SAP Analytics Cloud: intellectual analysis of small and medium-sized business activities in Russia in the context of COVID-19 Nazarov D.M. Departament of Business Informatics Ural State University of Economics Yekaterinburg, Russia slup2005@mail.ru Kovtun D.B. Departament of Business Informatics Ural State University of Economics Yekaterinburg, Russia kovtun.d.b@gmail.com Reichert T.N. Departament of Business Informatics Ural State University of Economics Yekaterinburg, Russia reichert@yandex.ru Abstract— The global trend of transition to a digital economy is pushing the scientific community to thoroughly research intellectual analytics models since the quality of models directly affects the choice of an effective decision-making strategy. The article discusses the possibilities and technologies for constructing data mining models in the digital service SAP Analytics Cloud, based on open data on the registration of legal entities and individual entrepreneurs in the Russian Federation. The impact of government support measures on the business activity of small and medium-sized businesses in the context of the spread of COVID- 19 is assessed. Predictive analytics models are being implemented in the SAP Analytics Cloud, which allows us to assess the future development trends of small and medium-sized businesses in Russia. Keywords—COVID-19, the digital economy, open data, SAP Analytic Cloud, data mining I. INTRODUCTION The first quarter of the 21st century is characterized by rapid processes of the economy's "digitalization". This time is characterized by the transformation of the global information space, which affects the market, society, business, and the state. According to the IDC analytical agency, it is expected that by 2025 the volume of processed data in the cloud segment using digital services will grow to 175 zettabytes [12,14]. The development of wireless technologies, smart devices, the Internet, augmented, and virtual reality technologies facilitate rapid growth in the volume of processed data. In this regard, for the state and large companies in the context of digital transformation, the quality, reliability, and speed of information-analytical forecasting based on predictive analytics models are of particular importance [16]. The growth of information and data in cloud storage acted as a catalyst for the emergence of intelligent digital services on the market [4]. Over the past 15 years, the world's largest vendors have released products that can cope with the challenges posed by the 21st century. Tools such as SAP Business Objects Predictive Analysis, IBM Predictive Insights, SAS Rapid Predictive Modeler, Oracle Retail Predictive Application Server, IBM SPSS Decision Management and IBM SPSS Modeler, as well as open-type digital services: Python, R, Orange, RapidMiner can cope with the above tasks, and also have additional libraries of predictive analytics, the basis for high-quality forecasting of various economic results [6]. Predictive analytics uses many methods of data mining, statistics, modelling, machine learning, and artificial intelligence to analyze historical and operational data to make a forecast for the future [2]. The national program “Digital Economy” adopted and approved by the Government of the Russian Federation in 2017 is aimed at optimizing the management of the economic activities of our country, the basis of which are digital platforms [8]. At the state level, a large number of digital platforms have been created, and a leader in this direction, as President of the Russian Federation V.V. Putin has emphasized, is the FTS - the Federal Tax Service. One of these digital platforms is a portal that accumulates data on the registration and liquidation of various business units - the USRLE (Unified State Register of Legal Entities) [11,15]. The data on this portal is well structured and open. Application of data mining technologies to them will allow obtaining (extracting) additional, understandable, and well-interpreted information that will let us evaluate and forecast business activity in the Russian regions. The purpose of our study is to build a pool of smart models for studying business activity during the COVID-19 pandemic in the SAP Analytics Cloud digital service based on open data from the register of legal entities of the Russian Federation and the Federal Tax Service. II. DESCRIPTION OF MEASURES TO SUPPORT SMALL AND MEDIUM-SIZED BUSINESSES IN THE CONTEXT OF COVID-19 At the beginning of 2020, the global economy was faced with a crisis caused by the COVID-19 pandemic, the Russian economy, being an integral part of the global economy, was no exception. In the realities that have come, building a strategy for the country's economic development is more relevant than ever. The economic development of the Russian Federation, as President Vladimir Putin has repeatedly emphasized, depends not only on hydrocarbon exports but also on the business 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT) | 978-1-7281-7386-3/20/$31.00 ©2020 IEEE | DOI: 10.1109/AICT50176.2020.9368635 © IEEE 2021. This article is free to access and download, along with rights for full text and data mining, re-use and analysis.