Data Mining for Learning and Practical Application in the Economy

The market economic reforms, the increasing of producer's competition and the need to prevent threats of financial risk require advanced professional features from professionals; increase the responsibility of managers for performance and consequences of decisions. In these conditions, the strategic component of business development is a steady trend of information management processes and efficiency of the organization is determined by using innovative methods and software and hardware for supporting. The purpose of the article is to assess the current state of data mining and an overview of its use in teaching and practice on the example of the agrarian economy. The growth of information flow requires the use of advanced data analysis tools. Data mining ? the collection of modern methods of information processing. The ways of using data mining to study the economic efficiency of agricultural production were grounded. The information source is the average economic performance of agricultural enterprises for 2009-2013 years. Data mining had been performed by using EM ? algorithm and direct classification procedures with using cluster analysis. The three clusters of areas Kirovohrad region were determined. The systematic analysis of the economic efficiency of farms in 21 districts of Kirovohrad region was conducted and it was established a rational direction and value of basic industries of agriculture, which provides maximum profit from 1 hectare of agricultural land. The analysis showed (for 21 districts) the rational direction of specialization of agricultural production, ensuring maximum profit from 1 hectare of agricultural land: the proportion of grains and oilseeds - 39 and 39%, and livestock production - not less than 12%.