Abstract
Business Intelligence refers to a collection of tools and techniques for data management, analysis and decision support. It is the most commonly-referenced function of the Analytics Domain. In fact, in several cases, this component is mistaken to represent the entire Analytics Domain. As outlined in the Framework for Analytics, BI simply represents one component of a successful analytical framework. While it may be obvious that such a limited view of analytics usually dooms analytical aspirations, there are several reasons (historical, political, financial and serendipitous) why such a perception is endemic and it is critical to understand these reasons if one is to ensure success in an organization’s analytical aspirations.
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Notes
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“Predicts 2012: Business Intelligence Still Subject to Nontechnical Challenges”—Gartner Research ID Number G00227192.
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Rick van der Lans, international BI expert from R20/Consultancy, ITWeb BI Summit, Feb 2012.
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Kimball R , Caserta J (2004) The data warehouse ETL toolkit. Wiley, Indianapolis.
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Kimball R (1996) The data warehouse toolkit. Wiley, New York.
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Inmon B (1992) Building the data warehouse. Wiley, New York.
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A more detailed comparison of the data warehouse structures and the trade-offs can be obtained from Robert Hilliard in his book: Hillard R (2010) Information-driven business. Wiley, New York.
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Online Analytical Processing (OLAP) cube is an array of data that is arranged by multiple dimensions. These are very commonly used in Business Intelligence systems for fast retrieval of organized data grouped and categorized along any on the cubes dimensions.
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Saxena, R., Srinivasan, A. (2013). Business Intelligence. In: Business Analytics. International Series in Operations Research & Management Science, vol 186. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6080-0_7
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DOI: https://doi.org/10.1007/978-1-4614-6080-0_7
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