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

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-14
DOI
https://doi.org/10.5281/zenodo.19564074
Primary Topic
Technology and Human Factors in Education and Health
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Mukhamadaziz Rasulmukhamedov, Abatbay Karamatdinov
Zenodo (CERN European Organization for Nuclear Research)
Technology and Human Factors in Education and Health
article

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

Mukhamadaziz Rasulmukhamedov, Abatbay Karamatdinov
article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Technology and Human Factors in Education and Health
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