Precision agriculture is used in a wide variety of field operations and agricultural practices that affect our daily lives. Many fields of agriculture are increasingly adopting equipment automation, robotics, and machine learning techniques. These all lead to recognize that data collection and exploitation is a valuable tool assisting in real-time farming and livestock decisions. Thus, the immediate need to empower students in Agriculture Sciences with mathematical tools using data analysis is more imperative than ever before. Such tools will better prepare them for the challenges they face while working with data analysis and models in the context of Internet of Things (IoT). This paper aims to summarize previous experience in teaching Mathematics using data analyses as motivation to important Mathematical concepts towards applications in the area. This is a result from a thorough research and discussion with colleagues among many areas of applications within the field of Agriculture Sciences, which is in itself a rich interdisciplinary field. The examples gathered from this work were then used as motivation for teaching Mathematics to agriculture engineering students based and data analysis, aimed to prepare them towards using these tools more effectively not only throughout their degree, but helping to advance the field towards precision agriculture. I will describe a few instances of how data obtained from the literature are contextualized to present the concepts of functions, derivative and integration, multivariable functions, and linear algebra. In this one-year course, the students were introduced to and got familiarized with concepts and laws that would help them into to succeed in Soil Physics, Statistics, Meteorology, Topography, Economics, Biology, and so on. Besides sharing this experience, the idea here is to stir in the community this new paradigm for teaching Mathematics in the field of Agriculture Sciences.