Abstract : The emergence of digital technologies, cloud computing, and artificial intelligence has significantly increased the volume of data generated by organizations. Big Data Analytics (BDA) has emerged as a powerful tool that enables organizations to extract meaningful insights from massive datasets to support strategic and operational decision-making. The primary objective of this study is to examine the role of big data analytics in organizational decision-making and evaluate how data-driven technologies improve business performance. The study adopts a conceptual research design based on secondary data sources such as academic journals, industry reports, and information systems literature published between 2014 and 2025. The analysis highlights major big data models, analytical frameworks, and decision-support mechanisms used by organizations. The findings indicate that big data analytics enhances organizational efficiency, improves forecasting accuracy, supports strategic planning, and enables data-driven innovation. Organizations that integrate advanced analytics tools such as machine learning, predictive analytics, and real-time data processing gain significant competitive advantages in dynamic market environments. However, challenges related to data privacy, infrastructure costs, and data governance remain critical concerns. The study concludes that the adoption of big data analytics frameworks can significantly improve decision quality and organizational performance when supported by appropriate technological infrastructure and data management strategies.
Keywords : Big Data Analytics, Decision-Making, Business Intelligence, Data-Driven Organizations, Information Systems, Artificial Intelligence.
Cite : Prakash, A. (2026). Big Data Analytics And Its Role In Decision-Making In Organizations (1st ed., pp. 196-202). Noble Science Press. https://noblesciencepress.org/chapter/nspebeparddias2026ch-22
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