TDspora is a Test Data Management product capable of reducing the footprint of test data in non-production environments, maintaining referential integrity, generates compliant, statistically representative synthetic data protected by a differentially private deep neural network.
- Visualizes data table relationships as flexible, easy to understand graphs
- Supports heterogeneous data sources and targets
- Maintains relationships defined on the database and application levels
- Supports fine-tuning of resulting data set
- Reduces time and cost of test data provisioning
- Integrates into CI/CD processes via rich REST API
- Controls privacy vs. utility trade-off via privacy budget
- Can increase test data variability and volume
- Utilizes distributed, fault-tolerant Apache Spark cluster
This section explains the installation process using Docker.
The section guides you through the initial configuration of the application resources such as sources, targets, clusters, and pipelines.
All known issues and limitations of the product are collected in the troubleshooting section.
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