Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing
By Hamid R. Nemati, D. Steiger, Lakshmi Shankar Iyer, R. Herschel. Decision Support Systems, 2002
448 citations recorded by the source corpus.
Decision support systems (DSS) are becoming increasingly more critical to the daily operation of organizations. Data warehousing, an integral part of this, provides an infrastructure that enables businesses to extract, cleanse, and store vast amounts of data. The basic purpose of a data warehouse is to empower the knowledge workers with information that allows them to make decisions based on a solid foundation of fact. However, only a fraction of the needed information exists on computers; the vast majority of a firm's intellectual assets exist as knowledge in the minds of its employees. What is needed is a new generation of knowledge-enabled systems that provides the infrastructure needed to capture, cleanse, store, organize, leverage, and disseminate not only data and information but also the knowledge of the firm. The purpose of this paper is to propose, as an extension to the data warehouse model, a knowledge warehouse (KW) architecture that will not only facilitate the capturing and coding of knowledge but also enhance the retrieval and sharing of knowledge across the organization. The knowledge warehouse proposed here suggests a different direction for DSS in the next decade. This new direction is based on an expanded purpose of DSS. That is, the purpose of DSS in knowledge improvement. This expanded purpose of DSS also suggests that the effectiveness of a DSS will, in the future, be measured based on how well it promotes and enhances knowledge, how well it improves the mental model(s) and understanding of the decision maker(s) and thereby how well it improves his/her decision making.
Subfields: Management Information Systems, Management Science and Operations Research, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/750ae193908f039e05ddae0fa82daf750f60c57f
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In Management Information Systems
In Management Science and Operations Research
In Strategy and Management
Citations in the corpus
- Artificial intelligence in operations management and supply chain management: an exploratory case study (2021, background): “Examples of this kind of task are related to machine vision, natural The AI research community has been connected to DSS and other approaches in the area of operation management, such as planning and scheduling since the 1960s (Nemati et al. 2002; C¸alis¸ and Bulkan 2015).”
- Employee relationship and knowledge sharing: a case study of a Taiwanese finance and securities firm (2004, background): “Knowledge warehouse and knowledge mining are the architecture for creating, sharing, leveraging, and learning knowledge in order to implement decision support and knowledge management in organization (Nemati et al., 2002).”
- Knowledge management technologies and applications - literature review from 1995 to 2002 (2003, background): “Keywords: Knowledge management; Knowledge management technologies; Knowledge management applications; Literature survey”