IT 领域的数据驱动决策:利用人工智能和数据科学实现商业智能

Comfort Idongesit Michael, Oluwaseun Johnson Ipede, Adejoke Deborah Adejumo, Ibrahim Oyeyemi Adenekan, Damilola Adebayo, Adefisayo Simon Ojo, Praise Ayomide Ayodele
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引用次数: 0

摘要

数据驱动决策(DDDM)利用人工智能(AI)和数据科学的巨大潜力,将原始数据转化为可操作的见解,已成为现代 IT 和业务领域的基石。本综述论文探讨了这些领域的交叉点,重点介绍了将人工智能和数据科学整合到商业智能(BI)中的相关方法、应用、优势和挑战。通过对当前文献的广泛综述,本文阐明了企业如何利用这些技术来推动战略决策、优化运营和保持竞争优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-driven decision making in IT: Leveraging AI and data science for business intelligence
Data-driven decision-making (DDDM) has become a cornerstone in modern IT and business landscapes, leveraging the immense potential of artificial intelligence (AI) and data science to transform raw data into actionable insights. This review paper explores the intersection of these domains, highlighting methodologies, applications, benefits, and challenges associated with integrating AI and data science into business intelligence (BI). Through an extensive review of current literature, this paper elucidates how organizations can harness these technologies to drive strategic decisions, optimize operations, and maintain a competitive edge.
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