BIG DATA MINING: AN OVERVIEW OF CURRENT PRACTICES AND FUTURE INNOVATIONS

DOI: https://doie.org/10.10399/JBSE.2025274226

Priyam Vaghasia , Dhruvitkumar Patel

Keywords:

Big Data Mining, Distributed Systems, Machine Learning, Privacy-Preserving Techniques, Quantum Computing, IoT Integration.

Abstract:

Big Data Mining (BDM) is a critical enabler of modern data-driven decision-making, transforming raw data into actionable insights across industries. This paper synthesizes the evolution, methodologies, and challenges of BDM, emphasizing scalable algorithms, distributed architectures, and ethical considerations. It explores emerging innovations such as quantum computing, edge analytics, and automated machine learning (AutoML), while addressing unresolved technical and ethical hurdles. Applications in healthcare, finance, smart cities, and manufacturing are analyzed to demonstrate BDM’s transformative potential. The paper concludes with strategic recommendations to advance research and adoption.

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