Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
Poor data quality can seriously hinder the effectiveness of organizations and businesses. Growing awareness of this has led to major public initiatives like the "Data Quality Act" in the USA and the "European 2003/98" directive of the European Parliament.
Here is a systematic introduction to the array of issues related to data quality. The book opens by describing the parameters of data quality: accuracy, completeness and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change. The text gives an excellent overview of the current state of the art, describing techniques and methodologies from core data quality research and from related fields like data mining, statistical data analysis, and machine learning. The presentation concludes with a critical comparison of tools and practical methodologies, to help readers resolve their own quality problems. This book is a useful combination of the theoretical and the practical.
Data Quality is well-suited for researchers, students, or professionals, and serves as a bas
Content Level »Professional/practitioner
Keywords »Data Accuracy - Data Availability - Data Completeness - Data Consistency - Data Integration - Data Quality - Distributed Data Management - data mining - learning - organization