
Data
virtualization is the method of manipulating data from various sources to
develop a common, logical and virtual view of information so that it can be
accessed by front-end solutions such as applications, dashboards and portals
without having to know the data's exact storage location.
What are the benefits of Data virtualization?
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Data virtualization increases revenues.
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Data virtualization lowers costs.
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Data virtualization reduces risks
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It is much faster way to manage data.
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It complements traditional data-warehouse
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It maximize performance of overall information
system environment.
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Data virtualization automatically enables
self-service BI.
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It goes far beyond data federation.
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Data virtualization is more agile than
traditional method.
·
Data virtualization is the right context for Big
Data and Data Lake.
The process of data virtualization involves
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Abstracting
·
Transforming
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Federating
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Delivering of final data.
Data virtualization software is often used in tasks such
as:
·
Data integration
·
Business integration
·
Service-oriented architecture data services
·
Enterprise search
Data virtualization 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. To resolve
differences in source and consumer formats and semantics, various abstraction
and transformation techniques are used. This concept and software is a subset
of data integration and is commonly used within business intelligence,
service-oriented architecture data services, cloud computing, enterprise search,
and master data management.
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