Data Science Techniques & Applications - Workflow

Editor's note: In their book, "Data Science: Concepts and Practice," authors Vijay Kotu and Bala Deshpande explain the core principles and applications of modern data science. Kotu is vice president of analytics at ServiceNow; Deshpande is a data scientist and consultant. This article, which focuses on primary applications of data science, is adapted with permission. Data science problems can be broadly categorized into supervised or unsupervised learning models. Supervised or directed data science tries to infer a function or relationship based on known (labeled) training data and uses this function to map new unknown (unlabeled) data--for example, predicting if a current customer will not return based on the behaviors of all customers who have left before.