Data Preparation

The Data Preparation phase covers all activities to construct the final dataset (the data that will be fed into the modeling tool(s)) from the initial raw data. Data Preparation is often described as the most labor-intensive phase for the data analyst. It is terribly important that Data Preparation is done well, and a substantial amount of this book is dedicated to it. We cover cleaning, selecting, integrating, and constructing data, in Chapter 5, Cleaning and Selecting Data; Chapter 6, Combining Data Files; and Chapter 7, Deriving New Fields, respectively. However, a book dedicated to the basics of data mining can really only start you on your journey when it comes to Data Preparation, since there are so many ways in which you can improve and prepare data. When you are ready for a more advanced treatment of this topic, there are two resources that will go into Data Preparation in much more depth, and both have extensive Modeler software examples: The IBM SPSS Modeler Cookbook (Packt Publishing) and Effective Data Preparation (Cambridge University Press).

The five Data Preparation tasks are:

• Select data
• Clean data
• Construct data
• Integrate data
• Format data