 Live from Stanford University, it's theCUBE, covering the Women in Data Science Conference 2017. Hi, welcome back to theCUBE, Lisa Martin here with Jeff Frick and we have had an amazing day, Jeff, the second annual Women in Data Science Conference. What an incredible group of women that are here sharing their stories and the inspiration is definitely symbiotic, it's going both ways here. We've had a fantastic day of really a lot of enlightenment. I'm a little jealous, Lisa, we gave you the seat after we came to the first one a couple of years ago but it really is a special, it's a special conference. So you've been sitting here, pulling the duty, getting a lot of great interviews in. What are some of your impressions or what are some of the kind of the big themes that have come out over and over and over that maybe you didn't expect? Yeah, definitely. You know, one of the things that I was really excited about coming into the event was the fact that we're seeing Data Science applicable in so many different domains. We've had, you know, we had Walmart Labs on this morning, you know, the influence there in retail and SAP was here in technology. Those are more tangible for a lot of us, especially in the Valley. One of the things that I found really intriguing was data science and human rights. That's not something that I really spent much time thinking about. How essential that is to be able to help different initiatives and really help evaluate what's going on in certain parts of the world. I thought that was fantastic. I also, from a thematic perspective, a couple of things really popped up. One is that the core data science skills are still absolutely there, you know, being a statistician, being a hybrid hacker, mathematician, being able to understand numbers, but also a couple of elements that are coming in that are really new sort of on the behavioral side, being able to be creative, interpret the information that the data say and explain it, communicate it in a way that either describes the value and shows where investment should be made or helps take you in a different direction. So communication was a really big theme as part of a core evolved data scientist role, as well as empathy, which really kind of caught me by surprise. Not something I would have thought about, but empathy for the different types of data sets you were looking at. And so those were some things that really were kind of a-ha educational moments for me that were very impactful. It's kind of this bifurcation of hardcore data science, hardcore smart mathematicians that are here talking about statistics and confidence levels, et cetera. But at the other time, as you said, the software skills are increasingly even more important for interpretation. Even evaluating the data, is it good data, bad data, clean data? Maybe it's too clean, maybe that's an issue. There was a conversation one of the keynotes about really inspecting the type of data that you have before you even get into the analysis. So the software skills continue to be really important as well as just the hardcore data analytics. Definitely. And one thing too that was another thing that came out of that was, we talked to a number of professors, professor from Harvard, we see a professor from the University of Utah. And looking at curriculum, it seems to be like a topic that's open for discussion. These data scientists recommending curriculum, whether kids are studying computer science or something related, needs to involve some business skills. Because nowadays in the boardroom, data science, data security data is a board level conversation and companies understand to some degree, there's a tremendous amount of business value in this. So for a data scientist to not only be able to communicate that, but to have enough understanding of business is also a core educational skill that was brought up a lot. It sounds like there's still a lot of room for improvement there. Yeah, it's funny, a bunch of my peers and myself, kids that are going through the college application process right now and they have to write their essays, right? And really the conversation that you still have to know how to write, regardless of the field that you go into, you got to communicate. And one of the themes that came up with Grace Hopper that I think when they were doing programs for younger kids, the kids were surprised at how much social activity was involved in doing math and data science because you have to communicate with the engineering teams. You have to communicate with the product managers. You have to communicate with the people you're collecting the data with. It's not this isolated sit in a room as like a quant jock on a spreadsheet. It's actually a much more social endeavor to get to the right answer. Absolutely, in fact, we were just talking to the COO of products and innovation at SAP and that was one of her recommendations is if you're going to be developing software for recruiters, don't do it in isolation. Go out there and actually sit and write along with the recruiter for a week to really understand the end user's perspective so that that can really drive, bring that real world applicability in to whatever that you're doing. So it was a really, it's neat to see the social skill influence there, how key that is. Collaboration, you mentioned that. That was another huge theme of how when we were talking to Janet George at Western Digital, who are the key collaborators of hers as the chief data scientist within the organization? How does she help take data, understand it, be able to process it and influence the manufacturing process? So it's communication is pervasive, it's horizontal and it's something that definitely should be part of I think the curriculum as well as the education that these people get when they're on the job. Right, it's funny too how the data science pieces keeps evolving and as the computers get smarter and the algorithms get smarter and they start to keep doing more and more of the computational load inside of the algorithm. How much again, you need some perspective, you need the software skills become even more important as the computers take over more and more of the actual computational skills. How about just kind of your impression of the vibe here in general? I know you've started to do more and more events and we're excited, we've got another great women in tech event later this month. Yes. The women transforming technology which will also be in Palo Alto. Just kind of your vibe, you know, kind of this small intimate event here at Stanford at the Ariaga Alumni Center. Geeking out over it. It's just been, the vibe is one of such positivity, such inspiration. It's very symbiotic, I think the speakers here, the women who are sharing their expertise, those whether they're doing keynotes or technical talks or on the career panel are learning just as much from the women that are here as the women that are here, maybe the young college girls are learning from them. So that symbiosis has been really, really, not apparent, it's palpable, you can feel it here. I think there's also a lot of excitement and appreciation for the gathering of 400 plus women just in Palo Alto today and how many cities is this being live streamed in? It's a fascinating, if you just go to the Twitter stream and look at WIDS 2017 is the hashtag. There are 70 cities, 25 countries, and there are groups all over there at SAP, they're at different universities, Harvard, MIT. I just saw WIDS Qatar, about 20 women in Qatar who reached out to the organization here, said we want to do something and found an academic sponsor. And you watch this, you know, there's a lot of conferences that try to appeal to a broad, engaged, really intimate audience. It's hard, unless you really have something people care deeply about, they're not going to engage. People are too busy. So to see this stream on the hashtag with these pictures of these little groups of people in conference rooms and rooms all over the world, it's really shows the passion that they've touched on here at the WIDS conference and really a compliment to the team. Absolutely, I think they've gotten also not only a phenomenal cross-section of guests and industries that have certainly opened my eyes to all of the different, or not all, some of the applicabilities of data science, but they've also had a great cross-section of business versus the technology side because clearly we're hearing, not just from SAP, but from a lot of the others, that even the professors, that those are essential to be married for this data science and where it is now to really be the catalyst for innovation. We were talking with professors, we were talking with people that are chief data scientists, and then we've had the CEO of SAP on talking to us from the business perspective who really understands fundamentally what the CEO needs to do or understand to help move the business forward with data. So in the second annual event, not only did they have Diane Greene as a keynote this year, in the second event that they've done, but they really in my perspective nailed it with the different diversity of speakers and industries and backgrounds, just incredibly educational. Right, and you've been stuck out here, I was in the keynote with Debra from the NSA. Another interesting thing, especially at the Q and A, because people were asking her to go places that she couldn't go. Last time it was Diane Bryant, so the question is what high-ranking Diane will we see next year in the keynote? Exactly. Well again, Lisa, thank you for all your help and hard work and really kind of carrying the freight today. Fantastic job, and we'll see you in a couple of weeks at the next thing. Yes, in fact, we have just taken a look at some of the upcoming shows that we have. We've got the Spark Summit next week, February 7th and 9th in Boston. MIT Expert Series, February 15th. This is by the way all, you can find all of this at siliconangle.tv. That's right. Google GCP next, 2017 in March. Google Cloud Platform, and also that we just added a new event, it's probably not even on the sheet, an IBM machine learning launch in Manhattan, February the 15th as well. Oh, fantastic. That's before we get to the women transforming technology at the end of the month. Exactly. It's a busy month. It is a busy month. Conference seasons upon us. It is. Well, thanks Jeff so much. It's been a pleasure being here. I'm so inspired by the people that we've spoken to and looking forward to the next event. Excellent. And we want to thank you for watching us all day. You can watch three plays at siliconangle.tv and on YouTube. We hope that you've learned as much as we have and we look forward to seeing you next time on our upcoming events. Bye for now.