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Essay / Research Paper Abstract
3 pages in length. With success or failure only as close as the nearest competitor, contemporary organizations spare no expense when it comes to unearthing new and more effective ways to stay ahead of the rest of the industry. Business Intelligence (BI) represents one of the most prudent and viable ways in which to accomplish this objective, inasmuch as it addresses an expansive element of technologies and programs where collection, storage, analysis and data access are concerned. Bibliography lists 6 sources.
Page Count:
3 pages (~225 words per page)
File: LM1_TLCBizIntell.rtf
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Unformatted sample text from the term paper:
stay ahead of the rest of the industry. Business Intelligence (BI) represents one of the most prudent and viable ways in which to accomplish this objective, inasmuch as it
addresses an expansive element of technologies and programs where collection, storage, analysis and data access are concerned. Information abounds in todays technologically-advanced society (Boomer, 2006); however, just as too little
information can be detrimental to an organizations success, so too can an overabundance of useless data; unable to wade through the vast amount of information inherent to contemporary commerce, many
organizations merely continue to paddle in place as the competition passes them by. As such, the notion of data mining is one of the most integral components of Business
Intelligence - which also includes decision support, statistical analysis, query and reporting, forecasting and online analytical processing (OLAP) (Grimes, 2006) - inasmuch as it ferrets out critical information and leaves
behind all the inconsequential and copious amounts of fluff. The contemporary version of data mining is Web mining, which provides a key application to facilitate Business Intelligence in an
e-business initiative. "The online analytical processing tool arena is now in its second decade, and the focus of business intelligence innovation has shifted to dashboard displays, applications such as
performance management, and operationally embedded analytics" (Grimes, 2006, p. 10). Web mining utilizes the vast and comprehensive availability of information that determines how and why a user visits a
particular site, allowing the organization to fine tune marketing strategies based upon the findings (Li et al, 2006). The ever-changing face of global e-commerce has called for greater efficiency
when it comes to understanding user habits, a critical component of online retailers that helps maintain knowledge of what users want and how they go about retrieving it. Modification
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