Data: the most precious commodity

diamonds320.jpgImage credit: Kim-bodia/Flickr

When you type “data is like oil” into Google you get 522 million results; while doing so in Bing yields a mere 270 million links. Do the same search substituting “gold” for “oil” and you get 1.3 billion and 364 million results from Google and Bing, respectively. You will forgive me when I admit I did not check them all.

I guess neither gold nor oil are worth enough. Now data is being called “the new diamond.” Perhaps Tiffany's will start selling USB sticks or disk drives as wedding rings in the near future?

It's understandable that some observers feel it's necessary to explain the rise in the value of data inside an organization by comparing it to an expensive commodity. Those who like the analogy note that, like oil and gold, data must be refined or processed in some way. Indeed, it is through analytics that data attains its true value.

But I disagree with the cozy comparison between data and commodities. I have lots of logical arguments that undermine the comparison. The most obvious is that oil and gold can be traded on open markets where buyers pay the same price. Data's value varies from user to user. Customer purchasing data for a given product is worth something to a company or a competitor that sells such a product, but not to my neighbor down the street. An ounce of gold or a barrel of Norwegian crude is worth the same to everyone.

Maybe because I work so closely with data, I feel it has more complexity than a physical commodity. Data yields information from which you can glean knowledge. And unlike a barrel of oil, you can use it repeatedly and it can increase in value. Use the oil once and it's gone forever. Data is so malleable it also often yields knowledge that you can leverage in many instances and venues beyond its original intent, something impossible with inert things as oil and gold.

Yes, I know, a chemist can do wonders with oil just as a metallurgist or jeweler can transform gold. But I'm more impressed when a data scientist extracts substantial value from columns and rows of information stored in a database. That, to me, is a more subtle and valuable art.

We shouldn't be trying to measure data's worth by likening it to a commodity. We should be extolling how much more valuable data is than gold or oil because it's the simple truth.

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