Abstract <p>The relevance of this research is determined by the development of digital technologies and the digital transformation of enterprises. The complexity is the modeling of business automation and innovation management, requiring methods of applied research management and the consideration of technology readiness. The purpose of this paper is to build an automation model in Orange analytical and simulation modeling environment. Descriptive, analytical and data discovery methods are used to achieve the research objective. The object of the study is the approaches to building a technology landscape. The subject of the study is the analysis of models and tools based on data mining. The result of the study is found in the developed model of automation based on intelligent data analysis, realized in the form of a conceptual scheme that can be used to build a technological landscape of innovative solutions at enterprises and conclusions are made about the feasibility of using this model.</p>

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Building a Technological Landscape of Innovative Solutions Based on Data Mining

  • V. A. Shiboldenkov,
  • D. M. Kkhan

摘要

Abstract

The relevance of this research is determined by the development of digital technologies and the digital transformation of enterprises. The complexity is the modeling of business automation and innovation management, requiring methods of applied research management and the consideration of technology readiness. The purpose of this paper is to build an automation model in Orange analytical and simulation modeling environment. Descriptive, analytical and data discovery methods are used to achieve the research objective. The object of the study is the approaches to building a technology landscape. The subject of the study is the analysis of models and tools based on data mining. The result of the study is found in the developed model of automation based on intelligent data analysis, realized in the form of a conceptual scheme that can be used to build a technological landscape of innovative solutions at enterprises and conclusions are made about the feasibility of using this model.