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Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.

Audience
data quality practitioners, data analysts, business analysts, database administrators, data administrators, data stewards, data architects, and data modelers; IT management, CIO, CTO and CKO people and their staffs; graduate CS students in data mining classes, graduate b-school students in IT management courses

Table of Contents
Preface. Acknowledgements. Forward.

Part 1: Understanding Data Accuracy: The Data Quality Problem. Definition of Accurate Data. Sources of Inaccurate Data.

Part 2: Implementing a Data Quality Assurance Program: Data Quality Assurance. Data Quality Issues Management. The Business Case for Accurate Data.

Part 3: Data Profiling Technology: Data Profiling Overview. Column Property Analysis. Structure Analysis. Single Data Rule Analysis. Complex Object Data Rule Analysis. Value Rule Analysis. Summary. Appendixes : Example of Column Properties, Data Structure, Data Rules and Value Rules. Content of Data Profiling Repository.

Bibliography.

Index.

292 pages