In the healthcare industry, Anonymizing data ("data-masking") can often render it useless for analytics and machine learning. Synthetic data is a promising solution. Synthetic data is artificiality generated data that is statistically similar to real data. It preserves data utility without sacrificing privacy.

The main applications of synthetic tabular data are enabling data-sharing and data-analytics on sensitive data.

In this session, I will describe some use-cases for synthetic data. I will introduce the latest methods for generating tabular synthetic data (and do a simple demo using a excel spreadsheet) and compare the methods against each other in detail.