IMPROVING CLIMATE MONITORING SYSTEMS THROUGH OBJECT-RELATIONAL MAPPING TECHNOLOGIES AND REAL-TIME ANALYTICAL PROCESSING

The article addresses challenges related to climate change research. It provides an overview of contemporary information technologies that facilitate the design of highly efficient climate monitoring information systems, specifically in terms of processing speed and data completeness. Particular emphasis is placed on the use of tools for automatic object-to-database table mapping based on real-time Object-Relational Mapping (ORM) systems, as well as on OLAP technologies, which leverage multidimensional cubes to accelerate the processing of large-scale climate data and enhance the effectiveness of multidimensional data analysis. The developed climate monitoring information system, presented herein, comprises components for aggregated data sets, backend processing, frontend visualization, and an analytical module implemented as OLAP cubes. The system enables scientific research on environmental parameters and supports the development of forecasting models for climate monitoring systems, providing predictive and decision-support capabilities designed to mitigate global warming.