Big Data-Driven Automation: Unlocking New Frontiers in Operational Innovation

DOI: https://doie.org/10.10399/JBSE.2025289717

Priyam Vaghasia, Dhruvitkumar Patel

Keywords:

Big Data, Automation, Intelligent Automation, Hyperautomation, Predictive Analytics, Operational Innovation, Edge Computing, Federated Learning, Digital Transformation

Abstract:

The convergence of big data analytics and automation has catalyzed a paradigm shift in operational models across industries. As data volumes surge and computational tools evolve, organizations increasingly rely on big data-driven automation (BDDA) to transform decision-making, enhance productivity, and foster innovation. This paper explores the foundational elements, architectural mechanisms, and sector-specific applications of BDDA, presenting a comprehensive framework that integrates real-time analytics, machine learning, and intelligent automation. By dissecting enabling technologies like IoT, edge computing, and generative AI, the paper demonstrates how BDDA unlocks operational excellence. It also discusses challenges such as data governance, algorithmic bias, and cybersecurity while identifying emerging trends like autonomous operations, quantum-enhanced optimization, and federated learning. The findings underscore that BDDA is not merely a technological upgrade but a transformative approach shaping the next frontier of organizational competitiveness.

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