AG 201 - Data-driven Decision Making

3 Credits

This course is an introductory class in agricultural data collection and decisions based on data currently available in Western Canada. Discussions will involve the understanding of the volume of agricultural data being collected, the ethics involved with data collection, process of data collection: extrapolate and current data.  The objective of the course is encompassing the concept of what constitutes a well-constructed inquiry and acquiring the knowledge to make decisions based on gathering data, ensuring the reduction of risk in the management process and attainment of long-term sustainability.

Rationale:

This course is required for second year Agribusiness students. Data collection is significant across western Canadian farms.  Substantial financial investments are linked to on-farm decision-making. While data is being gathered, it may not always be effectively leveraged to streamline these decisions and enhance sustainability. Upon completing this course, students will gain the ability to discern which decisions can be informed by data, locate the necessary data sources, analyze the data, and present in a manner that enables informed decision-making.

Prerequisites: AG 100 , BA 245  
Corequisites: None

Course Learning Outcomes:
 

1. Develop an understanding of data in facilitating informed and sustainable decision-making for Western Canadian Agriculture.
2. Articulate good data questions.
3. Identify pertinent datasets to address data-driven inquiries and support decision-making processes effectively.
4. Discuss ethical data collection uses and management.
5. Apply agriculture specific data management tools to create a data story.

Attendance will be recorded. Students who are absent are responsible for covering the material. All students are expected to demonstrate a high level of participation.

Agriculture Industry experts may be invited to speak on specific topics.

Classroom and laboratory attendance is considered vital to the learning process and as significant to the students’ evaluation as examinations and reports.

1. Students having a combination of excused and/or unexcused absence of 20 percent or higher for the scheduled course hours are required to withdraw and automatically receive a “RW” (required withdrawal) for the course, regardless of any other evaluation results. (RW is a failing grade.)
2. An excused absence is one that is verified with your instructor. Verification should be prior to the absence or the next class day following the absence. Verification of the absence may take the form of a note from your doctor/College nurse regarding illness, or a note from another instructor regarding a field trip or other activity, or authorization by your instructor. An unexcused absence is anything NOT verified by the instructor prior to the absence or the next class day following the absence.

It is the students’ responsibility to know their own absentee record.

Normal hours are 8:30 a.m. to 6:30 p.m., with potential for evening courses, exams, or extended field trips. Students are expected to be available for classes during these times.

Content of Course:
 

1. Purpose of Data Management
2. Ethical Concerns with Data Management
3. Asking Questions that can be Answered with Data
4. Precision Farming and Data Collection Software
5. Collection and Interpretation of Data
6. Data Decisions, the Impact on Long Term Sustainability