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Happy New Year! From everyone at GenRocket, we wish you a happy, healthy, and prosperous 2023. We’re thankful that 2022 was a fruitful year for both GenRocket and our clients. We couldn't be more excited about our plans for growth and expansion in 2023. It’s truly an exciting time for companies using synthetic data solutions, especially those like GenRocket that further automate and accelerate the delivery of exceptional enterprise-class software in the marketplace. We thought we’d take a few moments now to recap 2022 and look ahead at what 2023 may offer us.

We are often asked if GenRocket can perform data masking. The answer is, “Yes, of course – and with ease.” But like many questions asked about synthetic test data, the simple answer belies a complex explanation of the advantages of synthetic test data over production test data. Here, we explain five issues with masked production data and how Synthetic Data Masking overcomes them.

Obtaining test data for functional testing usually involves copying and subsetting the production data values used by the software under test. Production data must be carefully masked to comply with data privacy regulations and is often provisioned for testers by a dedicated test data support team. The assumption behind this approach is that production data is realistic, readily available, and made secure for testing.

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