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Forecasting the Demand of Agricultural Crops/Commodity Using Business Intelligence Framework

Forecasting the Demand of Agricultural Crops/Commodity Using Business Intelligence Framework
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Author(s): Satyadhyan Chickerur (KLE Technological University, India), Supreeth Sharma (Akamai Technologies, India) and Prashant M. Narayankar (KLE Technological University, India)
Copyright: 2019
Pages: 18
Source title: Advanced Methodologies and Technologies in Business Operations and Management
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7362-3.ch034

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Abstract

Information technology is playing a very important role in all the spheres of life, starting from healthcare to entertainment. The agricultural community is not far behind in utilizing information technology for increasing the efficiency and productivity of agriculture and allied activities. This chapter proposes how the concepts of BI (business intelligence), BI tools, data mining tools might be used for forecasting the agricultural demand of various crops reliably and more efficiently. The chapter clearly elaborates how BI tools could be used during various stages of ETL (extract, transform, and load) and how cleansed, quality data could be used by data mining tools for forecasting. Experiments are carried out for forecasting the demands for various agricultural crops by using the previous year's demand, and the results are encouraging. The experimental set up involved open source tools like Pentaho's Kettle and Weka.

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