文章基本信息

标题：INTEGRATING DATA ANALYTICS & KNOWLEDGE MANAGEMENT: A CONCEPTUAL MODEL
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作者：Chaojie Wang
期刊名称：Issues in Information Systems
印刷版ISSN：1529-7314
出版年度：2018
卷号：19
期号：2
页码：208-216
出版社：International Association for Computer Information Systems
摘要：Data analytics may be heavily reliant on technology such as statistical models, machine learning algorithms, big data, and cloud computing; however, its outcome depends largely on human qualities such as experience, intuition, value, and judgement. Human knowledge is at the core of data analytics and knowledge management plays a key role in the analytics process. This paper uses the Data-Information-Knowledge-Wisdom (DIKW) hierarchy as an overarching structure to examine the end-to-end process of data analytics and to illustrate a conceptual three-phase data analytics process model integrating knowledge management practices including the discovery, creation, and application of knowledge. Nonaka’s knowledge conversion theory is applied to the analytics process to shed light on the easily and often overlooked human and organizational aspects that are fundamental to the effectiveness of data analytics. The alignment and synergy between data analytics and knowledge management help foster collaboration, drive innovation, and ultimately improve outcome.
关键词：DIKW Hierarchy; Data Analytics; Knowledge Management; Knowledge Conversion