Introduction
Learn about Protegrity Synthetic Data.
Protegrity Synthetic Data
Protegrity Synthetic Data generates artificial data that mimics the structure and statistical properties of real data.
Protegrity Synthetic Data generates privacy-safe synthetic datasets from real data using machine learning models such as VineCopula, TabDiff, TabularGAN, and SMOTE. The generated data is statistically representative and suitable for development, testing, and analytics workflows.
Understanding the Architecture and Components
Overview of Protegrity Synthetic Data architecture, processing flow, and deployment components on AWS EKS.
Prerequisites for Deployment
Required tools, AWS permissions, and EKS cluster configuration for deployment.
Server Installation
Step-by-step deployment of Protegrity Synthetic Data.
Upgrading Protegrity Synthetic Data
Upgrade from the previous version.
User Creation in PPC
Update PPC role permissions, authenticate with the gateway, and create an Synthetic Data administrator user for API access.
Using Synthetic Data
Install and configure the Python SDK, validate connectivity, and use the API reference for client setup and Synthetic Data operations.
Uninstalling and Cleanup
Remove the Synthetic Data Helm release, clean up Kubernetes resources, and destroy provisioned AWS infrastructure with OpenTofu.
Troubleshooting
Troubleshoot common issues with Protegrity Synthetic Data, including pod failures, API errors, and OpenTofu infrastructure problems.
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