Dataset Generator

Fake Data Creator Dataset Generator + Collections (Multi-Table Export)

When you’re building an app, testing an API, designing an interface, or preparing a demo, you need data that looks real—but you can’t (and shouldn’t) use production data. Creating sample datasets manually is slow, inconsistent, and hard to scale.

That’s exactly what Fake Data Creator’s Dataset Generator is built for.

With the Dataset Generator tool You can define a dataset in a table, generate realistic fake values using 50+ data types, select a locale, export in multiple formats—and now, with Collections, you can also save multiple generated tables together and export them as a multi-sheet spreadsheet or a SQLite database.

What is a Dataset Generator?

A dataset generator is a tool that automatically creates structured sample data (rows + columns) for testing, prototyping, and development. Instead of manually writing dozens (or thousands) of rows, you define:

• Columns (e.g., First Name, Email, City, Company)
• Fake data types for each column (e.g., name, email, address)
• Locale (to generate region-specific patterns)
• Output format (CSV/Excel/JSON/code formats)

Then you click Generate Data, and the tool produces an instant dataset.

How Fake Data Creator’s Dataset Generator Works

1) Build your dataset in a table

Add the columns you need for your project—like:

• Full Name
• Email Address
• Phone
• City
• Country
• Date of Birth
• Company Name
• UUID / ID
• Website URL

2) Choose a category for each column

Each column maps to a fake data category (data type), such as name, email, address, and dozens more. With 50+ data types, you can build datasets for almost any use case.

3) Select a locale (optional)

Generate data that matches local patterns—helpful for names, addresses, and phone formats.

4) Generate data instantly

Click Generate Data and the tool produces realistic sample values in seconds.

5) Export or save to a Collection

Once you have a table you like, you can:

• Export it directly (CSV, Excel, JSON, etc.), or
• Save it into a Collection to combine it with other generated tables.

Best Use Cases (Examples)

For developers

• Create seed data for local development
• Export to JSON for API mocks
• Export Collections to SQLite for a complete demo database
• Generate fixtures for testing scripts

For QA and testers

• Generate bulk test data quickly
• Validate imports using CSV/Excel
• Use Collection exports for end-to-end testing with multiple tables

For designers and product teams

• Fill dashboards and admin panels with realistic data
• Export multi-sheet spreadsheets for demos and reviews
• Keep different datasets organized by Collection (per feature/prototype)