What is DataCebo SDV 2.0?

Synthetic data is artificially generated data that is not produced by real-world events. It matters because in many sensitive applications datasets exist but cannot be released to the general public, so privacy limits who can use them. SDV, the Synthetic Data Vault, is a Python library for creating tabular (table-shaped) synthetic data: it learns patterns from real data and emulates them in new, artificial data, including for several connected tables. DataCebo describes SDV 2.0 as a major release of SDV Enterprise, aimed at building generative models of whole databases made of linked tables, with more automation. The Synthetic Data Vault project was first created at MIT's Data to AI Lab in 2016.

Written from primary sources and reference pages, and checked against them by an independent AI fact-checker. Drafted with AI assistance.