Data virtualization describes the process of abstracting disparate data sources (databases, applications, file repositories, websites, data services vendors, etc.) through a single data access layer (which may be any of several data access mechanisms).
This abstraction enables data access clients to target a single data access layer, serialization, format, structure, etc., rather than making each client tool handle multiples of any or all of these.
This concept and software is commonly used within data integration, business intelligence, service-oriented architecture data services, cloud computing, enterprise search, master data management and virtual master data management.
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Data Virtualization software is an enabling technology which provides some or all of the following capabilities:
Data virtualization software may includes functions for development, operation, and/or management.
Enterprise Information Integration (EII) and data federation have been used by some vendors to describe a core element of data virtualization: the capability to create relational JOINs in a federated VIEW. Some forms of legacy data virtualization build on knowledge and concepts developed within EII and Data Federation.
Newer types of data virtualization do not always require movement of the data to construct the view. They may allow you to see the results of the relational joins before any data is moved anywhere. This additional capability is a very significant differentiation point between legacy data virtualization vendors (older EII technology) and newer technologies based upon persistent metadata servers.