The study of data analytics can be divided in traditional data analytics and big data analytics. The main processes are input, processing and output, and the framework of the analytics is determined on the basis of perspective-oriented and result-oriented concerns. The tools used for processing the data analytics environment are Apache, SPSS, Storm, Dryad, R, Tableau, Japer software. These are the various tools used for big data as well (Acharjya 2016).
Descriptive analytics is one of the method analytics which analyses the past data with summary of the data. In agriculture, crop yield data for 10 years is collected and descriptive analytics is applied on the data. KNN algorithms are also applied on the data. Accuracy is then measured for the KNN algorithm with root mean square error value (Renuka 2019). Predictive analytics helps to analyse the past data and forecast the future trend according to the data. Autoregressive integrated moving average (ARIMA) model is used to forecast the data and then SVM, KNN and ordinary least square are used for crop prediction (Kumar et al. 2018).
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