Set how many. Choose how many records to generate.
- Generate. Values are produced immediately in your browser.
- Copy into your fixture. Take the data for your form, seed or test file.
Random Test Data Generator features
- Names, emails, phone numbers, UUIDs, IP addresses, dates, cities, job titles, colours, numbers, booleans and lorem text
- Choose how many values to generate
- Seeded generation, so the same seed reproduces the same data
- Copy the values or download them
- Runs in your browser; nothing is sent anywhere
Frequently asked questions
What data types can it produce?
Full names, email addresses, phone numbers, UUIDs, IP addresses, dates, cities, job titles, colours, plain numbers, booleans and lorem text — the fields that populate most forms and fixtures.
Why does reproducibility matter?
Because a test that generates fresh data every run fails differently every time. Fixing the seed means the same values come back, so a failure can be investigated instead of merely observed.
Is any of it real data?
No. Values are assembled from component lists rather than drawn from any real dataset, so nothing corresponds to a real person — which is the entire reason to use generated data instead of a copy of production.
How does this differ from the fake data generator?
This produces individual field values by type, which suits filling a form or a column. The fake data generator produces whole coherent records — a person with a matching email, address and company — which suits seeding a database.