Data Virtualization

Techopedia explains Data Virtualization

Many organizations run multiple types of database management systems - such as Oracle and SQL servers - which do not work well with one another. Therefore, enterprises are facing new challenges in data integration and the storage of a huge amount of data. With data virtualization, business users are able to get real-time and reliable information quickly, which helps them to take major business decisions.

The process of data virtualization involves abstracting, transforming, federating and delivering data from disparate sources. The main goal of data virtualization technology is to provide a single point of access to the data by aggregating it from a wide range of data sources. This allows users to access the applications without having to know their exact location.

Data virtualization software is often used in tasks such as data integration, business integration, service-oriented architecture data services and enterprise search. The most recent implementation of the data virtualization concept is in cloud computing technology.

Some of the capabilities of data virtualization include:

• Abstraction of technical aspects of stored data such as application programming interface, access language, location and storage structure
• Connection to disparate data sources and the ability to make data accessible from a single place
  
• Data transformation, quality improvement and integration of data, depending on the business requirements
  
• The ability to combine the data result sets across multiple sources (also known as the data federation)
  
• The ability to deliver the data as requested by users