Abstract
The present-day pace in development of the modern information technologies in Russia greatly exceeds the speed at which the methodological, recommendatory, standardization and regulatory/reference framework is being developed for the governing documents that are in force in our country and are actually used by economic entities. In many cases the present-day methodical tools of business intelligence used in the domestic environment lag behind the evolution of the information tools or turn out to be insufficiently adapted to the peculiarities of the economy.
This study is aimed at identifying the basics for integrating and adapting the world-wide experience of using business intelligence solutions (Business Intelligence, BI) for the business entities’ economic performance analysis in order to optimize this domain in the Russian environment for various purposes, including elaboration of an information quality improvement program and development of corporate-wide business intelligence systems.
Based on the analysis of foreign experience, the author substantiates the national companies’ capability of elaborating the data control methodology and ensuring data transparency. The author concludes the wider methodological directions in using the business intelligence, which may be extrapolated from the international practice to the national companies’ business. The author developed the data handling algorithm in the course of the economic performance analysis in companies by means of the BI-technologies. This algorithm implies successive conversion of such data into information, information - into understanding, understanding - into knowledge, and general knowledge - into the goal-oriented applied knowledge that facilitates decision-making.
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Mitrovic, S. (2020). Adapting of International Practices of Using Business-Intelligence to the Economic Analysis in Russia. In: Ashmarina, S., Mesquita, A., Vochozka, M. (eds) Digital Transformation of the Economy: Challenges, Trends and New Opportunities. Advances in Intelligent Systems and Computing, vol 908. Springer, Cham. https://doi.org/10.1007/978-3-030-11367-4_13
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DOI: https://doi.org/10.1007/978-3-030-11367-4_13
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