The expediency of forming the specialized database about industry and the system of their automated collection and usage were justified in this paper. This system allows to provide the information needs of the analysts and the scientists about the problems of industrial development. It provides the automated collection of the information for many countries of the world using any number of sources available as client-server resources on the Internet. The usage of modern data integration algorithms provides a diverse presentation of information, formats for its provision and frequency of updates. In addition, the advanced users of the system are provided with a wide range of options for creating search criteria and data acquisition format. The system is built as a client-server technology and is available for seamless integration with similar systems as a source and storage of information. In order to build a system, the analysis of existing in the world and popular in use statistical databases was carried out, their features, advantages and disadvantages were deаfined. It has been established that most of the existing statistical systems do not provide statistical data for Ukraine, and where they are, there is no detail data by type of economic activity and industry, and especially in industry. In addition, there are certain technical difficulties in working with data for users, the personalization of access is almost non-existent. The possibilities of the integrating existing databases with the systems that use information for modeling and forecasting both in query mode and especially in real time are rather limited. The structure of the statistical database about the development of industry has been formed, the indicators have been selected for its filling. The indicators were distributed by the sectors of the economy (the raw material production sector, the processing sector, the macrostatistics, other sectors). The sectors were disclosed by the key types of economic activity in accordance with the classification of economic activities in 2010 (CEA-2010), providing the predominant part of the creation of the added value of the economy of Ukraine. Each specific type of economic activity is disclosed by groups of industries and industries. In addition, the formation of the statistical database was carried out on the basis of assigning to each of the indicators other characteristics necessary for the automation: code, units of measurement, period, base (distribution of the indicators into the separate groups for the possibility of modeling), source (the statistical bases and sources from which the indicators and the data were collected). The modern relational database was used to store information, which allows solving optimization issues for working with the most powerful, but not yet large data, taking into account the features of wide data, allows horizontal and vertical scaling, including in the PostgreSQL open source database system. The methodology for the formation and the technology for filling the statistical database automatically from a large number of sources, the access mode to which is set by the system configuration parameters has been created. The technology has been developed for data migrations available in flexible formats, including text, in particular Excel. The implementation of the developed automated information system integration of industrial statistics allows you to select the necessary indicators for the analysis of economic processes in industry, use the statistical data collected in a single information space for 130 countries of the world (including Ukraine) for conducting scientific researches, building economic and mathematical models and making managerial

The question of how the changes in money supply influence investment and GDP have been studied intensively in recent history. However, not all aspects of this impact are sufficiently researched. In particular, the “new normality” (that has evolved recently) limits the use of well-known classical concepts and models in monetary policy, especially for emerging economies to which Ukraine belongs. Thus, the subject of this study was to assess the relationship between monetary aggregates, investment, and GDP by the world economic data analysis using mathematical statistics. As the information base for the study, the World Bank official statistics were taken (including broad money, gross capital formation, and GDP). More than 71% of all investigated countries showed a significant correlation between M3 and gross investment. The issue of how the strength of this relationship depends on the level of socio-economic development was investigated. Classification of countries was carried out using the “nearest neighbors” method in a two-dimensional feature space, namely, per capita income and correlation tightness. The analysis showed that 79% of all countries fall into the class with a proven high correlation. Moreover, their level of wealth and development was irrelevant. A cluster analysis of countries was fulfilled in the chosen feature space using the “mean shift” method. With the help of this method, all countries have been distributed into five clusters with different socio-economic conditions and an accuracy of 91%. Among them, there was a group of countries highly sensitive to change in monetization, up to extremely negative economic impacts. The study helped to conclude that, regardless of economic development, GDP benefits from an increase in the money supply. Although this factor is considered necessary, it is nevertheless not sufficient for economic growth, especially in the time of the fourth industrial revolution, when the government has to play a more active and complex role in accelerating national technological development.