Big Data in U.S. Agriculture, Megan Stubbs, Specialist in Agricultural Conservation and Natural Resources Policy. January 6, 2016 – “Recent media and industry reports have employed the term big data as a key to the future of increased food production and sustainable agriculture. A recent hearing on the private elements of big data in agriculture suggests that Congress too is interested in potential opportunities and challenges big data may hold. While there appears to be great interest, the subject of big data is complex and often misunderstood, especially within the context of agriculture. There is no commonly accepted definition of the term big data. It is often used to describe a modern trend in which the combination of technology and advanced analytics creates a new way of processing information that is more useful and timely. In other words, big data is just as much about new methods for processing data as about the data themselves. It is dynamic, and when analyzed can provide a useful tool in a decision making process. Most see big data in agriculture at the end use point, where farmers use precision tools to potentially create positive results like increased yields, reduced inputs, or greater sustainability . While this is certainly the more intriguing part of the discussion, it is but one aspect and does not necessarily represent a complete picture. Both private and public big data play a key role in the use of technology and analytics that drive a producer’s evidence-based decisions. Public-level big data represent records collected, maintained, and analyzed through publicly funded sources, specifically by federal agencies (e.g., farm program participant records and weather data) . Private big data represent records generated at the production level and originate with the farmer or rancher (e .g ., yield, soil analysis, irrigation levels, livestock movement, and grazing rates) . While discussed separately in this report , public and private big data are typically combined to create a more complete picture of an agricultural operation and therefore better decision making tools.”