The Power of Augmenting Production Data with Synthetic Data

Test data sourced from production is real, accurate data that has been masked and delivered to a test environment for automated testing. The test dataset will typically contain production data that matches test case requirements as well as production data that does not match test case requirements resulting in a test data gap.

With GenRocket, synthetic data is used to augment production data to bridge the gap and maximize coverage. Testers simply configure the GenRocket platform to generate synthetic data based on a set of rules that define all data combinations and permutations, negative test data, edge case scenarios, and test data for new applications that have no historical data.

Learn how your organization can maximize coverage and accelerate testing by using synthetic data augmentation to achieve both goals simultaneously.