Data Preparation for Analytics

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Written by Gerhard Svolba in SAS Press. See Data Preparation for Analytics Using SAS. The book is also available at

Written for anyone involved in the data preparation process for analytics, this user-friendly text offers practical advice in the form of SAS coding tips and tricks, along with providing the reader with a conceptual background on data structures and considerations from the business point of view. Topics addressed include viewing analytic data preparation in the light of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations for data preparation for time series analysis, using various SAS procedures and SAS Enterprise Miner for scoring, creating meaningful derived variables for all data mart types, using powerful SAS macros to make changes among the various data mart structures, and more!


Customer Reviews

***** Christine Hallwirth: "Data Preparation for Analytics" is an excellent handbook for data miners and business analysts, October 18, 2007 This is a must read for anyone, who prepares data for data mining and analytics. Not only you receive ideas and suggestions for important derived variables for your datamart, you also get a lot of insight on the business rationale behind the scenes. The author does a great job in explaining you step by step the world of data preparation for data mining and shows a lot of example code and macros.

***** Lessia Shajenko: "Data Preparation for Analytics" is an encyclopedia for data miners and business analysts, May 3, 2007 In "An Owner's Manual" to Berkshire Hathaway shareholders, Warren Buffett wrote that, in respect to investment choices, he and most of the company's directors "eat their own cooking." Gerhard Svolba's book "Data Preparation for Analytics" is an "owner's manual" for data miners, business analysts and all who prefer to be in charge of and responsible for their own datasets. This book is for those who are not afraid of data, who understand data, and for whom rolling up their sleeves and getting their hands into data is an integral part of analytics and predictive modeling. The book takes the reader from a bird's-eye view of relational database models and their special forms (star, snowflake schemas) and various aspects of analysis process to detailed "classic" examples on how to structure datasets, transpose them, aggregate values to one-row-per-subject, bin observations into groups, deal with outliers and missing values, derive variables by concatenating absolute and relative frequencies, create categorical interaction variables, perform deviation (effect) coding and so forth. It walks you through the steps of formulating hypotheses you want to test and questions you want to answer and guides you on the selection of the most appropriate dataset design for your analysis. The chapters and sections of the book that particularly drew my attention were Coding for Predictive Modeling, Data preparation for Association and Sequence analysis, and Preparing Time Series Data with SAS Functions. From sampling to scoring and beyond, "Data Preparation for Analytics" has a wealth of handy SAS examples as well as ideas that you can further explore on your own. With several case studies including customer segmentation, data preparation with SAS Enterprise Miner and preparing data for time series analysis, Dr. Svolba stimulates your creative thinking which, for some readers, could be motivation enough to write their own book.

***** Günter Schmölz: A must to prepare data for advanved datamining, 11. April 2007 This book is a must for those, who are preparing data for datamining and those who want to be efficient and effective in preparing any meaningful analyses. It provides a lot of examples how to transform variables and data. I have got practical experience with SAS for more than 10 years, but this book gave me many new approaches, ideas and solutions. This book is very convenient and enjoyable to use, because it often starts with basics, so it is easy to understand and it makes it easy to get into it. Additionally it leads to more sophisticated solutions. This book deals exactly with those topics which are central for advanced datamining.

***** Friedrich Bauernberger 2007: Data Preparation, zweifellos der wichtigste Teil eines jeden Data Mining Projekts, wird meist zu wenig Aufmerksamkeit zu Teil. Dieses Buch nimmt sich genau dieser Thematik an und bietet selbst für einen erfahrenen SAS-User Tipps & Tricks um effizienter und schneller Daten aufzubereiten. Ein Buch aus der Praxis - ich konnte einige Bereich gleich in aktuelle Projekte übernehmen. Bleibt als einzige Kritik dass ich dieses Buch bereits vor 10 Jahren benötigt hätte.