(upbeat music) Live from Stanford University. It's theCUBE. Covering Global Women in Data Science Conference. Brought to you by SiliconANGLE Media. Good morning and welcome to theCUBE. I'm Lisa Martin, and we are live at the Global fourth annual Women in Data Science Conference at the Arrillaga Alumni Center at Stanford. I'm very pleased to be joined by one of the WiDS ambassadors this year, Srujana Kaddevarmuth, Data Science Senior Manager Accenture@Google, and as I mentioned, you are an ambassador for WiDS in Bangalore. The event is Saturday. Srujana, welcome to theCUBE. Thank you. The pleasure is mine Lisa. So, this is the fourth Women in Data Science Conference. This year over 150 regional events, or which you are hosting Bangalore on Saturday March 9th. Fifty plus countries. They are expecting 100 000 people to engage. Tell us a little bit about how you got to be involved in WiDS. Yeah, so I care about Data Science, but also about accurate representation of in gender minority in the space. And I think WiDS Global Initiative is doing an amazing job in creating a significant impact globally, and that kind of excited me to get involved with WiDS initiative. So you have, which I can't believe, you were in SME with 10+ years experience in data analytics, focusing on marketing and customer analytics. You had senior analytics leadership positions at Accenture, Hewlett-Packard, now Google. Tell me a little bit about, before we get into some of the things you are doing, specifically the Datathon, your experience as a female in technology the last 10+ years. It's been exciting. I started my career as an engineer. I wanted to be a doctor. Fortunately, unfortunately, it couldn't happen, and I ended up being an engineer. It has been an exciting ride since then. I felt that I had a passion for pursuing management. I pursued management in specialization of operational research and project management. I started my career as a data scientist, worked my way up to different leadership positions, and currently I am leading a portfolio for Accenture@Google. In the data science domain. It's exciting. Absolutely. So one of the things that is happening this year, at WiDS 2019, is the second annual Datathon. That's right. Really looking at a predictive analytics challenge for social impact. Tell us a little about why WiDS is doing this Datathon and what you're doing in that respectively in Bangalore. Okay, so, you see, data science in itself is a highly interdisciplinary domain. It requires people from different disciplines to come together, look at the problem from different perspectives, to be able to come up with the most amicable and optimal solution at any given point of time. And Datathon is one such avenue that fosters this collaboration. And Datathon is also an interesting avenue, because it helps young data science enthusiasts hone the required data science skill sets and also helps the data science practitioners enhance and sustain their skill sets. That's the reason WiDS Bangalore was keen on supporting WiDS Global Datathon initiative. So the skill set, I'd like to kind of dig into that a bit, because we're very familiar with those required data analytics skill sets, from a subject matter expertise perspective, but there's other skill sets that we talk about more and more, with respect to data science and analytics and that's empathy, it's communication, negotiation. Can you talk to us a little bit about how some of those other skills help these Datathon participants. Not just in the actual event, but to further their careers? Absolutely. When we enter the real world, there are a lot of these challenges wherein you would require a domain expert, you'd require someone who has according experience. Someone who has experience to handle multiple data science programmatically. Also, you need someone who has a background of statistics and mathematics. So you would need different people to come together, look at the problem, and then be able to solve the challenges, right. So, collaboration is extremely pivotal. It's extremely important for us to put ourselves in other's shoes and see a look at the problem. Looking at the problems from different perspectives and collaboration are the key to be able to be successful in Data Science Domain search. Okay so let's get in the specifics about this years Data Set and the teams that were involved in the Datathon. Alright so this years Datathon was focused on using Satellite Imagery to analyze the scenario of deforestation costs to oil palm plantations so what we did at WiDS Bangalore is we conducted a community workshop because our research indicated that men dominate the leaderboard not just in Bangalore but for India in general, despite that region having amazing female leader scientists who are innovates in their space with multiple patents publications and innovations to their credits. So we asked few questions to certain female leader scientists to understand what could be the potential reason for the low participation on the Kegal as a platform, and the responses led to us to these three reasons. Firstly, they need not have awareness about Kegal as a platform. Can you tell me a little bit more about that platform so our viewers can understand that. Alright so Kegal is a platform wherein a lot of these data sets have been posted if anybody is interested to hone the required data science skill sets, they can definitely try, explore, build some codes and submit those codes and the teams that are submitting the codes which are very effective having great accuracy will get scored on the Kegal Leader Board and you know that which is the most effective solution that can be implemented in the real world So we conducted this Datathon workshop and one of the challenges that most of the female leader scientists face is having an environment to network collaborate and come up with a team to be able to attempt a specific Datathon challenge That is in hand. So we kind of created a Datathon workshop to help participants overcome this challenge and to encourage them to participate in WiDS Global Datathon Challenge, so what we did as a part of this workshop was we gave them on how to navigate Kegel as a platform and we conducted a event specifically focused on networking so that participants could network from teams. We also conducted a deep in depth technical session focusing on deep mirror nets and specifically on conventional mirror nets the understanding of which was pivotal to be able to solve this year's Datathon challenge and the most interesting part of this Datathon workshop was the mentorship guidance. We were able to line up some amazing mentors and assigned these mentors to the concerned or interested participating teams. And these mentors work with the respective teams so the next three weeks and pride them with the required guidance coaching and mentorship and help them with their Datathon journey. That's fantastic, so over a three week period how many participants did you have? There were around 110+ people for the event. And there were multiple teams that were formed and we assigned those mentors, we identified 7 different mentors and assigned these mentors to the interested participating teams. We got a great response in terms of amazing turnout for the event, new teams got formed, new relationships got initiated. New relationships, new collaborations, alright tell us about those achievements. So there were, there was one team from Engineering branch or Engineering division who were very new to Kegal platform and they had their engineering exams coming up, but despite that, they learned lot of this new concepts, they formed the team, they worked together as team and were able to submit the code on the Kegal Leader Board but were not the top scoring team. But, this entire experience of being able to collaborate, look at the problem from different perspective and be able to submit the code despite lot of these challenges and also navigate the platform in itself was a decent achievement from my perspective. A huge achievement. So here you are, at Stanford today you're going to be flying back to go host the event there, tell us about from your perspective, if you look at the future lying in sight for Data Science let's just take a peek at the momentum that this WiDS movement is generating this is our fourth year covering the fourth annual event, fourth year on theCUBE and we see tremendous, tremendous momentum with not just females participating, and the WiDS leaders providing sustained education throughout the year, the podcast for example, that they released a few months ago on Google Play and iTunes, but, also the number of participants worldwide, as you look at where we are today, what in your perspective is the future for Data Science? Alright, so Data Science as a domain is evolving at a lightning speed and we possibly hold the solution to almost all the challenges faced by humanity in the near future, but to be able to come up with the most amicable and sustainable solution that's more relevant to the domain achieving diversity in this field is a must. And initiatives like WiDS help achieve that diversity and foster a great impact. Absolutely, well Srujana thank you so much for joining me on theCUBE this morning live from WiDS 2019, we appreciate that, wish you the best of luck at the WiDS outlook event in Bangalore over the weekend. Thank you, it was a pleasure discussing with you. We want to thank you, you're watching theCUBE live from Stanford University at the fourth annual WiDS conference, I'm Lisa Martins, stick around my next guest will join me in just a moment. (upbeat music)