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Depth in data modeling and database design: This is the core skill of the data architect, and the most requested in data architect job descriptions. The effective data architect is sound across all phases of data modeling, from conceptualization to database optimization.
Data architectures address data in storage, data in use, 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 used in an ...
A corporate data resource must be developed within single, organization-wide common data architecture. A data architecture is the science and method of designing and constructing a data resource that is business driven, based on real-world objects and events as perceived by the organization, and implemented into appropriate operating environments.
Data stewardship roles are common when organizations attempt to exchange data precisely and consistently between computer systems and to reuse data-related resources. [ citation needed ] Master data management often [ quantify ] makes references to the need for data stewardship for its implementation to succeed.
Applications architecture strategy involves ensuring the applications and the integration align with the growth strategy of the organization. If an organization is a manufacturing organization with fast growth plans through acquisitions, the applications architecture should be nimble enough to encompass inherited legacy systems as well as other large competing systems.
Around the 1970s/1980s the term information engineering methodology (IEM) was created to describe database design and the use of software for data analysis and processing. [3] [4] These techniques were intended to be used by database administrators (DBAs) and by systems analysts based upon an understanding of the operational processing needs of organizations for the 1980s.