Development of an algorithm for obtaining and analyzing data from regions to assess their development in the context of the transition of industry 4.0

Andrey Tuskov; Ivan Efimov; Petr Efimov; Botagoz S. Saparova; Altynai A. Saparova; Aigul A. Saparova

doi:10.1117/12.2681232

27 April 2023 Development of an algorithm for obtaining and analyzing data from regions to assess their development in the context of the transition of industry 4.0

Andrey Tuskov, Ivan Efimov, Petr Efimov, Botagoz S. Saparova, Altynai A. Saparova, Aigul A. Saparova

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Proceedings Volume 12637, International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023); 126370R (2023) https://doi.org/10.1117/12.2681232
Event: International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023), 2023, Fergana, Uzbekistan

Abstract

The transition to Industry 4.0 is accompanied by significant progress and change in many areas of society and the economy. Digitalization changes and improves business processes, simplifies and enriches people's lives. Innovation is taking place. New tools provide, among other things, the collection of large amounts of data. In this regard, the problem of big data analysis is urgent. Since this task is associated with a large amount of digital computing and relies heavily on advanced software and server tools, we were faced with the task of conducting such an in-depth analysis with available software tools with high efficiency. The constructed multi-level universal algorithm for obtaining, collecting, processing and visualizing data is implemented in Microsoft Excel using the Power Pivot add-on. The analysis carried out in the study is aimed at identifying and comparing regions in terms of the level of development of spheres of public life, including the level of digitalization in the context of industry 4.0.

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Andrey Tuskov, Ivan Efimov, Petr Efimov, Botagoz S. Saparova, Altynai A. Saparova, and Aigul A. Saparova "Development of an algorithm for obtaining and analyzing data from regions to assess their development in the context of the transition of industry 4.0", Proc. SPIE 12637, International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023), 126370R (27 April 2023); https://doi.org/10.1117/12.2681232

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KEYWORDS

Algorithm development

Radon

Data modeling

Excel

Industry

Statistical analysis

Data analysis

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