Key Aspects of Data Virtualization

  1. The data is combined and transformed in real time, so users or applications that consume the data have access to the latest data without needing to connect directly to the sources.
  2. The data virtualization layer abstracts the location and format of the original data so that the end user is not exposed to the complexity of the underlying data model. This means that if changes occur in the underlying data, the logical representation for the end user remains the same.
  3. The logical datasets created in the data virtualization layer can be used regardless of the consumption method , establishing data consistency across the organization.

Using Data Virtualization to Create a Data Services Layer

Other Benefits of Data Virtualization



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