IEEE CIS Task Force on Process Mining

Trace: slide2


XES Webinar

Slide 2: Data is omnipresent…

The real need for such a language originates from the fact that, these days, data is almost omnipresent, and coming at us in a rapid pace. For example, in two-thousand-eleven, McKinsey estimated that [TAB]thirty billion pieces of content were shared on Facebook, every month, that [TAB]two-hundred-and-thirty-five terabytes of data have been collected by the US Library of Congress by April of that year, that [TAB]fifteen out of seventeen sectors in the US have more data stored per company than the US Library of Congress, and that we need [TAB]one-and-a-half million more data-savvy managers to take full advantage of big data in the US alone.

In two-thousand-twelve, Gartner stated that in two-thousand-fifteen there would be a need of [TAB]four-point-four million analysts worldwide; of which only twenty-five percent can be met.

Figures from a Dutch newspaper from two-thousand-thirteen show a similar story: People produce per day [TAB]four-hundred million tweets, send over [TAB]three billion likes, and upload [TAB]three-hundred million pictures. Furthermore, Google Voice processes [TAB]ten years of spoken text daily, the UK has [TAB]two million surveillance cameras, and Facebook has [TAB]one billion users, who watch [TAB]four billion movies daily. Finally, in two-thousand-twenty there will be [TAB]twenty-four billion internet connected devices.