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[ Data Governance ] | +---------------------+---------------------+ | | | [Data Architecture] [Data Modelling] [Data Storage] | | | [Data Security] [Data Integration] [Document/Content] | | | [Master Data] [Data Warehousing] [Metadata Management] | | | +---------------------+---------------------+ | [ Data Quality ] 1. Data Governance
Constructing the logical/physical structure. Data Quality: Ensuring accuracy and reliability. Data Security: Protecting information assets. Why the Revised 2nd Edition (DMBOK2R)?
: DAMA-DMBOK2 is protected under strict copyright laws held by DAMA International. Purchasing an authorized digital or physical copy directly
Data management is a critical framework for modern businesses looking to harness the power of their information assets. At the center of this discipline is the , published by the Data Management Association International (DAMA).
Summary of DAMA-DMBOK 2nd Edition The Data Management Body of Knowledge (DAMA-DMBOK2), published by the Data Management Association International, serves as the definitive global standard for data management practices. It establishes a comprehensive framework for governance, security, and quality, ensuring organizations treat data as a critical corporate asset.
Published by , the second edition (DMBOK2) builds upon the foundational DMBOK1 to address modern challenges in the data landscape. It serves as the primary study resource for the Certified Data Management Professional (CDMP) designation. Core Knowledge Areas
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: Data Architecture, Data Modeling and Design, Data Storage and Operations, Data Security, Data Integration and Interoperability, Document and Content Management, Reference and Master Data, Data Warehousing and Business Intelligence, Metadata Management, and Data Quality Management. Critical Review & Practical Value Comprehensive but Complex
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Updated focus on cloud data management and modern integration.
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The is the definitive global standard for data management practices. Published by DAMA International, this comprehensive framework guides professionals in data governance, quality, and architecture.
: Discovery, analysis, and representation of data requirements.
Data Modeling and Design: Discovering, analyzing, and representing data requirements in precise models.
: Structuring data for analytics, reporting, and operational insights.
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