This is how a large-scale credit card transaction history file can be generated to accurately reflect production-quality transaction data without the risk of exposing sensitive customer data. The use of synthetic data ensures total compliance with privacy regulations while protecting the business from the damaging repercussions of an accidental data breach – a critically important test data requirement.

10 million transactions for 10 thousand customers were generated to simulate transaction history over a 12 month span of time - A large volume of data that maximizes test coverage, validates business logic and simulates a significant transaction load for the software under test.


Additional test data requirements in this scenario

  • Generate realistic composite (concatenated) account numbers
  • Perform reward calculations in real-time
  • Model a pre-determined ratio of customer reward categories
  • Maintain full referential integrity between all parent-child relationships


The video, shown below, showcases GenRocket’s new partition engine – a powerful feature for launching multiple GenRocket instances to generate millions or billions of rows of data in parallel to minimize data generation time.  

This use case illustrates the power of GenRocket to create authentic transaction history files in high volume and data that is based on complex business rules and data models.