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.
Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.
—Geoffrey Moore
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Demirbaga, Ü., Aujla, G.S., Jindal, A., Kalyon, O. (2024). Big Data Analytics. In: Big Data Analytics. Springer, Cham. https://doi.org/10.1007/978-3-031-55639-5_3
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DOI: https://doi.org/10.1007/978-3-031-55639-5_3
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