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Enterprise Knowledge Management


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Table of Contents

1. Introduction 2. Who Owns Information? 3. Data Quality in Practice 4. Economic Framework of Data Quality and the Value Proposition 5. Dimensions of Data Quality 6. Statistical Process Control and the Improvement Cycle 7. Domains, Mappings, and Enterprise Reference Data 8. Data Quality Assertions and Business Rules 9. Measurement and Current State Assessment 10. Data Quality Requirements 11. Metadata, Guidelines, and Policy 12. Rule-Based Data Quality 13. Metadata and Rule Discovery 14. Data Cleansing 15. Root Cause Analysis and Supplier Management 16. Data Enrichment/Enhancement 17. Data Quality and Business Rules in Practice 18. Building the Data Quality Practice

Promotional Information

Key Features * Expert advice from a highly successful data quality consultant * The only book on data quality offering the business acumen to appeal to managers and the technical expertise to appeal to IT professionals * Details the high costs of bad data and the options available to companies that want to transform mere data into true enterprise knowledge * Presents conceptual and practical information complementing companies' interest in data warehousing, data mining, and knowledge discovery

About the Author

David Loshin is President of Knowledge Integrity, Inc., a company specializing in data management consulting. The author of numerous books on performance computing and data management, including "Master Data Management" (2008) and "Business Intelligence - The Savvy Manager's Guide" (2003), and creator of courses and tutorials on all facets of data management best practices, David is often looked to for thought leadership in the information management industry.

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