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Master data management /
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 M...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; Boston :
Elsevier/Morgan Kaufmann,
©2009.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Loshin, David, |d 1963- | |
| 245 | 1 | 0 | |a Master data management / |c David Loshin. |
| 260 | |a Amsterdam ; |a Boston : |b Elsevier/Morgan Kaufmann, |c ©2009. | ||
| 300 | |a 1 online resource (xxv, 274 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 520 | |a 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 | ||
| 505 | 0 | |a Chapter 1) Introduction: Master Data and Master Data Management -- Chapter 2) Business Process Models, Stakeholders, and Participant Coordination -- Chapter 3) MDM Maturity and the Implementation Roadmap -- Chapter 4) Enterprise Data Governance -- Chapter 5) The Value of Data Quality -- Chapter 6) Data Standards and Metadata Management -- Chapter 7) Identifying Master Data -- Chapter 8) Data Modeling Issues for MDM -- Chapter 9) MDM Paradigms and Architectures -- Chapter 10) Data Consolidation and Integration -- Chapter 11) Master Data Synchronization -- -- Chapter 12) The Functional Application Services Layer -- Chapter 13) Management Guidelines and Summary. | |
| 504 | |a Includes bibliographical references (page 259) and index. | ||
| 505 | 0 | |a Master data and master data management -- Coordination, stakeholders, requirements, and planning -- Components and the maturity model -- Data governance for master data management -- Data quality and MDM -- Metadata management for MDM -- Identifying master metadata and master data -- Data modeling for MDM -- Paradigms and architectures -- Data consolidation and integration -- Master data synchronization -- And the functional services layer -- Management guidance for MDM. | |
| 588 | 0 | |a Print version record. | |
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| 650 | 6 | |a Systèmes d'information de gestion. | |
| 650 | 6 | |a Bases de données |x Gestion. | |
| 650 | 6 | |a Entrepôts de données (Informatique) | |
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