As more of commerce, entertainment, communication, and learning are occurring over the Web, the amount of data online activities generate is skyrocketing. Commercial entities have led the way in developing techniques for harvesting insights from this mass of data for use in identifying likely consumers of their products, in refining their products to better fit consumer needs, and in tailoring their marketing and user experiences to the preferences of the individual. More recently, researchers and developers of online learning systems have begun to explore analogous techniques for gaining insights from learners' activities online. This issue brief describes data analytics and data mining in the commercial world and how similar techniques (learner analytics and educational data mining) are starting to be applied in education. The brief examines the challenges being encountered and the potential of such efforts for improving student outcomes and the productivity of K--12 education systems. The goal is to help education policymakers and administrators understand how data mining and analytics work and how they can be applied within online learning systems to support education-related decision making.