Generate compliant test data required for your comprehensive testing needs, independently without technical help using Datagaps Test Data Manager. Test Data Manager: Test data generation, Sensitive Data identification Enterprises are increasingly becoming data-driven thanks to their digital transformation initiatives. Delivering these business-critical applications on time and with high quality requires a reliable and repeatable testing process to accelerate time-to-market and reduce costs. However, compliance requirements for privacy laws such as GDPR, CCPA, and HIPAA limit the usage of PII/PHI data in test environments. Preparing data for testing is highly labor-intensive and can consume more than 50 percent of your overall testing time and resources. Even if the test data were prepared manually, human errors and low data volumes became significant limitations. Data-driven testing challenges can cause spiraling costs and pose a substantial risk to the quality of the resulting application. It is simply not cost-effective to clone large production databases for testing environments in addition to increasing compliance risks. The legacy test data management tools helped generate fake data based on manually defined rules such as ranges, distributions, and correlation. However, defining these rules is a tedious and error-prone process. Modern test data management uses a Machine Learning-based approach to learn these rules automatically and generate realistic-looking test data referred to as Synthetic Data. DataOps TDM uses Artificial intelligence and Machine Learning based synthetic data generation algorithms to automatically detect PII elements and generate realistic-looking synthetic data. This is done by using a subset of original data or user-defined sample data to generate a large amount of synthetic data which reliably mimics the actual data behavior but does not reveal any information regarding real data.