The Mock Data Generator is a fast, browser-based tool that helps developers, QA testers, data engineers, and students instantly generate realistic fake datasets for testing. Whether you are building APIs, seeding a database, or validating business logic, this tool lets you create structured dummy data in seconds. No sign-up, no limits, and no coding required. Generate fake data online, export it to multiple formats, and customize every field with over a hundred data types.
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Modern applications rely on dynamic data. Collecting real datasets slows development and adds legal risk. The Mock Data Generator solves this problem by creating large volumes of fake data with realistic structure. No real personal information appears anywhere, which helps keep testing safe and compliant.
You generate user profiles, ecommerce records, logs, addresses, financial rows, or fully custom schemas in minutes. The workflow matches tools like Mockaroo, without artificial limits. Choose fields, select from more than 120 data types, define blank percentages, add custom arrays, then export results in CSV, JSON, or Excel.
Developers testing APIs, QA teams running automation, and engineers stress testing databases gain faster feedback and fewer blockers with this tool.
Select names, email addresses, IP values, dates, finance fields, product data, colors, geolocation values, UUIDs, random numbers, and more. Each type generates valid structured output automatically.
Example: For a signup flow, add Full Name, Email Address, Password, and Phone Number. Generate hundreds of sample users in seconds.
Large datasets generate without usage limits or paywalls.
Example: Stress test a database with 500,000 rows by entering the count and exporting immediately.
Pick a format aligned with the workflow.
Example: API testing workflows often use JSON. QA automation often relies on CSV.
Missing values appear by design to reflect real data conditions.
Example: Set Phone Number to 20% blank to reflect optional form fields.
Define custom value lists for domain-specific data.
Example: Create an Order Status field with Pending, Shipped, Delivered, and Cancelled.
Background processing keeps the browser responsive during large jobs.
Example: Generate one million rows without tab freezing.
Field definitions persist automatically between visits.
Example: Open the page later and continue with the same schema.
Add fields, reorder columns, adjust options, and export without friction.
All processing runs locally, so no data leaves the device.
Fields include Full Name, Email Address, Age, Phone Number, and Country.
Result supports testing authentication flows and profile pages.
Fields include Product Name, Product Price, Quantity, Order Status from a custom array, and Datetime.
Result fits dashboards and analytics testing.
Fields include UUID, Username, Password, City, and Postal Code.
Result fills local development databases with safe data.
Fields include IP Address, URL, Datetime, and HTTP Status Code.
Result supports testing monitoring pipelines and aggregation logic.
Fields include Bank Name, Money Amount, Currency Code, and Past Date.
Result supports demos and financial simulations.
Testing with real data introduces privacy risk and compliance issues. Mock data replaces real values with synthetic ones that follow the same structure and constraints. This approach helps validate schemas, benchmark performance, test edge cases, and verify frontend behavior.
QA workflows benefit from fast generation of invalid emails, missing phone numbers, or rare status combinations. Online mock data generation removes manual record creation and avoids copying production data.
Perfect datasets hide bugs. Real datasets include blanks, inconsistent casing, and incomplete addresses. Blank percentage controls help reproduce those conditions and expose issues earlier.
Teams seeking a fake database generator or dummy dataset creator gain flexibility across many testing scenarios. Speed, accuracy, and local execution support repeated iteration without overhead.
Anyone who needs structured dummy data benefits from this workflow.
Yes. Access stays free with no row limits and no account requirement.
Yes. Web Worker processing supports large datasets while keeping the interface responsive.
CSV, JSON, and Excel xlsx.
All generation runs on the client side. No uploads or server storage occur.
Mobile browsers work for smaller datasets. Desktop systems handle large volumes more smoothly due to memory limits.
Define fields, assign data types, and export. The result functions as a dummy database table.
Use the Random Element from Array field type to define custom lists.
Basic template string support exists for advanced data shaping.
The Mock Data Generator is one of the fastest and most flexible ways to generate fake data online. With support for 120+ data types, unlimited rows, multiple export formats, and instant browser-based processing, it gives developers and testers everything they need to work smarter and faster. Try it now and create your perfect dataset in seconds.