Organizations today have access to vast stores of data that come in a wide variety of forms and may be stored in places ranging from file cabinets to databases, and from library shelves to the Internet. The enormous growth in the quantity of data, however, has brought with it growing problems with the quality of information, further complicated by the struggles many organizations are experiencing as they try to improve their systems for knowledge management and organizational memory. Failure to manage information properly, or inaccurate data, costs businesses billions of dollars each year. This volume presents cutting-edge research on information quality. Part I seeks to understand how data can be measured and evaluated for quality. Part II deals with the problem of ensuring quality while processing data into information a company can use. Part III presents case studies, while Part IV explores organizational issues related to information quality. Part V addresses issues in information quality education.
Acknowledgments; Foreword, Vladimir Zwass; 1. Introduction, Elizabeth M. Pierce; Part I. Measuring Data Quality; 2. Measuring Data Accuracy: A Framework and Review, Thomas C. Redman; 3. Developing Measurement Scales for Data Quality Dimensions, Leo Pipino, Richard Wang, David Kopcso, and William Rybolt; 4. A Cyclic-Hierarchical Method for Database Data Quality Evaluation and Quality Evaluation and Improvement, Jennifer A. Long and Craig E. Seko; 5. Model-Based Data Quality Evaluation: A Comparison of Internet Classifieds Operated by Newspapers and Non-Newspaper Firms, Adenekan Dedeke and Beverly K. Kahn; Part II. Modeling and Developing Information Processes for Information Quality; 6. Building Quality into Information Supply Chains: Robust Information Supply Chains, Adenekan Dedeke; 7. What's in Your Information Product Inventory? Elizabeth M. Pierce; 8. IP-UML: A Methodology for Quality Improvement Based on Information Product Maps and Unified Modeling Language, Monica Scannapieco, Barbara Pernici, and Elizabeth M. Pierce; Part III. Data and Information Quality Improvement: Cases Studies; 9. Introducing Data Quality Management in Data Warehousing, Markus Helfert and Clemens Herrmann; 10. Improving Government-to-Business Relationships Through Data Reconciliation and Process Re-engineering, Marco Bertoletti, Paolo Missier, Monica Scannapieco, Pietro Aimetti, and Carlo Batini; 11. Understanding Interdependencies Between Information and Organizational Processes, Raisa Katz-Haas and Yang Lee; Part IV. Organizational Issues in Information Quality; 12. Exemplifying Business Opportunities for Improving Data Quality from Corporate Household Research, Stuart Madnick, Richard Wang, Krishna Chettayar, Frank Dravis, James Funk, Raissa Katz-Haas, Cindy Lee, Yang Lee, Xiang Xian, and Sumit Bhansali; 13. Criticality of Factors Affecting Data Quality of Accounting Information Systems: How Perceptions of Importance and Performance Can Differ, Hongjiang Xu and Latif Al-Hakim; Part V. Education and Capability-Building in Information Quality; 14. Teaching, Learning, and Curriculum Development to Support Managing Information as a Product, Diane M. Strong, Craig Fisher, David L. Feinstein, and Herbert E. Longenecker, Jr. 15. Redefining the Scope and Focus of Information Quality Work: A General Systems Theory Perspective, Woo Young Chung, Craig Fisher, and Richard Wang; Index; About the Editors and Contributors