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DMBOK - Chp 4

Data Architecture

QuestionAnswer
Purpose of Enterprise Data Architecture To describe how data should be organized and managed
Elements of Enterprise Data Architecture Data models Data definitions Data mapping specifications Data flows Structured data APIs
Zachman Framework for Enterprise Architecture First developed in the 1980s, comprised of a complete set of models required to describe an enterprise and the relationship between them.
Enterprise Data Model (EDM) Holistic, implementation-independent conceptual or logical data model providing a common consistent view of data across the enterprise.
Data Flow Design Defines the requirements and master blueprint for storage and processing across databases, applications, platforms, and networks
Enterprise Data Model includes Universal enterprise-wide conceptual and logical models and application or project specific data models, along with definitions, specifications, mappings, and business rules.
Data flows are a type of data lineage documentation that depicts how data moves through business processes and systems.
End-to-end data flows illustrate where data originated, where it is stored and used, and how it is transformed as it moves inside and between diverse processes and systems.
Enterprise Architecture deal with complexity from two viewpoints Quality-oriented, focused on improving execution within business and IT development cycles Innovation-oriented, focused on transforming business processes and IT to address new expectations and opportunities
Enterprise Data Architecture influences scope boundaries of projects and system releases through: Manage enterprise requirements within the project Reviewing project data designs Determining data lineage impact Data replication control Enforcing Data Architecture standards Guide data technology and renewal decisions
Enterprise Data Architecture roadmap Describes the architecture's 3-5 year development path. Together with the business requirements, consideration of actual conditions, and technical assessments, describes how the target architecture will become a reality.
Enterprise Data Architecture project-related activities include Define scope and ensure it's aligned with enterprise data model Understand business requirements Design detailed target specifications, including business rules in a data lifecycle perspective Implementation
Enterprise Data Architecture tools Data Modeling Tools Asset Management Software Graphical Design Applications (used to create architectural design diagrams)
Diagram characteristics Clear and consistent legend Match between objects and the legend Clear and consistent line direction Consistent line cross display method Consistent object attributes Linear symmetry
Implementing Enterprise Data Architecture is about Organizing the Enterprise Data Architecture teams and forums Producing initial versions of Data Architecture artifacts Establishing way of working in development projects Creating awareness throughout the organization of Data Architecture value
Data Architecture governance includes Overseeing projects (comply with Data Architecture standards) Managing architectural designs, lifecycle, and tools Defining standards Created data-related artifacts
Data Architecture metrics Architecture standard compliance rate Implementation trends Business value measurements
Created by: sshupert
 

 



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