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Study on the interaction between big data and artificial intelligence

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  • Jin Li
  • Ziwei Ye
  • Caiming Zhang

Abstract

The explosive growth of information has rapidly ushered people into the era of big data. Due to the large volume, high variety, and rapid velocity characteristics of big data, most traditional data mining methods developed for a centralized data analysis process cannot be applied directly. AI leverages machine intelligence to provide insights, automation, and new methods to interact with data, thereby promoting data literacy throughout the organization. Based on the theory of Big Data Cycle, this paper discusses the relationship between big data and AI and how they interact and influence each other. It adopts the integrative review research method to screen latest literature and summarizes the role of AI in different phases of big data cycle. We also provide an insight into the applications of big data and AI in three different areas, that is, social network, health care, and finance.

Suggested Citation

  • Jin Li & Ziwei Ye & Caiming Zhang, 2022. "Study on the interaction between big data and artificial intelligence," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 641-648, May.
    • Handle: RePEc:bla:srbeha:v:39:y:2022:i:3:p:641-648
    DOI: 10.1002/sres.2878
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    References listed on IDEAS

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    1. Yang Lu, 2019. "Artificial intelligence: a survey on evolution, models, applications and future trends," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(1), pages 1-29, January.
    2. Snyder, Hannah, 2019. "Literature review as a research methodology: An overview and guidelines," Journal of Business Research, Elsevier, vol. 104(C), pages 333-339.
    3. Campbell, Colin & Sands, Sean & Ferraro, Carla & Tsao, Hsiu-Yuan (Jody) & Mavrommatis, Alexis, 2020. "From data to action: How marketers can leverage AI," Business Horizons, Elsevier, vol. 63(2), pages 227-243.
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    Cited by:

    1. Yuqin Yang & Ying Zhang & Daner Sun & Wenmeng He & Yantao Wei, 2025. "Navigating the landscape of AI literacy education: insights from a decade of research (2014–2024)," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-12, December.

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