Intelligent Big Data Analytics Technologies as a Driver for Sustainable Agricultural Development

The article is devoted to the study of the role of innovative approaches to big data analysis in ensuring the sustainable development of the agricultural sector. It examines the potential of intelligent data processing methods to enhance the efficiency of management decisions and optimize production processes in agriculture. Through statistical analysis and modeling, the study identifies key factors determining the effectiveness of Big Data technologies in the agro-industrial sector. The conclusion highlights the need for the integrated use of predictive analytics, machine learning, and cloud computing to build highly productive agroecosystems resilient to market and climate risks. The importance of further developing the methodological and instrumental foundations of big data analytics is emphasized to ensure the competitiveness and environmental sustainability of the domestic agro-industrial complex.

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Publication Details

Journal
Agrarian science
Published
2025-06-24
DOI
https://doi.org/10.32634/0869-8155-2025-395-06-172-175
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Intelligent Big Data Analytics Technologies as a Driver for Sustainable Agricultural Development

A. I. Galkin
Agrarian science
Smart Agriculture and AI
article

Intelligent Big Data Analytics Technologies as a Driver for Sustainable Agricultural Development

A. I. Galkin
article en

Abstract

The article is devoted to the study of the role of innovative approaches to big data analysis in ensuring the sustainable development of the agricultural sector. It examines the potential of intelligent data processing methods to enhance the efficiency of management decisions and optimize production processes in agriculture. Through statistical analysis and modeling, the study identifies key factors determining the effectiveness of Big Data technologies in the agro-industrial sector. The conclusion highlights the need for the integrated use of predictive analytics, machine learning, and cloud computing to build highly productive agroecosystems resilient to market and climate risks. The importance of further developing the methodological and instrumental foundations of big data analytics is emphasized to ensure the competitiveness and environmental sustainability of the domestic agro-industrial complex.

Agrarian scienceVol. 1(6)
Financial University (RU)
Openalex Percentile: Top 89%
Smart Agriculture and AI
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