The key to a successful MDM initiative isn't technology or methods, it's people: the stakeholders in the organization and their complex ownership of the data that the initiative will affect.
Master Data Management equips you with a deeply practical, business-focused way of thinking about MDM-an understanding that will greatly enhance your ability to communicate with stakeholders and win their support. Moreover, it will help you deserve their support: you'll master all the details involved in planning and executing an MDM project that leads to measurable improvements in business productivity and effectiveness.
* Presents a comprehensive roadmap that you can adapt to any MDM project.
* Emphasizes the critical goal of maintaining and improving data quality.
* Provides guidelines for determining which data to "master.
* Examines special issues relating to master data metadata.
* Considers a range of MDM architectural styles.
* Covers the synchronization of master data across the application infrastructure.
Inhaltsverzeichnis
1;Front Cover;1 2;Master Data Management;6 3;Copyright Page;7 4;Contents;8 5;Preface;18 5.1;About the Approach Described in This Book;19 5.2;Overview of the Book;21 5.3;More about MDM and Contact Information;21 6;Acknowledgments;24 7;About the Author;26 8;Chapter 1: Master Data and Master Data Management;28 8.1;1.1 Driving the Need for Master Data;28 8.2;1.2 Origins of Master Data;30 8.2.1;1.2.1 Example: Customer Data;31 8.3;1.3 What Is Master Data?;32 8.4;1.4 What Is Master Data Management?;35 8.5;1.5 Benefits of Master Data Management;37 8.6;1.6 Alphabet Soup: What about CRM/SCM/ERP/BI (and Others)?;39 8.7;1.7 Organizational Challenges and Master Data Management;42 8.8;1.8 MDM and Data Quality;44 8.9;1.9 Technology and Master Data Management;45 8.10;1.10 Overview of the Book;45 8.11;1.11 Summary;47 9;Chapter 2: Coordination: Stakeholders, Requirements, and Planning;50 9.1;2.1 Introduction;50 9.2;2.2 Communicating Business Value;51 9.2.1;2.2.1 Improving Data Quality;52 9.2.2;2.2.2 Reducing the Need for Cross-System Reconciliation;52 9.2.3;2.2.3 Reducing Operational Complexity;52 9.2.4;2.2.4 Simplifying Design and Implementation;53 9.2.5;2.2.5 Easing Integration;54 9.3;2.3 Stakeholders;54 9.3.1;2.3.1 Senior Management;54 9.3.2;2.3.1 Business Clients;55 9.3.3;2.3.3 Application Owners;55 9.3.4;2.3.4 Information Architects;56 9.3.5;2.3.5 Data Governance and Data Quality;56 9.3.6;2.3.6 Metadata Analysts;57 9.3.7;2.3.7 System Developers;57 9.3.8;2.3.8 Operations Staff;57 9.4;2.4 Developing a Project Charter;58 9.5;2.5 Participant Coordination and Knowing Where to Begin;59 9.5.1;2.5.1 Processes and Procedures for Collaboration;60 9.5.2;2.5.2 RACI Matrix;60 9.5.3;2.5.3 Modeling the Business;61 9.5.4;2.5.4 Consensus Driven through Metadata;62 9.5.5;2.5.5 Data Governance;63 9.6;2.6 Establishing Feasibility through Data Requirements;63 9.6.1;2.6.1 Identifying the Business Context;64 9.6.2;2.6.2 Conduct Stakeholder Interviews;65 9.6.3;2.6.3 Synthesize Requirements;66 9.6.4;2.6
.4 Establishing Feasibility and Next Steps;68 9.7;2.7 Summary;68 10;Chapter 3: MDM Components and the Maturity Model;70 10.1;3.1 Introduction;70 10.2;3.2 MDM Basics;71 10.2.1;3.2.1 Architecture;72 10.2.2;3.2.2 Master Data Model;72 10.2.3;3.2.3 MDM System Architecture;73 10.2.4;3.2.4 MDM Service Layer Architecture;73 10.3;3.3 Manifesting Information Oversight with Governance;74 10.3.1;3.3.1 Standardized Definitions;74 10.3.2;3.3.2 Consolidated Metadata Management;75 10.3.3;3.3.3 Data Quality;76 10.3.4;3.3.4 Data Stewardship;76 10.4;3.4 Operations Management;76 10.4.1;3.4.1 Identity Management;77 10.4.2;3.4.2 Hierarchy Management and Data Lineage;77 10.4.3;3.4.3 Migration Management;78 10.4.4;3.4.4 Administration/Configuration;78 10.5;3.5 Identification and Consolidation;78 10.5.1;3.5.1 Identity Search and Resolution;79 10.5.2;3.5.2 Record Linkage;79 10.5.3;3.5.3 Merging and Consolidation;79 10.6;3.6 Integration;80 10.6.1;3.6.1 Application Integration with Master Data;80 10.6.2;3.6.2 MDM Component Service Layer;80 10.7;3.7 Business Process Management;81 10.7.1;3.7.1 Business Process Integration;81 10.7.2;3.7.2 Business Rules;82 10.7.3;3.7.3 MDM Business Component Layer;82 10.8;3.8 MDM Maturity Model;83 10.8.1;3.8.1 Initial;83 10.8.2;3.8.2 Reactive;83 10.8.3;3.8.3 Managed;86 10.8.4;3.8.4 Proactive;87 10.8.5;3.8.5 Strategic Performance;89 10.9;3.9 Developing an Implementation Road Map;90 10.10;3.10 Summary;92 11;Chapter 4: Data Governance for Master Data Management;94 11.1;4.1 Introduction;94 11.2;4.2 What Is Data Governance?;95 11.3;4.3 Setting the Stage: Aligning Information Objectives with the Business Strategy;96 11.3.1;4.3.1 Clarifying the Information Architecture;97 11.3.2;4.3.2 Mapping Information Functions to Business Objectives;98 11.3.3;4.3.3 Instituting a Process Framework for Information Policy;98 11.4;4.4 Data Quality and Data Governance;99 11.5;4.5 Areas of Risk;99 11.5.1;4.5.1 Business and Financial;99 11.5.2;4.5.2 Reporting;100 11.5.3;4.5.3 Entity Knowle
dge;100 11.5.4;4.5.4 Protection;101 11.5.5;4.5.5 Limitation of Use;101 11.6;4.6 Risks of Master Data Management;101 11.6.1;4.6.1 Establishing Consensus for Coordination and Collaboration;101 11.6.2;4.6.2 Data Ownership;102 11.6.3;4.6.3 Semantics: Form, Function, and Meaning;103 11.7;4.7 Managing Risk through Measured Conformance to Information Policies;104 11.8;4.8 Key Data Entities;105 11.9;4.9 Critical Data Elements;105 11.10;4.10 Defining Information Policies;106 11.11;4.11 Metrics and Measurement;107 11.12;4.12 Monitoring and Evaluation;108 11.13;4.13 Framework for Responsibility and Accountability;109 11.14;4.14 Data Governance Director;110 11.15;4.15 Data Governance Oversight Board;111 11.16;4.16 Data Coordination Council;111 11.17;4.17 Data Stewardship;112 11.18;4.18 Summary;113 12;Chapter 5: Data Quality and MDM;114 12.1;5.1 Introduction;114 12.2;5.2 Distribution, Diffusion, and Metadata;115 12.3;5.3 Dimensions of Data Quality;116 12.3.1;5.3.1 Uniqueness;117 12.3.2;5.3.2 Accuracy;117 12.3.3;5.3.3 Consistency;117 12.3.4;5.3.4 Completeness;118 12.3.5;5.3.5 Timeliness;119 12.3.6;5.3.6 Currency;119 12.3.7;5.3.7 Format Compliance;119 12.3.8;5.3.8 Referential Integrity;120 12.4;5.4 Employing Data Quality and Data Integration Tools;120 12.5;5.5 Assessment: Data Profiling;121 12.5.1;5.5.1 Profiling for Metadata Resolution;121 12.5.2;5.5.2 Profiling for Data Quality Assessment;123 12.5.3;5.5.3 Profiling as Part of Migration;123 12.6;5.6 Data Cleansing;124 12.7;5.7 Data Controls;126 12.7.1;5.7.1 Data and Process Controls;127 12.7.2;5.7.2 Data Quality Control versus Data Validation;127 12.8;5.8 MDM and Data Quality Service Level Agreements;128 12.8.1;5.8.1 Data Controls, Downstream Trust, and the Control Framework;128 12.9;5.9 Influence of Data Profiling and Quality on MDM (and Vice Versa);129 12.10;5.10 Summary;130 13;Chapter:6 Metadata Management for MDM;132 13.1;6.1 Introduction;132 13.2;6.2 Business Definitions;135 13.2.1;6.2.1 Concepts;136 13.2.2;6.2.2 Business Te
rms;136 13.2.3;6.2.3 Definitions;137 13.2.4;6.2.4 Semantics;137 13.3;6.3 Reference Metadata;138 13.3.1;6.3.1 Conceptual Domains;138 13.3.2;6.3.2 Value Domains;139 13.3.3;6.3.3 Reference Tables;140 13.3.4;6.3.4 Mappings;141 13.4;6.4 Data Elements;142 13.4.1;6.4.1 Critical Data Elements;143 13.4.2;6.4.2 Data Element Definition;143 13.4.3;6.4.3 Data Formats;144 13.4.4;6.4.4 Aliases/Synonyms;144 13.5;6.5 Information Architecture;145 13.5.1;6.5.1 Master Data Object Class Types;145 13.5.2;6.5.2 Master Entity Models;146 13.5.3;6.5.3 Master Object Directory;147 13.5.4;6.5.4 Relational Tables;147 13.6;6.6 Metadata to Support Data Governance;147 13.6.1;6.6.1 Information Usage;147 13.6.2;6.6.2 Information Quality;148 13.6.3;6.6.3 Data Quality SLAs;148 13.6.4;6.6.4 Access Control;149 13.7;6.7 Services Metadata;149 13.7.1;6.7.1 Service Directory;150 13.7.2;6.7.2 Service Users;150 13.7.3;6.7.3 Interfaces;150 13.8;6.8 Business Metadata;151 13.8.1;6.8.1 Business Policies;152 13.8.2;6.8.2 Information Policies;153 13.8.3;6.8.3 Business Rules;153 13.9;6.9 Summary;153 14;Chapter 7: Identifying Master Metadata and Master Data;156 14.1;7.1 Introduction;156 14.2;7.2 Characteristics of Master Data;158 14.2.1;7.2.1 Categorization and Hierarchies;158 14.2.2;7.2.2 Top-Down Approach: Business Process Models;160 14.2.3;7.2.3 Bottom-Up Approach: Data Asset Evaluation;161 14.3;7.3 Identifying and Centralizing Semantic Metadata;162 14.3.1;7.3.1 Example;162 14.3.2;7.3.2 Analysis for Integration;164 14.3.3;7.3.3 Collecting and Analyzing Master Metadata;164 14.3.4;7.3.4 Resolving Similarity in Structure;165 14.4;7.4 Unifying Data Object Semantics;166 14.5;7.5 Identifying and Qualifying Master Data;167 14.5.1;7.5.1 Qualifying Master Data Types;167 14.5.2;7.5.2 The Fractal Nature of Metadata Profiling;168 14.5.3;7.5.3 Standardizing the Representation;169 14.6;7.6 Summary;169 15;Chapter 8: Data Modeling for MDM;170 15.1;8.1 Introduction;170 15.2;8.2 Aspects of the Master Repository;171 15.2.1;8.2.1 Char
acteristics of Identifying Attributes;171 15.2.2;8.2.2 Minimal Master Registry;171 15.2.3;8.2.3 Determining the Attributes Called Identifying Attributes;172 15.3;8.3 Information Sharing and Exchange;173 15.3.1;8.3.1 Master Data Sharing Network;173 15.3.2;8.3.2 Driving Assumptions;173 15.3.3;8.3.3 Two Models: Persistence and Exchange;176 15.4;8.4 Standardized Exchange and Consolidation Models;176 15.4.1;8.4.1 Exchange Model;177 15.4.2;8.4.2 Using Metadata to Manage Type Conversion;178 15.4.3;8.4.3 Caveat: Type Downcasting;179 15.5;8.5 Consolidation Model;179 15.6;8.6 Persistent Master Entity Models;180 15.6.1;8.6.1 Supporting the Data Life Cycle;180 15.6.2;8.6.2 Universal Modeling Approach;181 15.6.3;8.6.3 Data Life Cycle;182 15.7;8.7 Master Relational Model;183 15.7.1;8.7.1 Process Drives Relationships;183 15.7.2;8.7.2 Documenting and Verifying Relationships;183 15.7.3;8.7.3 Expanding the Model;184 15.8;8.8 Summary;184 16;Chapter 9: MDM Paradigms and Architectures;186 16.1;9.1 Introduction;186 16.2;9.2 MDM Usage Scenarios;187 16.2.1;9.2.1 Reference Information Management;187 16.2.2;9.2.2 Operational Usage;189 16.2.3;9.2.3 Analytical Usage;191 16.3;9.3 MDM Architectural Paradigms;192 16.3.1;9.3.1 Virtual/Registry;193 16.3.2;9.3.2 Transaction Hub;195 16.3.3;9.3.3 Hybrid/Centralized Master;196 16.4;9.4 Implementation Spectrum;198 16.5;9.5 Applications Impacts and Architecture Selection;199 16.5.1;9.5.1 Number of Master Attributes;200 16.5.2;9.5.2 Consolidation;201 16.5.3;9.5.3 Synchronization;201 16.5.4;9.5.4 Access;201 16.5.5;9.5.5 Service Complexity;202 16.5.6;9.5.6 Performance;202 16.6;9.6 Summary;203 17;Chapter 10: Data Consolidation and Integration;204 17.1;10.1 Introduction;204 17.2;10.2 Information Sharing;205 17.2.1;10.2.1 Extraction and Consolidation;205 17.2.2;10.2.2 Standardization and Publication Services;206 17.2.3;10.2.3 Data Federation;206 17.2.4;10.2.4 Data Propagation;207 17.3;10.3 Identifying Information;208 17.3.1;10.3.1 Indexing Identifying Values;2
08 17.3.2;10.3.2 The Challenge of Variation;209 17.4;10.4 Consolidation Techniques for Identity Resolution;210 17.4.1;10.4.1 Identity Resolution;211 17.4.2;10.4.2 Parsing and Standardization;212 17.4.3;10.4.3 Data Transformation;213 17.4.4;10.4.4 Normalization;213 17.4.5;10.4.5 Matching/Linkage;214 17.4.6;10.4.6 Approaches to Approximate Matching;215 17.4.7;10.4.7 The Birthday Paradox versus the Curse of Dimensionality;216 17.5;10.5 Classification;217 17.5.1;10.5.1 Need for Classification;218 17.5.2;10.5.2 Value of Content and Emerging Techniques;218 17.6;10.6 Consolidation;219 17.6.1;10.6.1 Similarity Thresholds;220 17.6.2;10.6.2 Survivorship;220 17.6.3;10.6.3 Integration Errors;222 17.6.4;10.6.4 Batch versus Inline;223 17.6.5;10.6.5 History and Lineage;223 17.7;10.7 Additional Considerations;224 17.7.1;10.7.1 Data Ownership and Rights of Consolidation;224 17.7.2;10.7.2 Access Rights and Usage Limitations;225 17.7.3;10.7.3 Segregation Instead of Consolidation;226 17.8;10.8 Summary;226 18;Chapter 11: Master Data Synchronization;228 18.1;11.1 Introduction;228 18.2;11.2 Aspects of Availability and Their Implications;229 18.3;11.3 Transactions, Data Dependencies, and the Need for Synchrony;230 18.3.1;11.3.1 Data Dependency;231 18.3.2;11.3.2 Business Process Considerations;232 18.3.3;11.3.3 Serializing Transactions;233 18.4;11.4 Synchronization;234 18.4.1;11.4.1 Application Infrastructure Synchronization Requirements;235 18.5;11.5 Conceptual Data Sharing Models;236 18.5.1;11.5.1 Registry Data Sharing;236 18.5.2;11.5.2 Repository Data Sharing;237 18.5.3;11.5.3 Hybrids and Federated Repositories;238 18.5.4;11.5.4 MDM, the Cache Model, and Coherence;239 18.6;11.6.1 Incremental Adoption;242 18.6.1;11.6.1 Incorporating and Synchronizing New Data Sources;242 18.6.2;11.6.2 Application Adoption;243 18.7;11.7 Summary;243 19;Chapter 12: MDM and the Functional Services Layer;244 19.1;12.1 Collecting and Using Master Data;245 19.1.1;12.1.1 Insufficiency of ETL;245 19.1.2;12.1.2 Rep
lication of Functionality;246 19.1.3;12.1.3 Adjusting Application Dependencies;246 19.1.4;12.1.4 Need for Architectural Maturation;246 19.1.5;12.1.5 Similarity of Functionality;246 19.2;12.2 Concepts of the Services-Based Approach;247 19.3;12.3 Identifying Master Data Services;249 19.3.1;12.3.1 Master Data Object Life Cycle;249 19.3.2;12.3.2 MDM Service Components;251 19.3.3;12.3.3 More on the Banking Example;251 19.3.4;12.3.4 Identifying Capabilities;252 19.4;12.4 Transitioning to MDM;254 19.4.1;12.4.1 Transition via Wrappers;255 19.4.2;12.4.2 Maturation via Services;255 19.5;12.5 Supporting Application Services;257 19.5.1;12.5.1 Master Data Services;257 19.5.2;12.5.2 Life Cycle Services;258 19.5.3;12.5.3 Access Control;259 19.5.4;12.5.4 Integration;259 19.5.5;12.5.5 Consolidation;260 19.5.6;12.5.6 Workflow/Rules;260 19.6;12.6 Summary;261 20;Chapter 13: Management Guidance for MDM;264 20.1;13.1 Establishing a Business Justification for Master Data Integration and Management;265 20.2;13.2 Developing an MDM Road Map and Rollout Plan;267 20.2.1;13.2.1 MDM Road Map;267 20.2.2;13.2.2 Rollout Plan;268 20.3;13.3 Roles and Responsibilities;271 20.4;13.4 Project Planning;272 20.5;13.5 Business Process Models and Usage Scenarios;272 20.6;13.6 Identifying Initial Data Sets for Master Integration;273 20.7;13.7 Data Governance;273 20.8;13.8 Metadata;274 20.9;13.9 Master Object Analysis;275 20.10;13.10 Master Object Modeling;276 20.11;13.11 Data Quality Management;276 20.12;13.12 Data Extraction, Sharing, Consolidation, and Population;277 20.13;13.13 MDM Architecture;279 20.14;13.14 Master Data Services;280 20.15;13.15 Transition Plan;282 20.16;13.16 Ongoing Maintenance;283 20.17;13.17 Summary: Excelsior!;284 21;Bibliography and Suggested Reading;286 21.1;Bibliography;286 21.2;Suggested Reading;286 22;Index;288
