As we discuss Big Data, it is worth noting that there are many definitions of it floating around, and you may hear or see something a little different from each source. But, most of these definitions do have three characteristics in common: the increasing Volumes (amount) and Velocity (speed) of data, and, of course, the ever-evolving Variety (data types, sources, level of structure) of data.
Beyond that, you may also encounter some variations on what Big Data is. To some, it is when the volumes get into petabytes (1,000 terabytes) or even exabytes (1 million terabytes) range. Others focus on the amount of unstructured or semi-structured data coming in and its level of dispersion/distribution.
Some experts would say that it becomes Big Data when your standard software tools or your conventional data processing methods can no longer manage or process the data in a reasonable way. Others prefer to define it as when the volume and types of data involved cannot reasonably be contained in a relational database. Many simply take the view that if the amount of data has become a major problem, you have entered the world of Big Data.
None of these views are “wrong”, but are simply seeing Big Data from different perspectives. In future blogs, we will delve more deeply into all of these concepts, with the understanding that, regardless of your particular viewpoint or situation, this is an increasingly important topic for almost every industry today.
