Master Data Management in Practice

DALTON CERVO is Senior Solutions Consultant at DataFlux Corporation, assisting customers with master data management, data governance, and data quality implementations. Prior to joining DataFlux, Dalton was a senior program manager at both Sun Microsystems and Oracle, leading the data quality efforts as a member of the data governance team responsible for defining policies and procedures governing the oversight of master customer data. He is an expert panelist and a featured blogger for Data Quality PRO and a contributing author in The Next Wave of Technologies: Opportunities in Chaos (Wiley).MARK ALLEN is a Senior Consultant and Enterprise Data Governance Lead at WellPoint, Inc. Prior to joining WellPoint, Mark was a senior program manager in customer operations groups at both Sun Microsystems and Oracle. Mark has led Sun's Customer Data Governance Board and has been a member of customer advisory boards for DataFlux, Oracle, and Dun & Bradstreet, where he was a presenter and panel member for various data governance and master data management events and forums.Please visit their website at www.mdm-in-practice.com.

• Foreword xiiiPreface xviiAcknowledgments xxiIntroduction 1Part I: Planning Your Customer MDM Initiative 7Chapter 1: Defining Your MDM Scope and Approach 9MDM Approaches and Architectures 9Analytical MDM 11Operational MDM 14Enterprise MDM 18Defining the Business Case 20Cost Reduction 21Risk Management 22Revenue Growth 23Selecting the Right MDM Approach 23Data Management Maturity Level 24Addressing the ROI Question 27Summary 27Note 28Chapter 2: Establishing Effective Ownership 29The Question of Data Ownership 29Executive Involvement 31MDM with Segmented Business Practices 31A Top-Down and Bottom-Up Approach 32Creating Collaborative Partnerships 33Can Your Current IT and Business ModelEffectively Support MDM? 33The Acceptance Factor 34Business Access to Data 35Coordination of MDM Roles and Responsibilities 36Summary 38Notes 38Chapter 3: Priming the MDM Engine 39Introduction 39Positioning MDM Tools 40Data Integration and Synchronization 42Data Profiling 43Data Migration 46Data Consolidation and Segmentation 55Reference Data 57Metadata 60Summary 63Notes 63Part II: The Implementation Fundamentals 65Chapter 4: Data Governance 67Initiating a Customer Data Governance Model 67Planning and Design 69Establishing the Charter 70Policies, Standards, and Controls 78Implementation 85Process Readiness 85Implement 88Maintain and Improve 91Summary 93Notes 94Chapter 5: Data Stewardship 95From Concept to Practice 95People 96MDM Process Core Team 97Operational Process Areas 102Processes 107Data Caretaking 108Summary 109Chapter 6: Data Quality Management 111Implementing a Data Quality Model 111A Process for Data Quality 114Drivers 115Data Quality (DQ) Forum 117Controls/Data Governance 119Data Analysts 120Design Team 123IT Support/Data Stewards 125Metrics 126Establishing a Data Quality Baseline 127Context 127Data Quality Dimensions 129Entities and Attributes 129Putting It All Together 132Data Alignment and Fitness Assessment 136Data Correction Initiatives 137Summary 140Note 140Chapter 7: Data Access Management 141Creating the Business Discipline 141Beyond the System Administrator 142Creating the Right Gatekeeper Model 144Preparing 145Employee Data 146Access Management Requirements 146Add User Group Names 148Map Privileges to Requirement Categories 149Profiling the Data 150Implementing and Managing the Process 152Testing and Launching the Process 157Resolve Issues Immediately 157Auditing and Monitoring 158Segregation of Duty (SoD) Management 159Summary 161Notes 161Part III: Achieving a Steady State 163Chapter 8: Data Maintenance and Metrics 165Data Maintenance 165Specify, Profile, and Analyze 167Improve 167Data Quality Metrics 184Monitors 185Scorecards 187Summary 189Note 190Chapter 9: Maturing Your MDM Model 191How to Recognize and Gauge Maturity? 191Data Governance Maturity 193Data Stewardship Maturity 194Data Quality Maturity 195Data Access Management Maturity 197Summary 198Notes 199Part IV: Advanced Practices 201Chapter 10: Creating the Customer 360 View 203Introduction 203Hierarchy Management (HM) 206Operational versus Analytical Hierarchies 207Single versus Multiple Hierarchies 208Number of Levels in the Customer Hierarchy 209Virtual versus Physical Customer Records 211Legal versus Non-Legal Hierarchies 212The Elusive, yet Achievable, 360 Customer View 213Summary 213Chapter 11: Surviving Organizational Change 215How Adaptable is Your Customer Master Data? 215Data Quality Factors 216Data Completeness 217Data Consistency 217Data Integrity 218The Change Management Challenge 219Data Governance Can Greatly Assist a Transitioning State 220Leveraging the Data Stewards and Analysts 220Adopting Best Practices 222Summary 222Chapter 12: Beyond Customer MDM 225The Leading and Lagging Ends 225Technology’s Influence on MDM 226Overcoming the IT and Business Constraints 228Achieving an Effective Enterprise-Wide MDM Model 230Where Does MDM Lead? 233Summary 235Note 236Recommended Reading 237About the Authors 239Index 241