Analytics in agriculture involves the use of advanced data analysis techniques to gather, interpret, and apply information from various sources such as sensors, satellites, and historical records.

In agriculture, IoT enables real-time monitoring of factors like soil moisture, temperature, and crop growth. This data-driven approach enhances precision farming, allowing farmers to make timely decisions, optimize resource use, and improve overall efficiency and productivity.

Open data in agriculture refers to making agricultural data freely available and accessible to the public. This can include data related to crop yields, weather patterns, soil composition, and more.