>> Narrator: Live from Denver, Colorado, it's theCUBE. Covering Commvault Go 2019. Brought to you by Commvault. (upbeat electronic music) >> Hey, welcome back to theCUBE. Lisa Martin with Stu Miniman. We are covering Commvault Go '19 from Colorado and Stu and I are pleased to welcome a couple of guys back to theCUBE. We've got David Wigglesworth, a VP, now VP of Global Sales and Emerging Technologies at Commvault for what, a couple weeks now David? >> About a month and five days. >> About a month, and look who's back, it's Don Foster, VP of Storage Solutions, >> Great to be back. from the Keynote stage, welcome back Don. >> Thank you very much. >> Don, and we appreciate you bringing your own personal makeup artist, Sanjay Merchandandi, >> Yeah. >> A man of many skills. >> Indeed. (laughing) >> He really is. So if this whole, like, CEO thing doesn't work, he's clearly got a career in, you know, touch-up makeup. >> In makeup. >> Yeah, all right, so Wigs we'll start with you, you've got a cool nickname, so I got to use it. You've been here for about a month or so. This is a new Commvault. We've heard a lot in the last two days. A lot of news, a lot of leadership changes, obviously, go-to-market changes, new partner offerings, lots of stuff. Tell us first, before we dig in, what attracted you to Commvault? >> That's a pretty easy question to answer, it's the leadership. So, obviously I'm very familiar with Commvault. I've competed with them in my past career. Always been a very formidable competitor. When you walked into an account in my previous life and they said they had Commvault, you usually kind-of wiped your brow, and thought 'Oh okay, I've got to find something else here to talk about' but in all seriousness, for me it was, you know, when I first noticed in the News that Sanjay had come onboard. That peaked my interest, because obviously I knew Sanjay in my previous life at EMC and at VMware. And then when I watched Ricardo join the company, I was like, okay, this is something I really need to dig into. And so when I had the opportunity to meet with them and understand the direction of where they want to take the company, which was also already just a phenomenal IT organization, just a pillar in the IT community, with what the founders were able to do in relatively short amount of time. I was really excited to be able to come over and be a part of it. >> Wigs, you've got a emerging tech under your purview, tell us a little bit about what that's going to mean in your role. >> Right now it means I'm head big, right? So, by now, everyone's heard of the acquisition that was made. That was the other thing also that really interested me, was that technology because I really think that's where the market is going and I just felt like it was a great addition to the Commvault family of products. But it's a different technology. It's calling on a different set of folks with inside of an account and it's primarily an enterprise play. It can be a go-down-market a little bit, and enterprise's is kind of where I spent the last several years of my career, the last 20 or so (laughs) and so what we've decided to do is, because it's so different, we've decided for the time being, that we were going to create a special aid organization globally to go sell that solution so that our existing core sellers can focus on our existing set of products, right? That we can be a specialist organization that can help them with their customers, selling all of the additional emerging tech, right? And so, here at the show, we've obviously spent time talking about Hedvig. Metallic is another new technology for us. Now Metallic is going to handled differently, but as we continue to grow our emerging technologies from the traditional core Commvault family of products, that's what I'm going to be focused on. So it'll begin with Hedvig. >> So for the role that you're in now, you said about a month or so, are you bringing in a brand-new sales overlay team? Are you guys hiring like crazy or are some of the Commvault OG sales-guys-or-girls shifting up, we'll say? >> For the most part, we're bringing in new talent. We're looking for people that have a broad spectrum of the experience, right. Obviously someone with strong storage background, but also people that know virtualization code, people that understand containers. Those skillsets are really important to us. And so we're busy building out both an America sales team and also building out a Nemea sales team. And then my partner, I call him my partner-in-crime, Ediz. Ediz is building out our SE organization for the same two theaters. We'll start in those two theaters and then once we get the product fully integrated, which is part of what this guy is doing, once we get the product fully integrated, then I think you'll see us start to move into some other theaters. But right now we're going to focus on those. So yes, we're hiring. Right now my LinkedIn says, "David Wigglesworth, we're hiring." >> I think I saw that actually (laughing). >> So Don, we got to dig into some of the technology with you and Avinash yesterday. >> Absolutely. >> So we're now getting most of the way through the conference, bring us inside some of the conversations you're having. I know it was one of the biggest question, we had coming in was: 'All right The Hedvig that we knew, what's going to change, how does that fit?' Blurring the lines between primary and secondary and all those discussions we had with Sanjay. So take us to how people, are they kind of getting it at this point? And we know it's a journey for the integration and where it will ultimately end. >> Here's the real interesting thing, is probably in the first, I don't know, maybe 24 hours of having conversations with people from partner exchange all the way through to basically day one of actual Commvault Go, I probably had about four, maybe five if you count one of the service providers from Customers' Partners, come up and say, "Okay look, we looked at this tech about 18, 12 months ago and it was top of our list for what we wanted to do for building out this initiative, but there was a little bit too much risk." Going okay, do we really want to invest that much on a company that is maybe not the largest, most, I wouldn't want to say, reputable, but substantial in the marketplace. Will they be there in the future? And they're like, "Now that we know you've legitimized that business "and you want to keep that technology going forward, "this is fantastic. "We totally want to go and take a re-look back at this "and see how we can apply "that back into our infrastructure." So that's a great feedback to hear, and only serves as validation that when we look at the tech and say "This is good stuff," that we know it's good stuff and then of course the next piece is always, "All right, so now when can I start using this for Commvault and?" >> Right. >> That's when we start getting into the conversations of all right, we've got some integration work to do, the partners are asking when they can start to get access to sell it and again, we've got some work to do just to industrialize what we're doing and make the experience similar and then we'll start to roll it out in a considered fashion. >> I'm curious about the education piece. One of the customers that was onstage this morning, Sonic Healthcare, one of the things he said, on main stage and when he stopped by theCUBE a couple of hours ago, was, he said: "I wouldn't be in my job," and he runs disaster recovery and business continuity for Sonic Healthcare, "I wouldn't be in my job without Commvault's support." And I really appreciated and respected how he talked about some of the failures that they had. I always think failure is a good F-word if you leverage it in that way, (agreement) failure can mean success, if you learn from it. But the support organization and the training he talked about have been instrumental. Talk to us, guys, about how you're going to be partnering together to not just enable the big partners for those large enterprise accounts but maybe even the new sales-guys-and-girls that are coming, David, to your team to help everybody really understand how best to delivery a really stellar customer experience with something as exciting now as Hedvig is. >> You want to start, since you've been working on the integration. >> Yes, absolutely. First and foremost, I've been working with Avinash and his brother, Srinivas, and a lot of their engineering team. You really start to lock in things that are repeatable and scalable in nature, right? So that if we are going to open this up to more people, we do need to have repeatable nature of the building blocks for different use cases. So there's some core work we're doing on outlining, positioning, criteria, success, what the outcome needs to be, how that ties back in to hardware. Making sure as well that we understand how the messaging really does resonate and make sure that we're following and being focused on what our core targets are. Because a solution like what Hedvig offers, you can quickly start talking about a lot of different things that could be all things to many people, and we know that that's probably the worst decision to make, because you go super wide and don't go very deep at all and you end up losing the value prop. So identifying what the real core use cases are, getting deep in how it works, one with what the structure of it looks like, making it repeatable, that's the first and foremost thing, I think, for how we can help both Ediz and Wigs' sales team, and on the support side, doing very similar things but also doing some of the programmatic work of the integration and the experience. I talk about experience, like the sending of logs, the things that Matthew Magby from Sonic Healthcare was talking about how we really helped him. We want that same level of experience tied into where the software storage platform works as well. So there's some work to be done there. But as we get it done, the enablement on the support side, as you know, we deal with storage everyday anyway, so it's not like it's a big leap, but we do have to bring them into the mix of how the actual technology works, where it breaks, why it breaks, and those are all the things that we're really focused on in the next 90 days. >> Yeah, I think the real key for me as we talk to customers and also employees is I want them all to have the same experience with the new Hedvig solution that they experience with Commvault, right? And that goes from training our employees, really getting our SEs up to speed, so they can have a meaningful conversation to be able to get a customer to say, "Yeah, I think I'd like to speak with the Special Aid team. "Please have them give me a call." And also on the enablement for the clients, and having the customer understand that you can dial to 1-800 number for support, you can talk to somebody that can lead you down a path and give you the same quality of support you've been used to whether you're calling about a Hedvig solution or whether you're calling about a Commvault solution. >> Yeah, we talked about it a little yesterday, but the scale of the offering is a little bit different. >> It is. >> And therefore, that has some challenges on the support. And something that I'm sure Commvault is going to work on making that, it's not identical for every customer but a little bit more repeatable to be able to scale out that offering. >> I would agree, I would agree. The hardest thing to do is when you have a product that has so much functionality as Hedvig is to not lose focus and try to talk way too broad. What you've really got to do is, you've got to drill down with the client try to understand where their pinpoints are and because, quite frankly, the Hedvig product can do a lot of things. >> Don: Yeah, it can. >> Who's the ideal target customers, we talked about the theaters in which you're going to be launching first. Enterprise, we talked about that. Commvault has a significant presence in the Fortune 500, I think I read about three quarters of Commvault's revenue today comes from the Fortune 500, and Stu was saying yesterday about 80% of the revenue comes from the channel. So we look at Hedvig and the enterprise for a second, customers that are new to Commvault, those existing enterprise customers, GTM both? >> Yeah, I would say, the primary focus is going to be calling on the existent customer set. It's much easier to have a conversation with someone who knows who you are, even though you may be selling a new solution, at least they know who you are and they have a positive experience with us. So that, number one, we're going to focus on our probably our top 300 global accounts to start, as well as our top enterprise accounts. So there's probably, I would say, in the two theaters I mentioned earlier, there's probably about 35 hundred accounts that we're really going to focus on, and really try to make sure that we get in front of as many as we can and tell the story. I think that's where we have to start. Now, will there be greenfield opportunities? Yeah, I think quite frankly, that the Hedvig offering is different enough that it will enable us to go call on some of accounts that aren't doing business with Commvault today, maybe doing business with some of our competitors. So hopefully we can use that to actually win more traditional Commvault business. That's the plan. >> And the reason the enterprise really makes sense, the global accounts, is most larger companies have figured out how try solve the CapEx problem, right? >> David: Yeah. >> They've figured out just the economies of scale and how they grow and move, they can kind of handle that. What really still becomes a challenging piece is the operational efficiency. So, can I get the right solution at the right cost, but do it in a way that I'm actually making things more simplified? I'm not actually exploding more complexity into my environment. That's really where the Commvault data management platform and the Hedvig solution together really make a really solid story. >> All right, so Wigs, Don's team's really got their work cut out for them with all the integration work and know they've got a cadence and a roadmap. For you, obviously, new logos, there's got to be revenue goals. What are some of the key KPIs to measure how this becomes a successful acquisition? >> Well if my CEO is standing close by, he may be in earshot of this, right now it's trying to drive as much revenue as we can. But we also have to realize that we also have to build a pipeline, right? So right now my main focus here is I got to get a team in place that can go articulate the value of this solution to a client, right, number one, both technically and then working with Ediz to get the SE team in place, so that's number one. Number two, while we're doing that, we need to build a pipeline, right? When you make an investment, as you guys know, you're expected to start getting a return on that pretty quickly. And, it's nice, we inherited some nice pipeline with the acquisition. But with opportunity comes responsibility and so we've got to build that pipeline up and really get out in front of customers and find some opportunities that we can not only try to finish for this second half so we can hit all of our financial metrics, but really build pipeline for FY21, for us which starts in April. >> So the voice of the customer is, really can be really powerful. We've heard from a number of Commvault customers on our program yesterday, today on main stage. Is there a plan, Wigs, from your perspective, to get customers into some sort of data so that you have proof in the pudding to show those large enterprises and those theaters to help build that pipeline. Look at someone who's been an existing Commvault customer for five, 10 years or so, here's the, I don't want to say migration path, but maybe upgrade path to expand footprint in there. Here's how we did it, here's why this was ideal for this customer. Plans to get those early adopters to help you dial up the pipeline? >> So have you been reading my 'Go to market strategy' (laughing) 'cause you kind of you basically just read it. So yes, listen we are inheriting some nice accounts with Hedvig. They have some nice logos out there which is really good. And it's a good foundation for us to build upon. But we're very fortunate in that our core sellers have some really good relationships with some pretty large customers really in all different industries. And so, what we're doing right now is we're trying to identify probably about 10 accounts that make sense. That are really strong partners. They don't have to necessarily be really big customers, but just really strong partners that want to work together with us. And exactly what you just said, let's get in front of them, let's give them an opportunity to play with the technology and have them help us figure out, we think we have a pretty good idea what the go-to-marketing messaging should be for our existing customer base but certainly don't assume that we know everything. So have them help us build that strategy. So that is absolutely the plan. >> We've been hearing a lot about the last couple of days, of just, the openness of Commvault. Whether it's, I really thought it was cool with Metallic that the telemetry that partners can get to help customers, maybe even before a customer knows of an issue or an opportunity, but this telemetry, this 'let's learn from our customers,' couldn't agree as a marketer with you more about, we might think we have a great tagline, great messaging, but it's the users who need to validate that. What I'm hearing a lot over the last day and a half is how receptive Commvault is. We're listening to our customers, whether it's existing and comeback customers that Sanjay's team are dealing with, or even through partners. That message is loud and clear, and that's pretty important. >> Yeah, I couldn't agree more. And I'll be honest with you, what's it's also been able to give us an opportunity to do is where we've had some relationships, quite frankly, that maybe we need to work a little harder on. Hedvig has given us that opportunity to kind of start those conversations as well. I think there's a lot of value, both on the existing opportunities as well as growing the business overall. >> Guys, nothing short of a lot of work ahead. But, pretty exciting stuff. We thank you both. Wigs, welcome again to Commvault. >> Thank you. >> Can't wait for next year. Going to bring some cool customers on the program. >> Yeah, absolutely. >> Looking forward. The buzz is so amazing this year. So many customers have said, "I know you weren't here last year, but wow," and that's what they've said. I can't wait to see what this is going to be like next year. Thank you for having us on here. >> You've got to come back. >> Absolutely we will. >> Yeah? >> Yeah. >> All right, guys, thank you for joining Stu and I. >> Thank you both very much. >> Thank you. >> For Stu Miniman, I am Lisa Martin, and you're watching theCUBE from Commvault Go '19. (upbeat electronic music)

>> Live from Stanford University. It's the Cube covering global Women in Data Science conference brought to you by Silicon Angle media. >> Welcome back to the key. We air live at Stanford University for the fourth annual Women in Data Science Conference. The Cube has had the pleasure of being here all four years on I'm welcoming Back to the Cube, one of our distinguished alumni Janet George, the fellow chief data officer, scientists, big data and cognitive computing at Western Digital. Janet, it's great to see you. Thank you. Thank you so much. So I mentioned yes. Fourth, Annie will women in data science. And it's been, I think I met you here a couple of years ago, and we look at the impact. It had a chance to speak with Margo Garrett's in a about an hour ago, one of the co founders of Woods saying, We're expecting twenty thousand people to be engaging today with the Livestream. There are wigs events in one hundred and fifty locations this year, fifty plus countries expecting about one hundred thousand people to engage the attention. The focus that they have on data science and the opportunities that it has is really palpable. Tell us a little bit about Western Digital's continued sponsorship and what makes this important to you? >> So Western distal has recently transformed itself as a company, and we are a data driven company, so we are very much data infrastructure company, and I think that this momentum off A is phenomenal. It's just it's a foundational shift in the way we do business, and this foundational shift is just gaining tremendous momentum. Businesses are realizing that they're going to be in two categories the have and have not. And in order to be in the half category, you have started to embrace a You've got to start to embrace data. You've got to start to embrace scale and you've got to be in the transformation process. You have to transform yourself to put yourself in a competitive position. And that's why Vest Initial is here, where the leaders in storage worldwide and we'd like to be at the heart of their data is. >> So how has Western Digital transform? Because if we look at the evolution of a I and I know you're give you're on a panel tan, you're also giving a breakout on deep learning. But some of the importance it's not just the technical expertise. There's other really important skills. Communication, collaboration, empathy. How has Western digital transformed to really, I guess, maybe transform the human capital to be able to really become broad enough to be ableto tow harness. Aye, aye, for good. >> So we're not just a company that focuses on business for a We're doing a number of initiatives One of the initiatives were doing is a I for good, and we're doing data for good. This is related to working with the U. N. We've been focusing on trying to figure out how climate change the data that impacts climate change, collecting data and providing infrastructure to store massive amounts of species data in the environment that we've never actually collected before. So climate change is a huge area for us. Education is a huge area for us. Diversity is a huge area for us. We're using all of these areas as launching pad for data for good and trying to use data to better mankind and use a eye to better mankind. >> One of the things that is going on at this year's with second annual data fun. And when you talk about data for good, I think this year's Predictive Analytics Challenge was to look at satellite imagery to train the model to evaluate which images air likely tohave oil palm plantations. And we know that there's a tremendous social impact that palm oil and oil palm plantations in that can can impact, such as I think in Borneo and eighty percent reduction in the Oregon ten population. So it's interesting that they're also taking this opportunity to look at data for good. And how can they look at predictive Analytics to understand how to reduce deforestation like you talked about climate and the impact in the potential that a I and data for good have is astronomical? >> That's right. We could not build predictive models. We didn't have the data to put predictive boats predictive models. Now we have the data to put put out massively predictive models that can help us understand what change would look like twenty five years from now and then take corrective action. So we know carbon emissions are causing very significant damage to our environment. And there's something we can do about it. Data is helping us do that. We have the infrastructure, economies of scale. We can build massive platforms that can store this data, and then we can. Alan, it's the state at scale. We have enough technology now to adapt to our ecosystem, to look at disappearing grillers, you know, to look at disappearing insects, to look at just equal system that be living, how, how the ecosystem is going to survive and be better in the next ten years. There's a >> tremendous amount of power that data for good has, when often times whether the Cube is that technology conferences or events like this. The word trust issues yes, a lot in some pretty significant ways. And we often hear that data is not just the life blood of an organization, whether it's in just industry or academia. To have that trust is essential without it. That's right. No, go. >> That's right. So the data we have to be able to be discriminated. That's where the trust comes into factor, right? Because you can create a very good eh? I'm odder, or you can create a bad air more so a lot depends on who is creating the modern. The authorship of the model the creator of the modern is pretty significant to what the model actually does. Now we're getting a lot of this new area ofthe eyes coming in, which is the adversarial neural networks. And these areas are really just springing up because it can be creators to stop and block bad that's being done in the world next. So, for example, if you have malicious attacks on your website or hear militias, data collection on that data is being used against you. These adversarial networks and had built the trust in the data and in the so that is a whole new effort that has started in the latest world, which is >> critical because you mentioned everybody. I think, regardless of what generation you're in that's on. The planet today is aware of cybersecurity issues, whether it's H vac systems with DDOS attacks or it's ah baby boomer, who was part of the fifty million Facebook users whose data was used without their knowledge. It's becoming, I won't say accepted, but very much commonplace, Yes, so training the A I to be used for good is one thing. But I'm curious in terms of the potential that individuals have. What are your thoughts on some of these practices or concepts that we're hearing about data scientists taking something like a Hippocratic oath to start owning accountability for the data that they're working with. I'm just curious. What's >> more, I have a strong opinion on this because I think that data scientists are hugely responsible for what they are creating. We need a diversity of data scientists to have multiple models that are completely divorce, and we have to be very responsible when we start to create. Creators are by default, have to be responsible for their creation. Now where we get into tricky areas off, then you are the human auto or the creator ofthe Anay I model. And now the marshal has self created because it a self learned who owns the patent, who owns the copyright to those when I becomes the creator and whether it's malicious or non malicious right. And that's also ownership for the data scientist. So the group of people that are responsible for creating the environment, creating the morals the question comes into how do we protect the authors, the uses, the producers and the new creators off the original piece of art? Because at the end of the day, when you think about algorithms and I, it's just art its creation and you can use the creation for good or bad. And as the creation recreates itself like a learning on its own with massive amounts of data after an original data scientist has created the model well, how we how to be a confident. So that's a very interesting area that we haven't even touched upon because now the laws have to change. Policies have to change, but we can't stop innovation. Innovation has to go, and at the same time we have to be responsible about what we innovate >> and where do you think we are? Is a society in terms of catching As you mentioned, we can't. We have to continue innovation. Where are we A society and society and starting to understand the different principles of practices that have to be implemented in order for proper management of data, too. Enable innovation to continue at the pace that it needs. >> June. I would say that UK and other countries that kind of better than us, US is still catching up. But we're having great conversations. This is very important, right? We're debating the issues. We're coming together as a community. We're having so many discussions with experts. I'm sitting in so many panels contributing as an Aye aye expert in what we're creating. What? We see its scale when we deploy an aye aye, modern in production. What have we seen as the longevity of that? A marker in a business setting in a non business setting. How does the I perform and were now able to see sustained performance of the model? So let's say you deploy and am are in production. You're able inform yourself watching the sustained performance of that a model and how it is behaving, how it is learning how it's growing, what is its track record. And this knowledge is to come back and be part of discussions and part of being informed so we can change the regulations and be prepared for where this is going. Otherwise will be surprised. And I think that we have started a lot of discussions. The community's air coming together. The experts are coming together. So this is very good news. >> Theologian is's there? The moment of Edward is building. These conversations are happening. >> Yes, and policy makers are actively participating. This is very good for us because we don't want innovators to innovate without the participation of policymakers. We want the policymakers hand in hand with the innovators to lead the charter. So we have the checks and balances in place, and we feel safe because safety is so important. We need psychological safety for anything we do even to have a conversation. We need psychological safety. So imagine having a >> I >> systems run our lives without having that psychological safety. That's bad news for all of us, right? And so we really need to focus on the trust. And we need to focus on our ability to trust the data or a right to help us trust the data or surface the issues that are causing the trust. >> Janet, what a pleasure to have you back on the Cube. I wish we had more time to keep talking, but it's I can't wait till we talk to you next year because what you guys are doing and also your pact, true passion for data science for trust and a I for good is palpable. So thank you so much for carving out some time to stop by the program. Thank you. It's my pleasure. We want to thank you for watching the Cuba and Lisa Martin live at Stanford for the fourth annual Women in Data Science conference. We back after a short break.

>> Live from Stanford University. It's the Cube covering Global Women and Data Science Conference brought to you by Silicon Angle media. >> Welcome back to the Cubes Coverage of the fourth annual Women in Data Science Conference. This global winds event is the fourth annual our fourth year here, covering it for the Cuban Lisa Martin, joined by Gianluca Pecorino, the director on the Stanford Institute for Computational and Mathematical Engineering. Gianluca, it's a pleasure to have you on the program. Thank you. So the Institute for Computational and Mathematical Engineering. I see M e. Tell us a little bit about that and its involvement in wins. >> Yes, so the status has. Bean was funded fifteen years ago at Stanford as a really hard before computation of mathematics at Stanford. The intention was to connect computations and in general, the disciplines around campus towards using computing for evolution, for starting new ideas for pursuing new endeavors. And I think it's being extremely successful over the years in creating a number of different opportunities. Now weeds started four years ago. As you mentioned, it's part of an idea that the prior director advising me, Margo Garretson, had with few others, and I think the position of I see me at the center of campus really helped bring these events sort of across different fields and this different disciplines. And I think, has Bean extremely successful in expanding and creating a new, a completely new movement, a completely new way of off off engaging with with a large, very large community. And I think I seem, has Bean very happy to play this role? And I'm continuing to be excited about the opportunities >> you mentioned expansion and movement to things that jump out. Expansion way mentioned fourth annual on Lee started This Is three and a half years ago knew that twenty fifteen and we were had the pleasure of having Margo Garrett send one of the co founders of Woods on the Cube last year at wigs. And I loved how she actually said. Very cheeky winds really started sort of as a revenge conference for her and the co founders, looking at all of the technology, events and industry events and single a lack of diversity. But in terms of expansion, this there are one hundred fifty plus regional winds events this year in fifty plus countries. They're expecting over one hundred thousand people to engage this expansion. In this movement that you mentioned, it's palpable. Tell us about your Where's the impetus for you to be involved in the woods movement. >> Well, I think my interest in in data science and which particular is because of the role that I seem years in the education at Stanford. We obviously have a very important opportunity toe renew and remodel our curriculum and provide new opportunities for for education off the new generations and clearly starting with with the opportunity off being such an audience and reaching so many different discipline. It's a very different fields. Helps us understand exactly how to put that curriculum together. And so my focus of my interest has been mostly on making sure that I see me alliance with these new directions. And when we establish the institute, computational mathematics didn't really not have data is a very, very critical component, but we are adjusting to that clearly is becoming more and more important. We want to make sure we are ready for it, and we make sure that the students through our curriculum are ready for the world out there. >> So let's talk about this. The students and the curriculum. You've been a professor at Stanford for a very long time before we get into the specifics of today's curriculum. Tell me a little bit about how you have seen that evolve over time as we know that. You know, we're sort of in terms of where the involvement and women and technology and stump field words in the eighties and how that's dropped off. Tell me a little bit about the evolution in that curriculum that you've seen and where the ice Amy is today with that adaptation. >> Yes, certainly. The evolution has bean very quick. In the last few years, we have seen, um in a number of opportunity emerging because of the technology that is out there. The fact that certainly for data science, both the software and the artwork and the technology, the methodology, the algorithms are all in the open so that there is no real barrier into sort of getting started. And I think that helps everybody sort of getting excited about the idea and the opportunity very, very quickly. So we don't really need to goto an extensive curriculum to be ableto ready, solve problems and have an impact. And I think that, perhaps is one one other reason why we are sort of in a level playing field right. Everything is is available to everybody with relatively minor investment at the beginning. And so I think that certainly a difference with respect what the disciplines, where instead, it was much more laborious process to go through before you can actually start having an impact. Suffering every o opportunity, toe change world to toe come, you know, sort of your your vision's sort of impact in the world. So I think that's That's definitely something that the data science and the recent development into the science have created. And so I think, in terms of our role, sort of continuing role in this is tow Pet Shop six. You know, expand the view ofthe data. Science is not just the algorithm, the technology, the statistical learning that you need to accomplish. A student is a new comet into the field, but also is other other elements. And I would say certainly the challenges that we are that are opposed to data. Since they are challenges that have to do with the attics with privacy on DSO, these are clear, clearly difficult to handle because they require knowledge across disciplines the typical air not related to stem in In a traditional sense. But then, on the other hand, I think is the opportunity to be really creative. Data is not analyzing on its own right. He needs the input are sort of help in creating a story. And I think that's that's another element that he makes data science a little bit different. Another stem disciplines intend to be much more ascetic, much more sort of a cold if you like. I think >> that's where the things to you that I find really interesting is if you look at all the statistical and computational skills as you mentioned, that a good data scientist needs to have as we look at some of the challenges with the amount of data being created. So you mentioned privacy, ethics, cybersecurity issues. The create creative element is key for the analysis. Other things, too. That interest me, and I'd love to get your thoughts on how you see this being developed on the curriculum. Helping is is empathy, collaboration, communication skills. Where is that in the curriculum and how important you are? Those other skills to the hard skills >> that that's That's a great question. And I think where is in the curriculum? I think we're lagging behind that. This is one of the opportunities that we have to actually connect to our other places on campus, where instead the education is built much more closely around some of these topics is that you mentioned. So I think you know, again, I the real advantage in the real opportunity we have is that the data science in general reaches out to all these different disciplines in a very, very new way if you like. I think it's it's probably one of the reasons why so attractive toe younger generation is the fact that it's not just the art skills. You do need to have a lot off understanding of the technology, the foundational statistics and mathematics and so on. But it's much more than that. Communication is very important. Teamwork is extremely important. Transparency is very important. There are there are really all these elements that do not really make that they really didn't have a place in some of the more traditional dissidents. And I think that that's definitely a great way off. Sort of refreshing are way off, even considering education and curriculum. >> When you talk to some like the next to the younger generations. Is that one of the things that they find are they pleasantly surprised, knowing that I need to actually be pretty well rounded to me? A successful data scientists? It's how I analyzed the data. How I tell a story, is that something that you still find that excites but surprises this younger generation of well, that >> certainly is a component, very important component of the excitement of the sea. Are there the fact that you can really build the story, tell a story, communicated story and oven, in fact, immediately, quickly, I think is a is something that the newer generation really see it assess a great opportunity and, you know, and it tried to me. So I mean, it has been very difficult for more traditional disciplines to have the same level of impact, partly because the communities tend to be very close, very limited with with a lot of scrutiny. I think what we have in India, the scientists, that is really a lot off you no can do attitude the lot off, Really. You know, creative force that is >> behind, you know, >> basically this movement, but in general data science, I think that >> you write. The impacts is so potent and we've seen it and we're seeing it in every industry across the globe. But it's such an exciting time with Gianluca. We thank you so much for sharing some of your time on the program this morning and look forward to hearing more great things that the ice Amy is helping with prospective women in Stem over the next year. >> Absolutely. Thank you very much. >> My pleasure. We want to thank you. You're watching the Cube live from the fourth annual Women and Data Science Conference here at Stanford University. I'm Lisa Martin. Stick around. My next guest will join me in just a moment.