The article examines the man-made risks in the Arctic zone of the Russian Federation, methods of working with data related to the use of intellectual analysis, and the use of information systems for forecasting risks and is designed for the widest range of readers. The conducted research demonstrates that the use of data mining methods opens up broad prospects for data integration. This process includes the adaptation of the system to specific emergency situations typical of the Arctic zone of the Russian Federation, as well as the development of appropriate interfaces for interaction with external subsystems. As a result of the conducted research, the conclusions were obtained: 1. Intelligent methods allow you to analyze large amounts of data and identify hidden patterns, which helps you make more informed decisions. The quality of decisions is improved. 2. Intelligent data processing allows you to automate routine tasks and optimize business processes. This leads to increased productivity and lower costs. The efficiency of business processes increases. 3. Intelligent systems can analyze data about past events and predict future trends. This allows you to take measures to reduce risks and ensure safety. These processes make it possible to reduce risks. 4. Intelligent algorithms can process data in real time, which allows you to quickly respond to changes in the external environment. 5. In the future, it is planned to work out the issue of introducing intelligent data analysis algorithms into man-made emergency forecasting analytics systems and the development of the data science concept, such as the GIS Atlas of Natural Hazards and Risks.
Keywords: data mining, forecasting, emergency, man-made risk, information system