Data Quality for Analytics Using SAS

Additional Book Details

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.

Book Review

"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

Additional resources for this book can be found by accessing the link below.