CHAPTER

Importing Data into Excel

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17

FINDING INFORMATION WITH DATA MINING

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he types of data analysis we discuss in this and other chapters of this book are crucial to the success of most companies in today’s datadriven business world. However, the sheer volume of available data often defies traditional methods of data analysis.Therefore, a whole new set of methods—and accompanying software—has recently been developed under the name of data mining. Data mining attempts to discover patterns, trends, and relationships among data, especially non-obvious and unexpected patterns. For example, the analysis might discover that people who purchase skim milk also tend to purchase whole wheat bread, or that cars built on Mondays before 10 A.M. on production line #5 using parts from suppliers ABC and XYZ have significantly more defects than average.
This new knowledge can then be used for more effective management of a business.
The place to start is with a data warehouse.Typically, a data warehouse is a huge database that is designed specifically to study patterns

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Classification analysis attempts to find variables that are related to a categorical
(often binary) variable. For example, credit card customers can be categorized as those who pay their balances in a reasonable amount of time and those who don’t.
Classification analysis would attempt to find predictive variables that help explain which of these two categories a customer is in. Some variables, such as salary, are natural candidates for predictors, but the analysis might uncover less obvious predictors. Prediction is similar to classification analysis, except that it tries