Data-intensive computing has been receiving much attention as a collective solution to address the data deluge that has been brought about by tremendous advances in distributed systems and Internet-based computing. An innovative programming models such as MapReduce and a peta-scale distributed file system to support it have revolutionized and fundamentally changed approaches to large scale data storage and processing. These data-intensive computing approaches are expected to have profound impact on any application domain that deals with large scale data, from healthcare delivery to military intelligence. A new forum called big-data computing group has been formed by a consortium of industrial stakeholders and agencies including NSF and CRA (Computing Research Associates) to promote wider dissemination of the big-data solutions and transform mainstream applications. Given the omnipresent nature of large scale data and the tremendous impact they have on a wide variety of application domains, it is imperative to ready our workforce to face the challenges in this area. This project aims to improve the big-data preparedness of diverse STEM audience by defining a comprehensive framework for education and research in data-intensive computing.