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In this session, Dr. McCoy will introduce OptumLabs Data Warehouse (OLDW), a new big data resource that is available (with funding) to University of Maryland Baltimore investigators. She will discuss what data are included in OLDW, the types of studies that have been successfully conducted using these data, and the cost and process for data acquisition. She will also compare and contrast OLDW with other secondary data sources, including electronic health records and other available claims databases, to help determine what dataset is most appropriate for your research needs. Dr. Rozalina McCoy is Associate Professor of Medicine and the Associate Division Chief for Clinical Research in the University of Maryland School of Medicine’s Division of Endocrinology, Diabetes, and Nutrition. She also serves as the Director of Precision Medicine and Population Health in the University of Maryland Institute for Health Computing, where she leads interdisciplinary research efforts focused on improving the health and wellbeing of the people of Maryland and beyond. Dr. McCoy's research, funded by the NIH, PCORI, and the American Diabetes Association, leverages real-world data to improve the quality, accessibility, and sustainability of diabetes care on both the individual and population levels. Her methodologic expertise spans observational, interventional, and mixed methods study designs, including use of machine learning/artificial intelligence modeling methods; causal inference methods to emulate trials using real-world data; and pragmatic, point-of-care, and decentralized clinical trials of patient-centered interventions.