In particular, Big Data the term, coupled with awareness of Big Data the phenomenon, was clearly percolating at Silicon Graphics (SGI) in the mid 1990s. John Mashey, retired former Chief Scientist at SGI, produced a 1998 SGI slide deck entitled "Big Data and the Next Wave of InfraStress," which demonstrates clear awareness of Big Data the phenomenon. Related, SGI ran an ad that featured the term Big Data in Black Enterprise (March 1996, p. 60), several times in Info World (starting November 17, 1997, p. 30), and several times in CIO (starting February 15, 1998, p. 5). Clearly then, Mashey and the SGI community were on to Big Data early, using it both as a unifying theme for technical seminars and as an advertising hook.

Visualization provides an interesting challenge for computer
systems: data sets are generally quite large. taxing the capacities of main memory, local disk, and even remote disk. We call this the
problem of big data.

The cliometricians "specialize in the assembling of vast quantities of data by teams of assistants, the use of the electronic computer to process it all, and the application of highly sophisticated mathematical procedures to the results obtained", (Stone 1979: 11). Against these procedures, Stone lodges the objections that historical data are too unreliable, that research assistants cannot be trusted with the application of ostensibly uniform pules, that coding loses crucial details, that mathematical results are incomprehensible to the historians they are meant to persuade, that the storage of evidence on computer tapes blocks the verification of conclusions by other historians, that the investigators tend to lose their wit, grace, and sense of proportion in the pursuit of statistical results, that none of the big questions has actually yielded to the bludgeoning of the big-data people, that "in general the sophistication of the methodology has tended to exceed the reliability of the data, while the usefulness of the results seems — up to a point — to be in inverse correlation to the mathematical complexity of the methodology and the grandiose scale of data-collection'' (Stone 1979: 13).