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As we stand on the cusp of a new era in business management, the increasing complexity and velocity of market dynamics demand innovative approaches to data analysis and decision-making. An accelerating metamorphosis can be observed within the domain of data-driven management (U. Seebacher & Garritz, 2021 ), which is marked by an unprecedented proliferation of data, catalyzing a paradigm shift from traditional analytical practices to a comprehensive, predictive, and prescriptive data ethos. In antecedence, data-driven decision-making predominantly hinged upon retrospective analysis. Organizations would dissect historical datasets—financial records, consumer interactions, and erstwhile market trends—to inform future decisions. This analytical retrospection, while valuable, is rendered inadequate in the contemporary Big Data era, characterized by availability of voluminous amount of real-time data streams. The contemporary landscape necessitates not only the collection and storage of data but also its expeditious and cogent analysis. Accordingly, the crux of the contemporary challenge lies in distilling actionable insights from these vast oceans of data.
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