The Big Basics of Big Data for Farming Operations
4 December 2017
grower, you’ve undoubtedly already heard the buzz of “big data” and the impact it’s
making on the ag industry. Creating a strategy to collect and harness large
amounts of data can offer growers real, useful and valid information they can
use to better their operation. A study released in April 2016 conducted by DNV
GL-Business Assurance and GFK Eurisko found that 76 percent of respondents in the business world were already
tapping into the power of big data…and they
planned to continue to do so. But despite this impressive figure, the study
also found that only one out of four businesses surveyed were actually able to
leverage big data findings effectively.
Understanding the potential applications of this new technology can help your growing operation reach its full potential for productivity and profitability in the competitive agricultural marketplace. So where do you go from here? We’ll break it down for you.
What Is Big Data?
Simply put, big data involves collecting large quantities of information from multiple sources.
Once you have all the information, it’s compiled and analyzed to create models that can be used to both assess current performance and predict future events in a particular industry.
it’s still in the early stages of development in the business world, the study
above suggests that major industries (such as agriculture) are quickly
beginning to realize the huge opportunities these technologically advanced data
mining techniques can offer.
Farming as a Test Study
The same strategies used to implement precision farming in large-scale operations are also used in big data mining to create a “big picture” look at many factors in the working environment. A recent Fortune article demonstrates the use of big data techniques in a large-scale dairy and crop production operation:
- Land O’Lakes is currently using Google Cloud as
a jumping-off point for its big data mining and analytics processes. The large
scale operation is incorporating data from:
- weather and climate prediction services
- drone flights
- on-site testing of hybrid seeds and test
- soil analysis
- historical performance reports
The findings are allowing the company to make the best possible use of its resources to boost productivity and increase its profitability in a highly competitive marketplace. Additionally, Land O’Lakes is also using the geospatial mapping capabilities already built into Google to deliver accurate plotting and geographical information for all its growing and dairy farming operations.
By storing data from many disparate sources in one place, companies like Land O’Lakes can manage their own precision farming activities to ensure the best possible results from test crops and other growing processes. Companies that offer precision farming services perform similar data mining tasks on a smaller scale for agricultural operations across the U.S. As growers take more control over these activities, they can tailor their big data analytics to suit their needs more precisely.
What Are the Tools of the Trade?
Big data implementations in the agriculture industry generally use a variety of tools to gain data that’s wildly useful to growers. Sensors, drones, GPS tracking devices and historical data can all be uploaded to a centralized storage server for analysis.
By its very nature, big data cannot be manipulated or analyzed using traditional management software. Instead, advanced analytics software is necessary to consolidate and categorize data and then condense it into a usable form for businesses. Since agricultural applications for big data seem to have lagged behind some other industries, growers can likely expect to see huge advances in the features and capabilities that are available specifically for the agricultural industry over the next few years.
Creating a New Paradigm
Thus far, we’ve addressed only the general outlines of the big data revolution in business and agriculture. Before we get down to the nitty-gritty of big data implementations, it’s important to understand the changes that this advanced technology could generate for the industry.
When large quantities of data can be mined for actionable information, agricultural operations will be able to determine the viability of various strategies, not to mention they’ll also be able to see crystal clearly the most profitable ways to grow crops without the expense of failed trials and wasted efforts.
What Are the Concerns?
As with any new technology in an industry, new concerns will also arise with the paradigm created by big data analytics. Some of the major apprehension seems to stem from the following issues, which are likely to become even more critical for growers as the technology advances and becomes more widely implemented:
- ownership of private data
- access to public information
- reliable connections to Internet sources
issues may also arise, creating challenges and opportunities for large-scale
operations as growers begin the process of integrating big data into their
ongoing planning and oversight activities.
We intend this only as an introduction to the role big data will increasingly play in the modern farming environment. In later posts, we’ll further tackle this not-so-simple issue, addressing the reasons behind big data innovations and many other applications for the new technology. If you’re considering implementing big data tools and strategies in your own agricultural business model, be sure to check back for more in-depth information about this exciting emerging trend in the industry.
To continue learning more about big data, check out part two of our series here: Big Data Series: Why You Need It and How to Implement It
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