Data Quality for Analytics Using SAS - Softcover

Svolba Ph.D., Gerhard

Softcover

ISBN 10: 160764620X ISBN 13: 9781607646204

Publisher: SAS Institute, 2012

Synopsis

Analytics offers many capabilities and options to measure and improve data quality, and SAS is perfectly suited to these tasks. Gerhard Svolba's Data Quality for Analytics Using SAS focuses on selecting the right data sources and ensuring data quantity, relevancy, and completeness. The book is made up of three parts. The first part, which is conceptual, defines data quality and contains text, definitions, explanations, and examples. The second part shows how the data quality status can be profiled and the ways that data quality can be improved with analytical methods. The final part details the consequences of poor data quality for predictive modeling and time series forecasting.

With this book you will learn how you can use SAS to perform advanced profiling of data quality status and how SAS can help improve your data quality.

About this title

About the Author

Dr. Gerhard Svolba is a senior solutions architect and analytic expert at SAS Institute Inc. in Austria, where he specializes in analytics in different business and research domains. His project experience ranges from business and technical conceptual considerations to data preparation and analytic modeling across industries. He is the author of Data Preparation for Analytics Using SAS and teaches a SAS training course called "Building Analytic Data Marts."

Review

Data quality is the key ingredient for a successful analytics project. In our past research, we have extensively shown that the best investment to boost the performance of any analytical model is by understanding and improving data quality.

In his book, Gerhard Svolba provides comprehensive coverage of the topic by defining data quality first, followed by providing well-articulated guidelines to profile and improve data quality, and concluding with illustrating the impact of poor data quality in predictive modeling and time series forecasting, among other examples. The book is well-structured and written, with lots of practical examples clarifying the ideas presented. In short, I consider the book a must-read for anyone working on developing high-performing analytical models! --Dr. Bart Baesens, Professor, Department of Decision Sciences and Information Management, KU Leuven

Edition details

• Publisher: SAS Institute
• Publication date: 2012
• ISBN 10: 160764620X
• ISBN 13: 9781607646204
• Binding: Paperback
• Language: English
• Number of pages: 356