DataCebo Synthetic Data Vault (SDV) Description
The Synthetic Data vault (SDV) was designed as a Python library that allows you to create tabular synthetic data. The SDV uses machine learning algorithms to emulate patterns in synthetic data. The SDV offers a variety of models, from classical statistical methods to deep learning methods. Create data for single tables or multiple connected tables. Compare the synthetic data with the real data using a variety measures. Diagnose problems and create a quality report for more insights. Control data processing to enhance the quality of synthetic information, choose different types of anonymization and define business rules as logical constraints. Use synthetic data to replace real data or as an enhancement. The SDV is a comprehensive ecosystem of synthetic data models, metrics, and benchmarks.