As someone who had already studied the “statistics,” be such learning procedure an interesting experience or one unwilling process, within some remote days before, you may remember only some parts of such subject now. Or not. Should yes, how much modernization is your present statistical mind?
Acclaimed by some experts and publications yet was severely and widely rebuked mercilessly by more genuine experts, statistics scholars and on-the-field specialists, the “Super crunchers” is indeed one premature work of one statistics layman writing about the undoubted and overwhelming rise of the imminent glorious era of gigantic data mining, or super number crunching as the author named it. Still, the author, Ian Ayres, is both one law professor and management professor at the prestigious Yale schools. Meanwhile, he, or the publisher both, somewhat brazenly call himself an econometrician, however, such title was proved wrong within his scholastic works, and lawyer.
What is super number crunching, or gigantic data mining, indeed? It refers to using the statistically quantitative regression, with the help of computers to deal with gigantic data, to generate any specific desired outcome. Its best applications will be on forecasting some specific imminent results, then will greatly helpful on guiding any related host or decision-maker ranging from any business, professional to governmental sector, to meet its desired ideal outcomes on any specific decision-making process, forecast, insight, or marketing genre beforehand. Should any specific decision-making, forecast, or marketing technique (which is the direct result originating from the computer-generated mechanism within this case,) can be proved as the ideal example successfully afterward, the rise of the gigantic data mining mechanism will absolutely step upwardly, triumphantly and much rapidly. So far, this is both a positive fact and one ongoing trend, which is also the most core throughout this book.
Nevertheless, Super Crunchers have its many examples-based credits and more scholastic drawbacks. It depicts clearly some interesting incessant success stories (ranging from business, professional to governmental sectors) of many traditional experts and experience-based intuition were already outperformed by data mining mechanism; though such stories themselves are never true epitomes of real gigantic data mining applications. Clearly, Super Crunchers is never any textbook or guide-book on formulating the gigantic data mining, which is actually the computer-generated statistically quantitative regression mechanism, nor the simple traditional statistics indeed. It neither outlines the quintessence of the gigantic data mining memethodology nor portrays any definite example of such processing and its applications by utilizing this profound statistical regression mechanism. What he defies seriously is the ultimate law associating with any scientific research and subject that must be followed flawlessly: the strict defining on the question itself, the scientific methodology and its approaches on solving the target question, (which is the true gigantic data mining mechanism within this book) and its successful application and any potential limitation. None of these three frameworks is firmly and surely met within those addressed examples of this book.
Still, Super Crunchers vividly showcases the promising ascendance and prevalence of this gigantic data mining and effectively evoke the public attention spotting on the dawn of the forthcoming and groundbreaking computer-generated decision world, or the near future world driven by those destined decisions originating from lots of huge statistically quantitative regression mechanism actually. The diminish of traditional experts and experience-based intuition is already on the way. What’s left for we human beings? Hypothesize, as Ayres concluded.
At last but not the least, will you become obsolete or even totally be replaced by some computer-aided statistical regression mechanism on approaching the near foreseeable future ahead?
