Synthetic data refers to artificially generated information that replicates the characteristics and patterns of real-world data, produced using algorithms and statistical models. This type of data is invaluable in scenarios where actual data is scarce, costly to acquire, or involves sensitive information that cannot be shared. By providing a cost-effective and scalable alternative, synthetic data enables organizations to conduct machine learning training, software testing, and research without the limitations associated with real data. Its applications are especially prominent in fields like healthcare, finance, and autonomous driving, where data privacy and accessibility are critical concerns.
