DAMA-DMBOK: Data Management Body of Knowledge by DAMA International (Paperback, 2017)

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Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.

Product Identifiers

PublisherTechnics Publications LLC
ISBN-139781634622349
eBay Product ID (ePID)240015648

Product Key Features

Number of Pages626 Pages
LanguageEnglish
Publication NameDama-Dmbok: Data Management Body of Knowledge
Publication Year2017
SubjectComputer Science
TypeTextbook
AuthorDama International
FormatPaperback

Dimensions

Item Height280 mm
Item Weight1696 g
Item Width215 mm

Additional Product Features

Country/Region of ManufactureUnited States
Title_AuthorDama International

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  • Excellent

    Excellent "bible " for all things data

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