TY  - BOOK
ED  - DAMA Internacional
TI  - DAMA-DMBOK: data management body of knowledge 
SN  - 9781634622349
U1  - 005.74 23
PY  - 2017///
CY  - Nueva Jersey
PB  - Technics Publications
KW  - Administración de bases de datos
KW  - Estrategia y técnica
KW  - Análisis de datos
KW  - Big data
KW  - Cambio organizacional
KW  - Procesamiento electrónico de datos
KW  - Inteligencia de negocios
N1  - Incluye índice (579-588); Chapter 1: Data management ; Chapter 2: Data Handing ethics ; Chapter 3: Data governance ; Chapter 4: Data architecture ; Chapter 5: Data modeling and design ; Chapter 6: Data storage and operations ; Chapter 7: Data security ; Chapter 8: Data integration and interoperability ; Chapter 9: Document and content management ; Chapter 10: Reference and master data ; Chapter 11: Data warehousing and business intelligence ; Chapter 12: Metadata management ; Chapter 13: Data quality ; Chapter 14: Big data and data science ; Chapter 15: Data management maturity assessment ; Chapter 16: Data management organization and role expectations ; Chapter 17: Data management organizational change management
N2  - The second edition of DAMA International's Guide to the Data Management Body of Knowledge (DAMA-DMBOK2) updates and augments the highly successful DMBOK1. An accessible, authoritative reference book written by leading thinkers in the field and extensively reviewed by DAMA members, DMBOK2 brings together materials that comprehensively describe the challenges of data management and how to meet them by: 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, 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
ER  -