Data Virtualization (DV), an established form of data integration, provides a comprehensive approach to managing, accessing, integrating, and providing data to drive better decision-making throughout an organization.
It has become an important part of modern data infrastructure, used because it speeds development, increases data reuse, reduces data replication and movement, and breaks down data silos. Further, Gartner estimates that organizations that include DV in their overall data integration strategy spend approximately 45% less than those who do not. (Zaidi et al)
However, it is important to recognize that while DV has a number of advantages, it is not a panacea for all data integration challenges.
This document provides architects, analysts, and developers with guidance for making informed decisions on data virtualization software.