(upbeat techno music) >> Live from Las Vegas. Its theCUBE, covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World 2019 here in Sin City Nevada. I'm your host Rebecca Knight, along with my co-host John Furrier. We have two guests for this segment: we have Pinkrose Hamilton, she is the VP Business Intelligence at Hackensack Meridian Health. Thanks for coming on the show. >> Thank you for having me. >> And we have Andy Crago, he is the Managing Consultant at Infoverity, thanks so much Andy. >> Thanks for having me. >> So tell us a little bit about this partnership between Hackensack and Infoverity. >> Well we were looking for an implementation partner, we were looking for the skills to come in and help us really implement MDM specifically, we're also implementing a few other technologies that we can probably speak about, but that's how we got connected. >> So tell us a little bit about what life was like before MDM. What were sort of the obstacles, the challenges that you were wrestling with? >> So Hackensack Meridian Health is the largest health system in New Jersey, and we are a very fast-growing, we like to consider ourselves disruptive, health industry in New Jersey, and so because of that we were growing and acquiring mergers acquisitions, and many different EMRs, many different physician credentialing systems were involved in this so we had to make a decision of do we wait 'til we're all on one system, which we all know will never happen, or never happen in time sometimes, so we decided to do the MDM approach which makes the most sense to us. >> One of the things that's interesting we talked, we go to hundreds of events, we talk to a lot of experts and practitioners, and everyone buys into cloud at some level, cloud natives, certainly born in the cloud, great benefits. Data's critical because in SAS, data's great if you have it because you can feed machine learning, you can take more risks, be agile, and more risk more reward. And the apps, it's all good, right? On the enterprise side, on premises, legacy kind of kicks in. If data can't feed machine learning or can't feed the app, AI really can't be enabled. This becomes a key challenge in the industry. How do you guys look at that? Because as you lay out, it's not a simple answer go to the cloud, just do on prem, you got to think about architecture. What do you guys doing with regards to where the data's stored, how do you think about it, what's some advice, best practice can you share? >> Well, I consider data storage being more like a house you're living in, right? So we buy our starter homes and we start our families. And then we outgrow this house, and then we have to say okay, I need a bigger house and we start growing. And so data's run pretty much the same way. We start outgrowing our on prem houses, and so now we're moving out, and we're moving to bigger and better things, which is cloud. And so I think hybrid is where we start, right? We can't start with okay, everybody move out and move into this new house, it's let's go build this new house somewhere else, let's test it out and see if we like it. So that's my thought process around it. >> So you've got the addition, that's got to work with all the plumbing, right? >> Right! >> So it's the same thing And then you got more track homes, and you got electronic cars that go in between. >> Exactly. >> Automation. So this is more of a systems view? >> Yes. Take care of the operational piece. >> Absolutely. >> Then think about developer angle, what's that, how does that architecture look? >> So in terms of what we're trying to do right now, I mean, it has to be kind of short-term vision with kind of a larger scale architecture, so you know as Pink was saying in terms of the hybrid architecture, if we are able to develop reusable cleanse functions such as the address doctor funtionality, we're were reaching out to a third party service, bringing in more enriched information, we have that in an on prem model right now. But in the future, that configuration and work will easily transition into that cloud architecture, so we're trying to keep our eye on the future and make sure that things are reusable as we move forward. >> And how do you two work together? I mean, this is such an interest, in this age of co-opetition, you're not necessarily competitors of course, but how do you work together to come up with the right solutions? What does that look like, the partnership? >> Well, we totally hate each other. >> That's right. (laughs) >> It's the first we've talked in a while. >> No, the partnership, I think, we hit it off right from the beginning. It was just a matter of you know, when we acquire new technologies and that decision of how much time and effort is it going to take for me to train my team and to identify the right folks on my team and what work am I going to take away from them in order to give them this additional work and this learning curve that needs to go into place. So I think we have to augment our teams with experts like Infoverity to come in and say, this is how this tool functions, and sometimes we bring in the technologies and we kind of just crack it open, but we don't really get the full use of it to understand exactly every bell and whistle we can take advantage of, and these guys are the experts that help us do that. >> And it's always a challenge, I mean, I think data's been center of the version for many many years, it's kind of mainstream now, and you can't look at the headlines these days without hearing one year anniversary of GDPR, privacy, so there's always been that risk management compliance stuff that's been around, certainly you guys know that. But everyday there's a new thing. Oh, you've got cloud, you got georegions, you're in this country, you're in that country. So as more regulatory things creep up, who knows, maybe blockchain's out there. So again, all these things are circling around complexity, which constrains data, not necessarily frees it so much. Well maybe build software. Do how does Informatica and customer deal with this, because I'd imagine you have to build an extraction layer, has to be some tooling around it, monitoring. >> Yeah. >> What's your take on this complexity? >> So in terms of an architecture perspective, we consolidate all of the different silos of patient data into a centralized repository. Historically, you would build a lot of point to point feeds based on a certain application. We built some custom work and we ship them off some data. But really what we want to do is be able to master once and publish to a canonical model that's more self-service and hub and spoke so as consumers and customers of the data need to come and get it, they can come to a centralized place, we can augment what data's available there, and kind of scale that with the architecture across real time capabilities, cloud, and other use cases that we come across. >> Do you feel good, data's frictionless, it's out there, it's addressable. >> In terms of the vision that we're on? So I mean, it's a couple steps at a time. But in terms of; >> It's that addition to the house. The journey and set of tools that we have, that's definitely where we're going, so. >> I want to ask you about the skills gap. One of the things that has emerged is that in the healthcare industry, it is much more evolved in the sense of there's an understanding of how to work with data. And perhaps because you've just always worked with more data than say a retail company or a consumer products company. So first of all, how big a problem is this for Hackensack Meridian Health? Is it as bad as the headlines suggest? And also what are you doing to combat it? >> So our main goal is to take care of the patient, right? So when a patient is introduced to our system, we want to be able to take care of that patient and their family members in the best possible way that we can. So if we're working with a very disparate organization, where we're on multiple EMRs specifically, it's hard for us to identify that episode of care for that patient. So the MDM piece particularly, with the patient domain allows us to do that. It allows us to view the entire episode of care for that patient, to see you went to these doctor's offices, you had these things done, you went to this lab, you had these tests done, you went to the hospital, you had this procedure, and this is what your follow-up looked like. So from a; and we're also conscious of the patient's expense in all of this as well as you know what's the provider's expense, what's the payer's expense, so you want to make it cost-effective. You want to make it accessible so that are there services that a certain zip code or patient population needs that we're not providing? That we can provide? And so this is the whole entire continuity of care. To take care of our patients the best way we can. >> My daughter just graduated college this week in Cal, the first ever data analysis college class, inaugural class so it shows how early it is. Cal's a great school, been doing data for a while. Data's a huge opportunity. Whether it's women in tech, new service area comes up. You don't need to be a hardcore programmer to get into the data business. But there's certain patterns we're seeing emerge, that you don't have to have a certain degree, because the jobs that are open, there's no degree for. There's only the first class has graduated from Berkeley. So I got to ask you for the folks in high school, or parents out there or anyone looking to reskill, what specific foundational and/or advanced skill sets should people be looking at if they really want to get into data? It could be anything. So I'd love to get your take on what you think those skills are for people out there that they want to learn something new and ride the wave. >> I'll start a little bit. I think a lot of people get really technical with data, but I think you really have to understand data within business contexts. I mean, if you're looking at a physician record, understanding the type of physician, maybe where the care was administered. You have to really think about okay, what am I trying to solve, what pain point am I looking at. So it's not about relational databases and writing sequel, you really have to understand the functional purpose of data within the business problem that you're considering. >> So machine learning's hot, the nerds go there, the geeks go there, but there's a bigger picture than just coding. >> Exactly. There's a whole data strategy that you need to consider and kind of plug and play as you go along and really understanding the data within the business context is key. >> I'm so glad you asked that question, because I'm going to give a different viewpoint from this. I have a daughter who's a junior in high school, and she's preparing her career path, and so she wants to follow mom's career path and wants to do data science, so it's very exciting for me, you know? I'm actually a role model, which you never expect your children to think of you as one. >> Congratulations. >> But yeah, she picked up a few sequel classes early on in high school. And I think that the underlining foundation of coding is probably a little bit important to get that piece of it, because when you're leading the function, and definitely knowing the business knowledge. When we start any project, we go in and we start with discovery, right? What is it that you do, how do you do it, what are your workflows, what do they look like? So that's definitely key. But adding in that technical piece makes you that perfect data science human that I would look for as an employer. >> It's certainly evolving. There's no one yet playbook, 'cause there's so many diverse opportunities to take in from visualization to ethics to coding to business value, unbelievable. >> Yeah. >> Great. Well Pink and Andy thank you both so much for coming on the show. >> Thank you so much for having me. >> Lots of great advice for newly minted graduates! >> That's right >> Yes. >> Thank you. >> I'm Rebecca Knight, for John Furrier, you are watching theCUBE. (upbeat techno music).

>> Announcer: Live from Las Vegas, it's theCUBE! Covering HPE Discover 2017. Brought to you by Hewlett-Packard Enterprise. (electronic music) >> Welcome back everyone. We're here live in Las Vegas. This is SiliconANGLE Media's theCUBE. Coverage of HPE Discover 2017. That's Hewlett-Packard Enterprise. I'm John Furrier, the co-host of theCUBE. My co-host for the next three days, Dave Vellante, Chief analyst at Wikibon and co-founder with me of theCUBE. Our next guest is Partha Narasimhan, who's the CTO of Aruba, now part of HP for multiple years. Welcome to theCUBE, thanks for joining us. >> Thank you. Thanks for having me here. >> So chief technology officer of Aruba, we get to go under the hood a little bit, but it's really important the we kind of have that context because the wireless is beyond just wifi. I mean, wifi is joked on the internet as the lower level of the Maslow's hierarchy of needs. I mean, it's the biggest complaint people have. 'Where's the wifi? Is it secure?' So wifi obviously in wireless, certainly brings that digital life. Now you take wireless in an enterprise environment, unlimited possibilities with Internet of Things, campus, intelligent edge was the key part of this theme. Welcome to theCUBE and thanks for joining us. >> Narasimhan: Thank you. >> So your thoughts on the intelligent edge, what is Aruba's real innovation happening now? Where's the fruit coming off the trees, beyond just the access to wireless, because we all know is like, freedom. >> Right, and so think of it. People tend to think of wireless as just okay, getting rid of the cables. And yes, it does that, but it does a lot more than getting rid of the cables. And if you think about what it allows you to do, wireless enables mobility, right? So as people walk around and stay connected to all the things that they need connectivity to, we allow that to happen. But wireless enabling mobility also means that we have now the ability to observe things in the physical world that people reside in, right? Kinds of things that they interact with, whether it's in the workplace as part of their work, or whether it's as a customer when you enter a retail store, or when you enter a stadium or a venue for an event. How do we now gather our understanding of context from purely from a digital domain? Combine that with what we are learning about context, the other side of context from the physical domain. Blend that together, one, to either create new experiences for enthusers. Or to enhance existing ones that they're already used to, how can we make it work better? Right, and we have these used cases in- >> Is it true enabling technology and these new scenarios are new? I want to get into the used case, but I first want to get the hard news out of the way. You guys have some announcements here at HPE Discover that are notable. One is an extension to the course, which is 8400 line, real focus on the intelligent edge. And the other one is really comprehensive asset tracking. Assets could be anything, it could be people, it could be machines, devices and whatnot. This really kind of highlights the things that are possible. Obviously asset tracking is entering a change, and it's also big data, it's Internet of Things. Talk about this intelligent edge, talk about the switches and the asset tracking. What is the notable things about those two announcements? >> So let's start with the 8400, right it's a big core of new classes, Abdication switch. We don't have many of those built over the years in the industry, right? There have been very small number of instances of switches like this built in here. But the big difference with the 8400 is it's actually the first one that was completely built in an era that is defined increasingly by mobility in IoT, right? Think of mobility. With mobility, topology is never a constant. Right, I can never assume that the network topology is set and it never changes. Or changes can be controlled in some perspectives. So if you start with the given that topology is not a constant, how do we now create a switch that enables network administrators to deploy networks without having to worry about, you know, old methods of configuring and monitoring the switches, right? So, this was built ground up with the notion that it has to support today's use cases, not overlay today's use cases onto, you know a switch that might have worked many years ago. So programmability was important, modernality was important. It is built on a basic premise that you know, the entire state of the network, the switch, is stored in a database that is accessible through modern interfaces. It allows you to take that switch, plug it into existing workflows that are more modern than to try and force feed these modern workflows be constrained by technologies that were invented fifteen, twenty years ago. So that is the one that's important, right? And in addition to all of the connectivity options, the speeds and feeds that we have to go build, it's extremely interesting and there are advances and innovation on that side. The one that excites me the most is the software layer in the switch, right, that allows for the programmability, it allows for visibility, right, I'm able to get access to all of the state of the switch, and any trouble, problems that I see, I can quickly get to the bottom of, and go back and fix it. But more importantly, the biggest innovation that I think we have, is this thing that we call the Network Analytics Engine. This is what gives you the extensibility property for the switch. Where your ability to go extend the capabilities of the switch in the field, right? Not have to for our engineers to tell what features, but people in the field, either customers or our own field engineers, can extend the capabilities of the switch to go do things that we didn't think of, but exist in the field. >> So before we get to asset tracking, I love the way this press release was worded. You kind of hit on it, John. 'Setting it apart from other core aggregation switches in the market, the 8400's most unique innovation is the Aruba OSCX, a modern software foundation that is a departure from today's static, inflexible operating systems.' I'm not sure exactly who you're talking about there, but nonetheless, so when you talk about this network analytics engine, Are you suggesting that makers of static inflexible operating system designs would have to bolt something like that on? And it would just not be as effective? Or would it not be possible? >> Well you have to go deeper into the operating system, and do major surgery for that to happen. And that is very hard to do. So if you already built it for a certain static use case, and you're trying to now introduce support on certain things in there, you will always be limited by what lies underneath, compared to if you look at the operating system Aruba OSCX, it was built from the ground up with the modalality and extensibility in mind including the programmability for configuring the switches. This is not something that you can bolt on later and go fix it, because you have to go very deep into the operating system, and there's a lot of major surgery work that is for a switch of this magnitude and size, the effort is as good as starting from scratch, throwing everything away and starting from scratch and building it new. That is very hard to do. >> And tell us about the asset tracking. Let's not, I didn't want to lose that either. >> Well the asset tracking, before we get that point. Operating systems are generally about connecting things, subsystems. You mentioned the wireless as an unpredictable. Which is true, I agree with that. Now Internet of Things is even more unpredictable, and the rate of devices connecting: a watch on someone's wrist, a wearable, a phone. We saw the new Apple announcements yesterday, we covered that on SiliconANGLE.com, again more and more consumer devices, and yet, industrial equipment. This is important, I mean, it's not just machinery, it's like, it could be the air conditioning, it could be anything. Thoughts on this asset tracking concept? >> Narasimhan: I'll start the IoT's side, and how it applies to the network, and get to the asset tracking. Let me start with an example. One of our university customers, in adding to the story, right, they said one day the facilities people called and said hey, we just went out and swapped out about 400 door locks in a residence hall with wifi enabled door locks, and then they turn on the 400 of them and they don't work, and the network people are saying sure it doesn't work, we're not surprised, because the network's not built to have arbitrary things come in and start working. But if you look at it from the people that are deploying this equipment, they just think hey, it's wifi, it should just connect and work, right? Versus people running the network have certain ways in which they have configured the network either for quality of service, or security, that, you have to understand. But the network admins are also in a state where they just say that battle is probably lost. People are going to add things to my environment and my job is to go make sure that I gracefully accept them in and fit the into a profile. In the security profile that I already have. So this is why the programmability is key, right? As door locks come in, chances are those door locks don't need to communicate with everything on the network. Maybe only to a very specific server that pushes policy on which keys should open a particular door, and which one's shouldn't, but if you look at network's specifically designed with a certain notion of trust, saying okay, I have a security perimeter. Whether it's a physical perimeter that allows me entry into the building, or a digital perimeter that, you know, I have a dmz in a firewall, but once you're on the inside, you're in a safe zone. That safe zone is being challenged by IoT, right? Because these devices are not capable to begin with. Think of an electronic door lock, and compare it with many other servers, and the compute capabilities and the servers on the showfloor, versus what is available in the door lock. By itself, it's starting out at a very huge disadvantage on that front. But more importantly, the compute capabilities of a door lock are frozen in time. And they tend to stay on the door for ten years, fifteen years, twenty years. Versus the compute capabilities that are available to an attacker keeps pace with technology. So over time, the ability for the door lock to protect itself diminishes, right? And this is not just true of door locks, it's true of any of these IoT type of things that are getting added to the systems. So our goal is as we gracefully accept them and get them connected to the network and provide the network guys with the tools to kind of segment them into appropriate boundaries, we also have a need to go monitor their activity all the time. Because they become juicy targets for hackers. To get into and from there, propagate out to the rest of the network. So how do we know they're not getting attacked? Their vulnerability is not getting exploited, and the only way to do this is to continuously monitor them. But more importantly, to use a machine learning approach. A behavioral approach, rather than a signature based detection. So if I baseline behaviors of a certain IoT device, whether it's a door lock or a security camera, or any number of those, and whenever I see deviations from that baseline behavior, I want to alert somebody. Because, while it is an anomaly, and not all anomalies are malicious, but it could be potentially. And you need somebody to look at it, so how do we quickly detect that, okay, there's a deviation and is it malicious, and how do we react to it, and how do we shut it down? >> Now talk about the asset tracking announcement, because that's relevant to this show. What's the status, the news? What's the notable thing about the Aruba asset tracking? >> So the asset tracking is interesting on two counts: one is, when you want to track an asset, you need to attach a tag to it, that kind of puts out some notion of identity that I can attach to that asset. But there's also the infrastructure side of it, you need an infrastructure that picks up on these signals, and can locate the asset, and can figure out where all it's been, and who's kind of used it, and how it's getting used. So while we look at asset tags as one improvement, the infrastructure is also another improvement. Aruba we started down the bluetooth low energy as one of the elements for our location based services strategy, look at Meridian team as a central gravity for all location based services. We started out with beacons, and using the beacons as an indication of location, and then providing contextual information and semantic information about that location. But over time we've also recognized that in addition to beacons, we've integrated bluetooth into our access point. So any wireless LAN infrastructure that's based off of the Aruba solution that is getting deployed today is already ready for one half of the asset tracking solution, so the other half is the tags that we're introducing that can be attached to high value assets, and then together these two combine with a back end solution that not only provides you with where the assets are and where they've been, but also uses APIs to integrate with other asset tracking larger solutions that you might have. >> Furrier: So you're feeding data into a bigger picture on the edge? Alright, so let's talk about the fun stuff now. So we can get under the hood there. Getting a little technical, which is great. There's some real sexy deployments out that you guys have been involved in. One is, we've talked about, the folks watching theCUBE know, Levi Stadium in San Francisco, for the San Francisco 49ers is highly instrumented venue next is the provider, great service provider. You guys are the provider there. But it's interesting, this other use case. So talk about how the use cases are driving the value, and how people who are discovering these new value creation opportunities, how do they get there and give us some examples. >> So Levi Stadium, okay. We tend to talk about it a lot, but it also is because we learnt a lot of things as part of being, you know, we were fortunate to be part of that exercise. We learnt a lot of things, so one key learning was the people that built the stadium were very clear from the beginning, their competition was not another sporting venue, right? It's not the Oakland Raiders fans that they wanted to attract over into the stadium. They were very clear their competition was a TV in your living room. How do I convince a fan to not watch the game on the TV in their living room but instead to come into the stadium and watch it? So they said here's a list of experiences that I want to create for the fan that you can only have in the stadium, and that is compelling enough to get a fan into the stadium to watch the game. So once you define those, then it becomes a lot easier. The rest of it underlying here is all technology, and we know how to piece it together. So this was one of the first instances where we saw the whole infrastructure build out being driven top down, right? You define your experiences and then you work your way down on what kind of pieces of technology we need to go in there. Otherwise the networking industry was largely driven by hey, here's the connectivity infrastructure, and we'll figure what hooks are available, and then we'll figure out what you can do with it. >> Furrier: You constrain, naturally, with that. >> Correct, but if you start from the top, lot's of things become easier, right, what we need can be customized to go address the problem, specific problems if we want to go in there. And this is not something new. As you look at, yes it was true for the stadium, but retail stores have a similar problem, right, how do I convince a user to not buy a particular item online, and instead come into the store to do it? And Apple's done a pretty good job of it, the whole store is not a place where you go pick items off of the shelf, put it in your cart, and check it out. It is a place where you go and interact with the item. >> Experience! >> Experience, again. >> What other verticals are hot right now, obviously retail makes sense, sports makes sense, what other verticals- >> Narasimhan: Hospitality is another one where you want to create an experience that customers associate with a brand. If I can somehow make the whole process of you checking into a hotel room, and being in the hotel room and then checking out, if that whole experience can be made significantly better, then I'm going to associate it with that brand. And the next time I'm looking for a hotel- >> So it's an opportunity for brands to extend their brand value, digitally. >> Narasimhan: Correct. It is by creating a better experience in the physical world, you tie it to your brand, and customers associate it with it. And then you go into the workplace. Again, employees and how do I help improve their productivity with what kind of experiences? More and more workplaces are shifting to more open environments, all wireless workplace, because, you know, even if I had wires, there's nothing that I can plug into. I have three devices with me in my bag. Nothing with an Ethernet port in it. And we recently moved into a new facility in Santa Clarita. in January of this year, and the one thing you'll notice is that there are no wires running to where people sit. So when you go into an all wireless workplace, you convince users that it's viable, right, and the way to convince users it's viable is that the network is always there when they need it, when they need to do something on it. But the facilities people are also excited by the possibility, because it gives them a lot of flexibility in how they want to reconfigure space. >> Furrier: It's the future of work and the future of play kind of converging with analog and digital kind of coming together with experiences at the center, and wireless is the fabric for it all. >> Correct, and wireless is what enables mobility but more importantly location is the other fabric that interconnects the two worlds. If I can sense location on the digital side, location is an attribute of the physical world. That's what bridges the two together. >> Context, interest, location. These are all new variables, a whole new way of doing things. In fact, the modern mobility we suggest on SiliconANGLE, Wikibon and theCUBE is this is going to be the future of work, the future of play, all around modern mobility. >> Narasimhan: Correct. >> Partha, thanks so much for sharing your insights. The CTO here of Aruba Wireless, doing some amazing things, enabling new possibilities here in a new simplified, sounds complex to me, but it sounds like you simplifying, as the new message from HP. Thanks for sharing your insights. Of course, we're bringing that modern day to you here on theCUBE live in Las Vegas, our exclusive coverage for three days. This is theCUBE, I'm John Furrier, Dave Vellante, we'll be right back with more after this short break. (electronic music)

(upbeat music) >> From Phoenix Arizona, theCUBE. At Catalyst Conference, here is your host, Jeff Frick. (upbeat music) >> Hi welcome back everybody, Jeff Frick here with theCUBE. We are in Phoenix Arizona at the Girls in Tech Catalyst Conference. It's the fourth year they've had the conference, we're really excited to be here, it's our first time to visit, but we wanted to come down and check it out, about 400 people. We'll be back in the Bay Area next year with about 600 people. A three day show, and really doing good work. So we're excited for our next guest, Meg Withgott, the Co-Founder and CTO of Panafold, welcome. >> Thanks, glad to be here. >> Absolutely, so you mentioned before we got started, this was your first time at the Catalyst Conference, what are your impressions? >> Yes I've heard about it, but I always thought I was too busy, but I spoke and I'm so glad I, you know, to attend, to know about it. And next year it'll be in San Francisco. >> That's right. >> So, my backyard. >> So you're speech was on women, let me see if I can get this right; 122nd meridian west to the 58th meridian, so first off, where are those meridians? (laughs) >> So that forms a great circle around the globe, it goes through Silicon Valley; first I was going to talk about women in Silicon Valley, but then someone said, "Well why don't you branch out". And I said, "Well how, there's, "how do I narrow it down?" >> Right. >> And so I picked this circle around the world. >> Right, and then you said you had this project where you went and interviewed people and asked them, "What advice would you give your younger self?" What a fantastic idea; so how did that work out, where did you go, how many people did you interview? >> It worked out really well. I talked with around 20, and a dozen or so are there in the tape. I didn't know what would happen, you know, if it would be all over the map so to speak. >> Right. >> But there's seven themes that emerged; how to find joy when you're doing something hard, and the theme that really emerged was being open. Being open to, opening your heart, being open to life's friction. People went really deep, it was kind of surprising. >> And on these seven themes; so there was joy, there was being open, what were some of the other ones? >> Challenge, conflict; it wasn't surprising but kind of sad, stereotyping. Openness was the biggest theme though. People literally used that word, open, time and again. And I edited all the footage, and so it just stuck out. >> Right. >> It was interesting. >> And it was, was it advice to be more open? >> Mm-hmm. >> To get the other things, like joy and success, I mean is that kind of the, kind of a foundational kind of point of view if you will, or a kind of way of looking at the world that enables some of these other things? >> It was, and to being open to listening to your colleagues, and to viewing them not as kind of a finished product and categorizing them, but as someone who's learning. >> Right. >> Each person I interviewed had a slightly different perspective on what it means to be open, but they all went there. >> They all went there. And what was the biggest surprise that came out of that process? Besides the obvious one where you had kind of these seven feelings. >> It was being introduced to amazing people through strangers on LinkedIn. Because, you know, I know tons of people in California; but in Iran, Yemen, and Madagascar. Madagascar was the big surprise. >> Why? >> Getting to be in touch with people, like from famous music groups there. >> Okay. >> So I've never been to Madagascar, I want to go now. >> Did you go, you didn't go do the interview there? >> No, no. >> Rats. >> No, I mean I should have. No, the footage was really gritty, it was over Skype and that's how it was. >> So it's interesting you've mentioned a couple times you're from California, you know a lot of people in California, you were thinking about starting on California; but then people said, "You know "why don't you take it to a broader sphere". So with that context, you know, we're from the Bay Area, we've got Austin Boston too, but we're from the Bay Area, and there's kind of a Silicon Valley centric kind of point of view that people like and get wrapped up into. So do you see any big, distinguishing differences between, kind of what you expect, or what you know kind of in California versus some of these international things, or were there really not that much differences after all? >> Not really, as soon as you peel off the layer, what we talk about regarding technology, it was, the same themes emerged, all over the world. >> Interesting. I want to shift gears a little bit, and talk about academics. So you've been visiting fellow at Stanford, I forgot, I've got it all written down, a whole bunch of everything. Harvard, all these great schools; Barnard College. So you've got an academic kind of point of view. I'm curious to get your take on how women's issues, and specifically women's issues in technology are changing or being grabbed on to by some of these academic institutions to try to implement some change. >> Yeah, that's a really interesting topic. For instance, the precedent of Barnard College is looking forward in an interesting way. As I'm sure you know, it's a well known liberal arts college in New York, associated with Columbia University. They don't have a computer science major. So they're going to work on that, because some of the faculty I think probably thought that, "Why do you need computer science, "we're teaching something." >> Still today? >> Still today. And so, you know, where we live we think, "What"? And we scratch our heads, and at Stanford for instance, it's a really popular major. So it was a surprise to me to hear that people thought that way. At Sweet Briar, Barnard, a lot of these other colleges. They're now starting to see, "Well yeah, it is, "it is an academic study, it's not like repairing motors". >> Right, right. Well it's even a language, right? 'Cause I would even say in high school, when will CS be right there next to Biology, Chemistry, and Physics on just kind of your standard track? >> And there's evidence that if you study; I have a linguistics background as it turns out, if you study multiple languages, you'll do better at learning computer science early on too. So we think of it as something, if you're good at math you'll be got at CS; well actually if you're good at language you have an advantage as well. >> Right, yeah cause it's basically a language, right? It's basically writing, there's lots of ways you can solve the same problem, and it's really creative writing exercises. >> Well and logic. >> Right. >> And language if you look at it is logic plus emotion. >> And then what about at the high school level? Are you seeing anything at the high school level that's being done? It's tough for high school teachers, right? Especially public schools, it's tough. A lot of things being thrown at 'em. What are they doing, how can they better equip their kids, and girls specifically? >> Yeah, that's a really good question. What I see, I mean, there's some great programs; robotics in particular, it seems like kids gravitate to that. But you know, I'm working more closely with college students; for instance, Cal State Monterey Bay, they started a CS department and so, you know, first generation kids who's families have never been to college are taking computer science, and within three years, they're ready to go in the work force. It's a revelation to their parents, it's really inspiring. >> Yeah, that's great cause there's certainly a shortage of the skills, there's huge opportunities. All right, so we're running low on time, I want to give you the last word. What are you working on for the next six months, are you going to continue to work on your advice project, you got another project in the wings, what are you working on? >> Panafold is what's near and dear to me, and so it connects to the talk I gave though, because it's all about a learning journey. What the women had in common along with being open was they could step back and see their careers as a learning journey, and that gave them a lot of strength. So at Panafold, we're enabling people to share their experience with the web as a learning journey, so mostly it's for people who need to educate their clients. >> Okay. >> So we're giving them tools for that. >> All right, well check that out, that's at panafold.com? >> Yes. >> All right, super. Well Meg, thanks for taking a few minutes and stopping by. >> Nice meeting you. >> Absolutely, so I'm Jeff Frick, we are at the Women's, or excuse me, Girls In Tech Catalyst Conference in Phoenix Arizona, you're watching theCUBE. 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