The Data Management Body of Knowledge (DAMA-DMBOK2) presents a comprehensive view of the challenges, complexities, and value of effective data management.

Today's organizations recognize that managing data is central to their success. They recognize data has value and they want to leverage that value. As our ability and desire to create and exploit data has increased, so too has the need for reliable data management practices.

The second edition of DAMA International's Guide to the Data Management Body of Knowledge 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 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

Chapters include:

• Data Management


• Data Handling Ethics


• Data Governance


• Data Architecture


• Data Modeling and Design


• Data Storage and Operations


• Data Security


• Data Integration & Interoperability


• Document and Content Management


• Reference and Master Data


• Data Warehousing and Business Intelligence


• Metadata Management


• Data Quality Management


• Big Data and Data Science


• Data Management Maturity Assessment


• Data Management Organization and Role Expectations


• Data Management and Organizational Change Management

Standardization of data management disciplines will help data management professionals perform more effectively and consistently. It will also enable organizational leaders to recognize the value and contributions of data management activities.

La Guía del Conocimiento para la Gestión de Datos (DAMA-DMBOK2) presenta una visión exhaustiva de los desafíos, complejidades y valor de la gestión eficaz de los datos.

Las organizaciones de hoy en día reconocen que la gestión de los datos es fundamental para su éxito. Reconocen que los datos tienen valor y quieren aprovechar ese valor. A medida que nuestra capacidad y deseo de crear y explotar datos ha aumentado, también lo ha hecho la necesidad de prácticas de gestión de datos confiables.

La segunda edición de la Guía del Conocimiento para la Gestión de Datos de DAMA International actualiza y aumenta el exitoso DMBOK1. DMBOK2, un libro de referencia accesible y autorizado, escrito por los principales pensadores en el campo y ampliamente revisado por los miembros de DAMA, reúne materiales que describen exhaustivamente los desafíos de la gestión de datos y cómo cumplirlos mediante:

- Definir un conjunto de principios rectores para la gestión de datos y describir cómo se pueden aplicar estos principios dentro de las áreas funcionales de gestión de datos.

- Proporcionar un marco de referencia funcional para la implementación de prácticas de gestión de datos empresariales, incluyendo prácticas, métodos y técnicas ampliamente adoptadas, funciones, roles, entregables y métricas.

- Establecer un vocabulario común para los conceptos de gestión de datos y servir de base para las mejores prácticas para los profesionales de la gestión de datos.

A glossary of over 2,000 terms which provides a common data management vocabulary for IT and Business professionals, and is a companion to the DAMA Data Management Body of Knowledge (DAMA-DMBOK). Topics include:

• Analytics & Data Mining
• Architecture
• Artificial Intelligence
• Business Analysis
• DAMA & Professional Development
• Databases & Database Design
• Database Administration
• Data Governance & Stewardship
• Data Management
• Data Modeling
• Data Movement & Integration
• Data Quality Management
• Data Security Management
• Data Warehousing & Business Intelligence
• Document, Record & Content Management
• Finance & Accounting
• Geospatial Data
• Knowledge Management
• Marketing & Customer Relationship Management
• Meta-Data Management
• Multi-dimensional & OLAP
• Normalization
• Object-Orientation
• Parallel Database Processing
• Planning
• Process Management
• Project Management
• Reference & Master Data Management
• Semantic Modeling
• Software Development
• Standards Organizations
• Structured Query Language (SQL)
• XML Development