The three pillars of farm analytics are Data collection and management: This involves collecting and organizing data from various sources such as sensors, weather stations, farm equipment, and other relevant sources. The data is then stored in a centralized database where it can be easily accessed and analyzed. Data analysis and modeling: This involves using statistical and machine learning techniques to analyze the collected data and develop predictive models. This helps farmers to make informed decisions about crop management, irrigation, fertilization, and other important aspects of farming. Decision-making and action: This involves using the insights gained from data analysis to make informed decisions and take action to optimize farm operations. For example, farmers can use analytics to adjust irrigation schedules, optimize crop yields, and improve resource allocation.