PRINCIPLES OF CREATING REAL-TIME ANALYTICAL SYSTEMS BASED ON ARTIFICIAL INTELLIGENCE
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.
Authors
- Mukhamadaziz Rasulmukhamedov
- Abatbay Karamatdinov
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-04-14
- DOI
- https://doi.org/10.5281/zenodo.19564073
- Primary Topic
- Technology and Human Factors in Education and Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00