Journal: Volume 31, No. 2, 2026
Pages: 57 – 72
DOI: https://doi.org/10.62660/bcstu/2.2026.57
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Architectural and methodological approaches to the design of corporate and web-oriented information systems with elements of intelligent data analysis

Vladyslav Kozub, Olha Smahina, Halyna Kozub
Received 17.11.2025
Revised 16.03.2026
Accepted 18.05.2026
Published 26.06.2026

Abstract

The relevance of the study is due to the digital transformation and the need to improve architectural and methodological approaches to the design of intelligent corporate and web-oriented information systems. The purpose of the study was to form a conceptual approach to the design of information systems using intelligent data analysis tools. The study was based on the theoretical analysis of scientific materials and the application of systemic, conceptual, project-oriented, domain-oriented and data-driven methodological approaches to substantiate the principles of designing adaptive information systems. The results obtained demonstrated the transition of modern information systems to multi-level modular and data-centric architectures that combine functional flexibility, scalability and intelligent analytical data processing. The integration of artificial intelligence algorithms provides the implementation of predictive analytics, information classification and detection of anomalies in the system’s behaviour. The effectiveness of the platforms is assessed through a complex of time, resource and analytical metrics, in particular latency, throughput, central processing unit utilisation, memory consumption, error rate, mean absolute error, root mean squared error, mean absolute percentage error, precision, and recall. It is shown that the reliability of information systems is ensured by the use of fault-tolerant architectures, service component redundancy and self-tuning computing environments. The generalisation of the results confirmed the prospects for the development of adaptive cognitive-oriented data-centric information platforms of the new generation. The results can be used by scientists, developers, and software architects and organisations involved in the digital transformation of information systems in the design, optimisation and implementation of adaptive analytically oriented digital platforms

Keywords

machine learning; big data; data-driven; scalability; adaptive information platforms; domain-oriented design

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Suggested citation

Kozub, V., Smahina, O., & Kozub, H. (2026). Architectural and methodological approaches to the design of corporate and web-oriented information systems with elements of intelligent data analysis. Bulletin of Cherkasy State Technological University, 31(2), 57-72. https://doi.org/10.62660/bcstu/2.2026.57