Data Preparation for Analytics Using SAS (SAS Press) | 
 enlarge | Author: Gerhard, Ph.d. Svolba
Publisher: SAS Publishing
Category: Book
List Price: $67.95
Buy New: $60.87
You Save: $7.08 (10%)
New (7) Used (7) from $51.46
Avg. Customer Rating:  3 reviews
Sales Rank: 734831
Media: Paperback
Number Of Items: 1
Pages: 440
Shipping Weight (lbs): 2.1
Dimensions (in): 10.9 x 8.4 x 0.9
ISBN: 1599940477
Dewey Decimal Number: 005
EAN: 9781599940472
ASIN: 1599940477
Publication Date: November 30, 2006
Availability: Usually ships in 1-2 business days
Condition: BRAND NEW. 30 Day Satisfaction Guarantee. Quick International Airmail!
|
| Similar Items:
|
| Editorial Reviews:
Product Description
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:
 A reasonably good book for SAS data preparation. March 5, 2008
3 out of 3 found this review helpful
This is a good introduction about data preparation and management using SAS. The author covered some fundamental issues in building data mart and data manipulation. The macros included in the book are quite useful.
What I don't like about the book is its chatty style. A few basic topics are mentioned many times throughout the book. The first few chapters about the business rationale and background knowledge are also too long.
The coverage on time series analysis is extremely light. We can't quite blame the author, because the econometric functionalities in SAS/ETS are a bit out of date and limited.
 "Data Preparation for Analytics" is an excellent handbook for data miners and business analysts October 18, 2007
1 out of 1 found this review helpful
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.
"Data Preparation for Analytics" is an encyclopedia for data miners and business analysts May 3, 2007
5 out of 5 found this review helpful
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.
|
|
|
