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DOI: 10.15862/16ECOR326 (https://doi.org/10.15862/16ECOR326)

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Bogonosov K.A. System analysis of the big data analytics circuit in national and federal projects of the Russian Federation. Russian Journal of Resources. 2026; 13(3). Available at: https://resources.today/PDF/16ECOR326.pdf (in Russian). DOI: 10.15862/16ECOR326

System analysis of the big data analytics circuit in national and federal projects of the Russian Federation

Bogonosov Konstantin Alexandrovich
K.G. Razumovsky Moscow State University of Technology and management (First Cossack University),
Moscow, Russia
E-mail: bogonosov@mgutm.ru

Abstract. Big data analytics is set by Presidential Decree No. 309 of 7 May 2024 as part of the national digital transformation goal, yet within the system of national projects it is distributed among federal projects of different purpose, and its resource provision is not assessed separately. The paper performs a hierarchical decomposition of the national project «Data Economy and Digital Transformation of the State» across the levels of national goal, national project, federal project and indicator, divides nine federal projects into an infrastructure circuit and a data and analytics circuit, and identifies inter-project data links with national projects in health care, transport, labour and housing and utilities. A funding absorption index of a federal project, an indicator of residual funding requirement for the final year and a tension coefficient of an indicator’s target trajectory are proposed. Calculations based on passport funding for 2025–2030, cash execution in 2025, draft budget laws and statistics of HSE University, Rosstat and iKS-Consulting show that the infrastructure circuit absorbed 108 % of the average annual passport norm in 2025, whereas the data and analytics circuit absorbed only 41 %, so in 2026–2030 its funding must exceed the 2025 level by 2,7 times on average. Budget projections for 2025–2029 leave 237 billion roubles for 2030, which is 1,48 times the 2029 allocation. The tension coefficient is below one for the share of domestic software and the cloud market and exceeds four for data centre capacity. The relative lag of public administration in the use of big data analysis widened from 0,78 to 0,59 of the average for organisations.

Keywords: big data analytics; system analysis; national projects; federal projects; data economy; target indicators; absorption index; tension coefficient; data centres; digital transformation of public administration