- Explains the business value and impact of entity information management system (EIMS) and directly addresses the problem of EIMS design and operation, a critical issue organizations face when implementing MDM systems- Offers practical guidance to help you design and build an EIM system that will successfully handle big data- Details how to measure and evaluate entity integrity in MDM systems and explains the principles and processes that comprise EIM- Provides an understanding of features and functions an EIM system should have that will assist in evaluating commercial EIM systems- Includes chapter review questions, exercises, tips, and free downloads of demonstrations that use the OYSTER open source EIM system - Executable code (Java .jar files), control scripts, and synthetic input data illustrate various aspects of CSRUD life cycle such as identity capture, identity update, and assertions
Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.
1. The Value Proposition for MDM and Big Data? 2. What is entity information lifecycle management? 3. Metrics for Quantifying Entity Integrity 4. Identity Capture Deep Dive 5. Identity Archiving and Disposal 6. Identity Resolution 7. Identity Update 8. CSRUD for Big Data 9. Toward Big Data Analytics 10. Final Thoughts
Dr. John R. Talburt is Professor of Information Science at the University of Arkansas at Little Rock (UALR) where he is the Coordinator for the Information Quality Graduate Program and the Executive Director of the UALR Center for Advanced Research in Entity Resolution and Information Quality (ERIQ). He is also the Chief Scientist for Black Oak Partners, LLC, an information quality solutions company. Prior to his appointment at UALR he was the leader for research and development and product innovation at Acxiom Corporation, a global leader in information management and customer data integration. Professor Talburt holds several patents related to customer data integration and the author of numerous articles on information quality and entity resolution, and is the author of Entity Resolution and Information Quality (Morgan Kaufmann, 2011). He also holds the IAIDQ Information Quality Certified Professional (IQCP) credential.
Dr. Yinle Zhou is an IBM software architect and data scientist in the InfoSphere MDM development group in Austin, Texas, and also serves as an Affiliate Member of the Graduate Faculty at University of Arkansas at Little Rock (UALR). Dr. Zhou holds a PhD in Integrated Computing with Emphasis in Information Quality (IQ) from UALR where her doctoral research focused on modeling the management of entity identity information in entity resolution systems. She also holds a Master of Science in Information Quality from UALR, a Bachelor of Business Administration in Electronic Commerce from Nanjing University in China, and the Information Quality Certified Professional (IQCP) credential issued by the International Association for Information and Data Quality (IAIDQ). Her research and publications are in areas of information quality, identity management, entity and identity resolution, and social computing