Please use this identifier to cite or link to this item:
|Title:||Predictive analytics for network big data using knowledge-based reasoning for smart retrieval of data, information, knowledge, and wisdom (DIKW)||Authors:||Yusoff, A.
|Issue Date:||2017||Abstract:||The study of data science, analysis, and decision-making has evolved from translating the raw data, information sharing, and knowledge representation to the wisdom of the Web of Things. Starting from the idea of architecting a wisdom hierarchy, the base of the hierarchy is built upon a data, information, knowledge, and wisdom (DIKW) pyramid . The pyramid or hierarchy as illustrated in Figure 10.1 consists of the components of DIKW. In addition, the recent trend in the needs of network big data has challenged this hierarchy to be redefined and implemented beyond the contemporary use of data analytics. If data on its own is raw, information is adding the context, knowledge is describing on how to use it and wisdom is explaining why to use it , then the big data is challenging the hierarchy to be in a more complex yet integrated structure. © 2018 by Taylor and Francis Group, LLC.||DOI:||10.1201/b21278|
|Appears in Collections:||UNITEN Scholarly Publication|
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.