Analyzing big data

  • 5 minutes

The curriculum series continues with Section 2, Analyzing Big Data. This section is intended to be taught over the duration of five days. Each day is considered a 45-minute class period. A detailed timeline can be found in FarmBeats for Students Teacher Guide with all activities. Educators should follow the sequential order of instructional days to ensure a cohesive and meaningful learning experience.

Before starting this section, ensure you have these instructional resources and materials:

Teacher documents

  • Teacher Guide - Activity 1.4, Activity 1.5
  • AI4K12 Poster: 5 Big Ideas

Student documents

  • Activity 1.4 Growing Data
  • Activity 1.5 Data-Driven Decisions
  • FarmBeats - Big Data Excel workbook

PowerPoint presentations

  • Big Idea 3: Learning
  • Big Idea 5: Societal Impact

Supplies and materials

  • Computer device
  • Microsoft Excel (or any other data software of your choice)

What is data literacy?

Data literacy is understanding and working with data in a way that helps make better decisions. At its core, it is reading data (like numbers, charts, or trends), figuring out what the data is telling you, and using that information wisely. It's not just for experts—anyone can learn to ask the right questions about data, spot patterns or problems, and use it to answer everyday questions. Think of it as a life skill that helps you navigate the world, which is full of information, in a smarter and more confident way.

Data literacy and AI are deeply interconnected because AI systems are built and trained on data. To understand AI, one must grasp how data is collected, processed, and analyzed. Data literacy equips individuals to critically evaluate the data inputs that shape AI models, including recognizing biases, gaps, or inaccuracies in datasets. This understanding is crucial since the quality of an AI system's output heavily depends on the quality of the data it was trained on.

Explanation of activities

There are two specific activities with Section 2, Analyzing Big Data:

  • Activity 1.4: Growing Data
  • Activity 1.5: Data-Driven Decisions

Activity 1.4 - Growing Data

In this activity, students calculate growing degree units (GDUs) using accumulated temperature sensor readings. To calculate daily GDUs, students find the historical average daily temperature by adding the maximum temperature and the minimum temperature and dividing by two. Then, they subtract the base temperature for their crop.

Activity 1.5 - Data-Driven Decisions

In this activity, students use data intelligence to explore smaller sets of big data. Students use Microsoft Excel Analyze Data to extract data from multiple big data sources to make a key agricultural decision--where to locate new greenhouses.