Organizations run on data. They use it to manage programs, select products to fund or develop, make decisions, and guide improvement. Data comes in many forms, both structured (tables of numbers and text) and unstructured (emails, images, sound, etc.). Data are generally considered high quality if they are fit for their intended uses in operations, decision making, and planning. This definition implies that data quality is both a subjective perception of individuals involved with the data, as well as the quality associated with the objective measurements based on the data set in question. This post describes the work we’re doing with the Office of Acquisition, Technology and Logistics (AT&L)—a division of the Department of Defense (DoD) that oversees acquisition programs and is charged with, among other things, ensuring that the data reported to Congress is reliable.