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Synthetic data is data that is generated through algorithms and computational methods, rather than being derived from real-world events. It replicates the properties of real data without the troubles of capturing it, such as confidentiality, low-volume, or expensive-to-validate. Synthetic data can be used to train AI models, however, it is not a panacea and may not fully represent the unexpected events that happen in the real world. This article provides an overview of synthetic data, its uses, benefits, and challenges, as well as how it is generated.
