Tim Stombaugh Biosystems and Agricultural Engineering

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Presentation transcript:

Tim Stombaugh Biosystems and Agricultural Engineering Big Data, Big Headaches Tim Stombaugh Biosystems and Agricultural Engineering

Outcomes Describe different types of data Understand the current state of the ag big data industry Be able to help other farmers navigate the big data world

“Big Data” Large Data Sets Variety Velocity Require unique analysis techniques Variety Velocity Patterns, trends, and associations

What do we mean by Data? Machine Data Production Data Telematics

Data Performance (Outputs) Management (Inputs) yield, moisture, oil content, protein, runoff/leaching Management (Inputs) inputs, scouting, field management, machine data Environmental (Stuff I can’t change) weather, soil type, slope, field boundary issues Economic prices, interest, taxes, loans, insurance, capital Human Resources wages, reliability, efficiency, productivity

Telematics When the machine phones home Connectivity Internet of Things

Cloud Computing Storing data on a server somewhere That server does the computation Accessibility Multiple points Multiple users Security Back-ups

Applications Fleet Management Secure Storage Data Access – prescriptions, yields, Data analysis Prescription Generation Real-time adjustments Market leverage Performance Management Environmental Economic

State-of-the-Art (Farmers) Telematics common New machines connected Remote access Fleet management Data access (prescriptions, yield data, etc.) Data mining from machine data Basic data processing Prescription generation

The Players Farmers Regulators Landowners Watchdog groups Neighbors Investors Service Providers Consumers SP Competitors Input Suppliers Machine Mfgrs. Buyers

What other players want? Value of data? Examples Machinery companies Chemical companies Buyers Watchdog groups Models: trading analysis tools for data

Farmer Challenges Metadata Connectivity Data ownership Data access Think beyond production practices Long-term impacts

Metadata Data that describes the data Adds to value of data Critical to interpretation

Connectivity Cellular coverage Data plans Internet bandwidth

Data Ownership/Access Cloud storage facilitates multiple access points Ownership must be considered in contracts Fine print/implied Accessibility if changing providers

Thinking Outside the Box More of a business model New terminology Work Orders Receivables Inventory Efficiency More than marketing (selling) product

Long Term Impacts Sustainability of management strategies Risk nutrientstar.org

Wrap-Up What is ag big data? How is it being used? What is its potential? How are farmers going to have to respond?

Tim Stombaugh Biosystems and Agricultural Engineering Big Data, Big Headaches Tim Stombaugh Biosystems and Agricultural Engineering