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Properly executed, the data architecture phase of information system planning forces an organization to specify and describe both internal and external information flows. These are patterns that the organization may not have previously taken the time to conceptualize. It is therefore possible at this
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Without the guidance of a properly implemented data architecture design, common data operations might be implemented in different ways, rendering it difficult to understand and control the flow of data within such systems. This sort of fragmentation is undesirable due to the potential increased cost
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Certain elements must be defined during the design phase of the data architecture schema. For example, an administrative structure that is to be established in order to manage the data resources must be described. Also, the methodologies that are to be employed to store the data must be defined. In
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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
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These are usually suggested by the completed data architecture and database architecture designs. In addition, some technology drivers will derive from existing organizational integration frameworks and standards, organizational economics, and existing site resources (e.g. previously purchased
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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 three traditional architectural stages:
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These are also important factors that must be considered during the data architecture phase. It is possible that some solutions, while optimal in principle, may not be potential candidates due to their cost. External factors such as the
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Various constraints and influences will have an effect on data architecture design. These include enterprise requirements, technology drivers, economics, business policies and data processing needs.
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stage to identify costly information shortfalls, disconnects between departments, and disconnects between organizational systems that may not have been evident before the data architecture analysis.
160:, 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
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addition, a description of the database technology to be employed must be generated, as well as a description of the processes that are to manipulate the data. It is also important to design
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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.
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and the data disconnects involved. These sorts of difficulties may be encountered with rapidly growing enterprises and also enterprises that service different lines of
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A data architecture aims to set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems.
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472:, since this enables managerial decision making and other organizational processes. One of the architecture techniques is the split between managing
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These generally include such elements as economical and effective system expansion, acceptable performance levels (especially system access speed),
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In this second, broader sense, data architecture includes a complete analysis of the relationships among an organization's functions, available
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168:. Data architectures address data in storage, data in use, and data in motion; descriptions of data stores, data groups, and data items; and
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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
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items. A data entity is any real or abstract thing about which an organization or individual wishes to store data.
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Essential to realizing the target state, data architecture describes how data is processed, stored, and used in an
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performed in high volumes, data warehousing for the support of management information systems (and potential
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that also drive data architecture design include internal organizational policies, rules of
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of the actual database technology that would support the designed data architecture.
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Lewis, G.; Comella-Dorda, S.; Place, P.; Plakosh, D.; & Seacord, R., (2001).
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this stage is to define all of the relevant data entities, not to specify
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of those data artifacts to data qualities, applications, locations, etc.
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that is to support common data operations (i.e. emergency procedures,
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List of things and architectural standards important to the business
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consist of models, policies, rules, and standards that govern which
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Physical data architecture of an information system is part of a
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Logical - represents the logic of how entities are related.
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from data retrieval systems (as done in a data warehouse).
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to the data by other systems, as well as a design for the
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to be used in the implementation of the data architecture
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753:Building a modern data and analytics architecture
741:Achieving Usability Through Software Architecture
714:Achieving Usability Through Software Architecture
187:and also control the flow of data in the system.
647:GeekInterview, 2008-01-28, accessed 2011-04-28
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712:Bass, L.; John, B.; & Kates, J. (2001).
588:Enterprise Information Security Architecture
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183:operations to make it possible to design
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726:Adleman, S.; Moss, L.; Abai, M. (2005).
545:These include accurate and reproducible
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594:FDIC Enterprise Architecture Framework
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220:for enterprise architecture –
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468:is also a common organizational
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747:The Logical Data Architecture
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444:reliability, and transparent
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764:TOGAF 9: Preparation Process
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533:that can vary by applicable
202:Conceptual - represents all
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179:. It provides criteria for
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937:Unified Modeling Language
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268:Business Model/Conceptual
216:The "data" column of the
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542:Data processing needs
278:Enterprise data model
166:applications software
146:solution architecture
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932:Object–role modeling
482:data capture systems
291:System Model/Logical
138:architecture domains
51:improve this article
499:data virtualization
448:. In addition, the
315:Physical data model
66:"Data architecture"
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628:2013-03-30 at the
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917:Data-flow diagram
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527:regulatory bodies
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460:into more useful
411:transfers of data
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470:requirement
462:information
458:image files
442:transaction
409:, external
295:Enterprise/
242:Stakeholder
237:Data (What)
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983:XML schema
886:Geographic
800:Data model
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450:conversion
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350:data types
338:Developer
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185:data flows
77:newspapers
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690:cite book
577:Data mesh
555:reporting
506:Economics
334:databases
301:Designer
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