Mock Data Generator
Generate realistic fake names, emails and addresses as CSV or JSON
100% free. Runs entirely in your browser - your files and data never leave your device and nothing is uploaded to any server.
About this tool
Generate realistic-looking fake data - names, emails, addresses, and more - as CSV or JSON, useful for populating a test database, demoing an application with believable data, or testing how your code handles various data shapes without using any real personal information.
How to use this tool
- Choose output formatSelect JSON or CSV depending on your testing/import workflow.
- Pick fields and countConfigure record count and data columns like name, email, address, and custom values.
- Generate datasetCreate synthetic records instantly for development or demo usage.
- Download and importExport file and load into your app, seed scripts, or QA tools.
Why use fake data instead of real data
Copying production data into test or demo systems spreads real people’s personal information to places with weaker protection, which can breach privacy laws such as GDPR. Generated data looks realistic but belongs to nobody.
Generate enough rows to test pagination and performance, and include awkward values - long names, apostrophes, accented letters - to catch bugs before real users do.
Key features
- Creates realistic synthetic data without exposing real user information.
- Speeds up QA, demos, and development environment setup.
- Supports quick export in developer-friendly formats.
- Useful for testing validation and edge-case handling at scale.
Common uses
- Seeding local databases for development.
- Preparing realistic datasets for demos and screenshots.
- Testing forms, search, and pagination with varied records.
- Running API performance checks with larger sample payloads.
Tips for better results
- Include edge-case values to test validation robustness.
- Generate separate small and large datasets for unit vs load tests.
- Label synthetic data clearly so it is never confused with production records.
- Version seed files for reproducible QA scenarios.
Mistakes to avoid
- Using fake data structure that does not match real production schema.
- Forgetting to test null/empty values alongside normal records.
- Importing generated data into production by mistake.
- Assuming random samples cover all edge conditions automatically.
Frequently asked questions
No - all generated names, emails, and addresses are randomly fabricated and don't correspond to real individuals, making it safe to use for testing and demos.
You can typically generate a configurable number of rows/records in one batch, suited for populating test datasets of varying sizes.
Yes - select the specific fields you need (name, email, address, etc.) rather than being locked into a fixed set of columns.
CSV (for spreadsheets/databases) and JSON (for APIs/applications) are both supported as export formats.
Real customer data in test and demo environments is a privacy and compliance risk - laws such as GDPR apply to it wherever it is copied. Generated data looks realistic without exposing anyone.
Most databases import CSV directly: COPY in PostgreSQL, LOAD DATA in MySQL, the Import Wizard in SQL Server, or the .import command in SQLite. Make the column names match your table first.
Do not send to them. They are made up and may belong to real domains; for email testing, use a capture tool or a domain you control so nothing reaches a real inbox.