商业分析的起源及其对信息系统领域的影响

IF 1.7 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
N. Hassan
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引用次数: 6

摘要

像许多其他学科一样,信息系统(IS)社区已经接受了大数据分析和数据科学。然而,由于急于利用这一最新趋势的流行,与IS领域最相关的大数据分析和数据科学领域并没有明确。虽然很多考虑数据分析作为一个进化的决策支持系统(DSS),也就是说,作为一个技术需要管理或增强,本文追溯了复杂的分析,而不是回到Luhn起源和哲学的文本分析在1950年代末,Naur作为人类活动的计算及其datalogy图基的未来的数据分析1960年代,和科德的关系数据库模式在1970年代,在大数据分析和数据科学成为行业术语。现在被认为是大数据分析和数据科学主流思想的许多东西都可以追溯到这些有远见的人。本文探讨了数据分析和数据科学的复杂起源对信息系统领域的影响,特别是这些不同的话语如何影响未来的研究和实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The origins of business analytics and implications for the information systems field
ABSTRACT Like many other disciplines, the information systems (IS) community has embraced big data analytics and data science. However, in the rush to exploit the popularity of this latest trend, the areas of big data analytics and data science that are most relevant to the IS field are not made clear. While many consider data analytics as an evolution of decision support systems (DSS), that is, as a technology that needs to be managed or enhanced, this essay traces the complex origins and philosophy of analytics instead back to Luhn’s text analytics in the late 1950s, Naur’s Computing as a Human Activity and his datalogy, Tukey’s Future of Data Analysis of the 1960s, and Codd’s relational database schema in the 1970s, well before big data analytics and data science became industry buzzwords. Many of what is now considered mainstream thinking in big data analytics and data science can be traced back to these visionaries. This essay examines the implications of the complex origins of data analytics and data science for the IS field, specifically on how those different discourses impact future research and practice.
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来源期刊
Journal of Business Analytics
Journal of Business Analytics Business, Management and Accounting-Management Information Systems
CiteScore
2.50
自引率
0.00%
发文量
13
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