This paper investigates how Big Data Analytics (BDA) can accelerate the transition to a low-carbon digital economy. We present a systematic literature-based research framework (2015–2025) that synthesizes applications of BDA in energy systems, transportation, industry and supply chains. The methodology combines systematic review and conceptual modelling to identify pathways through which BDA reduces emissions: (1) demand-side optimization, (2) operational efficiency, (3) predictive maintenance and (4) data-driven policy and market instruments. Results highlight concrete case examples smart grids, digital twins, and green supply-chain analytics and quantify benefits reported in recent literature. Key challenges such as data governance, carbon costs of computing, and policy integration are discussed. The paper concludes with policy recommendations and a research agenda to align digitalization with decarbonization goals.
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