Data virtualization is a special kind of  data integration technology that provides access of data in real time, seamlessly all in one place. Think of it like a television guide which contains a listing of shows on a variety of channels, without having to be on that channel to see the content. In data virtualization, customers can access and manipulate each datum, regardless of physical location or formatting.  Instead it is one stop shopping. “Data virtualization solutions, also, create integrated views of the data, across the multiple sources, without moving the data to a new location.” Data virtualization typically can access a wide variety of Enterprise Data Architectures, including those on premise and in the cloud, and adapts agilely to structural changes, without impacting the business.

Other Definitions of Data Virtualization Include:

• A single database view/s allowing access to distributed databases and multiple heterogeneous data stores. (DAMA DMBoK2)
• “A technology that delivers information from various data sources, including big data sources such as Hadoop and distributed data stores in real-time and near-real time.” (Boston University)
• Abstraction of IT data resources “that masks the physical nature and boundaries of those resources from resource users.” (Gartner)
• A technical “approach by which data access can be easily centralized, standardized, and secured across the enterprise, no matter the location, design or platform of the data source.” (Indiana University)
• “The process of aggregating data from different sources of information to develop a single, 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.” (Techopedia)

Data Virtualization Use Case Examples Include:

• Creating “a world class process and strategy to automate the data forensics and resolve regulatory requirements across the organization”
• Complying with the European General Data Protection Regulation (GDPR)
• Aiding in the development of blockchain and machine learning projects within an organization

Businesses Need Data Virtualization To:

• Spend 40 percent less on building and managing data integration
• Connect distributed data assets
• Limit data silos
• Drive new innovations
• Streamline operations

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