What is Big Data Virtualization?
Big data virtualization is a process that focuses on creating virtual structures for big data systems. Companies and other parties can benefit from big data virtualization as they can use all the collected data to achieve different goals. There is a call in the IT industry for big data virtualization tools to aid in handling big data analytics. There is a call in the IT industry for big data virtualization tools to aid in handling big data analytics.
To explain the virtualization of big data, the general principles of virtualization as a whole must be understood. The main idea in virtualization is that heterogeneous or distributed systems are represented as complex systems through specific interfaces that replace physical hardware or data storage labels with virtual components. For example, in hardware virtualization, software turns a system of physical computers into a system of 'logical' or virtual computers. This virtualization system can represent parts of two or more different storage drives on two or more computers as a single 'Drive A' that users can access as a unified whole. In network virtualization, systems can represent one set of physical nodes and resources as a different set of virtual components.
One way to think about a large data virtualization resource is with an interface that was created to make big data analytics easier to use for end users. Some experts also explain this by creating a 'layer of abstraction' between the physical big data systems, i.e. where each bit of data is housed individually on computers or servers, creating a virtual environment that is much easier to understand and navigate. Big data virtualization aims to unite all of these distributed locations into one simple virtual element.
The business world has developed a sophisticated set of big data analysis tools, but not all support the principle of virtualizing big data and this type of work has its own challenges. Some claim that companies are slow to embrace big data virtualization because it is seen as arduous and difficult to implement. That may change, however, as service providers continue to manufacture the products and services businesses want, and seasoned IT professionals examine how to change the way a system is physically built and how it is used by an overall software architecture .