>> Announcer: Live, from Las vegas, it's theCUBE! Covering Informatica World 2018. Brought to you by Informatica. >> Hey, welcome back everyone to theCUBE, live here in Las Vegas at The Venetian. I'm John Furrier the co-host of theCUBE, we're here at Informatica Word 2018 with Peter Burris, analyst at Wikibon, and SiliconANGLE, and theCUBE, our next guest is Dave Green, Senior Director of IT Informatics, Genomic Health, welcome to theCUBE! >> Thank you, great to be here. >> You guys are doin' a ton of data so, we want to get into it, very cool, obviously, a lot of testing, lot of proprietary work, you know, this is where the power of data can come in. But first before we get into it, just take a quick minute to describe the company, what you do there, and what the mission is. >> Absolutely yep. So I work for Genomic Health, the company was founded in the year 2000, and it was founded on the premise, there was a lot of science and technology around the areas of genetic testing, but it hadn't been applied to the world of cancer, and cancer specifically. So we launched the first product on the market in 2004, and it's focused on breast cancer, based in the US. And the job the company has is to really help physicians sit down with their patient, and inform the treatment decision that the physician and patient have to make together. So the situation is, let's use breast cancer again, if a woman's been diagnosed with breast cancer, they'll often go for a biopsy, the cancer cells are actually extracted form the body. We get a sample of those in our lab, we run trough a lot of diagnostic testing, and based upon a lot of clinical research, evidence, and studies we've done over the years, it's a lot of data there in itself. We can help predict the likelihood of recurrence of cancer, over five years, 10 years, based upon different types of treatment options. And we basically, even though we do diagnostic testing, we're really an information provider, an information company, that's the we see ourselves. The idea is to sit down, have the physician sit down with the patient, we deliver a report at the end of the day. So all this testing, all the data crunching, everything we do, ends up with a relatively simple report, there's a risk curve, and based upon that, different types of treatment options make sense for the patient. So if maybe a woman decided do I need chemotherapy yes or no well chemotherapy's incredibly expensive from a healthcare economics perspective, it's incredibly invasive in terms of side-effects, you know, people know about hair loss, but there's a ton of other really, really detrimental side effects too. So if there's no clinical benefit from going through chemotherapy, we can help inform that decision, right? Give the patient confidence that they know it's the right thing to do, and I'm on a certain side of a risk curve, or there may be better options. Drug therapies these days, every single day, there's a new drug comin' on the market to combat certain types of cancer in some way. So that's our job, that's the gist of what we do. >> So what do you do with the data, so what's the strategic initiatives around data? Obviously data is key to this, 'cause you need to analyze data but, just give us an order of magnitude, a taste or a sample of some of the things that you're doing with data. >> Right, so I mean, we're growing as a company, it's a growing space, so far as, there's more and more people throughout the world with cancer every day, we're growing internationally too. So we have data that we receive from all over the world. In terms of some of the key initiatives we have underway. So we're doing a lot more in the space of partnering, we're built up a commercial infrastructure over the course of years. And that commercial infrastructure goes with the IT infrastructure that matches to it. So we're using that commercial channel to really expand, the number of tests we're able to bring to market, and we do that by partnering with smaller labs. They're not able to build the same infrastructure themselves so we can use all of the capabilities that we've built up, we bring them into our ecosystem and extend the reach that we have to bring in other types of product tests. So we look at things like data, one of the initiatives we have right now is it's very difficult space to operate, right? Healthcare is incredibly complex, from a data perspective, it's messy, there are people involved, there's humans involved, literally we're all unique, we're all individual. The job we have, and in many of these cases, where we bring in third-party labs as well, is to take care of all of the processing of the commercial, and clinical related information we need to get from patients. We need to move through, and make sure we get the right information the first time through. And we use that information, then, to trigger the rest of the testing process. It's both clinical, it's business, it's related to healthcare insurance providers, government mandated information we have to collect as well, we've got to bring all these different facets together. >> You've got to a lot of moving parts and dynamics, what's the relationship with Informatica? As a customer, you're using which product? Could you just take a minute to explain? >> Yep, absolutely, yeah, so we're a customer. The couple main products we use, so, we use their master data management product, it's very important for us, that we know and recognize the right physician, right? The physicianal link to the patient, we've got to get that right, We've got to have accurate information, >> John: That's a big one. >> That's a big one, yeah. >> And we use that for the older information we get in, and we also use it for the billing site too, so ultimately we get paid, 'cause we want to reinvest in our patients, we want to put them through more of our tests, that's one angle, so incredibly important for us. >> John: It's a critical component to the business model. >> It's, yeah, absolutely, it's mission critical. If we get that wrong, forget the rest of the tests, forget the science, the technology, all of the cool stuff we do, it's a basic fundamental thing we have to get right. >> Well, you didn't just blow a campaign, you blew a life. >> Yeah! Or at least we're slowing down, getting the right information, the actual information, >> John: That'll ruin your reputation, I mean, everything, dominoes will just fall. >> It's incredible important for us to get right, that's still one thing we've got from Informatica. The other thing we've partnered with them from, is where we, we look at the integrations between the default applications that we have. We have some data that we have to process on-premise, we have a laboratory information system, that's real-time, critical processing, it's interfacing with robots in a lab, and things like this, so that's got to interface with the likes of Salesforce, which is our CRM, which is where we receive all of your information, and where we clinical information from the physician on behalf of the patient. These things have to connect together, the data has to integrate, we have to make sense of it, we have to logically know, what information is flowing through what business process throughout the company, and we use Informatica to be able to do that as well. >> Peter: Well healthcare is at the vanguard of so many things, it's the vanguard of ethics, because of the role that people play. It's at the vanguard of big data, it was one of the first clear, you know, broadly understood, the drive to understand the genome was fundamentally a big data problem, and people said, wow, I didn't realize we could do that with data! It's also at the vanguard of understanding the relationship between analog and digital and the fact that, this is all an analog experience that has to be turned into a digital experience, so we can do things with it. You must watch much of what's going on around here and say, yeah, we've gone through that, what kind of advice and counsel can you give to folks who are perhaps just entering into new ways of thinking about using data, new ways of applying data, new ways of understanding that relation between analog and digital. How would you advise your peers to think differently? >> Yeah, so one of the things I've certainly noted, in walking around and talking to some of my peers at Informatica World this week was just, a bit of some of the frustration actually, from the technical side. And that becomes, because they see the technical solutions, they see the data and the opportunity, but what we've not done, in many cases, with this technology is be able to explain that to the business people that we're working with, and establishing that business partnership. So I think, been patient, looking to educate, looking for quick wins, opportunities to show what data can do, how transformative, you know, data can be in terms of, how business people work every single day. The connection I've certainly seen in my company, no different, it's somewhat ironic that we, we have this treasure trove of clinical information that we've built up over time. We've not been looking at our business, the way we run our business the same way. So, in some ways we've been able to, to, well we do it in this area, the clinical space, let's replicate that and transform, bring it through to the business side too. >> Evidence-based business management. >> Exactly right, yeah. So I think being persistent, looking for the ability to educate, looking for quick wins, and looking to use the technology to show what's possible, help lead the way, and be consistent and patient on that journey. And it's a journey, it's not a one project, it's not a I just bring in a tool, life is good, it has to be much more than that. So that's what I've learned, at least, what I've seen so far today, this week. >> Dave, thanks for taking the time to come on theCUBE and share your story. >> Sure thing. >> Genomic Health, great work, growing international, they got data challenges, they're solving them, and they're getting, they have to get 'em right, and this is, we're hearing more of this. Great story, thank you for coming on. >> Dave: Appreciate it, thank you. >> I'm John Furrier, Peter Burris, here for day two of coverage of Informatica World, stay with us, we'll be back after this break. (bubbly music)

>> Narrator: From around the globe, it's theCUBE, covering the Upgrade 2020, the NTT Research Summit presented by NTT Research. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in Palo Alto studio for our ongoing coverage of the Upgrade 2020, it's the NTT Research conference. It's our first year covering the event, it's actually the first year for the event inaugural, a year for the events, we're really, really excited to get into this. It's basic research that drives a whole lot of innovation, and we're really excited to have our next guest. He is Kazuhiro Gomi, he is the President and CEO of NTT Research. Kazu, great to see you. >> Hi, good to see you. >> Yeah, so let's jump into it. So this event, like many events was originally scheduled I think for March at Berkeley, clearly COVID came along and you guys had to make some changes. I wonder if you can just share a little bit about your thinking in terms of having this event, getting this great information out, but having to do it in a digital way and kind of rethinking the conference strategy. >> Sure, yeah. So NTT Research, we started our operations about a year ago, July, 2019. and I always wanted to show the world that to give a update of what we have done in the areas of basic and fundamental research. So we plan to do that in March, as you mentioned, however, that the rest of it to some extent history, we needed to cancel the event and then decided to do this time of the year through virtual. Something we learned, however, not everything is bad, by doing this virtual we can certainly reach out to so many peoples around the globe at the same time. So we're taking, I think, trying to get the best out of it. >> Right, right, so you've got a terrific lineup. So let's jump into a little bit. So first thing just about NTT Research, we're all familiar, if you've been around for a little while about Bell Labs, we're fortunate to have Xerox PARC up the street here in Palo Alto, these are kind of famous institutions doing basic research. People probably aren't as familiar at least in the states around NTT basic research. But when you think about real bottom line basic research and how it contributes ultimately, it gets into products, and solutions, and health care, and all kinds of places. How should people think about basic research and its role in ultimately coming to market in products, and services, and all different things. But you're getting way down into the weeds into the really, really basic hardcore technology. >> Sure, yeah, so let me just from my perspective, define the basic research versus some other research and development. For us that the basic research means that we don't necessarily have any like a product roadmap or commercialization roadmap, we just want to look at the fundamental core technology of all things. And from the timescale perspective obviously, not that we're not looking at something new, thing, next year, next six months, that kind of thing. We are looking at five years or sometimes longer than that, potentially 10 years down the road. But you mentioned about the Bell Lab and Xerox PARC. Yeah, well, they used to be such organizations in the United States, however, well, arguably those days have kind of gone, but so that's what's going on in the United States. In Japan, NTT has have done quite a bit of basic research over the years. And so we wanted to, I think because that a lot of the cases that we can talk about the end of the Moore's laws and then the, we are kind of scary time for that. The energy consumptions on ITs We need to make some huge, big, fundamental change has to happen to sustain our long-term development of the ideas and basically for the sake of human beings. >> Right, right. >> So NTT sees that and also we've been doing quite a bit of basic research in Japan. So we recognize this is a time that the let's expand this activities and then by doing, as a part of doing so is open up the research lab in Silicon Valley, where certainly we can really work better, work easier to with that the global talents in this field. So that's how we started this endeavor, like I said, last year. And so far, it's a tremendous progress that we have made, so that's where we are. >> That's great, so just a little bit more specific. So you guys are broken down into three labs as I understand, you've got the Physics, the PHI, which is Physics and Informatics, the CIS lab Cryptography and Information Security, and the MEI lab Medical and Health Informatics, and the conference has really laid out along those same tracks, really day one is a whole lot of stuff, or excuse me, they do to run the Physics and Informatics day. The next day is really Cryptography and Information Security, and then the Medical and Health Informatics. So those are super interesting but very diverse kind of buckets of fundamental research. And you guys are attacking all three of those pillars. >> Yup, so day one, general session, is that we cover the whole, all the topics. And but just that whole general topics. I think some people, those who want to understand what NTT research is all about, joining day one will be a great day to be, to understand more holistic what we are doing. However, given the type of research topic that we are tackling, we need the deep dive conversations, very specific to each topic by the specialist and the experts in each field. Therefore we have a day two, three, and four for a specific topics that we're going to talk about. So that's a configuration of this conference. >> Right, right, and I love. I just have to read a few of the session breakout titles 'cause I think they're just amazing and I always love learning new vocabulary words. Coherent nonlinear dynamics and combinatorial optimization language multipliers, indistinguishability obfuscation from well-founded assumptions, fully deniable communications and computation. I mean, a brief history of the quasi-adaptive NIZKs, which I don't even know what that stands for. (Gomi laughing) Really some interesting topics. But the other thing that jumps out when you go through the sessions is the representation of universities and really the topflight university. So you've got people coming from MIT, CalTech, Stanford, Notre Dame, Michigan, the list goes on and on. Talk to us about the role of academic institutions and how NTT works in conjunction with academic institutions, and how at this basic research level kind of the commercial academic interests align and come together, and work together to really move this basic research down the road. >> Sure, so the working with academic, especially at the top-notch universities are crucial for us. Obviously, that's where the experts in each field of the basic research doing their super activities and we definitely need to get connected, and then we need to accelerate our activities and together with the entities researchers. So that has been kind of one of the number one priority for us to jumpstart and get some going. So as you mentioned, Jeff, that we have a lineup of professors and researchers from each top-notch universities joining to this event and talking at a generous, looking at different sessions. So I'm sure that those who are listening in to those sessions, you will learn well what's going on from the NTT's mind or NTT researchers mind to tackle each problem. But at the same time you will get to hear that top level researchers and professors in each field. So I believe this is going to be a kind of unique, certainly session that to understand what's it's like in a research field of quantum computing, encryptions, and then medical informatics of the world. >> Right. >> So that's, I am sure it's going to be a pretty great lineups. >> Oh, absolutely, a lot of information exchange. And I'm not going to ask you to pick your favorite child 'cause that would be unfair, but what I am going to do is I noticed too that you also write for the Forbes Technology Council members. So you're publishing on Forbes, and one of the articles that you publish relatively recently was about biological digital twins. And this is a topic that I'm really interested in. We used to do a lot of stuff with GE and there was always a lot of conversation about digital twins, for turbines, and motors, and kind of all this big, heavy industrial equipment so that you could get ahead of the curve in terms of anticipating maintenance and basically kind of run simulations of its lifetime. Need concept, now, and that's applied to people in biology, whether that's your heart or maybe it's a bigger system, your cardiovascular system, or the person as a whole. I mean, that just opens up so much interesting opportunities in terms of modeling people and being able to run simulations. If they do things different, I would presume, eat different, walk a little bit more, exercise a little bit more. And you wrote about it, I wonder if you could share kind of your excitement about the potential for digital twins in the medical space. >> Sure, so I think that the benefit is very clear for a lot of people, I would hope that the ones, basically, the computer system can simulate or emulate your own body, not just a generic human body, it's the body for Kazu Gomi at the age of whatever. (Jeff laughing) And so if you get that precise simulation of your body you can do a lot of things. Oh, you, meaning I think a medical professional can do a lot of thing. You can predict what's going to happen to my body in the next year, six months, whatever. Or if I'm feeling sick or whatever the reasons and then the doctor wants to prescribe a few different medicines, but you can really test it out a different kind of medicines, not to you, but to the twin, medical twin then obviously is safer to do some kind of specific medicines or whatever. So anyway, those are the kind of visions that we have. And I have to admit that there's a lot of things, technically we have to overcome, and it will take a lot of years to get there. But I think it's a pretty good goal to define, so we said we did it and I talked with a couple of different experts and I am definitely more convinced that this is a very nice goal to set. However, well, just talking about the goal, just talking about those kinds of futuristic thing, you may just end up with a science fiction. So we need to be more specific, so we have the very researchers are breaking down into different pieces, how to get there, again, it's going to be a pretty long journey, but we're starting from that, they're try to get the digital twin for the cardiovascular system, so basically the create your own heart. Again, the important part is that this model of my heart is very similar to your heart, Jeff, but it's not identical it is somehow different. >> Right, right. >> So we are looking on it and there are certainly some, we're not the only one thinking something like this, there are definitely like-minded researchers in the world. So we are gathered together with those folks and then come up with the exchanging the ideas and coming up with that, the plans, and ideas, that's where we are. But like you said, this is really a exciting goal and exciting project. >> Right, and I like the fact that you consistently in all the background material that I picked up preparing for this today, this focus on tech for good and tech for helping the human species do better down the road. In another topic, in other blog post, you talked about and specifically what are 15 amazing technologies contributing to the greater good and you highlighted cryptography. So there's a lot of interesting conversations around encryption and depending kind of commercialization of quantum computing and how that can break all the existing kind of encryption. And there's going to be this whole renaissance in cryptography, why did you pick that amongst the entire pallet of technologies you can pick from, what's special about cryptography for helping people in the future? >> Okay, so encryption, I think most of the people, just when you hear the study of the encryption, you may think what the goal of these researchers or researches, you may think that you want to make your encryption more robust and more difficult to break. That you can probably imagine that's the type of research that we are doing. >> Jeff: Right. >> And yes, yes, we are doing that, but that's not the only direction that we are working on. Our researchers are working on different kinds of encryptions and basically encryptions controls that you can just reveal, say part of the data being encrypted, or depending upon that kind of attribute of whoever has the key, the information being revealed are slightly different. Those kinds of encryption, well, it's kind of hard to explain verbally, but functional encryption they call is becoming a reality. And I believe those inherit data itself has that protection mechanism, and also controlling who has access to the information is one of the keys to address the current status. Current status, what I mean by that is, that they're more connected world we are going to have, and more information are created through IOT and all that kind of stuff, more sensors out there, I think. So it is great on the one side that we can do a lot of things, but at the same time there's a tons of concerns from the perspective of privacy, and securities, and stuff, and then how to make those things happen together while addressing the concern and the leverage or the benefit you can create super complex accessing systems. But those things, I hate to say that there are some inherently bringing in some vulnerabilities and break at some point, which we don't want to see. >> Right. >> So I think having those securities and privacy mechanism in that the file itself is I think that one of the key to address those issues, again, get the benefit of that they're connected in this, and then while maintaining the privacy and security for the future. >> Right. >> So and then that's, in the end will be the better for everyone and a better society. So I couldn't pick other (Gomi and Jeff laughing) technology but I felt like this is easier for me to explain to a lot of people. So that's mainly the reasons that I went back launching. >> Well, you keep publishing, so I'm sure you'll work your way through most of the technologies over a period of time, but it's really good to hear there's a lot of talk about security not enough about privacy. There's usually the regs and the compliance laws lag, what's kind of happening in the marketplace. So it's good to hear that's really a piece of the conversation because without the privacy the other stuff is not as attractive. And we're seeing all types of issues that are coming up and the regs are catching up. So privacy is a super important piece. But the other thing that is so neat is to be exposed not being an academic, not being in this basic research every day, but have the opportunity to really hear at this level of detail, the amount of work that's being done by big brain smart people to move these basic technologies along, we deal often in kind of higher level applications versus the stuff that's really going on under the cover. So really a great opportunity to learn more and hear from, and probably understand some, understand not all about some of these great, kind of baseline technologies, really good stuff. >> Yup. >> Yeah, so thank-you for inviting us for the first one. And we'll be excited to sit in on some sessions and I'm going to learn. What's that one phrase that I got to learn? The N-I-K-Z-T. NIZKs. (laughs) >> NIZKs. (laughs) >> Yeah, NIZKs, the brief history of quasi-adaptive NI. >> Oh, all right, yeah, yeah. (Gomi and Jeff laughing) >> All right, Kazuhiro, I give you the final word- >> You will find out, yeah. >> You've been working on this thing for over a year, I'm sure you're excited to finally kind of let it out to the world, I wonder if you have any final thoughts you want to share before we send people back off to their sessions. >> Well, let's see, I'm sure if you're watching this video, you are almost there for that actual summit. It's about to start and so hope you enjoy the summit and in a physical, well, I mentioned about the benefit of this virtual, we can reach out to many people, but obviously there's also a flip side of the coin as well. With a physical, we can get more spontaneous conversations and more in-depth discussion, certainly we can do it, perhaps not today. It's more difficult to do it, but yeah, I encourage you to, I think I encouraged my researchers NTT side as well to basic communicate with all of you potentially and hopefully then to have more in-depth, meaningful conversations just starting from here. So just feel comfortable, perhaps just feel comfortable to reach out to me and then all the other NTT folks. And then now, also that the researchers from other organizations, I'm sure they're looking for this type of interactions moving forward as well, yeah. >> Terrific, well, thank-you for that open invitation and you heard it everybody, reach out, and touch base, and communicate, and engage. And it's not quite the same as being physical in the halls, but that you can talk to a whole lot more people. So Kazu, again, thanks for inviting us. Congratulations on the event and really glad to be here covering it. >> Yeah, thank-you very much, Jeff, appreciate it. >> All right, thank-you. He's Kazu, I'm Jeff, we are at the Upgrade 2020, the NTT Research Summit. Thanks for watching, we'll see you next time. (upbeat music)

(upbeat music) >> Live, from Las Vegas it's theCUBE. Covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World 2019. I'm your host Rebecca Knight along with my co-host John Furrier. We are joined by Adam Mariano, he is the Vice-President Health Informatics at HighPoint Solutions. Thanks for coming on theCUBE! >> Thank you for having me. >> So tell our viewers a little bit about HighPoint Solutions, what the company does and what you do there. >> Sure, HighPoint is a consulting firm in the Healthcare and Life Sciences spaces. If it's data and it moves we probably can assist with it. We do a lot of data management, we implement the full Infomatica stack. We've been an Infomatica partner for about 13 years, we were their North American partner of the year last year. We're part of a much larger organization, IQVIA, which is a merger of IMS quintiles, large data asset holder, big clinical research organization. So we're very much steeped in the healthcare data space. >> And what do you do there as Vice President of Health and Formatics? >> I'm in an interesting role. Last year I was on the road 51 weeks. So I was at over a hundred facilities, I go out and help our customers or prospective customers or just people we've met in the space, get strategic about how they're going to leverage data as a corporate asset, figure out how they're going to use it for clinical insight, how they're going to use it for operational support in payer spaces. And really think about how they're going to execute on their next strategy for big data, cloud strategy, digital re-imaginment of the health care space and the like. >> So we know that healthcare is one of the industries that has always had so much data, similar to financial services. How are the organizations that you're working with, how are they beginning to wrap their brains around this explosion of data? >> Well it's been an interesting two years, the last augur two years there isn't a single conversation that hasn't started with governance. And so it's been an interesting space for us. We're a big MDM proponent, we're a big quality proponent, and you're seeing folks come back to basics again, which is I need data quality, I need data management from a metadata perspective, I need to really get engaged from a master data management perspective, and they're really looking for integrated metadata and governance process. Healthcare's been late to the game for about five or six years behind other industries. I think now that everybody's sort of gone through meaningful use and digital transformation on some level, we're now arcing towards consumerism. Which really requires a big deep-dive in the data. >> Adam, data governance has been discussed at length in the industry, certainly recently everyone knows GDPR's one year anniversary, et cetera, et cetera. But the role of data is really critical applications for SAS and new kinds of use cases, and the term Data Provisioning as a service has been kicked around. So I'd love to get your take on what that means, what is the definition, what does it mean? Data Provisioning as a service. >> The industry's changed. We've sort of gone through that boomerang, alright, we started deep in the sort of client server, standard warehouse space. Everything was already BMS. We then, everybody moved to appliances, then everybody came back and decided Hadoop, which is now 15 year old technology, was the way to go. Now everybody's drifting to Cloud, and you're trying to figure out how am I going to provision data to all these self-service users who are now in the sort of bring your own tools space. I'd like to use Tablo, I'd like to use Click. I like SAS. People want to write code to build their own data science. How can you provision to all those people, and do so through a standard fashion with the same metadata with the same process? and there isn't a way to do that without some automation at this point. It's really just something you can't scale, without having an integrated data flow. >> And what's the benefits of data provisioning as a service? What's the impact of that, what does it enable? >> So the biggest impact is time to market. So if you think about warehousing projects, historically a six month, year-long project, I can now bring data to people in three weeks. In two days, in a couple of hours. So thinking about how I do ingestion, if you think about the Informatica stack, something like EDC using enterprise data catalog to automatically ingest data, pushing that out into IDQ for quality. Proving that along to AXON for data governance and process and then looking at enterprise data lake for actual self-service provisioning. Allowing users to go in and look at their own data assets like a store, pick things off the shelf, combine them, and then publish them to their favorite tools. That premise is going to have to show up everywhere. It's going to have to show up on AWS, and on Amazon, and on Azure. It's going to have to show up on Google, it's going to have to show up regardless of what tool you're using. And if you're going to scale data science in a real meaningful way without having to stack a bunch of people doing data munging, this is the way it's going to have to go. >> Now you are a former nurse, and you now-- >> I'm still a nurse, technically. >> You're still a nurse! >> Once a nurse, always a nurse. Don't upset the nurses. >> I've got an ear thing going on, can you help me out here? (laughter) >> So you have this really unique vantage point, in the sense that you are helping these organizations do a better job with their data, and you also have a deep understanding of what it's like to be the medical personnel on the other side, who has to really implement these changes, and these changes will really change how they get their jobs done. How would you say, how does that change the way you think about what you do? And then also what would you say are the biggest differences for the nurses that are on the floor today, in the hospital serving patients? >> I think, in America we think about healthcare we often talked about Doctors, we only talk about nurses in nursing shortages. Nurses deliver all the care. Physicians see at this point, the way that medicine is running, physicians see patients an average two to four minutes. You really think about what that translates to if you're not doing a surgery on somebody, it's enough time to talk to them about their problem, look at their chart and leave. And so nursing care is the point of care, we have a lot of opportunity to create deflection and how care is delivered. I can change quality outcomes, I can change safety problems, I can change length of stay, by impacting how long people keep IVs in after they're no longer being used. And so understanding the way nursing care is delivered, and the lack of transparency that exists with EMR systems, and analytics, there's an opportunity for us to really create an open space for nursing quality. So we're talking a lot now to chief nursing officers, who are never a target of analytics discussion. They don't necessarily have the budget to do a lot of these things, but they're the people who have the biggest point of control and change in the way care is delivered in a hospital system. >> Care is also driven by notifications and data. >> Absolutely. >> So you can't go in a hospital without hearing all kinds of beeps and things. In AI and all the things we've been hearing there's now so many signals, the question is what they pay attention to? >> Exactly. >> This becomes a really interesting thing, because you can get notifications, if everything's instrumented, this is where kind of machine learning, and understanding workflows, outcomes play a big part. This is the theme of the show. It's not just the data and coding, it's what are you looking for? What's the problem statement or what's the outcome or scenario where you want the right notification, at the right time or a resource, is the operating room open? Maybe get someone in. These kinds of new dynamics are enabled by data, what's your take on all this? >> I think you've got some interesting things going on, there's a lot of signal to noise ratio in healthcare. Everybody is trying to build an algorithm for something. Whether that's who's going to overstay their visit, who's going to be readmitted, what's the risk for somebody developing sepsis? Who's likely to follow up on a pharmacy refill for their medication? We're getting into the space where you're going to have to start to accept correlation as opposed to causation, right? We don't have time to wait around for a six month study, or a three year study where you employ 15,000 patients. I've got three years of history, I've got a current census for the last year. I want to figure out, when do I have the biggest risk for falls in a hospital unit? Low staffing, early in their career physicians and nurses? High use of psychotropic meds? There are things that, if you've been in the space, you can pretty much figure out which should go into the algorithm. And then being pragmatic about what data hospitals can actually bring in to use as part of that process. >> So what you're getting at is really domain expertise is just as valuable as coding and wrangling data, and engineering data. >> In healthcare if you don't have SMEs you're not going to get anything practical done. And so we take a lot of these solutions, as one of the interesting touch points of our organization, I think it's where we shine, is bringing that subject matter expertise into a space where pure technology is not going to get it done. It's great if you know how to do MDM. But if you don't know how to do MDM in healthcare, you're going to miss all the critical use cases. So it really - being able to engage that user base, and the SMEs and bring people like nurses to the forefront of the conversation around analytics and how data will be used to your point, which signals to pay attention to. It's critical. >> Supply chains, another big one. >> Yeah. >> Impact there? >> Well it's the new domain in MDM. It's the one that was ignored for a long time. I think people had a hard time seeing the value. It's funny I spoke at 10 o'clock today, about supply chain, that was the session that I had with Nathan Rayne from BJC. We've been helping them embark on their supply chain journey. And from all the studies you look at it's one of the easiest places to find ROI with MBM. There's an unbelievable amount of ways- >> Low hanging fruit. >> $24.5 billion in waste a year in supply chain. It's just astronomical. And it's really easy things, it's about just in time supplies, am I overstocking, am I losing critical supplies for tissue samples, that cost sometimes a $100,000, because a room has been delayed. And therefore that tissue sits out, it ends up expiring, it has to be thrown away. I'll bring up Nathan's name again, but he speaks to a use case that we talked about, which is they needed a supply at a hospital within the system, 30 miles away another hospital had that supply. The supply costs $40,000. You can only buy them in packs of six. The hospital that needed the supply was unaware that one existed in the system, they ordered a new pack of six. So you have a $240,000 price that you could have resolved with a $100 Uber ride, right? And so the reality is that supply could have been shipped, could have been used, but because that wasn't automated and because there was no awareness you couldn't leverage that. Those use cases abound. You can get into the length of stay, you can get into quality of safety, there's a lot of great places to create wins with supply chain in the MDM space. >> One of the conversations we're having a lot in theCUBE, and we're having here at Informatica World, it centers around the skills gap. And you have a interesting perspective on this, because you are also a civil rights attorney who is helping underserved people with their H1B visas. Can you talk a little bit about the visa situation, and what you're seeing particularly as it relates to the skills gap? >> We're in an odd time. We'll leave it at that. I won't make a lot of commentary. >> Yes. >> I'm a civil rights and immigration attorney, and on the immigration side I do a lot of pro bono work with primarily communities of color, but communities at risk looking to help adjust their immigration status. And what you've had is a lot of fear. And so you have, well you might have an H1B holder here, you may have somebody who's on a provisional visa, or family members, and because those family members can no longer come over, people are going home. And you're getting people who are now returning. So we're seeing a negative immigration of places like Mexico, you're seeing a lot of people take their money, and their learnings and go back to India and start companies there and work remotely. So we're seeing a big up-tick in people who are looking for staffing again. I think the last quarter or so has been a pretty big ramp-up. And I think there's going to continue to be this hole, we're going to have to find new sources of talent if we can't bring people in to do the jobs. We're still also, I think it just speaks to our STEM education the fact that we're not teaching kids. I have a 28 year old daughter who loves technology, but I can tell you, her education when she was a kid, was lacking in this technology space. I think it's really an opportunity for us to think about how do we train young people to be in the new data economy. There's certainly an opportunity there today. >> And what about the, I mean you said you were talking about your daughter's education. What would you have directed her toward? What kinds of, when you look ahead to the jobs of the future, particularly having had various careers yourself, what would you say the kids today should be studying? >> That's two questions. So my daughter, I told her do what makes you happy. But I also made her learn Sequel. >> Be happy, but learn Sequel. >> But learn sequel. >> Okay! >> And for kids today I would say look, if you have an affinity and you think you enjoy the computer space, so you think about coding, you like HTML, you like social media. There are a plethora of jobs in that space and none of them require you to be an architect. You can be a BA, you can be a quality assurance person, you can be a PM. You can do analysis work. You can do data design, you can do interface design, there's a lot of space in there. I think we often reject kids who don't go to college, or don't have that opportunity. I think there's an opportunity for us to reach down into urban centers and really think about how we make alternate pathways for kids to get into the space. I think all the academies out there, you're seeing rise, Udemy, and a of of these other places that are offering academy based programs that are three, six months long and they're placing all of their students into jobs. So I don't think that the arc that we've always chased which is you've got to come from a brand named school to get into the space, I don't think it's that important. I think what's important is can I get you the clinical skill, so that you've understood how to move data around, how to process it, how to do testing, how to do design, and then I can bring you into the space and bring you in as an entry level employee. That premise I think is not part of the American dream but it should be. >> Absolutely, looking for talent in these unexpected places. >> College is not the only in point. We're back to having I think vocational schools for the new data economy, which don't exist yet. That's an opportunity for sure. >> And you said earlier, domain expertise, in healthcare as an example, points to what we've been hearing here at the conference, is that with data understanding outcomes and value of the data actually is just as important, as standing up, wrangling data, because if you don't have the data-- >> You make a great point. The other thing I tell young people in my practice, young people I interact with, people who are new to the space is, okay I hear you want to be a data scientist. Learn the business. So if you don't know healthcare get a healthcare education. Come be on this project as a BA. I know you don't want to be a BA, that's fine. Get over it. But come be here and learn the business, learn the dialogue, learn the economy of the business, learn who the players are, learn how data moves through the space, learn what is the actual business about. What does delivering care actually look like? If you're on the payer side, what does claims processing look like from an end to end perspective? Once you understand that I can put you in any role. >> And you know digital four's new non-linear ways to learn, we've got video, I see young kids on YouTube, you can learn anything now. >> Absolutely. >> And scale up your learning at a pace and if you get stuck you can just keep getting through it no-- >> And there are free courses everywhere at this point. Google has a lot of free courses, Amazon will let you train for free on their platform. It's really an opportunity-- >> I think you're right about vocational specialism is actually a positive trend. You know look at the college University scandals these days, is it really worth it? (laughter) >> I got my nursing license through a vocational school originally. But the nursing school, they didn't have any technology at that point. >> But you're a great use case. (laughter) Excellent Adam, thank you so much for coming on theCUBE it's been a pleasure talking to you. >> Thank you. >> I'm Rebecca Knight for John Furrier. You are watching theCUBE. (techno music)