A customer places a call to Sears for an appliance repair. The phone system instantly recognizes the number. Once the caller is verified, the system automatically pulls up a complete set of records, including full history and service contracts that are available to the customer service representative answering the call. This is an example of good Customer Master Data Management (MDM) and an effective, profitable use of a company's data. Yet many organizations are still struggling to correct long-standing systemic business problems related to their data and its associated processes. Master Data…mehr
A customer places a call to Sears for an appliance repair. The phone system instantly recognizes the number. Once the caller is verified, the system automatically pulls up a complete set of records, including full history and service contracts that are available to the customer service representative answering the call. This is an example of good Customer Master Data Management (MDM) and an effective, profitable use of a company's data. Yet many organizations are still struggling to correct long-standing systemic business problems related to their data and its associated processes. Master Data Management in Practice shows you how to leverage the streamlining power of MDM to improve your organization's data, internal processes, productivity, and profits. Focusing on the much-needed "how" and "where" aspects of MDM planning and implementation, Master Data Management in Practice supports the business practice of Customer MDM from a program manager and data steward perspective. The book presents challenges, questions, advice, instruction, and solutions to help you gain a comprehensive sense of insight and technique that you can immediately apply to your own internal scenarios. Authors Dalton Cervo and Mark Allen draw on their own extensive business and IT experiences to provide a logical order toward planning, implementation, and ongoing management of Customer MDM practices. Rich with enlightening tables, graphs, and charts, Master Data Management in Practice covers: * Planning your Customer MDM initiative: the aspects of defining the underlying scope, approach, architecture, and objectives necessary for planning a Customer MDM initiative * Implementation fundamentals: the practical insight, guidance, questions, options, and examples related to the implementation of the four foundational Customer MDM practices * Achieving a steady state: how successful aintenance and monitoring practices lead to many self-governing and self-maintaining closed loop practices * The characteristics and concepts associated with a mature MDM model: transitioning your data management participants to become well-engaged MDM practitioners while communicating the success and benefits that have emerged from implementing solid MDM practices * Advanced practices: future concepts and implications associated with Customer MDM Managing data is key to your company's success. Discover how to support and connect transaction data from multiple business assets with the hands-on deployment strategies found in Master Data Management in Practice.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
Foreword xiii Preface xvii Acknowledgments xxi Introduction 1 Part I: Planning Your Customer MDM Initiative 7 Chapter 1: Defining Your MDM Scope and Approach 9 MDM Approaches and Architectures 9 Analytical MDM 11 Operational MDM 14 Enterprise MDM 18 Defining the Business Case 20 Cost Reduction 21 Risk Management 22 Revenue Growth 23 Selecting the Right MDM Approach 23 Data Management Maturity Level 24 Addressing the ROI Question 27 Summary 27 Note 28 Chapter 2: Establishing Effective Ownership 29 The Question of Data Ownership 29 Executive Involvement 31 MDM with Segmented Business Practices 31 A Top-Down and Bottom-Up Approach 32 Creating Collaborative Partnerships 33 Can Your Current IT and Business Model Effectively Support MDM? 33 The Acceptance Factor 34 Business Access to Data 35 Coordination of MDM Roles and Responsibilities 36 Summary 38 Notes 38 Chapter 3: Priming the MDM Engine 39 Introduction 39 Positioning MDM Tools 40 Data Integration and Synchronization 42 Data Profiling 43 Data Migration 46 Data Consolidation and Segmentation 55 Reference Data 57 Metadata 60 Summary 63 Notes 63 Part II: The Implementation Fundamentals 65 Chapter 4: Data Governance 67 Initiating a Customer Data Governance Model 67 Planning and Design 69 Establishing the Charter 70 Policies, Standards, and Controls 78 Implementation 85 Process Readiness 85 Implement 88 Maintain and Improve 91 Summary 93 Notes 94 Chapter 5: Data Stewardship 95 From Concept to Practice 95 People 96 MDM Process Core Team 97 Operational Process Areas 102 Processes 107 Data Caretaking 108 Summary 109 Chapter 6: Data Quality Management 111 Implementing a Data Quality Model 111 A Process for Data Quality 114 Drivers 115 Data Quality (DQ) Forum 117 Controls/Data Governance 119 Data Analysts 120 Design Team 123 IT Support/Data Stewards 125 Metrics 126 Establishing a Data Quality Baseline 127 Context 127 Data Quality Dimensions 129 Entities and Attributes 129 Putting It All Together 132 Data Alignment and Fitness Assessment 136 Data Correction Initiatives 137 Summary 140 Note 140 Chapter 7: Data Access Management 141 Creating the Business Discipline 141 Beyond the System Administrator 142 Creating the Right Gatekeeper Model 144 Preparing 145 Employee Data 146 Access Management Requirements 146 Add User Group Names 148 Map Privileges to Requirement Categories 149 Profiling the Data 150 Implementing and Managing the Process 152 Testing and Launching the Process 157 Resolve Issues Immediately 157 Auditing and Monitoring 158 Segregation of Duty (SoD) Management 159 Summary 161 Notes 161 Part III: Achieving a Steady State 163 Chapter 8: Data Maintenance and Metrics 165 Data Maintenance 165 Specify, Profile, and Analyze 167 Improve 167 Data Quality Metrics 184 Monitors 185 Scorecards 187 Summary 189 Note 190 Chapter 9: Maturing Your MDM Model 191 How to Recognize and Gauge Maturity? 191 Data Governance Maturity 193 Data Stewardship Maturity 194 Data Quality Maturity 195 Data Access Management Maturity 197 Summary 198 Notes 199 Part IV: Advanced Practices 201 Chapter 10: Creating the Customer 360 View 203 Introduction 203 Hierarchy Management (HM) 206 Operational versus Analytical Hierarchies 207 Single versus Multiple Hierarchies 208 Number of Levels in the Customer Hierarchy 209 Virtual versus Physical Customer Records 211 Legal versus Non-Legal Hierarchies 212 The Elusive, yet Achievable, 360 Customer View 213 Summary 213 Chapter 11: Surviving Organizational Change 215 How Adaptable is Your Customer Master Data? 215 Data Quality Factors 216 Data Completeness 217 Data Consistency 217 Data Integrity 218 The Change Management Challenge 219 Data Governance Can Greatly Assist a Transitioning State 220 Leveraging the Data Stewards and Analysts 220 Adopting Best Practices 222 Summary 222 Chapter 12: Beyond Customer MDM 225 The Leading and Lagging Ends 225 Technology's Influence on MDM 226 Overcoming the IT and Business Constraints 228 Achieving an Effective Enterprise-Wide MDM Model 230 Where Does MDM Lead? 233 Summary 235 Note 236 Recommended Reading 237 About the Authors 239 Index 241
Foreword xiii Preface xvii Acknowledgments xxi Introduction 1 Part I: Planning Your Customer MDM Initiative 7 Chapter 1: Defining Your MDM Scope and Approach 9 MDM Approaches and Architectures 9 Analytical MDM 11 Operational MDM 14 Enterprise MDM 18 Defining the Business Case 20 Cost Reduction 21 Risk Management 22 Revenue Growth 23 Selecting the Right MDM Approach 23 Data Management Maturity Level 24 Addressing the ROI Question 27 Summary 27 Note 28 Chapter 2: Establishing Effective Ownership 29 The Question of Data Ownership 29 Executive Involvement 31 MDM with Segmented Business Practices 31 A Top-Down and Bottom-Up Approach 32 Creating Collaborative Partnerships 33 Can Your Current IT and Business Model Effectively Support MDM? 33 The Acceptance Factor 34 Business Access to Data 35 Coordination of MDM Roles and Responsibilities 36 Summary 38 Notes 38 Chapter 3: Priming the MDM Engine 39 Introduction 39 Positioning MDM Tools 40 Data Integration and Synchronization 42 Data Profiling 43 Data Migration 46 Data Consolidation and Segmentation 55 Reference Data 57 Metadata 60 Summary 63 Notes 63 Part II: The Implementation Fundamentals 65 Chapter 4: Data Governance 67 Initiating a Customer Data Governance Model 67 Planning and Design 69 Establishing the Charter 70 Policies, Standards, and Controls 78 Implementation 85 Process Readiness 85 Implement 88 Maintain and Improve 91 Summary 93 Notes 94 Chapter 5: Data Stewardship 95 From Concept to Practice 95 People 96 MDM Process Core Team 97 Operational Process Areas 102 Processes 107 Data Caretaking 108 Summary 109 Chapter 6: Data Quality Management 111 Implementing a Data Quality Model 111 A Process for Data Quality 114 Drivers 115 Data Quality (DQ) Forum 117 Controls/Data Governance 119 Data Analysts 120 Design Team 123 IT Support/Data Stewards 125 Metrics 126 Establishing a Data Quality Baseline 127 Context 127 Data Quality Dimensions 129 Entities and Attributes 129 Putting It All Together 132 Data Alignment and Fitness Assessment 136 Data Correction Initiatives 137 Summary 140 Note 140 Chapter 7: Data Access Management 141 Creating the Business Discipline 141 Beyond the System Administrator 142 Creating the Right Gatekeeper Model 144 Preparing 145 Employee Data 146 Access Management Requirements 146 Add User Group Names 148 Map Privileges to Requirement Categories 149 Profiling the Data 150 Implementing and Managing the Process 152 Testing and Launching the Process 157 Resolve Issues Immediately 157 Auditing and Monitoring 158 Segregation of Duty (SoD) Management 159 Summary 161 Notes 161 Part III: Achieving a Steady State 163 Chapter 8: Data Maintenance and Metrics 165 Data Maintenance 165 Specify, Profile, and Analyze 167 Improve 167 Data Quality Metrics 184 Monitors 185 Scorecards 187 Summary 189 Note 190 Chapter 9: Maturing Your MDM Model 191 How to Recognize and Gauge Maturity? 191 Data Governance Maturity 193 Data Stewardship Maturity 194 Data Quality Maturity 195 Data Access Management Maturity 197 Summary 198 Notes 199 Part IV: Advanced Practices 201 Chapter 10: Creating the Customer 360 View 203 Introduction 203 Hierarchy Management (HM) 206 Operational versus Analytical Hierarchies 207 Single versus Multiple Hierarchies 208 Number of Levels in the Customer Hierarchy 209 Virtual versus Physical Customer Records 211 Legal versus Non-Legal Hierarchies 212 The Elusive, yet Achievable, 360 Customer View 213 Summary 213 Chapter 11: Surviving Organizational Change 215 How Adaptable is Your Customer Master Data? 215 Data Quality Factors 216 Data Completeness 217 Data Consistency 217 Data Integrity 218 The Change Management Challenge 219 Data Governance Can Greatly Assist a Transitioning State 220 Leveraging the Data Stewards and Analysts 220 Adopting Best Practices 222 Summary 222 Chapter 12: Beyond Customer MDM 225 The Leading and Lagging Ends 225 Technology's Influence on MDM 226 Overcoming the IT and Business Constraints 228 Achieving an Effective Enterprise-Wide MDM Model 230 Where Does MDM Lead? 233 Summary 235 Note 236 Recommended Reading 237 About the Authors 239 Index 241
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