Agriculture is one of the most important inventions of human civilization. The development of human civilization and development of agriculture technology were the two wheels of the cart. Unfortunately, it has been witnessed that the development of agriculture technology is not in the same ratio as human civilization is developed. Traditional tools and techniques used for forming are neither sufficient to predict nor, to optimize production results of yield. The agricultural data is diversified, complex and non-standard and information available about agriculture is in the form of static maps or tables or reports. Such information is not flexible enough to provide quick answers to the queries of farmers and decision makers. In this view the computerization of agricultural data is increasing need for economist and decision makers. Data warehouse technology is a dynamic and versatile technology capable of providing information to farmers for efficient planning and implementation. Historically, data warehouses have been implemented in marketing and financial institutions. However, a remarkable shift in agricultural practices has occurred over the past century in response to new technologies. This also led to design an agriculture data warehouse and provide a decision support system, based on OLAP and data mining techniques. In the absence of computational model, an enormous amount of redundancy of data is observed, it increases complexities in OLAP. To overcome this redundancy in operational data, a mathematical procedure is needed for computation of decision coefficient. In this manuscript, we are introducing a computational model to optimize cropping system that leads to design of data warehouse for agriculture.

Agriculture Technology Data Warehouse Computational Model Decision Support System