Development of a system for monitoring and analyzing the investment attractiveness of a constituent entity of the Russian Federation based on Big Data

Abstract

This study examines the problem of developing a system for monitoring and analyzing the investment attractiveness of a constituent entity of the Russian Federation based on Big Data technologies. The relevance of this topic is due to the need to attract investments into the economy of the regions and increase their competitiveness in the context of globalization and digitalization. The purpose of the study is to create an effective system for monitoring and analyzing the investment attractiveness of a constituent entity of the Russian Federation, capable of processing and analyzing huge amounts of structured and unstructured data from various sources, such as state information systems, social networks, news portals, geolocation data, etc. The work uses methods of data mining, machine learning, statistical analysis, as well as distributed data processing technologies (Hadoop, Spark). The architecture of the system is proposed, which includes modules for data collection, preprocessing, storage, analysis and visualization of results. A methodology has been developed to assess the investment attractiveness of the region based on a comprehensive analysis of more than 150 indicators characterizing the economic potential, infrastructure, human capital, innovation activity and investment climate of the subject of the Russian Federation. Using machine learning methods (Random Forest, Gradient Boosting), predictive models have been built that allow assessing the investment attractiveness of the region in the short and long term. The approbation of the developed system was carried out on the example of the Novosibirsk region. The results of the analysis showed that the Novosibirsk Region is among the top 15 regions of the Russian Federation in terms of investment attractiveness, but has a number of problem areas, in particular, an insufficiently developed transport and logistics infrastructure and a shortage of highly qualified personnel in the IT field. Based on the results obtained, recommendations are given to increase the investment attractiveness of the region. The developed monitoring and analysis system based on Big Data technologies can be scaled and adapted for other subjects of the Russian Federation, which will contribute to improving the effectiveness of management decisions in the field of investment policy and economic development of regions.