Description: Augmented Data refers to information that has been enhanced by adding context or additional details, allowing for a deeper and more accurate understanding of the original data. This process involves integrating various sources of information, which may include contextual data, metadata, or data generated by artificial intelligence models. The idea behind augmented data is to enrich the quality of the data to facilitate analysis and improve decision-making. In the realm of artificial intelligence and machine learning, augmented data is fundamental, as it enables models to learn more complex patterns and make more accurate predictions. Furthermore, this technique is particularly valuable in the context of Big Data, where the amount of information can be overwhelming and the quality of the data can vary significantly. By providing additional context, augmented data helps mitigate issues such as noise in the data and lack of representativeness, resulting in more robust and effective models.
