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Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining by Glenn J. Myatt

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1.1 OVERVIEW

Disciplines as diverse as biology, economics, engineering, and marketing measure, gather and store data primarily in electronic databases. For example, retail companies store information on sales transactions, insurance companies keep track of insurance claims, and meteorological organizations measure and collect data concerning weather conditions. Timely and well-founded decisions need to be made using the information collected. These decisions will be used to maximize sales, improve research and development projects and trim costs. Retail companies must be able to understand what products in which stores are performing well, insurance companies need to identify activities that lead to fraudulent claims, and meteorological organizations attempt to predict future weather conditions. The process of taking the raw data and converting it into meaningful information necessary to make decisions is the focus of this book.

It is practically impossible to make sense out of data sets containing more than a handful of data points without the help of computer programs. Many free and commercial software programs exist to sift through data, such as spreadsheets, data visualization software, statistical packages, OLAP (On-Line Analytical Processing) applications, and data mining tools. Deciding what software to use is just one of the questions that must be answered. In fact, there are many issues that should be thought through in any exploratory data analysis/data mining project. ...

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