Opportunities for a New Content and Methodological Line “Big Data Analysis” to Modernize the Training System of the Future Economist

The aim of the study is to apply the theory of pedagogical technologies to reveal the possibilities of the new content and methodological line “Big Data Analysis” in the aspect of modernizing the training system of the future economist.

Materials and methods. During the study, theoretical and empirical research methods were used, in particular, a theoretical analysis of methods for structuring the content of education and managing the educational and cognitive activities of higher school students based on technological goal-setting and identifying a sequence of tasks, according to the content and methods of solving graduates close to future professional activities; studying the products of pedagogical activities of lecturers of higher education and experimental work, including the method of pedagogical experiment.

Results. The necessity of modernization of the system of professional training of the future economist in the context of the development of data science through the selection and implementation of a new content-methodological line “Big Data Analysis” is substantiated. It points to the demand for methods of pedagogical design and the theory of pedagogical technologies for the methodologically expedient inclusion of elements of Big Data theory in the practice of professional training of future bachelors of economics. At the same time, attention is paid to both the content of already developed academic disciplines “Probability theory and mathematical statistics”, “Decision theory”, “System’s analysis in Economics”, “Instrumental methods in Economics”, and the setting of new professionally significant academic disciplines related to quantitative justification of the decisions made. The article presents and methodically describes the components of the content-methodological line “Big Data Analysis”: firstly, a sequence of six micro-goals that allow setting the implementation of this contentmethodological line in the language of educational and cognitive activities of the future bachelor of economics and taking into account the capabilities of new digital tools that support Big Data analysis models; secondly, five didactic modules that can be used to form individual educational trajectories of students of economic bachelor’s degree. Six types of application tasks are presented and characterized, which are of fundamental importance  for  the  implementation  of this content-methodological line. These tasks include the following: “Application problem for the analysis of Big Data on the RapidMiner platform”; “Data clustering application”; “Applied problem of soft and hard clustering”; “Applied classification problem”; “Applied problem on the application of methods for finding association rules”; “Applied problem for text mining”.

Conclusion. The approach proposed by the authors to structuring the content of professional training of the future bachelor of economics allows us to maintain the balance of four educational components of the content and methodological line “Big Data Analysis”: experience in cognitive and creative activities, experience in implementing standard methods of activity and emotional and value relations (ideals of entrepreneurship, value orientations and motives of economic activity, etc.) The material presented in this article can be useful for lecturers of the higher economic school, as well as for everyone who is interested in the modern achievements of data science.

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