Multidimensional Representation of COVID-19 Data Using OLAP Information Technology

In December 2019, an unknown disease was first reported in Wuhan (Hubei province, China), which subsequently spread around the world. COVID-19 is an infectious disease accompanied by severe acute respiratory syndrome (SARS-CoV-2) [1], which is called a "coronavirus" for the visual similarity of the pathogen to the crown [2]. On April 23 2020, the World Health Organization has identified more than 2.5 million confirmed cases of COVID-19 virus disease [3]. Considering the scope of spread and features of the pandemic caused by the COVID-19 virus, timely diagnosis of the disease of citizens is important. The first step in developing any diagnostic or treatment tools is to effectively process data collections, much of which are based on open data from national, provincial, and municipal health facilities. At the same time, the importance of IT support the processes of making operational and strategic decisions in the health sector, as a critical area of smart cities and smart regions is increasing. Therefore, developing effective and reliable means of generating and processing detailed collections of COVID-19 outbreaks in real-time is an important research area in the implementation of innovative information technology projects of the smart city and smart region class. It requires design, development and implementation of information technology and software-algorithmic tools to collect and process data globally.