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Data integration, by contrast, is a permanent part of the IT architecture, and is responsible for the way data flows between the various applications and data stores—and is a process rather than a project activity. Standard ETL technologies designed to supply data from operational systems to data warehouses would fit within the latter category.
Crosswalk tables are often employed within or in parallel to enterprise systems, especially when multiple systems are interfaced or when the system includes legacy system data. In the context of Interfaces, they function as an internal extract, transform, load (ETL) mechanism. For example, this is a metadata crosswalk from MARC standards to ...
A data management plan or DMP is a formal document that outlines how data are to be handled both during a research project, and after the project is completed. [1] The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; [2] this may lead to data being well-managed in the present ...
Applying a schema migration to a production database is always a risk. Development and test databases tend to be smaller and cleaner. The data in them is better understood or, if everything else fails, the amount of data is small enough for a human to process. Production databases are usually huge, old and full of surprises.
The Oracle unified method (OUM), first released by Oracle Corporation in 2006, is a standards-based method with roots in the unified process (UP). OUM is business-process and use-case driven and includes support for the Unified Modeling Language (UML), though the use of UML is not required. OUM combines these standards with aspects of Oracle's ...
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.
Data conversion is the conversion of computer data from one format to another. Throughout a computer environment, data is encoded in a variety of ways. For example, computer hardware is built on the basis of certain standards, which requires that data contains, for example, parity bit checks.
Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at source, or where it is physically located, [1] and can provide a single customer view (or single view of any other entity) of the overall data.
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