All Things Techie With Huge, Unstructured, Intuitive Leaps

Future Job Category ~ Data Grader And Goal-Oriented Valuator

The one thing that I have learned from designing a remarketing platform, is that there is a market for absolutely everything.  This was exemplified by my trip to Siberia. Near Finland's border I discovered a Russian millionaire who made his money from crap. Literally.  He was a chicken farmer.  Up on the north peninsula to Finland, the ground is rocky and devoid of nutrients.  Chicken crap is an amazing fertilizer full of nitrogen.  He would trade piles of chicken crap for used Swedish cars - mostly beaters that the Finnish farmers bought cheaply.  Getting a car in Russia is tough if you are not in a major center, and he marked up his cars considerable and within a few years, became a millionaire.  Like I say, there is a market for everything.

I was watching a video on the modern fur trade, from the trapping right down to the auction. It was fascinating because when we think of fur trade, we think of glamorous women in fur coats on the runway.   In the case of furs, there is an industrial market for crap furs.  The Chinese are the biggest buyers. They will buy rabbit fur, and furs that are not good enough for clothing, and use them for toys, novelties, lining on the inside of boots -- wherever.

So there is a job description in the fur purveying process called a fur grader.  Before the auction, he and his staff go through the bales and bundles of furs, and groups them according to quality and type. Bales for sale consist of similar types and grades so that the quality of the bale is consistent.

As I was watching this, it struck me that the same thing will happen to data.  There will be a data grader who will assemble datasets, grade them, evaluate their marketability, cleanse the data, and put it on a data exchange.  In the case of valuable datasets, there will be a data auction.  And if you are thinking of starting a data exchange, have I got the platform for you !!!

You will also get the arbitrageur and day trader of data. If I see I dataset that is going cheap, I just may pick it up.  You see, I will have machine learning on my side, so I can process it.  I will do goal-oriented mining, and create multiple datasets of differing things with differing values.  Much like capital partners buy and ailing company, and break up and sell its parts for more than the overall thing was worth, the same will be done for data.

It's a brave new world out there.  Folks in the industry used to think that the never-ending, endlessly multiplying streams of data were a scourge.  They are actually a raw material and an asset. After all, there is a market for everything.  Sign up for my emails on the right for more.

# DO-IT #tag for NLP machine learning for this article.

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