Community-based organizations use data for program design, services provision and strategic planning. However, CBOs often have limited ability to identify, access and apply these data. Thus, CBOs may make decisions on the basis of inadequate data, or limited understanding of the local environment, or limited ability to generate mission-aligned solutions.Community data analytics (CDA) uses local know-how and clearly-articulated values in order to transform data into action. CDA is rooted in principles of operations research and management science for public benefit. These principles include: active participation by local stakeholders to identify problems of interest; a critical perspective on issues of problem and solution design; appropriate technology, and local control of solution implementation. This presentation features two examples of current research in community data analytics: planning and decision support for land use in declining regions and blighted communities, and community-derived measures of local economic development success. These cases yield insights into ways that urban communities can assert control over local development at a time when the smart cities and big data movements represent as-yet unfullled potential for local development and revitalization.