Pierre Bonnet is the co-founder of Orchestra Networks, a software editor specialized in Model-driven MDM. He is also the founder of the "Sustainable IT Architecture" and "MDM Alliance Group" communities.

• Testimonials from the MDM Alliance Group xiiiForeword xxvPreface xxixAcknowledgements xxxixIntroduction to MDM xliPART ONE: THE MDM APPROACH 1Chapter 1. A Company and its Data 31.1. The importance of data and rules repositories 31.2. Back to basics 61.3. Reference/Master data definition 121.4. Searching for data quality 191.5. Different types of data repositories 27Chapter 2. Strategic Aspects 372.1. Corporate governance 372.2. The transformation stages of an IT system 422.3. Sustainable IT Architecture 51Chapter 3. Taking Software Packages into Account 573.1. The dead end of locked repositories 573.2. Criteria for choosing software packages 593.3. Impact for software vendors 633.4. MDM is also a software package 65Chapter 4. Return on Investment 694.1. Financial gain from improved data quality 694.2. The financial gain of data reliability 714.3. The financial gain of mastering operational risks 744.4. The financial gain of IS transformation 774.5. Summary of the return on investment of MDM 83PART TWO: MDM FROM A BUSINESS PERSPECTIVE 87Chapter 5. MDM Maturity Levels and Model-driven MDM 895.1. Virtual MDM 895.2. Static MDM 925.3. Semantic MDM 955.4. The MDM maturity model 1005.5. A Model-driven MDM system 103Chapter 6. Data Governance Functions 1096.1. Brief overview 1096.2. Ergonomics 1116.3. Version management 1126.4. The initialization and update of data by use context 1146.5. Time management 1186.6. Data validation rules 1226.7. The data approval process 1286.8. Access rights management 1296.9. Data hierarchy management 1306.10. Conclusion 131Chapter 7. Organizational Aspects 1337.1. Organization for semantic modeling 1337.2. The definition of roles 1467.3. Synthesis of the organization required to support the MDM 148PART THREE: MDM FROM THE IT DEPARTMENT PERSPECTIVE 151Chapter 8. The Semantic Modeling Framework 1538.1. Establishing the framework of the method 1538.2. Choosing the method 1618.3. The components of Enterprise Data Architecture 1728.4. The drawbacks of semantic modeling 1788.5. Ready-to-use semantic models 180Chapter 9. Semantic Modeling Procedures 1879.1. A practical case of semantic modeling: the address 1879.2. Example of Enterprise Data Architecture 1999.3. Semantic modeling procedures 202Chapter 10. Logical Data Modeling 21510.1. The objectives of logical modeling 21510.2. The components of logical data modeling 21610.3. The principle of loose-coupling data 21710.4. The data architecture within categories 22110.5. Derivation procedures 22110.6. Other logical modeling procedures 229Chapter 11. Organization Modeling 23311.1. The components of pragmatic modeling 23411.2. Data approval processes 23511.3. Use cases 23911.4. Administrative objects 24311.5. The derivation of pragmatic models to logical models 244Chapter 12. Technical Integration of an MDM system 24712.1. Integration models 24812.2. Semantic integration 25412.3. Data synchronization 25812.4. Integration with the BRMS 26112.5. Classification of databases and software development types 263Conclusion 267Appendix. Semantic Modeling of Address 271A.1. The semantic model 272A.2. Examples of screens generated by Model-driven MDM 277A.3. Semantic modeling and data quality 282A.4. Performance 282A.5. Lifecycle of the Address business object 282A.6. Insight into the XML schema 283Bibliography 285Index 287