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DATA WAREHOUSING FUNDAMENTALS: A Comprehensive Guide for IT Professionals by Paulraj Ponniah

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17.2. WHAT IS DATA MINING?

Before providing some formal definitions of data mining, let us try to understand the technology in a business context. Like all decision support systems, data mining delivers information. Please refer to Figure 17-1 showing the progression of decision support. Note the earliest approach, when primitive types of decision support systems existed. Next came database systems providing more useful decision support information. In the 1990s, data warehouses with query and report tools to assist users in retrieving the types of decision support information they need began to be the primary and valuable source of decision support information. For more sophisticated analysis, OLAP tools became available. Up to this point, the approach for obtaining information was driven by the users. But the sheer volume of data renders it impossible for anyone to use analysis and query tools to discern useful patterns. For example, in marketing analysis, it is almost impossible to think through all the probable associations and gain insights by querying and drilling down into the data warehouse. You need a technology that can learn from past associations and results, and predict customer behavior. You need a tool that will accomplish the discovery of knowledge by itself. You want a data-driven approach and not a user-driven one. This is where data mining steps in and takes over from the users.

Figure 17-1. Decision support progresses to data mining.

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