Entity Information Life Cycle for Big Data - Info and Reading Options
Master Data Management and Information Integration
By John R. Talburt and Yinle Zhou
"Entity Information Life Cycle for Big Data" was published by Elsevier Science & Technology Books in 2015 - Amsterdam Boston, it has 254 pages and the language of the book is English.
“Entity Information Life Cycle for Big Data” Metadata:
- Title: ➤ Entity Information Life Cycle for Big Data
- Authors: John R. TalburtYinle Zhou
- Language: English
- Number of Pages: 254
- Publisher: ➤ Elsevier Science & Technology Books
- Publish Date: 2015
- Publish Location: Amsterdam Boston
“Entity Information Life Cycle for Big Data” Subjects and Themes:
- Subjects: ➤ Database management - Big data - Semantic Web - Pattern recognition systems - Data mining - Massendaten - Managementinformationssystem - Informationsintegration - Datenmanagement
Edition Identifiers:
- The Open Library ID: OL28566267M - OL21103464W
- Online Computer Library Center (OCLC) ID: 910078680
- Library of Congress Control Number (LCCN): 2015506891
- ISBN-13: 9780128005378
- All ISBNs: 9780128005378
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"Entity Information Life Cycle for Big Data" Description:
Open Data:
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
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