Big Data Analytics

Ümit Demirbaga, Gagangeet Singh Aujla (), Anish Jindal () and Oğuzhan Kalyon ()
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Ümit Demirbaga: University of Cambridge, Department of Medicine
Gagangeet Singh Aujla: Durham University, Department of Computer Science
Anish Jindal: Durham University, Department of Computer Science
Oğuzhan Kalyon: Newcastle University, Faculty of Medical Sciences

Chapter Chapter 3 in Big Data Analytics, 2024, pp 31-42 from Springer

Abstract: Abstract This chapter introduces the dynamic domain of big data analytics, illuminating its multifaceted aspects and profound significance. It commences by furnishing a comprehensive definition of big data analytics and delves into the taxonomy of this discipline, encompassing descriptive, diagnostic, predictive, prescriptive, and cognitive analytics, each underscored by its distinctive applications. Furthermore, this chapter elucidates the manifold advantages that big data analytics affords, notably its pivotal role in bolstering risk management, effecting cost reduction, facilitating informed decision-making, and catalysing advancements in product development. In parallel, it conscientiously scrutinises the challenges endemic to this field, encompassing the dearth of proficient practitioners, misconceptions, concerns about escalating data volumes, intricacies associated with tool selection, and the salient issues of data security and privacy. The essential stages inherent to big data analytics are methodically expounded to facilitate a comprehensive understanding, encompassing data acquisition, preprocessing, storage, and analysis, thereby furnishing a nuanced appreciation of the foundational principles and intricate nuances intrinsic to this pivotal discipline.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-55639-5_3

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DOI: 10.1007/978-3-031-55639-5_3

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