Enterprise Data Governance : Reference and Master Data Management Semantic Modeling


Pierre. Bonnet
Bok Engelsk 2013 · Electronic books.
Annen tittel
Utgitt
Hoboken : : Wiley, , 2013.
Omfang
1 online resource (334 p.)
Opplysninger
Description based upon print version of record.. - Cover; Title Page; Copyright Page; Table of Contents; Testimonials from the MDM Alliance Group; Foreword; Preface; Acknowledgements; Introduction to MDM; PART ONE: THE MDM APPROACH; Chapter 1. A Company and its Data; 1.1. The importance of data and rules repositories; 1.2. Back to basics; 1.2.1. Past differences; 1.2.2. The rich data model; 1.3. Reference/Master data definition; 1.3.1. Data initialized before use by transactional systems; 1.3.2. Duplicate data; 1.3.3. Data exchanged with third parties; 1.4. Searching for data quality; 1.4.1. Data quality; 1.4.2. The quality of data models. - 1.4.3. The level of maturity of data quality1.5. Different types of data repositories; 1.5.1. Technical classification; 1.5.2. Customer Data Integration (CDI); 1.5.3. Product Information Management (PIM) and Product Life Management (PLM); 1.5.4. Lightweight Directory Access Protocol (LDAP); Chapter 2. Strategic Aspects; 2.1. Corporate governance; 2.1.1. Forced against the wall by regulations; 2.1.2. The new scorecard; 2.2. The transformation stages of an IT system; 2.2.1. First stage: the data repository; 2.2.2. Second stage: the business rules repository is added to the data repository. - 2.2.3. Third stage: adding the business processes repository2.3. Sustainable IT Architecture; 2.3.1. The new management control; 2.3.2. Maintaining knowledge and the strategic break; Chapter 3. Taking Software Packages into Account; 3.1. The dead end of locked repositories; 3.2. Criteria for choosing software packages; 3.2.1. Availability of the data model; 3.2.2. Repository updates; 3.2.3. Neutralization of a locked MDM; 3.3. Impact for software vendors; 3.4. MDM is also a software package; Chapter 4. Return on Investment; 4.1. Financial gain from improved data quality. - 4.2. The financial gain of data reliability4.3. The financial gain of mastering operational risks; 4.3.1. An all too often inefficient control system; 4.3.2. MDM for the control of operational risks; 4.4. The financial gain of IS transformation; 4.4.1. The overlap of an Information System and IT; 4.4.2. Financial valuation of an Information System; 4.4.3. The MDM as a springboard for transformation of IS; 4.5. Summary of the return on investment of MDM; PART TWO: MDM FROM A BUSINESS PERSPECTIVE; Chapter 5. MDM Maturity Levels and Model-driven MDM; 5.1. Virtual MDM; 5.2. Static MDM. - 5.3. Semantic MDM5.3.1. Improved administration by business users; 5.3.2. A greater reliability in the data repository; 5.3.3. Preparation for MDM integration with the rest of a system; 5.4. The MDM maturity model; 5.5. A Model-driven MDM system; 5.5.1. Variants; 5.5.2. Hiding join tables; Chapter 6. Data Governance Functions; 6.1. Brief overview; 6.2. Ergonomics; 6.3. Version management; 6.4. The initialization and update of data by use context; 6.4.1. The affiliation of contexts; 6.4.2. The automatic detection of shared data; 6.5. Time management; 6.5.1. Data history tracking. - 6.5.2. Business transaction. - In an increasingly digital economy, mastering the quality of data is an increasingly vital yet still, in most organizations, a considerable task. The necessity of better governance and reinforcement of international rules and regulatory or oversight structures (Sarbanes Oxley, Basel II, Solvency II, IAS-IFRS, etc.) imposes on enterprises the need for greater transparency and better traceability of their data. All the stakeholders in a company have a role to play and great benefit to derive from the overall goals here, but will invariably turn towards their IT department in search of the answ
Emner
Sjanger
Dewey
ISBN
9781848211827

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