By Mahesh Raisinghani
Enterprise Intelligence within the electronic economic system: possibilities, barriers and dangers describes what company Intelligence (BI) is, the way it is being performed and controlled and its significant possibilities, boundaries, concerns and hazards. This publication takes an in-depth examine the scope of worldwide technological switch and BI. in this transition to BI, info doesn't only upload potency to the transaction; it provides worth. businesses which are in a position to leverage the rate and ubiquity of electronic communications are going to have the virtue over people who find themselves late-adopters within the years yet to come. The ebook brings jointly top of the range expository discussions from specialists during this box to spot, outline, and discover BI methodologies, structures, and ways to be able to comprehend the possibilities, obstacles and hazards.
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Publication Date: February 19, 2009
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Extra info for Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks
Hendler, J. (1996). Intelligent agents: Where AI meets information technology. IEEE Expert, 11(6), 20-23. Lederer, A. , & Sims, K. (1998). Using WISs to enhance competitiveness. Communications of the ACM, (41)7, 94-95. Maes, P. (1994). Agents that reduce work and information overload. Communications of the ACM, 37(7), 30-40. , & Guttmann, R. (1998). Agent-mediated electronic commerce: Issues, challenges and some viewpoints. Proceedings of the 2nd International Conference on Autonomous Agents, Minneapolis, Minnesota (May 9-13, pp.
Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. 36 Baritchi from domain analysis and data selection, to data preprocessing and transformation, to the data mining itself, and finally the interpretation and evaluation of the results as applied to the domain. We describe the different flavors of data mining, including association rules, classification and prediction, clustering and outlier analysis, customer profiling, and how each of these can be used in practice to improve a business’ understanding of its customers.
A valid pattern is one that correctly describes the training data and also correctly describes new data with some degree of certainty. The stipulation that patterns be novel and potentially useful is intuitive; what good is a system that points out obvious yet irrelevant redundancies? Finally, it is desirable for the discovered patterns to be ultimately understandable so they can be analyzed further to study their causes and effects. KNOWLEDGE-DISCOVERY STEPS According to Fayyad et al. ” The KDD process can be divided into seven discrete steps, as shown in Figure 1.
Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks by Mahesh Raisinghani