All invented products are at some point commoditized, and all their value tends to diminution. The wheel was a premium asset at one time, no doubt. The cavemen and women showed it off as a point of pride, and they were envious of the neighbor’s wheel: They talked disparagingly about it, and gave each other meaning glances. And look at the wheel now, we all have at least one, or did at one time or another, and we don’t particularly care. It took a while to get to this point, and there were carriages and cars that came between the first wheel and the modern variation, but those carriages and cars too have lost their glimmer. The novelty at least is not what it once was. There aren’t many invented products I can think of that don’t follow this pattern – perhaps fire, which is to say, energy, but that’s a different story. The subject of this post is big data.
The extent to which this field is truly new or is just now getting more widespread attention is debatable. Although the concept was perhaps around for many years, if not decades in one form or another, perhaps it now more truly “exists” because it has a name: Big Data. (It’s catchy, a little bit like a frat bro’s nickname, at least at the more technical schools.) Regardless of when the field was in actuality born, it’s fair to say that it too, like other invented products before, is undergoing evolution. It is an enormously complex product – much more so than the wheel, at least in some ways – that incorporates issues of science as well as law, art as well as commerce, consumption as well as production. It is a highly specialized field, in which expertise is difficult to come by. I’m not an expert, but working very hard to learn.
An initial conclusion that I draw – reserving the right to change my mind as I learn more about the subject – is that, like other invented products, big data will follow an evolutionary path to commoditization. From up in the clouds, the landscape and its horizon are looking roughly as follows:
Let’s call the starting point creation, which is the collection or accumulation of massive amounts of data in a variety of on- and off-line platforms. The subsequent locale is analysis, an increasingly popular neighborhood of which is visualization. This allows our minds to extract meaning from otherwise impossible jumbles of raw information. Analysis has been with us since the point of creation, but visualization is now coming to its own, and it truly makes a world of difference: Images and symbols often convey a rich message, despite the seeming superficiality.
The next destination along the path is going to be valuation, which is not only an appraisal of product worth, but also a setting of standards. The two disciplines are closely related, and one drives the other as much as vice versa. While data is being collected and visualized, in many cases for the first time, we are still in a state of excitement, as it were, discovering new ways to play with this big data toy we now hold. Some of these ways will have not much more than entertainment value, while others will transcend the razzle-dazzle. As the distinction between the two and the nuances in between fall into place, so too will processes and procedures and standards of measure and accepted practice… And the next step from that – when the mystery and unlimited potential have been revealed and thus narrowed – is price competition: More generally termed, commoditization.
This is not to say that big data will necessarily be bought or sold, although a lot of it will be and already is – directly or indirectly – but its relative merits, its differentiators, are prone to become standard. This follows the theme of all invented products, and it isn’t to say that these turn obsolete. The wheel hasn’t, but the differences between one wheel and another have turned minor. So too, a time may come when differences between one dataset and another will not be a matter of quality as much as quantity. If so, the label Big Data may prove to be more correct than we might currently imagine.
