onul.works

Random Data Generator

Generate random sample data for testing in JSON, CSV, or SQL.

⌘ Runs in browser ◴ No data stored ⌁ Free

Search-intent guide

Use cases for generating test data

Generate names, emails, numbers, and dates quickly for API mocks, form testing, and mock JSON payloads in JSON, CSV, or SQL output.

Use this tool to create multiple synthetic rows for API integration tests, QA workflows, and data import validation without manual typing.

It is designed for test data assembly, so you can produce realistic-looking JSON samples that match your frontend or backend contract checks.

Common scenarios

Mock API responses, seed data, dashboard demos, and randomized QA datasets for quick repeatable workflows.

Core fields

Combine name, email, number, and date fields with configurable row counts and export as JSON, CSV, or SQL.

Safe usage

These values are for synthetic test data only. Do not use this as a generator for security tokens, secrets, passwords, or API keys.

The generated records are non-production placeholders. Avoid treating them as real user data or using them as secret credential material.

Generated random data

How to use

  1. 1 Choose the number of records and the output format you need: JSON, CSV, or SQL.
  2. 2 Add or edit field names and data types.
  3. 3 Click generate random data to create sample data in the selected format.
  4. 4 Copy the result or download it as a file.

Common use cases

  • Mock API response data
  • Random CSV sample dataset preparation
  • SQL INSERT test data creation

Frequently asked questions

What random fields can I create?

You can add or remove ID, UUID, name, email, phone, country, city, address, date, number, and boolean fields, then choose the row count and output format.

What output formats are available?

The tool can generate JSON, CSV, or SQL INSERT statements. You can copy the output or download it as a random_data file using the current format.

Can I treat the generated data as real personal data?

No. It is sample test data. Numbers are generated from 1 to 1000, dates are generated between 2020-01-01 and the current date, and the records are not real user information.

Related workflow

Random Data GeneratorChoose the fields and row count first, then generate random sample data to test with. → Cron GeneratorWhen sample generation or checks need timing, write that cadence as Cron. → Diff ViewerAfter changing the output format or settings, compare the generated result.