Management - Data Warehousing And Essay

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At times, though, data mining and data warehousing can become more trouble than they are actually worth, and that can lead to all types of problems for a company (Thearling, 2009). In order to make sure that data mining and warehousing do not become too much trouble for a company to handle, it is vital that the company is clear on the data it wishes to collect. There is no reason to collect every single scrap of data from every person who uses the company's website or searches the internet for the product or service that the company offers. Basic demographic information that relates to the company's product or service, or that relates to the creation of a target market segment, is all very important (Greenfield, 2005a. There are many other data markers that are outliers, however, and that will not have any effect on whether a person would use what the company has to offer. When those data markers are also collected, it can become easy for a company to get overwhelmed by the information coming in (Greenfield, 2005b).

Sorting out the important data from the unimportant data is something that must be done at the very early stages of data mining (Thearling, 2009). Then, only the significant data that the company actually needs can be warehoused and used as needed. That is the best way to collect, store, and use any data that a company can benefit from. Companies that use data warehousing must reduce the amount of data that they store and the length of time they keep that data, or they run the risk of simply becoming overwhelmed with information that they really are not using and that they are not able to do anything productive with. Avoiding that kind of problem is not always easy, but it is certainly worthwhile for any company no matter the industry in which that...

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Like any business practice, though, it can be overused and misused to the point that it is no longer valuable to the company (Greenfield, 2005b). Because of the potential for problems, data mining and data warehousing should be treated with caution by any company involved with either one or both of those practices. By mining and warehousing only the data that is really necessary to help the company stay on track, move forward, and keep up with the competition, the company will be much more likely to see success and not become overwhelmed by the collection and study of data. When done correctly, there is a great deal of value to be seen from mining and warehousing data that is collected from customer and prospective customers.

Sources Used in Documents:

References

Betancourt, L. (2010). How Companies are using your Social Media Data, Retrieved on July 26, 2010 from http://www.enterpriseirregulars.com/5706/the-top-10-trends-for-2010-in-analytics-business-intelligence-and-performance-management/

Greenfield, L. (2005a) The Case for Data Warehousing Retrieved on July 26, 2010 from http://www.dwinfocenter.org/casefor.html

Greenfield, L. (2005b) The Case Against Data Warehousing Retrieved on July 26, 2010 from http://www.dwinfocenter.org/against.html

Hadfield, M. (2009) Case Study: Jaeger uses data mining to reduce losses from crime and waste Retrieved on July 26, 2010 from http://www.computerweekly.com/Articles/2009/02/23/234953/case-study-jaeger-uses-data-mining-to-reduce-losses-from-crime-and.htm
Thearling, K. (2009) An Introduction to Data Mining. Retrieved July 26, 2010 from http://www.thearling.com/dmintro/dmintro_2.htm


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