I am a student who has an assignment in which I have to define the role of data mining in enterprise decision support systems. Any help would be greatly appreciated.
I was hunting for information on Data Mining and Data warehousing a while ago. And I found SAS a very good resource for these topics. Go to the website :
It is important to define Data Mining correctly. Many vendors will tell you that drilling down into data is 'mining', this is really 'data discovery'. My definition is that Data Mining involves a product that generates information (rules, trends, patterns, etc.) from data.<br>
The main uses for Data Mining are;<br>
1. Segmentation - identifying similar characteristics of customers that might indicate a propensity to purchase.<br>
2. Clustering - grouping into clusters of alike customers<br>
3. Rule generation - e.g. a neural net that decides whether a customer is a good lead.<br>
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see. SPSS, Angoss KnowledgeSeeker, Model-1 and others.
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Data mining is discovering previously unknown patterns in large volumes of data. These patterns reveal wisdom that has real business significance and when acted upon make a measurable impact to a business's bottom line.<br>
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You better believe that this is more than just OLAP. There is a business focussed methodology involved here coupled with some serious statistical methods. Neural Networks ring a bell?<br>
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Another misconception worth mentioning about DM is that you can do it without the help of a statisticial.....forget it. And while I'm about it I may as well tell you that if you dont want your statistician to waste 80% of his/her time on dataprocessing issues then for goodness sake supply him/her with data from a data mart or data warehouse and use your data warehouse to disseminate the valuable findings from your data mining efforts.<br>
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Cheers<br>
SASMAN
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