As the Internet becomes larger and data grows at an exponential rate, the abundance of information has become unimaginable.  Along with the impossibility of trying to realize the depth of information, it becomes even more impossible to try to manage a growing network of data.  Thus, the management and utilization of data has become a topic of interest in the past decade, along with misperceptions as well as misunderstandings along with the technology allowing you to utilize the data.  As such, one of the most controversial topics of discussion is data virtualization.  It is not only a hot topic of discussion for experts in technology and business analysis, but even end users of a product who are curious as to the process utilized to create/manufacture/manage a product.

For those who are not very tech savvy, it may be hard to understand why anybody would be interested in data virtualization.  After all, it’s just a technological service and there are hundreds of them out there.  Why the immense attention on data virtualization?  The attractiveness of data virtualization ranges for a couple of reasons.  First, it is capable of supporting multiple data sources for an organization, allowing businesses to manage data in an effective manner across the enterprise.  It allows businesses to be able to respond effectively to dynamic business conditions, and decreases costs and time for developing and developed products.  It even allows acceleration of project completions, ultimately benefiting the bottom line of any organization.

In short, data virtualization allows you to have access to the information you need, when you need it.  Thus, it is a crucial element of any organization or business.  However, data virtualization itself will not allow you to create a compilation of data that becomes easily accessible.  You need to utilize other services in unison in order to fully benefit from data virtualization.  These technologies include data federation and ETL (Extract-Transform-Load).  Data federations allow you to create an archive of data, which stores the locations of all data across the enterprise, making data easily accessible.  ETL then steps in, and extracts the data from these locations, transforms them into a common language following the business rules set by a company, and loads them into a virtual database, able to be used by data virtualization technology.  Now perhaps you may be able to understand the hype behind data virtualization.  It takes data integration to a new level that could never have been imagined, allowing businesses to manage their data on an unimaginable level.