Create high quality synthetic data in your cloud with Gretel.ai and Python

The text discusses generating synthetic versions of datasets using Gretel.ai to meet compliance requirements and work with sensitive data within approved environments. It provides instructions for setting up the local environment, installing dependencies, training models, and generating synthetic data. The synthetic data can be compared with the original source data to ensure similar correlations and insights. This approach is useful in industries like healthcare, finance, and consumer protection where handling sensitive data requires adherence to regulations such as HIPAA, PCI, GDPR, or CCPA.