According to the Data Management Body of Knowledge (DMBOK), Data Architecture “includes specifications used to describe existing state, define data requirements, guide data integration, and control data assets as put forth in a data strategy.” Data Architecture bridges business strategy and technical execution, and according to our 2017 Trends in Data Architecture Report:
“Data Architecture is as much a business decision as it is a technical one, as new business models and entirely new ways of working are driven by data and information.”
Data Architecture can be synthesized into the following components:
- Data Architecture Outcomes: Models, definitions, and data flows on various levels, usually referred as Data Architecture artifacts.
- Data Architecture Activities: Forms, deploys, and fulfills Data Architecture intentions.
- Data Architecture Behaviors: Collaborations, mindsets, and skills among the various roles that affect the enterprise’s Data Architecture.
Other Definitions of Data Architecture Include:
- “Common vocabulary expressing integrated requirements ensuring that data assets are stored, arranged, managed, and used in systems in support of an organizational strategy.” (Dr. Peter Aiken)
- “A set of rules, policies, and models that determine what kind of data gets collected, and how it gets used, processed and stored within a database system.” (Keith D.Foote)
- “Using data effectively and built on a foundation of business requirements.” (McKinsey)
- “Describes how data is collected, stored, transformed, distributed and consumed. IT includes rules governing structured formats, such as databases and file systems, and the systems for connecting data with the business process that consume it.” (Harvard Business Review)
- “Models, policies, rules, or standards that govern which data is collected, and how it is stored, arranged and put to use in a database system and or in an organization.” (Business Dictionary)
Visual Example of Data Architecture Elements:
Businesses Use Data Architecture to:
- Strategically prepare organizations to quickly evolve and to take advantage of business opportunities inherent in emerging technologies.
- Translate business needs into data and system requirements.
- Facilitate alignment of IT and business systems.
- Manage complex data and information delivery throughout the enterprise. Acts as agents for change transformation and agility.
- “Depict the flow of information between people (users) and Business Processes.”
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