Data Architecture

A Data Architecture is an information system architecture for organizational data.

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• Example(s):
  • a Enterprise Data Architecture.
  • …
• Counter-Example(s):
  • a Database Architecture.
  • a Software Code Architecture.
• See: Computer Hardware, Data Integration, Data Structure, Applications Software, Data Mapping, Information System, Data Processing, Data Flow, Data Architect, Zachman Framework, Entity-Relationship Model, Logical Data Model, Information Technology, Solution Architecture, Architecture Domain, Enterprise Architecture.

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References

2017a

• (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/data_architecture Retrieved:2017-3-31.
  • In information technology, data architecture is composed of models, policies, rules or standards that govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and in organizations. Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture.

2017b

• (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/data_architecture#Overview Retrieved:2017-3-31.
  • A data architecture shouldset data standards for all its data systems as a vision or a model of the eventual interactions between those data systems. Data integration, for example, should be dependent upon data architecture standards since data integration requires data interactions between two or more data systems. A data architecture, in part, describes the data structures used by a business and its computer applications software. Data architectures address data in storage and data in motion; descriptions of data stores, data groups and data items; and mappings of those data artifacts to data qualities, applications, locations etc.

    Essential to realizing the target state, Data Architecture describes how data is processed, stored, and utilized in an information system. It provides criteria for data processing operations so as to make it possible to design data flows and also control the flow of data in the system.

    The data architect is typically responsible for defining the target state, aligning during development and then following up to ensure enhancements are done in the spirit of the original blueprint.

    During the definition of the target state, the Data Architecture breaks a subject down to the atomic level and then builds it back up to the desired form. The data architect breaks the subject down by going through 3 traditional architectural processes:

    • Conceptual - represents all business entities.
    • Logical - represents the logic of how entities are related.
    • Physical - the realization of the data mechanisms for a specific type of functionality.
  • The "data" column of the Zachman Framework for enterprise architecture –

    In this second, broader sense, data architecture includes a complete analysis of the relationships among an organization's functions, available technologies, and data types.

    Data architecture should be defined in the planning phase of the design of a new data processing and storage system. The major types and sources of data necessary to support an enterprise should be identified in a manner that is complete, consistent, and understandable. The primary requirement at this stage is to define all of the relevant data entities, not to specify computer hardware items. A data entity is any real or abstracted thing about which an organization or individual wishes to store data.

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