For this episode of Craft Beer and Data, Mark and I hung out with Eric Matelski, tap-room manager at the Epic Brewing Company, and talked about how Big Data is transforming the agricultural industry. But first, Eric told us about one of his favorite beers (lately), Falling Monk:
“This is a beer we made for Falling Rock Tap House here in Denver that celebrates their 20th anniversary. It’s barrel aged in bourbon barrels with two different types of cherries and fresh almonds.”
For more about the ales and Epic Brewing, watch the video, above, or come visit Eric in the River North District of Denver!
Big Data is creating digital transformation
Everyone understands that Big Data is a technology that can be used, that there are new frameworks for processing it. But what are the benefits to a particular industry?
So we thought we would take a section of our video series and really focus in on how data transitions, digitizes, and improves certain industries.
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Does agriculture need Big Data?
By 2050, it’s been estimated that the population will grow to over 9 billion people. What that means is we need to find ways to produce and distribute food at double the current rate. This is especially challenging when you consider that 40% of the earth’s surface is already used for agriculture.
However, over a third of all food produced is either lost or wasted through the entire production process. Even if you’re just worried about the wasted money, it’s estimated that the wasted food has about a $940 billion impact on the global economy.
There’s clearly a need for more use of data in agriculture and the food industries.
The four Vs of Big Data in agriculture
There are definitely some ways that the agricultural industry is already using data. Much of the farming industry uses it throughout their processes.
Let’s look at the big Vs of Big Data at work in agriculture through the production of the crops and the data that brings in:
For years, John Deere has had sensors on their farming equipment to capture information and data. They, and other seed companies, even using satellite imagery to help farmers determine where they do and don’t need to spray certain pesticides.
This also speaks to variety and velocity, because the data is coming from everywhere. John Deere is really only one of the major farm and tractor companies out there — there are plenty of companies doing exactly the same thing bringing data that looks different.
Then, there’s a huge discussion in the agricultural sciences about how you should collect and store this data. It is coming in from every angle.
Big Data applications in agriculture
Big Data and machine learning are huge in predicting things like when you might want to use certain pesticides. The US has regulations around not using certain pesticides 24 hours before a “predicted rain storm” of more than an inch of rain. So how do you get that information out to the farmers who are about to spray their fields?
One Talend customer is trying to help farmers better understand their soil. They have found this really interesting way of providing a mobile lab that these farmers can use, because it’s currently very expensive to get a soil analysis. They’ve also built a hand-held x-ray machine that takes a soil analysis to figure out things like nitrogen and potassium levels, and which types of fertilizers or crops can be used to make adjustments in the soil.
Agribusiness Big Data in the cloud
The cloud is a huge topic in agribusiness right now. The scope of available data is pushing most industries to cloud environments, but there’s an added challenge in the agriculture industry. Check out the full episode, above, for more on this conversation.
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Watch the whole episode of Craft Beer and Data for more on Big Data in agriculture, including a story about a coder in Japan who owned a cucumber farm, concerns about how all this data might be used against farmers, and more.
And catch up on all of Season 1 on YouTube.