AUTOMATION OF DATA ANALYSIS USING ARTIFICIAL INTELLIGENCE METHODS

The article discusses modern approaches to automating data analysis using artificial intelligence (AI) methods. With the rapid growth of data volumes entering various systems, their analysis and processing are becoming a complex task. Automating these processes with AI allows us to increase the efficiency and accuracy of data analysis, minimize the human factor, and speed up decision-making. The article discusses machine learning and deep learning methods used to automate data analysis, as well as examples of their application in various industries, such as finance, medicine, industry, and marketing. Particular attention is paid to the advantages and limitations of existing approaches, as well as prospects for their further development. The article discusses in detail the conditions and methods of research aimed at studying and evaluating the effectiveness of various AI models in automating data analysis. The obtained results are analyzed and prospects for further development of AI technologies in this area are discussed. The study emphasizes the importance of interpretability of AI models, the need to develop new methods that can effectively work with limited and noisy data, as well as reducing the computational costs associated with their use.

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Publication Details

Journal
Bulletin of Shakarim University Technical Sciences
Published
2024-09-27
DOI
https://doi.org/10.53360/2788-7995-2024-3(15)-6
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
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article

AUTOMATION OF DATA ANALYSIS USING ARTIFICIAL INTELLIGENCE METHODS

S. B. Kaysanov, V. I. Shumkin
Bulletin of Shakarim University Technical Sciences
Anomaly Detection Techniques and Applications
article

AUTOMATION OF DATA ANALYSIS USING ARTIFICIAL INTELLIGENCE METHODS

S. B. Kaysanov, V. I. Shumkin
article en

Abstract

The article discusses modern approaches to automating data analysis using artificial intelligence (AI) methods. With the rapid growth of data volumes entering various systems, their analysis and processing are becoming a complex task. Automating these processes with AI allows us to increase the efficiency and accuracy of data analysis, minimize the human factor, and speed up decision-making. The article discusses machine learning and deep learning methods used to automate data analysis, as well as examples of their application in various industries, such as finance, medicine, industry, and marketing. Particular attention is paid to the advantages and limitations of existing approaches, as well as prospects for their further development. The article discusses in detail the conditions and methods of research aimed at studying and evaluating the effectiveness of various AI models in automating data analysis. The obtained results are analyzed and prospects for further development of AI technologies in this area are discussed. The study emphasizes the importance of interpretability of AI models, the need to develop new methods that can effectively work with limited and noisy data, as well as reducing the computational costs associated with their use.

Bulletin of Shakarim University Technical Sciences(3(15))
Shakarim University (KZ)
Openalex Percentile: Top 82%
Anomaly Detection Techniques and Applications
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AUTOMATION OF DATA ANALYSIS USING ARTIFICIAL INTELLIGENCE METHODS — S. B. Kaysanov, V. I. Shumkin · Bulletin of Shakarim University Technical Sciences (2024) | TGRS Research Map | TGRS