Download e-book for iPad: Business Intelligence in the Digital Economy: Opportunities, by Mahesh Raisinghani

By Mahesh Raisinghani

ISBN-10: 1591402069

ISBN-13: 9781591402060

Company Intelligence within the electronic financial system: possibilities, obstacles and hazards describes what enterprise Intelligence (BI) is, the way it is being carried out and controlled and its significant possibilities, boundaries, concerns and hazards. This publication takes an in-depth examine the scope of world technological swap 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 those who find themselves late-adopters within the years yet to come. The ebook brings jointly prime quality expository discussions from specialists during this box to spot, outline, and discover BI methodologies, platforms, and ways in an effort to comprehend the possibilities, obstacles and hazards.

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There are no limits to the possible uses of classification or the number of “buckets” into which the records can be classified. Regression: learning a function f that, when given as input in a set of variables to represent a data record, maps the record to a real-valued prediction variable. Note that regression is very similar to classification, with the exception that the function is mathematically more complex due to its non-discrete nature. Clustering: discovering groups (clusters) of similar items in the input data.

Anatomy of Risk. New York: Wiley. Copyright © 2004, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. E. (1999). The Complexity Challenge. London: Pinter Publishers. , & Bowman-Upton, N. (1990). Female and male entrepreneurs: Psychological characteristics and their role in gender-related discrimination. Journal of Business Venturing, 5(1), 29-36. Shapira, Z. (1995). Risk Taking: A Managerial Perspective. New York: Russell Sage.

Is prohibited. Data Mining and Knowledge Discovery 39 These seven steps, which collectively form the methodology of the KDD process, are explained as follows: 1. 2. 3. 4. 5. 6. 7. Domain Analysis: the nature of the data in the domain is analyzed and the goals of the discovery are considered. If any prior domain knowledge exists, it is evaluated. Selection: the data is reduced to a target data set containing the desired data to analyze, which can mean eliminating fields or rows in the data, or both.

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Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks by Mahesh Raisinghani

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