{"id":14830,"date":"2021-03-20T14:00:35","date_gmt":"2021-03-20T12:00:35","guid":{"rendered":"https:\/\/modecon.mnau.edu.ua\/?p=14830"},"modified":"2021-03-22T13:06:17","modified_gmt":"2021-03-22T11:06:17","slug":"theoretical-principles-of-implementation-and","status":"publish","type":"post","link":"https:\/\/modecon.mnau.edu.ua\/en\/theoretical-principles-of-implementation-and\/","title":{"rendered":"Burlakov A., Mushenyk I. Theoretical Principles of Implementation and Use of Modern Technologies of Intellectual Data Analysis in Economy"},"content":{"rendered":"

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JEL Classification<\/strong>: C 88, M 12, L 86, J 21.
\n<\/span><\/td>\n		DOI<\/b>: https:\/\/doi.org\/10.31521\/modecon.V25(2021)-04<\/a><\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

[\/vc_column_text][vc_column_text]<\/p>\n

Burlakov Alexandr<\/strong>, PhD in Economic, Assistant Professor at the Department of Accounting, Taxation and E-business Technology, State Agrarian and Engineering University in Podilla, Ukraine<\/p>\n

ORCID:<\/strong> 0000-0003-2753-3600<\/a>
\ne-mail:<\/strong> alexburl1982@gmail.com<\/a><\/p>\n

Mushenyk Irina<\/strong>, PhD in Economic, Assistant Professor at the Department of Mathematical Subjects, Computer Science and Modeling, State Agrarian and Engineering University in Podilla, Ukraine<\/p>\n

ORCID:<\/strong> 0000-0003-4379-7358<\/a>
\ne-mail:<\/strong> mushenik77@ukr.net<\/a><\/p>\n

Theoretical Principles of Implementation and Use of Modern Technologies
\nof Intellectual Data Analysis in Economy<\/h2>\n

 <\/p>\n

Abstract. The aim of the article<\/strong> is to study the theoretical foundations of the introduction and use of modern technologies of data mining in the economy of Ukraine.<\/p>\n

Research methodology.<\/strong> The theoretical and methodological basis of the article were the works of leading foreign and domestic scientists on the evaluation of the effectiveness of the implementation and use of data mining technologies. Achieving this goal was carried out using the following scientific techniques and research methods: monographic (in reviewing and studying the literature on evaluating the effectiveness of data mining technologies), analysis and synthesis (for research and generalization of research results); logical-theoretical and dialectical (to form the conclusions of the study). In the process of research, the substantiation of theoretical calculations and conclusions was carried out on the basis of system-functional and structural approaches to the analysis of information flows and control systems of data mining technologies. The information base of the study is articles and monographs, including those posted on web pages.<\/p>\n

Results of the research.<\/strong> The theoretical bases of functioning of modern technologies of data mining in the information economy are systematized, and also questions of the basic directions of application of the Data Mining system are analyzed, namely as a mass product for business applications and as a tool for unique researches.<\/p>\n

Scientific novelty of research results.<\/strong> It consists in the theoretical substantiation of possibilities of introduction and application of modern technologies of intellectual analysis, in various branches of economy, as effective tools of providing the timely information for the management of business entities on the basis of which it is possible to make qualitative administrative decisions.<\/p>\n

The practical significance of the research results.<\/strong> The obtained results can be used for further prospective research of information systems of economic entities, which are created on the basis of modern data mining systems, as well as in the implementation of computerization tools for analytical and synthetic data processing of information systems in the enterprise.<\/p>\n

Keywords:<\/strong> information system; data mining; information technology; data mining.<\/p>\n

References:<\/strong><\/p>\n

    \n
  1. Kassambara, A. (2017) Practical Guide to Cluster Analysis in R: Unsupervised Machine Learning. Statistical tools for high-throughput data analysis STHDA. Retrieved from: http:\/\/www.sthda.com\/<\/li>\n
  2. Ian H. Witten, Eibe Frank & Mark A. Hall. Data Mining (2011). Practical Machine Learning Tools and Techniques (3rd ed), Morgan Kaufmann.<\/li>\n
  3. Barsegyan, A.A., Kupriyanov, M.S. & Stepanenko, V.V. (2010). Tehnologii analiza dannyih: Data Mining, Visual Mining, Text Mining, OLAP. SPb: BHV-Peterburg [in Ukrainian].<\/li>\n
  4. Burlakov, O.S. (2013). \u201cRisk management of IT outsourcing in the current economic conditions\u201d. Innovatsijna ekonomika, 8[46], 341-343. Retrieved from: http:\/\/nbuv.gov.ua\/j-pdf\/inek_2013_8_76.pdf [in Ukrainian].<\/li>\n
  5. Burlakov, O.S. (2013). IT outsourcing as a tool for optimization of enterprises, Stalyi rozvytok ekonomiky, 4[42], 90-93 [in Ukrainian]..<\/li>\n
  6. Burlakov, O.S. (2013). E-commerce as a means of improving sales activity agroformations, Innovatsiina ekonomika, 1[39], 306-308 [in Ukrainian].<\/li>\n
  7. Gavrilenko, V.V., Ivanchenko, G.F. & Shevchenko G.E. (2012). Methods and technologies of data mining. Visnik NTU, 2, 491-497.<\/li>\n
  8. Kinash, I. A. (2012). Farm management of information technology, Stalyi rozvytok ekonomiky, 2(12), 50-53 [in Ukrainian].<\/li>\n
  9. Ostaletskyi, V.B. (2015), \u201cTheoretical approaches to the classification of information management systems\u201d, Ekonomichnyi visnyk Natsionalnoho tekhnichnoho universytetu Ukrainy \u00abKyivskyi politekhnichnyi instytut\u00bb, no. 12, pp. 294-299.<\/li>\n
  10. Chuprina, M. O., Shekhovtsova, I. A. (2016), \u201cUse of IT tools to optimize the management of business processes in Ukrainian enterprises\u201d, Ekonomichnyi visnyk Natsionalnoho tekhnichnoho universytetu Ukrainy \u00abKyivskyi politekhnichnyi instytut\u00bb, no. 13, pp. 324-329.<\/li>\n<\/ol>\n

    [\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]Received:<\/strong> 09 January 2021<\/p>\n

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    Burlakov A., Mushenyk I. (2021). Theoretical Principles of Implementation and Use of Modern Technologies of Intellectual Data Analysis in Economy. Modern Economics<\/em>, 25(2021), 27-32. DOI: https:\/\/doi.org\/10.31521\/modecon.V25(2021)-04.<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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    [vc_row][vc_column][vc_column_text] JEL Classification: C 88, M 12, L 86, J 21. DOI: https:\/\/doi.org\/10.31521\/modecon.V25(2021)-04 [\/vc_column_text][vc_column_text] Burlakov Alexandr, PhD in Economic, Assistant Professor at the Department of Accounting, Taxation and E-business Technology, State Agrarian and Engineering University in Podilla, Ukraine ORCID: 0000-0003-2753-3600 e-mail: alexburl1982@gmail.com Mushenyk Irina, PhD in Economic, Assistant Professor at the Department of Mathematical Subjects,
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