Summary

In this module, we introduced you to the key concepts related to data in farming and agriculture. The application of new technologies and tools in digital agriculture represents a growing opportunity to create new value for your farm and to build the success of the wider Canadian agri-food value chain. 

There are many ways that agricultural data can be collected, and there are even more ways to think about how this data can be organized. Go back and take a look at the 📁⁠⁠Catalogue of Agriculture Data⁠  - there are a wide range of data sources on farms and inside farm businesses that fall into six broad categories: agronomic data, livestock data, land data, farm management data, machine and equipment data, climate and weather data. If we zoom out to look at the wider agri-food value chain, these data are constantly flowing between different software tools, pieces of machinery and stakeholders in the agriculture data ecosystem. As a farmer you play a central role as one of the primary data originators, or data collectors.  

Of course, putting data to work on your farm isn’t easy. Producers run into a whole host of challenges connected to technology adoption. Obstacles ranging from cost, to data quality and internet connectivity, can put a dent in your ability to leverage digital agriculture tools and agriculture data in your operation. For this reason, it’s critical to be aware of these issues and to take the necessary steps to work around them where possible. 

Now let’s turn our attention to putting your agriculture data to action. Building on the data ecosystem map that you just created in the exercise at the end of the module, you are now in position to move onto Module 3, which looks at data management principles that enable you to work effectively with your data on-farm. 



Looking ahead - the next step is  💻⁠⁠Module 3: Working with Data⁠ .

This third module will cover the importance of strong data management practices on-farm.