Data Quality for Analytics Using SAS

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SAS Institute, Apr 1, 2012 - COMPUTERS - 356 pages
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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.

This book is part of the SAS Press program.

 

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Contents

Data QualityProfiling and Improvement
121
Consequences of Poor Data QualitySimulation Studies
199
References
327

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About the author (2012)

Gerhard Svolba, Ph.D. is a product manager and pre-sales consultant at SAS Institute Inc. in Austria, where he specializes in Analytics and customer intelligence. His project experience ranges from conceptual considerations (both business and technical) to data preparation and analytic modeling.

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