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Research Note Description:
In contrast to OLAP, which organizes data into predefined multidimensional structures to facilitate exploration, data mining performs the explorative analysis and identifies interesting nuggets of information such as groupings of data for the analyst or manager to examine. Data mining can also create decision trees that can be used to predict future data based on attributes of existing data elements. Analysis Services incorporates sophisticated data mining algorithms that can be used to analyze data in the relational database or in OLAP cubes. The results of the data mining analysis can also be used with OLAP cubes to enhance explorative analysis. For example, you can let data mining find groupings of customers according to their attributes and then use these groupings to create an additional dimensional view of OLAP data cubes and explore the data from the perspective of these groupings. For more information, see this note in the
Microsoft Library
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Prof. Ashay Dharwadker