Within the world of enterprise IT, “data virtualisation” is an unusually overloaded term that is used to describe a number of distinct technologies. This can be very confusing, particularly because data virtualisation of all stripes is becoming an increasingly popular and even commoditised capability.
This paper will seek to illuminate this state of affairs, describing how the term is used, the different approaches it encompasses, and the advantages and disadvantages of each. We begin with a brief overview of what the term data virtualisation means and how it is currently being used in various different markets, before moving on to pick apart several conflicting uses of the term. Finally, since data virtualisation is becoming more or less ubiquitous within analytics environments, we will also describe the different technological options that may be adopted to provide data virtualisation, along with their respective advantages and disadvantages, in that context.