Data Virtualization is an approach that allows one to be able to access, administer, and optimize a heterogeneous infrastructure as if it were a logically unified, single resource. It ensures that data is integrated well with the other systems to allow enterprises to harness big data for the purposes of operations and analysis.
Big Data Virtualization is an approach that focuses on the creation of virtual structures for big data systems. This is extremely beneficial for organizations since it allows them to utilize all the data assets collected to achieve their objectives.
There is a big call for Big Data Virtualization in the IT industry. This is because it offers immense help in handling big data analytics.
A Big Data Virtualization resource can be considered as an interface that has been created to make big data analytics more user friendly. It can be easily explained as the creation of an abstract layer between the physical big data systems where each data bit is stored on servers or computers and the designing of a virtual environment that is easier for the user to understand and navigate. The main aim of Big Data Virtualization is to combine all of these locations into one, unified virtual environment.
While the business world has developed an array of big data analytics tools, some of them are ill-equipped to support the idea of Big Data Virtualization. With time, this would change as well and there would be development and effective utilization of sophisticated tools as well.
This whitepaper sets out details about various key performance indicators
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