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Data integration refers to the process of combining, sharing, or synchronizing data from multiple sources to provide users with a unified view. [1] There are a wide range of possible applications for data integration, from commercial (such as when a business merges multiple databases) to scientific (combining research data from different bioinformatics repositories).
Another significant barrier is the cost in time and money in the initial setup. The preliminary expenses and time that arise from the implementation, customization and training can be costly. It is important to select the correct level of integration to match the business requirement.
Information integration (II) is the merging of information from heterogeneous sources with differing conceptual, contextual and typographical representations.It is used in data mining and consolidation of data from unstructured or semi-structured resources.
Web data integration (WDI) is the process of aggregating and managing data from different websites into a single, homogeneous workflow. This process includes data access, transformation, mapping, quality assurance and fusion of data. Data that is sourced and structured from websites is referred to as "web data".
An integration competency center (ICC), sometimes referred to as an integration center of excellence (COE), is a shared service function providing methodical data integration, system integration, or enterprise application integration within organizations, particularly large corporations and public sector institutions.
Enterprise information integration (EII) is the ability to support a unified view of data and information for an entire organization.In a data virtualization application of EII, a process of information integration, using data abstraction to provide a unified interface (known as uniform data access) for viewing all the data within an organization, and a single set of structures and naming ...
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 .
Semantic integration is the process of interrelating information from diverse sources, for example calendars and to do lists, email archives, presence information (physical, psychological, and social), documents of all sorts, contacts (including social graphs), search results, and advertising and marketing relevance derived from them.