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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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Preface

Almost every field of study is generating an unprecedented amount of data. Retail companies collect data on every sales transaction, organizations log each click made on their web sites, and biologists generate millions of pieces of information related to genes daily. The volume of data being generated is leading to information overload and the ability to make sense of all this data is becoming increasingly important. It requires an understanding of exploratory data analysis and data mining as well as an appreciation of the subject matter, business processes, software deployment, project management methods, change management issues, and so on.

The purpose of this book is to describe a practical approach for making sense out of data. A step-by-step process is introduced that is designed to help you avoid some of the common pitfalls associated with complex data analysis or data mining projects. It covers some of the more common tasks relating to the analysis of data including (1) how to summarize and interpret the data, (2) how to identify nontrivial facts, patterns, and relationships in the data, and (3) how to make predictions from the data.

The process starts by understanding what business problems you are trying to solve, what data will be used and how, who will use the information generated and how will it be delivered to them. A plan should be developed that includes this problem definition and outlines how the project is to be implemented. Specific and measurable success ...

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