Decision-making in selecting information and analytical systems for corporate IT cluster enterprises

Purpose. This article explores the process of selecting information and analytical support systems (IASS) for enterprises operating within a corporate IT cluster. The study aims to identify the key selection criteria, technological factors, and integration challenges that influence the effectiveness of such systems in the context of digital transformation and inter-organizational collaboration. Methods. The research is grounded in the analysis of scientific literature, regulatory frameworks, industry reports, and corporate practices of IT enterprises. The methodological approach includes system analysis, expert evaluation, and comparative analysis of modern IASS platforms. Particular attention is paid to the integration potential, scalability, and security aspects of the systems under consideration. Results. The study reveals that the choice of IASS in the IT cluster environment should be based not only on functional capabilities but also on strategic alignment with cluster goals, interoperability with partner infrastructures, and adaptability to evolving business needs. The findings emphasize the advantages of hybrid models that combine centralized and decentralized data architectures with cloud-based services to ensure flexibility and efficiency. A decision-making algorithm for IASS selection is proposed to support enterprises in developing a sustainable digital strategy. Conclusions. The outcomes of the study provide a conceptual and practical basis for selecting and implementing IASS in corporate IT clusters. The proposed framework can serve as a guideline for IT managers, analysts, and policymakers involved in building integrated digital ecosystems and enhancing analytical capabilities at the organizational level.