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Master Data Management and Data Governance (Alex Berson)（Z-Library）

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Master Data Management and Data Governance (Alex Berson)（Z-Library）

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The latest techniques for building a customer-focused enterprise environment "The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works." — Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc. Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and...

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This is a great book about MDM and its impact on our businesses, governments, and in many ways most of our lives. Written in a simple and effective style, it tells the story of how Master Data Management works, what it does, and why we should care very much how it is governed. If you have any interest in MDM, data or information governance, read this book. —Steven B. Adler, CIPP IBM Information Governance Solutions In this book, Alex Berson and Larry Dubov convey the many facets of the value of adopting Master Data Management techniques while ably articulating an implementation roadmap. By maintaining the need to incorporate business process modeling, master data modeling, master metadata management, and data governance, the authors properly frame the necessary ideas for organizational preparation while still providing deep technical detail about both architecture and algorithms. This book is a definite addition to the MDM body of knowledge. —David Loshin President, Knowledge Integrity Incorporated Alex and Larry have done it again: published a very comprehensive, highly applicable book on MDM and data governance that achieves an excellent balance between thought-provoking academic treatment of some very technical subjects, and highly relevant, usable advice on how to achieve success in implementing a successful MDM and data governance program. This is a must-read for any program sponsor, CIO, CTO, enterprise architect, information architect, data steward, program manager, or practitioner of MDM and data governance. This is not a read-and-forget book, but a great reference manual. —Martin Moseley Chief Architect, CTO, Information Agenda Tiger Team IBM Software Group This work is one of the most comprehensive, clear, well-researched, and insightful guidebooks on Master Data Management and data governance. Larry and Alex did an exceptional job covering these complex topics from many viewpoints, including technical, business, architectural, security, industry, social, international, product, and regulatory perspectives. I was so impressed at the level of detail and how much is in this book. The book
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covers critical principles, concepts, emerging trends, and misconceptions, based upon the authors’ extensive experience and research, and clarifies keys in creating successful MDM and data governance programs. —Len Silverston Best-selling author of The Data Model Resource Book, Volumes 1, 2, and 3 Clearly, Alex Berson and Larry Dubov were hard at work tackling the tough topic of “master data governance” before the software vendor community had yet found religion (as the market now has “active,” “passive,” and my favorite “passive-aggressive” data governance flavors among the many marketing variations). —Aaron Zornes Chief Research Officer The MDM Institute, San Francisco
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About the Authors Alex Berson is an internationally recognized expert, thought leader, author, and advisor in various areas of information technologies. Throughout his professional career, Alex held leadership technology and management positions in companies such as BearingPoint, Entrust, Merrill Lynch, enCommerce, Dun & Bradstreet, PricewaterhouseCoopers, Solomon Smith Barney, and others. He’s currently a chief technology architect for a major global financial services institution. Alex holds graduate and postgraduate degrees in Applied Math and Computer Sciences and has an extensive scientific background in applied research with specific concentration on advanced areas of algorithmic computations, linear programing, computer simulations, and computing architectures. He taught undergraduate and graduate classes and lectured on these topics throughout his career. Alex combines his extensive scientific background and practical industry experience by focusing his professional activities on advanced multi-disciplined areas of information technology such as Identity Management and Information Security; Master Data Management (MDM) and Customer Data Integration (CDI); CRM and Business Intelligence; Database technologies, including Column-store and very large databases (VLDB); data warehousing and data mining; service-oriented architecture (SOA); mobile computing; enterprise application integration (EAI), messaging, and middleware. Throughout his career, Alex has continued to successfully apply his knowledge, experience, and vision to creating complex ground-breaking solutions for financial services, manufacturing, pharmaceutical and technology industries. Alex is a member of the Board of Directors of the Wall Street Technology Association (WSTA) and is a member of Standard & Poor’s Vista Research Society of Industrial Leaders (SIL). He actively participates in professional associations such as IEEE Computer Society, ACM, and Aberdeen Group’s Technology Forecasting Consortium; standards organizations including OMG, OASIS, Open Group; various industry consortia such as the Data Warehousing Institute (TDWI), and technical advisory boards of several technology companies.
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Alex has published numerous direction-setting technical articles in trade magazines and online publications, and is the author and coauthor of a number of best-selling professional books, including Master Data Management and Data Governance; Master Data Management and Customer Data Integration for a Global Enterprise; Building Data Mining Applications for CRM; Data Warehousing, Data Mining and OLAP; Client/Server Architecture; SYBASE and Client/Server Computing; and APPC: Introduction to LU6.2. Dr. Lawrence Dubov (Larry) is a recognized scientist, expert and thought leader in the implementation of complex business-driven technology solutions for financial services, banking, telecommunications, and pharmaceutical verticals, with the primary focus on Master Data Management (MDM), Customer Relationship Management (CRM), data warehousing, operational data stores, and service-oriented architecture. He has gained both depth and breadth of technical knowledge in multiple areas of Master Data Management, including data and solution architecture, matching technologies, customer-centric data transformations, data stewardship, and applications of information theory and advanced statistical methods to information quality. He has developed a strong holistic vision of the MDM problem domain and Master Data Governance implementation methodology based on practical experience gained through successful project implementations. He is an internationally recognized speaker and writer on the topics of Master Data Management and information management, quality, and governance. Larry has authored over 110 publications, with a recent focus on advanced mathematical methods in data governance, master data modeling, MDM roadmap development, business case definition, and accelerators for high complexity MDM programs and projects. In 2007 he coauthored a definitive book on MDM, Master Data Management and Customer Data Integration for a Global Enterprise. Larry has held senior technology and management positions with IBM, Initiate Systems, Inc., and consulting companies, including BearingPoint and FutureNext ZYGA. Larry formerly worked as an independent consultant for a number of companies across various industry verticals. The list of Larry’s clients includes but is not limited to Fortune 1000 companies and established mid-size organizations, such as Merrill Lynch, Bessemer
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Trust, Washington Mutual, Cenlar Bank, Merck, Johnson & Johnson, Hoffmann La Roche, Aventis, Estée Lauder, AT&T, Daimler-Benz. Larry spent two years at Princeton University as a visiting research scientist working on mathematical models for optimal control of molecular processes. Earlier, during his career in Russia, he gained a strong scientific background with Ph.D. and Dr. Sci. degrees in Mathematical Physics. A combination of multiple backgrounds—science (physics, chemistry, and advanced math), a deep knowledge of information technology, and an understanding of business processes—helps Larry see unique approaches to complex business problems and offer their solutions. About the Technical Editors Bernard K. Plagman is cofounder and chairman of TechPar Group (TPG), a technology advisory services company that consults on all facets of the information technology (IT) industry. TPG has delivered strategic and tactical advisory services to over 160 clients in eight years, serving technology investors, vendors, and enterprise users. Paul Raskas has 30+ years of Fortune 500 consulting experience, working as a senior consultant at IBM and as an independent consultant. His work addresses application and data solutions in financial services, pharmaceutical, telecom, utilities, and transportation industries. He combines industry domain knowledge and cross-industry strategies, focusing on data architecture, data integration, data quality, Master Data Management, data governance, and Business Intelligence solutions.
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Master Data Management and Data Governance Second Edition Alex Berson Larry Dubov
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Copyright © 2011 by The McGraw-Hill Companies. All rights reserved. Printed in the United States of America. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of the publisher. ISBN: 978-0-07-174459-1 MHID: 0-07-174459-2 The material in this eBook also appears in the print version of this title: ISBN: 978-0-07-174458-4, MHID: 0-07-174458-4. All trademarks are trademarks of their respective owners. Rather than put a trademark symbol after every occurrence of a trademarked name, we use names in an editorial fashion only, and to the benefit of the trademark owner, with no intention of infringement of the trademark. Where such designations appear in this book, they have been printed with initial caps. McGraw-Hill eBooks are available at special quantity discounts to use as premiums and sales promotions, or for use in corporate training programs. To contact a representative please e-mail us at bulksales@mcgraw-hill.com. Information has been obtained by McGraw-Hill from sources believed to be reliable. However, because of the possibility of human or mechanical error by our sources, McGraw-Hill, or others, McGraw-Hill does not guarantee the accuracy, adequacy, or completeness of any information and is not responsible for any errors or omissions or the results obtained from the use of such information. TERMS OF USE This is a copyrighted work and The McGraw-Hill Companies, Inc. (“McGraw-Hill”) and its licensors reserve all rights in and to the work. Use of this work is subject to these terms. Except as permitted under the Copyright Act of 1976 and the right to store and retrieve one copy of the work, you may not decompile, disassemble, reverse engineer, reproduce, modify, create derivative works based upon, transmit, distribute, disseminate, sell, publish or sublicense the work or any part of it without
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McGraw-Hill’s prior consent. You may use the work for your own noncommercial and personal use; any other use of the work is strictly prohibited. Your right to use the work may be terminated if you fail to comply with these terms. THE WORK IS PROVIDED “AS IS.” McGRAW-HILL AND ITS LICENSORS MAKE NO GUARANTEES OR WARRANTIES AS TO THE ACCURACY, ADEQUACY OR COMPLETENESS OF OR RESULTS TO BE OBTAINED FROM USING THE WORK, INCLUDING ANY INFORMATION THAT CAN BE ACCESSED THROUGH THE WORK VIA HYPERLINK OR OTHERWISE, AND EXPRESSLY DISCLAIM ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. McGraw-Hill and its licensors do not warrant or guarantee that the functions contained in the work will meet your requirements or that its operation will be uninterrupted or error free. Neither McGraw-Hill nor its licensors shall be liable to you or anyone else for any inaccuracy, error or omission, regardless of cause, in the work or for any damages resulting there from. McGraw-Hill has no responsibility for the content of any information accessed through the work. Under no circumstances shall McGraw-Hill and/or its licensors be liable for any indirect, incidental, special, punitive, consequential or similar damages that result from the use of or inability to use the work, even if any of them has been advised of the possibility of such damages. This limitation of liability shall apply to any claim or cause whatsoever whether such claim or cause arises in contract, tort or otherwise.
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To Irina, Vlad, Michelle, Tara, Colin, and Anna —Alex Berson To Irene, Anthony, Stacy, my mother and father, and Vladimir Zamansky —Larry Dubov
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Contents at a Glance Part I Introduction to Master Data Management 1 Overview of Master Data Management 2 MDM: Overview of Market Drivers and Key Challenges 3 MDM Applications by Industry Part II Architectural Considerations 4 MDM Architecture Classifications, Concepts, Principles, and Components 5 Data Management Concerns of MDM Architecture: Entities, Hierarchies, and Metadata 6 MDM Services for Entity and Relationships Resolution and Hierarchy Management 7 Master Data Modeling Part III Data Security, Privacy, and Regulatory Compliance 8 Overview of Risk Management for Master Data 9 Introduction to Information Security and Identity Management 10 Protecting Content for Secure Master Data Management 11 Enterprise Security and Data Visibility in Master Data Management Environments Part IV Implementing and Governing Master Data Management 12 Building a Business Case and Roadmap for MDM
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13 Project Initiation 14 Entity Resolution: Identification, Matching, Aggregation, and Holistic View of the Master Objects 15 Beyond Party Match: Merge, Split, Party Groups, and Relationships 16 Data Synchronization, MDM System Testing, and Other Implementation Concerns 17 Master Data Governance Part V Master Data Management: Markets, Trends, and Directions 18 MDM Vendors and Products Landscape 19 Where Do We Go from Here? Part VI Appendixes A List of Acronyms B Glossary Index
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Contents Forewords Acknowledgments Introduction Part I Introduction to Master Data Management 1 Overview of Master Data Management Master Data Management (MDM) Defining Master Data Why Master Data Management Now? Challenges of Creating and Managing Master Data Defining Master Data Management Master Data Management for Customer Domain:Customer Data Integration (CDI) Evolution of MDM and CDI Other MDM Variants: Products, Organizations, Hierarchies Challenges of MDM Implementation for Product Domain Introduction to MDM Classification Dimensions Key Benefits of Master Data Management References 2 MDM: Overview of Market Drivers and Key Challenges Market Growth and Adoption of MDM MDM Growth and Customer Centricity
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Business and Operational Drivers of MDM Improving Customer Experience Improving Customer Retention and Reducing Attrition Rates Growing Revenue by Leveraging Customer Relationships Improving Customer Service Time:Just-in-Time Information Availability Improving Marketing Effectiveness Reducing Administrative Process Costs and Inefficiencies Reducing Information Technology Maintenance Costs MDM Challenges Senior Management Commitment and Value Proposition Customer Centricity and a 360-Degree View of a Customer Challenges of Selling MDM Inside the Enterprise Socializing MDM as a Multidimensional Challenge Technical Challenges of MDM Implementation Costs and Time-to-Market Concerns Data Quality, Data Synchronization, and Integration Challenges Data Visibility, Security, and Regulatory Compliance Challenges of Global MDM Implementations References 3 MDM Applications by Industry Industry Views of MDM Commercial Sector
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Financial Services, Banking, and Insurance Telecommunications Industry Healthcare Services Ecosystem Hospitality and Gaming Industry Manufacturing and Software Pharmaceutical Industry Shipping and Logistics Airlines Retail Sales Public Sector Social Services Law Enforcement, Border Protection, and Intelligence Agencies References Part II Architectural Considerations 4 MDM Architecture Classifications, Concepts, Principles, and Components Architectural Definition of Master Data Management Evolution of Master Data Management Architecture MDM Architectural Philosophy and Key Architecture Principles Enterprise Architecture Framework: A Brief Introduction MDM Architecture Viewpoints Services Architecture View Architecture Viewpoints of Various MDM Classification Dimensions
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Reference Architecture Viewpoint References 5 Data Management Concerns of MDM Architecture: Entities, Hierarchies, and Metadata Data Strategy Guiding Principles of Information Architecture Data Governance Data Stewardship and Ownership Data Quality Data Quality Tools and Technologies Managing Data in the Data Hub Data Zone Architecture Approach Operational and Analytical MDM and Data Zones Loading Data into the Data Hub Data Synchronization Overview of Business Rules Engines Data Delivery and Metadata Concerns Enterprise Information Integration and Integrated Data Views References 6 MDM Services for Entity and Relationships Resolution and Hierarchy Management Architecting an MDM System for Entity Resolution Recognizing Individuals, Groups, and Relationships MDM and Party Data Model
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Entity Groupings and Hierarchies Challenge of Product Identification, Recognition, and Linking MDM Architecture for Entity Resolution Key Services and Capabilities for Entity Resolution Entity Resolution and MDM Reference Architecture Entity Recognition, Matching, and Generation of Unique Identifiers Matching and Linking Services and Techniques Aggregating Entity Information Data Hub Keys and Life-Cycle Management Services Key Management and Key Generation Service Record Locator Services References 7 Master Data Modeling Importance of Data Modeling Predominant Data Modeling Styles MDM Data Modeling Requirements Data Modeling Styles and Their Support for Multidomain MDM Approach 1: The “Right” Data Model Approach 2: Metadata Model Approach 3: Abstract MDM-Star Model References Part III Data Security, Privacy, and Regulatory Compliance 8 Overview of Risk Management for Master Data
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Risk Taxonomy Regulatory Compliance Landscape Integrated Risk Management: Benefits and Challenges Regulatory Compliance Requirements and Their Impact on MDM IT Infrastructure The Sarbanes-Oxley Act Gramm-Leach-Bliley Act Data Protection Provisions Other Regulatory/Compliance Requirements Key Information Security Risks and Regulatory Concerns Identity Theft GLBA, FCRA, Privacy, and Opt-Out Key Technical Implications of Data Security and Privacy Regulations on MDM Architecture References 9 Introduction to Information Security and Identity Management Traditional and Emerging Concerns of Information Security What Do We Need to Secure? End-to-End Security Framework Traditional Security Requirements Emerging Security Requirements Overview of Security Technologies Confidentiality and Integrity Network and Perimeter Security Technologies Secure HTTP Protocols/SSL/TLS/WTLS
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Application, Data, and User Security Integrating Authentication and Authorization SSO Technologies Web Services Security Concerns Authentication Data Integrity and Confidentiality Attacks WS-Security Standard Putting It All Together References 10 Protecting Content for Secure Master Data Management Data Security Evolution Emerging Information Security Threats Regulatory Drivers for Data Protection Risks of Data Compromise Technical Implications of Data Security Regulations Data Security Overview Layered Security Framework Data-in-Transit Security Considerations Data-at-Rest Protection Enterprise Rights Management ERM Processes and MDM Technical Requirements ERM Use Case Examples
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References 11 Enterprise Security and Data Visibility in Master Data Management Environments Access Control Basics Groups and Roles Roles-Based Access Control (RBAC) Policies and Entitlements Entitlements Taxonomy Transactional Entitlements Entitlements and Visibility Customer Data Integration Visibility Scenario Policies, Entitlements, and Standards XACML Integrating MDM Solutions with Enterprise Information Security Overview of Key Architecture Components for Policy Decision and Enforcement Integrated Conceptual Security and Visibility Architecture References Part IV Implementing and Governing Master Data Management 12 Building a Business Case and Roadmap for MDM Importance of the MDM Business Case and the Current State of the Problem MDM Sponsorship Scenarios and Their Challenges Business Strategy–Driven MDM
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