Data Virtualization

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Data virtualization is a logical data layer that integrates all enterprise data siloed across the disparate systems, manages the unified data for centralized security and governance, and delivers it to business users in real time.

Data virtualization is an approach to integrating data from multiple sources of different types into a holistic, logical view without moving it physically. In simple terms, data remains in original sources while users can access and analyze it virtually via special middleware

Data virtualization is the process of integrating enterprise data from multiple sources and managing it with centralized security and governance to deliver a single virtual view of real-time data to business users and front-end solutions.

Key differences: Data virtualization leaves the source data where it is and delegates the queries down to the source systems while ETL copies the data from the source system and stores it in a duplicate data store.

Data virtualization enables business users to consume data through reports, dashboards, portals, mobile apps, and Web applications. The Consume layer enables a single point of access and interaction with the underlying data sources, as well as abstracted data views in a standard delivery format.