Ethical testing: Generation of realistic fictional data to protect privacy

In the era of Big Data and strict privacy compliance, protecting the information your applications handle during the development and commercial demonstration phases is mandatory.

The use of real personal data in uncontrolled environments is one of the most frequent causes of regulatory fines and corporate data leaks.

Masking and Synthetic Generation

To solve this challenge, engineers use two methodologies:

1. Data Masking: Encrypt or obfuscate existing production data.
2. Synthetic Data Generation: Create records from scratch that mimic real human behavior (such as valid postal addresses, test card numbers, and structured dummy telephone numbers).

Using synthetic data ensures that your analysts and software testers have realistic material to work with, without any physical possibility of compromising real identities.

To quickly generate structured collections of mock data in JSON or CSV format, you can use our local generator:

Try our Dummy Data Generator

Customize the fields you need and export secure test information for your databases instantly.