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Essay / Research Paper Abstract
This 3 page paper examines both positive and negative aspects. Bibliography lists 3 sources.
Page Count:
3 pages (~225 words per page)
File: RT13_SA848dm.rtf
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does give companies an edge. However, sometimes these processes are more trouble than they are worth. Sometimes, it is better to forgo these processes because they are not conducive to
a lean structure that is indicated in a time when money issues loom large. The economy is in a significant slump. Large companies are folding and others are being
bailed out by the government. Data-mining and data-warehousing are costly and should really be eliminated if not necessary. Even if a company is doing well, it may be thought of
as a great expense. Sometimes it is worthwhile, but it is probably not desirable for a number of small to medium-sized firms. Certainly, these protocols are not necessary parts of
any companys strategy. In order to evaluate these processes, it pays to examine them both. II. Data-Mining and Data-Warehousing Data mining is actually the
process of analyzing data from different points of view and then summarizing the information so it translates to useful material ("What is data mining," 2008). Data mining software is an
important adjunct for analysis, and data mining in general can be utilized to increase revenue ("What is data mining," 2008). It is about finding patterns or correlations from databases ("What
is data mining," 2008). Advances in data are able to see the processing of power and data transmission ("What is data mining," 2008). It allows organizations to integrate a number
of databases into data warehouses ("What is data mining," 2008). Data-warehousing is thought to be "a process of centralized data management and retrieval" ("What is data mining," 2008). Both data
mining and data warehousing are relatively new ideas but the ideas behind the concept are not all that new ("What is data mining," 2008). When implementing these things, centralization of
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