“What exactly is Big Data? At first glance, the term seems rather vague referring to something that is large and full of information. That description does indeed fit the bill, yet it provides no information on what Big Data really is. Big Data is often described as extremely large data sets that have grown beyond the ability to manage and analyze them with traditional data processing tools. Searching the Web for clues reveals an almost universal definition, shared by the majority of those promoting the ideology of Big Data, that can be condensed into something like this: Big Data defines a situation in which data sets have grown to such enormous sizes that conventional information technologies can no longer effectively handle either the size of the data set or the scale and growth of the data set. In other words, the data set has grown so large that it is difficult to manage and even harder to garner value out of it. The primary difficulties are the acquisition, storage, searching, sharing, analytics, and visualization of data.There is much more to be said about what Big Data actually is. The concept has evolved to include not only the size of the data set but also the processes involved in leveraging the data. Big Data has even become synonymous with other business concepts, such as business intelligence, analytics, and data mining. Paradoxically, Big Data is not that new. Although massive data sets have been created in just the last two years, Big Data has its roots in the scientific and medical communities, where the complex analysis of massive amounts of data has been done for drug development, physics modeling, and other forms of research, all of which involve large data sets. Yet it is these very roots of the concept that have changed what Big Data has come to be” (from: Frank J. Ohlhorst, Big data analytics : turning big data into big money, 2013)
cosimoaccoto.com 