Entity Information Life Cycle for Big Data walks you through the ins and outs of managing entity information so you can successfully achieve master data management (MDM) in the era of big data. This book explains big data's impact on MDM and the critical role of entity information management system (EIMS) in successful MDM. Expert authors Dr. John R. Talburt and Dr. Yinle Zhou provide a thorough background in the principles of managing the entity information life cycle and provide practical tips and techniques for implementing an EIMS, strategies for exploiting distributed processing to handle big data for EIMS, and examples from real applications. Additional material on the theory of EIIM and methods for assessing and evaluating EIMS performance also make this book appropriate for use as a textbook in courses on entity and identity management, data management, customer relationship management (CRM), and related topics.

Discover the details of managing entity information to successfully achieve master data management (MDM) in the era of big data. "Entity resolution and identity information management are the major challenges in master data management. John Talburt and Yinle Zhou have synthesized their considerable expertise to address this challenge in the era of big data. Anyone who wants to manage data strategically should start here." - Laura Sebastian-Coleman, Data Quality Center of Excellence Lead, Cigna

About the Author
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

Reviews
"...good as a textbook and also as independent reading for professionals in the sector. The references where the solutions and methods treated were originally presented are included so that they can be found for further reading...a highly recommended book." --Computing Reviews "... covers MDM in a traditional manner, that is, maintaining current entity identity information, very well, and it can be recommended to advanced MDM practitioners (and advanced students of databases and data warehouses)." --Computing Reviews



Book Information
ISBN 9780128005378
Author John R. Talburt
Format Paperback
Page Count 254
Imprint Morgan Kaufmann Publishers In
Publisher Elsevier Science & Technology
Weight(grams) 540g