The 2002 reauthorization of the Elementary and Secondary Education Act mandates that schools receiving federal funding must desegregate their student performance data by race, gender, and socioeconomic status in order to provide progress information to the community and state. Data-driven decision making is particularly important in urban schools whose populations are disproportionately poor, minority, and in need of special services. This digest discusses the types of data that schools should collect and the ways to use the information effectively in decision making to enhance equity. It begins by explaining how to use data to enhance quality, then it describes data types (student learning data, student demographics, perceptions data, and school process data). It goes on to explain the disaggregation of data, which allows schools to determine more accurately the effects of programs and strategies on segments of its student body. Finally, this digest explains data-driven decision making and describes how to choose a technology tool to support data-driven decision making (functionality, data storage capacity, training, and format). A sidebar presents data disaggregation tools. Data support resources are listed. (SM)