Supporting database constraints in synthetic data generation based on generative adversarial networks

Abstract

Disclosed herein are system, method, and computer program product embodiments for generating synthetic data records with database constraints using generative adversarial networks (GAN). The method can include training, by using a generator loss function, a generator neural network of a generator model of the GAN to generate a scaling factor and a cluster vector for a datum of a continuous variable of a continuous column of a data table, and a datum for a categorical variable of a categorical column of the data table. The generator loss function includes a penalty component determined based on a set of data constraints related to the continuous column or the categorical column.