book

Master Data Management

by David Loshin

July 2010

Beginner to intermediate

304 pages

7h 45m

English

Morgan Kaufmann

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1.1. Driving the Need for Master Data1.2. Origins of Master Data1.3. What Is Master Data?1.4. What Is Master Data Management?1.5. Benefits of Master Data Management1.6. Alphabet Soup: What about CRM/SCM/ERP/BI (and Others)?1.7. Organizational Challenges and Master Data Management1.8. MDM and Data Quality1.9. Technology and Master Data Management1.10. Overview of the Book1.11. Summary
2.1. Introduction2.2. Communicating Business Value2.3. Stakeholders2.4. Developing a Project Charter2.5. Participant Coordination and Knowing Where to Begin2.6. Establishing Feasibility through Data Requirements2.7. Summary
3.1. Introduction3.2. MDM Basics3.3. Manifesting Information Oversight with Governance3.4. Operations Management3.5. Identification and Consolidation3.6. Integration3.7. Business Process Management3.8. MDM Maturity Model3.9. Developing an Implementation Road Map3.10. Summary

4.1. Introduction4.2. What Is Data Governance?4.3. Setting the Stage: Aligning Information Objectives with the Business Strategy4.4. Data Quality and Data Governance4.5. Areas of Risk4.6. Risks of Master Data Management4.7. Managing Risk through Measured Conformance to Information Policies4.8. Key Data Entities4.9. Critical Data Elements4.10. Defining Information Policies4.11. Metrics and Measurement4.12. Monitoring and Evaluation4.13. Framework for Responsibility and Accountability4.14. Data Governance Director4.15. Data Governance Oversight Board4.16. Data Coordination Council4.17. Data Stewardship4.18. Summary
5.1. Introduction5.2. Distribution, Diffusion, and Metadata5.3. Dimensions of Data Quality5.4. Employing Data Quality and Data Integration Tools5.5. Assessment: Data Profiling5.6. Data Cleansing5.7. Data Controls5.8. MDM and Data Quality Service Level Agreements5.9. Influence of Data Profiling and Quality on MDM (and Vice Versa)5.10. Summary
6.1. Introduction6.2. Business Definitions6.3. Reference Metadata6.4. Data Elements6.5. Information Architecture6.6. Metadata to Support Data Governance6.7. Services Metadata6.8. Business Metadata6.9. Summary
7.1. Introduction7.2. Characteristics of Master Data7.3. Identifying and Centralizing Semantic Metadata7.4. Unifying Data Object Semantics7.5. Identifying and Qualifying Master Data7.6. Summary
8.1. Introduction8.2. Aspects of the Master Repository8.3. Information Sharing and Exchange8.4. Standardized Exchange and Consolidation Models8.5. Consolidation Model8.6. Persistent Master Entity Models8.7. Master Relational Model8.8. Summary
9.1. Introduction9.2. MDM Usage Scenarios9.3. MDM Architectural Paradigms9.4. Implementation Spectrum9.5. Applications Impacts and Architecture Selection9.6. Summary
10.1. Introduction10.2. Information Sharing10.3. Identifying Information10.4. Consolidation Techniques for Identity Resolution10.5. Classification10.6. Consolidation10.7. Additional Considerations10.8. Summary
11.1. Introduction11.2. Aspects of Availability and Their Implications11.3. Transactions, Data Dependencies, and the Need for Synchrony11.4. Synchronization11.5. Conceptual Data Sharing Models11.6. Incremental Adoption11.7. Summary
12.1. Collecting and Using Master Data12.2. Concepts of the Services-Based Approach12.3. Identifying Master Data Services12.4. Transitioning to MDM12.5. Supporting Application Services12.6. Summary
13.1. Establishing a Business Justification for Master Data Integration and Management13.2. Developing an MDM Road Map and Rollout Plan13.3. Roles and Responsibilities13.4. Project Planning13.5. Business Process Models and Usage Scenarios13.6. Identifying Initial Data Sets for Master Integration13.7. Data Governance13.8. Metadata13.9. Master Object Analysis13.10. Master Object Modeling13.11. Data Quality Management13.12. Data Extraction, Sharing, Consolidation, and Population13.13. MDM Architecture13.14. Master Data Services13.15. Transition Plan13.16. Ongoing Maintenance13.17. Summary: Excelsior!