Here is the synopsis of our sample research paper on Data Mining as a Competitive Business Intelligence Tool
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Essay / Research Paper Abstract
This is a 7 page paper discussing data mining. The increasingly competitive markets have resulted in the development of more sophisticated business intelligence tools which can be applied to data warehouses. Data mining tools have been developed to not only give businesses the advantage of analyzing past and present data within their organizations but also allow future trends and analysis of customer behavior among other significant factors which give businesses an increase in focus in customer relations and marketing in a more efficient and non-redundant manner. Included in the paper is a 1 page outline, description of the leading data mining tools and an example of a business (PNC Bank Corp.) who purchased a data mining tool (Unica’s Model 1) in order to give them a competitive advantage in regards to marketing and expanding their customer satisfaction base.
Bibliography lists 6 sources.
Page Count:
7 pages (~225 words per page)
File: D0_TJdatam1.rtf
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Unformatted sample text from the term paper:
developed to not only give businesses the advantage of analyzing past and present data within their organizations but also allow future trends and analysis of customer behavior among other significant
factors which give businesses an increase in focus in customer relations and marketing in a more efficient and non-redundant manner. Several data mining tools have been developed within the
last five years which include Cognos Scenario TM, Angoss Knowledge Suite, SPSS Clementine and the current leaders in the industry: Enterprise Miner by SAS; Darwin by Oracle; Model 1 by
Unica; and, MineSet by SGI. A graphic of a comparison of seventeen data mining tools available shows the strengths and weaknesses of each product which is also helpful in businesses
making decisions about which factors are the most important to them when choosing a data mining tool. Along with expense, businesses should consider ease of use, compatibility, depth of algorithms
and tree options available among other functions. Regardless of the data mining tool selected, all researchers and analysts within the field agree that businesses data warehouses must be cleaned first
to avoid importation of any unnecessary data. There are several Extraction, Transformation and Loading (ETL) tools also available to help do this but it is mandatory to clean out any
"junk" from the system before uploading the data and implementing a data mining tool. PNC Bank Corp. is used as an example of a high profile business which chose
to use one of the leading tools, Unicas Model 1. In focusing on the importance of their customer relations and functions, PNC felt that the implementation of a data mining
tool would allow them to better analyze their customer needs in a more efficient manner thus giving them a competitive edge. Data Mining
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