The Wisdom of the Crowd Looks at What's Hot and What's Not on Data Science for 2015

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CrowdFlower is an interesting company located in the Mission District of San Francisco, CA.  What makes them interesting is that they have a technology platform that takes large, data-heavy projects and divides them into small tasks that are distributed to a multi-million-person, on-demand workforce around the world.  In fact, the company says that contributors from 208 countries and territories have completed more than 1.3 billion judgments for CrowdFlower customers. And, in case you are wondering how they can get all of that work done it is through 5 million contributors, aka the smart crowd.

Along with their business model, what also makes the company one worth following is that the wisdom of this crowd can be intriguing.  The latest example is an infographic from CrowdFlower on a subject that is incredibley timely—what as interpretted by the data scientists at CrowdFlower thinks will be hot and not in 2015 in the area of data science.

What is data science?  We know it more commonly as big data coupled with data analytics. It is all about getting as much information as possible and rapidly turning into actionable insights on a myriad of fronts from predicting consumer behavior to driving changes in product features and business models.

So what is hot and not according to the wisdom of the crowd?  Take a close look.

Source: CrowdFlower (click to enlarge)

As a fan of occasionally being what the Brits call “cheeky” the descriptions are both a bit irreverant but to use another term popular in the U.K., “Spot On.”

I happen to think the first and last points may be the most important.

As others have pointed out big data and analytics are great assuming you have somebody with the multitude of skills to actually be a data scientist. The problem is that there are very few people in the world with such skills. It means being a brilliant geek as well as a brilliant business person—think Steve Jobs, Bill Gates and the very few others like them. In fact, given the silos to be broken down, the culture changes to be made, having not just business skills but finely honed political ones are going to be critical for the people who attain this status and are successful.

That leads us from the first point to the last. Where are the data scientists of the future, upon whom so much will be expected, going to come from?  Unfortuantely, to say the answer to that question is problematic is an understatement. Indeed, the crowd gets really small on that subject but hopefully out of that group of 5 million (and growing) already engaged with CrowdFlower, the seeds for talented data scientists are going to emerge.

Finally, while this need is part of the crowd’s view on 2015 it is by no means a one year deal. As more and more companies come to rely heavily on crunching the data and try to be ever more responsive to perceived changing market requirements it is arguable that the skills required of “qualified” data scientists are only going to increase.  Hence, if you have one cherish them, and by all means have them mentor as many promising folks as possible since the talents at the top of the company regarding how to best use data do need to permeate the lines of business.




Edited by Maurice Nagle
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