Description
Existing mock data generators can only create individual, unrelated tables of fake data. Synthetic data services that can produce interwoven datasets require real data to anonymize. This leaves only error-prone custom scripts to create realistic, interdependent datasets for development and testing.
In this session learn how to define a .json configuration file and leverage the graph-data-generator PyPi package to quickly create custom, deeply interconnected fake datasets for your own Python projects.