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

2. 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

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

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

5. 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

6. Telematics When the machine phones home Connectivity
Internet of Things

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

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

9. 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

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

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

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

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

14. Connectivity
Cellular coverage
Data plans
Internet bandwidth

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

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

17. Long Term Impacts Sustainability of management strategies Risk
nutrientstar.org

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

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