The past ten years have seen a revolution in two disciplines related to operations and strategy design. “Big Data” has transformed the theory and practice of producing and selling goods and services through methods associated with computer science and information technology. “Analytics” has popularized primarily quantitative models and methods by which organizations and systems can measure multiple aspects of performance. As these fields rely on information technology to collect, store, process and share data, we refer to the collection of knowledge and applications associated with Big Data and analytics as “data analytics and information technology.” The impacts of data analytics and IT are most visible in the actions of for-profit organizations and government. However, the not-for-profit sector has a more ambivalent relationship with Big Data, analytics and information technology. This is particularly true for, mission-driven community-based organizations with limited budgets and small staffs. What role can the Big Data and analytics movements play for nonprofit organizations, especially community-based organizations, and the communities they serve? How can the argument be made that substantial investment by nonprofits in data- and analytics-related technologies and processes are worthwhile? This paper reviews the current state of research and practice of data analytics and information technology with a focus on community-based organizations. I argue that there are a number of dimensions along which the needs of CBOs with respect to data and analytics differ markedly from other organizations. Through descriptions of technologies that support data analytics for nonprofit organizations, and frameworks for data-driven analysis, I develop principles to support theory development for CBO data analytics and IT, and perform field research to evaluate propositions related to capacity of CBOs to make productive use of date. Finally, I describe opportunities for specific research projects that that will serve as an opportunity for theory-building, data analysis and information technology solution design.