Above is a time series graph of “big data” and “web 2.0” .
Contrary to this graph, data did not accumulate and pass the “big” status threshold in 2011. It is certain that we collect data in increasingly larger quantities, in fact we collect more regardless of importance due to economies of scale. These changes have been incremental and not a qualitative departure from the past. Much like a scalar big data has only magnitude and not direction; big data is a marketing campaign. Where as interest in web 2.0 was organic, referring to cumulative changes in the ways software developers and end-users use the web, interest in “big data” was not and is a result of vendor marketing.
Similar to frivolous terms coined in other industries, such as bicycles, “over-mountain, all-mountain, enduro, cross country, freeride, downhill” they have been coined to promote new interest in barely differentiated and overlapping products. Decision support systems come in just as many flavors: BI, business analytics, data benchmarking, data analytics, performance monitoring, and data mining. Essentially these terms or rather their owners benefit from being loosely defined and it is only the job of a non-technically entrenched “business person” to try to differentiate them.
Following the first rule of doing a good online marketing (according to http://seobergen.no ), I did the search for a data analysis and reporting solution for my company, and came across many “white papers” and reports from “global institutes”. I was surprised to find so many organizations vying to be the authority in data XYZ. My academic habitual instinct was to search Wikipedia and I was not surprised that citations were not from computer science journals or op-ed pieces from subject matter experts out of Sloan, Haas, Anderson, or Wharton, but from BI vendors.