Synthetic data

Synthetic data is created through simulations, rules, generative models, or statistical techniques to resemble the structure and behavior of real data. Teams use it to expand rare scenarios, test systems, train machine learning models, and reduce dependence on sensitive or difficult-to-collect datasets. Its usefulness depends on how accurately it represents the properties that matter for the target task, so synthetic datasets still require validation for bias, coverage, and realism.