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The ‘Softer’ Side of Data Analytics

An article on setting up your data science team at Information Management of course suggests knowing “the products” you want these folks to produce: ad hoc, periodic and real time. The “spanners,” as it calls them, who cover all aspects of business analytics are likely to be expensive, while a multi-person team might offer various […]

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Susan Hall
Susan Hall
Nov 27, 2012

An article on setting up your data science team at Information Management of course suggests knowing “the products” you want these folks to produce: ad hoc, periodic and real time.

The “spanners,” as it calls them, who cover all aspects of business analytics are likely to be expensive, while a multi-person team might offer various plusses, such as niche skills with a particular business unit.

It struck me, though, that rather than someone who “jumps all over the tech” — though the article suggests having separate ETL and data warehouse people and as much automation as possible — Accretive Health Chief Data Scientist Scott Nicholson stressed the need for solid communication skills and curiosity. I’ve heard curiosity mentioned several times as a vital skill in analytics. He’s quoted as saying:

The engineering stuff you can pick up … but the curiosity? That’s something that’s built in. I can teach someone Python, but the curiosity is far harder to get.

And communication skills topped the list in this Wall Street Journal post, “Must-Have Job Skills in 2013.”  As Meghan Genovese, senior associate director of the University Michigan’s health informatics program, told me recently, it’s not just about gleaning insights from the data, but in communicating them as well.

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