Centralized Parallel Computing as a Cloud Service for Solving Digital Transformation Problems in Smart Cities

The digital processing of geospatial data could be a significant challenge especially in automated performing of different kinds of analysis. The current computer file formats and standards for such data are oriented to expert works in specific areas, which predetermines a traditional way of working with the use of different software tools running on local PCs. Each expert or expert group is focused on specific problem solving, performing an analysis and applying the result, where the last one is required. It is quite natural at first, that a lot of state administrations, municipalities and research institutes are interested in geospatial data and GIS services, because a number of regulations and legislation forces digital transformation. In addition, the business interest in accessing and working with geospatial data is increasing in order to provide innovative products to the customers. The main aim of this paper is to illustrate a sustainable model of digital transformation by analyzing geospatial data, which combines enterprise and scientific approach to build a complex architecture, including high-performance and secure API services, signaling mechanisms and service for parallel computation, which performs given analysis with the use of GPU hardware.