Free Synthetic Data Generation Tool Online

Generate artificial datasets with the same Properties as real data, so you can develop and test AI models, testing algorithms, training machine learning models, prototyping applications, and conducting simulations without compromising privacy.

What is Synthetic Data Generator?

A synthetic data generator is a tool or software system that creates artificial data that mimics the characteristics of real-world data without containing any personally identifiable information (PII) or sensitive data.
The advantage of using synthetic data lies in its ability to represent diverse scenarios and edge cases that may not be readily available in real-world datasets. It also alleviates privacy concerns associated with using sensitive or personally identifiable information for testing and development purposes.

How to use Test Data Generator?

1. First Choose Type Of Data e.g (Name,Email etc..)
2. Click on the Data Button.
3. Data Button will turn in green.
4. Click on "Generate Test Data" Button.
5. File will be automatically Saved.
6. Check file in Download folder.

Types Of Synthetic Test Data We Offer To Generate:

StatePostcodeMobile Number
EmailStreet AddressJob Title
CompanyCompany EmailUsername
PasswordDomain nameURL
macaddressUUIDCountry Code
Language CodeCurrency CodeCredit Card No
DateMonthNameDay Of Week
yearTimeZoneUnix Time

Why ?

  • Easy-to-use interface.
  • Generate Mock data quickly with 1 click.
  • Safe access to the right data.
  • Accurate and Safe synthetic data
  • 2000 Records In CSV Format.
  • Quick and Easy to Download.
  • 37 types of data to generate (names, emails, countries,company etc.)
  • No Signup, No Charge, All Free.

Why is Synthetic data important?

Test data generation is important for a variety of reasons, primarily in the context of software testing and quality assurance. Here are some key reasons why test data generation is crucial:

  • Verification of Functionality: Test data is used to verify that a software application functions correctly. By providing various types of input data, testers can ensure that the software performs as expected under different conditions and scenarios.
  • Error Detection: Testing with different data sets helps identify errors and defects in the software. The goal is to uncover issues such as bugs, crashes, and unexpected behaviors that may occur when the software encounters certain types of data.
  • Performance Testing: Performance testing often involves generating large volumes of test data to evaluate how the software performs under heavy loads and stress conditions. Test data is essential for load testing, stress testing, and scalability testing.
  • Compatibility Testing: Test data should cover a range of device configurations, operating systems, browsers, and network conditions to ensure that the software works correctly across different environments.
  • Data-Driven Testing: Many modern software applications rely on data from various sources, such as databases, APIs, and external systems. Test data generation allows for data-driven testing, where test cases use different data sets to validate the software's behavior under various conditions.
  • Data Privacy and Security Testing: In applications that handle sensitive data, such as personal information or financial data, it's essential to test how the software handles and protects this data. Test data generation helps create realistic but anonymized or obfuscated data for privacy and security testing.
  • Cost and Time Efficiency: Manually creating test data can be time-consuming and error-prone. Automated test data generation can save time and reduce human errors, making the testing process more efficient.
  • Automated Testing: Automated testing tools often rely on predefined test data to execute test cases automatically. By generating test data in advance, organizations can streamline their test automation processes.