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Cloud Computing for Big Data Analytics

In: Big Data Analytics

Author

Listed:
  • Ümit Demirbaga

    (University of Cambridge, Department of Medicine
    Bartin University, Department of Computer Engineering, Faculty of Engineering, Architecture, and Design)

  • 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)

Abstract

In this chapter, the exploration unfolds within the domain of cloud computing, emphasising its instrumental role in empowering the realm of big data analytics. Commencing with a comprehensive exposition, the historical evolution of cloud computing is meticulously traced across various computing generations, culminating in its contemporary manifestation as a transformative and indispensable component of the Information Technology (IT) landscape. Subsequently, cloud computing service models are systematically elucidated in conjunction with an exhaustive examination of deployment models, including public, private, hybrid, and community clouds. Furthermore, multi-cloud strategies are explored, with an in-depth exploration of key cloud computing platforms. A thorough comparison of these renowned cloud providers is offered to aid in making well-informed decisions and provide stakeholders with the necessary knowledge to effectively use cloud computing’s promise to enhance big data analytics.

Suggested Citation

  • Ümit Demirbaga & Gagangeet Singh Aujla & Anish Jindal & Oğuzhan Kalyon, 2024. "Cloud Computing for Big Data Analytics," Springer Books, in: Big Data Analytics, chapter 0, pages 43-77, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-55639-5_4
    DOI: 10.1007/978-3-031-55639-5_4
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