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Tam Harbert

IT Pros Need Right-Brain Thinking for Big-Data Success

Written by Tam Harbert
11/20/2012 45 comments
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We're all familiar with the stereotype of the IT professional. He (and it is usually a he) prefers machines to people, and would rather write programs than prose. It's the classic left-brain skillset.

Like many stereotypes, there is some truth to the assumptions, even though they don't fit every individual. As IT becomes more integral to business, however, IT departments will need more people who buck the cliché. They'll need staff with strong right-brain skills: creativity, intuition, and empathy.

Nowhere is this need more pronounced than in big-data, a growing field that is already suffering from a lack of qualified workers. McKinsey & Co. predicts that by 2018, the United States could face a shortage of more than 1.5 million people who can work with, analyze, and interpret data in ways that enable business decisions.

Many IT departments are scrambling to find people with the right technical skills for big-data. They are looking for people with strong backgrounds in statistics, business analytics, search algorithms, natural language processing, or other specialized skills (on the software side), along with Hadoop and/or data storage skills (on the hardware/infrastructure side). Such specialists are being snapped up fast and paid exorbitant salaries, especially if they have worked for one of the search or social media companies that have pioneered data analysis. (One analyst told me that $300,000 to $500,000 wasn't out of line for a top data scientist.)

Rather than a crisis, this shortage could be an opportunity for CIOs to enrich and strengthen their department by identifying and encouraging IT staffers with right-brain skills. For IT professionals, it's an opportunity to increase their level of job satisfaction and potential for advancement. In recent interviews for a Computerworld story, several data scientists said the best candidates for big-data jobs are "Renaissance men" -- intensely curious and creative people who are interested in many different disciplines, including the arts and humanities. Again and again, my sources pointed to the following characteristics:

  • Intellectual curiosity
  • A comfort level with non-technical people and the ability to explain big-data concepts and analysis in terms that business people understand
  • An ability to understand how to analyze data in ways that support the business and further business goals
  • Dogged persistence despite repeated failure, because big-data is an area in which you have to try lots of things that don't work, in order to find those that do
  • An open, flexible mind that can switch perspectives and assumptions
  • A strong creative bent

"These are people who fit at the intersection of multiple domains," said D.J. Patil, data scientist in residence at Greylock Partners, a venture capital firm. "They have to take ideas from one field and apply them to another field, and they have to be comfortable with ambiguity."

Patil ought to know. He is among the first wave of data scientists, having worked on data analytics at LinkedIn, PayPal, and eBay. Last year, he placed second on Forbes magazine's ranking of data scientists, just behind Larry Page. With Jeff Hammerbacher (founder of Cloudera), Patil coined the term "data scientist" when they both worked at LinkedIn. It's the type of mind a person has that determines how well they can work with data. People can learn the technical skills along the way. At LinkedIn, for example, Patil hired a neurosurgeon for his data analytics team. "He hated surgery," he says.

Of course, there are different specializations within data science, each of which might be suited to different individuals. An IT person with an interest in art, for example, might be perfect at the job of visualizing complex data. Someone who writes well could thrive at explaining how data analysis can be turned into business advantage.

To take advantage of this opportunity, both CIOs and IT professionals need to broaden their thinking when it comes to IT hiring. CIOs shouldn't focus narrowly on searching only for technical qualifications. Instead, they should keep an ear to the ground -- perhaps through their professional networks -- for these Renaissance types. And they should review the staff they already have, looking for those closet right-brainers with an interest in and aptitude for big-data.

IT professionals need to demonstrate all their skills and interests. Especially for those who've felt confined by the nerd stereotype, now is the time to break out of the mold and talk about your community theater alter ego. Enlightened managers are starting to realize that your right brain may be just as valuable, perhaps even more valuable, than your left.

Tam Harbert is a freelance journalist based in Washington, D.C.

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Michael P. Kassner
Thinkernetter
Tuesday November 20, 2012 8:19:12 AM
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I can only assume that you are outside looking in. IT types are good at what they do because that behavior was required at the time. Now that a different marker is being applied you degrade the existing IT worker. 

I also might suggest that you are not aware of the adaptablity of those you stereotype. 

Ariella
Thinkernetter
Tuesday November 20, 2012 8:41:20 AM
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This past summer, a Venture Beat article suggested that data scientists should really be called data artists. John Koetsier wrote: "Perhaps these scientists are not the Einsteins and Edisons but the Van Goghs and Picassos of the big data revolution." 

Of course, Edison was an inventor rather than a scientist and Einstein identified imagination as key to scientific progress, but the point is really to break out of thinking of data as something fixed to be amassed but to consider it a medium for creative thought.  

The fact is that working with Big Data effectively calls for using both the creative and methodical parts of the brain. That is what Einstein called science:

"The mere formulation of a problem is far more essential than its solution, which may be merely a matter of mathematical or experimental skills. To raise new questions, new possibilities, to regard old problems from a new angle requires creative imagination and marks real advances in science."

 



kiranIE
IQ Crew
Tuesday November 20, 2012 9:40:46 AM
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I think we should think outside the box. No way we are degrading the IT scientists but for their own benefit ,and with the organizaitions up coming demands, one should broaden their scope of knowladge and work to fit in well with the new trends. By using a little more of " creativity, intuition, and empathy" the IT scientist will not be any less but could do better at his job ,explaining his analysis in case of Big-data, while communicating with the customers and fellow employees. 

DrT
IQ Crew
Tuesday November 20, 2012 10:40:20 AM
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I agree. Data scientists would have to look at the data in hand in different angles to understand if there is any value to the business. They can really help business re-discover itself. I also think we need to innovate further tools to be able to deal with the exponentially growing unstructured data, we need to find new ways to deal with it, then we let data scientists choose the right tool and be creative as much as they can.

Bolingbroke
IQ Crew
Tuesday November 20, 2012 10:50:15 AM
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Stereotpes make for a very comfortable and simplistic outlook. Personally I found stereotypes were extremely useful during the recent political jeremiad we all had to endure. Stereotypes also come in mighty handy in tv sitcoms where 2 demensional characters are an absolute requirement.

I can't/won't reveal my sources but a high ranking tv exec ( we were fratboys a long time ago ) recently whispered in my ear  that a sitcom is being developed where the main character is a recently hired Hadoop specialist ( i.e. super-nerd ) who thru necessity is rooming with a wild-eyed Van Gogh type. You can just imagine the merriment and jollity that are bound to ensue. It should be aired this Spring and the provisional title is Hadoop.    

syedzunair
IQ Crew
Tuesday November 20, 2012 12:05:46 PM
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DrT: 

I agree. Data analysis is difficult especially with all kinds of raw data the business stores. Analysis also has to done with help from the business. The business has to define the variables they are looking out for and then the data analysts can help them in getting some concrete results. Without collaboration I don't think it will work. 

kiranIE
IQ Crew
Tuesday November 20, 2012 12:43:53 PM
no ratings

thats something i will look forward to seeing! such shows would encourage and make the nerd-IT specialist look cool and famous . We see shows of all kind, a little different show based on IT tech will help people see how hard the work of these people are and they are actually a huge support in every organization and behind every business. 

Kicheko
IQ Crew
Tuesday November 20, 2012 3:12:50 PM
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Interesting that Hadoop should hit the entertainment screens....after which it would become a terminology not just in the workplace jargon of IT specialists. I agree with this story on the mportance of the right-brained people in the IT field. At the very least the provide a bridge between the geeks and the rest of the world. e.g. by designing interactive games buy which people can learn these technologies.
lin crampton
IQ Crew
Tuesday November 20, 2012 4:55:22 PM
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Thinking outside the box is not enough.  Exploration of new territories usually requires people who refuse to recognize the existence of the box.  

I wonder if I should re-write my resume to include all those uber anti-technical things I did while working my way through college ... 

Mitch Wagner
Thinkernetter
Tuesday November 20, 2012 5:18:00 PM
no ratings

Good point, Michael! How has your experience differed from Tam's description?

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The ThinkerNet does not reflect the views of TechWeb. The ThinkerNet is an informal means of communication to members and visitors of the Internet Evolution site. Individual authors are chosen by Internet Evolution to blog. Neither Internet Evolution nor TechWeb assume responsibility for comments, claims, or opinions made by authors and ThinkerNet bloggers. They are no substitute for your own research and should not be relied upon for trading or any other purpose.
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