- Круглик, Олег (orcid.org/0009-0003-9416-753X) (2026) Developing analytical competence of future economists through the integration of digital instrumental platforms Information Technologies and Learning Tools, 2 (112). pp. 44-58. ISSN 2076-8184
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Abstract
The article substantiates the rationale for integrating scenario modelling and pilot design technologies, supported by off-the-shelf business intelligence solutions, into the process of developing the analytical competence of future economists. A conceptual and methodological model has been developed that enables economics students to formulate alternative business scenarios, to justify the choice of experimental regions, to critically interpret analytical findings, and to scale up successful practices using modern BI (Business Intelligence) platforms, OLAP tools, and cloud-oriented planning systems. The study’s methodological framework is based on competence-based, scenario-based and experimental pedagogical approaches, as well as a systematic review of over eighty academic sources reflecting the evolution of digital analytics in higher economic education. The proposed conceptual and methodological model, which follows the sequence “data → scenario → pilot → analytics”, is implemented through Power BI, Tableau, Qlik, SSAS Tabular, Anaplan, Oracle Cloud EPM and Optimizely. These tools do not require programming skills and support interactive what-if analysis, multidimensional aggregation and driver-based budgeting. The theoretical contribution of the study lies in the systematisation of the functional capabilities of ready-made IT solutions in the context of developing the cognitive, technological, communicative and reflective components of the analytical competence of future economists. The practical contribution is represented by a set of three hypothetical cases: “four regions – four scenarios” for a distribution network, A/B testing of pricing policy in electronic commerce (e-commerce), and production capacity planning under conditions of electricity price volatility. For each case, the structure of input data, success criteria, a checklist for assessing student solutions and dashboard mock-ups are provided. The proposed approach reduces the gap between theoretical training and the practical requirements of employers, enhances graduates’ readiness to participate in data-driven decision-making processes, and promotes the development of a culture of experimental research in the Ukrainian business environment.
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