Information Quality [Paperback]

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, MonlӁ