PRINCIPLES OF CREATING REAL-TIME ANALYTICAL SYSTEMS BASED ON ARTIFICIAL INTELLIGENCE

Abstract

The rapid development of digital technologies has led to a dramatic growth in the volume of  data generated across different sectors. Modern information systems must process and analyze these  data streams quickly in order to support effective decision‑making. This article examines the  principles of developing real‑time analytical systems based on artificial intelligence technologies.  The research analyzes the role of machine learning algorithms and neural network models in  processing large data streams, detecting hidden patterns, and generating predictive insights.  Particular attention is paid to system architecture, scalability, data processing speed, and reliability.  The study demonstrates that integrating artificial intelligence with real‑time data processing  platforms significantly improves analytical capabilities and enables more accurate forecasting of  complex processes.