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Data Science

In: Logistics Information Systems

Author

Listed:
  • Batuhan Kocaoglu

    (Istanbul Topkapi University)

Abstract

This chapter is a comprehensive exploration of the transformative power of data in logistics operations. It begins by explaining the relationship between data, information, and knowledge. The chapter delves into the realm of big data and explores machine learning and artificial intelligence, including supervised, unsupervised, reinforcement, and deep learning techniques. Various methodologies and tools in data science are discussed, along with the significance of addressing bias in data. Additionally, the chapter covers Business Intelligence, data warehousing, and Online Analytical Processing (OLAP), as well as data mining and business analytics, encompassing descriptive, diagnostic, predictive, and prescriptive analytics. This chapter equips readers with a deep understanding of how data science empowers logistics operations by transforming data into actionable insights, fostering innovation and efficiency in the logistics domain.

Suggested Citation

  • Batuhan Kocaoglu, 2024. "Data Science," Springer Texts in Business and Economics, in: Logistics Information Systems, chapter 0, pages 235-285, Springer.
    • Handle: RePEc:spr:sptchp:978-3-031-60290-0_8
    DOI: 10.1007/978-3-031-60290-0_8
    as

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