: New dimensions for data quality, such as bias and drift , are being added to address the specific challenges of AI models.
Formalized frameworks for decentralized data management models, such as Data Mesh and Data Fabric, moving beyond traditional centralized data warehousing.
: Structuring data for analytics and reporting. Dama-dmbok 3rd Edition Pdf
: Managing the physical database environments.
DAMA-DMBOK 3.0 represents a monumental effort to reshape the very foundation of data management knowledge. It is a complete reimagining designed to equip professionals with the frameworks and standards needed to navigate an increasingly AI-driven, complex, and regulated data world. : New dimensions for data quality, such as
: Data Architecture, Data Modeling & Design, and Data Governance. Operational Knowledge Areas
The heart of the DMBOK remains the "DAMA Wheel," which places at the center of ten interconnected knowledge areas. Governance acts as the authority and control, ensuring that policies for data security, quality, and storage are consistently applied. The 3rd Edition expands these areas to better integrate with agile methodologies and automated data pipelines. Key Knowledge Areas : Managing the physical database environments
The second edition (DAMA-DMBOK 2.0), published in 2017, represented a substantial expansion, incorporating deeper insights into areas like data governance, quality management, and the growing complexities of enterprise data landscapes. In 2024, a revised second edition was released, which addressed known inconsistencies and inaccuracies within the previous version, providing a more reliable and up-to-date resource. This revised edition also became the standard reference for the Certified Data Management Professional (CDMP®) certification.
Moving and transforming data between systems (ETL/ELT).