SADT MODEL FOR ASSESSING THE FEASIBILITY OF INTEGRATION OF DISTRIBUTED DATA PROCESSING SYSTEMS INTO CLOUD SERVICES OF TRADE ENTERPRISES
DOI:
https://doi.org/10.28925/2663-4023.2026.34.1316Keywords:
integration, distributed information processing systems, cloud services, digital transformation, SADT methodology, multi-criteria analysis, decision support, cloud infrastructure, information securityAbstract
The digital transformation of commercial enterprises in Ukraine has accelerated the adoption of cloud services (CSs) to ensure scalable data processing, enhance the flexibility of IT infrastructure, and optimize business processes. Alongside the advantages of cloud technologies, the integration of distributed information processing systems into cloud environments is currently associated with a range of technical, economic, and organizational risks. These risks are primarily related to information security, regulatory compliance, the reliability of cloud services, dependence on cloud service providers, and the complexity of managerial decision-making regarding the feasibility of cloud adoption. The purpose of this study is to develop a methodological framework for assessing the efficiency and risks of integrating distributed information processing systems into cloud services based on functional modeling using the Structured Analysis and Design Technique (SADT). The research methodology is grounded in the paradigms of structural analysis, functional modeling, expert evaluation, multicriteria analysis, and a systems approach to decision-making. The paper proposes an SADT-based model of the integration process that formalizes the sequence of primary data collection, expert assessment, verification of compliance with international information security requirements, and calculation of an integrated indicator for evaluating the feasibility of cloud service implementation. A hierarchical system of evaluation criteria is developed, taking into account technological, economic, organizational, and security-related factors influencing integration. In addition, the architecture of a software module for an intelligent decision support system is proposed to automate the assessment of the effectiveness of integrating distributed information processing systems into a cloud environment. The scientific novelty of the research lies in improving the methodological support for evaluating the feasibility of cloud integration through the combined application of functional modeling, multicriteria analysis, and expert evaluation techniques. The practical significance of the obtained results lies in the possibility of applying the proposed methodology to support managerial decision-making during the digital transformation of commercial enterprises, reduce integration risks, and improve the efficiency of cloud infrastructure utilization.
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