Data has become a critical advantage for information-driven agencies. By providing unprecedented access to actionable information, agencies can use data to better understand their operations, improve their services, and ultimately fulfill their mission requirements. To access this information, agencies need to be able to effectively operationalize data across their operations. This includes discovering and embedding past-, present-, and future-looking analytics into their end users’ workflow in order to move the metrics that matter. However, if this data doesn’t reach the end consumer in a timely manner, then data is left out of analyses, latency occurs in applications, and end users don’t get the information they need. This, in turn, causes a negative return on data investments and agency inefficiencies at the operational level. As large volumes of data continue to be operationalized across the government, pressure is put on existing data infrastructure, causing challenges to arise. These challenges have compelled federal agencies to rethink how they approach data management by revamping their architecture to support this new way of business. By implementing an operational data store (ODS), designed for a big data world, these forward-looking organizations have complemented their existing data infrastructure to support the current and future needs of government.