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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