[request_ebook] Data Preparation for Analytics Using SAS (SAS Press) (Paperback)

Description

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.

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