The Cross-Industry Standard Process for Data Mining (CRISP-DM), despite being the most popular data mining process for more than two decades, is known to leave those organizations lacking operational data mining experience puzzled and unable to start their data mining projects. This is especially apparent in the first phase of Business Understanding, at the conclusion of which, the data mining goals of the project at hand should be specified, which arguably requires at least a conceptual understanding of the knowledge discovery process. We propose to bridge this knowledge gap from a Data Science perspective by applying Natural Language Processing techniques (NLP) to the organizations’ e-mail exchange repositories to extract explicitly state...