So, data tagging typically involves assigning keywords or metadata to data for organization, while data labeling refers to the process of annotating data to train machine learning models. Labels can signify the sensitivity of the contents of a file or email. Tags, in turn, can associate friendly business terms with technical structured data in a database or data warehouse.
Take for example the generative AI labeling process. Here, annotated data is used to teach generative AI models to create content, facilitating the development of realistic outputs by these advanced systems.