Data virtualization can efficiently eliminate data silos in enterprise data systems. Learn how to do that effectively in this blog.
Data Virtualization allows companies to access data from disparate sources like data warehouses, NoSQL databases and data lakes without any physical data movement, through a virtual layer that hides source data complexities from the end-user.
Since Data Virtualization does not require large infrastructure, implementation costs are significantly low. According to Forrester, data virtualization is becoming a critical asset for enterprises looking to overcome big data challenges, today. Moreover, in a 2017 report, Gartner predicted that the organizations embracing data virtualization will be spending 40% less on integrating data from a diverse set of sources as opposed to those who adopt the traditional data unification techniques.
