UPDATED 10:21 EST / FEBRUARY 06 2017

BIG DATA

These skills have nothing to do with data, so why do all data scientists need them now? | #WiDS2017

The Stanford Global Women in Data Science Conference 2017 wrapped up last week, leaving attendees clearer on where the young field is maturing and where there is room for improvement.

“The softer skills are increasingly even more important for interpretation, evaluating the data — is it good data, bad data, clean data? Maybe it’s too clean,” said Jeff Frick (@JeffFrick), co-host of theCUBE, SiliconANGLE Media’s mobile live streaming studio.

Frick and Lisa Martin (@Luccazara) (pictured), cohost of theCUBE, said the diversity of organizations applying data science is encouraging. But if this situation creates jobs, the data scientists to fill them may not materialize unless the curriculum and training they need become more widely available. (*Disclosure below.)

Martin noted that companies like @WalmartLabs on the retail side and SAP in tech represented the diverse users of data science at the event. But, she said, the applications seem to have much broader reach, even outside of business.

“One of the things that I found really intriguing was [the relationship between] data science and human rights,” she said, noting the use of data science in humanitarian initiatives around the world.

Frick and Martin spoke about a bifurcation of hard skills, like statistics, and softer skills, like creativity and communication, noting that with data science uses multiplying, there is a need to outfit pros with the skillsets they require.

Data science U

So will all of these skills come in one prepackaged degree program soon? Martin said the professors they spoke to at the conference contend there is room for improvement in data science curriculum.

These academics said that data scientists need to have some solid business training, “because nowadays in the boardroom, data science, data security, data is a board-level conversation,” she explained, adding that the C-suite and the data scientists will need to work tightly together and speak the same language.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of the Stanford Global Women in Data Science (WiDS) Conference(*Disclosure: TheCUBE is a media partner at the conference. Neither Stanford nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo by SiliconANGLE

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