Discussions around "Big Data" -- and farmers beginning to use the tools known as "data science" to make business and production decisions -- took real steps forward in 2015. While there was much reporting on small pieces of this story during the year -- new companies launched, new partnerships created -- the sum of all those steps marked the beginning of the coming of age of Big Data as an industry.
One sign of that dawning was the progress of companies such as Granular, Farmers Network, Winfield, Climate Corporation, FarmLink and a host of others signing up paying customers (beyond beta testers) and the beginnings of success stories from some of those growers.
Another sign, arguably, of data science making tangible progress was that the actual discussion around the "data" portion of Big Data began to change. Late-year discussions on the topic centered more on what can be -- and has been -- learned by bringing agriculture into the digitized world, and revolved less around the contentious issue of who owns the data. While data security and privacy of critical business information are still concerns, in general the conversation has begun to focus more on what are the returns on investment and how quickly those paybacks come.
At the 2015 DTN/The Progress Farmer Ag Summit in Chicago, a panel of Big Data big wigs discussed that coming of age. The panel included Pat Christie, CEO of Conservis; Sid Gorham, co-founder and CEO of Granular; and Ron LeMay, founder and head of FarmLink. Much of the discussion was on the need for farmers to start thinking about the accuracy and the "cleanliness" of the data they can gather from equipment and other places.
"Little differences make all the difference," LeMay told farmers in the session. "In some areas if you get it a little bit wrong you're going to pay a big price, so there needs to be a lot of care in the way data is collected and managed."
One of the biggest untapped, yet relatively clean, sets of data for most farm operations is the mountain of financial information trapped away in Excel. "That data is mostly very straightforward, and quick to access," said Gorham. Collected and run through the right data analysis tools, that information should quickly begin to allow farmers compare issues across crop years in a way not possible in standard spreadsheets.
Agronomic data, such as information gathered from combine yield monitors and sprayer "as-applied" maps may or may not be free of errors. "But don't let perfect be the enemy of good," Gorham said. "This [data science effort] is part of a long game; this is part of farming forever. Get after it."
"I understand people want perfect, they want the answer from the black box," FarmLink's Ron LeMay said at the DTN Ag Summit. "It doesn't work that way." Digitization of information and cloud analytics don't provide big, revolutionary answers, he and other data experts said. It's more about being involved in "a cycle of continuous improvement."
Greg Horstmeier can be reached at firstname.lastname@example.org
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