Stephanie Cox & Matthew Link, University of Indiana | Citrix Synergy 2019
>> live from Atlanta, Georgia. It's the two you covering. Citric Synergy. Atlanta 2019. Brought to You by Citrix >> Welcome back to the Cubes. Continuing coverage of Citrix Energy, 2019 from Atlanta, Georgia. I'm Lisa Martin. My co host for the event is Keith Townsend and Keith and I are excited to talk. Teo, one of the Citrix Innovation Award nominees, Indiana University, with a couple of folks from Indiana University joining us. Stephanie Cox, manager, a Virtual Platform Services and Mat Link, associate vice president of research Technologies Guys, thanks so much for joining Keith and me, Thank you. And congratulations on Indiana University being nominated for an innovation award. I was talking with Tim in hand there CMO yesterday, saying there was over a thousands nomination. So to even get down to being in the top three is pretty exciting stuff. Talk to us a little bit about Indiana University. Us. This is a a big, big organization. Lots of folks accessing the network through lots of devices. Matt, let's start with you. Give us that picture of what's going on there. Yes, so I >> u is about 130,000 students across seven campuses. We've got about 20,000 faculty and staff across those seven campuses. One of the things that makes us a little unique is were consolidated shop. So there are 1,200 of us and I you that support the entire university and all the campuses and anyone point in time, there could be 200,000 devices touching the network and using those services. >> That's a Big 70 talk. Talk to us about your virtual a footprint. How How big is the location? Data centers? What's the footprint? >> Well, we have two data centers. One of them is in Indianapolis, which is my home. It's one of our larger campus is calling Indiana University Purdue University affectionately, I U P y. There is a data center there, but our large danna center is at the flagship campus, which is in Bloomington, Indiana, >> and to support 100,000 plus people and to hundreds of any given the 2nd 200,000 devices. How have you designed that virtual infrastructure to enable access to students, faculty, etcetera and employees. >> So from the network perspective, we have several network master plans that have rolled, and we're in our 2nd 10 year next network master plan, and the network master plan is designed to continually upgrade the network. Both the physical network, the infrastructure and the wireless network in our last 10 year budget, for that was around $170,000,000 of investment just to support the network infrastructure. And then Stephanie rides on top of that as the virtual platform with Citrix to deliver the images anywhere on campus. Whether it's wirelessly or whether it's connected via network connection >> kill seven campuses is already a bit. If you ever look at a map, Indiana sits Christ map damp in the middle of the country. It's a big space. Right before we hit record, we were just talking about that. Drive off I 65 from Indianapolis to Chicago is just a lot of rules area, and I'm sure part of your mission is to make sure technology and education is the sensible thing. Everyone in Indiana talk to us about the challenges of getting connective ity and getting material virtual classrooms to those remote areas. >> Yeah, it's really one of the major strengths of our partnership with Citrix. They are really at the premiere Remote solution connectivity offering at Indiana University. So we built our citrix environment. Teo encompass everyone. We wanted to make sure we could have enough licenses and capacity for all of our 130,000 faculty, staff and students to use the service. Do they all show up at the same time? No, thank goodness. But we do offer it to everyone, which is I found in the education. You're in a very unique tin Indiana University. Another another thing to have consolidated I t. And then to be able to offer a service like ours to everyone and not just restricted to specific pockets of the university. With that, we've been able to them extend offering of any application or something that you might need for a class to any of our other remote location. So if you're a student who is working in or go, you know, lives in rule Indiana and you want Teo get in Indiana University degree, you can do that without having to travel to one of our campus sites or locations. We I have a very nice of online program, just a lot of other options that that we've really tried Teo offer for remote access. >> So Citrix has really enabled this. I think you call it the eye. You anywhere. Indiana University anywhere Program. Tell us about opening up this access to everyone over the time that you've been ascetics Customer, how many more people can you estimate have access now, that didn't hurt not too long ago. >> Yeah, I think initially, and Matt was probably no more before me before I Even before I even came on the scene, I believe that the original youth case was really just trying. Teo, extend what we were already doing on premise in what we call just our Indiana University lab supported areas. Right? So just your small, like the old days you would goto your college campus and you go into your computer lab with it. We just really wanted Teo the virtual Isar expand the access to just those specific types of APS and computers. And that was an early design. Since then, over the years, we've really kind of, you know, just really expanded. Really. We used the Citrix platform to redesign and distribute how we deliver the applications and the virtual desktops. So now not only do we service those students who would who would normally come onto the campus just to use your traditional computer lab. Wait do a lot, especially programs for other schools. Like we, we deliver a virtual desktop for our dentistry. Students may actually use that whole platform in the dental clinic to see real patients are third tier. Third year doctors do that way. Also replicated that same thing and do it in our speech and hearing sciences for our future audiologist. We have certain professors that have wanted to take a particular course that they're teaching and extended to different pockets all over the world. So we might host a class from Budapest or Africa somewhere else. You know, wherever that faculty and staff has three sources that they know they need to get to in their content already virtualized. We worked to make that happen all the time. >> That's a lot of what you just said is first of all, initially, maybe before Citrix being able to provide support in the computer labs for your maybe seven core campuses. Now you get your giving 130,000 plus individuals anywhere, anytime. Access that is the ex multiplier on that is massive, but you're also gone global It's not just online, it's you're able to enable professors to teach in other parts of the world where it was before. It was just people that were in Indiana, but master and and >> you're just limited by the network. So that's the only draw back. When you go to the rule areas way out, you're just limited by the network. You know, the initial program was really you really thought of as a cost saving measure way we're goingto put thin clients out. We wouldn't have to do life cycle replacements for desktop machines that were getting more expensive and more expensive, you know, 10 years ago, and now the way that we look at it is I you wants to provide services across the breath of the organization and make those services at no additional cost and open to everybody open access to everybody. The desktop, for example, is one of you know Stephanie is, is the brainchild behind the desktop, took three years of dedicated hard work to create an environment to support the visually impaired. >> Talk to us more about that because that was part of the video and that captured my intention immediately. What is 80 accessibility, technology, accessibility technology is inaccessible to get that. So I'm just, you know, hundreds thousands, and not just those that are sight and hearing. >> So one of the things then I think it's just a wonderful thing about working at a university. We're able to buy software licenses in a big quantity, large quantity, right? Because we have that kind of buying power software that I normally never would see or get access to, even in my private sector. Administer tricks engineer for a long time. But when you come to a university and then you're selling or you're getting licenses for 50 60 70 80,000 you get to see some of these products that you don't normally as a regular consumer. You'd like it, but you know you can't really afford it. So with that, when we started looking at all of the different applications that they could buy in a large quantity site licence, you know, the way we thought, Oh my goodness, let's virtualized these and make sure everybody gets access to them and the ones that were really attractive to us, where the ones for the visually impaired, sure they're in niche and They're very, very expensive, but we but let's just try it. We'll see how well they perform in a virtual environment. And with that, our Citrix infrastructure underneath they performed quite well. Plus, the apse have evolved a great deal over just the last four years. So we're really proud to offer our virtual desktop to our blind students. We had to work really hard to make sure that the speech recognition software was fast enough for them. It turns out that blind people listen to speech really, really, really, really, really fast, and so we had to make sure that we kept our platform while we're working on it to keep it sped an updated so that it's usable to them right since functional to me. But they really need it to be like, 10 times faster. I found that out after even shooting the award video and spending even more time with them, I thought, Why don't you guys tell me it was slow to you? But yeah, it's, uh, it's been an honor, really, Teo to be up for that award. But tow work with those students to learn more about their needs to learn more about the city different applications that people write for people with old disabilities. I hope we can do more in that space. >> So the young man in it and why I don't remember his name. >> Priscilla, Bela, Chris. So >> share just quickly about Chris's story. >> Yeah, and he watches the Cube. I hope he's listening because I >> think I think this whole >> kind of >> really put a little bit icing on the cake because you're taking an environment and urine empowering a student to do what they want to do versus what they are able or not able to do. So Christmas story is pretty cool of where he wants to go with his college career. >> Yeah, I won't say he's a big, you know, proponent, user of the virtual desktop, because he's just so advanced. He's like, way beyond everything We're learning from him. But he is Indiana University's believe. I'm saying this right, very first biomedical chemical engineer who is blind and fourth completely blind, Yes, wow and is quite a brilliant young man, and we were lucky to have him be r. He will test anything for me and and Mary Stores, who was featured in the video Chris Meyer. And he's also featured in the video. Gonna remember their names? I mean, it's a hole. I'm lucky to have a whole community of people that will Yeah, they know where we want to be there for them. We don't always get it right. What? We're gonna listen and keep trying to move forward. So >> But if you kind of think of even what a year or two ago not being able to give any of this virtualized desktop access to this visually impaired and how many people are now using it? >> Um, well, we open it up to everyone. We have hundreds and hundreds of users, but we know not everyone who uses it is blind. People like you can use it if you want it or not way. Don't really understand why some people prefer to use that one over there. The other But it does have some advantages. I mean, there there are different levels of sight impairment, too, as I've just been educated right. There are some people who are just at the very beginning of that journey of just losing their site. So we if if that happens to be, you know, someone that we can extend our environment to. It's probably better t use it now and get really familiar with that issue. Transition to losing your sight later in life. I've been told so >> So you ask a little bit about the scope of of the desktop, so I'll layer on a little bit of the scope of eye you anywhere. Last year, around 65,000 individual unique users over well over 1,000,000 Loggins and 8,000,000 and the average session time was around 41 minutes. That's so our instructors teach with it. Are clinicians treat people with it? We've built it in two. How's Elektronik protected health data? Er hit. The client's gonna be critical, writes the hip a standard because you can't say compliance anymore because you can't be compliant with a standard change. That wording several times way are very familiar with meeting hip. A standard we've been doing that for about 12 years now with where I came from was the high performance computing area of the university. So that's my background, and I >> so one thing we didn't get a chance to talk, uh, touch 12 100,000 devices were a citrus citrus is a Microsoft partner. Typically, when those companies think of 200,000 users, they think for profit. There's, you know, this is a niche use case for 200,000 users. Obviously, you guys have gotten some great pricing as part of being a educational environment. What I love to hear is kind of the research stories, because the ability to shrink the world, so to speak, you know, hi HPC you're giving access to specialized equipment to people who can't get their normally. You know, you don't have to be physically in front of GPU CPUC century. What other cool things have been coming out of the research side of the house because of the situation able? >> So this is cool. I mean, >> I get it. So >> So one of our group's research software solutions stole the idea from Stephanie to provide a research desktop. Barr >> imitation. Highest form of flattery, Stephanie. Absolutely. So what we've >> done is is is we always continually to try to reduce the barriers of entry and access? Uh, you know, supercomputing. Before you had to be this tall to ride this ride. Well, now we're down to here and with the hopes that will get down even farther. So what we've done is we've taken virtualized desktop, put it in front of the supercomputers, and now you can be wherever you want to be and have access to HPC. Untie you and that's all the systems. So we have four super computers and we have 40 petabytes of spinning disc ah, 160 petabytes of archival tape library. So we're we're a large shop and, you know, we couldn't have done it without looking at what Stephanie has done and and really looking in that model differently. Right? Because to use HPC before, you'd have to use a terminal and shell in and now, looking at you anywhere that gives you just the different opportunity to catch a different and more broad customer base. And I call on customers because we try to treat him as customers and and helps the diversity of what you're doing. So last year alone, our group research technologies supported a 151 different departments way were on 937 different grants, and we support over 330 different disciplines. Uh, it I you and so it's It's deep, but it's also very broad. First, larger campus we are. And as a large organization as we are, you know, we're fairly nimble. Even a 1,200 people. >> Wow! From what I've heard, it's no wonder that what you've done at Indiana University has garnered you the Innovation Award nominee. I can't imagine what is next. All that you have accomplished. Stephanie. Matt, thank you so much for joining Key to me. We wish you the best of luck and good a citric scott dot com Search Innovation Awards where you can vote for the three finalists. We wish you the very best of luck will be waiting with bated breath tomorrow to see who wins. >> So thank you very much. Thank you. Thank you. Keep >> our pleasure for Keith Townsend. I'm Lisa Martin. You're watching the Cube live from Citrix. Synergy 2019. Thanks for watching
SUMMARY :
It's the two you covering. So to even get down to being in the top three So there are 1,200 of us and I you that support Talk to us about your virtual a footprint. at the flagship campus, which is in Bloomington, Indiana, and to support 100,000 plus people and to So from the network perspective, we have several network master Everyone in Indiana talk to us about the challenges of getting connective of any application or something that you might need for a class to any of I think you call it the eye. sources that they know they need to get to in their content already virtualized. That's a lot of what you just said is first of all, initially, So that's the only draw back. So I'm just, you know, hundreds thousands, and not just those that are sight and hearing. the award video and spending even more time with them, I thought, Why don't you guys tell me it was slow to So Yeah, and he watches the Cube. really put a little bit icing on the cake because you're taking an environment Yeah, I won't say he's a big, you know, proponent, user of the virtual desktop, because he's just so advanced. you know, someone that we can extend our environment to. so I'll layer on a little bit of the scope of eye you anywhere. the world, so to speak, you know, hi HPC you're giving access to So this is cool. So the idea from Stephanie to provide a research desktop. So what we've that gives you just the different opportunity to catch a different and more broad customer We wish you the very best of luck will be So thank you very much. our pleasure for Keith Townsend.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Keith | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
Stephanie | PERSON | 0.99+ |
Indianapolis | LOCATION | 0.99+ |
Stephanie Cox | PERSON | 0.99+ |
Keith Townsend | PERSON | 0.99+ |
Indiana | LOCATION | 0.99+ |
Chris | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Chris Meyer | PERSON | 0.99+ |
Africa | LOCATION | 0.99+ |
Citrix | ORGANIZATION | 0.99+ |
Budapest | LOCATION | 0.99+ |
Chicago | LOCATION | 0.99+ |
Priscilla | PERSON | 0.99+ |
One | QUANTITY | 0.99+ |
200,000 devices | QUANTITY | 0.99+ |
40 petabytes | QUANTITY | 0.99+ |
Indiana University | ORGANIZATION | 0.99+ |
Matt | PERSON | 0.99+ |
Tim | PERSON | 0.99+ |
Teo | PERSON | 0.99+ |
Atlanta, Georgia | LOCATION | 0.99+ |
200,000 users | QUANTITY | 0.99+ |
Last year | DATE | 0.99+ |
160 petabytes | QUANTITY | 0.99+ |
8,000,000 | QUANTITY | 0.99+ |
Citrix Energy | ORGANIZATION | 0.99+ |
Indiana University Purdue University | ORGANIZATION | 0.99+ |
937 different grants | QUANTITY | 0.99+ |
1,200 people | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
100,000 plus people | QUANTITY | 0.99+ |
tomorrow | DATE | 0.99+ |
Bela | PERSON | 0.99+ |
2019 | DATE | 0.99+ |
First | QUANTITY | 0.99+ |
Matthew Link | PERSON | 0.99+ |
Bloomington, Indiana | LOCATION | 0.99+ |
around $170,000,000 | QUANTITY | 0.99+ |
three finalists | QUANTITY | 0.99+ |
three sources | QUANTITY | 0.99+ |
Indiana University | ORGANIZATION | 0.99+ |
Mary Stores | PERSON | 0.99+ |
three years | QUANTITY | 0.99+ |
Third year | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
seven campuses | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
10 times | QUANTITY | 0.99+ |
2nd 200,000 devices | QUANTITY | 0.99+ |
10 years ago | DATE | 0.99+ |
Atlanta | LOCATION | 0.98+ |
hundreds | QUANTITY | 0.98+ |
80 | QUANTITY | 0.98+ |
University of Indiana | ORGANIZATION | 0.98+ |
about 12 years | QUANTITY | 0.98+ |
2nd 10 year | QUANTITY | 0.98+ |
over 330 different disciplines | QUANTITY | 0.97+ |
fourth | QUANTITY | 0.97+ |
130,000 faculty | QUANTITY | 0.97+ |
two | QUANTITY | 0.97+ |
Citrix | TITLE | 0.97+ |
two data centers | QUANTITY | 0.97+ |
12 100,000 devices | QUANTITY | 0.97+ |
about 130,000 students | QUANTITY | 0.97+ |
Both | QUANTITY | 0.97+ |
around 41 minutes | QUANTITY | 0.97+ |
about 20,000 faculty | QUANTITY | 0.97+ |
Stephanie Cox & Matthew Link, Indiana University | Citrix Synergy 2019
>> Live from Atlanta, Georgia. It's theCUBE covering Citrix Synergy Atlanta 2019. Brought to you by Citrix. >> Welcome back to theCUBE's continuing coverage of Citrix Synergy 2019 from Atlanta, Georgia. I'm Lisa Martin, my co-host for the event is Keith Townsend and Keith and I are excited to talk to one of the Citrix Innovation Award nominees, Indiana University. We have a couple of folks from Indiana University joining us, Stephanie Cox, Manager of Virtual Platform Services and Matt Link, Associate Vice President of Research Technologies. Guys, thanks so much for joining Keith and me. >> Thank you Lisa. >> Thank you. >> And thank you Keith. >> It's an honor to be here, yeah. >> And congratulations on Indiana University being nominated for an innovation award. I was talking with Tim Minahan, their CMO yesterday saying there was over a thousand nominations, so to even get down to being in the top three is pretty exciting stuff. >> Yeah. >> Awesome. >> So talk to us a little bit about Indiana University. You guys, this is a big, big big organization lots of folks accessing the network through lots of devices. Matt, let's start with you, give us that picture of what's going on there. >> Yeah, so IU is about 130,000 students across seven campuses. We got about 20,000 faculty and staff across those seven campuses. One of the things that makes us a little unique is, we're a consolidated IT shop. So, there are 1200 of us at IU that support the entire university and all the campuses. And at any one point in time, there could be 200,000 devices touching the network and using those services. >> Big, that's big. >> Big. >> Wow, that is big. Stephanie talk, talk to us about your virtual imp, footprint and how big is the location. How many data centers? What's the footprint? >> Well we have two data centers, one of them is in Indianapolis which is my home. It's one of our larger campuses, we call it Indiana University Purdue University, affectionately IUPUI. There is a data center there but our larger data center is at the flagship campus which is in, Bloomington, Indiana. >> And, to support 100,000 plus people and, you said at any given second, 200,000 devices. How have you designed that Virtual Integral Structure to enable access to students, faculty, et cetera and employees? >> So from the network perspective we have several network master plans that have rolled and we're in our second 10 year network master plan. And, the network master plan is designed to continually upgrade the network, both the physical network, the infrastructure, and the wireless network. In our last 10 year budget for that was around $170 million of investment just to support the network infrastructure. And then, Stephanie rides on top of that as the Virtual Platform with Citrix to deliver the images anywhere on campus, whether it's wirelessly or whether it's connected via network connection. >> Yep. >> So seven campuses is already a bit. If you ever look at a map, Indiana sits right smack dab in the middle of the country. It's a big space, right before we hit record, we were just talking about that drive up I-65 from Indianapolis to Chicago is just, a lot of rural area and, I'm sure part of your mission is to make sure technology and education is accessible to everyone in Indiana. Talk to us about the challenges of getting connectivity and getting material, virtual classrooms to those remote areas. >> Yeah, that's really one of the major strengths of our partnership with Citrix. They are really the premier remote solution connectivity offering at Indiana University. So, we built our Citrix environment to encompass everyone. We wanted to make sure we could have enough licenses and capacity for all of our 130,000 faculty, staff, and students to use the service. Now do they all show up at the same time? No, thank goodness. >> Thankfully. >> But we do offer it to everyone which is, I found, in the education arena, very unique to Indiana University. Another thing to have the consolidated IT and then to be able to offer a service like ours to everyone and not just restrict it to separate pockets of the university. With that, we've been able to then extend, offering of any application or something that you might need for a class to any of our other remote locations. So, if you're a student who is working in or lives in rural Indiana and you want to get an Indiana University degree, you can do that without having to travel to one of our campus sites or locations. We have a very nice online program and just a lot of other options that we've really tried to offer for remote access. >> So Citrix has really enabled this, I think you call it the IUanyWare, Indiana University Anywhere Program. >> Yeah. >> Tell us about opening up this access to everyone over the time that you've been a Citrix customer how many more people can you guesstimate have access now that didn't not too long ago? >> Yeah, I think initially, and Matt would probably know more before me, before I even came on the scene, I believe that the original use case was really just trying to extend what we were already doing on premise in what we call just our Indiana University lab supported areas. Right, so just your small, like the old days when you would go to your college campus and you go into your computer lab, we just really wanted to virtualize, or expand, the access to just those specific types of apps and computers. And that was an early design, since then over the years we've really kind of, just really expanded. Really use the Citrix platform to redesign and distribute how we deliver the applications and the virtual desktops. So, now not only do we service those students who would normally come onto the campus just to use your traditional computer lab, we do a lot of specialty programs for other schools. Like we deliver a virtual desktop for our dentistry students, they actually use that whole platform in the dental clinic to see real patients our, third tier, third year doctors do that. We also replicated that same thing and do it in our speech and hearing sciences for our future audiologists. We have certain professors that have wanted to take the particular course that they're teaching and extend it to different pockets all over the world so we might host a class from Budapest or Africa somewhere else, wherever that faculty and staff has resources that they know they need to get to and their content already virtualized. We work to make that happen all the time. >> That's, a lot of what you just said is first of all, initially, maybe before Citrix being able to provide support in the computer labs for your maybe seven core campuses, now you're giving 130,000 plus individuals anywhere, anytime access. That is, the X multiplier on that is massive. But you're also gone global, it's not just online, you're able to enable professors to teach in other parts of the world, where it was before it was just people that were in Indiana. >> Right. >> That's massive. >> And you're just limited by the network. So that's the only drawback when you go to the rural areas way out, you're just limited by the network. The initial program was really, really thought of as a cost saving measure. We were going to put thin clients out, we wouldn't have to do life cycle replacements for desktop machines that were getting more expensive and more expensive 10 years ago, and now the way that we look at it is IU wants to provide services across the breadth of the organization, and make those services at no additional cost. And open to everybody. Open access to everybody, the AT desktop, for example is one of, Stephanie is, the brainchild behind the AT desktop. Took three years of dedicated hard work to create an environment to support the visually impaired. >> Talk to us more about that, because that was part of the video and that captured my attention immediately. What is AT? >> Accessibility. >> Technology. >> Technology. >> Accessibility Technology. >> Accessible, is it Accessible Technology? >> Accessible Technology. >> Yeah, I always get that wrong. (laughs) >> So, hundreds, thousands, and not just those that are sight and hearing. >> Right. >> Yeah, so one of the things that I think was, it's just a wonderful thing about working at a university, we're able to buy software licenses in a big quantity, large quantity right, because we have that kind of buying power. Software that I normally never would see or get access to even in my private sector, I've been a Citrix engineer for a long time, but when you come to a university and then you're selling or you're getting licenses for 50, 60, 70, 80,000, you get to see some of these products that you don't normally, as a regular consumer, (laughs) you like it but you know you can't really afford it. So, with that when we started looking at all of the different applications that they could buy in a large quantity site license way we thought oh my goodness, let's virtualize these and make sure everybody gets access to them. And the ones that were really attractive to us were the ones for the visually impaired. Sure they're a niche and they're very, very expensive but we thought let's just try it. We'll see how well they perform in a virtual environment and with our Citrix infrastructure underneath they performed quite well, plus the apps have evolved a great deal over just the last four years. So, we were really proud to offer our virtual desktop to our blind students. We had to work really hard to make sure that the speech recognition software was fast enough for them. It turns out that blind people listen to speech really, really, really, really, really, fast and so we had to make sure that we kept our platformer working on it, to keep it sped and updated so that it's usable to them, right. Seems functional to me, but they, it really needed to be like, 10 times faster. After I found that out, after even shooting the award video and spending even more time with them I thought, why did you guys tell me it was slow to you? But yeah it's been an honor, really, to be up for that award but to work with those students, to learn more about their needs, to learn more about the different applications that people write for people with all disabilities. I hope we can do more in that space. >> So the young man, in, at IUPUI. >> Yes. >> I don't remember his name. >> Chris Lavilla. >> Chris. >> Yes. >> So share, just quickly about Chris' story. >> If, he watches theCUBE I hope he's listening 'cause I think he's kind of remarkable. >> I think this'll really put some, a little bit of icing on that cake because you're taking an environment and you're empowering a student to do what they want to do, versus what they are able or not able to do, so Chris' story is pretty cool of where he wants to go with his college career. >> Yeah, now I won't say he a big proponent user of the virtual desktop because he's just so advanced, he's like way beyond everything. We're learning from him, but he is Indiana University's I believe I'm saying this right, very first biomedical chemical engineer who is blind since birth, completely blind, yes. >> Wow. >> He is, and he's quite a brilliant young man and we're lucky to have him be our, he will test anything for me, and Mary Stores, who's featured in the video Chris Mire, he's also featured in the video I got to remember their names, I mean, it's a whole, I'm lucky to have a whole community of people that will. Yeah, they know, we want to be there for them, we don't always get it right, but we're going to listen and keep trying to move forward, so. >> But, if you kind of think of, even a what, a year or two ago, not being able to give any of this virtualized desktop access to the visually impaired and how many people are now using it? >> Well we open it up to everyone. We have hundreds and hundreds of users but we know not everyone who uses it is blind. People can, you can use it if you want it or not. We don't really understand why some people prefer to use that one over any other but it does have some advantages, there are different levels of sight impairment too, as I've just been educated right. There are some people who are just at the very beginning of that journey of just losing their sight so, if that happens to be someone that we can extend our environment to it's probably better to use it now and get really familiar with that as you transition to losing your sight later in life, I've been told so. >> So you asked a little bit about the scope of the AT desktop, so I'll layer on a little bit of the scope of IUanyWare. Last year around 65,000 individual unique users over, well over a million logins and-- >> 1.4 million. >> 1.4 million. And the average session time was around 41 minutes. >> That's long. >> So. >> Yeah. >> Our instructors teach with it, our clinicians treat people with it, we've built it to house electronic protected health data. >> So HIPA compliance, got to be critical, right? >> It meets the HIPA standard. >> Right. >> Because you can't say compliance anymore because you can't be compliant with a standard. (Stephanie laughing) They've changed that wording several times in the course of the year. >> We know this. >> So, and we are very familiar with meeting the HIPA standard, we've been doing that for about 12 years now, with, where I came from was the high performance computing area of the university so that's my background that I. >> So, one thing we didn't get a chance touch on, 200,000 devices. We're at Citrix, Citrix is a Microsoft partner. Typically when those companies think of 200,000 users they think for profit, this is a niche use case for 200,000 users. Obviously you guys have gotten some great pricing as part of being an education environment. What I would love to hear is, kind of the research stories because the ability to shrink the world, so to speak high HPC, you're giving access to specialized equipment to people who can't get there normally, you have to be physically in front of GPUs, CPUs, et cetera. What other cool things have been coming out of the research side of the house because of the Citrix enablement? >> So, this is cool I mean. >> You got to, got to. (laughs) >> Right, so one of our groups, Researched Software and Solutions stole the idea from Stephanie to provide a research desktop. >> Borrowed. >> Borrowed. >> Imitation, highest form of flattery, Stephanie. >> That's right, absolutely. So what we've done is we always continually to try to reduce the barriers of entry and access. Supercomputing before, you had to be this tall to ride this ride, well now we're down to here. And, with the hopes that we'll go down even farther. So what we've done is we've taken a virtualized desktop, put it in front of the supercomputers, and now you can be wherever you want to be, and have access to HPC at IU. And that's all the systems, so we have four supercomputers And we have 40 petabytes of spinning disc, 160 petabytes of archival tape library so, we're a large shop. And, we couldn't have done it without looking at what Stephanie has done and really looking at that model differently, right? Because to use HPC before you'd have to use a terminal and shell in. And now, looking at IUanyWare, that gives you just the different opportunity to catch a different and more broad customer base. And I call them customers because we try treat them as customers >> Right. >> And it helps the diversity of what you're doing so last year alone our group, Research Technologies supported 151 different departments. We were on 937 different grants. And we support over 330 different disciplines at IU and so it's deep, but it's also very broad, for as large a campus we are and as large an organization as we are, we're fairly nimble even at 1200 people. >> Wow, from what I've heard it's no wonder that what you've done at Indiana University has garnered you the Innovation Award nominee. I can't imagine what is next with all that you have accomplished. Stephanie, Matt, thank you so much for joining Keith and me, we wish you the best of luck. You can go to Citrix.com, search Innovation Awards where you can vote for the three finalists. We wish you the very best of luck. We'll be waiting with bated breath tomorrow to see who wins. >> So will we, thank you very much. >> Thank you. >> Thank you Lisa. Thank you Keith. >> Our pleasure. For Keith Townsend, I'm Lisa Martin. You're watching theCUBE live from Citrix Synergy 2019. Thanks for watching. (upbeat techno music)
SUMMARY :
Brought to you by Citrix. and Keith and I are excited to talk to one of the Citrix a thousand nominations, so to even get down to being So talk to us a little bit about Indiana University. One of the things that makes us a little unique is, Stephanie talk, talk to us about your virtual imp, but our larger data center is at the flagship campus And, to support 100,000 plus people and, So from the network perspective we have Talk to us about the challenges of getting 130,000 faculty, staff, and students to use the service. and then to be able to offer a service like ours to everyone I think you call it the IUanyWare, in the dental clinic to see real patients our, third tier, That's, a lot of what you just said is and now the way that we look at it is Talk to us more about that, Yeah, I always get that wrong. that are sight and hearing. After I found that out, after even shooting the award I think he's kind of remarkable. to do what they want to do, versus what they are able of the virtual desktop because he's just so advanced, I got to remember their names, I mean, it's a whole, if that happens to be someone a little bit of the scope of IUanyWare. And the average session time was around 41 minutes. to house electronic protected health data. in the course of the year. So, and we are very familiar with meeting because the ability to shrink the world, so to speak You got to, got to. to provide a research desktop. just the different opportunity to catch a different And it helps the diversity of what you're doing we wish you the best of luck. Thank you Lisa. Thanks for watching.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
David | PERSON | 0.99+ |
Maribel | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Keith | PERSON | 0.99+ |
Equinix | ORGANIZATION | 0.99+ |
Matt Link | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Indianapolis | LOCATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Scott | PERSON | 0.99+ |
Dave Nicholson | PERSON | 0.99+ |
Tim Minahan | PERSON | 0.99+ |
Paul Gillin | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Dave | PERSON | 0.99+ |
Lisa | PERSON | 0.99+ |
Europe | LOCATION | 0.99+ |
Stephanie Cox | PERSON | 0.99+ |
Akanshka | PERSON | 0.99+ |
Budapest | LOCATION | 0.99+ |
Indiana | LOCATION | 0.99+ |
Steve Jobs | PERSON | 0.99+ |
October | DATE | 0.99+ |
India | LOCATION | 0.99+ |
Stephanie | PERSON | 0.99+ |
Nvidia | ORGANIZATION | 0.99+ |
Chris Lavilla | PERSON | 0.99+ |
2006 | DATE | 0.99+ |
Tanuja Randery | PERSON | 0.99+ |
Cuba | LOCATION | 0.99+ |
Israel | LOCATION | 0.99+ |
Keith Townsend | PERSON | 0.99+ |
Akanksha | PERSON | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
Akanksha Mehrotra | PERSON | 0.99+ |
London | LOCATION | 0.99+ |
September 2020 | DATE | 0.99+ |
Intel | ORGANIZATION | 0.99+ |
David Schmidt | PERSON | 0.99+ |
90% | QUANTITY | 0.99+ |
$45 billion | QUANTITY | 0.99+ |
October 2020 | DATE | 0.99+ |
Africa | LOCATION | 0.99+ |
Steven Hatch, Cox Automotive | Splunk .conf18
>> Live from Orlando, Florida, it's theCUBE. Covering .conf18, brought to you by Splunk. >> Welcome back to Orlando everybody, home of Disney World, and this week, home of theCUBE. I'm Dave Vellante and he's Stu Miniman. Steven Hatch is here, he's the manager of Enterprise Logging Services at Cox Automotive. Steven, thanks for coming on theCUBE. >> Thank you. >> So, you've been with Splunk for a while, we're here at conf18. Logging services, enterprise logging services. When you think of Splunk, their roots, Splunk go back to, sort of, log files, analyzing log files, it's in your title. (laughs) You must be pretty intimately tied to, as a practitioner, to this capability, but talk about your role and what you do at Cox. >> Primarily, the role is to be the evangelist, the enabler, and the center of excellence when it comes down to getting those best practices propergated within the enterprise. >> So people come to you for advice, council, you play, sort of, internal consultant. What qualified you to do that? You were a practitioner prior to this, so you got your hands dirty and you kind of now, elevated to-- >> My prior role was a Site Operations, or Site Reliability Engineer, and then Manager. And so, having that background, I've been in IT since '96, so I'm a little old in the game, but basically, having that operational knowledge, and knowing how to think big picture when things are happening or transpiring, or the reverse and go back and find that root cause analysis. >> '96, just a pup, my friend, okay? (both laugh) So, talking to Stu, we were talking off camera, about the number of brands that Cox Automotive has, Cox at Kelley Blue Book and at numerous others, like dozens, each of these is kind of it's own data silo. How do you guys go about using Splunk? Are you able to break down some of those silos? Maybe you could share that with us. >> Yeah, so we have been successful on a lot of the big three really, at Kelley Blue Book, Manheim, as well as Auto Trader, to really break in. A lot of that was because of our, already previous, relationships with team members and leaders. On the other side of the coin is the newly acquired companies that are not in Atlanta, Georgia. That are in places like Groton, Connecticut, South Jordan, Utah, Upstate New York, as well as the Toronto area in Canada. And so, WebEx joined me, email just won't cut it. You actually have to sit down with these people and really showcase your business case, your model, and what you're trying to bring to the table. But of course, the approach is always important. >> And are you using Splunk to do that? As a collaboration tool as well? >> Yes sir, yep. >> Explain that a little bit if you would. >> So, a lot of times, as you mentioned, the silos, as a bigger brand now, it's no longer an excuse for you to only be responsible for your data and not showcase it, or share that data. Because we're thinking about the entire life-cycle of Cox Automotive, and this entity of Cox Automotive, that's important to us now. So for you to hold tight, or to hoard your data, or your metrics and not share them, that's not good business anymore. >> Yeah, so Steven, we talked to a lot of companies that do M&A, and it's usually like, well, this is the products we use, these are the structures that we have. One of the things we hear from Splunk is that you can get to your data, your way. How does the Splunk modeling, and how you look at the data, fit into that M&A? Is that an enabler for you to be able to get that in. >> Yeah, and so, when you can showcase the ability of how the data comes in and, quickly. Key word, right? To showcase how that data can be very valuable to them, especially to their stakeholders, that's when light bolts will go off. And, again, it's the stakeholders, and then champions, that we need to bring to the table to make sure that we can get full adoption. >> Yeah, we've also-- Dave's been to the show a few times, it's my first time, and what I've really heard a bunch of is the people that know how to use Splunk, they're super valuable inside of the company. They get training, people inside the company, they look to get hired, tell us a little about what you've seen, what it means to your role inside the company, and as you network with your peers here. >> It's a lot of exposure. A lot of people are very anxious to get some type of insights into their world, their infrastructure, their applications, their business tools. A lot of times, there are people out there that are very savvy from a business perspective, that have a bunch of KPIs in their head, but no one has actually extracted that information from them, and so, our job is to align with their KPIs. You know, over the last couple of years, that's what we've-- the journey that we've been on, is to now revisit the data that we've just ingested. That's the basic foundation. We want to elevate now and really get more mature, and to align with those business KPIs. >> Meaning they got this tribal knowledge in their head, and you want to codify that so that it can be shared. >> Correct. >> How do you go about doing that? Is it sitting in a whiteboard and understanding that? >> It can be a whiteboard, it can be over a coffee. If I need to get on a plane and go see them in person, and to really just listen and ask the questions when it's time but, again, listen and really understand what's important to them, what is important to their business, to their function, to their silos? Cox Automotive has five, of what we call, pillars, where there's international, finance, marketing, retail, or media, and each one of those owners, over time, wants the specific value. >> So if you go and have a chalkboard session, whiteboard session, with one of these folks, how do you operationalize it? You got to figure out where the data exists, so that you can align with what's in their head? Is that right? And then, how do you do that? How do you scale it? >> Well, so, again, you have to start from the top. If you start from the bottom, you'll be in the weeds until the end of time. So that the more efficient manner is to start from the top and realize those KPIs from those leaders, those stakeholders, and then from there, a tool like ITSI, which is basically built around services, entities, and aligning to their service decomposition model, and that right there allows you to stay consistent and efficient on getting that information. >> So you start top down, but ultimately, people are going to want granularity. So you start-- is it top down, bottom up, type of approach? Where you actually drill, drill, drill, drill, drill, and then get to the point where you can answer all those granule questions? And then, by doing that, if I understand it correctly, it sums to the top line, is that fair? >> Yeah, yeah, there's a point in time where you say, you know what? I could really now enhance or enrichen the data by a dataset that I know where it is. So the keypal will get you to a certain point, and then, to find that happy medium, or that common denominator from the data that you already have on premise, or from your apps, wherever they reside, that's where you can meet the gap. >> Otherwise you're never get it done. You'll end up boiling the ocean. >> That's correct, yes sir. >> All right, so, when we talked to you two years ago, you were using Splunk Cloud, you know? And when we talked to practitioners it's-- the things that they're managing, a lot of times now, most of it's not what they own, and so, how do I get the right information? How do I manage that environment? Talk to us a little bit about what you've seen in the maturation of Splunk and Splunk Cloud, if there's anything in 7.2, or Splunk Next, that's exciting you, to help you do your job even better. >> Oh man, so of course, the keynote today, the DSP, the processing layer that's in front of the Cloud, or in front of the indexes now. Where in real time, I can now route data, specifically from a security standpoint. If there's some type of event, without having to go through all the restarts and configuration management and everything else, I can simply put something in there, right there, and move the data, or mask the data. The ability with the infrastructure app, that's exciting to me, as well as all the feature updates for ITSI, enterprise security, as well as the Cloud itself. >> Can we do a little Splunk 101 for my benefit? So I heard today, from one of the product folks, that it used to be when you added another indexer, you had to add storage and compute simultaneously, whether or not you needed the storage, you had to add it, or vise versa. So an indexer is what, is it, essentially, a Splunk node? >> No, it can be a, basically, a Linux host, that actually has the agent running as an indexer with the attached disk. >> Right, okay, and it used to be you had to buy that in chunks, kind of like HCI, right? And you couldn't scale storage independent of compute? >> That's correct. >> What that meant is you were paying for stuff that you might not need. >> Right. >> So, with 7.2, I guess it is, you can split those and you get more granule, or what does that mean for you? >> Well, being a, now four year customer of Splunk Cloud, and anytime we went to the next version of, or license, the next step up, currently we're on about six terabytes. When we go up to eight, that the entailed more indexes being added to the cluster, which meant more time for the replication of search factors to be met, which can take however long, and then, or if there's any kind of issue with the indexer, where one had to be pulled out and another one introduced. How long does that take? Now, with the decoupling of the compute from the storage, it's minutes, and so it's a fraction of the time. >> And if I understand, I understood it real well when it's an appliance, but it's the same architecture if it's done in the Cloud, is that correct? >> It's, essentially, actually, it's a new architecture in my mind, where now it's able to scale more, and then there's-- I'm not sure how much they talked about it, but there's a potential of the elasticity of it. And so, now, I don't have to be so fixed, I can, on certain times, expand the cluster, you know, for search performance, or bring it back down when it's not needed. >> Some of the promise of Cloud. >> Yes, sir, Splunk Cloud. >> So it's like the Billy Dean, the five tool star. You've got the cost, you've got availability, you got speed, you got flexibility, and you've got business value, ultimately, which is what's driving here. So, I take it, I'm inferring here, you'd expect to use this capability in the near future? >> Very much so. >> Great. What else is on your horizon? What are the cool stuff you're working on? And things you want to share with us? >> Well, in addition to our leveraging Splunk Cloud for four years, next year we plan to move away from our current sim tool, into enterprise security. So it's very exciting to hear that they're continually updating that product, and so our security team has been knocking on my door for the last six months to really get that started. So, once we get there, we'll start the migration efforts and get Splunk Cloud now, enabled with the enterprise security, to really empower our security team, and stay ahead of our threats. >> So, I've been around a long time, and, ever since I can remember being in this business, customers have wanted to consolidate the number of vendors with whom they work. But the allure of best of breed always sucks them in to, oh, lets try this, or you get shadow IT. It sounds like, with Splunk, you're approaching this as a platform that you can use for a variety of different use cases. >> That is correct. >> Now, whether or not you reduce the number of vendors is, maybe a separate conversation, but I guess the question I have is, how are you using Splunk in new ways? It sounds like its permutating a line of business, SecOps, etc, is that an accurate picture? If you could describe it. >> Yeah, so Splunk itself, the core is the platform for so many different other functions within the business. You have security, you have the development group, DevOps, where, from a CICD perspective, now they can measure the metrics or the latency in between, when they create a car, say in rally, all the way to the very end of the line, what are all those metrics that are there, that they can leverage to increase their productivity? Obviously, infrastructure. As we consolidate all of our data centers down, wouldn't it be nice to know if these specific low bouncers or switchers are still having traffic to verse them? And to actually get a depiction of the consolidation effort. From a virtualization standpoint, isn't it powerful to know how many devices E6 hosts are actually fully being utilized, and how many are actually vacant? And how much money can be saved if we were actually to turn down those specifics blades or hosts? Or VMs that aren't being leveraged, but they're sitting there, taking up valuable resources. >> I remember when Splunk, right around the time they went public, I remember two instances, maybe three. There was a MPP database company, there was a large three letter firm, and there was an open-source specialist, and I heard the same thing from each of them, was we have the Splunk killer, this was like, five, six years ago. It seems like this Splunk killer was Splunk. And it really never happened. Why is it? Why is Splunk so effective? You obviously see, you know, you're independent, you want to use the best thing for Cox Automotive. What is it about Splunk that sets them apart, puts them in the lead? >> The scale capabilities, having this type of environment with the conferences and the sales group and the support groups, very intentional about listening. Having workshops where they come on premise to help us out on our use cases, to really educate their users, because the more their users are elevated from a knowledge standpoint, the more they will then exercise the application. If they all stay basic, why would I need another component of Splunk? Why would I need enterprise security? Why would I need to expand my subscription into the Cloud? The more I can exercise it, the more I'll need. >> So this is kind of a give, get. They come in knowing that if they expose you to other best practices, you'll going to be more effective in the use of Splunk and you might apply it in to other parts of your business. >> My appetite will grow and my users appetite will grow. >> And these are freebies that they're doing? Services freebies, or are they paid for services? >> Oh yeah, they have no problem coming in, supplying the necessary ammunition, or food, to entice, to have folks come in, but it's powerful to have all the engineers in there to really show us how things work. 'Cause, again, it's a win, win. >> And you're a football fan, I understand? >> Oh, yes, sir. >> Chiefs are your team, right? >> That's correct. >> Were you a football player? >> For a little while, yes. Now I coach, so that's my-- >> And you coach, what? >> Little girls. >> Kiddie football, huh, awesome. Is that Pop Warner these days, still? >> I guess you call it that. >> Flag football or tackle? >> Tackle football >> Really? >> Yep. >> Eight years old? >> Yes, my son is eight and he's playing full back right now, I'm very excited, happy father. >> Is he a big boy, like his dad? >> He's going to be bigger, I think, than his father, yes, sir. (both laugh) >> That's awesome. Well, listen, thanks very much, Steven, for coming on theCUBE, it's really a pleasure meeting you. >> That's appreciated, thank you very much. All right, keep it right there everybody. Stu and I will be back with our next guest. We're live from Splunk .conf18, you're watching theCUBE.
SUMMARY :
brought to you by Splunk. Steven Hatch is here, he's the manager of and what you do at Cox. the enabler, and the center of excellence so you got your hands and knowing how to think about the number of brands But of course, the approach So, a lot of times, as you mentioned, How does the Splunk modeling, and how you Yeah, and so, when you inside the company, and as you and to align with those business KPIs. and you want to codify that and ask the questions So that the more efficient and then get to the point where you can or that common denominator from the data Otherwise you're never get it done. talked to you two years ago, and move the data, or mask the data. you had to add storage and that actually has the agent running that you might not need. and you get more granule, or a fraction of the time. of the elasticity of it. So it's like the Billy And things you want to share with us? for the last six months to consolidate the number of reduce the number of vendors is, that they can leverage to and I heard the same and the support groups, very and you might apply it my users appetite will grow. all the engineers in there Now I coach, so that's my-- Is that Pop Warner these days, still? I'm very excited, happy father. He's going to be bigger, I for coming on theCUBE, it's thank you very much.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
Steven | PERSON | 0.99+ |
Steven Hatch | PERSON | 0.99+ |
Groton | LOCATION | 0.99+ |
Cox Automotive | ORGANIZATION | 0.99+ |
Kelley Blue Book | ORGANIZATION | 0.99+ |
Toronto | LOCATION | 0.99+ |
Cox | ORGANIZATION | 0.99+ |
Utah | LOCATION | 0.99+ |
five | QUANTITY | 0.99+ |
Dave | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
next year | DATE | 0.99+ |
South Jordan | LOCATION | 0.99+ |
four years | QUANTITY | 0.99+ |
Orlando | LOCATION | 0.99+ |
four year | QUANTITY | 0.99+ |
Auto Trader | ORGANIZATION | 0.99+ |
Connecticut | LOCATION | 0.99+ |
eight | QUANTITY | 0.99+ |
each | QUANTITY | 0.99+ |
Canada | LOCATION | 0.99+ |
three | QUANTITY | 0.99+ |
WebEx | ORGANIZATION | 0.99+ |
first time | QUANTITY | 0.99+ |
Stu | PERSON | 0.99+ |
two instances | QUANTITY | 0.99+ |
Splunk Cloud | ORGANIZATION | 0.99+ |
Orlando, Florida | LOCATION | 0.99+ |
Upstate New York | LOCATION | 0.99+ |
Splunk | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
dozens | QUANTITY | 0.99+ |
Manheim | ORGANIZATION | 0.98+ |
two years ago | DATE | 0.98+ |
Linux | TITLE | 0.98+ |
three letter | QUANTITY | 0.98+ |
both | QUANTITY | 0.98+ |
this week | DATE | 0.97+ |
Disney World | LOCATION | 0.97+ |
five | DATE | 0.97+ |
six years ago | DATE | 0.97+ |
'96 | DATE | 0.97+ |
five tool | QUANTITY | 0.96+ |
one | QUANTITY | 0.96+ |
One | QUANTITY | 0.96+ |
each one | QUANTITY | 0.92+ |
about six terabytes | QUANTITY | 0.92+ |
Splunk 101 | TITLE | 0.91+ |
theCUBE | ORGANIZATION | 0.9+ |
Atlanta, Georgia | LOCATION | 0.9+ |
M&A | ORGANIZATION | 0.9+ |
Eight years old | QUANTITY | 0.89+ |
last six months | DATE | 0.87+ |
Splunk | TITLE | 0.84+ |
E6 | COMMERCIAL_ITEM | 0.82+ |
keypal | ORGANIZATION | 0.78+ |
7.2 | TITLE | 0.77+ |
Enterprise Logging Services | ORGANIZATION | 0.77+ |
last couple of years | DATE | 0.74+ |
ITSI | ORGANIZATION | 0.72+ |
Splunk node | TITLE | 0.7+ |
Warner | ORGANIZATION | 0.7+ |
Splunk | EVENT | 0.7+ |
Splunk | PERSON | 0.7+ |
Pop | PERSON | 0.68+ |
7.2 | QUANTITY | 0.68+ |
Splunk Cloud | TITLE | 0.66+ |
Brian Cox, Nutanix | Microsoft Ignite 2018
>> Live from Orlando, Florida, it's theCUBE covering Microsoft Ignite, brought to you by Cohesity and theCUBE's ecosystem partners. >> Welcome back, everyone, to theCUBE's live coverage of Microsoft Ignite here at the Orange County Civic Center in Orlando, Florida. I'm your host, Rebecca Knight, along with my co-host, Stu Miniman. We're joined by Brian Cox, he is the director of product marketing at Nutanix. Thank you so much for coming on the show. >> Well thanks for having me, Rebecca, and Stu, it's good to see you again, so-- >> Yes, you're a CUBE alum, an esteemed CUBE alum. >> I've been here before and it's a great experience. >> Great, well, before the cameras were rolling we were talking about how Nutanix really pioneered hyper-converged infrastructure. But, the vision is bigger, Nutanix is about more than hyper-converged. >> Yeah, and we're very, actually, glad to see here at Microsoft Ignite that Microsoft, in the next version of Windows, is touting the whole hyper-converged concept. So, we are seeing validation from one of the most established computing companies in the world. The thing is, when Nutanix got started, we didn't even know what to call it. We never used the term hyper-converged infrastructure. It was one of your colleagues in the analyst community, they coined that term. We were really thinking of something, I think, bigger and beyond, which is, how can we simplify IT, because at the end of the day, all the business cares about are the services that IT delivers. Those get delivered through applications. Everything below that, frankly, the business doesn't care, right? If you're a donut company, you want to make donuts. If you're a shipping company, you want to have trucks and all that logistics to be optimal. IT, and finance, and marketing, and HR, they're all just means to an end. And so, when we looked at this we said, What can we do to just deliver those services and apps, and simplify everything else? Anything that we can do to save time, that we can save money, we get to return that back to the business to help be a better trucking company or a better donut company, right? So with that in mind, we said we need to simplify. >> Brian, great point, I mean, your background, my background, we're on the infrastructure side of things. You know, I got reminded many times in my career, Look, the whole goal of infrastructure is to make those apps run. You know, it's my data and my applications, those are the important things of the business. That doesn't mean that we've, you know, made y'know, IT is not yet a utility, it's not completely commoditized, there's differentiation, so, maybe help explain a little bit, Nutanix in the Microsoft ecosystem and how that fits in the overall view of Nutanix's value in the marketplace. >> Sure, so, the larger vision that Nutanix had is just, Let's simplify everything below the app layer. We did start at one place, which is just to fundamentally clean up and simplify the physical infrastructure, so you have storage arrays over here, servers over here, a sand-fabric in-between, virtualization layered on top of that, all coming from different vendors, not necessarily all tested together. I know because I used to work at the vendors, right? All different management consoles. It's really hard to become a mastermind of all of that, to have it optimized, and not to have points of failure. So we said, The first thing we need to do is eliminate that complexity. So we brought that down into like a single building block appliance, which ultimately got termed hyper-converged infrastructure, but that wasn't our destination. That was just, we needed common building blocks like LEGO pieces, right, that can snap together without any fuss and allow the companies to build that up. Then, from there, we can then raise the level of simplification all the way between the physical infrastructure to the app. So, one of the things that we get an immediate benefit from, when we consolidate storage and servers, the virtualization, is that we improve performance for things like Microsoft SQL or Exchange. So, no longer do you have that long hop from the compute with the servers all the way out to the external storage arrays. It all collapses, performance gets better, we eliminate points of failure, and, in fact, even when you have multiple of these LEGO blocks, this cluster, we try to always associate the data and the compute onto the same node, so there's very little latency at all. So, Microsoft SQL, Exchange performance goes up, the up-time goes up, and then to manage it, is also simpler. >> Alright, so Microsoft business productivity apps live on the Nutanix infrastructure-- >> Yeah, they benefit immediately by going to the simpler infrastructure versus this complex distributed architecture, where there's different pieces from different vendors. >> Alright, so, we hear from Microsoft, and we know customers hear, it's a multi-hypervisor and multi-cloud world, so, how does the Microsoft pieces of that fit in with the Nutanix Story? >> Well, we realize that customers want to have choice. So, if you look at really the three pillars, that come from our founding, is we want to be able to make it simple, we want to make it scalable, and we do want to give you choice. So, when we look at that last one, we're going to give you a choice of, let's say, whatever hyper-visor you wish to use. It could be Hyper-V, it could be DSXI, it could be the Nutanix AHV, it could be XenServer from Citrix. All of those are supported, we support this on multiple different hardware platforms. So, you have Adelium C, Lenovo, IBM, Fujitsu in Europe, we just added Hitachi last week as a partner, we run on Cisco, we run on HPE servers, and that list continues to grow. So, whatever is your standard, we'll go ahead and work with that. We'll give you choices, different clouds, as well. So, the software to manage and optimize is not only just for your on-prem environment, you can use this if you're in a distributed environment, whether it's Robo or Edge sites, like oil rigs and other IOT, we can give the same interface, and then the same interface out to the public cloud as well. So we give you the choice of different clouds, different platforms, different hyper-visors, and then different operating systems. We support everything from a Windows server environment to Linux and even IBM's AIS. All are supported on the platform, so you get to have it fit the way you want to work, versus the other way around. >> How closely do you work with customers in making theses decisions? Because, as you said, your goal is simplification, making it easy for them to choose and deploy, so how do you walk them through the process, and is it ever analysis paralysis, because there are simply so many options? >> Well for some customers who are struggling with that choice, we do offer our own branded appliance. So, it's very simple, you have the computing framework, the Nutanix software's there, it's one single support line to call, and that's a very simple model. Other customers, though, have chosen who their platform of choice is, whether that's on-prem, like a physical server, or it's a public cloud. That choice, oftentimes, has already been made, right? We're just working with that, so, for those who already have an opinion in the customers sight, we'll work with that. If for some reason they don't have an opinion, or they want it even simpler, they can go with the Nutanix branded offering, but we'll work either way. >> Great, Brian, you go to a number of different shows. Tell us, what are you hearing from customers, what are some of the challenges, what are they looking for, and maybe what's different about the customers who are here at the Microsoft show, versus some of the others we might hear. >> Well, it depends on who you're talking to right? So, if you're talking to C-suite, at the end of the day, these are the guys or gals running the donut company, they're running the trucking company, and they view IT just like they view HR, or finance, or whatever. It's like, yes, that's absolutely critical, we need that function, but the goal is to make it more efficient, more effective so I can deliver more shipments, make more donuts, right? So, for the C-suite, they want to see, On my capital that I'm investing, what is the return on this, and do I have to over-commit capital now, because I can only buy it in big chunks?. So we address that by having what we call fractional consumption. Basically, you're buying one LEGO block at a time, so you're not consuming capital that could elsewhere be used in the business. So, C-suite, they have a different, y'know, one set of needs. Then you look at the sys admins, and they are overwhelmed with all of this complexity of infrastructure, it burns all of their time. They're spending all their nights, all their weekends, they're not very happy, they make mistakes. If we can give them back hours in their day, they're going to be more productive. They can actually do higher level tasks. And even for the folks on the dev team, if we can simplify the infrastructure and spin up new instances, whether it's containers, or VMs, and they can even do it through self-service, that makes them more productive. So, we try to address the needs of all those audiences. >> The customers you are referring to, they are different groups of customers, but they're all essentially the same company, so, are they talking to each other? I mean, are the tech people talking to the business people in terms of what are over-arching goals here. >> Yeah, they do talk to each other. Granted, probably the audience we talk to them most frequently are the sys admins, y'know, because we're very operationally tied, and we'll then arm them with arguments to talk to the C-suite, right? So I was just presenting yesterday here, told them, You're going to get your nights and weekends back., but when you got to go talk to the CFO, here are the things that that person's going to care about, right? When you go talk to the dev team, here's the things that you need to share with them. So, we do arm the sys admins, but we do have a growing presence, at the C-suite, for example. We've also started attending a number of developer conferences, saying, Hey, this actually makes sense to you, to get your job done, it's not just the sys admins, it's you as a developer, it's you as a leader of the company. This is transforming the power of IT to help fulfill the organization's mission. >> I'm curious about your perceptions of Microsoft. Right now we have Satya Nadella, who really portrays this company as a company that is open, inclusive, with a growth mindset, Don't be a know-it-all, be a learn-it-all. I mean, is that your... Do you feel that as someone who works closely with Microsoft, who rubs up against its colleagues-- >> I think it's an embrace, like what you can't exact in regards to, the reality is customers want choice, and it's not one size fits all, not one cookie-cutter approach. So Satya is saying, Hey, what can we do to integrate with Linux? That never would've been heard, maybe, under the previous regimes, right? What can you do to work more closely in the app development environments that the app developers want to work in? So, there's a lot of affinity, I think, between Nutanix and where Satya's going, and in providing that choice, providing best-in-class wherever you can then let the customer choose, but provide them the pros and cons, so they make an informed decision. >> Brian, thank you so much for coming on theCUBE. It was a pleasure having you. >> Well, thank you Rebecca, and thank you Stu, it's always great to be here. >> We will have more from theCUBE's live coverage of Microsoft Ignite coming up in just a little bit. (techno music)
SUMMARY :
covering Microsoft Ignite, brought to you of Microsoft Ignite here at the But, the vision is bigger, Nutanix is Anything that we can do to save time, in the Microsoft ecosystem and how that So, one of the things that we get by going to the simpler infrastructure versus this and we do want to give you choice. So, it's very simple, you have the computing framework, of the others we might hear. So, for the C-suite, they want to see, so, are they talking to each other? here's the things that you need to share with them. Right now we have Satya Nadella, that the app developers want to work in? Brian, thank you so much for coming on theCUBE. thank you Stu, it's always great to be here. live coverage of Microsoft Ignite
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
IBM | ORGANIZATION | 0.99+ |
Rebecca | PERSON | 0.99+ |
Fujitsu | ORGANIZATION | 0.99+ |
Brian | PERSON | 0.99+ |
Rebecca Knight | PERSON | 0.99+ |
Lenovo | ORGANIZATION | 0.99+ |
Brian Cox | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Nutanix | ORGANIZATION | 0.99+ |
Cisco | ORGANIZATION | 0.99+ |
Hitachi | ORGANIZATION | 0.99+ |
Stu | PERSON | 0.99+ |
Europe | LOCATION | 0.99+ |
yesterday | DATE | 0.99+ |
Orlando, Florida | LOCATION | 0.99+ |
Orange County Civic Center | LOCATION | 0.99+ |
last week | DATE | 0.99+ |
LEGO | ORGANIZATION | 0.99+ |
Cohesity | ORGANIZATION | 0.99+ |
Satya Nadella | PERSON | 0.99+ |
Windows | TITLE | 0.98+ |
AIS | TITLE | 0.98+ |
Linux | TITLE | 0.98+ |
Satya | PERSON | 0.98+ |
theCUBE | ORGANIZATION | 0.98+ |
Adelium C | ORGANIZATION | 0.98+ |
one | QUANTITY | 0.97+ |
three pillars | QUANTITY | 0.97+ |
Citrix | ORGANIZATION | 0.97+ |
CUBE | ORGANIZATION | 0.96+ |
one set | QUANTITY | 0.96+ |
SQL | TITLE | 0.95+ |
Exchange | TITLE | 0.94+ |
Microsoft Ignite | ORGANIZATION | 0.91+ |
one place | QUANTITY | 0.87+ |
Nutanix | TITLE | 0.87+ |
first thing | QUANTITY | 0.85+ |
single building block | QUANTITY | 0.83+ |
Edge | TITLE | 0.83+ |
one cookie | QUANTITY | 0.79+ |
single support | QUANTITY | 0.78+ |
XenServer | TITLE | 0.64+ |
2018 | DATE | 0.53+ |
DSXI | ORGANIZATION | 0.52+ |
Ignite | EVENT | 0.46+ |
AHV | COMMERCIAL_ITEM | 0.42+ |
block | COMMERCIAL_ITEM | 0.31+ |
Ignite | TITLE | 0.3+ |
Rod Lappin, Lenovo & Roger Cox, Gartner | Lenovo Transform 2018
>> Live from New York City, It's theCUBE! Covering Levnovo Transform 2.0. Brought to you by Lenovo. (techno music) >> Welcome back to theCUBE's live coverage of Lenovo Transform here in New York City. I'm your host Rebecca Knight along with my co-host Stu Miniman. We're joined by Rod Lappin. He is the senior vice president in marketing here at Lenovo. And Roger Cox, the research vice president at Gartner. Thank you much, gentlemen for coming on theCUBE. >> Thanks for having us! Excited. >> So the big news for the day, NetApp, Lenvovo Two global powerhouses joining forces I want to hear Rod, the Lenovo speil, and then I want to hear your analysis of the deal and what you make of it. So why don't you go ahead. >> Yes, so obviously we're really really excited, Rebecca. It's a great day for us. I think it's something that we've been really planning with NetApp for obviously a long time, and to actually have it come to fruition is really exciting for all of us, right. So as you would have known, probably, our storage offering in market has been quite small up until now. We're addressing about 15% of the market. With this new deal with NetApp we're sort of in the TAM the target market. We can after up to about 92%. We've been quite good at storage. We've been growing about 2X the market average in Flash, over 100% year on year, but we haven't really had the full product range that we've needed to really address out customers' needs, and so, now having this, having this deal now with NetApp means we can go after our customers and really bring value to them the way that we have wanted and definitely the way our customers are asking us to. >> And so that's my question. Was it customer driven? Was it them saying: We just need you to able to do more or what? >> I think if you look at our core business last quarter, Gartner, obviously, ranked us as the fastest growing server business globally. We grew 68% year on year on our revenue last quarter. And so, with the momentum we've got now as a business, we're seeing our customers want us to do more. We're number one in customer satisfaction, number one in reliability, so they see value in us generally but we had sort of what I would classify as a subsegment of the storage market that we want to address. And of course our customers are saying to us: Hey, we want you to do more for us because we like the way you've performed. So it's been good for us. We're excited >> Yeah. >> So, Rodger you know a thing or two about the storage industry and NetApp specifically. So give us the customer viewpoint. You talked to a lot of them. >> Well, first of all let's say this is one of the better kept secrets because it never leaked out. So really haven't been getting customer calls on this event yet but I'm sure we will starting today be getting a lot >> Yeah, they brought a few analysts down to RTP in July and I remember, Rodger you said: What do I do when the customers call? and they're like, shh, shh. Customers aren't going to call. We're going to keep it under wraps. >> And they did a good job of it. But anyways, what it means, I think, to Lenovo is it really elevates Lenovo's standing as a provider of IT technology for the data center. So they now have, not only a very competitive server offering, which Rod's talked about quite a bit, they have what many believe to be one of the best storage offerings in the business. And now they can go compete head to head against Dell EMC, as well as with HPE, which would be the two larger competitors that they have to deal with. So it's going to be very good in terms of providing an alternative to clients for data center technology-involved storage. Good thing. We like competition. >> Absolutely, and we want to be part of it. I think up until now we probably haven't been able to. So when you look at how we're going to market, my field sales team has been planning with the NetApp field's also. We've been basically coordinating how we go to market where do we attack together, where do we have conflict, where do we not. So we actually go in and really focus in on those core competitors that Roger's just described which is where we want to go. >> In the keynote this morning it said from a channel standpoint, there's not a lot of overlap which, on the one hand, I'm saying: Well, sounds like we'll need a lot of training then. But how do you hit the ground running fast? >> So we are already ready to go. We start shipping tomorrow, so that's the good thing about this announcement. Like Roger said, we kept it under wraps, but we are ready to manufacture and go. So, I think it's a really exciting spot for us. From a go-to-market perspective in the channel, NetApp has traditionally been very much about engaging end users, fulfilling through the channel, but engaging end users. Where Lenovo's got a much stronger forte around mid-market and SMB. And we've got a much stronger forte in emerging market, so if you actually start to split geographically the world up a little bit and then you can start to split how we got to market a little you can actually find some really big parts of the market that we don't conflict at all that we can go after. >> But you see, from my point of view, the bigger challenge they have is to go to market. Now they could say there's not much overlap, but you know there's always overlap. There's going to be certain accounts where Lenovo already has a position, and maybe NetApp has a position, too. Then, who's going to do what given a time? So, the biggest challenge that Lenovo has here is also a challenge for NetApp is how they manage together the go to market motion, as well as the service and support because Lenovo's going to have level one, level two support responsibility. They're going to have that revenue to go for support. We'll see how that works out over time. >> I want to ask you what your advice would be to Lenovo leadership in terms of, this deal enables it to go after bigger players and to take over more of the market. But when it's now going head to head with Dell EMC , what do you think it should focus on? >> I think it should focus more on marketing. The products speak for themselves. The competency of these products are well-known. Besides this, it gives Lenovo the opportunity to become more cloud-friendly, too. Because they also have access to all of the software out of NetApp's cloud data services organization. So my main advice would be to Rod, because he's responsible for this, (Rod and Rebecca laugh) is put more wood behind arrow. Get Huawei to put up more money to accentuates the marketing of the product. Create more enthusiasm about the fact that you're now up at another level in terms of being an IT provider to the data center. >> It's a well kept secret as you started out by saying >> Yeah! >> That's right so we've got a business case that we've put together that's starting today obviously. Which involves us getting out and starting to hit the ground running with a lot of media. There's a lot of social media noise today on it obviously. Thanks very much to people like yourselves which is great. And I think we're going to see a lot more marketing-based initiative that run both through the channel as well as to the end users across our, what I classify as our T-1 countries to start with. To Roger's point, though, when we look at the go-to-market, we basically categorize in all the accounts into four boxes. Those accounts where NetApp's very strong and Lenovo's very strong which means Lenovo's strong from the server perspective. NetApp's very strong from the storage perspective. >> FAP would be one of those. >> That's right. That's a very good example. And in that environment, we're going to collaborate and show them we're communicating with each other and ultimately, not fight with each other. We're going to recognize that we want to continue to protect our server business. They're protecting their storage business. We don't want to touch that. In a place where Lenovo, for example, may be weak and NetApp very strong, so they're got a very good storage relationship, we want them to bring our servers into that space. Because obviously if they don't bring us in, then one of our key competitors that is also competitive in NetApp is going to have a foot in the door there somewhere. So, we're going to drive a little bit of a different strategy in that environment. Then, we've got obviously the third environment where Lenovo's very strong from a server perspective and NetApp's nowhere. In that environment, it's free fields for Lenovo to go after that with our new storage array. And then obviously, where we're both neither engaging those customers, it's in acquisition for both. We're going to play and ultimately go after them. There's some really great things that we've been able to put together with this relationship. Like for example, comp neutrality. So, the NetApp teams when we go into that third and fourth box I was just talking about, the NetApp sales force is going to paid the same whether it goes on a Lenovo hardware or goes on the NetApp hardware. So, we've got some pieces that sort of ensure that we don't have conflicts and we're all aligned to ultimately grow and compete with Dell EMC and HPE. >> So, Roger There have been some interesting server and storage partnerships. I think back a decade ago, Dell and EMC did billions of dollars together. It eventually broke up, and then what do you know, it went back together. I think five years ago, NetApp had pretty strong server partnership there. The storage market has changed a lot in the five to ten years. Tell our audience a little bit how NetApp's different, how the storage market's different, and how customers should be thinking about an arrangement like this. >> Well, the storage market's different because there's more alternatives for storage. There's the Cloud: AWS, Azure, even Google Cloud. You get over to Asia, Alibaba over in Asia and so forth. So that's had a very large impact on on-premises storage. The other one is hyper converged. Lenovo's very much a hyper converged business. They have relationships with Nutanix. They've got them with VMware. They have them with Pivot3 and some others. And so, all of these things come together to create a different alternative to the classical three-tier infrastructure: server, networking, and storage. So, all those things are going to exist. And, the upright storage market, while it may be a declining market from a revenue perspective, has a long payoff. It's going to be like mainframe, so it'll be here forever. Like Tate, here forever. It's like me. I'll be here forever. (Rod and Rebecca laugh) So right now, Stu, we're seeing a little bit of a bubble. So we are getting a bubble interns of, this is a good time by the way for Lenovo to have this partnership because there is more likelihood of increase spending for IT. Good economy in the States, good economy over in Europe. Good economy around the world for that matter. I think it's going to last another couple years. 2018, 2019, maybe in the 20's before it starts tailing off again. So the way people are talking to me now, it's kind of like a flush. Hey, we got all this money. We're going to go spend it. Refresh everything. Get more over into Flash. I think they will sell a lot of Flash, even with the entry product, what they call a DE. I think they'll sell a lot of Flash there. And of course up in the DM series, which is the equivalent of NetApp's A200, A300 which are top tier products. They'll sell a lot of Flash there, too. >> I would say as what you just mentioned, the traditional storage market is reducing, but Flash is obviously growing. NetApp last quarter was the number one Flash company in the world. 27.6% market share-- >> Where do I check that out? (Rebecca laughs) That comes from another source >> That comes from another source, yeah sorry. But they hit number one last quarter according to an unknown source. But I think that's really encouraging, right? And at that part of the market Flash is about 30-40% of the overall storage market right now and easily the fastest growing. So this product range really drives an all-Flash array type solution that we can actually take advantage of. >> Rod, we want to get your perspective China, too. That's a big piece of this announcement. Maybe you an talk a little bit about that. I think Roger's got some comments on it. >> Well, think this is a good deal for NetApp. This is the reason why I think maybe the channel conflict won't be as bad as it was for the Dell EMC guys. This is the way for NetApp. NetApp wants to go more and more towards the Cloud. You look at their strategy. It's going more and more towards the Cloud with all of the Cloud data services software that they're developing. And so they're putting more and more emphasis on that. At the same time, the relationship they have with Lenovo gives them the opportunity to get really a creative revenue that otherwise would not get. Allows them maybe to reduce the burden that they would have under manufacturing SGNE expenses and stuff like that. But the big benefit is China. They JB in China is going to give NetApp a entry into China that otherwise would not be able to get because of the laws that the People's Republic of China have. It's a big deal. >> I think we're really excited about China. Obviously that's one of the cornerstones of the deal. So it's an independent organization that's going to be set up. Lenovo will have 51% ownership. NetApp will have 49. Seven board members. Four of them will be Lenovo. Three of them will be NetApp. And ultimately we are going to have that organization just purely specializing on the Lenovo product that is designed by NetApp originally. And it's going to be doing joint IP. We'll have joint developers in there. We'll be able to leverage my existing sales force in China, that's our traditional sales force, to go and drive for everything from a tier one city all the way down to a tier six, tier seven city in PRC. But, that joint venture itself will just be a specialist organization specifically on storage. It's really exciting. >> The thing about the JB it's very very important. Whatever is developed by the JB has to stay in China. That software cannot be taken outside of China because of all the geopolitical issues that you have around the world. Big point. >> Yeah, and a challenge. >> Absolutely It's a challenge that both NetApp and Lenovo have to manage with respect to each other. >> Just for the record, I'm not totally sure. If we develop something in the joint venture, I'm not totally sure that we have to keep that in China. >> I'm not saying that legally you have to. I'm saying emotionally you should. >> Emotional we should. >> Ahhh... >> I was going to say... >> There might be some government concerns on some of that. >> I think it's always going to depend on the government. And we don't want to get into a geopolitical conversation. I think Europe for example will be a lot more liberally open to that sort of stuff >> Speak a little bit about the cultures coming together. NetApp. You've been working on this deal together. sometimes that can be the strength or the challenge. >> I think company cultures are always challenging. And when you get two companies that are, especially right now, as we've heard this morning in some of the sessions, turning the corner. They're both growing. They're both doing very well at the moment. So, there's always a level of confidence, shall we say, in both those situations that you've just got to break down. And I think what we've done very successfully this time is Wei Wei, and George and Kirk, and George and Henri Ricard and myself and Brad Anderson, you saw today who was actually up on stage with us today as well working with us as the executive sponsor on that side. We're lining up our executives globally. All of the field team for Henri Ricard's team and my field team globally have all been interlocking with each other. They're account planning. They're territory planning. We're really trying to break down any of the walls the way may have from a cultural perspective. And really drive a much more open conversation, so we don't get caught out early in the deal. There's a escalation process in the deal. So it goes to a geo level up and then ends up with Henri and myself to actually manage worldwide if something was to get really out of control. But, at the moment, day one, don't see any issues. Seems to be going okay, touch wood. >> They both, Brad and Kirk, said they're complementary companies. Is that your perspective, too? Would you agree with that? >> Well, I think they gave complementary purposes. The interesting thing here is this thing's coming together when both companies are on the uptick. It's not because, go back three years ago and look at where NetApp was three years ago versus where they are today. So it's coming together when both companies, and matter of fact, go back to look at Lenovo two years ago as well >> Absolutely. >> So it's been an uptick that happened here over the last three years, so this thing's coming together when both companies are doing quite well in that respect. >> So-- >> By the way I want to mention Gartner will be publishing a report in September on this transaction from NetApp's point of view. And we'll be publishing a report on in November on this transaction from Lenovo's point of view. >> Great, so one of the things people like Roger and I have to do is, we look at how we would say whether something's successful or not. So I want to get your point first too and then when you look out six, 12, 18 months from now, whether it is successful and the thing I have to say is Kirk and Brad said, well, our goal is to number three in China, and I said isn't that a low bar? Aren't you practically on day one? I mean you're two joint companies. It's going to be there? >> I can't count on my boss to be honest with you. >> You've got the sales team. I know you can do that. >> I would love to. I think at the moment let's just talk about the joint venture for a second. I think the point is at the moment we are only 15% addressable market with our existing range. And so at the moment, we're saying, hey we can address 15% of the market. That puts us way outside of the number 10 slot in PRC. So, to say we want to be number three, is quite ambitious. Especially because we want to try to do it in the next couple of years. So, I actually feel like he's being quite aggressive from a growth perspective, so I think that's quite balanced. Outside of that, I really want to measure us on profitable growth. We really want to diversify our share of wallet and our customer base. We've got a great customer base now from a server perspective. We need to really expand that to ensure that we're taking advantage of the customer feedback we've had. So, I think that's a pretty good spot. >> At the end of the day, the success of non-success of this program is in Rod's hands. (laughing) On the one hand, >> I love the pressure you're putting me under >> And then Laura, on the services support side. People will support this program if they get good quality service and support. So, you have to keep that up for this program. >> Absolutely, and at the moment, the services model is level one and level two is run by Lenovo internally and then level three escalation runs into the NetApp program. We believe we've got a model that runs well. >> A good note to end on. Thanks so much for coming on theCUBE Rod and Roger. >> Thank you very much. >> Thanks for having us I appreciate it very much. It's my inaugural time here. >> First of many. I'm Rebecca Knight for Stu Miniman. We will have more from theCUBE at Lenovo Transform just in a little bit. (techno music)
SUMMARY :
Brought to you by Lenovo. He is the senior vice president Thanks for having us! So the big news for the day, NetApp, Lenvovo We're addressing about 15% of the market. We just need you to able to do more or what? a subsegment of the storage market that we want to address. the storage industry and NetApp specifically. of the better kept secrets because it never leaked out. We're going to keep it under wraps. So it's going to be very good in terms of providing I think up until now we probably haven't been able to. In the keynote this morning it said From a go-to-market perspective in the channel, the bigger challenge they have is to go to market. and to take over more of the market. Because they also have access to all of the software the go-to-market, we basically categorize in the NetApp sales force is going to paid the same in the five to ten years. I think it's going to last another couple years. Flash company in the world. And at that part of the market Flash is about 30-40% Rod, we want to get your perspective China, too. because of the laws that So it's an independent organization that's going to be set up. Whatever is developed by the JB has to stay in China. have to manage with respect to each other. Just for the record, I'm not totally sure. I'm not saying that legally you have to. government concerns on some of that. I think it's always going to depend on the government. sometimes that can be the strength or the challenge. So it goes to a geo level up and then ends up Would you agree with that? and matter of fact, go back to look at Lenovo two years ago the last three years, so this thing's coming together By the way I want to mention have to do is, we look at how we would say You've got the sales team. So, to say we want to be number three, is quite ambitious. At the end of the day, the success of non-success on the services support side. Absolutely, and at the moment, the services model A good note to end on. I appreciate it very much. First of many.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Rod | PERSON | 0.99+ |
Rod Lappin | PERSON | 0.99+ |
Rebecca Knight | PERSON | 0.99+ |
Laura | PERSON | 0.99+ |
Rodger | PERSON | 0.99+ |
George | PERSON | 0.99+ |
Rebecca | PERSON | 0.99+ |
Roger Cox | PERSON | 0.99+ |
Lenovo | ORGANIZATION | 0.99+ |
September | DATE | 0.99+ |
Asia | LOCATION | 0.99+ |
EMC | ORGANIZATION | 0.99+ |
Brad Anderson | PERSON | 0.99+ |
China | LOCATION | 0.99+ |
Europe | LOCATION | 0.99+ |
November | DATE | 0.99+ |
Roger | PERSON | 0.99+ |
July | DATE | 0.99+ |
Gartner | ORGANIZATION | 0.99+ |
five | QUANTITY | 0.99+ |
49 | QUANTITY | 0.99+ |
Alibaba | ORGANIZATION | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
15% | QUANTITY | 0.99+ |
Huawei | ORGANIZATION | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Stu | PERSON | 0.99+ |
51% | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
68% | QUANTITY | 0.99+ |
two companies | QUANTITY | 0.99+ |
NetApp | ORGANIZATION | 0.99+ |
2018 | DATE | 0.99+ |
third | QUANTITY | 0.99+ |
Nutanix | ORGANIZATION | 0.99+ |
12 | QUANTITY | 0.99+ |
2019 | DATE | 0.99+ |
both companies | QUANTITY | 0.99+ |
last quarter | DATE | 0.99+ |
27.6% | QUANTITY | 0.99+ |
three years ago | DATE | 0.99+ |
today | DATE | 0.99+ |
both | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
A200 | COMMERCIAL_ITEM | 0.99+ |
Brad | PERSON | 0.99+ |
Dell EMC | ORGANIZATION | 0.99+ |
Klara Young, AppBuddy & Steven Cox, NetApp | SAP SAPPHIRE NOW 2018
>> From Orlando, Florida, it's theCUBE, covering SAP Sapphire Now 2018. (upbeat electronic music) Brought to you by NetApp. >> Welcome to theCUBE, I'm Lisa Martin, in the NetApp booth, at Sapphire Now 2018. We are in Orlando, this is an enormous event, there's more than 20,000 people here, and there's about a million people that SAP is expecting to engage online, that's a lot. We're excited to welcome to theCUBE for the first time, Klara Young, the director of Strategic Alliances from AppBuddy and Steven Cox, the head of Global Sales Tools at NetApp, hi, guys. >> Howdy. >> Hello. >> Hi, Lisa. >> Thanks for having us. >> Absolutely, so Klara tell me about AppBuddy. Who are you guys and what do you do? >> So AppBuddy is a provider of a user experience layer that can sit on top of core systems like SAP Sales Cloud or SAP Service Cloud and that really allows the administrators to configure a dream workspace where you can get all the data that you need to work with in one place, and then, the users can interact with that very easily. And so, it's all very user friendly and it allows us to enable sales processes, I want to manage my pipelines, or my accounts, my contacts, all with a very easy to use interface right in the middle of the core system. >> So your target audience would be customers that are already using SAP or customers that are maybe in the transition from, say Oracle to SAP, or something like that? >> So any users that are planning to use SAP or are already using SAP and then want to enhance that user experience, want to give them a faster way to interact with the data, more intuitive, more functionality, right in the same core interface. So those would be good clients for us to enhance that experience, absolutely. >> And what about customers by industry know SAP really kind of being very, very strong in a lot of industries but manufacturing, digital supply chain, but if you look at their customers that are here at Sapphire and there's a million of them, they span so many industries. >> Yeah. >> I think yesterday they were saying HANA is installed in 23,000 customers across 60 industries. Does AppBuddy have a particular suite of industries where you really add even more value, or is it fairly horizontal? >> Oh, that's a real good question. Actually what's the beauty, I think, of AppBuddy's product, is that it is completely agnostic of which process or which industry that you're deploying it in. So you decide what objects, what information I want to put on that. It's not a purpose-built application specifically for one process or one industry. So we serve clients in all sorts of industries. We have a lot in high tech, or in the health care industry, manufacturing, as well but we're not specific to one industry. So really welcoming any use case and we'd love to hear from customers, hey, can I do this? With AppBuddy, could I put this object and that object together and build a process basically, almost in your own app. And we're very looking forward to those feedback from customers and wanting to build those use cases with them. >> And that's been such a huge theme or really an undertone at SAP Sapphire the last few days is how much SAP listens to their customers and really involves them and especially strategic accounts like in a collaborative way and yesterday, Steven, we spoke with your CIO Bill Miller. We talked to him about NetApp and SAP have been partners for 17 years. NetApp is 26 years young now and has undergone a big transformation. Bill talked about some of that yesterday, but you guys also did a big transformation that you were leading within your sales processes and your CRM move into SAP, talk to us about that. What were some of the reasons for that transformation? >> Yeah, it's working with Bill and his team I'm represent the business side and we're looking as NetApp is transforming from a traditional storage company to more a cloud. It's a change in the way we go to market. In the past we shipped boxes to people and they install them or we install them. And in the future, we're looking to more services and cloud-oriented things. And so the kind of infrastructure that we built up to support our large sales force doesn't work as well in the new world. And so we about two years ago, started a pretty big transformation journey to move from this more old-school hardware to more new cloud and through that process, we needed to change our systems. Changing out our CRM became an important component of that 'cause we need more flexibility and we needed to sort of be more contemporary and we worked with AppBuddy and our old system, we used to have Salesforce, and the field was pretty used to using that kind of interface. And when you build stuff like this, you don't always know how important it is to the field. You know, you have guesses at it, and as we looked at things that we had to do to prepare to move this was always something on our list that we felt like was important but we weren't able to do it immediately. It took us an extra release to get it out, so an extra few months. And through those few months, we learned the hard way that the field really wanted it. It was really impacting them. And we had guessed that we thought it was somewhere around 25% improvement in their overall productivity. And what we found was that it's at least that, if not more. >> Wow. >> Because they came back and said, "We can't do our jobs "without this, you guys gotta get it for us." >> So they said either AppBuddy or the highway? >> Yeah, pretty much. (laughs) Pretty much, AppBuddy or they're not happy. They're not happy all the time anyway but I feel like they-- >> Salespeople. >> That by getting that to 'em we were enabling them to go faster in a few things. And it's simple, it's hard to understand, I think, for everybody, it's a simple layer. Whenever you build a CRM or any kinda system, your job is to collect information and then display it back, make it easy to change. And the way CRMs typically work today is, you have a list for you of stuff, opportunities, or new registrations, quotes and you just have to look at that list and then pick one you wanna edit and then go to this details screen and look at it and then go to the edit screen and then edit it and then go back, back, back. And what AppBuddy provides, is it takes all that noise and makes it into one screen so that you can just simply make and change the data, the way you would expect to on a spreadsheet, in a simple experience. And once you give it to the reps, they sorta expect that as the tablestakes, and it's a gap if you look at most CRMs they don't have this kind of in-line edit capability out of the box. And so this is a great, SAP is really excited about this 'cause it gives them a way to solve this problem without having to build it themselves and that's the beauty of these kind of infrastructures where you can add capabilities by just plugging something in. >> Right. >> And it speaks using the APIs to the tool. And so all the rules that we build around the data about who should access it, what should happen when they change stuff, should we protect data. All that is followed, because AppBuddy works right through our APIs, through the SAP provides. And so it doesn't require a lot extra coding or anything. In fact. >> That's right. >> IT guys are standing over there somewhere. They don't like it 'cause I do it myself. I'll actually build experiences for the field really quickly 'cause that I can make a quick custom business process to support something that's needed. >> So, on the AppBuddy website, Klara, I saw, I love stats, and you guys said, we can save time and improve enterprise productivity by 5X to 10X. >> That's right. >> Those are big numbers. >> That's right. >> And you were saying there's been a massive improvement in employment productivity and I imagine in terms of the speed is essential. You know, we were talking, one of the underlying themes here at Sapphire, this year, is the intelligent enterprise, which demands the integration and the embedding of advanced emerging technologies, AI, for example, to make these enterprises truly intelligent, connecting supply chain and demand chain and it's essential, its table stakes these days. >> Yep. >> To be able to drive things faster, right? So that you guys can get what your customers need faster. >> Yep. >> So, you mentioned that huge productivity boost there but also that you were familiar with AppBuddy before your sales guys and gals were like, hey we need to have something that we're familiar with to be able to make our jobs better, so you're also doing, it sounds like a pretty good job of listening to your customers. >> Yeah, I try >> Who are probably very vocal. >> I try, I try, I mean, it's a hard job because you're sort of channeling the sales guys and in our world they're very different. In Europe, they sell very different than they sell in the US and APAC is different. And even within different sections of Europe or in the US, they act differently, and our goal is to try to streamline that so that they can act as much the same as they can across that and we can deploy sort of one experience without having to customize it totally. But tools like AppBuddy give us the ability to be much more targeted and flexible. A simple example I've been given pretty commonly is we have our sales kick-off this week also in Las Vegas and all of our sales guys are going there to learn about how to sell better, how to sell our new products and solutions and leverage some of our improved selling processes and before they go there, we wanted to have them identify a few key opportunities they're working on to say hey, these are the one's that I'm gonna use as my work case as I'm learning these new things, and in theory as we go through and finish our sales kick-off they go back and start the selling process those opportunities should sell at a higher rate then the other opportunities. And so to make that work, I configured a grid, or an AppBuddy list view, and all I put on it was the list of opportunities in one field that says, this is appropriate for our kick-off and so, instead of putting it in the middle of a very complex world, I sent 'em an email, they had a list and they just had to say this guy, this guy, and that guy, and that's all they had to do. And so our response rate on something, which if you sent a list of things to do for the field, they're not gonna respond. They're busy, they're makin' money. But in this case, because it was tied to the new learning and they felt value in it, 80% of 'em responded within 10 days. >> Yeah, wow. >> And you know, you just don't see that kind of response. But it works because it's a simple experience, right? The only thing they could do with that, they get an email that says, do this, they open it, they see the list, they click, yes, yes, yes, and it's done. And that's a whole business process that in the old days could take months to prepare for and create fields and deploy new code and do all the things you have to do. And in this case, I can create the fields in a day, create the grid in five minutes, and then I put it in an email, and done, you know? So this is where you take things to the next level and make it easier for the sales reps to do the things they need to do help us all be successful. >> Did it also sort of abstract, I can imagine, the fundamental challenges that go along with replacing an entire new CRM, going from Salesforce to SAP. >> Yeah. >> Has that been able to help kind of abstract some of the inner machinations of that so that the sales people can just focus on we know this same interface? >> It totally does, because the list views that we create are only the things they have to have. In any system like this you have a bunch of other fields that are specialized for, say, we have a professional services group and they really want to know blah blah but most sales reps, they don't deal with that at all. But you need it on the page, I need to build that. In these views, I can build it for a sales rep view that is perfect for them, right? Meaning there's no extra fields on that list. It's what you need to get your job done. And so it's like a laser focus, and then I can build a separate one for a different kind of role and give that one to them. So without changing the tool, I'm just creating a focused experience. It all uses the same things. You need sorting, you need filtering, you need a simple edit and that's all available and once they learn that core capability then the rest just kind of falls in. >> And then from your perspective it's probably business outcomes that, George, your CEO, is going to be really excited about, cost savings, employee productivity. >> Yep. >> I'm wondering though, we're talking about it in the context of what you're doing within your sales processes and your CRM. Klara, so obviously working with SAP, are there other businesses processes that AppBuddy can sit on top of and help to streamline the interface with? >> Yeah, great question, and actually thank you for asking 'cause I was gonna say, we talked a lot about sales but we could be enabling any other processes as well and services, for example, is a big one. I've got a list, a queue of cases, I want to make quick updates to that. I want to change things or I'm doing some forecasting, some account planning, but our vision, ultimately is to be able to bring from lead to cache all processes and again tailor it for each user, role specifically for them and we're not giving the solution, the customers are defining what do they need for each one of those processes and that's the power, I think, of this configurability and agility that you get. It's not built and hard coded. It's really you who puts it together. But again, we really have that vision of not only linking the CRM data but ultimately we would love to be able to get more use cases of, hey the CRM data together maybe with your ERP data, I want to see my opportunities but I also want to see the orders and I want to see the invoices so get really this 360 view of your customers that I think we've talked a lot about, even Bill McDermott was talking about it. It's so essential and critical to be customer focused is to have that visibility and with this application where you can basically pull data from wherever you need it for that specific view, you give your users that full visibility and therefore much faster answer questions, be in contexts, not lose critical information of a customer. >> Right, you're right, Bill McDermott did mention yesterday in the keynote about really what, SAP's been pretty vocal about for a while, they want to be one of the top 10 global brands. >> Mm-hmm. >> Right. >> Most valuable brands, and they want to be up there with Apple and Google. >> Right. >> And Coca-Cola, and that's for a software company that sells invisible technology, they're on their way. They're now ranked number 17, but he talked about this. >> Yeah. >> Kind of unique position that SAP's in to link and synchronize >> That's right. >> The demand chain with the supply chain >> That's right. >> Which is pretty revolutionary but ultimately, it's not about just having a 360 view of sales automation, it's of the entire customer process. >> Correct, yeah. >> So Steven, sounds like you are a rockstar in that app, with your sales guys going, hey, we need this AppBuddy technology to make our lives easier, our jobs easier. Do you foresee rolling the AppBuddy technology out to include other business processes? >> All the time, yeah, it's all about the data. And change management or getting the field to act in the same way is really hard and it doesn't sound like it should be but, (Lisa laughs) it's like having 1,000 cats on the table and getting them all to look one direction, it just doesn't happen, right? So my job is to make that and if I can have it with a single user experience, right, without having different flavors of screens and extra fields and narrow it down to what they need, bringing whatever data they need to flow from end to end it makes life easier and I've got 'em all trained. You know, we had very high usage in our previous platform and we're building now from that but they all know how to use it now so I don't have to train the cats to look in the same direction, they all know where to go. All I gotta do is add the data, right? And if you look at NetApp's transformation, from a storage company to a data company my job is really data, it's not about the tools as much. It's about how do we facilitate the salespeople to do more with what they have, right? How do I do a cross-sell, up-sell, how do I get them enabled so they can move faster so that's innate and built into what they do? >> Yeah. >> And in that you have to build, and we were just at another panel talking with SAP about, you have to give back to the sales reps and to the people doing the data 'cause CRM's not fun, I mean, it's not like, hey, I'm gonna go play my CRM tonight. (laughs) It's a different deal. CRM requires work and so you need to give them stuff back. Do machine learning, do things that provide scoring, show the probability of close, help them be more successful at their job and bring the data together in one spot. >> You know, I think yesterday one of the themes also was data and trust, the new currency, right? If you can't access it and extract valuable insights immediately and act on them then you risk being usurped by your competition. So being able to enable the data to be accessible, insights gleaned as quickly as possible, you must be the king. >> Well, I don't know about that. >> The data king. (laughs) >> Yeah, it's definitely our job. >> But as we wrap here in the last few seconds, digital transformation and every company has to go through it or you're not relevant but that requires a cultural transformation as well. >> It does. >> And it sounds like what you guys are doing together is helping that at least from the sales force's perspective of where change has to happen. >> Yep. >> Not only is it improving the efficiency of your SAP environment, your CRM environment, but it's also helping, sounds like, from a cultural perspective, as, hey, we've got to go through this transformation, let's make it where we can simplify, let's do that. >> Very much so. Just like I was talking about the cat problem. You've got the reps that are used to doing something the way and you're saying hey, we're gonna evolve and do something different and that change is rough and people don't feel like it's the right thing at times. The great news with this change and the timing of it is that when you're moving from one platform to the other, it's the one time in the life cycle of these products where you can make significant change, drop whole business process and they won't even notice it. I dropped three quarters of the stuff that we had before and just didn't build it. And I don't have people coming to me going, hey, I really miss doing that, and that's good news, we're helping drive the change. >> Yeah. >> Well, thank so much you guys for stopping by theCUBE and Klara telling us about AppBuddy, what you guys do, how you're working together with NetApp and SAP. We appreciate your time. >> Thank you so much. >> Thank you for the opportunity, Lisa, thank you. >> We want to thank you for watching theCUBE. I'm Lisa Martin at SAP Sapphire 2018. Thanks for watching. (upbeat electronic music)
SUMMARY :
(upbeat electronic music) Brought to you by NetApp. in the NetApp booth, at Sapphire Now 2018. Who are you guys and what do you do? the administrators to configure a dream workspace to interact with the data, more intuitive, but if you look at their customers that are here at Sapphire where you really add even more value, and that object together and build a process that you were leading within your sales processes It's a change in the way we go to market. "without this, you guys gotta get it for us." They're not happy all the time anyway and makes it into one screen so that you can just simply And so all the rules that we build around the data I'll actually build experiences for the field really quickly and you guys said, we can save time and improve enterprise And you were saying there's been a massive improvement So that you guys can get what your customers need faster. but also that you were familiar with AppBuddy and that guy, and that's all they had to do. and deploy new code and do all the things you have to do. the fundamental challenges that go along are only the things they have to have. is going to be really excited about, cost savings, in the context of what you're doing and agility that you get. in the keynote about really what, Most valuable brands, and they want to be up there And Coca-Cola, and that's for a software company of sales automation, it's of the entire customer process. technology to make our lives easier, our jobs easier. And change management or getting the field to act And in that you have to build, then you risk being usurped by your competition. The data king. has to go through it or you're not relevant And it sounds like what you guys are doing together Not only is it improving the efficiency and people don't feel like it's the right thing at times. what you guys do, how you're working together We want to thank you for watching theCUBE.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
George | PERSON | 0.99+ |
Steven | PERSON | 0.99+ |
Josh | PERSON | 0.99+ |
Bill | PERSON | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Carl | PERSON | 0.99+ |
Carl Olofsen | PERSON | 0.99+ |
Cisco | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
Bill McDermott | PERSON | 0.99+ |
Klara | PERSON | 0.99+ |
Orlando | LOCATION | 0.99+ |
Lisa | PERSON | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
Klara Young | PERSON | 0.99+ |
Europe | LOCATION | 0.99+ |
Steven Cox | PERSON | 0.99+ |
80% | QUANTITY | 0.99+ |
Bill Miller | PERSON | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
Carl Olofson | PERSON | 0.99+ |
17 years | QUANTITY | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
US | LOCATION | 0.99+ |
24 hour | QUANTITY | 0.99+ |
five minutes | QUANTITY | 0.99+ |
23,000 customers | QUANTITY | 0.99+ |
1,000 cats | QUANTITY | 0.99+ |
two types | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
Coca-Cola | ORGANIZATION | 0.99+ |
60 industries | QUANTITY | 0.99+ |
26 years | QUANTITY | 0.99+ |
5X | QUANTITY | 0.99+ |
Postgres | ORGANIZATION | 0.99+ |
HANA | TITLE | 0.99+ |
Orlando, Florida | LOCATION | 0.99+ |
360 view | QUANTITY | 0.99+ |
Sapphire | ORGANIZATION | 0.99+ |
more than 20,000 people | QUANTITY | 0.99+ |
one platform | QUANTITY | 0.99+ |
Carls | PERSON | 0.99+ |
first time | QUANTITY | 0.99+ |
IDC | ORGANIZATION | 0.99+ |
one database | QUANTITY | 0.99+ |
NetApp | ORGANIZATION | 0.99+ |
mySQL | TITLE | 0.99+ |
Josh Burgers | PERSON | 0.98+ |
tonight | DATE | 0.98+ |
one time | QUANTITY | 0.98+ |
EDB | ORGANIZATION | 0.98+ |
SAP | ORGANIZATION | 0.98+ |
both | QUANTITY | 0.98+ |
Matthew Cox, McAfee | Informatica World 2018
(techy music) >> Announcer: Live from Las Vegas, it's theCUBE, covering Informatica World 2018. Brought to you by Informatica. >> Hello, and welcome back to theCUBE. We are broadcasting from Informatica World 2018, The Venetian in Las Vegas. I'm Peter Burris, once again, my cohost is Jim Kobielus, Wikibon/SiliconANGLE. And at this segment, we're joined by Matthew Cox, who's the director of Data & Technology Services in McAfee. Welcome to theCUBE, Matthew. >> Thank you very much. Glad to be here. >> So, you're a user, so you're on the practitioner side. Tell us a little bit about what you're doing in McAfee then. >> So, from a technology standpoint, my role, per se, is to create and deliver an end-to-end vision and strategy for data, data platforms and services around those, but always identifying a line to measurable business outcomes. So my goal is to leverage data and bring meaning of data to the business and help them leverage more data-driven decisions, more toward business outcomes and business goals. >> So you're working both with the people who are managing the data or administering the data, but also the consumers of the data, and trying to arbitrate and match. >> Absolutely, absolutely. So, the first part of my career, I was in IT for many years, and then I moved into the business. So for probably the last 10 years, I've been in sales and marketing in various roles, so it gives me kind of a unique perspective in that I've lived their life and, probably more importantly, I understand the language of business, and I think too often, with our IT roles, we get into an IT-speak, and we aren't translating that into the world of the business, and I have been able to do that. So I'm really acting as a liaison, kind of bringing what I've seen of the business to IT, and helping us deliver solutions that drive business outcomes and goals. >> What strategic initiatives are you working on at McAfee that involve data? >> Well, we have a handful. Number one, I would say that our first goal is to build out our hub-and-spoke model with MDM, and really delivering our-- >> Jim: Master data management? >> Our master data management, that's correct. And really delivering our, because at MDM, that is where we define our accounts, our contacts, we build our upward-linking parents and our account hierarchies, and we create that customer master. That's the one lens that we want to see, our customers across all of our ecosystem. So we're finishing out that hub-and-spoke model, which is kind of an industry best practice, but for both realtime and batch-type integrations. But on top of that, MDM is a great platform, and it gives you that, but the end-to-end data flow is another area that we've really put a priority on, and making sure that as we move data throughout the ecosystem, we are looking at the transformations, we are looking at the data quality, we're looking at governance, to make sure that what started on one end of the spectrum look the same, or, appropriately, it was transformed by the time it gets to the other side as well. I'll say data quality three times: Data quality, data quality, data quality. For us, it's really about mastering the domain of data quality, and then looking at other areas of compliance, and the GDPR just being one. There's a number of areas of compliance areas around data, but GDPR's the most relevant one at this time. >> There's compliance, there's data quality, but also, there must be operational analytical insights to be gained from using MDM. Can you describe how McAfee, what kind of insights you're gaining from utilization of that technology in your organization? >> Sure, well, and MDM's a piece part of that, so I can talk how the account hierarchy gives us a full view. Now you've got other products, like data quality, that bolt on, that allow us to filter through and make sure that that data looks correct, and is augmented and appended correctly, but MDM gives us that wonderful foundation of understanding the lens of an account, no matter what landscape or platform we're leveraging. So if I'm looking at reporting, if I'm looking at my CRM system, if I'm looking at my marketing automation platform, I can see Account A consistently. What that allows me to do is not only have analytics built that I can have the same answers, because if I get a different number for Company A at every platform, we've got problem. What I should be seeing, the same information across the landscape, but importantly, it also drives the conversation between the different business units, so I can have marketing talk to sales, talk to operations, about Company A, and they all know who we're talking about. Historically, that's been a problem for a lot of companies because a source system would have Company A a little bit differently, or would have the data around it differently, or see it differently from one spectrum to the next. And we're trying to make that one lens consistent. >> So MDM allows you to have one consistent lens, based on the customer, but McAfee, I'm sure, is also in the midst of finding new ways, sources of data and new ways of using data, like product information, how it's being used, improving products, improving service quality. How is it, how is that hub-and-spoke approach able to accommodate some of the evolving challenges or evolving definitions and needs of data, since so much of that data often is localized to specific activities after they're performed? >> In business, there is a lot of data that happens very specific to that silo. So I have certain data within, say, marketing, that really is only marketing data, so one of the things that we do is we differentiate data. This kind of goes to governance, even saying there's some data as an organization is kind of our treasure that we want to make sure we manage consistently across the landscape of the ecosystem. There's some data that's very specific to a business function, that doesn't need to proliferate around. So we don't necessarily have the type of governance that would necessitate the level of governance that an ecosystem level data attribute would. So MDM provides, in that hub-and-spoke, what's really powerful for that as it relates to that account domain, because you're talking about product. Products is another area we may go look at at some point, adding a product domain into MDM, but today with our customer domain, and kind of our partners as well, it gives us the ability to, with this hub-and-spoke topology, to do realtime and batch, whereas before, it may have been a latency as we moved information around, and things could get either out of sync or there'd be a delay. With that hub-and-spoke, we're able to now have a realtime integration, a realtime interaction, so I can see changes made-- >> At the spoke? >> Peter: At the spoke, right. So the spoke pops back to the hub, hub delivers that back out again, so I can have something happening in marketing, translate that to sales, very quickly, translate that out to service and support, and that gives me the ability to have clarity, consistency, and timeliness across my ecosystem. And the hub-and-spoke helps drive that. >> Tell us about, you just alluded to it, sales and marketing, how is customer data, as an asset that you manage through your MDM environment, how is that driving better engagement with your customers? >> Well, it drives better engagement, first of all, you said an important thing, which is asset. We are very keen on doing data as an asset. I mean, systems come and go, platforms come and go. It's CRM tool today, CRM tool number two tomorrow, but data always is. Some of the things we've done is try to house and put a label on data as an asset, something that needs to be managed, that needs to be maintained, that needs to-- >> Governed. >> have an investment to. Right, governed, because if you don't, then it's going to decline in value over time, just like a physical asset, like a building. If you don't maintain and invest, it deteriorates. It's the same with data. What's really important about getting data from a customer's standpoint is the more we can align quality data, again, looking at that, not all data. Trying to govern all data is very difficult, but there's a treasure of data that helps us make decisions about our customers, but having that data align consistently to a lens of an account that's driven by MDM proliferate across your ecosystem so that everyone knows how to act and react accordingly, regardless of their function, gives us a very powerful process that we can gauge our customers, so that customer experience becomes consistent as well. If I'm talking to someone in sales and they understand me differently, then I'm talking to someone in support, versus talking to someone in marketing or another organization, it creates a differentiating customer experience. So if I can house that customer data, aligned to one lens of the customer, that provides that ubiquity and a consistency from a view in dealing with our customers. >> Talk to us about governance and stewardship with the data. Who owns the customer data? Is it sales, is it marketing, or is there another specified data steward who manages that data? >> Well, there's several different roles that you've going to hit through. Stewardship, we have, within my data technology services organization, we have a stewardship function. So, we steward data, act on data, but there's processes that we put in place, that's you're default process, and that's how we steward data and augment data over time. We do take very specific requests from sales and marketing. More likely, when it comes to an account from marketing, sorry, from sales, whose sales will guide, you know, move this, change this, alter that. So from a domain perspective, one of the things we're working through right now is data domains, and who has, I don't know if you're familiar with racing models, but who is responsible, who is accountable, who is consulted, who just receives an interest or gets information about it. But understanding how those data domains play against data is very, very important. We're working through some of that now, but typically, from a customer data, we align more toward sales, because they have that direct engagement. Part of it, also, is that differentiated view. Who has the most authority, the most knowledge about the top 500, top 1,000, top 2,000 customers is different than the people you had customer 10,000. So you usually have different audiences that play, who helps us govern and steward that data. >> So, one of the tensions that's been in place for years as we tried to codify and capture information about engagement, was who put the data in, what was the level of quality that got in there, and in many respects, the whole CRM thing, took a long time to work, precisely, because what we did is we moved data entry jobs from administrators into sales people, and they rebelled. So as you think about the role that quality plays and how you guide your organization to become active participants in data quality, what types of challenges do you face in communicating with the business, how to do about doing that, and then having your systems reflect what is practical and real in the rest of your organization? >> Well, it's a number of things. First of all, you have to make data relevant. If the data that that these people are entering is not relevant and isn't meaningful to them, the quality isn't going to be there, because they haven't had a purpose or a reason to engage. So, first thing is help make the data be relevant to the people who are you're data creators, right? And that's also to your business leaders. You also want the business leaders coming to you and talking about data, not just systems, and that's one of the things we're working toward as well. But as part of that, though, is giving them tools to ease the process of data-create. If I can go to my CRM tool instead of having to type in a new account, if I can then click on a tool and say, Hey, send to CRM, or add to CRM. So it's really more of a click and action that moves data, so I ensure that I have a good quality source that moves into my data store. That removes that person from being in the middle, and making those typing mistakes, those error mistakes. So it's really about the data-create process and putting a standard there, which is very important, but also then having your cleansing tools and capabilities in your back end, like the MDM or a data stewardship function. >> So by making the activity valuable, you create incentive for them to stay very close to quality consideration? >> Absolutely, because at the end of the day, they use that old term, garbage in, garbage out, and we try to be very clear with them, listen, someday you're going to want to see this data, and you probably should take the time to put quality effort in to begin with. >> Got it, one last quick question. If you think about five years, how is your role going to change? 30 seconds. >> I think the role's going to change in going from an IT-centric view, where I'm looking at tools and systems, to driving business outcomes and addressing business goals, and really, talking to business about how do they leverage data as a meaningful asset to move their business forward, versus just how am I deploying stewardship governance and systems and tools. >> Excellent. Matthew Cox, McAffee, data quality and utilization. >> Absolutely. >> Once again, you're watching theCUBE. We'll be back in a second. (techy music)
SUMMARY :
Brought to you by Informatica. Welcome to theCUBE, Matthew. Glad to be here. on the practitioner side. and bring meaning of data to the business but also the consumers of the data, seen of the business to IT, is to build out our and making sure that as we move data to be gained from using MDM. What that allows me to do is not only is also in the midst of finding new ways, that doesn't need to proliferate around. and that gives me the ability something that needs to be managed, is the more we can Talk to us about governance that we put in place, and in many respects, the whole CRM thing, the quality isn't going to be there, and we try to be very clear with them, how is your role going to change? and really, talking to business about Matthew Cox, McAffee, data We'll be back in a second.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jim Kobielus | PERSON | 0.99+ |
Peter | PERSON | 0.99+ |
Peter Burris | PERSON | 0.99+ |
Matthew Cox | PERSON | 0.99+ |
McAfee | ORGANIZATION | 0.99+ |
Informatica | ORGANIZATION | 0.99+ |
Matthew | PERSON | 0.99+ |
Jim | PERSON | 0.99+ |
today | DATE | 0.99+ |
30 seconds | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
tomorrow | DATE | 0.99+ |
both | QUANTITY | 0.99+ |
three times | QUANTITY | 0.98+ |
First | QUANTITY | 0.98+ |
first goal | QUANTITY | 0.97+ |
GDPR | TITLE | 0.97+ |
McAffee | ORGANIZATION | 0.97+ |
one | QUANTITY | 0.97+ |
Las Vegas | LOCATION | 0.97+ |
Data & Technology Services | ORGANIZATION | 0.95+ |
theCUBE | ORGANIZATION | 0.94+ |
Company A | ORGANIZATION | 0.93+ |
first part | QUANTITY | 0.92+ |
about five years | QUANTITY | 0.92+ |
one spectrum | QUANTITY | 0.91+ |
Informatica World 2018 | EVENT | 0.87+ |
top | QUANTITY | 0.86+ |
one consistent | QUANTITY | 0.84+ |
MDM | TITLE | 0.84+ |
one last quick question | QUANTITY | 0.77+ |
Wikibon | ORGANIZATION | 0.76+ |
2,000 customers | QUANTITY | 0.74+ |
Informatica World | EVENT | 0.72+ |
last 10 | DATE | 0.7+ |
MDM | ORGANIZATION | 0.7+ |
SiliconANGLE | ORGANIZATION | 0.69+ |
2018 | DATE | 0.68+ |
one end | QUANTITY | 0.68+ |
second | QUANTITY | 0.62+ |
top 500 | QUANTITY | 0.6+ |
10,000 | QUANTITY | 0.51+ |
years | QUANTITY | 0.51+ |
Venetian | LOCATION | 0.5+ |
1,000 | QUANTITY | 0.49+ |
two | QUANTITY | 0.42+ |
Donna Woodruff, Cox Automotive - ServiceNow Knowledge 2017 - #Know17 - #theCUBE
>> Announcer: Live from Orlando, Florida, it's theCUBE! Covering ServiceNow Knowledge17. Brought to you by ServiceNow. >> We're back in Orlando, everybody. This is theCUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise. We're here at Knowledge17. I'm Dave Vellante, with my cohost Jeff Frick. Donna Woodruff is here, she's the service enablement leader at Cox Automotive. Donna, thanks for coming to theCUBE. >> Hi, thank you for having me. >> Good to see you, you're welcome. Tell us a little bit about Cox Automotive, and specifically your role. Are you an IT practitioner by trade, or business process person? Share with us. >> A little bit of everything, actually. First of all, Cox Automotive is a large, privately-held organization that's part of the Cox Enterprises family. We are changing the way the world buys, sells, and owns vehicles. We are made up of five key solution group areas. Everything from inventory solutions, which includes our auto auctions, and everything to get cars from dealerships to our auctions and back out again for their inventory. We have financial services, which provides floor planning to our dealerships so they can buy cars from our auctions. We have media services, which are all about how do you connect the cars that you're selling to retail customers, so autotrader.com, Kelley Blue Book are some notable brands as part of our organization. We develop software around analytics, and an ERP system for dealerships, to help them move their inventory and do their floor planning, so they can maximize sales in their dealerships. And then of course we have international. We are a global company. We have over 34,000 team members that we support. We're a very heterogeneous organization, and that can drive complexity into the organization. My role is, I am the service enablement leader. I am based out of technology, but I look at my role as much broader than that. It's about solving problems for our business and being able to deliver services internally and externally, and help the organization run more efficient and effectively. >> So you've seen, you know, the narrative in IT, and ServiceNow's described that very well over the years, IT getting beat up, and you only call IT when there's a problem, and obviously the platform and the adoption of that have changed a lot of organizations, presumably you experience something similar. So, take us back to the beginning days, the early days of what it was like, the before and after ServiceNow. What led you to that decision? What were some of the drivers, how'd you get there? >> Absolutely. Well, Kelley Blue Book was an acquisition for Autotrader group of companies about four or five years ago, and they had implemented ServiceNow as a help desk ticketing system. When we acquired them, we saw some great wins with the platform that we thought, hey, this really should be our help desk ticketing system. And so it brought under cross that small group of companies, but it was always viewed as a help desk ticketing system. Over time, just like many other platforms, it starts to get highly customized. Fast-forward to a couple of years ago, we had a need. I was supporting HR and communications from a technology liaison perspective. The problem that they were trying to solve was that they have two employee service centers, one on the East Coast, one on the West Coast, that were staffed by analysts, and they primarily helped our auto auction personnel deal with their benefits and questions around just HR. All the way down to time sheet corrections and things like that. They came to me with this problem, and they said, "You know, we've been using Remedy to some extent." We were in a transitional time in the organization where we were collapsing our help desk tools onto ServiceNow, and they said, "We need some help, here." "We just want to do a few requests." Well, we identified early on as that liaison that I really think that this ticketing platform can do what you need it do. Myself along with a business analyst and an intern sat down with the business, we understood the requirements, and that was the launch of our HR portal. While we were in there-- >> Just you, an analyst, and an intern. >> That's correct. That's correct. And we weren't developers. It was all about configuration. But we understood the tool, we understand that this is really no different than any other business process, and we set out to deliver the first service catalog around HR services. Since then, we haven't looked back. We learned a lot about the platform. We diagrammed out what was wrong with how the service desk had been highly customized, we sat down with our VP and we just showed him the diagram and said, "We think that this platform can do a lot more." He listened to us, and he turned to us, and he said, "Well, do you guys want the platform?" And I turned to my team, and I said, "Do you guys want it?" We took it on, and since then, in the last 18 months, we have expanded the platform very broadly. We've implemented performance analytics to improve our help desk services. Beyond the HR portal, we are now implementing governance risk compliance, a vulnerability management. We're now doing PPM as well. We are re-looking at our CMDB because we want to do more with automation. We've done some orchestration with storage agility and how we can get those engineers more productive by doing zero-touch ticket requests from our developers to expand file shares and to sunset file shares, or to request new file shares with other applications. >> So what'd you do with all the custom mods, when you talked about the Kelley Blue Book coming over. Did you sort of scrub the hose and start over, or-- >> Well, you know what, we took it back to out of the box, and it wasn't difficult to do. We just rationalized the things that were duplicated across requests and incident, we pulled it back to out of the box, we took an agile approach. My team now is very agile. We do weekly releases on the platform. By bringing it back to out of the box, it allows us to upgrade to the latest major feature releases within a two-week period. Because of that, we're able to adopt and consume the new product enhancements that ServiceNow has to offer very, very quickly. >> So, obviously you had success, or you wouldn't have been able to expand the footprint so radically. How are you measuring success, how did you go from a little bitty thing to a very large thing? >> I think it's about visibility. Visibility and strong leadership support, and showing how we're getting better incrementally over time. I think one of the strategic things that we've done, probably in the last six months, is implement performance analytics, which that started to show the behaviors of how people were working within the platform, how they were addressing incidents, how they were responding to our mean time to response, to our mean time to closure of a ticket, the aging of these tickets. When we first implemented performance analytics, we found a lot of anomalies in the platform. We found orphaned assignment groups, which to the behavior of the organization, they weren't necessarily working the system the way they should be. >> Jeff: Orphaned assignment groups. >> Orphaned assignment groups. Tickets were going in and they were backing up, and nobody was working them. So, allowed us to change the behavior of the organization, to drive consistency in how they were using this, which then made the metrics more meaningful. Now people are running their areas of operation from the platform. >> So the next thing I got to ask you, we talked about it in the open, is behavior. Tech's hard, but it's not that hard compared to people and process. How did you get people at that moment of truth, when I need something, to not send an email like I'm used to, and to actually execute my work through this tool? >> Well, one thing we did that was very unique, and we've continued to do that is as we roll out major feature functionality, we actually create commercials about ServiceNow, about the platform. Internally, we call it Service Station. Everything is associated with a vehicle. We've promoted our brand around the platform as well, and our brand is about doing things more simply, getting things routed to the right people, that's why it's better than email, and demonstrating the power of what it will do to you, and getting those answers more quickly instead of going to your favorite IT person or your favorite HR person. How this platform is helping you get to your answers more quickly, as well as all the self-service capabilities and the knowledge articles around, hey, fix it yourself. You don't have to talk to somebody on the phone. But we still give that personalized touch if they really need help and they want to talk to an individual. >> So really, a lot more carrots than sticks. >> Lot more carrots than sticks, absolutely. It's if you can solve your problem faster, why not? 'Cause at the end of the day, that's ultimately what you want to do. Solve your problem, and get on to the rest of your day. >> How long does it take for a typical employee to go, "Ah, this is fantastic!", and to really shift their behavior and buy in and start selling it, as your advocate? >> I think we're doing a better job now, introducing it to our new hires as soon as they get engaged in the organization, about this is your platform to go to when and if you need help. And here's how easy it is to find the things that you need. It's something that just happens over time, and I think if you address some of those small wins, you create advocates in the organization, and when they have a good experience, they tell others. So some of it's word-of-mouth, some of it is internal promotion. A big part of it is leveraging the platform to get the work done and having a great user experience along the way. >> Donna, you mentioned Service Catalog and CMDB, these are consistently two components that allow customers like you to get more leverage out of the ServiceNow platform. So, specifically as it relates to CMDB, what are you doing there? Do you have a single CMDB across the organization? Is that something you're considering? >> That's probably one of our next big transformational areas. We do have a CMDB within the platform that's been used primarily around the linkages for incident, problem, and change management. But we know that we need to do more with it, and like I said before, we've grown through acquisition, so there's a number of other CMDBs. And we are in the process of bringing that all together onto the ServiceNow platform. Because we're seeing the power of everything else that that connects to. And that's also going to be a key on how we promote more orchestration, more automation, more about the health of our services. >> So, ServiceNow's obviously promoting you guys throughout this event, showcasing some of the things that you've been doing. What've you been talking to other customers about? What are you most proud of? >> Honestly, I'm really proud of my team (laughs), because we are responding to the needs of the organization, and the fact that you can add value through what you do on a day-to-day basis is great. I think one of the most unique things that, in terms of the application, is we actually built an application for our safety auctions. So, as you can imagine, we have a hundred auctions. There's a lot of people working in the auctions. We have everything that a dealership would have, and we have lanes of vehicles running through to be auctioned off with our dealerships. So we have service areas, we have vehicles and people moving about the auction. So safety is a very critical thing for our organization. About a year ago, the safety director came and said, "You know, we have this problem. "We are doing these auctions' safety checklist "around compliance, how can we make "our auctions a safer place?" "You know, we don't have a lot of money, "but we think there's a better way to do it." And they explained the process where they had six area safety managers that were distributed across these hundred auctions, and trying to get the safety message out there through making sure people were wearing their goggles, or that they had all the appropriate OSHA standards in place. So after having a lot of conversations around this, again, we found ServiceNow would be a great solution. We did work with a partner to help us build it, but we took a very manual process and we automated it on the platform. Now we've moved the safety business process to the auctions themselves, where they own it. The general manager's involved, the shop leads are involved in it. And what it's done, it's been a catalyst to reducing our workers' comp claims. We've seen a two basis point improvement over the number of workers' comp claims, which is cost-avoidance, you know. When your average worker comp claim can be around $10,000, that's a significant saving. With a very, very small investment, we saw a 3,000% ROI on this initiative alone. We're bringing visibility to the process, using the platform and the reporting capabilities. It's gotten the general managers and the shop leads engaged and having the conversation about safety. >> This is great, 'cause you got the platform piece of it, and went from basic application delivery to seeing that it is just a workflow tool. >> Donna: Exactly. >> And the benefit of the automation, and now applying it to, I don't think they announced a auto auction safety module this morning. >> No. (laughing) >> Not yet, but we are doing a session... (Donna laughs) >> It's pretty impactful that you were able to see that, execute it with a really small investment, like you said, your initial one with you, an analyst and an intern, and now, really grow and expand the footprint within the organization. >> Yeah, it's really just about business processes in general. You've got everything you need to collect some attributes, or some information, you need to route it or get approvals around it, and then you can measure it. And you can see what's going on with that business process, and then you focus on, how do we improve the business process? The tool helps enable that and facilitate that. >> And how has the conversation around IT value changed, since you started this journey, right? >> Yeah. >> It used to be very cost-focused, I'm sure. Has it evolved to more of a, you mentioned ROI? >> It is, look at it, it's still cost-focused. It's still about savings, but it's also about how do we get things done in an organization more efficiently, with less people pushing paper, and actually focused on solving problems. And being able to measure how we get better in the activities that we're supporting. And then the dollars will follow. >> Dave: Is there a recognition in the business units, that things are changing? >> You know, there really is. One of the areas that we're starting to see real recognition is we're now dipping our toe into customer service management. We brought two platforms together with one of our business units that we acquired in the last year. They were doing some things on Zendesk, they were doing some things on another tool, and they were the same team. So, we've taken that experience, we've brought those agents onto the platform. We didn't change the experience for the customer just yet, because we wanted our agents to be very successful and help them work differently than through email. We pull those channels onto the platform, and now they have a dashboard of these issues in supporting our lenders, who are our customers. Next is really around the portal, in changing the experience for those end customers. Moving it out of the reply to all with email and making it more measurable. We've gotten halfway there, and we see a big growth area there for us, and making a better experience around our customers' support. >> And are you sunsetting some of these other systems as you bring stuff in? >> We absolutely are. I mean, our goal is to eliminate all other ticketing-type systems. In fact, all of the people that are on those ticketing systems, like, "When can we get on the platform?" "We want to be there now." "Help us get there." But bringing things together is going to help us across all of our functional areas, in supporting our customers and our team members much more effectively. It really is becoming our system of action, where you go to get things done. >> Donna, what, from your perspective, is on ServiceNow's to-do list? >> ServiceNow's to-do list. You know, and I've been pretty vocal with ServiceNow, it's like, make it easier for us to use and consume the other capabilities of the platform much more quickly. Allow us to use the great capabilities with some of our external collaborators a little bit more effectively. And I think that's where it is. I think ServiceNow does a fantastic job of bringing more capabilities and maturing all of their service areas. I like the fact that they have two major feature releases a year, and we consume them as quickly as they can send them out, probably faster than some other customers do. And continue to listen to your customers. Just, listen to what our problems are, and our needs are, and continue to answer them. They're doing a good job of that. >> Well, Donna, I have to say thanks for all the great products you guys build. The Kelley Blue Book, we've used it for years-- >> Oh, wonderful! >> And Autotrader, it's a great way to shop for vehicles. So thanks for that! >> You're welcome! >> Dave: Thanks for coming on theCUBE. >> Thank you so much. >> Thanks for sharing your story. >> Keep it right there, everybody. Jeff and I will be back with our next guest. This is theCUBE, we're live from Knowledge17. We'll be right back. (energetic music)
SUMMARY :
Brought to you by ServiceNow. We go out to the events, and specifically your role. and that can drive complexity into the organization. and obviously the platform and the adoption of that and that was the launch of our HR portal. and how we can get those engineers more productive So what'd you do with all the custom mods, and consume the new product enhancements How are you measuring success, the system the way they should be. areas of operation from the platform. So the next thing I got to ask you, and demonstrating the power of what it will do to you, It's if you can solve your problem faster, why not? And here's how easy it is to find the things that you need. that allow customers like you to get more leverage And that's also going to be a key on how we promote showcasing some of the things that you've been doing. and the fact that you can add value through This is great, 'cause you got the platform piece of it, And the benefit of the automation, Not yet, but we are doing a session... execute it with a really small investment, like you said, and then you can measure it. Has it evolved to more of a, you mentioned ROI? And being able to measure how we get better Moving it out of the reply to all with email In fact, all of the people that are on and our needs are, and continue to answer them. for all the great products you guys build. And Autotrader, it's a great way to shop for vehicles. Jeff and I will be back with our next guest.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Donna Woodruff | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Jeff Frick | PERSON | 0.99+ |
Jeff | PERSON | 0.99+ |
Donna | PERSON | 0.99+ |
Orlando | LOCATION | 0.99+ |
Cox Automotive | ORGANIZATION | 0.99+ |
Dave | PERSON | 0.99+ |
3,000% | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
Kelley Blue Book | ORGANIZATION | 0.99+ |
two platforms | QUANTITY | 0.99+ |
two-week | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
Orlando, Florida | LOCATION | 0.99+ |
first | QUANTITY | 0.99+ |
One | QUANTITY | 0.98+ |
around $10,000 | QUANTITY | 0.98+ |
Zendesk | ORGANIZATION | 0.98+ |
two components | QUANTITY | 0.98+ |
single | QUANTITY | 0.98+ |
hundred auctions | QUANTITY | 0.98+ |
over 34,000 team members | QUANTITY | 0.97+ |
West Coast | LOCATION | 0.97+ |
ServiceNow | ORGANIZATION | 0.97+ |
ServiceNow | TITLE | 0.97+ |
East Coast | LOCATION | 0.97+ |
Autotrader | ORGANIZATION | 0.96+ |
autotrader.com | ORGANIZATION | 0.96+ |
couple of years ago | DATE | 0.95+ |
Knowledge17 | ORGANIZATION | 0.95+ |
CMDB | TITLE | 0.94+ |
About a year ago | DATE | 0.94+ |
two major feature | QUANTITY | 0.93+ |
five years ago | DATE | 0.92+ |
Service Catalog | TITLE | 0.91+ |
Remedy | ORGANIZATION | 0.9+ |
a year | QUANTITY | 0.89+ |
last 18 months | DATE | 0.88+ |
hundred | QUANTITY | 0.88+ |
Cox Enterprises | ORGANIZATION | 0.86+ |
Kelley Blue Book | TITLE | 0.85+ |
five key solution | QUANTITY | 0.84+ |
last six months | DATE | 0.84+ |
this morning | DATE | 0.83+ |
#Know17 | EVENT | 0.83+ |
theCUBE | ORGANIZATION | 0.81+ |
two basis point | QUANTITY | 0.81+ |
six area safety managers | QUANTITY | 0.77+ |
two employee service centers | QUANTITY | 0.74+ |
Knowledge | TITLE | 0.72+ |
about four | DATE | 0.66+ |
OSHA | ORGANIZATION | 0.61+ |
Service Station | TITLE | 0.57+ |
more | QUANTITY | 0.5+ |
theCUBE | TITLE | 0.48+ |
2017 | DATE | 0.47+ |
Poojan Kumar, Clumio & Paul Meighan, Amazon S3 | AWS re:Invent 2022
>>Good afternoon and welcome back to the Classiest Show in Technology. This is the Cube we are at AWS Reinvent 2022 in Fabulous Sin City. That's why I've got my sequence on. We love a little Vegas, don't we? I'm joined by John Farer, another, another Vegas >>Fan. I don't have my sequence, I left it in my room. We're >>Gonna have to figure out how to get us 20 as soon as possible. What's been your biggest shock for you at the show so far? >>Well, I think the data story and security is so awesome. I love how that's front and center. If you look at the minutes of the keynote of Adamski, the CEO on day one, it's all bulked into data and security. All worked hand in hand. That's on top of already the innovation of their infrastructure. So I think you're gonna see a lot of interplay going on in this next segment. It's gonna tell a lot of that innovation story that's coming next. It's pretty awesome. >>It is pretty awesome, and I'm super excited. It's not only what we do here on the Cube, it's also in my show notes. We are gonna be geeking out for the next segment. Please welcome Paul and Puja. Wonderful to have you both here. Paul from Amazon, s3, glacier, and Pujan, CEO of kuo. I wanna turn to you Pujan, to start us off, just in case the audience isn't familiar, give us the Kuo pitch. >>Yeah, so basically Kuo is a, a backup as a service offering, right? Built in AWS four aws, right? And effectively going after, you know, any service that a customer uses on top of aws, right? And so a lot of the data sitting on s3, right? So that's been like our, our big use case going and basically building backup and air gap protection for, for s3. But we basically go to every other service, e c two, ebs, dynamo, you know, you name it, right? So basically do the whole thing >>And the relationship with aws. Can you guys share, I mean, you got you here together. You guys are a great partnership. Born in the cloud, operation in the cloud. Absolutely. I think talk about the partnership with aws. >>Absolutely. I think the last five years of building on AWS has been phenomenal, right? And I love the platform. It's, it's a very pure platform for us. You know, the APIs and, and the access you get and access you get to the service teams like Paul sitting here and the other teams you have gotten access to, I think has been phenomenal. But we also have, I would say, pushed the envelope in terms of how innovative we have been and how aggressive we have been in utilizing all the innovation that AWS has built in over the last few years. But it would not have happened without the fantastic partnership with the service teams. >>Paul, talk about the, AM the S3 part of this. What's the story there? >>Well, it's been great working with the CUO team over the course of the last few years. We were just upstairs diving deep into the, to the features that they're taking advantage of. They really push us hard on behalf of customers, and it's been a, it's just been a great relationship over the last years. >>That's awesome. And the ecosystem at such a, we're gonna hear tomorrow, the keynote on the, from Aruba who's gonna tend over the ecosystem. You guys are working together. There's a lot of strategic partnerships, so much collaboration between you guys that makes it very, this is the next gen cloud of cloud environment we're seeing. And you heard the, the economies around the corner. It's still gonna be challenging, but still there's more growth in the cloud. This is not stopping. This is impacts the customers. What are the customers saying to you guys when you work backwards from their needs? They want it faster, easier, cheaper. They want it more integrated. What are some of the things, all those you guys hearing from customers? >>So for us, you know, if you think about it, like, you know, as people are moving to the cloud, especially like take a use case like s3, right? So much of critical data sitting on top of S3 today. And so what folks have realized that as they're, you know, putting all of those, you know, what, over two 50 trillion objects, you know, sitting on s3, a lot of them need backup and data protection because there could be accidental deletions, there could be software bugs, there could be a ransomware type event due to which you need a second copy of the data that is outside of your security domain, right? But again, that needs to get be done at the, at the right price point, right? And that's where like a technology like Columbia comes in because since we've been built on the cloud, we've optimized it correctly. So especially for folks who are very cost conscious, given the macroeconomic conditions, we are heading into a technology that's built correctly so that, you know, you get the right architecture and the right solution at the right price point and the scale, right? Talking about trillions of objects, billions of objects within a single customer, within a single bucket sometimes. And that's where Columbia comes in. Cause we basically do that at scale without, again, impacting the, the customer's wallet more than it needs to. >>The porridge has to be the right temperature and the right size bowl. With the right spoon. You've got a lot of complexity when it comes to solving those customer challenges. You have a couple customer story examples you're allowed to share with us. Correct? Paul, do you want to kick one off? Go ahead. Oh, puja. All right. >>No, absolutely. I think there's a ton of them. I, I'll talk about, you know, want to begin with like Cox Automotive, right? A phenomenal customer that we, all of us have worked together with them. And again, looking for a solution to backup S3 to essentially go air gap protection outside of their account, right? They looked at doing it themselves, right? They thought they'll go and basically do it themselves. And then they fortunately bumped into Columbia, they looked at our architecture, looked at what it would really go and take to build it. And guess what, sitting in 2022, getting 23 right now, nobody wants to go and build this themselves. They actually want a turnkey solution that just does it, right? And so, again, we are a phenomenal joint customer of ours doing this at a pretty massive scale, right? And there are many more like that. There's Warner Brothers that are essentially going into the cloud from on premises, right? And they're going really fast accelerating the usage on aws again, looking at, you know, backup and data protection and using clum because of our extreme simplicity that we provide. >>Yeah, I think it's, you've got a, a lot of different people solving different problems that you're working with all the time. Millions of customers. Well, how do you prioritize? >>Well, for us, it really all comes down to fundamentals, right? So Amazon, s3 s unique distributed architecture delivers industry leading durability, availability, performance and security at virtually unlimited scale, right? And it's really been delivering on the fundamentals that has earned the trust of so many customers of all sizes and industries over the course of over 16 years. Now, in terms of how we prioritize on behalf of those customers, we always say that 90% of our roadmap comes directly from what customers are telling us is important. And a large number of our customers now are using S3 through lumino, which is why the relationship is so important. We're here talking about customer use cases here at the show, and we do that regularly throughout the year as well. And that's, that's how we land on a road. >>And what are the, what are the top stories from customers? What, what are they telling you? What's the number one top three things you're hearing? >>I tell you, like, again, it just comes down to the fundamentals, right? Of security, availability, durability and performance at virtually unlimited scale. Like that is the first customer first discussions that we have with customers talking about durable storage, for >>Sure. What I find interesting in, you mentioned scale, right? That comes up a lot scale with data. Yeah. That we heard data. The big theme here, security, what's in my S3 bucket? Can you find out what's in there? Is it backed up properly? How do I get it back? Where's the ransomware? Why not just target the ransomware? So how do you navigate the, the security challenges, the, the need to store all that scale data? What's the secret sauce? >>Yeah, so I think the, the big thing is we'll start with the, you know, how we have architected the product, right? If you think about it, this, you're dealing with a lot of scale, right? You get to a hundred million, a billion and billions very fast on S3 few, especially on a cloud native application. So it starts with the visibility, right? It's basically about, like we have things where you do, where you create a subset of your buckets called protection groups that you can essentially, you know, do it based on prefixes. So now you can essentially figure out what prefix you want to back up and what you don't want to back up. Maybe there's log data that you don't care about, so you don't back that up, right? And it all starts with that visibility that you give. And the prefix level data protection then comes the scale, which is where I was telling you, right? We have basically built an orchestration engine, right? It's like we call the ES for Lambdas, right? So we have a internal orchestration engine and essentially what what we have done is we have our own language internally that spawns off these lambdas, right? And they go after these S3 partitions do the right things and then you basically reel them back. So things like that that we do that are not possible if you're not built on the >>Clock. Well also, I mean, just mind blowing and go back 10 years. Yeah. I mean you got Lambda. What you're talking about here is the gift of the cloud innovation. Yeah. So the benefit of S3 is now accelerated. This is the story this year. Yeah. I mean they're highlighting it at scale, not just in the data, but like what we knew when Lambda came out and what S3 could do. But now mainstream solutions are coming in. Does that change your backup plans? Because we're gonna see a lot more end to end, lot more solutions. We heard that on the keynote. Some are saying it's more complexity. Of course it might, but you can abstract another way with the cloud that's the best part of the cloud. So these abstraction leads. So what's your view on that? But I wanna get your thoughts because you guys are perfectly positioned for this scale, but there's more coming. Yes. Yes. Exactly. What, how are you looking at that? >>So again, I think the, you know, obviously the, the S3 teams and every team in AWS is basically pushing the envelope in terms of innovation. But the key for a partner like us is to go and take that innovation. A lot of complex architectures behind the scene. But what you deliver to the customer is simple. I'll give you one more example. One of the things we launched that, you know, Paul and others are very excited about, is this ability to do instant access on the backup, right? So you could have billions of objects that you backed up. Maybe you need just 10,000 of them for a DR test. And we can basically create like an instant virtual bucket on top of that backup that you can instantly restore >>Spinning up a sandbox of temporary data to go check it >>Out. Exactly. Offer an inte application. >>Think we're geeking out right now. >>Yeah, I know. Brought that part of the segment, John. Don't worry, we're safely there. But, >>But that's the thing, right? That all that is possible because of all the, the scale and innovation and all the APIs and everything that, you know, Paul and the team gives us that we go and build on top of >>Paul, geek out on with us on this. We >>Are super excited for instant restore >>For store. I mean, automation programmability. >>It is, I mean it's the logical next step for backup in the cloud. Exactly. Yeah. But it's a super hard engineering problem to go solve for customers. I mean, the RTO benefits alone are super compelling, but then there's a cost element as well of not having to bring back all that stuff for a test restore, for example. And so it's, it's been really great to, to work with the team on that. We have some ideas on how we may help solve it from our side, and we're looking forward to collaborating on it. >>This is a great illustration of what I was writing about this week around the classic cloud, which is great. And as Adam said, and used like to use the word and, and you got this new functionality we're seeing emerge from the growth. Yes. From the companies that are built on Amazon web services that are growing. You're a partner, they have a lot of other partners and people are taking over restaurant here off action. I mean, there's real growth and new functionality on top of aws. You guys are no different. What's, are you prepared for that? Are you ready to go? >>Yeah, no, absolutely. And I think if you think about, if you think about it, right, I think it's also about doing this without impacting the primary application. Like if the customer is running a primary application at scale on s3, a backup application like ours can't come in and really mess with that. So I think being able to do things where, and this is where you solve really hard computer science problems, right? Where you're bottling yourself. If you are essentially seeing any kind of, you know, interfering with the primary, you're going to cut yourself down. You're gonna go after a different partition. So there are a lot of things you need to do behind the scenes, which is again, all the complexity, all of that, but deliver the, to the customer a very, very simple thing. >>You know, Paul, I wanna get your thoughts and I want you to chime in. Yeah. In 2014, I interviewed Steven Schmidt, my first interview with the, he was the CISO then, and now he's a CSO and, and former ciso, he's back at that time, the word was the cloud's not secure. Now we're talking about security. Just in the complexity of how you're partitioning and managing your sub portions, how you explained it, it's harder for the attackers. The cloud in its in its architecture has become a more secure environment. Yeah. Well, and getting more secure as you have laying out this, this is a new dynamic. This is good. Can you explain the, >>I mean, I, I can just tell you that at AWS security is job zero and that it will always be our number one priority, right? We have a, an infrastructure with under AWS that is vetted and approved to run even top secret workloads, which benefits all customers in all regions. >>And your, your security posture is embedded on top of that. And you got your own stuff. >>Yeah. And if you think of it as a shared responsibility model, so security of the cloud is the responsibility of the cloud provider, but then security of the data on top of it. Like you, you go and delete stuff, your software goes and does something that resiliency, the integrity of the data is your responsibility as a customer. And that's where, you know, we come in. Who >>Shared responsibility has been such a hot topic all week. Yeah. >>I gotta ask him one more question. Cause this is fascinating. And we are talking about on the cube all day today after we saw the announcement and Adam's comment on the cube, Adams LE's comment on the keynote. I mean, he said, if you're gonna tighten your belt, meaning economic cost recovery, re right sizing. If you want to tighten your belt, come to the cloud. So I have to ask you guys, Puja, if you can comment, that'd be great. There's a lot of other competitors out there that aren't born on aws. What is the customer gonna do when they tighten the build? What does that mean? They're gonna go to, to the individual contracts. They're gonna work in the marketplace. I mean this, there's a new dynamic in town. It's called AWS 2022. They weren't really around much in the recession of 2008. They were just starting to grow. Now they're an economic force. People like yourselves have embedded in there. There's a lot of competition. What's gonna happen? >>I think people are gonna just go to a place like, you know, AWS marketplace. You're going to essentially look for solutions and essentially like, and, and the right solutions built in are going to be self-service like aws. It's a very self-service thing. A hundred percent. So you go and do self-service, you figure out what's working, what's not working. Also, the model has to be consumption oriented. No longer can you expect the customer to go and pay a bunch of money for shelfware, right? It's like, like how we charge how AWS charges, which is you pay for what you consume. That and all has to be front and center, >>Right? I think that's a really, I think that's a really important >>Point. It's time >>And I think it's time. So we have a new challenge on the cube. We give you 30 seconds roughly to give us your extraordinarily hot take your shining thought leadership moment and, and highlight what you think is the most important takeaway from the show. The biggest soundbite, the juiciest announcement. Paul, I'll >>Start with an Instagram. Real basically. Yeah. Okay. >>Yeah. Hi. Go. I would just say from an S3 perspective, over the course of the last several years, we've really seen workloads shift from just backup and recovery and static images on websites to data lake analytics applications. And you continue to see that here. And I can tell you that some of these scaled applications are running at enormous mind blowing scale, right? And so, so every year we come here, we talk to customers, and it's just every year it sort of blows me away. And I've been in the storage industry for a long time and it's just is, it blows me away. Just the scale at customers are running in >>And >>Blowing scale. And when it comes to backup, let me just say that it's easy to back up and recover a single object, but doing an easy thing, a billion or 10 billion times over, that's actually quite hard. >>And just to, just to bold that a little bit, just pull out my highlighter. S3 now has over 280 trillion objects. That's a lot. >>That's a lot of objects. >>Yeah. You are not, you are not kidding. When you talk about scale, I mean, this is the most scalable. >>That's not solution's not there. Yeah. That, that's right. And we wake up every, we have a culture of durability and we wake up every single day to raise the bar on the fundamentals and make sure that every single one of those objects is protected and safe. >>Okay. You, I, >>I can't imagine worrying about two, two 80 trillion different things. >>Let's go. You're Instagram real >>For me again, you know, between S3 and us, we are two players out there that are really, you know, processing the data at the end of the day, right? And so I'm very excited about, you know, what we are going to do more and more with the instant restore capability where we can integrate third party services on top of it that can do more things with the data that is not, not passively sitting, but now becomes active data that you can analyze and do things with. So that's something where we take this to the next level is something that I'm super excited about. >>There's a lot to be excited about and, and we're excited to have you. We're excited to hear what happens next. Excited to see more collaboration like this. Paul Pon, thank you so much for joining us here on the show. Thank all of you from for tuning into our continuous wall to wall super thrilling live coverage of AWS reinvent here in fabulous Las Vegas, Nevada, with John Furrier. I'm Savannah Peterson. We're the cube, the leading source for high tech coverage.
SUMMARY :
This is the Cube we are at AWS Reinvent 2022 in Fabulous Sin We're Gonna have to figure out how to get us 20 as soon as possible. If you look at the minutes of the keynote of Adamski, the CEO on day one, it's all bulked into data Wonderful to have you both here. And effectively going after, you know, any service that And the relationship with aws. and the access you get and access you get to the service teams like Paul sitting here and the other teams you have gotten access What's the story there? of customers, and it's been a, it's just been a great relationship over the last years. What are the customers saying to you guys when you work backwards And so what folks have realized that as they're, you know, putting all of those, you know, what, Paul, do you want to kick one off? I, I'll talk about, you know, want to begin with like Cox Automotive, Well, how do you prioritize? And it's really been delivering on the fundamentals that has earned the trust of so many customers Like that is the first customer first discussions that we have with customers talking about durable So how do you navigate the, the security challenges, And it all starts with that visibility that you give. I mean you got Lambda. One of the things we launched that, you know, Paul and others are very excited about, is this ability to do instant Offer an inte application. Brought that part of the segment, John. Paul, geek out on with us on this. I mean, automation programmability. I mean, the RTO benefits alone are and you got this new functionality we're seeing emerge from the growth. And I think if you think about, if you think about it, right, I think it's also about doing this without Well, and getting more secure as you have laying I mean, I, I can just tell you that at AWS security is job zero and that And you got your own you know, we come in. Yeah. So I have to ask you I think people are gonna just go to a place like, you know, AWS marketplace. It's time shining thought leadership moment and, and highlight what you think is the Start with an Instagram. And I can tell you that some of these scaled applications are running at enormous And when it comes to backup, let me just say that it's easy to back up and recover a single object, And just to, just to bold that a little bit, just pull out my highlighter. When you talk about scale, I mean, this is the most scalable. And we wake up every, we have a culture of durability and we wake You're Instagram real you know, processing the data at the end of the day, right? Thank all of you from for tuning into our continuous wall to wall super thrilling
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Paul | PERSON | 0.99+ |
2014 | DATE | 0.99+ |
Adam | PERSON | 0.99+ |
Steven Schmidt | PERSON | 0.99+ |
Paul Pon | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Savannah Peterson | PERSON | 0.99+ |
John | PERSON | 0.99+ |
90% | QUANTITY | 0.99+ |
John Furrier | PERSON | 0.99+ |
Cox Automotive | ORGANIZATION | 0.99+ |
30 seconds | QUANTITY | 0.99+ |
Paul Meighan | PERSON | 0.99+ |
John Farer | PERSON | 0.99+ |
two players | QUANTITY | 0.99+ |
Warner Brothers | ORGANIZATION | 0.99+ |
Vegas | LOCATION | 0.99+ |
10 billion | QUANTITY | 0.99+ |
aws | ORGANIZATION | 0.99+ |
2022 | DATE | 0.99+ |
2008 | DATE | 0.99+ |
Puja | PERSON | 0.99+ |
Poojan Kumar | PERSON | 0.98+ |
second copy | QUANTITY | 0.98+ |
today | DATE | 0.98+ |
billions | QUANTITY | 0.98+ |
this year | DATE | 0.98+ |
one more question | QUANTITY | 0.98+ |
first interview | QUANTITY | 0.98+ |
20 | QUANTITY | 0.98+ |
Millions of customers | QUANTITY | 0.98+ |
One | QUANTITY | 0.97+ |
Adamski | PERSON | 0.97+ |
over 16 years | QUANTITY | 0.97+ |
tomorrow | DATE | 0.97+ |
Columbia | LOCATION | 0.97+ |
Las Vegas, Nevada | LOCATION | 0.97+ |
over 280 trillion objects | QUANTITY | 0.97+ |
10 years | QUANTITY | 0.97+ |
first customer | QUANTITY | 0.97+ |
10,000 | QUANTITY | 0.96+ |
ORGANIZATION | 0.96+ | |
both | QUANTITY | 0.96+ |
kuo | ORGANIZATION | 0.96+ |
S3 | TITLE | 0.96+ |
Clumio | PERSON | 0.95+ |
Pujan | ORGANIZATION | 0.95+ |
billions of objects | QUANTITY | 0.95+ |
23 | QUANTITY | 0.95+ |
two | QUANTITY | 0.95+ |
a billion | QUANTITY | 0.94+ |
Lambdas | TITLE | 0.94+ |
over two 50 trillion objects | QUANTITY | 0.94+ |
first discussions | QUANTITY | 0.93+ |
ES | TITLE | 0.93+ |
single object | QUANTITY | 0.93+ |
this week | DATE | 0.92+ |
dynamo | ORGANIZATION | 0.92+ |
single bucket | QUANTITY | 0.92+ |
Fabulous Sin City | LOCATION | 0.92+ |
Cube | COMMERCIAL_ITEM | 0.9+ |
s3 | TITLE | 0.9+ |
CUO | ORGANIZATION | 0.89+ |
Aruba | LOCATION | 0.89+ |
80 trillion | QUANTITY | 0.88+ |
Adams LE | PERSON | 0.88+ |
glacier | ORGANIZATION | 0.87+ |
s3 | ORGANIZATION | 0.85+ |
Joni Klippert, StackHawk | theCUBE on Cloud 2021
>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. Welcome to the cubes event. Virtual event. Cuban Cloud. I'm John for your host. We're here talking to all the thought leaders getting all the stories around Cloud What's going on this year and next today, Tomorrow and the future. We gotta featured startup here. Jonah Clipper, who is the CEO and founder of Stack Hawks. Developing security software for developers to have them put security baked in from the beginning. Johnny, thanks for coming on and being featured. Start up here is part of our Cuban cloud. Thanks for joining. >>Thanks so much for having me, John. >>So one of our themes this year is obviously Cloud natives gone mainstream. The pandemic has shown that. You know, a lot of things have to be modern. Modern applications, the emerald all they talked about modern applications. Infrastructure is code. Reinvent, um is here. They're talking about the next gen enterprise. Their public cloud. Now you've got hybrid cloud. Now you've got multi cloud. But for developers, you just wanna be building security baked in and they don't care where the infrastructure is. So this is the big trend. Like to get your thoughts on that. But before we jump in, tell us about Stack Hawk What you guys do your founded in 2019. Tell us about your company and what Your mission is >>Awesome. Yeah, our mission is to put application security in the hands of software developers so that they can find and fix upset books before they deployed a production. And we do that through a dynamic application scanning capability. Uh, that's deployable via docker, so engineers can run it locally. They can run it in C I C. D. On every single PR or merge and find bugs in the process of delivering software rather than after it's been production. >>So everyone's talking about shift left, shift left for >>security. What does >>that mean? Uh, these days. And what if some of the hurdles that people are struggling with because all I hear is shift left shift left from, like I mean, what does What does that actually mean? Now, Can you take us through your >>view? Yes, and we use the phrase a lot, and I and I know it can feel a little confusing or overused. Probably. Um, When I think of shift left, I think of that Mobius that we all look at all of the time, Um, and how we deliver and, like, plan, write code, deliver software and then manage it. Monitor it right like that entire Dev ops workflow. And today, when we think about where security lives, it either is a blocker to deploying production. Or most commonly, it lives long after code has been deployed to production. And there's a security team constantly playing catch up, trying to ensure that the development team whose job is to deliver value to their customers quickly, right, deploy as fast as we can, as many great customer facing features, um there, then, looking at it months after software has been deployed and then hurrying and trying to assess where the bugs are. And, um, trying to get that information back to software developers so that they can fix those issues. Shifting left to me means software engineers are finding those bugs as their writing code or in the CIA CD pipeline long before code has been deployed to production. >>And so you guys attack that problem right there so they don't have to ship the code and then come back and fix it again. Or where we forgot what the hell is going on. That point in time some Q 18 gets it. Is that the kind of problem that that's out there? Is that the main pain point? >>Yeah, absolutely. I mean a lot of the way software, specifically software like ours and dynamic applications scanning works is a security team or a pen tester. Maybe, is assessing applications for security vulnerability these, um, veteran prod that's normally where these tools are run and they throw them back over the wall, you know, interrupting sprints and interrupting the developer workflow. So there's a ton of context switching, which is super expensive, and it's very disruptive to the business to not know about those issues before they're in prod. And they're also higher risk issues because they're in fraud s. So you have to be able to see a >>wrong flywheel. Basically, it's like you have a penetration test is okay. I want to do ship this app. Pen test comes back, okay? We gotta fix the bug, interrupts the cycle. They're not coding there in fire drill mode. And then it's a chaotic death spiral at that point, >>right? Or nothing gets done. God, how did >>you What was the vision? How did you get here? What? How did you start? The company's woke up one morning. Seven started a security company. And how did what was the journey? What got you here? >>Sure. Thanks. I've been building software for software engineers since 2010. So the first startup I worked for was very much about making it easy for software engineers to deploy and manage applications super efficiently on any cloud provider. And we did programmatic updates to those applications and could even move them from cloud to cloud. And so that was sort of cutting my teeth and technology and really understanding the developer experience. Then I was a VP of product at a company called Victor Ops. We were purchased by spunk in 2018. But that product was really about empowering software engineers to manage their own code in production. So instead of having a network operations center right who sat in front of screens and was waiting for something to go wrong and would then just end up dialing there, you know, just this middle man trying to dial to find the person who wrote the software so that they can fix it. We made that way more efficient and could just route issues to software engineers. And so that was a very dev ops focused company in terms of, um, improving meantime to know and meantime to resolve by putting up time in the hands of software engineers where it didn't used to live there before it lived in a more traditional operations type of role. But we deploy software way too quickly and way too frequently to production to assume that another human can just sit there and know how to fix it, because the problems aren't repeatable, right? So So I've been living in the space for a long time, and I would go to conferences and people would say, Well, I love for, you know, we have these digital transformation initiatives and I'm in the security team and I don't feel like I'm part of this. I don't know. I don't know how to insert myself in this process. And so I started doing a lot of research about, um, how we can shift this left. And I was actually doing some research about penetration testing at the time, Um, and found just a ton of opportunity, a ton of problems, right that exist with security and how we do it today. So I really think of this company as a Dev Ops first Company, and it just so happens to be that we're taking security, and we're making it, um, just part of the the application testing framework, right? We're testing for security bugs, just like we would test for any other kind of bucks. >>That's an awesome vision of other great great history there. And thanks for sharing that. I think one of the things that I think this ties into that we have been reporting aggressively on is the movement to Dev Stack Up, Dev, Ops Dev SEC Ops. And you know, just doing an interview with the guy who stood up space force and big space conversation and were essentially riffing on the idea that they have to get modern. It's government, but they got to do more commercial. They're using open source. But the key thing was everything. Software defined. And so, as you move into suffer defined, then they say we want security baked in from the beginning and This is the big kind of like sea level conversation. Bake it in from the beginning, but it's not that easy. And this is where I think it's interesting where you start to think, uh, Dev ops for security because security is broken. So this is a huge trend. It sounds easy to say it baked security in whether it's an i o T edge or multi cloud. There's >>a lot >>of work there. What should people understand when they hear that kind of platitude of? I just baked security and it's really easy. It's not. It's not trivial. What's your thoughts on >>that? It isn't trivial. And in my opinion, there aren't a lot of tools on the market that actually make that very easy. You know, there are some you've had sneak on this program and they're doing an excellent job, really speaking to the developer and being part of that modern software delivery workflow. Um, but because a lot of tools were built to run in production, it makes it really difficult to bake them in from the beginning. And so, you know, I think there are several goals here. One is you make the tooling work so that it works for the software engineer and their workflow. And and there's some different values that we have to consider when its foreign engineer versus when it's for a security person, right? Limit the noise, make it as easy as possible. Um, make sure that we only show the most critical things that are worth an engineer. Stopping what they're doing in terms of building business value and going back and fixing that bugs and then create a way to discuss in triage other issues later outside of the development. Workflow. So you really have to have a lot of empathy and understanding for how software is built and how software engineers behave, I think, in order to get this right. So it's not easy. Um, but we're here and other tools air here. Thio support companies in doing that. >>What's the competitive strategy for you guys going forward? Because there's a big sea change. Now I see an inflection point. Obviously, Cove it highlights. It's not the main reason, but Cloud native has proven it's now gone mainstream kubernetes. You're seeing the big movement there. You're seeing scale be a huge issue. Software defined operations are now being discussed. So I think it's It's a simple moment for this kind of solution. How are you guys going to compete? What's what's the winning strategy? How are you guys gonna compete to win? >>Yeah, so there's two pieces to that one is getting the technology right and making sure that it is a product that developers love. And we put a ton of effort into that because when a software engineer says, Hey, I'd love to use the security product, right? CSOs around the world are going to be like, Yes, please. Did a software engineer just ask me, You have the security product. Thank you, Right. We're here to make it so easy for them and get the tech right. And then the other piece, in terms of being competitive, is the business model. There were something like, I don't You would know better than me, but I think the data point I last saw was like 1300 venture backed security companies since 2012 focused on selling to see SOS and Fortune 2000 companies. It is a mess. It's so noisy, nobody can figure out what anybody actually does. What we have done is said no, we're going to take a modern business model approach to security. So you know, it's a SAS platform that makes it super easy for a software engineer or anybody on the team to try and buy the software. So 14 day trial. You don't have to talk to anybody if you don't want Thio Awesome support to make sure that people can get on boarded and with our on boarding flow, we've seen that our customers go from signing up to first successful scan of their platform or whatever app they chose to scan in a knave ridge of about 10 minutes. The fastest is eight, right? So it's about delivering value to our customers really quickly. And there aren't many companies insecurity on the market today. That do that? >>You know, you mentioned pen test earlier. I I hear that word. Nice shit. And, like, pen test penetration test, as it's called, um, Sock reports. I mean, these are things that are kind of like I got to do that again. I know these people are doing things that are gonna be automated, but one of the things that cloud native has proven as be killer app is integrations because when you build a modern app, it has to integrate with someone else. So there you need these kind of pen tests. You gotta have this kind of code review. And as code, um, is part of, say, a purpose built device where it's an I o T. Edge updates have toe happen. So you need mawr automation. You need more scale around both updating software to, ah, purpose built device or for integration. What's your thoughts in reaction to that? Because this is a riel software challenge from a customer standpoint, because there are too many tools out there and every see so that I talk to says, I just want to get rid of half the tools consolidate down around my clouds that I'm working through my environment and b'more developer oriented, not just purchasing stuff. So you have all this going on? What's your reaction to that? You got the you know, the integration and you've got the software updates on purpose built devices. >>Yeah, I mean, we I make a joke a little bit. That security land is like, you know, acronyms. Dio there are so many types of security that you could choose to implement. And they all have a home and different use cases that are certainly valuable toe organizations. Um, what we like to focus on and what we think is interesting and dynamic application scanning is because it's been hard toe automate dynamic application for especially for modern applications. I think a lot of companies have ignored theon pertuan ity Thio really invest in this capability and what's cool about dynamic. And you were mentioning pen testing. Is that because it's actively attacking your app? It when you get a successful test, it's like a It's like a successful negative test. It's that the test executed, which means that bug is present in your code. And so there's a lot less false positives than in other types of scanning or assessment technologies. Not to say there isn't a home for them. There's a lot of we could we could spend a whole hour kind of breaking down all the different types of bugs that the different tools confined. Um, but we think that if you want to get started developer first, you know there's a lot of great technologies. Pick a couple or one right pick stack hawk pick, sneak and just get started and put it in your developer workflow. So integrations are super important. Um, we have integrations with every C I C. D provider, making it easy to scan your code on every merge or release. And then we also have workflow integrations for software engineers associated with where they want to be doing work and how they want to be interrupted or told about an issue. So, you know, we're very early to market, but right out of the gate, we made sure that we had a slack integration so that scans are running. Or as we're finding new things, it's populating in a specific slack channel for those engineers who work on that part of the app and you're a integration right. If we find issues, we can quickly make tickets and route them and make sure that the right people are working on those issues. Eso That's how I think about sort of the integration piece and just getting started. It's like you can't tackle the whole like every accurate, um, at once like pick something that helps you get started and then continue to build out your program, as you have success. >>A lot of these tools can they get in the hands of developers, and then you kind of win their trust by having functionality. Uh, certainly a winning strategy we've seen. You know, Splunk, you mentioned where you worked for Data Dog and very other tools out there just get started easily. If it's good, it will be used. So I love that strategy. Question. I wanna ask you mentioned Dr earlier. Um, they got a real popular environment, but that speaks to the open source area. How do you see the role of open source playing with you guys? Is that gonna be part of your community outreach? Does the feed into the product? Could you share your vision on how stack hawks engaging and playing an open source? >>Yeah, absolutely. Um So when we started this company, my co founders and I, we sat down and said here, What are the problems? Okay, the world doesn't need a better scanner, right? If you walk the floor of, ah, security, uh, conference. It's like our tool finds a million things and someone else is. My tool finds a million and five things. Right, And that's how they're competing on value. It's really about making it easy to use and put in the pipeline. So we decided not to roll. Our own scanner were based on an open source capability called Zap the Set Attack Proxy. Uh, it is the most the world's most downloaded application scanner. And, uh, actually we just hired the founder of Zap to join the Stack Hawk team, and we're really excited to continue to invest in the open source community. There is a ton of opportunity to grow and sort of galvanize that community. And then the work that we do with our customers and the feedback that we get about the bugs we find if there, ah, false positive or this one's commonly risk accepted, we can go back to the community, which were already doing and saying, Hey, ditch this rule, Nobody likes it or we need to improve this test. Um, so it's a really nice relationship that we have, and we are looking forward to continuing to grow that >>great stuff. You guys are hot. Start of love. The software on security angle again def sec. Cox is gonna be It's gonna be really popular. Can you talk about some of the customer success is What's the What's the feedback from customers? Can you share some of the use cases that you guys are participating in where you're winning? You mentioned developers love it and try It can just give us a couple of use cases and examples. >>Yeah. Ah, few things. Um ah, lot of our customers are already selling on the notion. Like before we even went to G A right. They told all of their customers that they scan for security bugs with every single release. So in really critical, uh, industry is like fintech, right. It's really important that their customers trust that they're taking security seriously, which everybody says they dio. But they show it to their customers by saying here, every single deploy I can show you if there were any new security bugs released with that deploy. So that's really awesome. Other things We've heard our, uh, people being able to deploy really quickly thio the Salesforce marketplace, right? Like if they have toe have a scan to prove that that they can sell on Salesforce, they do that really rapidly. Eso all of that's going really well with our customers. >>How would I wanna How would I be a customer if I was interested in, um, using Stack Hawks say we have some software we wanna stand up, and, uh, it's super grade. And so Amazon Microsoft Marketplace Stairs Force They'll have requirements or say I want to do a deal with an integration they don't want. They want to make sure there's no nothing wrong with the code. This seems to be a common use case. How doe I if I was a customer, get involved or just download software? Um, what's the What's the procurement? What's the consumption side of it looked like, >>Yeah, you just go to Stockholm dot com and you create an account. If you'd like to get started that way so you can have a 14 day free trial. We have extremely extensive documentation, so it's really easy to get set up that way. You should have some familiarity. Or grab a software engineer who has familiarity with a couple of things. So one is how to use Docker, right? So Docker is, ah, deployment mechanism for the scanner. We do that so you can run it anywhere that you would like to, and we don't have to do things like pierce firewalls or other protective measures that you've instrumented on your production environment. You just run it, um, wherever you like in your system. So locally, C I c d So docker is an important thing to understand the way we configure our scanner is through a, um, a file. So if you are getting a scan today, either your security team is doing it or you have a pen tester doing it. Um, the whole like getting ready for that engagement takes a lot of time because the people who are running the tests don't know how the software was built. So the way we think about this is, just ask them. So you just fill out a Yamil file with parameters that tell the scanner what to dio tell it how to authenticate and not log out. Um, feed us an A p. I speak if you want, so weaken super efficiently, scan your app and you can be up and running really quickly, and then that's it. You can work with our team at any time if you need help, and then we have a really efficient procurement process >>in my experience some of the pen tests of firms out there, is it? It's like the house keeping seal of approval. You get it once and then you gotta go back again. Software change, new things come in. And it's like, Wait a minute, what's the new pen test? And then you to write a check or engaged to have enough meeting? I mean, this is the problem. I mean, too many meetings. Do you >>guys solve that problem? Do >>you solve that problem? >>We solve a piece of that problem. So I think you know, part of how I talk about our company is this idea that we live in a world where we deploy software every single day. Yet it seems reasonable that once a year or twice a year, we go get a pen test where human runs readily available, open source software on our product and gives us a like, quite literal. Pdf of issues on. It's like this is so intellectually dishonest, like we deploy all of the time. So here's the thing. Pen tests are important and everybody should do them. But that should not be the introduction to these issues that are also easy to automate and find in your system. So the way we think about how we work with pen testers is, um, run, stack hawk or zapped right in an automated fashion on your system, and then give that, give the configuration and give the most recent results to your pen tester and say, Go find the hard stuff. You shouldn't be cutting checks for $30,000 to a pen tester or something that you could easily meet in your flare up. Klein. You could write the checks for finding finding the hard stuff that's much more difficult to automate. >>I totally agree. Final question. Business model Once I get in, is it a service software and services? A monthly fee? How do you guys make money? >>Yep, it is software as a service, it is. A monthly fee were early to market. So I'm not going to pretend that we have perfectly cracked the pricing. Um, but the way that we think about this is this is a team product for software engineers and for, you know, informed constituents, right? You want a product person in the product. You want a security person in the product? Um, and we also want to incent you to scan your APS And the most modern fashion, which is scanning the smallest amount of http that lives in your app, like in a micro services architecture because it makes a lot easier, is easy to isolate the problems where they live and to fix those issues really quickly. So we bundle team and for a UPS and then we scale within, uh, companies as they add more team. So pen users. 10 APS is 3 99 a month. And as you add software engineers and more applications, we scale within your company that way. >>Awesome. So if you're successful, you pay more, but doesn't matter. You already succeeded, and that's the benefit of by As you go Great stuff. Final question. One more thing. Your vision of the future. What are the biggest challenges you see in the next 24 months? Plus beyond, um, that you're trying to attack? That's a preferred future that you see evolving. What's the vision? >>Yeah, you've touched on this a couple of times in this interview with uh being remote, and the way that we need to build software already has been modernizing, and I feel like every company has a digital transformation initiative, but it has toe happen faster. And along with that, we have to figure out how Thio protect and secure these Moderna Gail. The most important thing that we do the hearts and minds of our support engineers and make it really easy for them to use security capabilities and then continue to growth in the organization. And that's not an easy thing tied off. It's easy change, a different way of being security. But I think we have to get their, uh, in order to prepare the security, uh, in these rapidly deployed and developed applications that our customers expect. >>Awesome. Jodi Clippers, CEO and founder of Stack Hawk. Thank you for coming on. I really appreciate it. Thanks for spending the time featured Startup is part of our Cuban cloud. I'm Sean for your host with silicon angle to Cube. Thanks for watching
SUMMARY :
cloud brought to you by silicon angle. But before we jump in, tell us about Stack Hawk What you guys do your founded in 2019. And we do that through a dynamic application scanning capability. What does Can you take us through your look at all of the time, Um, and how we deliver and, And so you guys attack that problem right there so they don't have to ship the code and then come back I mean a lot of the way software, specifically software like ours and Basically, it's like you have a penetration test is okay. right? How did you get here? as a Dev Ops first Company, and it just so happens to be that we're taking security, And this is where I think it's interesting where you start to think, uh, Dev ops for security because What's your thoughts on And so, you know, What's the competitive strategy for you guys going forward? So you know, it's a SAS platform that You got the you know, the integration and you've got the software Um, but we think that if you want to get started developer first, A lot of these tools can they get in the hands of developers, and then you kind of win their trust by having Um, so it's a really nice relationship that we have, and we are looking forward to continuing Can you share some of the use cases that you guys are participating by saying here, every single deploy I can show you if there were any new security bugs released What's the consumption side of it looked like, So the way we think about this is, just ask them. And then you to write a check or engaged to have enough So the way we think about how we work with pen testers is, How do you guys make money? Um, and we also want to incent you to scan your APS What are the biggest challenges you see in the next 24 months? being remote, and the way that we need to build software already has been Thank you for coming on.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jonah Clipper | PERSON | 0.99+ |
$30,000 | QUANTITY | 0.99+ |
Joni Klippert | PERSON | 0.99+ |
2019 | DATE | 0.99+ |
Johnny | PERSON | 0.99+ |
2018 | DATE | 0.99+ |
Jodi Clippers | PERSON | 0.99+ |
14 day | QUANTITY | 0.99+ |
John | PERSON | 0.99+ |
two pieces | QUANTITY | 0.99+ |
Victor Ops | ORGANIZATION | 0.99+ |
first | QUANTITY | 0.99+ |
eight | QUANTITY | 0.99+ |
this year | DATE | 0.99+ |
Zap | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
about 10 minutes | QUANTITY | 0.99+ |
Sean | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Splunk | PERSON | 0.98+ |
2010 | DATE | 0.98+ |
a million things | QUANTITY | 0.98+ |
2012 | DATE | 0.98+ |
Tomorrow | DATE | 0.98+ |
one | QUANTITY | 0.97+ |
first startup | QUANTITY | 0.97+ |
Dev Ops | ORGANIZATION | 0.97+ |
CIA | ORGANIZATION | 0.97+ |
Data Dog | ORGANIZATION | 0.96+ |
Stack Hawk | ORGANIZATION | 0.96+ |
once a year | QUANTITY | 0.95+ |
3 99 a month | QUANTITY | 0.95+ |
twice a year | QUANTITY | 0.95+ |
Cuban | OTHER | 0.94+ |
SOS | ORGANIZATION | 0.94+ |
pandemic | EVENT | 0.94+ |
both | QUANTITY | 0.93+ |
Klein | PERSON | 0.93+ |
One | QUANTITY | 0.92+ |
one morning | QUANTITY | 0.91+ |
tools | QUANTITY | 0.91+ |
Mobius | ORGANIZATION | 0.9+ |
Cube | ORGANIZATION | 0.9+ |
half | QUANTITY | 0.9+ |
Stack Hawk | PERSON | 0.9+ |
One more thing | QUANTITY | 0.9+ |
Docker | TITLE | 0.89+ |
next 24 months | DATE | 0.87+ |
1300 venture | QUANTITY | 0.87+ |
Stack Hawks | ORGANIZATION | 0.87+ |
G A | ORGANIZATION | 0.86+ |
Cox | ORGANIZATION | 0.86+ |
Q | TITLE | 0.85+ |
a million and | QUANTITY | 0.84+ |
single day | QUANTITY | 0.84+ |
Cloud | TITLE | 0.81+ |
14 day free | QUANTITY | 0.79+ |
first Company | QUANTITY | 0.78+ |
C | TITLE | 0.77+ |
Stockholm dot com | ORGANIZATION | 0.77+ |
next today | DATE | 0.77+ |
docker | ORGANIZATION | 0.76+ |
five things | QUANTITY | 0.75+ |
10 APS | QUANTITY | 0.74+ |
StackHawk | ORGANIZATION | 0.73+ |
Fortune | ORGANIZATION | 0.71+ |
Salesforce | ORGANIZATION | 0.71+ |
Microsoft | ORGANIZATION | 0.7+ |
spunk | ORGANIZATION | 0.7+ |
a whole hour | QUANTITY | 0.69+ |
couple | QUANTITY | 0.69+ |
Cove | PERSON | 0.68+ |
too many tools | QUANTITY | 0.67+ |
UPS | ORGANIZATION | 0.67+ |
single release | QUANTITY | 0.66+ |
single | QUANTITY | 0.64+ |
minute | QUANTITY | 0.63+ |
theCUBE | ORGANIZATION | 0.63+ |
18 | OTHER | 0.62+ |
Seven | QUANTITY | 0.62+ |
use cases | QUANTITY | 0.61+ |
Dr. Taha Kass-Hout, AWS | AWS re:Invent 2020
>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 >>sponsored by >>Intel and AWS. Yeah, Welcome back to the cubes. Ongoing coverage of aws reinvent virtual the Cuba has gone virtual to. We're gonna talk about machine intelligence, cloud and transformation in healthcare. An industry that is rapidly evolving and reinventing itself to provide better quality care faster and more accurate diagnoses. And this has to be done at lower cost. And with me to talk about This is Dr Taha. Awesome. Who? Who is the director of machine learning at Amazon Web services? Doctor, good to see you again. Thanks for coming on. >>Thank you so much. Good to see Dave. >>Yeah, last time we talked, I think it was a couple of years ago. We remember we were talking about Amazon. Comprehend medical. And, of course, you've been so called so called raising the bar, so to speak, Over the past 24 months, you made some announcements today, including Amazon Health Lake, which we're gonna talk about. Tell us about it. >>Well, we're really excited about eso our customers. Amazon Half Lake, a new hip eligible service for health care providers health insurance companies and pharmaceutical companies to securely store, transform Aquarian, analyze health data in the cloud at petabytes scale, a Amazon health lake uses machine learning models trained to automatically understand context and extract meaningful data from medical data from raw, disparate information such as medications, procedures, Um, and diagnosis. Um Therefore, revolutionizing a process that was traditionally manual Arab prone and highly costly requires a lot of expertise on teams within these organizations. What healthcare Catholic does is it tags and indexes every piece of information on then structure in an open standard. The fire standard, or that's the fast healthcare interoperability resource, is in order to provide a complete view 360 degree view of each patient in a consistent way so you'll be able to curry and share that data securely. It also integrates with other machine learning services and a lot of services that AWS offers, such as Amazon Quicksight or Amazon sage maker. In order to visualize and understand the relationships in the data identify trends, Andi also make predictions. The other great benefit is since the Amazon health lake automatically structures all the health care organizations data into open standard. The fire industry format. The information now can be easily and securely shared between systems. Health systems onda with third party applications. So eso providers, health care providers will will enjoy the ability to collaborate more effectively with each other but also allowing patients and federal access to their medical information. >>I think now, so one of things that people are gonna ask is Okay, wait a minute. Hip eligible Is that like cable ready or HD ready? And but people need to understand that it's a shared responsibility. But you can't come out of the box and be HIPPA compliant there a number of things and processes, uh, that that your customer has to do. Maybe you could explain that a little >>bit. Absolutely. I mean, in practice a little bit. This is a very, very important thing, and and it's something that we really fully baked into the service and how we built Also the service, especially dealing with health care information. First off, AWS, as you know, is vigilant about customers, privacy and security. It is job zero for us. Your data and Health Lake is secure, compliant, and auditable data version is enabled to protect um, the data against any accident collision, for example, and per fire sophistication. If you are to delete one piece of data, it will be version it will be on Lee. Hidden from analysis is a result not believed from the service. So your dad is always encrypted on by using your own customer. Manage key in a keys in a single tenant. Architectures is another added benefit to provide the additional level of protection when the data is access and search for example, every time inquiry a value, for example, someone's glucose level if the data is encrypted and decrypted and and and and so on and so forth. So, additionally, this system in a single tenant architectures so that that way the data, uh, the key. The same key is not shared across multiple customers. So you're saying full ownership and control of your data along with the ability to encrypt, protect move, deleted in alignment with organization, security and policies. Now a little bit about the hip eligibility. It's a term that AWS uses eso for customers storing protected health information or P h. I A. DBS by its business associate agreement on also Business Associate amendment require customers to encrypt data addressed in transit when they're using area services. There are over 100 services today. They're hip eligible, including the Amazon. Health like this is very important, especially for, uh enabling discovered entities and their business associates subject to HIPAA regulations, and is be able to kind of and this shared model between what a the best protection and services and how it can process and store and managed ph I. But there's additional level of compliance is required on the on the customer side, um, about you know, anywhere from physical security thio how each application can be built, which is no different than how you manage it. For example, today in your own that data center, what not? But this is why many cats, growing number of health care providers, um, players as well as I, because professionals are using AWS utility based cloud services today to process, store and transmit pH. I. >>So tell us more about who was gonna benefit from this new capability, what types of organizations and would be some of the outcomes for for for patients, >>absolutely every healthcare provider today, or a payer like a health insurance company or a life. Science companies such as Pharma Company is just trying to solve the problem of organizing instruction their data. Because if you do, you make better sense of this information from better patient support decisions. Design better clinical trials, operate more efficiently, understand population health trends on be able them to share that that security. It's really all starts with making sense of that of that data. And those are the ultimate customers that we're trying to empower with the Amazon Amazon Health Lake. Um, >>well, And of course, there's downstream benefits for the patient. Absolutely. That's ultimately what we're trying to get to. I mean, absolutely. I mean, I set up front. I mean, it's it's everybody you know, feels the pain of high health care costs. A lot of times you're trying to get to see a doctor, and it it takes a long time now, especially with with covitz so and much of this, oftentimes it's even hard to get access to your own data s. So I think you're really trying to attack that problem. Aren't >>you absolutely give you a couple of examples like I mean, today, the most widely used clinical models, uh, in practice to predict. Let's say someone's disease risk lack personalization. Um, it's you and I can be lumped in the same in the same bucket, for example, based on a few attributes that common, UM, data elements or data points, which is problematic also because the resulting models produce are imprecise. However, if you look at an individual's medical records, for example, you know a diabetic type two diabetic patients there, if you look at the entire history and from all this information coming to them, whether it's doctor knows medication dosages, which line of treatment the second line treatment, uh, continuous monitoring of glucose and that sort of thing is over hundreds. You know, there are hundreds of thousands of data points in their entire medical history, but none of this is used today. At the point of care on. You want all this information to be organized, aggregated, structured in a way that you will be able to build even better models easily queried this information, aan den observed the health of the individual in comparison with the rest of the population because at that point you'll be able to make those personalized decisions and then also for patient engagement with the health lake ability to now emit data back on dshea air securely the a p i s that conform to the fire standard. So third party applications can be built also, um, Thio provide the access whether that's for analytics or digital health application, for example, a patient accident, that information all that is very, very, very important. Because ultimately you wanna, um, get at better care of these these populations better. In Roma, clinical trials reduce duplicative tests and waste and health care systems. All that comes when you have your entire information available in a way that structured and normalize on be able to Korean and analyze andan the seamless integration between the health lake and the arrest of the services like Amazon sage maker. You can really start to understand relationships and meaning of the information, build better, better decision support models and predictive models at the individual on a population level. >>Yeah, right. You talked about all this data that's not not really used on. It's because it's not accessible. I presume it's not in in one place that somebody can analyze its not standardized. It's not normalized. Uh, is that >>right, that is the biggest. That is the biggest challenge for every healthcare provider, pair or life science organization today. If you look at this data, it's difficult to work with. Medical health. Data is really different that I siloed spread out across multiple systems, and it's sort of not incompatible formats. If you look at the last decade, I mean, one of the greatest things is we witnessed a great transformation healthcare towards digitization of the record. But your data is scattered across many of these systems anywhere from found your family history, the clinical observation, diagnosis and treatment. When you see the vast majority of that data is contained in unstructured medical records like Dr Notes P. D efs of insurance, um, of laboratory reports or insurance claims and forms with the With With Covad, we've seen in quite a bit of uptake of digital sort of, um uh, delivery of care such as telemedicine and recorded audios and videos, X rays and images, uh, the large propagation of digital health, APS and and digital assistances and on and wearables and as well as these sort of monitors like glucose, monitor or not, data come in all shapes and form and form and start across all these things. It's a huge heavy lift for any health care organization to be able to aggregate normalized stored securely on. Then also be able to kind of analyze this information and structure in a way that zizi to scale. Um uh, with regards, Thio, the kind of problems that you're going after. >>Well, Dr Cox, who We have to leave it there. Thank you so much. I have been saying for years in the Cube. When is it? That machine's gonna be able to make it make better diagnoses than doctors. Maybe that's the wrong question. Maybe it's machines helping doctors make faster and more accurate diagnoses and lowering our costs. Thanks so much for coming. >>Thank you very much. Appreciate it. Thank you. >>Thank you for watching everybody keep it right there. This is Dave Volonte. We'll be back with more coverage of aws reinvent 2020. You virtual right after this short break
SUMMARY :
It's the Cube with digital Doctor, good to see you again. Thank you so much. so to speak, Over the past 24 months, you made some announcements today, including Amazon Health or that's the fast healthcare interoperability resource, is in order to provide a complete And but people need to understand that it's a shared responsibility. of compliance is required on the on the customer side, Because if you do, you make better sense of this information much of this, oftentimes it's even hard to get access to your own data s. All that comes when you have your entire information is that If you look at the last decade, I mean, one of the greatest things is we witnessed a great transformation Thank you so much. Thank you very much. Thank you for watching everybody keep it right there.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Volonte | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Thio | PERSON | 0.99+ |
360 degree | QUANTITY | 0.99+ |
Taha | PERSON | 0.99+ |
Cox | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Taha Kass-Hout | PERSON | 0.99+ |
Roma | LOCATION | 0.99+ |
HIPAA | TITLE | 0.99+ |
over 100 services | QUANTITY | 0.99+ |
today | DATE | 0.98+ |
Intel | ORGANIZATION | 0.97+ |
each application | QUANTITY | 0.97+ |
one piece | QUANTITY | 0.97+ |
one | QUANTITY | 0.97+ |
First | QUANTITY | 0.95+ |
Amazon Web | ORGANIZATION | 0.94+ |
Arab | OTHER | 0.94+ |
Health Lake | COMMERCIAL_ITEM | 0.93+ |
one place | QUANTITY | 0.93+ |
aws | ORGANIZATION | 0.92+ |
each patient | QUANTITY | 0.92+ |
last decade | DATE | 0.92+ |
over hundreds | QUANTITY | 0.9+ |
a minute | QUANTITY | 0.87+ |
Health Lake | ORGANIZATION | 0.87+ |
second line treatment | QUANTITY | 0.86+ |
2020 | DATE | 0.84+ |
months | DATE | 0.84+ |
Lake | ORGANIZATION | 0.84+ |
hundreds of thousands of data points | QUANTITY | 0.83+ |
couple of years ago | DATE | 0.83+ |
Catholic | ORGANIZATION | 0.83+ |
petabytes | QUANTITY | 0.82+ |
Dr Notes P. | ORGANIZATION | 0.81+ |
With With Covad | ORGANIZATION | 0.79+ |
Half Lake | COMMERCIAL_ITEM | 0.79+ |
Andi | PERSON | 0.75+ |
job | QUANTITY | 0.72+ |
single tenant | QUANTITY | 0.71+ |
years | QUANTITY | 0.7+ |
two diabetic patients | QUANTITY | 0.69+ |
Cuba | LOCATION | 0.68+ |
2020 | TITLE | 0.68+ |
Korean | LOCATION | 0.65+ |
health lake | COMMERCIAL_ITEM | 0.65+ |
Dr | PERSON | 0.58+ |
past | DATE | 0.57+ |
Cube | COMMERCIAL_ITEM | 0.55+ |
Health | COMMERCIAL_ITEM | 0.54+ |
Dr. | PERSON | 0.52+ |
lake | ORGANIZATION | 0.49+ |
24 | QUANTITY | 0.45+ |
Aquarian | TITLE | 0.44+ |
Lee | ORGANIZATION | 0.43+ |
Quicksight | TITLE | 0.41+ |
DBS | ORGANIZATION | 0.4+ |
Sizzle Reel | Splunk .conf19
so it definitely fits into basic being able to automate the redundant main mundane types of tasks that anyone can do right so you if you think about it if you have a security operations center with five or ten analysts it might take one analyst to do a task make two comes two or three hours and where you can leverage a tool like Sansom any type of sort platform to actually create a playbook to do that tasks within 30 seconds so not only are you minimizing the amount of you know headcount to do that you're also you know using your consistent tool to make that folks should make the function of you know more I want to say enhanced so you can build playbooks around it you can basically use that on a daily basis whether it's for security monitoring or network operations reporting all that becomes and the impact of mine thank you so what we do is we are a data analytics and intelligence nonprofit dedicated to countering all forms of human trafficking whether it's labor trafficking sex King or any of the subtypes men women and children all over the world so when you think about that what that really means is that we interact with thousands of state across law enforcement government nonprofits academia and then the private sector as well and all of those essentially act as data silos for human trafficking data and when you think about that as trafficking as a data problem or you tackle it as a data problem what that really means is that you have to have a technology and data led solution in order to solve the problem so that's really our mission here is to bring together all of those stakeholders give them easy access to tools that can help improve their counterpose yeah so like a day to day or like kind of what our team does is we focus on like what's going on previously what are we seeing in the wild like what campaigns are happening and then my role within my team is focused on what's coming so what are what are red team's working on what are pen testers looking into take that information begin testing it begin building proof of concepts put that back into our product so that whether it's two weeks six months two years we have coverage for it no matter what so a lot of us a lot of our time is generating proof of concepts on what may be coming so there's a lot of you know very unique things that maybe in the wild today and then there's some things that we may never see that are just very novel and kind of once one Center once a time kind of thing I joined nine months ago and when I was interviewing for the role I remember Doug Merritt saying to me hey you know we might be the only two billion dollar enterprise software company that nobody's ever heard of he said I want to go solve for that right like the folks you know Splunk and our customers they love us our product is awesome and our culture is awesome but the world doesn't know about us yet and we haven't invested there so I want to go take the brand to the next level and I want the world to understand what data use cases are out there that are so broad and so vast leave that every problem ultimately can be solved through data are almost every problem and we wanted to set the stage for that with this new brand campaign about the product were you guys ad using Splunk and you putting data sensors out there you leveraging an existing data bulb take us through some of that you know the nuts and bolts of what's going on the price so part of it is building out some data sets so there are some data sets that don't exist but the government and the counties and the private sector have built out a huge ball of corpus of data around where the buildings are where the people are where the cell phones are where the traffic is so we're able to leverage that information as we have it today the technology we're using the Amazon stack it's easy for us to spin up databases it's easy for us to build out and expand as we grow and the response we're able to have a place for all this real-time data to land and for us to be able to build API is to pull it out very very simple when we say dated everything we really mean it it's really you know it's a personal story for me I am on the government affairs team here is blog so I manage our relationships with governor's and mayors and these are the issues that they care about right when the city is burning down the mayor cares about that the governor this is you know one of the governor and California's and major initiatives is trying to find solutions on wildfires you know I met charlie my hometown Orinda California art fire chief in that town was one of sort of the outside advisors working with Charlie on this idea and we ran I met him at a house party where the fire chief was telling me that trim my trees back and shrubs back and then I was at a conference three days later that same fire chief Dave Winokur was on a panel with like folks from a super computer lab and NASA and MIT I was like you know my fire chief's still the smartest guy in that panel I got to meet this guy a few weeks later we were literally in the field doing these proof of concepts with sensors and data super savvy folks some of the other folks from Cal Fire there you know dropping Cox was with us today here it's what my and you know we've we've just been collaborating the whole time and seeing you know that that Splunk can really put some firepower the power behind these guys and we just see like look they've got the trust of these customers and we need to make sure this idea happens it's a great idea and it's going to save lives yeah the little small nuance data to everything data time and the reason behind that was we believe you can bring and we can enable our customers to bring data to every question every decision and every action to create meaningful outcomes and the use cases are vast and enormous we talked about some of them before the show started but helping look global law enforcement get ahead of human trafficking fierce Punk and spelunking what's going on across all sorts of data sources right helping zone Haven which is our first investment from Splunk ventures which startup that's actually helping firefighters figure out burn burn patterns with pilot wildfires but also when temperatures and humidity change we're sensors are they can alert firefighters 30 to 45 minutes earlier than they would usually do that and then they can also help influence evacuation patterns I mean it's it's remarkable what folks are doing with data today and it's really at the core of solving some of the world's biggest issues so I'm glad you mentioned data right we're a data company and we're very proud that we actually pull star diversity inclusion number so we moved the needle 1.8% on gender last year year-on-year pride but not satisfied we understand that there's much more to diversity inclusion than just gender but our strategy is threefold for diversity inclusion so its workforce workplace marketplace the farces arranged is where I talk about is improving our representation so that these women are no longer the only czar in the minority they were much more represented and we're lucky we have three women on our board we have four women in our C suite so we're making good good progress but there's a lot more to do and as I say it's not just about gender we want to do we know that innovation is fueled by diversity so we want to attract you know folks of different race different ethnicity books who are military veterans people with disability one its plans to be successful the important thing thing is you know the things you mentioned the the vulnerability scanning the intrusion detection these are all still important in the cloud I think the key thing that the cloud offers is the fact that you have the ability to now automate and integrate your security teams more tightly with the things that you're doing and you can actually we always talk about the move fast and stay secure customers choose AWS for the self-service the elasticity of the price and you can't take advantage of those unless you're secure you can actually keep up with you so the fact that everything isn't based on an API you can define infrastructure as code you can actually enforce standards now whether they be before you write a line of code in your DevOps pipeline we're actually being able to detect and >> those things all through code and in a consistent way really allows you to be able to look in your security in a different way and take the kind of philosophy and mindset you've always had around security but actually do something with it and be able to maybe do the things you've always wanted to do that have never had a chance to do it so I think I think security can actually keep up with you and actually help you different you're different to your business the acquisition is really extremely you know exciting for us you know after meeting Marcus I've known of Marcus he's a very positive influence in the community but having worked with him the vision for threat care and the vision for alike rests really closely aligned so where we want to take the future of security testing testing controls making sure upstream controls are working where threat care wanted to go for that was very much with what we aligned war so it made sense to partner up so very excited about that and I think we will roll that in our gray matter platform as another capability we really see the product involving the same way that you see a lot of the portfolio overall so Doug has talked a lot about investigate monitoring and analyzing and right and so those same concepts apply to how you think about a process as well so right now we're really helping the investigation and monitoring but will also continue to extend across that spectrum lifetime a lot of cloud services and micro services observability a big part of all this yeah definitely and how we've built the product but also I think you can sit alongside some of the other things that you're also seeing in that so I think the thing to understand is correct we're not just a security company but we are number one in the security magic quadrant we're number one in both IDC and Gartner and so that's important but what happens is all of the data that you collect first security can also be used for all these other use cases so generally speaking whatever you're collecting for security is also valuable for IT operations and it's also valuable for many other use cases so I'll give you an example Domino's which is a great customer of ours there they've gone 65% of their orders now come in digitally ok and so they monitor the entire end-to-end customer experience what they monitor not only from an IT operations perspective that same data that they use for IT operations also tells them you know what's being ordered what special orders are being made and they use that data for promotions based upon volume in traffic and timing they actually create promotions so now you're talking about the same data that you collected for a security night operations you can actually use for promotions which is marketing it's a great intro on data is awesome but we all have data to get to decisions first and actions second what that in action there's no point in gathering data and so many companies been working their tails off to digitize her landscapes why well you want a more flexible landscape but why the flexibility because there's so much data being generated there you can get effective decisions and then actions that landscape can adapt very very rapidly which goes back to machine learning and eventual AI opportunity set so that is absolutely squarely where we've been focused is translating that data into value and into actual outcomes which is why our orchestration automation piece is so so important one big 18 factors that we felt as existed is for this plunk index it's only for this blank index the pricing mechanism mechanism has been data volume and that's a little bit contrary to the promise which is you don't know where the values could be within data and whether it's a gigabyte or whether it's a petabyte why shouldn't be able to put whatever day do you want in to experiment you
SUMMARY :
the amount of you know headcount to do
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Susan Wojcicki | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
Jim | PERSON | 0.99+ |
Jason | PERSON | 0.99+ |
Tara Hernandez | PERSON | 0.99+ |
David Floyer | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Lena Smart | PERSON | 0.99+ |
John Troyer | PERSON | 0.99+ |
Mark Porter | PERSON | 0.99+ |
Mellanox | ORGANIZATION | 0.99+ |
Kevin Deierling | PERSON | 0.99+ |
Marty Lans | PERSON | 0.99+ |
Tara | PERSON | 0.99+ |
John | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Jim Jackson | PERSON | 0.99+ |
Jason Newton | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Daniel Hernandez | PERSON | 0.99+ |
Dave Winokur | PERSON | 0.99+ |
Daniel | PERSON | 0.99+ |
Lena | PERSON | 0.99+ |
Meg Whitman | PERSON | 0.99+ |
Telco | ORGANIZATION | 0.99+ |
Julie Sweet | PERSON | 0.99+ |
Marty | PERSON | 0.99+ |
Yaron Haviv | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Western Digital | ORGANIZATION | 0.99+ |
Kayla Nelson | PERSON | 0.99+ |
Mike Piech | PERSON | 0.99+ |
Jeff | PERSON | 0.99+ |
Dave Volante | PERSON | 0.99+ |
John Walls | PERSON | 0.99+ |
Keith Townsend | PERSON | 0.99+ |
five | QUANTITY | 0.99+ |
Ireland | LOCATION | 0.99+ |
Antonio | PERSON | 0.99+ |
Daniel Laury | PERSON | 0.99+ |
Jeff Frick | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
six | QUANTITY | 0.99+ |
Todd Kerry | PERSON | 0.99+ |
John Furrier | PERSON | 0.99+ |
$20 | QUANTITY | 0.99+ |
Mike | PERSON | 0.99+ |
January 30th | DATE | 0.99+ |
Meg | PERSON | 0.99+ |
Mark Little | PERSON | 0.99+ |
Luke Cerney | PERSON | 0.99+ |
Peter | PERSON | 0.99+ |
Jeff Basil | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Dan | PERSON | 0.99+ |
10 | QUANTITY | 0.99+ |
Allan | PERSON | 0.99+ |
40 gig | QUANTITY | 0.99+ |
Charlie Crocker, Zonehaven & Tim Woodbury, Splunk | Splunk .conf19
>>live from Las Vegas. It's the Cube covering Splunk dot com. 19. Brought to You by spunk >>Hey, welcome back, everyone. We're live here in Las Vegas for Splunk dot com. I'm John Ferrier with Q two great guests. Tim would Bury, director of state and local affairs for Splunk and Charlie Crocker, CEO Zone Haven. Very innovative. Start up doing some incredible things with Splunk Ventures Financing Summerlee Financing around Really check for good guys. Welcome. Thank you, Charlie. First, explain what you guys are doing real quick because I think this is a great example of what I've been seeing now for two years now. But now, in the past year, renaissance of entrepreneurial activity around mission driven tech for good, where entrepreneurs are using the cloud and sass models and platforms like Splunk to stand up Mission Value Commission >>value. I like the term. Explain what you're doing. So simply put, we're building in evacuation planning and support to. So right now, there are more stronger fires happening. Over the last five years, we've had more than half of California's most destructive wildfires happened just in the last five years. So it's it's mission critical that we figure this out. Now the's fires air. So big goal is really just to get people out of harm's way. And that's a difficult job to figure out at three in the morning with a map on the hood of a pickup truck. So we're building Zillah ways for fire. There's no ways for five ways has got public safety >>people no ways. But the thing is, is that yesterday I was watching on TV and Pacific Palisades, California air drop of water on the canyon, right before house, and I see the people running right. You like running for their lives. There was a serious business. Exactly. You guys are trying to provide system >>we're trying to do. What we've built are a set of zones, the ability for the Fire Department, law enforcement and, oh yes, to work on customizing hyper local evacuation plans, hyperlocal down to the neighborhood level and then we're scaling that statewide. So how do you make sure that this fire department on these three law enforcement groups are coordinated before and how do they have the conversation with community before the event happens? If we can save five minutes at the time, the event happens, we're going to save lives. >>So this is really about making efficiency around the first responders on the scene from leveraging data which maps or their >>maps, data dynamic data, telemetry, data where the fire's gonna go simulations for how the fire could potentially grow. Who needs to get out of harm's way first. What's that gonna do to the traffic and Road Network? Talk >>about the original story. Then we get to this plug involvement, the origination stories you're sitting around. You're talking to friends in the business. >>So we have colleagues and friends that are in the business and many of them, you know, from the Silicon Valley these guys are innovative leaders in in fire on. They've got a lot of really good ideas on how to make their jobs better. >>They >>don't have a tech team, they don't have a tech arms. So we literally said, Look, we'll come in and we'll make work what your vision is, and that started to expand on. Now we started to move from these smaller jurisdictions. Too much larger >>jurisdictions. Data is driving the future. That's a tagline I'm reading. I've seen the new branding by the way, the new brains very strong, by the way. Love it, Thank you. So this is a good example of data driven value constituency fire professionals. That's all they think about is how to make people save put, get in harm's way to try to solve the fires. They don't have tech teams. You don't have a data center they don't have, like with boot up a consulting. To come into a waterfall of a meeting by that sign is just, Yeah, you can't just do that. They can't stand up. How did you guys get involved in this? It's data driven, obviously. What's the story? >>Way, Say, dated everything. We really mean it. It's really you know, it's a personal story for me. I am on the government affairs team here. It's flowing, so I manage relationships with governors and mayors, and these are the issues that they care about right When the city's burning down, the mayor cares about that. The governor, This is you know, one of the governor in California's major initiatives is trying to find solutions on wildfires. I met Charlie, my hometown. Orinda, California Aren't Fire Chief in that town was one of sort of the outside advisers working with Charlie on this idea. And we're and I met him at a house party where the fire chief was telling me to trim my trees back and shrubs back. And then I was at a conference three days later that same fire chief, Dave Liniger. I was on a panel with folks from a super computer lab and NASA and M i t was like, you know, my fire chiefs, Still the smartest guy in that panel. I gotta meet this guy. A few weeks later, we were literally in the field doing these concepts with sensors and data. Super savvy folks. Some of the other folks from Cal Fire there. Dr. Cox was with us today. Here on. You know, we've just been collaborating the whole time and seeing you know that that Splunk and really put some fire power power behind these guys and we see like, Look, they've got the trust of these customers and we need to make sure this idea happens. It's a great idea, and it's gonna save lives. >>It's crazy way did a test burn where we run a small burn on a day where we're very confident it won't grow. Put the sensors out right next to a school in Arena. It was his kid's school. >>Yeah, I have a kindergartner that goes to that school, so >>it's slightly personal for you. I could >>be I could be said that this is just me protecting my own. But it is something that I think will save lives around the world. >>First of all, this, there is huge human safety issues on both sides. The ire safety put in harm's way. Those professionals go out all day long, putting their lives at risk to save human, the other human beings. And so that's critical. But if you look at California, this other impact cost impact rolling blackouts because they can't instrument the lines properly just because of the red red flag warnings off wind. I mean, I could be disrupted businesses, disruptive safety. So so PG and e's not doing us any favors either. Sound so easy. Just fix it. >>It sounds easy, but I think with be Jeannie, it's interesting way do need to prevent wildfires and really any way that we can. But like you said, if we could bring more data to the problem maybe we can have the blackouts be smaller. You know, they don't have to be a CZ big. >>There's certainly no lack of motivation to find solutions to this issue. There are lives on the line. There's billions of dollars on the line that these types of solutions own haven a part of part of what is going to fix it. But there are many very large stake holders that need these solutions very quickly. >>Well, you know the doers out there making it happen of the people in the front lines on the people they're trying to protect our cities, our citizens on this sounds like a great example of tech for good, where you guys are doing an entrepreneurial efforts with people who need it. There's a business, miles, not free non profit. You're gonna get paid. It's a business model behind. >>There is a business bottle behind it, and I think the value proposition is only beginning to be understood, right? There were so many missions in so many different ways. Wildfires are massive. You can come at him from satellite, come at him from on the ground. We're working with the people on the ground who need to get people out of harm's way. We're focusing on making their jobs easier, so they're safer and they get people out >>more quickly. You guys in the tech business, we always talking. We go. These events were re platforming our business. A digital transformation. You know all the buzz, right? Right. This is actually an acute example of what I would call re platforming life because you're taking a really life example. Fire California Fire forest There, out in the trees trimming thing is all real life. This isn't like, you know, some digital website. >>We certainly I mean, I've been in the data business for more more time than I can remember, and we've got the tools, tools, like Splunk tools. Like Amazon Web service is we've got the data. There's satellites all over. We've got smart people in machine learning way. Need to start applying that to do good, right? It exists. We do not need to go invent new technology right now in order to solve this problem, >>Charlie, really inspired by your position and your your posture. I want you to spend more time talking about that feature because you're an entrepreneur. You're not just detect for good social justice Warrior, You're an experienced data entrepreneur, applying it to a social good project. It's not like I'm gonna change the world, you actually doing it. There's a path for other entrepreneurs to make money to do good things fast. Talk about the journey because with cloud computing, it's not like a 10 year horizon. There's a path for immediate benefit. I >>mean the pat. So I mean in terms of creating a profitable venture. We're a young company way feel like we have a good, good direction way feel like there is a market for this way. Also feel like there's public private partnerships Here is well, I think that we can take the same solutions that we have here and apply them to campuses. You could apply it to, you know, a biotech campus, a university campus. You could apply it to a military base, right? There's insurance could be involved in this because insurance risk people are losing insurance in their homes as well. So you know, there's a lot of different angles that we can take for this exact same. Say >>that what's the expression dated to everything. Yet this is an example of taking data on applying it to some use case. >>A very specific cool evacuation neighborhood evacuation and really building the community fabric so that people take care of each other and can get out together. Where are the vulnerable populations in that zone? Who's gonna go respond to those If if the fire department can't come in, right, How are we gonna get those people out? >>I love the vision. You guys were also for putting some cash in their spunk. Ventures. Congratulations. Talk about the product. Where you guys at using Splunk. You putting data sensors out there, You leveraging existing data. Both take us through some of the nuts and bolts of what's going on the >>price. So part of it is building out some data sets. So there are some data sets that don't exist. But the government and the counties and the private sector have built out a huge corpus of data around where the buildings are, where the people are, where the cell phones are, where the traffic is. So we're able to leverage that information as we have it today. Technology. We're using the Amazon stack. It's easy for us to spin up databases. It's easy for us to build out and expand, as as we grow online with Splunk were able to have a place for all this real time data toe land. And for us to be able to build a P I's to pull it out very >>simply having a conversation with Teresa Carlson, who runs Amazon Web sites. Public sector variety of these things of projects are popping up. Check for good. That's for profit. It helps people and the whole idea of time to value with cloud and flunks. Platform of leveraging diverse data making Data Realtor whether it's real time, time, serious data or using a fabric surge or accelerated processing capabilities is that you can get the value quicker. So if you got an idea for you to wait two years of just e whether it was it a hit or not, you can illiterate now. So this idea of the start of agile startup is now being applied to these public sadly like things. So it's everything >>you spot on, and you know the unique element of Splunk with some of these data sources way don't necessarily know which ones are gonna be the right ones. We're talking about satellite data, sensor data. Some of this on. Part of it is we're building an outdoor smoke alarm, right? No one's ever done that before. So, you know, with court nature of Splunk technology being able to easily, you know, try to see if that is the right data source is critical, giving people the man with two go try to make this happen. >>You guys are a great example of zone haven, Charlie, You and your team of what I call a reconfiguration of the value creation of startups. You don't need to have full stack develop. You got half the stack and Amazon domain expertise in the inertial properties flipped around from being software on this intellectual mode to domain specific intellectual property. You took the idea of firefighters and you're implementing their idea into your domain expertise using scale and data to create a viable, busy >>other thing. I want to throw in there, though, and this is something that people often forget a big part of our investments going to be in user experience. This thing needs to be usable by the masses. It cannot be a complicated solution. >>You X is the new software data is the new code, but anyone can start a company if they have an innovative idea. You don't have to have a unique algorithm that could be a use case to solve a problem. >>If you have a very Calgary them, you can put it on Splunk Platform or Amazons platform and scale it. >>This is going to change, I think, the economic landscape of what I call tech for good now. But it's entrepreneurship redefined. You guys are great working example of that. Congratulations on the vision. Thank you to you and your team. Thanks for coming on the Q. Thanks for sharing. It's great to be here. It's a great example of what's going on with data for everything. Of course, this acute were cute for everything. We go to all the events of smart people and get the data and share that with you here in Las Vegas for dot com. 10 years of conference our seventh year, I'm John Ferrier. We'll be back with more coverage after this short break
SUMMARY :
It's the Cube covering But now, in the past year, So big goal is really just to get people out of harm's way. But the thing is, is that yesterday I was watching on TV and Pacific Palisades, So how do you make sure that this fire department on these three law enforcement for how the fire could potentially grow. about the original story. So we have colleagues and friends that are in the business and many of them, you know, from the Silicon Valley these guys So we literally said, Look, we'll come in and we'll make work the new brains very strong, by the way. I am on the government affairs team here. Put the sensors out right next to a school in Arena. I could be I could be said that this is just me protecting my own. instrument the lines properly just because of the red red flag warnings off wind. You know, they don't have to be a CZ big. There's billions of dollars on the line that these types of solutions own haven our citizens on this sounds like a great example of tech for good, where you guys are doing You can come at him from satellite, come at him from on the ground. You guys in the tech business, we always talking. We certainly I mean, I've been in the data business for more more time than I can remember, Talk about the journey because with cloud computing, You could apply it to a military base, right? on applying it to some use case. really building the community fabric so that people take care of I love the vision. It's easy for us to build out and expand, as as we grow online with Splunk were idea of time to value with cloud and flunks. being able to easily, you know, try to see if that is the right data source is critical, You got half the stack and Amazon domain expertise in the inertial properties flipped around This thing needs to be usable by the masses. You X is the new software data is the new code, but anyone the data and share that with you here in Las Vegas for dot com.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Liniger | PERSON | 0.99+ |
Teresa Carlson | PERSON | 0.99+ |
John Ferrier | PERSON | 0.99+ |
Charlie | PERSON | 0.99+ |
Charlie Crocker | PERSON | 0.99+ |
five minutes | QUANTITY | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
Splunk | ORGANIZATION | 0.99+ |
two years | QUANTITY | 0.99+ |
NASA | ORGANIZATION | 0.99+ |
Silicon Valley | LOCATION | 0.99+ |
10 years | QUANTITY | 0.99+ |
seventh year | QUANTITY | 0.99+ |
First | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
Tim Woodbury | PERSON | 0.99+ |
three days later | DATE | 0.99+ |
10 year | QUANTITY | 0.99+ |
Amazons | ORGANIZATION | 0.99+ |
California | LOCATION | 0.99+ |
both sides | QUANTITY | 0.99+ |
Cal Fire | ORGANIZATION | 0.99+ |
Cox | PERSON | 0.98+ |
Zone Haven | ORGANIZATION | 0.98+ |
billions of dollars | QUANTITY | 0.98+ |
Both | QUANTITY | 0.98+ |
Jeannie | PERSON | 0.98+ |
today | DATE | 0.97+ |
one | QUANTITY | 0.97+ |
two | QUANTITY | 0.97+ |
Ventures | ORGANIZATION | 0.96+ |
Pacific Palisades | LOCATION | 0.96+ |
three law enforcement groups | QUANTITY | 0.96+ |
Splunk Ventures Financing Summerlee Financing | ORGANIZATION | 0.96+ |
Fire Department | ORGANIZATION | 0.95+ |
Tim would Bury | PERSON | 0.95+ |
PG | ORGANIZATION | 0.95+ |
first responders | QUANTITY | 0.95+ |
Calgary | ORGANIZATION | 0.94+ |
Dr. | PERSON | 0.92+ |
A few weeks later | DATE | 0.91+ |
more than half | QUANTITY | 0.9+ |
five ways | QUANTITY | 0.89+ |
last five years | DATE | 0.88+ |
two great guests | QUANTITY | 0.86+ |
Splunk dot com | ORGANIZATION | 0.86+ |
Mission Value Commission | ORGANIZATION | 0.84+ |
past year | DATE | 0.83+ |
Orinda, California | LOCATION | 0.78+ |
half | QUANTITY | 0.74+ |
Splunk .conf19 | OTHER | 0.66+ |
CEO | PERSON | 0.65+ |
Zonehaven | ORGANIZATION | 0.63+ |
hat town | ORGANIZATION | 0.62+ |
three | QUANTITY | 0.59+ |
fire | ORGANIZATION | 0.59+ |
agile | TITLE | 0.54+ |
zone haven | ORGANIZATION | 0.46+ |
lunk Platform | ORGANIZATION | 0.43+ |
Zillah | PERSON | 0.36+ |
Roger Scott, New Relic | New Relic FutureStack 2019
>> Narrator: From New York City It's theCUBE covering New Relic FutureStack 2019. Brought to you by New Relic. >> Hi, I'm Stu Minimen and we're here at New Relic's FutureStack 2019 at the Grand Hyatt, next to Grand Central Station, here in New York City. Happy to welcome to the program a first time guest, Roger Scott who's the Chief Customer Officer at New Relic. Roger, thanks so much for joining us. >> Thanks, Stu. Thanks for having me on. Good to be here. >> Alright so, I love this morning actually in addition to hearing all of the announcements, my first hand full of guests on theCUBE were customers. So I got to hear from them and we know your team is always excited about the announcements, but definitely enthusiasm from the customers, things in the keynote that got people. >> Fired up! Yeah. >> Clapping, and fired up. >> Great to see. >> Things like, oh wait! 10 terabytes of data, pressure thing, refresh for like a second, and >>oh my gosh! There's results. Yeah >> Pretty impressive so maybe give us a little bit of insight into customer engagement and how it's let to the bevy of announcements here at the show. >> Oh it's a great question actually and I think in my capacity as Chief Customer Officer and the functions I'm responsible for, we're continually engaging with customers as you can imagine. And one of the things we take a lot of pride in is being a proxy for the voice of the customer back into the organization. So we have a pretty rigid process. Not rigid, a pretty discipline process, I would argue, that allows us to get feedback from the field, listen to our customers, understand what's important to them, and reflect that in our product roadmap. And I'll let you know that's on a weekly cadence we do that. Now we're not doing that in a reactive fashion such that our roadmap diverts every single week in there, but we hear that constant feedback from the field as to what our customers are lacking. So lot of what you hear today, in terms of those six great announcements that we have were a combination of feedback that we've had over the last couple of years, I would argue. Because it's a dramatic shift to go from what we were previously, which was essentially six individual products that work really well together. But through the release of New Relic 1 in May earlier this year and what we announced today has truly developed us in to a observability platform. So monitoring with six different products to a true observably platform that's open, connected and programmable is a dramatic shift. And that's a combination of a bunch of feedback from our customers over the years. >> Yeah. I'm sure it's pretty much feedback from all customers. They're not asking for more tools and more interfaces and more things that they need to learn. >> Roger: Not at all, right. >> In many ways software can be a unifying feature especially that term platform who spend a bunch of time emphasizing what's needed from platform. >> Maybe, what were your costumers struggling with that kind of New Relic 1 in general is looking to solve as well as the observability piece? What went into that launch that was costumer pinpoints and things that they'd been asking for. >> Yeah maybe to stand back a little bit and understand some of the challenges that costumers had and then why they were asking for different solutions or evolution of our solution. If you think about today's world, there's this rapid development an deployment of software, so it's almost got to the point of continuous software deployment. And so your speed of needing to be able to react to problems in your environment, your costumer experience are degrading, ect. Being able to respond to that really quickly is essential, understanding the costumer experience is essential. You talked about operational efficiency of reducing the number of tooling sets or data sets that I'm looking at continually. So anything that we could provide to our costumers that allowed them to get to answers quicker, understand the why, and then be able to remediate that really easily so that the costumers have a greater experience. And at the same time reduces this friction that's unnecessarily introduced when you're going from one product to another, one tool to another and you're spending too much time rationalizing data sets across those tool sets. So consolidation is a big theme, ability to get to your answers really quickly is a big theme and that's really been the genesis of being able to create a platform. But not just a platform for consolidation, for better visibility, and observability but we believe it's not truly a platform until you can develop on it. If you think back in technology history of all the different peradams we've had throughout the history of technology, those who've won the platform wars over the years have been really good at being able to provide tools and ease of adoption of the platform by virtue of being able to build things on top of it. The ability to give people tools that allow them to build technology is really a therasense of the platform as well. >> You know, Roger, there's a certain trust level that costumers have to have if they're going to be building on top of your platform. >> When I've talked to costumers in New Relic they do talk about a partnership >> and the good back and forth but there's definitely a certain amount of stickiness once they've built something on your platform. >> Roger: Right, yeah. >> Any concerns from them as to, you know there's that term lock in out there as to the how do I know that this is going to work for me, and that I'm not going to have my pricing kind of crank up over time and be like oh my gosh, a year or two later, what did I get myself into? >> Right. It's a really important point that I'd like to start off by actually reemphasizing the point you made. I think we pride ourselves on the relationship we have with our costumers. It truly is the heart of everything at my organization does. We have this saying that we are because they are. In the realization that if we don't serve our costumers really well they have choices frequently, we're a saas vendor, the contracts come up for renewal frequently. And if you're unable to deliver on the promises that you made in the sales process, once they implement your solutions and try to use those in production, environments and everyday work if you can't deliver on those promises then you're going to breakdown that level of trust. And trust is at the center of all relationships as you know. Whether it's a personal relationship, you're playing on a sports team, whether you're working with your costumers. And so we want to make sure that we can deliver on those promises once we've sold them the product. So I haven't heard any specific concerns about lock in or anything, I think what they regularly come to us though with is they want us to have a really strong point of view, want us to be opinionated, tell them how this should work effectively together, what does best practice look like, what's the gold standard, what are some of the artifacts, tools, frameworks, reusable templates that we can share with them that accelerates their time to value. So I think the value significantly outweighs the concerns around lock in or reduction of the number of vendors that they're working with. >> If I look at really the enterprise space, you've got costumers working through their application modernization. They've got their modelist their going after micro services. I heard a stat that only about five to ten percent of apps are monitored at the app level today. >> Yeah, pretty scary, isn't it? >> Yeah, how many of your costumers are dealing with the installed state versus new deployments and what are some of the challenges you're hearing from costumers there? >> Yeah and I think it's important to pause that number because I think it's five to ten percent or growing to twenty percent as I think got indicated. If you look at those organizations Born In The Cloud or Born Digital it's significantly higher percentage of that which is possibly an indictment of the low level of instrumentation we see in a lot of legacy software technology stacks. And so I think in today's world we're tryna get that level of instrumentation observability up as much as possible. But maybe to link back to your previous question as well I think there's an important aspect here of when we move to a platform. When you're a product company your differentiation comes through product, comes through the capability of that product features and functions and we've certainly found ourselves in a significant number of those battles against competition where it's feature and function based. That's not a great comfort for the costumer. I think when you move to a platform it's very much around the networks differentiation. When I say network differentiation I think it's about getting the users of your service access to third party applications to third party data sources be they open source data emitters, opentelementry, open sensors, Zipkin any of those data sets that we are now in support for today. Giving them access to those data sets and being able to enrich the experience that we provide them that network effects and that's really where we see the opportunity to deliver significantly more value to our costumers with the ability to then build your own applications on top of the platform. That's second to none in the industry in my opinion. >> Roger, what's New Relic's role in helping costumers as really they're modernizing their work force? When I talk to so many companies it's like they need to retrain and they have to have new skill sets they need to make sure as certain cloud in automation changes where they focus on things and embrace devops and new ways of doing things. There are a lot of challenges there. Where does New Relic play in that modernization for costumers? >> You know what I think it's in a couple ways. The ways that we, my organization, can help the costumer in terms of just sheer understanding of the capability of the platform, what are best practices, how we can drive better accountability as you move to these new technology stacks and new ways of working much more agile environments. And so I think we can do a combination of that just sheer skills development, working really tightly with the likes of AWS you would've heard Dave McCann this morning talking about how when costumers migrate the application work goes to the AWS cloud environment. Hopefully they're not just doing that by way of compute lift and shift but they were actually looking at modernizing and refactoring those applications and when they do that, you heard Dave talk through a number of assets and frameworks and models and reusable best practices that we're trying to work with them on that we can give to our costumers that accelerate their journey 'cause it's not easy. We were talking to Chris Dillon this morning from Cox Automotive and when you think of an organization like that that's forty, fifty years old and has had to transform itself in terms of digital experience for it's costumer base, it's a significant cultural adjustment quite often to get teams to work in fundamentally different ways. So it's not an insignificant challenge but that's partly why we've invested so heavily in costumer success. Taking the costumers on the journey, thinking about their maturity over time, and constantly look for them to get better value from the platform. >> Roger, there are a number of things that have jumped out at me. Things like oh hey, we can save you potentially millions of dollars on your AWS cloud bill. You've already got costumers building on top of the platform, you had the future Haka event just a couple of weeks ago. Any other kind of interesting or exemplary costumer outcomes that you might be able to share? Either doesn't have to be about the new stuff but just that you've recently with your costumers. >> You know, one of the things that's most gratifying for me when talking to costumers is when we've been able to see when you work with older, more traditional companies that are undergoing some form of digital transformation and they're trying to shift a lot of the applications into a more modern stack and environment, become more agile, etc. they frequently sort of peel off part of the business and will have a digital division that will build some innovative, typically mobile based, apps. We've seen a number of different retailers that we've worked with. Number of different travel organizations where we've started out intrumenting the mobile application because they've built a new application to give their consumers or costumers access through to their services, and at some point that application is going to merge into the backend and have to connect back into older technology. And it's been the beauty of being able to connect those two different environments together. Not starting off at what we would've got as slightly easier place to start which was the more modern application environment where we are really well suited to. But then seeing the full value of being able to instrument the front end all the way through to the backend, link that back to the costumer's experience and to the impact on the business in terms of funnel analysis from number of people using the mobile application to actually ordering something to once they've ordered it, feeling satisfied in actually receiving the goods that they ordered. Being able to instrument all of that and understand the impact of performance and availability on the overall business arcam, that's when it's been truly transformational in working with costumers and that's certainly where we'd love to help more of our costumers in that fashion. >> Alright, Roger, want to give you the final word. Of course you bring together a number of costumers here at FutureStack in the U.S as well there's a few of those run in other geographical areas but throughout the year, any other key things you want to highlight as to how costumers can get engaged even more. >> Yeah, I mean, we've got a sort of what I would argue is a tiered approach to costumer success. At the very high end of our engagement model we have a significant number of resources. Solution architects, costumer success managers that we can deploy directly with our costumers. We typically do that in conjunction with them, build out success plans, etc. What we looking at investing Heavily at the moment is also having a good understanding of what the ideal costumer journey is like. Realizing that a costumer can come to an event like this and learn about our product but the best way for them to experience that is in the course of using the product. So heavy focus on product lead growth and how we actually deliver better value through the product itself, remove friction and adoption and getting to better value. We want to automate some of that costumer journey so that we know that if you've just signed up and, for instance, you've configured you're agent and you've done your learning policy but you haven't yet configured a custom apdex on that application or you haven't understood what your key transactions are, we've got all that data in the backend. So we're working really hard to understand how we get that information back out to costumers and go hey we know you haven't necessarily done this yet, here's some access to great assets. A short video clip, a self paced learn guide that somebody can get on demand from an LMS system. So trying to use a combination of direct resource investment, events like this where it's great to make announcements like we did about the six grade innovations and then increasingly using digital through the products but also through just the general costumer journey to say hey this is really important content and information, you should look at this now 'cause it's going to add value in what you're doing today. >> Alright, well Roger Scott, Chief Customer Officer at New Relic, thanks so much for joining us. >> Thanks so much, it's been great talking to you. >> All right. I'm Stu Minimen back with lots more here at New Relic FutureStack 2019 in New York City. Thanks for watching theCUBE. (outro music)
SUMMARY :
Brought to you by New Relic. at the Grand Hyatt, next to Grand Central Station, Good to be here. in addition to hearing all of the announcements, Yeah. oh my gosh! and how it's let to the bevy of announcements Because it's a dramatic shift to go from what that they need to learn. of time emphasizing what's needed that kind of New Relic 1 in general is looking to solve that allowed them to get to answers quicker, that costumers have to have if they're going and the good back and forth that I'd like to start off I heard a stat that only about five to ten percent of apps and being able to enrich the experience that we provide them to retrain and they have to have new skill sets and constantly look for them to get better value of the platform, you had the future Haka event just a couple that application is going to merge into the backend of costumers here at FutureStack in the U.S as well Realizing that a costumer can come to an event like this Chief Customer Officer at New Relic, in New York City.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave McCann | PERSON | 0.99+ |
Roger Scott | PERSON | 0.99+ |
five | QUANTITY | 0.99+ |
Roger | PERSON | 0.99+ |
Chris Dillon | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Cox Automotive | ORGANIZATION | 0.99+ |
New Relic | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
twenty percent | QUANTITY | 0.99+ |
10 terabytes | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
U.S | LOCATION | 0.99+ |
Stu | PERSON | 0.99+ |
Grand Central Station | LOCATION | 0.99+ |
today | DATE | 0.99+ |
six different products | QUANTITY | 0.98+ |
ten percent | QUANTITY | 0.98+ |
FutureStack | ORGANIZATION | 0.98+ |
two different environments | QUANTITY | 0.98+ |
six great announcements | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
Haka | EVENT | 0.98+ |
second | QUANTITY | 0.97+ |
one tool | QUANTITY | 0.97+ |
first time | QUANTITY | 0.97+ |
Grand Hyatt | LOCATION | 0.96+ |
six individual products | QUANTITY | 0.95+ |
one product | QUANTITY | 0.95+ |
May earlier this year | DATE | 0.95+ |
Relic FutureStack 2019 | EVENT | 0.95+ |
Stu Minimen | PERSON | 0.94+ |
forty, | QUANTITY | 0.93+ |
millions of dollars | QUANTITY | 0.91+ |
about five | QUANTITY | 0.9+ |
first | QUANTITY | 0.89+ |
six grade | QUANTITY | 0.88+ |
a year or | DATE | 0.88+ |
this morning | DATE | 0.87+ |
couple of weeks ago | DATE | 0.87+ |
New Relic FutureStack 2019 | EVENT | 0.86+ |
two later | DATE | 0.84+ |
a second | QUANTITY | 0.82+ |
fifty years old | QUANTITY | 0.8+ |
New Relic | LOCATION | 0.8+ |
Zipkin | ORGANIZATION | 0.75+ |
2019 | TITLE | 0.74+ |
single week | QUANTITY | 0.71+ |
last couple of years | DATE | 0.7+ |
New Relic 1 | TITLE | 0.7+ |
FutureStack 2019 | EVENT | 0.66+ |
theCUBE | ORGANIZATION | 0.64+ |
couple | QUANTITY | 0.61+ |
Heavily | ORGANIZATION | 0.57+ |
New Relic FutureStack | EVENT | 0.45+ |
Todd Osborne, New Relic & David McCann, AWS | New Relic FutureStack 2019
>> From New York City, it's theCube covering New Relic Feature Stack 2019. Brought to you by New Relic. >> Stu: Hi, I'm Stu Miniman and this is theCube's first year of coverage at the seventh year of New Relic's Futurestack 2019 here in New York City and happy to welcome back to the program two Cube alumni. So, Todd Osborne is the GVP of Alliances and Channel with New Relic and Dave McCann is the Vice President of Migration Services, Marketplace and Control Services with AWS. Gentlemen, thanks so much for joining us. >> Dave: Great seeing you again, Stu. >> Todd: Thanks for having us. >> Allright, um, Todd, let's start with you uh, you know, quite a bit of a relationship with, between New Relic and AWS. I know we've had Lou on our program at the AWS shows a couple of times. So, set us up with the, the partnership and how it's been evolving. >> Todd: Yeah, it's been a, uh an unbelievable partnership, um, for many, many years we've worked together starting with technology integrations, we've got dozens of them that, that natively monitor a bunch of different AWS services but the most exciting thing of late ah, really came to life middle of last year when we started working with, uh, a bunch of different folks at AWS. Our, basically, our biggest thing that we need help with is migrations. We know we have this massive opportunity, uh, to, for more and more applications more and more workloads to move to the cloud. There's lots of different ways in which customers, partners and Amazon needed help in doing that. They brought us several different challenges related to that and we responded by, ah, at Reinvent Launch last year, launching what we call the Cloud Adoption Solution. That really was how, um, a process that linked up with the Amazon Migration Acceleration Program and used New Relic as the platform to help with migrations from beginning to end. So, starting with the planning, uh, phase of the process, getting the information you need to have a successful migration and design a successful migration, troubleshooting that may, of anything tat may occur during the migration and then post migration, really helping to optimize the performance and cost of how that migration, uh, or that post migration, ah, optimization and run phase. So, it started with that. It's really evolved. What's been really amazing, just since we launced last November December at Reinvent, the whole, we've seen a massive shift already, just the last nine months, where it's not about just simple lift and shift anymore, almost all customers that are migrating now, are also thinking about modernizing their software stack, running on containers, using kubernetes, running micro services, which is New Relic's sweet spot, really, at the application space. So, as we've evolved, starting with migration, evolving into modernization, it's been an amazing partnership working with AWS. >> Stu: So, Dave, migration services, obviously something we hear a lot about from AWS. Every time I go on one of these shows, it's one of the key steps that gets thrown out. Uh, you have a very broad ecosystem, the marketplace, uh, you know is, is the closest I call to the kind of the enterprise app store, uh, of today. Tell us what's, you know, special and, really, you know the effort that goes together between AWS and New Relic here. >> Dave: So, I think, from a migration point of view, um, you know we've spent a lot of time in AWS designing a migration methodology. Our professional services team, let by Tom Weatherby is really delivering a playbook directly to our customers on how to migrate. And, also, we've certified over fifty consultant partners who are certified to do the migration. But all the migrations hinge on a customer knowing what they have and whether they want to migrate it. And, so, to necessarily know what you have, you have to go through application discovery. So, if you've got a larger server fleet, you've got four or five thousand instances, you have a thousand apps, you've actually got to discover and analyze what you have. And, clearly New Relic's tool is widely installed. So they actually have the visibility to a lot of the installed apps. So, last year, at the end of last year, we bought a Canadian company called TSO Logic. And TSO Logic is a business case tool from building the business case on whether to move an application running on PRIM. What would it look like on The Cloud? So, we need to have that data in the tool. And, so, New Relic's been a great partner, integrating New Relic into TSO Logic, so we cal actually take the instrument in visibility that New Relic brings to the table and pop it right into the tool. And, so, the New Relic, TSO tool integration is a great new mechanism that we have. And we just acquired TSO in Q1 of 2019. So that we're now giving the TSO tool to all of our solution architects and all of our consulting partners and New Relic feeds the data right into the TSO tool. So that's a huge, um, uh, mechanism for accelerating migration. >> Okay, uh, can, can you speak to, you know, how, are you, who and what customers and how are you targeting them, uh, for, for this solution? >> So, first of all, customer are moving to AWS. You know, thousand of enterprises are moving applications. I think you have to assume that most enterprises are moving to The Cloud. And the question is, "At what speed?" So, as our sales teams engage with the customer, the sales team have a notion to discuss migration we run migration methodology. And so, as we engage with the teams, the solution architect brings TSO to the tool, to the discussion. And that's happening all around the world. And we've trained our solution architects on TSO. And as we've done that, the second thing we've done is, you know, New Relic engineered engine marketplace over two years ago. But we've launched a new capability called Private Offers. And Private Offers is where the customer, while they're planning the migration, may also need to license more New Relic and New New Relic. And, so, how do we make licensing really easy? And, so, New Relic worked with us on, the, what we call the Private Offers Workflow. And that Private Offer Workflow allows a New Relic sales executive to generate the quote right in the marketplace portal. And you, an AWS customer, and you receive that private quotation right in your AWS account. So not only are we business casing on TSO, but New Relic is quoting through marketplace. So that's happening into lots of large customers. >> Stu: Yeah, uh, you know, what if you talk about the adoption of Cloud we need to make it simpler for customers to move those. And the financial piece has always been one of the promises of Cloud, but things like this Private Offer, it sounds like it helps accelerate, uh, that simplicity, and, and you know, reduces any, you know, perceived barriers there are between some of the software vendors and what you're offering. >> Dave: Well, it flows the New Relic software supply right through marketplace and more and more large companies are using marketplace for software supply. And, so, New Relic's in there. It means that our sales teams are working together So, we talked this morning at the conference with the VP of Cloud architecture who was in the conversation. And so, Chris has been working with the AWS team and with the New Relic team and we're joined at the hip as they expand their use of New Relic. And they announced this morning that they've now moved over thirty percent of all of the Cox application onto the AWS Cloud. And New Relic's been the center of that visibility. >> Stu: All right, so, Todd, a lot of announcements at the show, especially uh, you know, the capital p platform as Lou talked about in the keynote this morning. Well, you know, AWS is one of the largest platforms out there today. Help us understand how these fit together, both platforms as well as just, just the announcements in general as to how they work with AWS. >> Yeah, what every single thing we announced today had some sort of AWS tie to it. So, I mean first of all with New Relic, one, being a platform, it's open, connected, and, um, and, and programmable. And, so, the open part of that means that not only can we just inject data with New Relic agents, now we, we now are an observability platform that will take date from all kinds of sources, so think of what that opens up in working with AWS and AWS's other partners and getting data from a bunch of different sources, to then make the observability even better. We announce a log in solution. We're already connected with AWS, uh, cloud watch logs and, and, uh, working on some other new feature solutions in the log in space. And then from a programmability perspective, um, we can now take what we have, we can write all kinds of applications on top of the New Relic platform. And some of the initial couple of, of the dozen application that have already been opensource, one is a cost optimization play which looks at Amazon data, uh, both utilization performance data, some other sources of data that New Relic has, and then pulls in the Amazon cost data, can actually look at, in the New Relic platform, as a free opensource application, how do I optimize my cost in the AWS environment? And the second one, which we didn't talk about too much this morning but it's out there, but we can take some of VienMore data and some of the on PRIM data that we have visibility to today and help design that landing zone to help migrations do better, So, it's just two really quick examples of how we can take data from all these different sources and program it, write new applications on top of it, create an awesome customer use case and work with Amazon and, uh, help migrations and optimization along the way. >> Stu: All right, Dave, I'm wondering if you have any customer examples that might highlight some of the joint work that's being worked on between New Relic and AWS. >> Dave: Also, You Know, obviously I've just made some Cox We stood on stage this morning with the press where Cox has said that they've now got nine thousand work loads under New Relic visibility. And so that nine thousand work loads is across hundreds of development teams and, I think, Cox is just an illustration of many customers that we have in common. Um, you know, we're, AWS has got thousands of enterprises, so does New Relic. I think you've said you have over one hundred thousand five hundred enterprises using you. So, some large number. So there's a high overlap in many customers at this conference. And as we sat in the room this morning, um, I would say more than half the room held up their hands when I said, "Who in this room is using AWS?" Half of the audience here are AWS customers and New Relic customers. >> Todd: If I could maybe just add on the Cox story a little bit, because I've been very involved with that one. The beauty of the partnership we have there was multiple, on multiple phases. First, Cox has been a customer of ours for a number of years. Both on PRIM and in the cloud as they have accelerated their cloud, we've helped a lot with that. What was great about that partnership was that our field teams got together and, and actually really sat down and, and mapped out the migration, multiple migration scenarios. We had data on a bunch of on PRIM stuff that was valuable to AWS. AWS was the standard on a couple of divisions on cloud that we weren't monitoring all the applications there. So the teams really worked really well together and then at the end of the day, we came together and said, um, there's a bunch of benefits for the customer, for AWS and us, if the, if uh, if a transaction, the last transaction we did there, went though the marketplace, which was a significant transaction that we did with, ah, on the marketplace. So it was just such a win, win, win that tied together the, uh, all the aspects of the strategic nature-natureship, nature of our partnership. >> Stu: All right, so, you know, it's clear you're teams have been working close tother, iterating and adding a lot of the last kind of year, year or two or so. Give us a little bit look forward. What more should we expect of, a, from, from this partnership? >> Dave: So the area I think I would talk about next, that I think all customers are paying attention to, is spam management. So, you migrate your application to the cloud, you establish a could operating modem, um, we license out software through marketplace, you're now running it, at last week we have another product that I run called Service Catalog. And last week what we launched in Service Catalog was a new ability, and Service Catalog is a library of templates, so those templates are launched as Jason Templates using something called cloud formation and we've versioned the templates and what we launched last week was an integration between Service Catalog and another tool our customers have called AWS Budgets. So now what you actually want to do is you want to grant the team access to a resource and on the tag of the template, you actually want to give that resource template a budget. So that is actually under an API, so there's an AWS Budget API, there's a Service Catalog API, Lou's team today announced a whole raft of New Relic tools. But one of the things that they announced was the ability to essentially build these new widgets, using a React widget, and pull data from other sources. So that's the area some of the customers are looking at as far as taking your spam widget and connecting it into both AWS Budgets and Service Catalog. I don't know if you want to give us your thoughts on that. >> Todd: I, I already talked a little bit about it but it's, it's, it's where we can go. Like the future if almost, almost, uh, infinity right now. What we can go do together. We are trying to align to several of the programs Dave mentioned around Service Catalog, Migration Hub, focus on a couple different use cases of what, um, ever migration has a bunch of nuances and every optimization story has a bunch of nuances. But how can we create the right application, which are a starting point, opensource, put, put the repository up on get up and then allow customers and partners to go and fork that, do what they want to match, kind of of standard use case and maybe eighty percent of the way there. But then it needs a little but of tweak, a little bit of customization basesd on whatever that customer's situation is. We've enabled the entire, uh, community of millions apps that are going to migrate to the AWS cloud over the next couple of years. We've enabled that with what we've launched today. So, the, uh, the future is, is infinity and beyond. >> Stu: All right, well, Todd and Dave, thank you so much for the update. We look forward to seeing what gets announced at AWS Reinvent, which, of course, it'll be our seventh year of having theCube there. Big presence, uh, please reach out if you want to talk to us ahead of time. And check out theCube.net, of course, where you can see, uh, where we will be, including, of course, AWS Reinvent, uh, in December, uh, in Las Vegas. So, This is theCube at Future Stack 2019. I'm Stu Miniman. Thanks for watching theCube.
SUMMARY :
Brought to you by New Relic. and Dave McCann is the Vice President at the AWS shows a couple of times. and cost of how that migration, uh, the marketplace, uh, you know is, and New Relic feeds the data right into the TSO tool. And the question is, "At what speed?" And the financial piece has always been of all of the Cox application onto the AWS Cloud. of announcements at the show, especially and some of the on PRIM data that some of the joint work that's being of many customers that we have in common. The beauty of the partnership we have there iterating and adding a lot of the last and on the tag of the template, and maybe eighty percent of the way there. Big presence, uh, please reach out if you
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Chris | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Tom Weatherby | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Todd Osborne | PERSON | 0.99+ |
David McCann | PERSON | 0.99+ |
Dave McCann | PERSON | 0.99+ |
Todd | PERSON | 0.99+ |
last year | DATE | 0.99+ |
last week | DATE | 0.99+ |
New York City | LOCATION | 0.99+ |
New Relic | ORGANIZATION | 0.99+ |
seventh year | QUANTITY | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
TSO Logic | ORGANIZATION | 0.99+ |
December | DATE | 0.99+ |
two | QUANTITY | 0.99+ |
Stu | PERSON | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
first year | QUANTITY | 0.99+ |
First | QUANTITY | 0.99+ |
second one | QUANTITY | 0.99+ |
nine thousand work | QUANTITY | 0.99+ |
last November December | DATE | 0.99+ |
today | DATE | 0.98+ |
Reinvent | ORGANIZATION | 0.98+ |
one | QUANTITY | 0.98+ |
nine thousand work loads | QUANTITY | 0.98+ |
eighty percent | QUANTITY | 0.98+ |
both platforms | QUANTITY | 0.98+ |
Michael's Angel Paws | Dell Technologies World 2019
>> live from Las Vegas. It's the queue covering del Technologies. World twenty nineteen. Brought to you by Del Technologies and its ecosystem partners. >> Welcome on board technologies World. Lisa Martin with Rebecca Night for the first time hosting together. And I have to say this is probably one of my favorite times of del technologies world because we have dogs on the Cube joining us for Michael Angel Pause. We've got Alicia Halloran. She's back. She's a Q. Pietro's here last year. Your Fallen here, Here's OD and Gracie and holding Creasy is Denise Michael's Cox Global Experiential marketing from Del Technologies. Tony's Thank you for joining us as well. Certainly a lot of female power. You right out. He's just letting a male hanging out. Alicia, it's so good to have you back Way have enjoyed being having our set Next. Tio Michael's age. Applause again. This year. It's so great to hear barking. Yeah, when you're talking about, I think I'm at home so true. Talk to us a little bit about Michael's Angel. Pause your experience as a volunteer out. Yeah, D'Oh well, first of all, Michael Angel paused >> is was a static to nonprofit established in Las Vegas, and they have three main programs. They have a community dog program, which really strengthens the bonds between people and their animals. And they have a therapy dog program, which is what these lovelies air part of, and we just love to bring joy and delight everywhere we go. And then they also have a service dog training, which allows people with autism or with their mobility issues or any kind of medical alert. So that's the main process of what Michael Angel paused does way air volunteers with them. We have loved being volunteers with them. Uh, OD is blind, and we managed to get him through the therapy dog program, and we love to come to conferences and just really help people feel better. And Gracie, of course, is just a little beauties. So, >> yeah, so Denise, tell me a little bit about why Dell has partnered with this with this organ, which is a great organization. And why might people need to feel better when they're out of touch? Honor. That's been may be related to this morning's kid note address with the anxiety, sometimes technology way. You do like >> to say we think of everything for Del Technologies world. So what is one more thing? How to surprise and delight our costumers? Air attendees here. And also it's really important for us as Del Technologies to give back to the community. And so it's a great opportunity to give back to great organization like Michael's Angels. Pause and surprise and delight our guests with the with several dogs to pet. Because you know, when you go to a conference when you travel, you miss your pets a lot. A lot of people miss their dogs, and so we're here for them to get a dog fix or maybe just come in for a few minutes. Distress. Er, jetsam dogs come out happy. Everyone who walks in, walks in, smiling and walks out, smiling bigger. So it's a great place. Tio work here, too. >> We were hearing last year that Michael Age, a PAS exhibit exhibit, was one of the most popular places for Get fourteen fifteen thousand people to congregate. Ru. Do you experience the same thing this year? Yes, >> definitely, definitely didn't really. It's been really busy, like these little ebbs and flows like you just catch a breath and then twenty five people are there and they're all like, Oh, it's so great. It's so great to see people relax and be able to kind of sit down and take a breath, which I think is really hard in a conference like this. >> It is, and it's also STD. So you mentioned it's nice to recognize that they're all people. They all have families, a lot of them, whether their pet owners or not. It's just a nice way to just sort of get back to reality, maybe come down from the cloud right on and actually have a little bit of something that just brings a just a smile to your heart. Yes, >> bring some joy even without technology. >> So we know the humans love it. But here, the Toups, how are they doing? Because, as you said, they usually you're going toe spills There. You told each home write and write and how are they handling? They >> handle it. Amazingly, they love to come. You know, the energy is very, very different, so they can be a little bit more rambunctious. They could move a little bit more because they're not working with somebody that is in hospice or you know has an illness. So it's people who are exactly feeling sad that they don't have their animals with them, and they get to get cuddled and squeezed and they love it. So it's a wonderful experience for them. They love to do it. She kind of looks a little sleepy, but that's kind of her way of being like >> he's himself. You're >> yeah, Just loves it. What is some of the reactions elation that you've experience out in the field like, for example, in the hospital or a hospice organization or in firemen's Yeah, that you see patients. Oh, yeah, they light owns, >> they light up. I mean, when you go to a hospital, people are in a hospital, and so everything is very regimented, their way woken up in the middle of the night to do whatever needs to be done. And people are kind of like talking about them, but not actually to them, and that animals don't differentiate there just like we want to sit with you, and that's what we're going to do. We're just going to sit with you, so it gives them a moment to just relax again and not have to think about. When's the next blood draw? When's the next thing that's gonna happen? So it's a really wonderful, relaxing experience for them. It's it's it's and and the joy that it brings. And I think there's a lot of healing in that that when your feel good, you feel good, you have the ability to heal better. And so I think therapy dogs are so important in a in a hospital environment, and >> this is a two step sort of certification program. They become a therapy dog first, and then they would become a service dog. Or can they go into a hospital as a therapy dog to >> go in as a therapy dog? Yes, so that's That's the work that these guys do service dogs or more about if you have something on illness, or that you have some mobility issues that you need balance or you need if you have PTSD that you need to have a dog with you all the time just to kind of keep you keep you together, which I think everybody understands that it feels good to have an animal with you. So these guys are therapy dogs, which is not the service dogs. >> Got it? Yeah. >> Denise, this is your baby. This thing, The show. Congratulations. It was a great show. Fifteen thousand attendees. Eso money partners. So money. A lot of great energy and a great vibe. Can you just talk a little bit? About what? This year's event This this dull world technologies has meant to you. This has >> been a great event every year. It's a great about. But this year, Thea Energy is even higher, so positive it's always really positive. Be here anyway. And so many more people this year, too. It's just a constant Gogo energy all the time. And it's It's wonderful. It's so fun. I love being part of the organization and proud to be able to say that I helped and some a little bit put this together. And so I'm just happy to be here and proud to be a part of Del Technologies to >> Denise before we let you go and get some well deserved. This's also a charity and philanthropy that's close, and Michael Dell's Hart Can you explain a little bit about that? And how he helps veterans in this way? >> Well, how Michael helps veterans or Michael's Angels pause veterans because they both do. >> Michael, let's talk about Michael Dell for since this is kind of his thing, yeah, well, it's, >> um, like for Del itself, a Michael Dell to is very important to him. To give back to the community is is important to us all. And that's a big part of what we dio and this opportunity to that now contribute event. Veterans like these guys go to that veteran homes and help with, um now Del itself. And Michael Dell also contributes Teo many veteran organizations helping veterans with PTSD. And we saw that last year at Del World talking a lot about continue working with veterans, working through PTSD with the art art for veterans. And so there's many organizations like that we work with our Del Technologies and Michael Dell works with, and that give that >> exit was we heard that maybe there was some support financial support for dogs that go through service training to become service dogs for veterans, which is a pretty extensive process and quite expensive. So nice to hear how much it really doesn't mean to the heart of Adele Denise Alicia. Thank you. Someone like you, but I mean, of course, Odeon, Gracie. Humans think they are. Thanks, guys. Really brought a smile to my heart and I got to go home to my dog with first. She's yet, right? Yeah. Like for Rebecca Knight. I'm Lisa Martin. You're watching The Cube live from Dale Technologies World twenty nineteen. Thanks so much for watching.
SUMMARY :
Brought to you by Del Technologies it's so good to have you back Way have enjoyed being having our set Next. And they have a therapy dog program, which is what these lovelies air part of, That's been may be related to this morning's kid note address with the anxiety, And so it's a great opportunity to give back to of the most popular places for Get fourteen fifteen thousand people to It's so great to see people relax and be able to kind of sit down and take a breath, and actually have a little bit of something that just brings a just a smile to your heart. But here, the Toups, how are they doing? Amazingly, they love to come. You're Yeah, that you see patients. And people are kind of like talking about them, but not actually to them, and that animals Or can they go into a hospital as a therapy dog to that it feels good to have an animal with you. Yeah. has meant to you. And so I'm just happy to be here and proud to be a part of Del Denise before we let you go and get some well deserved. they both do. And so there's many organizations like that we Really brought a smile to my heart and I got to go home to my dog with first.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Lisa Martin | PERSON | 0.99+ |
Alicia Halloran | PERSON | 0.99+ |
Denise | PERSON | 0.99+ |
Del Technologies | ORGANIZATION | 0.99+ |
Adele | PERSON | 0.99+ |
Alicia | PERSON | 0.99+ |
Michael | PERSON | 0.99+ |
Rebecca Knight | PERSON | 0.99+ |
Rebecca Night | PERSON | 0.99+ |
Michael Angel | PERSON | 0.99+ |
Michael Dell | PERSON | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
Gracie | PERSON | 0.99+ |
Odeon | PERSON | 0.99+ |
last year | DATE | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
Denise Michael | PERSON | 0.99+ |
Tio Michael | PERSON | 0.99+ |
del Technologies | ORGANIZATION | 0.99+ |
The Cube | TITLE | 0.99+ |
first time | QUANTITY | 0.99+ |
Michael's Angels | ORGANIZATION | 0.99+ |
This year | DATE | 0.99+ |
this year | DATE | 0.99+ |
Tony | PERSON | 0.99+ |
twenty five people | QUANTITY | 0.98+ |
Del Technologies | ORGANIZATION | 0.98+ |
two step | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
Del | PERSON | 0.98+ |
first | QUANTITY | 0.98+ |
fourteen fifteen thousand people | QUANTITY | 0.97+ |
Eso | ORGANIZATION | 0.96+ |
three main programs | QUANTITY | 0.96+ |
both | QUANTITY | 0.95+ |
Thea Energy | ORGANIZATION | 0.94+ |
Fifteen thousand attendees | QUANTITY | 0.92+ |
each home | QUANTITY | 0.9+ |
Michael Age | PERSON | 0.89+ |
twenty | QUANTITY | 0.87+ |
2019 | DATE | 0.85+ |
Pietro | PERSON | 0.83+ |
Dale Technologies World | ORGANIZATION | 0.83+ |
one more thing | QUANTITY | 0.8+ |
OD | PERSON | 0.8+ |
twenty nineteen | QUANTITY | 0.77+ |
Denise Alicia | PERSON | 0.76+ |
Del World | ORGANIZATION | 0.75+ |
Gogo energy | ORGANIZATION | 0.75+ |
Cox | ORGANIZATION | 0.74+ |
Michael Angel Pause | PERSON | 0.73+ |
more people | QUANTITY | 0.73+ |
this morning | DATE | 0.72+ |
Michael's Angel Paws | TITLE | 0.66+ |
del technologies | ORGANIZATION | 0.65+ |
neteen | QUANTITY | 0.64+ |
D'Oh | PERSON | 0.59+ |
Technologies | EVENT | 0.58+ |
Creasy | PERSON | 0.44+ |
Angel | PERSON | 0.42+ |
ni | TITLE | 0.38+ |
Hart | ORGANIZATION | 0.33+ |
Josh Kahn, ServiceNow | ServiceNow Knowledge18
>> Announcer: Live from Las Vegas, it's theCUBE, covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back, everyone, to theCUBE's live coverage of ServiceNow Knowledge 18, here in Las Vegas. I'm your hose, Rebecca Knight, along with my cohost, Dave Vellante. We're joined by Josh Kahn. He is the General Manager of Platforms, ServiceNow. Thanks so much for coming on theCUBE again. >> Yeah, really excited to be here. Thanks for being here and thanks for being part of our event. >> Thank you. >> You're welcome. >> It's been a lot of fun. >> Newly minted. >> Yeah that's right. (laughing) >> Yes, congrats on the recent promotion. So tell us about your new role. >> Yeah, so I run the Platform Business Unit. We use the word platform a lot of different ways at ServiceNow and I think we're trying to get a little bit more clear about that. On the one hand, our platform is the core foundation that all of our applications and all of our customers' applications are built on. It's also a way that independent software vendors and our customers can build their own applications. So what my group is trying to do is really be more thoughtful and structured about how we go about gathering those requirements from our customers and our independent software vendor partners and make sure we're bringing the products to market that meet their needs, and that we're doing all of the things across the board as a company we need to do to make them successful because there's a lot that goes into long-term customer success from the sales teams to the solutions consultants to professional services and the Customer Success Management Team. We're bringing all those things to make sure that, as our customers are building applications, we're helping them be successful. >> I remember we had Erik Brynjolfsson and Andy McAfee on and they were making a point. This was years ago when they wrote their, I think, most recent book. They were saying platforms beat products, I'm like, okay, what do you mean? Look, you can make a great living doing products, but we are entering a platform era. It reminds me of the old Scott McNealy, car dealers versus car makers. If you want to be a car maker in this day and age, unfortunately Sun Microsystems never became that car maker, but you've got to have a platform. What's your perspective on all that? >> I totally agree. I think that every customer I talk to is looking for fewer, more strategic vendors and partners, and they're really saying, hey, be a strategic partner to me. Digital transformation is everywhere. Disruption is everywhere, and they're saying, hey, we need a few people we can really count on to help us build a strategy and execute on that strategy to get to the next place. Isolated, independent pieces of software tend to have a hard time becoming one of those strategic vendors, and I think the more you can be thought of as a platform, the more different kinds of workloads run on the same common shared infrastructure that provide shared data services, that can provide simple ways to get work across each other, the more value that you can bring and the more you can be thought of in that strategic partner realm. >> So you guys are a platform of platforms, we use that terminology a lot, and I think there's no question that for a lot of the C-level executives, particularly the CIOs that I talk to, you are becoming, ServiceNow is becoming a strategic platform provider. Who else is in there? Let's throw some... IBM, because of its huge services in certain industries, for sure, SAP because of its massive ERP estate. I mean, I don't know, Oracle, maybe, but it feels different, but maybe in some cases. Who do you see as your peers? >> The category of players that are in this space are really people that are investing big in the Cloud and investing big in intelligence and automation. And, I think, a lot of times automation can have kind of a negative connotation to it, but we really believe that automation can be used to serve people in the workplace and to make the world work better for people, not just make the world of work work without people. So when you look around at the people that are moving into that strategic realm, it's Cloud players, people who are providing either Cloud infrastructure or Cloud functions, a wide set of microservices capabilities, and people providing applications software as a service that start to cover a broader and broader portfolio. Clearly, Workday is thought of oftentimes as a strategic partner to their customers, because they provide a human capital management capability that's broader than just being a data repository. Salesforce is clearly a strategic partner to the sales and marketing organizations. The reality, though, is a lot of work that happens in the Enterprise cuts across these things, and so there's an opportunity for us to work with the Saleforces and the Workdays and the Googles and the Amazon Web Services of the world to help bring all of those things together. I think that what customers want is not only strategic technology providers, but strategic technology providers that will work with each other to solve customers' problems. >> John Donahoe on, I guess it was Tuesday, was saying we're very comfortable being that horizontal layer. We don't have to be the top layer, although I would observe that the more applications you develop, the more interesting the whole landscape becomes. >> Yeah, well, I think that's absolutely true. We're in the early stages of this, right? If you look at the amount of money that's spent in IT in the enterprise sector and then you start adding up all of these areas that I just mentioned, Cloud and SAS, it's still a very small amount of that overall spent. So clearly, big legacy technology vendors are incredibly relevant still today, but the challenge they'll have is making sure they stay relevant as this tide shifts to more Cloud, more intelligence, more automation in the workplace. >> I wonder if you could walk us through the process that you go through when you are working closely with customers, collaborating, trying to figure out what their problems are and solve them and then also solve the problems they don't even know they have, that you can provide solutions for. >> Actually, it's amazing, because in a lot of cases, the innovation, and this has been a phenomenal week, because I've gotten to meet with so many customers and see what they're doing. And what tends to happen with ServiceNow is the IT organization, oftentimes, it starts there. The IT organization brings it in for IT service management, and people start using that to request things that they need from IT, and they very quickly say, man, I have a process that would really benefit from exactly what you just did. Can you build my application on that? And so there starts to become this tidal wave of people asking the IT organization if they can start hosting applications on the platform. I'll give you one example from a company called Cox Automotive. Donna Woodruff, who's an innovation leader there and leads the ServiceNow platform team, found a process where they had a set of safety checks they do at all these remote sites as part of a car auctions, and it was a very spreadsheet-driven process that involved a lot of people doing manual checks, but it also had regulatory implications, insurance implications, and workplace happiness implications. And they were able to take this, put it on ServiceNow, and automate a lot of that process, make it faster, I should say digitize it, 'cause you still need the people going through and doing the checks, but were able to digitize it and make that person's job that much better. These applications are all over the place. They're in shared email inboxes, they're in Excel spreadsheets, they're in legacy applications. We don't actually have to go drive the innovation and the ideas. They end up coming to the ServiceNow platform owners and our customers. >> I'd like you to comment on some of the advantages of the platform and maybe some of the challenges that you face. When I think about enterprise software, I would generally characterize enterprise software as not a great user experience, oftentimes enterprise software products don't play well with other software products. They're highly complex. Oftentimes there's lots of customerization required, which means it's really hard to go from one state to another. Those are things that you generally don't suffer from. Are there others that give you advantages? And what are maybe some of the challenges that you face? >> I think it's true. Enterprise software, you used to have to train yourself to it. It's like, hey, we're going to roll out the new system. How are we going to train all the users? But you don't do that with the software we use in the consumer world. You download it from the app store and you start using it. If you can't figure it out, it's not going to go. >> You aint going to use it. >> Josh: Exactly right. So we put a lot of that thought process from the consumer world into our technology, but not just the technology we provide. We're trying to make it easier for our customers to then provide that onto their internal and external customers as well. Things like the Mobile Application Builder that we showed earlier today, that's coming in Madrid, it's an incredibly simple way to build a beautiful mobile application for almost anything in the workplace. And, again, as I was saying before, a lot of the ideas for applications come from people in the workplace. We've got to make it easy enough for them to not only to identify what the application potential is, but then build something that's amazing. What we're trying to do is put a lot of those design concepts, not just into the end products we sell, but into tools and technology that are part of the platform and the Platform Business Unit so that our customers can build something just like it in terms of experience, usability, simplicity, and power without having to have as many developers as we do. >> You and I have known each other for a number of years now, and just as we observed the other day, off camera, that you've been forced into a lot of challenges. I say forced, but welcomed a lot of challenges. >> I love it, I love it. >> All right, I mean, it's like, hey, I'll take that. No problem. You've had a variety of experiences at large companies. Things you've learned, opportunities ahead, maybe advice you'd give for others, like the hard stuff. >> I think one of the biggest things I've learned here, particularly at ServiceNow, is just the importance of staying focused on customers rather than competitors. I think a lot of times when you're in the business roles or strategy roles, you can really think a lot about who am I competing against, and you can forget that you really just need to solve the customer's problem as well as you possibly can. Be there for them when they need it. Have something that's compelling that addresses their needs, and stay laser-focused on what works for them, and at the end of the day you're got be successful. So that's a strategy we've really tried to take to heart at ServiceNow, is put the customers at the center of everything we do. We don't worry that much about competitors. They're out there and we know they're there and we study them, but it's really the customer that gets us up every morning. >> You know, it's interesting, I've had this, as well as John Furrier has, had this conversation with Andy Jassy a lot, and they're insanely focused on the customer where he says, even though he'll say, we get into a competitive situation, we'll take on anybody, but his point was both methods can work. Your former company, I would put into the very competitive, Oracle, I think, is the same way. Microsoft maybe used to me, maybe that's changing, but to a great extent would rip your face off if you were a competitor. My question is this: Is the efficacy of the head-to-head, competitive drive as effective as it used to be, and are we seeing a change toward a customer-centric success model? >> I think there's two things going on. I think one is once a market really kind of reaches maturity, the competitive dynamic really heats up. >> Dave: 'Cause you got to gain share. >> Yeah, you got to gain share. And today, in the Cloud world, in the intelligence world, there's just so much opportunity that you could just keep going for a long time before you even bump into people. I think in mature markets it's different, so I think a lot of times, partly at EMC, that was one of the dynamics we had is a very, very mature market on on-premise storage, and so you had to go head-to-head every time. But I think there's also the changing tenor of the world. People have a lot less, they don't care for that kind of dialogue as much anymore. They don't like it when you come in and talk bad about anybody else. So I think there's both dynamics at one, and the markets we're in, they're so new, they're growing so fast that it's not as important, but also, people don't care for it. I don't think it helps, if anything, sometimes it makes people wonder if they ought to be, oh, I didn't think about talking to them, maybe we should go call the competitor you just mentioned. (laughing) so, all that said, when you get into a fight, you got to fight hard and you got to come with the best stuff, so I think that's the reality. >> Dave: Great answer. >> That's a good note to end on. Thanks so much, Josh, for coming on theCUBE again. It's been a real pleasure having you here. >> All right. Thank you, I really appreciate it. >> I'm Rebecca Knight for Dave Vellante. We will have more from ServiceNow Knowledge 18 just after this. (techy music)
SUMMARY :
Brought to you by ServiceNow. He is the General Manager of Platforms, ServiceNow. Yeah, really excited to be here. Yeah that's right. Yes, congrats on the recent promotion. and the Customer Success Management Team. I'm like, okay, what do you mean? and I think the more you can be thought of as a platform, particularly the CIOs that I talk to, you are becoming, and the Amazon Web Services of the world I would observe that the more applications you develop, in the enterprise sector and then you start adding up that you can provide solutions for. and leads the ServiceNow platform team, and maybe some of the challenges that you face. You download it from the app store and you start using it. but not just the technology we provide. and just as we observed the other day, off camera, maybe advice you'd give for others, like the hard stuff. and at the end of the day you're got be successful. and are we seeing a change the competitive dynamic really heats up. and so you had to go head-to-head every time. It's been a real pleasure having you here. All right. I'm Rebecca Knight for Dave Vellante.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Josh | PERSON | 0.99+ |
Rebecca Knight | PERSON | 0.99+ |
Josh Kahn | PERSON | 0.99+ |
Donna Woodruff | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Cox Automotive | ORGANIZATION | 0.99+ |
John Donahoe | PERSON | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
Madrid | LOCATION | 0.99+ |
Sun Microsystems | ORGANIZATION | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
two things | QUANTITY | 0.99+ |
Tuesday | DATE | 0.99+ |
Excel | TITLE | 0.99+ |
Andy Jassy | PERSON | 0.99+ |
Andy McAfee | PERSON | 0.99+ |
ServiceNow | ORGANIZATION | 0.99+ |
Erik Brynjolfsson | PERSON | 0.99+ |
Amazon Web Services | ORGANIZATION | 0.99+ |
theCUBE | ORGANIZATION | 0.99+ |
both methods | QUANTITY | 0.98+ |
EMC | ORGANIZATION | 0.97+ |
John Furrier | PERSON | 0.97+ |
one | QUANTITY | 0.97+ |
Googles | ORGANIZATION | 0.96+ |
one example | QUANTITY | 0.95+ |
ServiceNow Knowledge 18 | TITLE | 0.95+ |
Salesforce | ORGANIZATION | 0.95+ |
today | DATE | 0.95+ |
SAS | ORGANIZATION | 0.93+ |
Saleforces | ORGANIZATION | 0.92+ |
ServiceNow | TITLE | 0.92+ |
SAP | ORGANIZATION | 0.89+ |
ServiceNow Knowledge 2018 | TITLE | 0.88+ |
both dynamics | QUANTITY | 0.88+ |
earlier today | DATE | 0.85+ |
Scott McNealy | ORGANIZATION | 0.83+ |
one state | QUANTITY | 0.74+ |
Cloud | TITLE | 0.65+ |
Knowledge18 | TITLE | 0.61+ |
years | DATE | 0.49+ |
Mobile Application | ORGANIZATION | 0.4+ |
18 | ORGANIZATION | 0.37+ |
Knowledge | TITLE | 0.36+ |
Builder | TITLE | 0.35+ |
Nathan Hart, NextGear Capital | PentahoWorld 2017
(upbeat music) >> Announcer: Live from Orlando Florida, it's theCUBE covering PentahoWorld 2017. Brought to you by Hitachi Vantara. >> Welcome back to theCUBE's live coverage of PentahoWorld, brought to you of course by Hitachi Vantara. My name is Rebecca Knight, and I'm here with Dave Vellante, my co-host. We are joined by Nathan Hart, he is the Development Manager at NextGear Capital. Thanks so much for coming on theCUBE, Nathan. >> Thanks for having me. >> So let's start by telling our viewers a little bit about what NextGear Capital is, and what you do there. >> Sure, NextGear Capital is a, we do auto financing for auto dealerships, so if a dealer goes to an auction and wants to buy some inventory, we're going to be the ones who actually finance that and purchase it for them, and then they pay us back. >> Great, and your role as a development manager. >> Yep, I am over our integrations team, so we are responsible for basically getting data in and out of the company, a lot of that is getting data to and from our sister companies, all under Cox Automotive. >> And the data we're talking about is? >> Uh, it's a whole lot of things, obviously it's a lot of financial data, as we are a finance company, but a lot of things like inventory, unit statuses, where a car is located, we have credit scores, and that sort of work as well, so all kinds of data are coming in and out and then into our systems. >> So, are the cars instrumented to the point where you can kind of track where they are in an automated way, or is it? >> Yes, we do have some GPS units, not on all that inventory, just because we have quite a few open floor plans, about 500,000 I believe. But yes, we do have some select units that are GPS'd that we can track that way, or we have inspectors that go to lots. >> Okay so as a developer you know this story well, back in the day if you had a big data problem, you'd buy a Unix box and you'd stuff all the data in there and then you'd buy a bunch of Oracle licenses, and if you had any money left over, you could maybe do something, maybe buy a little storage, or conduct business. Okay that changed, quite dramatically. I wonder, if you could tell us your version of that story and how it's affected your business. >> Sure, so, uh. (laughter) >> Dave: Is it a fair representation? >> Not, not... >> Dave: Is the old world, was it a big data warehouse world? >> Yeah, so. >> Where it's sort of expensive to get stuff in and get stuff out and has that changed? Or is that sort of? >> Yeah, it has changed greatly, we're not quite that bad, but we do currently have an older monolithic database system that we are trying to get away from. >> Dave: It's hard. >> Yeah, exactly. And so a lot of our processes right now, go in and come out of this so obviously, if anything in that breaks, it hurts everywhere. >> Dave: Right. >> So yes. >> Dave: Sort of a chain reaction. >> Exactly. >> Okay, but so how have you, talk about the journey of bringing in Pentaho and how that has affected you. >> Sure, Pentaho has been great for us, just in terms of being able to be really flexible with our data. Like I said, we're trying to get away from this monolithic service, so we have, in Pentaho, we can easily branch off and say, go to the monolithic database, but also talk to another service that is going to replace it. And then it's just one click of a button, and now this is off, this is on, or we can do both and have some replication going, just so we have that flexibility, and that kind of adaptability around those changes. >> So why Pentaho, I mean, a lot of tools out there, there's open source, you could roll your own, you could do everything in the cloud, why Pentaho? >> We liked Pentaho because of the, I guess the freedom and independence it kind of offers, in the sense that it allows us to have a large set of steps and tools that are already prebuilt, that we can just use right out of the box, and, it's just a massive library, far greater than most of the competition that we looked at. And then it also is just built on this great Java platform that we can, if we need to, write a custom Java class, pop it in, and then that can do what we need to, if we don't have something out of the box. >> Dave: So it's integrated, >> Yep >> but it's customizable. >> Nathan: Exactly. >> If you need it to be. >> Nathan: Yep. >> Okay, and one of the things that customers like you tell us about Pentaho is that they like the sort of end-to-end integration. >> Nathan: Yep. >> We were talking off camera, you had mentioned that you've got an initiative to move toward the cloud. Maybe you could talk about that a little bit. >> Yeah, so right now, just Cox, as a whole, is kind of investigating the cloud. I definitely don't want to speak out of turn, or say we're definitely going there, but that is the current initiatives are to start experimenting with how we can leverage this more. I know one of the, kind of the first steps that we're taking towards that is we have large archives, we keep all of the files we've ever received or sent out, and we don't access them much, we don't need them much, but we want to keep them, just so we have this history, and we can always look back if we need to. So using the cloud for something like that, where's it's just like a deep storage, where we can just upload it and forget it, and if we ever need it, it's there and easily accessible, and this way we don't have to pay for as much storage on print. >> Very workload specific, cheap storage. >> Nathan: Yep. >> Probably a lot of test and dev. >> Nathan: Exactly. >> So going back to the Pentaho, and why Pentaho, and you mentioned the freedom and the flexibility that it provides, can you talk about some of the best practices that you've discovered that could help some other Hitachi Vantara customers? >> Absolutely, the biggest change, learning curve that we went through, my first introduction was Pentaho when I started at NextGear, and it was a real huge learning curve for the whole team. We all started within about a month of each other, and there were only three of us to start. So, it was a real learning curve of, okay, here's how we do this, here's how we do this. So, once we kind of got the workflow going and understanding what we were trying to do, the next step was figuring out okay we can make this very modular, we can build a sub job that does a very specific task, and we can use it everywhere. And we just did that again and again and again, so now we have a library of about 118 different utilities that we can just plug and drop anywhere and they just do what they need to do, we don't need to re-test them, we don't need to think about them ever. And of course, if we update one of those, it updates every single job that it touches. As soon as we kind of unlocked that and figured we didn't have to make a custom solution for every single job, that we could use a lot of reuseability. It really sped up our development, and how we do things. >> Could you talk about data sources, have they or how have they evolved over the last decade? >> Sure, I can't speak for the whole decade, I haven't actually been in the industry that long, but a lot of what we came into and inherited when I came in, were flat files, just everything is CSV, TXT, either in or out, and we still do a lot of that, that's still kind of our bread and butter, just by the nature of our current role, but as it's changing we are interacting more and more with APIs. We're shifting away from this monolithic database into micro services so we're having to interact with those a lot more and figure out how we can get that real time communication and get the data where it needs to go so it's all in its happy place. >> One of the things that Brian Householder, the CEO, got up on the main stage and talked about how, for companies, the two most important assets are the people and the data. I want to talk to you about the people aspect. >> Nathan: Okay. >> We're hearing so much about the shortage, the tech shortage of data scientists, and other kinds of talent in this industry. How hard is it for you to recruit? Your company, as you said, is based in Carmel, Indiana is that right? >> Nathan: Yep. >> What are you finding out there? >> The greater Indianapolis area, like many other places, is very starved for tech talent. It's very, very easy as a developer to throw a stone and get an interview. It's definitely a challenge. We actually currently have two openings on my team. Just, do less with more and do what we can. So, it's definitely a challenge, but I think that there's a lot of really great young talent coming out of colleges right now that are coming in, they've grown up with this right? They're a lot further along than necessarily I was when I came out of school and some of our other developers. So they can step in and already understand a lot of these complex architectures that we're dealing with and can just hit the ground running. >> So at least 10 times a week, I get somebody hitting me on LinkedIn about hey do you need development resources? (Nathan laughing) As a developer, it must happen to you 100 times a week, but there's obviously challenges of off-shoring and managing that remotely. I'm sure you've thought about it. What are your thoughts on off-shoring? You want someone there in a bee hive effect? Maybe talk about that a little bit. So, at NextGear we've been fairly rigid about butts in the seats, in the office, real collaborative environment, where you're at the morning stand up, you're there in the meetings, and it's a very present environment. And we are being a little bit more adaptable with that, just as time changes and other companies, obviously do offer more remote from home or what have you, so that is shifting a little bit, as far as necessarily off-shoring, that's way above my pay grade to even make that call, I have worked in previous environments where that was a large part of it. In a previously life we had a US based team and then we had a Malaysia based team, and I thought it was a really great experience cause we basically all had our own counterparts over there, so at the end of your day, you just email your notes, here's what I did today, here's where I left off, and they pick it up and do the same, then we had about a weekly meeting. So I think it definitely can work, I'm all for the global tech community all coming up together, when appropriate and when it works. >> But you've got to have the right infrastructure and processes in place, >> Nathan: Absolutely. >> Or it's just, it sucks all your productivity out. >> Nathan: Absolutely, if you spend half your day trying to figure out what the other person did, then you've lost your day. >> Yeah, right. And you follow the sun, yes and no right, you've got to wait for the sun sometimes. Pentaho, back to Pentaho, what are the things that, as a customer, you want them to do. What's on their to-do list, you know, when you're talking to Donna Prlich and her team, what are you pushing them for? >> So, the biggest things kind of on our wish list and that we're seeing is interacting more natively with those microservices like I mentioned and I was really glad that that came up in the keynote as something that they're focusing on and it's something that is going to come up in 8.0, at least the kind of stepping stones to go in that direction. So, that's really exciting stuff for us, just it answers a lot of questions we're currently having of how are we going to interact with those, and the answer can still be Pentaho moving forward. >> I was struck in the keynote, when Brian was asking hands up please, how many people are doing business with Hitachi outside of Pentaho, and just a smattering, right, I presume your hand was down. >> Nathan: My hand was down. >> And then, had you heard of Hitachi Vantara? >> I read the press release when they first announced Vantara, but that's about the extent of it. Obviously I knew about Hitachi from when they purchased Pentaho. We actually were having a week long, kind of a tech support get together that week that it happened, so I think on the Tuesday or something, our rep was like I now work for Hitachi. It was a fun thing, but yeah I'm not terribly familiar with Hitachi's products or, obviously I know where they're going with the Vantara concept, but. >> As a developer in a very focused area, >> Yep. >> Cox Automotive, obviously has some IOT initiatives, I'm sure, >> Absolutely. >> And some process automation, but I presume you haven't really dug into that yet, but when you think about the messaging that you heard this morning. What does it mean to you? Do you say, okay, nice, but I've got other problems? Or do you see the potential to leverage some of the technologies down the road? I definitely see the potential to start, at least exploring that direction, and figuring out what can we get out of this, right. It makes a lot more sense to play in a singular ecosystem and have all those tools at our hand just in one bucket instead of trying to figure out how does this play nice with this, how does this play nice over here, if we just can have a singular ecosystem that does it all together, that definitely makes our jobs a lot easier. >> How about the event, is this your first PentahoWorld? >> Yep, this is my first PentahoWorld. >> So it's early, but why do you come to events like this, and what do you hope to take away? >> Sure, I came to this event, cause I was specifically invited to. That's really it. It was nothing more than that, but I definitely come to kind of, see what's next and learn about the new technologies, and get that chance to visit some of the booths and some of the breakout sessions for maybe things that I don't get to do in my day to day life. We're very heads down in PDI so I don't get to spend too much time learning about the analytics and playing with those tools. So it's a lot of fun to come here and kind of see what's out there and be like, oh could we leverage this, or how could I adapt, or what are some of the other professionals doing that maybe I can bring back and improve our processes. >> And it's early days, but what are your thoughts on 8.0? >> I liked what I saw, and then I stopped by the booth and got another demo and I can definitely already see a couple of use cases where we can improve existing jobs with some of the new streaming features that they have in play, so I'm excited for that to come out and for us to start working with that. >> So that, the integration of streaming, Kafka, and the like was appealing to you? >> Yep, absolutely, and that'll be something that we can probably use right out of the gate, so excited for that. >> Well great, Nathan thank you so much for coming on theCUBE. >> Nathan: Yeah, thank you. >> I'm Rebecca Knight for Dave Vellante, we will have more from PentahoWorld just after this. (upbeat music)
SUMMARY :
Brought to you by Hitachi Vantara. brought to you of course and what you do there. is a, we do auto financing Great, and your role a lot of that is getting data to and from we have credit scores, and that are GPS'd that we can track that way, back in the day if you Sure, so, uh. that we are trying to get away from. if anything in that breaks, talk about the journey of just so we have that flexibility, that we can just use right out of the box, Okay, and one of the about that a little bit. and this way we don't have to pay that we can just plug and drop anywhere and get the data where it needs to go One of the things that How hard is it for you to recruit? of colleges right now that are coming in, and do the same, then we all your productivity out. the other person did, the sun, yes and no right, and the answer can still and just a smattering, right, I read the press I definitely see the potential to start, and get that chance to what are your thoughts on 8.0? that to come out and for us that we can probably use right out Well great, Nathan thank you so much we will have more from
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
Hitachi | ORGANIZATION | 0.99+ |
Brian | PERSON | 0.99+ |
Nathan | PERSON | 0.99+ |
Rebecca Knight | PERSON | 0.99+ |
Nathan Hart | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Donna Prlich | PERSON | 0.99+ |
Brian Householder | PERSON | 0.99+ |
Pentaho | ORGANIZATION | 0.99+ |
NextGear Capital | ORGANIZATION | 0.99+ |
Cox Automotive | ORGANIZATION | 0.99+ |
NextGear | ORGANIZATION | 0.99+ |
US | LOCATION | 0.99+ |
Orlando Florida | LOCATION | 0.99+ |
Malaysia | LOCATION | 0.99+ |
Tuesday | DATE | 0.99+ |
Java | TITLE | 0.99+ |
first | QUANTITY | 0.99+ |
Nath | PERSON | 0.99+ |
both | QUANTITY | 0.99+ |
today | DATE | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
one click | QUANTITY | 0.99+ |
Hitachi Vantara | ORGANIZATION | 0.98+ |
theCUBE | ORGANIZATION | 0.98+ |
first steps | QUANTITY | 0.98+ |
100 times a week | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
about 500,000 | QUANTITY | 0.98+ |
PentahoWorld | EVENT | 0.98+ |
Carmel, Indiana | LOCATION | 0.98+ |
One | QUANTITY | 0.98+ |
half | QUANTITY | 0.97+ |
Indianapolis | LOCATION | 0.96+ |
two openings | QUANTITY | 0.96+ |
three | QUANTITY | 0.96+ |
about 118 different utilities | QUANTITY | 0.96+ |
about a month | QUANTITY | 0.96+ |
ORGANIZATION | 0.96+ | |
PentahoWorld | ORGANIZATION | 0.95+ |
2017 | DATE | 0.95+ |
one bucket | QUANTITY | 0.95+ |
first introduction | QUANTITY | 0.93+ |
Kafka | TITLE | 0.89+ |
this morning | DATE | 0.88+ |
Vantara | ORGANIZATION | 0.88+ |
last decade | DATE | 0.85+ |
10 times a week | QUANTITY | 0.85+ |
Wikibon Presents: Software is Eating the Edge | The Entangling of Big Data and IIoT
>> So as folks make their way over from Javits I'm going to give you the least interesting part of the evening and that's my segment in which I welcome you here, introduce myself, lay out what what we're going to do for the next couple of hours. So first off, thank you very much for coming. As all of you know Wikibon is a part of SiliconANGLE which also includes theCUBE, so if you look around, this is what we have been doing for the past couple of days here in the TheCUBE. We've been inviting some significant thought leaders from over on the show and in incredibly expensive limousines driven them up the street to come on to TheCUBE and spend time with us and talk about some of the things that are happening in the industry today that are especially important. We tore it down, and we're having this party tonight. So we want to thank you very much for coming and look forward to having more conversations with all of you. Now what are we going to talk about? Well Wikibon is the research arm of SiliconANGLE. So we take data that comes out of TheCUBE and other places and we incorporated it into our research. And work very closely with large end users and large technology companies regarding how to make better decisions in this incredibly complex, incredibly important transformative world of digital business. What we're going to talk about tonight, and I've got a couple of my analysts assembled, and we're also going to have a panel, is this notion of software is eating the Edge. Now most of you have probably heard Marc Andreessen, the venture capitalist and developer, original developer of Netscape many years ago, talk about how software's eating the world. Well, if software is truly going to eat the world, it's going to eat at, it's going to take the big chunks, big bites at the Edge. That's where the actual action's going to be. And what we want to talk about specifically is the entangling of the internet or the industrial internet of things and IoT with analytics. So that's what we're going to talk about over the course of the next couple of hours. To do that we're going to, I've already blown the schedule, that's on me. But to do that I'm going to spend a couple minutes talking about what we regard as the essential digital business capabilities which includes analytics and Big Data, and includes IIoT and we'll explain at least in our position why those two things come together the way that they do. But I'm going to ask the august and revered Neil Raden, Wikibon analyst to come on up and talk about harvesting value at the Edge. 'Cause there are some, not now Neil, when we're done, when I'm done. So I'm going to ask Neil to come on up and we'll talk, he's going to talk about harvesting value at the Edge. And then Jim Kobielus will follow up with him, another Wikibon analyst, he'll talk specifically about how we're going to take that combination of analytics and Edge and turn it into the new types of systems and software that are going to sustain this significant transformation that's going on. And then after that, I'm going to ask Neil and Jim to come, going to invite some other folks up and we're going to run a panel to talk about some of these issues and do a real question and answer. So the goal here is before we break for drinks is to create a community feeling within the room. That includes smart people here, smart people in the audience having a conversation ultimately about some of these significant changes so please participate and we look forward to talking about the rest of it. All right, let's get going! What is digital business? One of the nice things about being an analyst is that you can reach back on people who were significantly smarter than you and build your points of view on the shoulders of those giants including Peter Drucker. Many years ago Peter Drucker made the observation that the purpose of business is to create and keep a customer. Not better shareholder value, not anything else. It is about creating and keeping your customer. Now you can argue with that, at the end of the day, if you don't have customers, you don't have a business. Now the observation that we've made, what we've added to that is that we've made the observation that the difference between business and digital business essentially is one thing. That's data. A digital business uses data to differentially create and keep customers. That's the only difference. If you think about the difference between taxi cab companies here in New York City, every cab that I've been in in the last three days has bothered me about Uber. The reason, the difference between Uber and a taxi cab company is data. That's the primary difference. Uber uses data as an asset. And we think this is the fundamental feature of digital business that everybody has to pay attention to. How is a business going to use data as an asset? Is the business using data as an asset? Is a business driving its engagement with customers, the role of its product et cetera using data? And if they are, they are becoming a more digital business. Now when you think about that, what we're really talking about is how are they going to put data to work? How are they going to take their customer data and their operational data and their financial data and any other kind of data and ultimately turn that into superior engagement or improved customer experience or more agile operations or increased automation? Those are the kinds of outcomes that we're talking about. But it is about putting data to work. That's fundamentally what we're trying to do within a digital business. Now that leads to an observation about the crucial strategic business capabilities that every business that aspires to be more digital or to be digital has to put in place. And I want to be clear. When I say strategic capabilities I mean something specific. When you talk about, for example technology architecture or information architecture there is this notion of what capabilities does your business need? Your business needs capabilities to pursue and achieve its mission. And in the digital business these are the capabilities that are now additive to this core question, ultimately of whether or not the company is a digital business. What are the three capabilities? One, you have to capture data. Not just do a good job of it, but better than your competition. You have to capture data better than your competition. In a way that is ultimately less intrusive on your markets and on your customers. That's in many respects, one of the first priorities of the internet of things and people. The idea of using sensors and related technologies to capture more data. Once you capture that data you have to turn it into value. You have to do something with it that creates business value so you can do a better job of engaging your markets and serving your customers. And that essentially is what we regard as the basis of Big Data. Including operations, including financial performance and everything else, but ultimately it's taking the data that's being captured and turning it into value within the business. The last point here is that once you have generated a model, or an insight or some other resource that you can act upon, you then have to act upon it in the real world. We call that systems of agency, the ability to enact based on data. Now I want to spend just a second talking about systems of agency 'cause we think it's an interesting concept and it's something Jim Kobielus is going to talk about a little bit later. When we say systems of agency, what we're saying is increasingly machines are acting on behalf of a brand. Or systems, combinations of machines and people are acting on behalf of the brand. And this whole notion of agency is the idea that ultimately these systems are now acting as the business's agent. They are at the front line of engaging customers. It's an extremely rich proposition that has subtle but crucial implications. For example I was talking to a senior decision maker at a business today and they made a quick observation, they talked about they, on their way here to New York City they had followed a woman who was going through security, opened up her suitcase and took out a bird. And then went through security with the bird. And the reason why I bring this up now is as TSA was trying to figure out how exactly to deal with this, the bird started talking and repeating things that the woman had said and many of those things, in fact, might have put her in jail. Now in this case the bird is not an agent of that woman. You can't put the woman in jail because of what the bird said. But increasingly we have to ask ourselves as we ask machines to do more on our behalf, digital instrumentation and elements to do more on our behalf, it's going to have blow back and an impact on our brand if we don't do it well. I want to draw that forward a little bit because I suggest there's going to be a new lifecycle for data. And the way that we think about it is we have the internet or the Edge which is comprised of things and crucially people, using sensors, whether they be smaller processors in control towers or whether they be phones that are tracking where we go, and this crucial element here is something that we call information transducers. Now a transducer in a traditional sense is something that takes energy from one form to another so that it can perform new types of work. By information transducer I essentially mean it takes information from one form to another so it can perform another type of work. This is a crucial feature of data. One of the beauties of data is that it can be used in multiple places at multiple times and not engender significant net new costs. It's one of the few assets that you can say about that. So the concept of an information transducer's really important because it's the basis for a lot of transformations of data as data flies through organizations. So we end up with the transducers storing data in the form of analytics, machine learning, business operations, other types of things, and then it goes back and it's transduced, back into to the real world as we program the real world and turning into these systems of agency. So that's the new lifecycle. And increasingly, that's how we have to think about data flows. Capturing it, turning it into value and having it act on our behalf in front of markets. That could have enormous implications for how ultimately money is spent over the next few years. So Wikibon does a significant amount of market research in addition to advising our large user customers. And that includes doing studies on cloud, public cloud, but also studies on what's happening within the analytics world. And if you take a look at it, what we basically see happening over the course of the next few years is significant investments in software and also services to get the word out. But we also expect there's going to be a lot of hardware. A significant amount of hardware that's ultimately sold within this space. And that's because of something that we call true private cloud. This concept of ultimately a business increasingly being designed and architected around the idea of data assets means that the reality, the physical realities of how data operates, how much it costs to store it or move it, the issues of latency, the issues of intellectual property protection as well as things like the regulatory regimes that are being put in place to govern how data gets used in between locations. All of those factors are going to drive increased utilization of what we call true private cloud. On premise technologies that provide the cloud experience but act where the data naturally needs to be processed. I'll come a little bit more to that in a second. So we think that it's going to be a relatively balanced market, a lot of stuff is going to end up in the cloud, but as Neil and Jim will talk about, there's going to be an enormous amount of analytics that pulls an enormous amount of data out to the Edge 'cause that's where the action's going to be. Now one of the things I want to also reveal to you is we've done a fair amount of data, we've done a fair amount of research around this question of where or how will data guide decisions about infrastructure? And in particular the Edge is driving these conversations. So here is a piece of research that one of our cohorts at Wikibon did, David Floyer. Taking a look at IoT Edge cost comparisons over a three year period. And it showed on the left hand side, an example where the sensor towers and other types of devices were streaming data back into a central location in a wind farm, stylized wind farm example. Very very expensive. Significant amounts of money end up being consumed, significant resources end up being consumed by the cost of moving the data from one place to another. Now this is even assuming that latency does not become a problem. The second example that we looked at is if we kept more of that data at the Edge and processed at the Edge. And literally it is a 85 plus percent cost reduction to keep more of the data at the Edge. Now that has enormous implications, how we think about big data, how we think about next generation architectures, et cetera. But it's these costs that are going to be so crucial to shaping the decisions that we make over the next two years about where we put hardware, where we put resources, what type of automation is possible, and what types of technology management has to be put in place. Ultimately we think it's going to lead to a structure, an architecture in the infrastructure as well as applications that is informed more by moving cloud to the data than moving the data to the cloud. That's kind of our fundamental proposition is that the norm in the industry has been to think about moving all data up to the cloud because who wants to do IT? It's so much cheaper, look what Amazon can do. Or what AWS can do. All true statements. Very very important in many respects. But most businesses today are starting to rethink that simple proposition and asking themselves do we have to move our business to the cloud, or can we move the cloud to the business? And increasingly what we see happening as we talk to our large customers about this, is that the cloud is being extended out to the Edge, we're moving the cloud and cloud services out to the business. Because of economic reasons, intellectual property control reasons, regulatory reasons, security reasons, any number of other reasons. It's just a more natural way to deal with it. And of course, the most important reason is latency. So with that as a quick backdrop, if I may quickly summarize, we believe fundamentally that the difference today is that businesses are trying to understand how to use data as an asset. And that requires an investment in new sets of technology capabilities that are not cheap, not simple and require significant thought, a lot of planning, lot of change within an IT and business organizations. How we capture data, how we turn it into value, and how we translate that into real world action through software. That's going to lead to a rethinking, ultimately, based on cost and other factors about how we deploy infrastructure. How we use the cloud so that the data guides the activity and not the choice of cloud supplier determines or limits what we can do with our data. And that's going to lead to this notion of true private cloud and elevate the role the Edge plays in analytics and all other architectures. So I hope that was perfectly clear. And now what I want to do is I want to bring up Neil Raden. Yes, now's the time Neil! So let me invite Neil up to spend some time talking about harvesting value at the Edge. Can you see his, all right. Got it. >> Oh boy. Hi everybody. Yeah, this is a really, this is a really big and complicated topic so I decided to just concentrate on something fairly simple, but I know that Peter mentioned customers. And he also had a picture of Peter Drucker. I had the pleasure in 1998 of interviewing Peter and photographing him. Peter Drucker, not this Peter. Because I'd started a magazine called Hired Brains. It was for consultants. And Peter said, Peter said a number of really interesting things to me, but one of them was his definition of a customer was someone who wrote you a check that didn't bounce. He was kind of a wag. He was! So anyway, he had to leave to do a video conference with Jack Welch and so I said to him, how do you charge Jack Welch to spend an hour on a video conference? And he said, you know I have this theory that you should always charge your client enough that it hurts a little bit or they don't take you seriously. Well, I had the chance to talk to Jack's wife, Suzie Welch recently and I told her that story and she said, "Oh he's full of it, Jack never paid "a dime for those conferences!" (laughs) So anyway, all right, so let's talk about this. To me, things about, engineered things like the hardware and network and all these other standards and so forth, we haven't fully developed those yet, but they're coming. As far as I'm concerned, they're not the most interesting thing. The most interesting thing to me in Edge Analytics is what you're going to get out of it, what the result is going to be. Making sense of this data that's coming. And while we're on data, something I've been thinking a lot lately because everybody I've talked to for the last three days just keeps talking to me about data. I have this feeling that data isn't actually quite real. That any data that we deal with is the result of some process that's captured it from something else that's actually real. In other words it's proxy. So it's not exactly perfect. And that's why we've always had these problems about customer A, customer A, customer A, what's their definition? What's the definition of this, that and the other thing? And with sensor data, I really have the feeling, when companies get, not you know, not companies, organizations get instrumented and start dealing with this kind of data what they're going to find is that this is the first time, and I've been involved in analytics, I don't want to date myself, 'cause I know I look young, but the first, I've been dealing with analytics since 1975. And everything we've ever done in analytics has involved pulling data from some other system that was not designed for analytics. But if you think about sensor data, this is data that we're actually going to catch the first time. It's going to be ours! We're not going to get it from some other source. It's going to be the real deal, to the extent that it's the real deal. Now you may say, ya know Neil, a sensor that's sending us information about oil pressure or temperature or something like that, how can you quarrel with that? Well, I can quarrel with it because I don't know if the sensor's doing it right. So we still don't know, even with that data, if it's right, but that's what we have to work with. Now, what does that really mean? Is that we have to be really careful with this data. It's ours, we have to take care of it. We don't get to reload it from source some other day. If we munge it up it's gone forever. So that has, that has very serious implications, but let me, let me roll you back a little bit. The way I look at analytics is it's come in three different eras. And we're entering into the third now. The first era was business intelligence. It was basically built and governed by IT, it was system of record kind of reporting. And as far as I can recall, it probably started around 1988 or at least that's the year that Howard Dresner claims to have invented the term. I'm not sure it's true. And things happened before 1988 that was sort of like BI, but 88 was when they really started coming out, that's when we saw BusinessObjects and Cognos and MicroStrategy and those kinds of things. The second generation just popped out on everybody else. We're all looking around at BI and we were saying why isn't this working? Why are only five people in the organization using this? Why are we not getting value out of this massive license we bought? And along comes companies like Tableau doing data discovery, visualization, data prep and Line of Business people are using this now. But it's still the same kind of data sources. It's moved out a little bit, but it still hasn't really hit the Big Data thing. Now we're in third generation, so we not only had Big Data, which has come and hit us like a tsunami, but we're looking at smart discovery, we're looking at machine learning. We're looking at AI induced analytics workflows. And then all the natural language cousins. You know, natural language processing, natural language, what's? Oh Q, natural language query. Natural language generation. Anybody here know what natural language generation is? Yeah, so what you see now is you do some sort of analysis and that tool comes up and says this chart is about the following and it used the following data, and it's blah blah blah blah blah. I think it's kind of wordy and it's going to refined some, but it's an interesting, it's an interesting thing to do. Now, the problem I see with Edge Analytics and IoT in general is that most of the canonical examples we talk about are pretty thin. I know we talk about autonomous cars, I hope to God we never have them, 'cause I'm a car guy. Fleet Management, I think Qualcomm started Fleet Management in 1988, that is not a new application. Industrial controls. I seem to remember, I seem to remember Honeywell doing industrial controls at least in the 70s and before that I wasn't, I don't want to talk about what I was doing, but I definitely wasn't in this industry. So my feeling is we all need to sit down and think about this and get creative. Because the real value in Edge Analytics or IoT, whatever you want to call it, the real value is going to be figuring out something that's new or different. Creating a brand new business. Changing the way an operation happens in a company, right? And I think there's a lot of smart people out there and I think there's a million apps that we haven't even talked about so, if you as a vendor come to me and tell me how great your product is, please don't talk to me about autonomous cars or Fleet Managing, 'cause I've heard about that, okay? Now, hardware and architecture are really not the most interesting thing. We fell into that trap with data warehousing. We've fallen into that trap with Big Data. We talk about speeds and feeds. Somebody said to me the other day, what's the narrative of this company? This is a technology provider. And I said as far as I can tell, they don't have a narrative they have some products and they compete in a space. And when they go to clients and the clients say, what's the value of your product? They don't have an answer for that. So we don't want to fall into this trap, okay? Because IoT is going to inform you in ways you've never even dreamed about. Unfortunately some of them are going to be really stinky, you know, they're going to be really bad. You're going to lose more of your privacy, it's going to get harder to get, I dunno, mortgage for example, I dunno, maybe it'll be easier, but in any case, it's not going to all be good. So let's really think about what you want to do with this technology to do something that's really valuable. Cost takeout is not the place to justify an IoT project. Because number one, it's very expensive, and number two, it's a waste of the technology because you should be looking at, you know the old numerator denominator thing? You should be looking at the numerators and forget about the denominators because that's not what you do with IoT. And the other thing is you don't want to get over confident. Actually this is good advice about anything, right? But in this case, I love this quote by Derek Sivers He's a pretty funny guy. He said, "If more information was the answer, "then we'd all be billionaires with perfect abs." I'm not sure what's on his wishlist, but you know, I would, those aren't necessarily the two things I would think of, okay. Now, what I said about the data, I want to explain some more. Big Data Analytics, if you look at this graphic, it depicts it perfectly. It's a bunch of different stuff falling into the funnel. All right? It comes from other places, it's not original material. And when it comes in, it's always used as second hand data. Now what does that mean? That means that you have to figure out the semantics of this information and you have to find a way to put it together in a way that's useful to you, okay. That's Big Data. That's where we are. How is that different from IoT data? It's like I said, IoT is original. You can put it together any way you want because no one else has ever done that before. It's yours to construct, okay. You don't even have to transform it into a schema because you're creating the new application. But the most important thing is you have to take care of it 'cause if you lose it, it's gone. It's the original data. It's the same way, in operational systems for a long long time we've always been concerned about backup and security and everything else. You better believe this is a problem. I know a lot of people think about streaming data, that we're going to look at it for a minute, and we're going to throw most of it away. Personally I don't think that's going to happen. I think it's all going to be saved, at least for a while. Now, the governance and security, oh, by the way, I don't know where you're going to find a presentation where somebody uses a newspaper clipping about Vladimir Lenin, but here it is, enjoy yourselves. I believe that when people think about governance and security today they're still thinking along the same grids that we thought about it all along. But this is very very different and again, I'm sorry I keep thrashing this around, but this is treasured data that has to be carefully taken care of. Now when I say governance, my experience has been over the years that governance is something that IT does to make everybody's lives miserable. But that's not what I mean by governance today. It means a comprehensive program to really secure the value of the data as an asset. And you need to think about this differently. Now the other thing is you may not get to think about it differently, because some of the stuff may end up being subject to regulation. And if the regulators start regulating some of this, then that'll take some of the degrees of freedom away from you in how you put this together, but you know, that's the way it works. Now, machine learning, I think I told somebody the other day that claims about machine learning in software products are as common as twisters in trail parks. And a lot of it is not really what I'd call machine learning. But there's a lot of it around. And I think all of the open source machine learning and artificial intelligence that's popped up, it's great because all those math PhDs who work at Home Depot now have something to do when they go home at night and they construct this stuff. But if you're going to have machine learning at the Edge, here's the question, what kind of machine learning would you have at the Edge? As opposed to developing your models back at say, the cloud, when you transmit the data there. The devices at the Edge are not very powerful. And they don't have a lot of memory. So you're only going to be able to do things that have been modeled or constructed somewhere else. But that's okay. Because machine learning algorithm development is actually slow and painful. So you really want the people who know how to do this working with gobs of data creating models and testing them offline. And when you have something that works, you can put it there. Now there's one thing I want to talk about before I finish, and I think I'm almost finished. I wrote a book about 10 years ago about automated decision making and the conclusion that I came up with was that little decisions add up, and that's good. But it also means you don't have to get them all right. But you don't want computers or software making decisions unattended if it involves human life, or frankly any life. Or the environment. So when you think about the applications that you can build using this architecture and this technology, think about the fact that you're not going to be doing air traffic control, you're not going to be monitoring crossing guards at the elementary school. You're going to be doing things that may seem fairly mundane. Managing machinery on the factory floor, I mean that may sound great, but really isn't that interesting. Managing well heads, drilling for oil, well I mean, it's great to the extent that it doesn't cause wells to explode, but they don't usually explode. What it's usually used for is to drive the cost out of preventative maintenance. Not very interesting. So use your heads. Come up with really cool stuff. And any of you who are involved in Edge Analytics, the next time I talk to you I don't want to hear about the same five applications that everybody talks about. Let's hear about some new ones. So, in conclusion, I don't really have anything in conclusion except that Peter mentioned something about limousines bringing people up here. On Monday I was slogging up and down Park Avenue and Madison Avenue with my client and we were visiting all the hedge funds there because we were doing a project with them. And in the miserable weather I looked at him and I said, for godsake Paul, where's the black car? And he said, that was the 90s. (laughs) Thank you. So, Jim, up to you. (audience applauding) This is terrible, go that way, this was terrible coming that way. >> Woo, don't want to trip! And let's move to, there we go. Hi everybody, how ya doing? Thanks Neil, thanks Peter, those were great discussions. So I'm the third leg in this relay race here, talking about of course how software is eating the world. And focusing on the value of Edge Analytics in a lot of real world scenarios. Programming the real world for, to make the world a better place. So I will talk, I'll break it out analytically in terms of the research that Wikibon is doing in the area of the IoT, but specifically how AI intelligence is being embedded really to all material reality potentially at the Edge. But mobile applications and industrial IoT and the smart appliances and self driving vehicles. I will break it out in terms of a reference architecture for understanding what functions are being pushed to the Edge to hardware, to our phones and so forth to drive various scenarios in terms of real world results. So I'll move a pace here. So basically AI software or AI microservices are being infused into Edge hardware as we speak. What we see is more vendors of smart phones and other, real world appliances and things like smart driving, self driving vehicles. What they're doing is they're instrumenting their products with computer vision and natural language processing, environmental awareness based on sensing and actuation and those capabilities and inferences that these devices just do to both provide human support for human users of these devices as well as to enable varying degrees of autonomous operation. So what I'll be talking about is how AI is a foundation for data driven systems of agency of the sort that Peter is talking about. Infusing data driven intelligence into everything or potentially so. As more of this capability, all these algorithms for things like, ya know for doing real time predictions and classifications, anomaly detection and so forth, as this functionality gets diffused widely and becomes more commoditized, you'll see it burned into an ever-wider variety of hardware architecture, neuro synaptic chips, GPUs and so forth. So what I've got here in front of you is a sort of a high level reference architecture that we're building up in our research at Wikibon. So AI, artificial intelligence is a big term, a big paradigm, I'm not going to unpack it completely. Of course we don't have oodles of time so I'm going to take you fairly quickly through the high points. It's a driver for systems of agency. Programming the real world. Transducing digital inputs, the data, to analog real world results. Through the embedding of this capability in the IoT, but pushing more and more of it out to the Edge with points of decision and action in real time. And there are four capabilities that we're seeing in terms of AI enabled, enabling capabilities that are absolutely critical to software being pushed to the Edge are sensing, actuation, inference and Learning. Sensing and actuation like Peter was describing, it's about capturing data from the environment within which a device or users is operating or moving. And then actuation is the fancy term for doing stuff, ya know like industrial IoT, it's obviously machine controlled, but clearly, you know self driving vehicles is steering a vehicle and avoiding crashing and so forth. Inference is the meat and potatoes as it were of AI. Analytics does inferences. It infers from the data, the logic of the application. Predictive logic, correlations, classification, abstractions, differentiation, anomaly detection, recognizing faces and voices. We see that now with Apple and the latest version of the iPhone is embedding face recognition as a core, as the core multifactor authentication technique. Clearly that's a harbinger of what's going to be universal fairly soon which is that depends on AI. That depends on convolutional neural networks, that is some heavy hitting processing power that's necessary and it's processing the data that's coming from your face. So that's critically important. So what we're looking at then is the AI software is taking root in hardware to power continuous agency. Getting stuff done. Powered decision support by human beings who have to take varying degrees of action in various environments. We don't necessarily want to let the car steer itself in all scenarios, we want some degree of override, for lots of good reasons. They want to protect life and limb including their own. And just more data driven automation across the internet of things in the broadest sense. So unpacking this reference framework, what's happening is that AI driven intelligence is powering real time decisioning at the Edge. Real time local sensing from the data that it's capturing there, it's ingesting the data. Some, not all of that data, may be persistent at the Edge. Some, perhaps most of it, will be pushed into the cloud for other processing. When you have these highly complex algorithms that are doing AI deep learning, multilayer, to do a variety of anti-fraud and higher level like narrative, auto-narrative roll-ups from various scenes that are unfolding. A lot of this processing is going to begin to happen in the cloud, but a fair amount of the more narrowly scoped inferences that drive real time decision support at the point of action will be done on the device itself. Contextual actuation, so it's the sensor data that's captured by the device along with other data that may be coming down in real time streams through the cloud will provide the broader contextual envelope of data needed to drive actuation, to drive various models and rules and so forth that are making stuff happen at the point of action, at the Edge. Continuous inference. What it all comes down to is that inference is what's going on inside the chips at the Edge device. And what we're seeing is a growing range of hardware architectures, GPUs, CPUs, FPGAs, ASIC, Neuro synaptic chips of all sorts playing in various combinations that are automating more and more very complex inference scenarios at the Edge. And not just individual devices, swarms of devices, like drones and so forth are essentially an Edge unto themselves. You'll see these tiered hierarchies of Edge swarms that are playing and doing inferences of ever more complex dynamic nature. And much of this will be, this capability, the fundamental capabilities that is powering them all will be burned into the hardware that powers them. And then adaptive learning. Now I use the term learning rather than training here, training is at the core of it. Training means everything in terms of the predictive fitness or the fitness of your AI services for whatever task, predictions, classifications, face recognition that you, you've built them for. But I use the term learning in a broader sense. It's what's make your inferences get better and better, more accurate over time is that you're training them with fresh data in a supervised learning environment. But you can have reinforcement learning if you're doing like say robotics and you don't have ground truth against which to train the data set. You know there's maximize a reward function versus minimize a loss function, you know, the standard approach, the latter for supervised learning. There's also, of course, the issue, or not the issue, the approach of unsupervised learning with cluster analysis critically important in a lot of real world scenarios. So Edge AI Algorithms, clearly, deep learning which is multilayered machine learning models that can do abstractions at higher and higher levels. Face recognition is a high level abstraction. Faces in a social environment is an even higher level of abstraction in terms of groups. Faces over time and bodies and gestures, doing various things in various environments is an even higher level abstraction in terms of narratives that can be rolled up, are being rolled up by deep learning capabilities of great sophistication. Convolutional neural networks for processing images, recurrent neural networks for processing time series. Generative adversarial networks for doing essentially what's called generative applications of all sort, composing music, and a lot of it's being used for auto programming. These are all deep learning. There's a variety of other algorithm approaches I'm not going to bore you with here. Deep learning is essentially the enabler of the five senses of the IoT. Your phone's going to have, has a camera, it has a microphone, it has the ability to of course, has geolocation and navigation capabilities. It's environmentally aware, it's got an accelerometer and so forth embedded therein. The reason that your phone and all of the devices are getting scary sentient is that they have the sensory modalities and the AI, the deep learning that enables them to make environmentally correct decisions in the wider range of scenarios. So machine learning is the foundation of all of this, but there are other, I mean of deep learning, artificial neural networks is the foundation of that. But there are other approaches for machine learning I want to make you aware of because support vector machines and these other established approaches for machine learning are not going away but really what's driving the show now is deep learning, because it's scary effective. And so that's where most of the investment in AI is going into these days for deep learning. AI Edge platforms, tools and frameworks are just coming along like gangbusters. Much development of AI, of deep learning happens in the context of your data lake. This is where you're storing your training data. This is the data that you use to build and test to validate in your models. So we're seeing a deepening stack of Hadoop and there's Kafka, and Spark and so forth that are driving the training (coughs) excuse me, of AI models that are power all these Edge Analytic applications so that that lake will continue to broaden in terms, and deepen in terms of a scope and the range of data sets and the range of modeling, AI modeling supports. Data science is critically important in this scenario because the data scientist, the data science teams, the tools and techniques and flows of data science are the fundamental development paradigm or discipline or capability that's being leveraged to build and to train and to deploy and iterate all this AI that's being pushed to the Edge. So clearly data science is at the center, data scientists of an increasingly specialized nature are necessary to the realization to this value at the Edge. AI frameworks are coming along like you know, a mile a minute. TensorFlow has achieved a, is an open source, most of these are open source, has achieved sort of almost like a defacto standard, status, I'm using the word defacto in air quotes. There's Theano and Keras and xNet and CNTK and a variety of other ones. We're seeing range of AI frameworks come to market, most open source. Most are supported by most of the major tool vendors as well. So at Wikibon we're definitely tracking that, we plan to go deeper in our coverage of that space. And then next best action, powers recommendation engines. I mean next best action decision automation of the sort of thing Neil's covered in a variety of contexts in his career is fundamentally important to Edge Analytics to systems of agency 'cause it's driving the process automation, decision automation, sort of the targeted recommendations that are made at the Edge to individual users as well as to process that automation. That's absolutely necessary for self driving vehicles to do their jobs and industrial IoT. So what we're seeing is more and more recommendation engine or recommender capabilities powered by ML and DL are going to the Edge, are already at the Edge for a variety of applications. Edge AI capabilities, like I said, there's sensing. And sensing at the Edge is becoming ever more rich, mixed reality Edge modalities of all sort are for augmented reality and so forth. We're just seeing a growth in certain, the range of sensory modalities that are enabled or filtered and analyzed through AI that are being pushed to the Edge, into the chip sets. Actuation, that's where robotics comes in. Robotics is coming into all aspects of our lives. And you know, it's brainless without AI, without deep learning and these capabilities. Inference, autonomous edge decisioning. Like I said, it's, a growing range of inferences that are being done at the Edge. And that's where it has to happen 'cause that's the point of decision. Learning, training, much training, most training will continue to be done in the cloud because it's very data intensive. It's a grind to train and optimize an AI algorithm to do its job. It's not something that you necessarily want to do or can do at the Edge at Edge devices so, the models that are built and trained in the cloud are pushed down through a dev ops process down to the Edge and that's the way it will work pretty much in most AI environments, Edge analytics environments. You centralize the modeling, you decentralize the execution of the inference models. The training engines will be in the cloud. Edge AI applications. I'll just run you through sort of a core list of the ones that are coming into, already come into the mainstream at the Edge. Multifactor authentication, clearly the Apple announcement of face recognition is just a harbinger of the fact that that's coming to every device. Computer vision speech recognition, NLP, digital assistance and chat bots powered by natural language processing and understanding, it's all AI powered. And it's becoming very mainstream. Emotion detection, face recognition, you know I could go on and on but these are like the core things that everybody has access to or will by 2020 and they're core devices, mass market devices. Developers, designers and hardware engineers are coming together to pool their expertise to build and train not just the AI, but also the entire package of hardware in UX and the orchestration of real world business scenarios or life scenarios that all this intelligence, the submitted intelligence enables and most, much of what they build in terms of AI will be containerized as micro services through Docker and orchestrated through Kubernetes as full cloud services in an increasingly distributed fabric. That's coming along very rapidly. We can see a fair amount of that already on display at Strata in terms of what the vendors are doing or announcing or who they're working with. The hardware itself, the Edge, you know at the Edge, some data will be persistent, needs to be persistent to drive inference. That's, and you know to drive a variety of different application scenarios that need some degree of historical data related to what that device in question happens to be sensing or has sensed in the immediate past or you know, whatever. The hardware itself is geared towards both sensing and increasingly persistence and Edge driven actuation of real world results. The whole notion of drones and robotics being embedded into everything that we do. That's where that comes in. That has to be powered by low cost, low power commodity chip sets of various sorts. What we see right now in terms of chip sets is it's a GPUs, Nvidia has gone real far and GPUs have come along very fast in terms of power inference engines, you know like the Tesla cars and so forth. But GPUs are in many ways the core hardware sub straight for in inference engines in DL so far. But to become a mass market phenomenon, it's got to get cheaper and lower powered and more commoditized, and so we see a fair number of CPUs being used as the hardware for Edge Analytic applications. Some vendors are fairly big on FPGAs, I believe Microsoft has gone fairly far with FPGAs inside DL strategy. ASIC, I mean, there's neuro synaptic chips like IBM's got one. There's at least a few dozen vendors of neuro synaptic chips on the market so at Wikibon we're going to track that market as it develops. And what we're seeing is a fair number of scenarios where it's a mixed environment where you use one chip set architecture at the inference side of the Edge, and other chip set architectures that are driving the DL as processed in the cloud, playing together within a common architecture. And we see some, a fair number of DL environments where the actual training is done in the cloud on Spark using CPUs and parallelized in memory, but pushing Tensorflow models that might be trained through Spark down to the Edge where the inferences are done in FPGAs and GPUs. Those kinds of mixed hardware scenarios are very, very, likely to be standard going forward in lots of areas. So analytics at the Edge power continuous results is what it's all about. The whole point is really not moving the data, it's putting the inference at the Edge and working from the data that's already captured and persistent there for the duration of whatever action or decision or result needs to be powered from the Edge. Like Neil said cost takeout alone is not worth doing. Cost takeout alone is not the rationale for putting AI at the Edge. It's getting new stuff done, new kinds of things done in an automated consistent, intelligent, contextualized way to make our lives better and more productive. Security and governance are becoming more important. Governance of the models, governance of the data, governance in a dev ops context in terms of version controls over all those DL models that are built, that are trained, that are containerized and deployed. Continuous iteration and improvement of those to help them learn to do, make our lives better and easier. With that said, I'm going to hand it over now. It's five minutes after the hour. We're going to get going with the Influencer Panel so what we'd like to do is I call Peter, and Peter's going to call our influencers. >> All right, am I live yet? Can you hear me? All right so, we've got, let me jump back in control here. We've got, again, the objective here is to have community take on some things. And so what we want to do is I want to invite five other people up, Neil why don't you come on up as well. Start with Neil. You can sit here. On the far right hand side, Judith, Judith Hurwitz. >> Neil: I'm glad I'm on the left side. >> From the Hurwitz Group. >> From the Hurwitz Group. Jennifer Shin who's affiliated with UC Berkeley. Jennifer are you here? >> She's here, Jennifer where are you? >> She was here a second ago. >> Neil: I saw her walk out she may have, >> Peter: All right, she'll be back in a second. >> Here's Jennifer! >> Here's Jennifer! >> Neil: With 8 Path Solutions, right? >> Yep. >> Yeah 8 Path Solutions. >> Just get my mic. >> Take your time Jen. >> Peter: All right, Stephanie McReynolds. Far left. And finally Joe Caserta, Joe come on up. >> Stephie's with Elysian >> And to the left. So what I want to do is I want to start by having everybody just go around introduce yourself quickly. Judith, why don't we start there. >> I'm Judith Hurwitz, I'm president of Hurwitz and Associates. We're an analyst research and fault leadership firm. I'm the co-author of eight books. Most recent is Cognitive Computing and Big Data Analytics. I've been in the market for a couple years now. >> Jennifer. >> Hi, my name's Jennifer Shin. I'm the founder and Chief Data Scientist 8 Path Solutions LLC. We do data science analytics and technology. We're actually about to do a big launch next month, with Box actually. >> We're apparent, are we having a, sorry Jennifer, are we having a problem with Jennifer's microphone? >> Man: Just turn it back on? >> Oh you have to turn it back on. >> It was on, oh sorry, can you hear me now? >> Yes! We can hear you now. >> Okay, I don't know how that turned back off, but okay. >> So you got to redo all that Jen. >> Okay, so my name's Jennifer Shin, I'm founder of 8 Path Solutions LLC, it's a data science analytics and technology company. I founded it about six years ago. So we've been developing some really cool technology that we're going to be launching with Box next month. It's really exciting. And I have, I've been developing a lot of patents and some technology as well as teaching at UC Berkeley as a lecturer in data science. >> You know Jim, you know Neil, Joe, you ready to go? >> Joe: Just broke my microphone. >> Joe's microphone is broken. >> Joe: Now it should be all right. >> Jim: Speak into Neil's. >> Joe: Hello, hello? >> I just feel not worthy in the presence of Joe Caserta. (several laughing) >> That's right, master of mics. If you can hear me, Joe Caserta, so yeah, I've been doing data technology solutions since 1986, almost as old as Neil here, but been doing specifically like BI, data warehousing, business intelligence type of work since 1996. And been doing, wholly dedicated to Big Data solutions and modern data engineering since 2009. Where should I be looking? >> Yeah I don't know where is the camera? >> Yeah, and that's basically it. So my company was formed in 2001, it's called Caserta Concepts. We recently rebranded to only Caserta 'cause what we do is way more than just concepts. So we conceptualize the stuff, we envision what the future brings and we actually build it. And we help clients large and small who are just, want to be leaders in innovation using data specifically to advance their business. >> Peter: And finally Stephanie McReynolds. >> I'm Stephanie McReynolds, I had product marketing as well as corporate marketing for a company called Elysian. And we are a data catalog so we help bring together not only a technical understanding of your data, but we curate that data with human knowledge and use automated intelligence internally within the system to make recommendations about what data to use for decision making. And some of our customers like City of San Diego, a large automotive manufacturer working on self driving cars and General Electric use Elysian to help power their solutions for IoT at the Edge. >> All right so let's jump right into it. And again if you have a question, raise your hand, and we'll do our best to get it to the floor. But what I want to do is I want to get seven questions in front of this group and have you guys discuss, slog, disagree, agree. Let's start here. What is the relationship between Big Data AI and IoT? Now Wikibon's put forward its observation that data's being generated at the Edge, that action is being taken at the Edge and then increasingly the software and other infrastructure architectures need to accommodate the realities of how data is going to work in these very complex systems. That's our perspective. Anybody, Judith, you want to start? >> Yeah, so I think that if you look at AI machine learning, all these different areas, you have to be able to have the data learned. Now when it comes to IoT, I think one of the issues we have to be careful about is not all data will be at the Edge. Not all data needs to be analyzed at the Edge. For example if the light is green and that's good and it's supposed to be green, do you really have to constantly analyze the fact that the light is green? You actually only really want to be able to analyze and take action when there's an anomaly. Well if it goes purple, that's actually a sign that something might explode, so that's where you want to make sure that you have the analytics at the edge. Not for everything, but for the things where there is an anomaly and a change. >> Joe, how about from your perspective? >> For me I think the evolution of data is really becoming, eventually oxygen is just, I mean data's going to be the oxygen we breathe. It used to be very very reactive and there used to be like a latency. You do something, there's a behavior, there's an event, there's a transaction, and then you go record it and then you collect it, and then you can analyze it. And it was very very waterfallish, right? And then eventually we figured out to put it back into the system. Or at least human beings interpret it to try to make the system better and that is really completely turned on it's head, we don't do that anymore. Right now it's very very, it's synchronous, where as we're actually making these transactions, the machines, we don't really need, I mean human beings are involved a bit, but less and less and less. And it's just a reality, it may not be politically correct to say but it's a reality that my phone in my pocket is following my behavior, and it knows without telling a human being what I'm doing. And it can actually help me do things like get to where I want to go faster depending on my preference if I want to save money or save time or visit things along the way. And I think that's all integration of big data, streaming data, artificial intelligence and I think the next thing that we're going to start seeing is the culmination of all of that. I actually, hopefully it'll be published soon, I just wrote an article for Forbes with the term of ARBI and ARBI is the integration of Augmented Reality and Business Intelligence. Where I think essentially we're going to see, you know, hold your phone up to Jim's face and it's going to recognize-- >> Peter: It's going to break. >> And it's going to say exactly you know, what are the key metrics that we want to know about Jim. If he works on my sales force, what's his attainment of goal, what is-- >> Jim: Can it read my mind? >> Potentially based on behavior patterns. >> Now I'm scared. >> I don't think Jim's buying it. >> It will, without a doubt be able to predict what you've done in the past, you may, with some certain level of confidence you may do again in the future, right? And is that mind reading? It's pretty close, right? >> Well, sometimes, I mean, mind reading is in the eye of the individual who wants to know. And if the machine appears to approximate what's going on in the person's head, sometimes you can't tell. So I guess, I guess we could call that the Turing machine test of the paranormal. >> Well, face recognition, micro gesture recognition, I mean facial gestures, people can do it. Maybe not better than a coin toss, but if it can be seen visually and captured and analyzed, conceivably some degree of mind reading can be built in. I can see when somebody's angry looking at me so, that's a possibility. That's kind of a scary possibility in a surveillance society, potentially. >> Neil: Right, absolutely. >> Peter: Stephanie, what do you think? >> Well, I hear a world of it's the bots versus the humans being painted here and I think that, you know at Elysian we have a very strong perspective on this and that is that the greatest impact, or the greatest results is going to be when humans figure out how to collaborate with the machines. And so yes, you want to get to the location more quickly, but the machine as in the bot isn't able to tell you exactly what to do and you're just going to blindly follow it. You need to train that machine, you need to have a partnership with that machine. So, a lot of the power, and I think this goes back to Judith's story is then what is the human decision making that can be augmented with data from the machine, but then the humans are actually training the training side and driving machines in the right direction. I think that's when we get true power out of some of these solutions so it's not just all about the technology. It's not all about the data or the AI, or the IoT, it's about how that empowers human systems to become smarter and more effective and more efficient. And I think we're playing that out in our technology in a certain way and I think organizations that are thinking along those lines with IoT are seeing more benefits immediately from those projects. >> So I think we have a general agreement of what kind of some of the things you talked about, IoT, crucial capturing information, and then having action being taken, AI being crucial to defining and refining the nature of the actions that are being taken Big Data ultimately powering how a lot of that changes. Let's go to the next one. >> So actually I have something to add to that. So I think it makes sense, right, with IoT, why we have Big Data associated with it. If you think about what data is collected by IoT. We're talking about a serial information, right? It's over time, it's going to grow exponentially just by definition, right, so every minute you collect a piece of information that means over time, it's going to keep growing, growing, growing as it accumulates. So that's one of the reasons why the IoT is so strongly associated with Big Data. And also why you need AI to be able to differentiate between one minute versus next minute, right? Trying to find a better way rather than looking at all that information and manually picking out patterns. To have some automated process for being able to filter through that much data that's being collected. >> I want to point out though based on what you just said Jennifer, I want to bring Neil in at this point, that this question of IoT now generating unprecedented levels of data does introduce this idea of the primary source. Historically what we've done within technology, or within IT certainly is we've taken stylized data. There is no such thing as a real world accounting thing. It is a human contrivance. And we stylize data and therefore it's relatively easy to be very precise on it. But when we start, as you noted, when we start measuring things with a tolerance down to thousandths of a millimeter, whatever that is, metric system, now we're still sometimes dealing with errors that we have to attend to. So, the reality is we're not just dealing with stylized data, we're dealing with real data, and it's more, more frequent, but it also has special cases that we have to attend to as in terms of how we use it. What do you think Neil? >> Well, I mean, I agree with that, I think I already said that, right. >> Yes you did, okay let's move on to the next one. >> Well it's a doppelganger, the digital twin doppelganger that's automatically created by your very fact that you're living and interacting and so forth and so on. It's going to accumulate regardless. Now that doppelganger may not be your agent, or might not be the foundation for your agent unless there's some other piece of logic like an interest graph that you build, a human being saying this is my broad set of interests, and so all of my agents out there in the IoT, you all need to be aware that when you make a decision on my behalf as my agent, this is what Jim would do. You know I mean there needs to be that kind of logic somewhere in this fabric to enable true agency. >> All right, so I'm going to start with you. Oh go ahead. >> I have a real short answer to this though. I think that Big Data provides the data and compute platform to make AI possible. For those of us who dipped our toes in the water in the 80s, we got clobbered because we didn't have the, we didn't have the facilities, we didn't have the resources to really do AI, we just kind of played around with it. And I think that the other thing about it is if you combine Big Data and AI and IoT, what you're going to see is people, a lot of the applications we develop now are very inward looking, we look at our organization, we look at our customers. We try to figure out how to sell more shoes to fashionable ladies, right? But with this technology, I think people can really expand what they're thinking about and what they model and come up with applications that are much more external. >> Actually what I would add to that is also it actually introduces being able to use engineering, right? Having engineers interested in the data. Because it's actually technical data that's collected not just say preferences or information about people, but actual measurements that are being collected with IoT. So it's really interesting in the engineering space because it opens up a whole new world for the engineers to actually look at data and to actually combine both that hardware side as well as the data that's being collected from it. >> Well, Neil, you and I have talked about something, 'cause it's not just engineers. We have in the healthcare industry for example, which you know a fair amount about, there's this notion of empirical based management. And the idea that increasingly we have to be driven by data as a way of improving the way that managers do things, the way the managers collect or collaborate and ultimately collectively how they take action. So it's not just engineers, it's supposed to also inform business, what's actually happening in the healthcare world when we start thinking about some of this empirical based management, is it working? What are some of the barriers? >> It's not a function of technology. What happens in medicine and healthcare research is, I guess you can say it borders on fraud. (people chuckling) No, I'm not kidding. I know the New England Journal of Medicine a couple of years ago released a study and said that at least half their articles that they published turned out to be written, ghost written by pharmaceutical companies. (man chuckling) Right, so I think the problem is that when you do a clinical study, the one that really killed me about 10 years ago was the women's health initiative. They spent $700 million gathering this data over 20 years. And when they released it they looked at all the wrong things deliberately, right? So I think that's a systemic-- >> I think you're bringing up a really important point that we haven't brought up yet, and that is is can you use Big Data and machine learning to begin to take the biases out? So if you let the, if you divorce your preconceived notions and your biases from the data and let the data lead you to the logic, you start to, I think get better over time, but it's going to take a while to get there because we do tend to gravitate towards our biases. >> I will share an anecdote. So I had some arm pain, and I had numbness in my thumb and pointer finger and I went to, excruciating pain, went to the hospital. So the doctor examined me, and he said you probably have a pinched nerve, he said, but I'm not exactly sure which nerve it would be, I'll be right back. And I kid you not, he went to a computer and he Googled it. (Neil laughs) And he came back because this little bit of information was something that could easily be looked up, right? Every nerve in your spine is connected to your different fingers so the pointer and the thumb just happens to be your C6, so he came back and said, it's your C6. (Neil mumbles) >> You know an interesting, I mean that's a good example. One of the issues with healthcare data is that the data set is not always shared across the entire research community, so by making Big Data accessible to everyone, you actually start a more rational conversation or debate on well what are the true insights-- >> If that conversation includes what Judith talked about, the actual model that you use to set priorities and make decisions about what's actually important. So it's not just about improving, this is the test. It's not just about improving your understanding of the wrong thing, it's also testing whether it's the right or wrong thing as well. >> That's right, to be able to test that you need to have humans in dialog with one another bringing different biases to the table to work through okay is there truth in this data? >> It's context and it's correlation and you can have a great correlation that's garbage. You know if you don't have the right context. >> Peter: So I want to, hold on Jim, I want to, >> It's exploratory. >> Hold on Jim, I want to take it to the next question 'cause I want to build off of what you talked about Stephanie and that is that this says something about what is the Edge. And our perspective is that the Edge is not just devices. That when we talk about the Edge, we're talking about human beings and the role that human beings are going to play both as sensors or carrying things with them, but also as actuators, actually taking action which is not a simple thing. So what do you guys think? What does the Edge mean to you? Joe, why don't you start? >> Well, I think it could be a combination of the two. And specifically when we talk about healthcare. So I believe in 2017 when we eat we don't know why we're eating, like I think we should absolutely by now be able to know exactly what is my protein level, what is my calcium level, what is my potassium level? And then find the foods to meet that. What have I depleted versus what I should have, and eat very very purposely and not by taste-- >> And it's amazing that red wine is always the answer. >> It is. (people laughing) And tequila, that helps too. >> Jim: You're a precision foodie is what you are. (several chuckle) >> There's no reason why we should not be able to know that right now, right? And when it comes to healthcare is, the biggest problem or challenge with healthcare is no matter how great of a technology you have, you can't, you can't, you can't manage what you can't measure. And you're really not allowed to use a lot of this data so you can't measure it, right? You can't do things very very scientifically right, in the healthcare world and I think regulation in the healthcare world is really burdening advancement in science. >> Peter: Any thoughts Jennifer? >> Yes, I teach statistics for data scientists, right, so you know we talk about a lot of these concepts. I think what makes these questions so difficult is you have to find a balance, right, a middle ground. For instance, in the case of are you being too biased through data, well you could say like we want to look at data only objectively, but then there are certain relationships that your data models might show that aren't actually a causal relationship. For instance, if there's an alien that came from space and saw earth, saw the people, everyone's carrying umbrellas right, and then it started to rain. That alien might think well, it's because they're carrying umbrellas that it's raining. Now we know from real world that that's actually not the way these things work. So if you look only at the data, that's the potential risk. That you'll start making associations or saying something's causal when it's actually not, right? So that's one of the, one of the I think big challenges. I think when it comes to looking also at things like healthcare data, right? Do you collect data about anything and everything? Does it mean that A, we need to collect all that data for the question we're looking at? Or that it's actually the best, more optimal way to be able to get to the answer? Meaning sometimes you can take some shortcuts in terms of what data you collect and still get the right answer and not have maybe that level of specificity that's going to cost you millions extra to be able to get. >> So Jennifer as a data scientist, I want to build upon what you just said. And that is, are we going to start to see methods and models emerge for how we actually solve some of these problems? So for example, we know how to build a system for stylized process like accounting or some elements of accounting. We have methods and models that lead to technology and actions and whatnot all the way down to that that system can be generated. We don't have the same notion to the same degree when we start talking about AI and some of these Big Datas. We have algorithms, we have technology. But are we going to start seeing, as a data scientist, repeatability and learning and how to think the problems through that's going to lead us to a more likely best or at least good result? >> So I think that's a bit of a tough question, right? Because part of it is, it's going to depend on how many of these researchers actually get exposed to real world scenarios, right? Research looks into all these papers, and you come up with all these models, but if it's never tested in a real world scenario, well, I mean we really can't validate that it works, right? So I think it is dependent on how much of this integration there's going to be between the research community and industry and how much investment there is. Funding is going to matter in this case. If there's no funding in the research side, then you'll see a lot of industry folk who feel very confident about their models that, but again on the other side of course, if researchers don't validate those models then you really can't say for sure that it's actually more accurate, or it's more efficient. >> It's the issue of real world testing and experimentation, A B testing, that's standard practice in many operationalized ML and AI implementations in the business world, but real world experimentation in the Edge analytics, what you're actually transducing are touching people's actual lives. Problem there is, like in healthcare and so forth, when you're experimenting with people's lives, somebody's going to die. I mean, in other words, that's a critical, in terms of causal analysis, you've got to tread lightly on doing operationalizing that kind of testing in the IoT when people's lives and health are at stake. >> We still give 'em placebos. So we still test 'em. All right so let's go to the next question. What are the hottest innovations in AI? Stephanie I want to start with you as a company, someone at a company that's got kind of an interesting little thing happening. We start thinking about how do we better catalog data and represent it to a large number of people. What are some of the hottest innovations in AI as you see it? >> I think it's a little counter intuitive about what the hottest innovations are in AI, because we're at a spot in the industry where the most successful companies that are working with AI are actually incorporating them into solutions. So the best AI solutions are actually the products that you don't know there's AI operating underneath. But they're having a significant impact on business decision making or bringing a different type of application to the market and you know, I think there's a lot of investment that's going into AI tooling and tool sets for data scientists or researchers, but the more innovative companies are thinking through how do we really take AI and make it have an impact on business decision making and that means kind of hiding the AI to the business user. Because if you think a bot is making a decision instead of you, you're not going to partner with that bot very easily or very readily. I worked at, way at the start of my career, I worked in CRM when recommendation engines were all the rage online and also in call centers. And the hardest thing was to get a call center agent to actually read the script that the algorithm was presenting to them, that algorithm was 99% correct most of the time, but there was this human resistance to letting a computer tell you what to tell that customer on the other side even if it was more successful in the end. And so I think that the innovation in AI that's really going to push us forward is when humans feel like they can partner with these bots and they don't think of it as a bot, but they think about as assisting their work and getting to a better result-- >> Hence the augmentation point you made earlier. >> Absolutely, absolutely. >> Joe how 'about you? What do you look at? What are you excited about? >> I think the coolest thing at the moment right now is chat bots. Like to be able, like to have voice be able to speak with you in natural language, to do that, I think that's pretty innovative, right? And I do think that eventually, for the average user, not for techies like me, but for the average user, I think keyboards are going to be a thing of the past. I think we're going to communicate with computers through voice and I think this is the very very beginning of that and it's an incredible innovation. >> Neil? >> Well, I think we all have myopia here. We're all thinking about commercial applications. Big, big things are happening with AI in the intelligence community, in military, the defense industry, in all sorts of things. Meteorology. And that's where, well, hopefully not on an every day basis with military, you really see the effect of this. But I was involved in a project a couple of years ago where we were developing AI software to detect artillery pieces in terrain from satellite imagery. I don't have to tell you what country that was. I think you can probably figure that one out right? But there are legions of people in many many companies that are involved in that industry. So if you're talking about the dollars spent on AI, I think the stuff that we do in our industries is probably fairly small. >> Well it reminds me of an application I actually thought was interesting about AI related to that, AI being applied to removing mines from war zones. >> Why not? >> Which is not a bad thing for a whole lot of people. Judith what do you look at? >> So I'm looking at things like being able to have pre-trained data sets in specific solution areas. I think that that's something that's coming. Also the ability to, to really be able to have a machine assist you in selecting the right algorithms based on what your data looks like and the problems you're trying to solve. Some of the things that data scientists still spend a lot of their time on, but can be augmented with some, basically we have to move to levels of abstraction before this becomes truly ubiquitous across many different areas. >> Peter: Jennifer? >> So I'm going to say computer vision. >> Computer vision? >> Computer vision. So computer vision ranges from image recognition to be able to say what content is in the image. Is it a dog, is it a cat, is it a blueberry muffin? Like a sort of popular post out there where it's like a blueberry muffin versus like I think a chihuahua and then it compares the two. And can the AI really actually detect difference, right? So I think that's really where a lot of people who are in this space of being in both the AI space as well as data science are looking to for the new innovations. I think, for instance, cloud vision I think that's what Google still calls it. The vision API we've they've released on beta allows you to actually use an API to send your image and then have it be recognized right, by their API. There's another startup in New York called Clarify that also does a similar thing as well as you know Amazon has their recognition platform as well. So I think in a, from images being able to detect what's in the content as well as from videos, being able to say things like how many people are entering a frame? How many people enter the store? Not having to actually go look at it and count it, but having a computer actually tally that information for you, right? >> There's actually an extra piece to that. So if I have a picture of a stop sign, and I'm an automated car, and is it a picture on the back of a bus of a stop sign, or is it a real stop sign? So that's going to be one of the complications. >> Doesn't matter to a New York City cab driver. How 'about you Jim? >> Probably not. (laughs) >> Hottest thing in AI is General Adversarial Networks, GANT, what's hot about that, well, I'll be very quick, most AI, most deep learning, machine learning is analytical, it's distilling or inferring insights from the data. Generative takes that same algorithmic basis but to build stuff. In other words, to create realistic looking photographs, to compose music, to build CAD CAM models essentially that can be constructed on 3D printers. So GANT, it's a huge research focus all around the world are used for, often increasingly used for natural language generation. In other words it's institutionalizing or having a foundation for nailing the Turing test every single time, building something with machines that looks like it was constructed by a human and doing it over and over again to fool humans. I mean you can imagine the fraud potential. But you can also imagine just the sheer, like it's going to shape the world, GANT. >> All right so I'm going to say one thing, and then we're going to ask if anybody in the audience has an idea. So the thing that I find interesting is traditional programs, or when you tell a machine to do something you don't need incentives. When you tell a human being something, you have to provide incentives. Like how do you get someone to actually read the text. And this whole question of elements within AI that incorporate incentives as a way of trying to guide human behavior is absolutely fascinating to me. Whether it's gamification, or even some things we're thinking about with block chain and bitcoins and related types of stuff. To my mind that's going to have an enormous impact, some good, some bad. Anybody in the audience? I don't want to lose everybody here. What do you think sir? And I'll try to do my best to repeat it. Oh we have a mic. >> So my question's about, Okay, so the question's pretty much about what Stephanie's talking about which is human and loop training right? I come from a computer vision background. That's the problem, we need millions of images trained, we need humans to do that. And that's like you know, the workforce is essentially people that aren't necessarily part of the AI community, they're people that are just able to use that data and analyze the data and label that data. That's something that I think is a big problem everyone in the computer vision industry at least faces. I was wondering-- >> So again, but the problem is that is the difficulty of methodologically bringing together people who understand it and people who, people who have domain expertise people who have algorithm expertise and working together? >> I think the expertise issue comes in healthcare, right? In healthcare you need experts to be labeling your images. With contextual information where essentially augmented reality applications coming in, you have the AR kit and everything coming out, but there is a lack of context based intelligence. And all of that comes through training images, and all of that requires people to do it. And that's kind of like the foundational basis of AI coming forward is not necessarily an algorithm, right? It's how well are datas labeled? Who's doing the labeling and how do we ensure that it happens? >> Great question. So for the panel. So if you think about it, a consultant talks about being on the bench. How much time are they going to have to spend on trying to develop additional business? How much time should we set aside for executives to help train some of the assistants? >> I think that the key is not, to think of the problem a different way is that you would have people manually label data and that's one way to solve the problem. But you can also look at what is the natural workflow of that executive, or that individual? And is there a way to gather that context automatically using AI, right? And if you can do that, it's similar to what we do in our product, we observe how someone is analyzing the data and from those observations we can actually create the metadata that then trains the system in a particular direction. But you have to think about solving the problem differently of finding the workflow that then you can feed into to make this labeling easy without the human really realizing that they're labeling the data. >> Peter: Anybody else? >> I'll just add to what Stephanie said, so in the IoT applications, all those sensory modalities, the computer vision, the speech recognition, all that, that's all potential training data. So it cross checks against all the other models that are processing all the other data coming from that device. So that the natural language process of understanding can be reality checked against the images that the person happens to be commenting upon, or the scene in which they're embedded, so yeah, the data's embedded-- >> I don't think we're, we're not at the stage yet where this is easy. It's going to take time before we do start doing the pre-training of some of these details so that it goes faster, but right now, there're not that many shortcuts. >> Go ahead Joe. >> Sorry so a couple things. So one is like, I was just caught up on your incentivizing programs to be more efficient like humans. You know in Ethereum that has this notion, which is bot chain, has this theory, this concept of gas. Where like as the process becomes more efficient it costs less to actually run, right? It costs less ether, right? So it actually is kind of, the machine is actually incentivized and you don't really know what it's going to cost until the machine processes it, right? So there is like some notion of that there. But as far as like vision, like training the machine for computer vision, I think it's through adoption and crowdsourcing, so as people start using it more they're going to be adding more pictures. Very very organically. And then the machines will be trained and right now is a very small handful doing it, and it's very proactive by the Googles and the Facebooks and all of that. But as we start using it, as they start looking at my images and Jim's and Jen's images, it's going to keep getting smarter and smarter through adoption and through very organic process. >> So Neil, let me ask you a question. Who owns the value that's generated as a consequence of all these people ultimately contributing their insight and intelligence into these systems? >> Well, to a certain extent the people who are contributing the insight own nothing because the systems collect their actions and the things they do and then that data doesn't belong to them, it belongs to whoever collected it or whoever's going to do something with it. But the other thing, getting back to the medical stuff. It's not enough to say that the systems, people will do the right thing, because a lot of them are not motivated to do the right thing. The whole grant thing, the whole oh my god I'm not going to go against the senior professor. A lot of these, I knew a guy who was a doctor at University of Pittsburgh and they were doing a clinical study on the tubes that they put in little kids' ears who have ear infections, right? And-- >> Google it! Who helps out? >> Anyway, I forget the exact thing, but he came out and said that the principle investigator lied when he made the presentation, that it should be this, I forget which way it went. He was fired from his position at Pittsburgh and he has never worked as a doctor again. 'Cause he went against the senior line of authority. He was-- >> Another question back here? >> Man: Yes, Mark Turner has a question. >> Not a question, just want to piggyback what you're saying about the transfixation of maybe in healthcare of black and white images and color images in the case of sonograms and ultrasound and mammograms, you see that happening using AI? You see that being, I mean it's already happening, do you see it moving forward in that kind of way? I mean, talk more about that, about you know, AI and black and white images being used and they can be transfixed, they can be made to color images so you can see things better, doctors can perform better operations. >> So I'm sorry, but could you summarize down? What's the question? Summarize it just, >> I had a lot of students, they're interested in the cross pollenization between AI and say the medical community as far as things like ultrasound and sonograms and mammograms and how you can literally take a black and white image and it can, using algorithms and stuff be made to color images that can help doctors better do the work that they've already been doing, just do it better. You touched on it like 30 seconds. >> So how AI can be used to actually add information in a way that's not necessarily invasive but is ultimately improves how someone might respond to it or use it, yes? Related? I've also got something say about medical images in a second, any of you guys want to, go ahead Jennifer. >> Yeah, so for one thing, you know and it kind of goes back to what we were talking about before. When we look at for instance scans, like at some point I was looking at CT scans, right, for lung cancer nodules. In order for me, who I don't have a medical background, to identify where the nodule is, of course, a doctor actually had to go in and specify which slice of the scan had the nodule and where exactly it is, so it's on both the slice level as well as, within that 2D image, where it's located and the size of it. So the beauty of things like AI is that ultimately right now a radiologist has to look at every slice and actually identify this manually, right? The goal of course would be that one day we wouldn't have to have someone look at every slice to like 300 usually slices and be able to identify it much more automated. And I think the reality is we're not going to get something where it's going to be 100%. And with anything we do in the real world it's always like a 95% chance of it being accurate. So I think it's finding that in between of where, what's the threshold that we want to use to be able to say that this is, definitively say a lung cancer nodule or not. I think the other thing to think about is in terms of how their using other information, what they might use is a for instance, to say like you know, based on other characteristics of the person's health, they might use that as sort of a grading right? So you know, how dark or how light something is, identify maybe in that region, the prevalence of that specific variable. So that's usually how they integrate that information into something that's already existing in the computer vision sense. I think that's, the difficulty with this of course, is being able to identify which variables were introduced into data that does exist. >> So I'll make two quick observations on this then I'll go to the next question. One is radiologists have historically been some of the highest paid physicians within the medical community partly because they don't have to be particularly clinical. They don't have to spend a lot of time with patients. They tend to spend time with doctors which means they can do a lot of work in a little bit of time, and charge a fair amount of money. As we start to introduce some of these technologies that allow us to from a machine standpoint actually make diagnoses based on those images, I find it fascinating that you now see television ads promoting the role that the radiologist plays in clinical medicine. It's kind of an interesting response. >> It's also disruptive as I'm seeing more and more studies showing that deep learning models processing images, ultrasounds and so forth are getting as accurate as many of the best radiologists. >> That's the point! >> Detecting cancer >> Now radiologists are saying oh look, we do this great thing in terms of interacting with the patients, never have because they're being dis-intermediated. The second thing that I'll note is one of my favorite examples of that if I got it right, is looking at the images, the deep space images that come out of Hubble. Where they're taking data from thousands, maybe even millions of images and combining it together in interesting ways you can actually see depth. You can actually move through to a very very small scale a system that's 150, well maybe that, can't be that much, maybe six billion light years away. Fascinating stuff. All right so let me go to the last question here, and then I'm going to close it down, then we can have something to drink. What are the hottest, oh I'm sorry, question? >> Yes, hi, my name's George, I'm with Blue Talon. You asked earlier there the question what's the hottest thing in the Edge and AI, I would say that it's security. It seems to me that before you can empower agency you need to be able to authorize what they can act on, how they can act on, who they can act on. So it seems if you're going to move from very distributed data at the Edge and analytics at the Edge, there has to be security similarly done at the Edge. And I saw (speaking faintly) slides that called out security as a key prerequisite and maybe Judith can comment, but I'm curious how security's going to evolve to meet this analytics at the Edge. >> Well, let me do that and I'll ask Jen to comment. The notion of agency is crucially important, slightly different from security, just so we're clear. And the basic idea here is historically folks have thought about moving data or they thought about moving application function, now we are thinking about moving authority. So as you said. That's not necessarily, that's not really a security question, but this has been a problem that's been in, of concern in a number of different domains. How do we move authority with the resources? And that's really what informs the whole agency process. But with that said, Jim. >> Yeah actually I'll, yeah, thank you for bringing up security so identity is the foundation of security. Strong identity, multifactor, face recognition, biometrics and so forth. Clearly AI, machine learning, deep learning are powering a new era of biometrics and you know it's behavioral metrics and so forth that's organic to people's use of devices and so forth. You know getting to the point that Peter was raising is important, agency! Systems of agency. Your agent, you have to, you as a human being should be vouching in a secure, tamper proof way, your identity should be vouching for the identity of some agent, physical or virtual that does stuff on your behalf. How can that, how should that be managed within this increasingly distributed IoT fabric? Well a lot of that's been worked. It all ran through webs of trust, public key infrastructure, formats and you know SAML for single sign and so forth. It's all about assertion, strong assertions and vouching. I mean there's the whole workflows of things. Back in the ancient days when I was actually a PKI analyst three analyst firms ago, I got deep into all the guts of all those federation agreements, something like that has to be IoT scalable to enable systems agency to be truly fluid. So we can vouch for our agents wherever they happen to be. We're going to keep on having as human beings agents all over creation, we're not even going to be aware of everywhere that our agents are, but our identity-- >> It's not just-- >> Our identity has to follow. >> But it's not just identity, it's also authorization and context. >> Permissioning, of course. >> So I may be the right person to do something yesterday, but I'm not authorized to do it in another context in another application. >> Role based permissioning, yeah. Or persona based. >> That's right. >> I agree. >> And obviously it's going to be interesting to see the role that block chain or its follow on to the technology is going to play here. Okay so let me throw one more questions out. What are the hottest applications of AI at the Edge? We've talked about a number of them, does anybody want to add something that hasn't been talked about? Or do you want to get a beer? (people laughing) Stephanie, you raised your hand first. >> I was going to go, I bring something mundane to the table actually because I think one of the most exciting innovations with IoT and AI are actually simple things like City of San Diego is rolling out 3200 automated street lights that will actually help you find a parking space, reduce the amount of emissions into the atmosphere, so has some environmental change, positive environmental change impact. I mean, it's street lights, it's not like a, it's not medical industry, it doesn't look like a life changing innovation, and yet if we automate streetlights and we manage our energy better, and maybe they can flicker on and off if there's a parking space there for you, that's a significant impact on everyone's life. >> And dramatically suppress the impact of backseat driving! >> (laughs) Exactly. >> Joe what were you saying? >> I was just going to say you know there's already the technology out there where you can put a camera on a drone with machine learning within an artificial intelligence within it, and it can look at buildings and determine whether there's rusty pipes and cracks in cement and leaky roofs and all of those things. And that's all based on artificial intelligence. And I think if you can do that, to be able to look at an x-ray and determine if there's a tumor there is not out of the realm of possibility, right? >> Neil? >> I agree with both of them, that's what I meant about external kind of applications. Instead of figuring out what to sell our customers. Which is most what we hear. I just, I think all of those things are imminently doable. And boy street lights that help you find a parking place, that's brilliant, right? >> Simple! >> It improves your life more than, I dunno. Something I use on the internet recently, but I think it's great! That's, I'd like to see a thousand things like that. >> Peter: Jim? >> Yeah, building on what Stephanie and Neil were saying, it's ambient intelligence built into everything to enable fine grain microclimate awareness of all of us as human beings moving through the world. And enable reading of every microclimate in buildings. In other words, you know you have sensors on your body that are always detecting the heat, the humidity, the level of pollution or whatever in every environment that you're in or that you might be likely to move into fairly soon and either A can help give you guidance in real time about where to avoid, or give that environment guidance about how to adjust itself to your, like the lighting or whatever it might be to your specific requirements. And you know when you have a room like this, full of other human beings, there has to be some negotiated settlement. Some will find it too hot, some will find it too cold or whatever but I think that is fundamental in terms of reshaping the sheer quality of experience of most of our lived habitats on the planet potentially. That's really the Edge analytics application that depends on everybody having, being fully equipped with a personal area network of sensors that's communicating into the cloud. >> Jennifer? >> So I think, what's really interesting about it is being able to utilize the technology we do have, it's a lot cheaper now to have a lot of these ways of measuring that we didn't have before. And whether or not engineers can then leverage what we have as ways to measure things and then of course then you need people like data scientists to build the right model. So you can collect all this data, if you don't build the right model that identifies these patterns then all that data's just collected and it's just made a repository. So without having the models that supports patterns that are actually in the data, you're not going to find a better way of being able to find insights in the data itself. So I think what will be really interesting is to see how existing technology is leveraged, to collect data and then how that's actually modeled as well as to be able to see how technology's going to now develop from where it is now, to being able to either collect things more sensitively or in the case of say for instance if you're dealing with like how people move, whether we can build things that we can then use to measure how we move, right? Like how we move every day and then being able to model that in a way that is actually going to give us better insights in things like healthcare and just maybe even just our behaviors. >> Peter: Judith? >> So, I think we also have to look at it from a peer to peer perspective. So I may be able to get some data from one thing at the Edge, but then all those Edge devices, sensors or whatever, they all have to interact with each other because we don't live, we may, in our business lives, act in silos, but in the real world when you look at things like sensors and devices it's how they react with each other on a peer to peer basis. >> All right, before I invite John up, I want to say, I'll say what my thing is, and it's not the hottest. It's the one I hate the most. I hate AI generated music. (people laughing) Hate it. All right, I want to thank all the panelists, every single person, some great commentary, great observations. I want to thank you very much. I want to thank everybody that joined. John in a second you'll kind of announce who's the big winner. But the one thing I want to do is, is I was listening, I learned a lot from everybody, but I want to call out the one comment that I think we all need to remember, and I'm going to give you the award Stephanie. And that is increasing we have to remember that the best AI is probably AI that we don't even know is working on our behalf. The same flip side of that is all of us have to be very cognizant of the idea that AI is acting on our behalf and we may not know it. So, John why don't you come on up. Who won the, whatever it's called, the raffle? >> You won. >> Thank you! >> How 'about a round of applause for the great panel. (audience applauding) Okay we have a put the business cards in the basket, we're going to have that brought up. We're going to have two raffle gifts, some nice Bose headsets and speaker, Bluetooth speaker. Got to wait for that. I just want to say thank you for coming and for the folks watching, this is our fifth year doing our own event called Big Data NYC which is really an extension of the landscape beyond the Big Data world that's Cloud and AI and IoT and other great things happen and great experts and influencers and analysts here. Thanks for sharing your opinion. Really appreciate you taking the time to come out and share your data and your knowledge, appreciate it. Thank you. Where's the? >> Sam's right in front of you. >> There's the thing, okay. Got to be present to win. We saw some people sneaking out the back door to go to a dinner. >> First prize first. >> Okay first prize is the Bose headset. >> Bluetooth and noise canceling. >> I won't look, Sam you got to hold it down, I can see the cards. >> All right. >> Stephanie you won! (Stephanie laughing) Okay, Sawny Cox, Sawny Allie Cox? (audience applauding) Yay look at that! He's here! The bar's open so help yourself, but we got one more. >> Congratulations. Picture right here. >> Hold that I saw you. Wake up a little bit. Okay, all right. Next one is, my kids love this. This is great, great for the beach, great for everything portable speaker, great gift. >> What is it? >> Portable speaker. >> It is a portable speaker, it's pretty awesome. >> Oh you grabbed mine. >> Oh that's one of our guys. >> (lauging) But who was it? >> Can't be related! Ava, Ava, Ava. Okay Gene Penesko (audience applauding) Hey! He came in! All right look at that, the timing's great. >> Another one? (people laughing) >> Hey thanks everybody, enjoy the night, thank Peter Burris, head of research for SiliconANGLE, Wikibon and he great guests and influencers and friends. And you guys for coming in the community. Thanks for watching and thanks for coming. Enjoy the party and some drinks and that's out, that's it for the influencer panel and analyst discussion. Thank you. (logo music)
SUMMARY :
is that the cloud is being extended out to the Edge, the next time I talk to you I don't want to hear that are made at the Edge to individual users We've got, again, the objective here is to have community From the Hurwitz Group. And finally Joe Caserta, Joe come on up. And to the left. I've been in the market for a couple years now. I'm the founder and Chief Data Scientist We can hear you now. And I have, I've been developing a lot of patents I just feel not worthy in the presence of Joe Caserta. If you can hear me, Joe Caserta, so yeah, I've been doing We recently rebranded to only Caserta 'cause what we do to make recommendations about what data to use the realities of how data is going to work in these to make sure that you have the analytics at the edge. and ARBI is the integration of Augmented Reality And it's going to say exactly you know, And if the machine appears to approximate what's and analyzed, conceivably some degree of mind reading but the machine as in the bot isn't able to tell you kind of some of the things you talked about, IoT, So that's one of the reasons why the IoT of the primary source. Well, I mean, I agree with that, I think I already or might not be the foundation for your agent All right, so I'm going to start with you. a lot of the applications we develop now are very So it's really interesting in the engineering space And the idea that increasingly we have to be driven I know the New England Journal of Medicine So if you let the, if you divorce your preconceived notions So the doctor examined me, and he said you probably have One of the issues with healthcare data is that the data set the actual model that you use to set priorities and you can have a great correlation that's garbage. What does the Edge mean to you? And then find the foods to meet that. And tequila, that helps too. Jim: You're a precision foodie is what you are. in the healthcare world and I think regulation For instance, in the case of are you being too biased We don't have the same notion to the same degree but again on the other side of course, in the Edge analytics, what you're actually transducing What are some of the hottest innovations in AI and that means kind of hiding the AI to the business user. I think keyboards are going to be a thing of the past. I don't have to tell you what country that was. AI being applied to removing mines from war zones. Judith what do you look at? and the problems you're trying to solve. And can the AI really actually detect difference, right? So that's going to be one of the complications. Doesn't matter to a New York City cab driver. (laughs) So GANT, it's a huge research focus all around the world So the thing that I find interesting is traditional people that aren't necessarily part of the AI community, and all of that requires people to do it. So for the panel. of finding the workflow that then you can feed into that the person happens to be commenting upon, It's going to take time before we do start doing and Jim's and Jen's images, it's going to keep getting Who owns the value that's generated as a consequence But the other thing, getting back to the medical stuff. and said that the principle investigator lied and color images in the case of sonograms and ultrasound and say the medical community as far as things in a second, any of you guys want to, go ahead Jennifer. to say like you know, based on other characteristics I find it fascinating that you now see television ads as many of the best radiologists. and then I'm going to close it down, It seems to me that before you can empower agency Well, let me do that and I'll ask Jen to comment. agreements, something like that has to be IoT scalable and context. So I may be the right person to do something yesterday, Or persona based. that block chain or its follow on to the technology into the atmosphere, so has some environmental change, the technology out there where you can put a camera And boy street lights that help you find a parking place, That's, I'd like to see a thousand things like that. that are always detecting the heat, the humidity, patterns that are actually in the data, but in the real world when you look at things and I'm going to give you the award Stephanie. and for the folks watching, We saw some people sneaking out the back door I can see the cards. Stephanie you won! Picture right here. This is great, great for the beach, great for everything All right look at that, the timing's great. that's it for the influencer panel and analyst discussion.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Judith | PERSON | 0.99+ |
Jennifer | PERSON | 0.99+ |
Jim | PERSON | 0.99+ |
Neil | PERSON | 0.99+ |
Stephanie McReynolds | PERSON | 0.99+ |
Jack | PERSON | 0.99+ |
2001 | DATE | 0.99+ |
Marc Andreessen | PERSON | 0.99+ |
Jim Kobielus | PERSON | 0.99+ |
Jennifer Shin | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Joe Caserta | PERSON | 0.99+ |
Suzie Welch | PERSON | 0.99+ |
Joe | PERSON | 0.99+ |
David Floyer | PERSON | 0.99+ |
Peter | PERSON | 0.99+ |
Stephanie | PERSON | 0.99+ |
Jen | PERSON | 0.99+ |
Neil Raden | PERSON | 0.99+ |
Mark Turner | PERSON | 0.99+ |
Judith Hurwitz | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Elysian | ORGANIZATION | 0.99+ |
Uber | ORGANIZATION | 0.99+ |
Qualcomm | ORGANIZATION | 0.99+ |
Peter Burris | PERSON | 0.99+ |
2017 | DATE | 0.99+ |
Honeywell | ORGANIZATION | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
Derek Sivers | PERSON | 0.99+ |
New York | LOCATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
New York City | LOCATION | 0.99+ |
1998 | DATE | 0.99+ |
Day 3 Kickoff - ServiceNow Knowledge 17 - #Know17 - #theCUBE
>> Voiceover: Live, from Orlando Florida, it's theCUBE, covering ServiceNow Knowledge17, brought to you by ServiceNow. >> Welcome back, this is Day 3 of ServiceNow Knowledge17, and this is theCUBE, the leader in live tech coverage, where we go out to the events and we extract the signal from the noise. My name is Dave Vellante, and my co-host this week has been Jeff Frick. Not only this week, Jeff, but for the last five years, we've been doing ServiceNow Knowledge events, really getting a sense as to what this company is all about, the evolution of the company, the transformation from really early days of IT, help desk, service management, to now just permeating throughout the enterprise. One of the key things, Jeff, that is notable, and that we saw a couple years ago, I think it was three years ago, when they had the first CreatorCon. In fact, actually, in 2013, I think you did a little sidebar, you went out-- >> It was the Hackathon, we went with Allan Leinwand and checked in on the Hackathon. >> The point I want to make is that we work with these events, we come to these events. We see a lot of large company events, And whether it's Oracle or IBM or HPE, even, in the past. Even EMC with its code initative, they are drooling over developers. They can't get enough developer action, and it's like ServiceNow builds this platform, they create, they open it up with this low-code development kit, essentially, throw their glove in the field, and everybody comes to the game. >> Right, right. >> It's just amazing, and so today, Day 3, is about CreatorCon, and it was hosted by Pat Casey, who's the senior vice president of DevOps, and really the closest, I think, to the Fred Luddy DNA. I mean that's really Pat, you know, Fred Luddy's the founder of the company and sort of the icon of ServiceNow, not here, you know? We're entering a new era and it's really underscored culturally by CreatorCon and Pat Casey. You were in there today. What'd you think? >> Was it Fred termed the citizen developer? I can't remember, I'll have to go back and check the tape, because he definitely talked about low code, and I think he may have been the one that said citizen developer. And it's funny, even with CJ Desai, right, when he was thinking about coming over, what was the first thing he did? He downloaded the app, and wanted to create a little app. So everybody here is a developer, and I think, just looking back at some of the interviews yesterday, Donna from Cox Automotive, she built a prototype app. It was her, one business analyst, and an intern to start a whole new perspective, so I think, you know, they're really trying to make everybody a developer. It's a different way to think, and not just the business analyst, then you have to pass it off to development, but using, again, a simple workflow tool, it's still a workflow tool, to let everybody automate processes. And we were just in the CreatorCon. The other piece that really strikes me, and it strikes me every time I look at my phone now, you know, my phone knows I follow the Warriors, and so it just automatically gives me an update. So it's kind of this soft, a push of AI and machine learning into your day-to-day activity without this heavy overlay. And that's really how they do it effectively, and then that's kind of the basis of what they're doing here with integrating the machine learning into the applications to collect the data, build the models, try to take some of the mundane, mind-numbing work off of your plate and get people doing it, real decisions based on the machine giving you better data. >> It's an incredible dynamic to me, Jeff, because it's not like this company has a blank sheet of paper and says, "Okay, let's go after developers." They have this impassioned community of people, and they just keep rolling out new function, and then of course, ServiceNow has some really killer developers, internally, and so they make those people available to inspire and educate other developers, and so, as they say, this platform just permeates throughout the organization. I mean, it's really hard to do platforms. We've seen it so many times, you know, companies saying, "Okay, we're developing a platform," and the platform gets a little traction and it gets bought out, but this company, ServiceNow, really has a foothold here. So 4,500 people at CreatorCon this year, it's up from 2,000 last year, so another example of just super meteoric growth. Pat Casey, I loved, he put up the, you know, he showed a mainframe. It actually looked like a VAX to me, but anyway he put up a mainframe, and then he showed the H-P-U-X, what did he call it, HPUX? And, oh yeah we thought that was better, and then client server, it kind of worked for a while, and then he put up "August of 1995," and of course I was immediately saying, that's Gabe Ryden. >> Right, right. >> And then he showed the NetScape logo, and that really changed the development paradigm. >> Just as a way to, you know, and I'm sure none of us thought of it, it was just kind of web bulletin boards with pictures now, when you saw NetScape back in the day, but really as an application delivery vehicle, when you think of what browsers have become, it's pretty fascinating. I had a friend who was working on Chrome, and they described it as kind of an OS in a browser, and I'm like, who would want an OS in a browser? Well, now we're basically here. It's like the old Sun Ray machine, right? Anytime you log onto your browser, you're basically into everything in your world. Whether it's your phone, your tablet, my computer, your desktop computer. It's pretty fascinating. The other thing that Pat talked about was, you know, these things that we grew up with kind of in our imagination. He talked about flying cars, and then he adjusted it to maybe electronic cars, this vision, and now, you know, electronic cars are here, and Tesla's the highest-selling luxury nameplate out there. But in my old world it was flat TVs. The Jetsons had flat TVs. The concept of a flat TV was completely bizarre, and I remember seeing the first one in Chicago, at the Consumer Electronics show. It was like nine inches, you had to have secret passes to get back to see it, but now look what happened. I can't help but think of a Mar's Law, Dave, and he's Gartner's Trough of Disillusionment. I like a Mar's Law better, which is we overestimate the impact in the short term, but way underestimate the impact in the long term. Look at flat screens now, compared to, well, it didn't even exist now. And that's going to happen in AI, it's going to happen in machine learning, and in a very short period of time, especially with the advances in compute-store, networking, cloud, speed of networks, IOT, it's going to be a phenomenal amount of horsepower driving your interaction with all these various objects. >> Look at even the dot-com, you know, how overhyped that was, when really it was underhyped. >> Jeff: Right, in the long term. >> So, the other thing I loved, we've been talking about data for quite some time, and every time we came to a Knowledge show, we'd say, is there a big data angle here? Eh, well kind of, and it's really now coming into focus what the machine learning and AI and big data angle is, and Pat threw up a really nice infographic. He went back to 1969, he gave some interesting stats that I wasn't aware of. I knew the 2k, the moon landing was done on a computer with 2k of memory, that I knew. What I did not know is that it had two programs: one for docking and one for landing, and there wasn't enough memory on the computer to have both programs, so they had to reprogram the computer after the dock. >> Not even reload, right? They couldn't just put the USB stick into it. >> They had the code, which is kind of cool. So that was 2k, he had an intern download the 1982 census, and it was 182 megabytes. And then the human genome project was 53 gigabytes, which he's right, it wouldn't have fit on your previous iPhone, but it will fit on this one. And then, I didn't know this stat, the spell-checker in all of our phones and the red lines and so forth, the back end of that, that's sitting in the cloud, is four terabytes. So you're seeing this explosion of data. These are just some simple examples. So this company, again, it's not just starting from scratch saying, here's some kind of machine learning tool, apply it. What they're doing is saying, we're going to build this into the platform, take the existing corpus of data that you have, now what is that corpus of data? It's a bunch of incidents, it's a bunch of categories and people and it's going to autocategorize, for example, all these incidents, on an existing corpus of data. That's not how most people are using machine learning today. What many people are talking about is a use case of real time continuous applications and doing machine learning in real time to try to affect an outcome, which means try to get you to buy something, or try to detect fraud, or whatever it is. Some healthcare outcome, even. Although you'd think healthcare could be some more post process, but essentially that's what ServiceNow is doing. They're using a post-process methodology on top of this corpus of data to add instant value that lives inside of the platform. It's very compelling, simple, and practical in my view. >> And that's the part I love the best, Dave, is simple and practical and delivers immediate results. Allen Leinwand, who we'll have on later and we've had on a number of times, made a mention that the other thing that's very different is now the apps are listening in real time, and they're adjusting what they're doing and rejiggering their algorithm based on stuff that's happening in real time. So it's a different way to think about applications. And just a couple of things I wanted to touch on from yesterday, with some of the guests we had, a great reason we love the show is the number of customers we get is so high. And I was just struck by Donna Woodruff from Cox Automotive, how much she understood innately that it's a platform. Yes, she bought some applications, but she really understood the platform component and was able to drive from it. And the other one I just wanted to touch on was Eresh from Vitas Healthcare, and the impact of mobile. All I could think about when he was talking about was delivery service. Where's my truck, I had my fridge fixed the other day, where's the guys he close called me, and then to apply that to something as powerful as the work they're doing around hospice and to enable that nurse to get to one more stop per day. Wow, what an impact, just by getting on mobile. And the funny part, he said, is some of their older nurses, when they saw the mobile device, said, "I'm done, I'm not doing it anymore. I'd rather schlep around 25 pages of case information and then go back and forth to the hub in between every stop." So again it's this combination of all this power, all this coming to bear along the three horses of compute that are now delivering phenomenal transformation to people that are willing to think of things in a slightly different lens. >> Yeah, and when you look at the problems that ServiceNow is solving, they are in the boring but important category. And that's why I think that this company for a long time sort of flew under the radar, and is still misunderstood. I mean, even CJ, who's basically in charge of all the products, when he was first approached by ServiceNow, he's like "Meh, I don't really know." And then he dug into it and said, "Wow." So a lot of people don't understand it. I talked to a lot of people in the software business, software sales, people that just don't understand the power of what this company does, and I would make a prediction, is that like Salesforce before it, and we've been talking about this for years, how these guys are on a collision course, and they'll say "No, no, no" but very clearly, the power of the platform that Salesforce has, for example, and ServiceNow is replicating, in some way is much much different. Because Salesforce has a lot of bulldogs, sorry, we love it, we use it, but my point is, my prediction is that over time this company is going to become a very well-known company because of the impacts that it's having on the business. It's going from boring but important to, you know, fundamental transformation of organizations. And I tell you, CRM, I even put it up there with ERP. I think that what ServiceNow is doing is as big as the ERP trend, potentially bigger when you put in all the IOT stuff and the machine learning capabilities and the like with what is a relatively modern platform. >> Well, we're in an attention game, right? On the consumer side it's about attention. The thing that people have the least amount of anymore is time, so how do you get their attention? Do they spend their time on Facebook, Instagram, Snapchat, watching TV, looking at YouTube videos? Watch your kids. How do they spend those hours of their day? On the work side, what screen are you interacting with in your day? Are you in Salesforce all day? Are you in email all day? Are you in Salesforce all day? Are you in Marketo all day? That's where the competition is going to come. And there's only going to be two or three primary applications in which you engage and get work done, and they're making a hard play to say, "We are the application that we want basically in your face, that you're using to get stuff done all day long." >> One of the things, too, I wonder, you always wonder, is think about blind spots to a company like this. They're on this amazing ascendancy. What could come in and disrupt ServiceNow? And you think about the millenials, there's no question that ServiceNow is on to the new way to work. I call it the new way to work, I don't think they use that term. And the millenials are going to come in, and they don't want to use email. They're going to be much more open to adopting a platform. Now, is that platform going to be something like ServiceNow or is it going to be too boring but important? Are they going to do something more like Facebook? My feeling is this is enterprise, and as we talked about yesterday, is it possible that enterprise could actually begin adopting a lot of these consumer-like interfaces and user experiences and leapfrog in some regards because of the use of AI and the enterprise nature and the security capabilities that a company like this can bring? I don't know, maybe that's a stretch, but the gap between consumer and enterprise has to close. It is closing, and I think it will continue to close. >> I think it's the automation piece, to automate themselves out of their customer base. As more and more things are automated, there's going to be less and less and less people looking at the screen to do fewer tasks in terms of just an in. Blind spots always come where you're not looking, that's what's going to hit them, but certainly as more and more of this mundane stuff can be automated, if they can actually execute their vision so these autocategorization and autorouting and things are getting solved before they get to a customer service agent, happen, then their C-base licenses, but that's why they're trying to find other places to go. Facilities management, HR management, integration on the human connection across multiple applications, and to even these other systems, like we've heard about on the HR side, etc. So, I think that's, as the nature of work changes, what will people be doing with their work, or are they just going to be getting assigned tasks to go execute what the machines can't do? It's going to be interesting to watch it evolve. >> Well, and then coming back to the top of this segment, the developers, and that's really where the innovation occurs. The developer ecosystem here continues to grow. The importance of developers is very well understood. We've seen it previously with companies like Microsoft. We see all the big enterprise companies trying to appeal to the developer community. Certainly Amazon, Google, having great, very strong developer ecosystems, Apple as well, Facebook, and so forth. Enterprise guys continue to struggle, frankly, in that regard, and IBM's done a good job with Bluemix, but it's been a real heavy lift for IBM, HP. We've talked to, from Kadifa to all their software execs, and they just never were able to figure it out. Oracle kind of lost its developer edge, despite the fact that it owns Java now, and it's trying to get that back, whereas, as they say, ServiceNow just says, "Hey, let's have a game," and they throw their glove in the field and boom, everybody shows up. >> Think of the focus of a SaaS software company, or even like an Amazon, AWS, right? Everyone here in the company is working on platforms and derivative products from that platform. They don't have this hardware group, that hardware group, this software group, that software group. It's a single application at the end of the day. Salesforce is a single application at the end of the day, work day, single application at the end of the day. AWS, infrastructure for customers at the end of the day. So I think that gives them a huge advantage in terms of focus, everybody going in the same direction, and ability to execute. >> Everybody talks about platform as a service, and it's really, a lot of people say that whole market's collapsing. It's IaaS+, think Amazon, and it's SaaS-, think Salesforce and ServiceNow. All right, we've got to wrap. Keep it right there, buddy. We'll be back with our next guest at theCUBE, we're live, Day 3 from Knowledge17. We're right back. (upbeat music)
SUMMARY :
brought to you by ServiceNow. One of the key things, Jeff, that is notable, and checked in on the Hackathon. in the field, and everybody comes to the game. and sort of the icon of ServiceNow, not here, you know? and not just the business analyst, and so they make those people available to inspire and that really changed the development paradigm. and I remember seeing the first one in Chicago, Look at even the dot-com, you know, I knew the 2k, the moon landing was done They couldn't just put the USB stick into it. in all of our phones and the red lines and so forth, and then go back and forth to the hub and the like with what is a relatively modern platform. and they're making a hard play to say, and the enterprise nature and the security capabilities at the screen to do fewer tasks in terms of just an in. Well, and then coming back to the top of this segment, It's a single application at the end of the day. and it's really, a lot of people say
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
Donna Woodruff | PERSON | 0.99+ |
two | QUANTITY | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Jeff | PERSON | 0.99+ |
Donna | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
Jeff Frick | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Pat Casey | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Fred | PERSON | 0.99+ |
Allan Leinwand | PERSON | 0.99+ |
Cox Automotive | ORGANIZATION | 0.99+ |
August of 1995 | DATE | 0.99+ |
Allen Leinwand | PERSON | 0.99+ |
two programs | QUANTITY | 0.99+ |
Chicago | LOCATION | 0.99+ |
HP | ORGANIZATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
53 gigabytes | QUANTITY | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
CJ Desai | PERSON | 0.99+ |
ORGANIZATION | 0.99+ | |
Pat | PERSON | 0.99+ |
182 megabytes | QUANTITY | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
Orlando Florida | LOCATION | 0.99+ |
Tesla | ORGANIZATION | 0.99+ |
both programs | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
4,500 people | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
2013 | DATE | 0.99+ |
1969 | DATE | 0.99+ |
Fred Luddy | PERSON | 0.99+ |
Java | TITLE | 0.99+ |
iPhone | COMMERCIAL_ITEM | 0.99+ |
nine inches | QUANTITY | 0.99+ |
Eresh | PERSON | 0.99+ |
Chrome | TITLE | 0.99+ |
last year | DATE | 0.99+ |
Mar's Law | TITLE | 0.99+ |
CreatorCon | EVENT | 0.99+ |
three horses | QUANTITY | 0.99+ |
Gabe Ryden | PERSON | 0.99+ |
EMC | ORGANIZATION | 0.99+ |
three years ago | DATE | 0.99+ |
HPE | ORGANIZATION | 0.99+ |
first one | QUANTITY | 0.99+ |
Vitas Healthcare | ORGANIZATION | 0.99+ |
ServiceNow | ORGANIZATION | 0.98+ |
Salesforce | ORGANIZATION | 0.98+ |
first | QUANTITY | 0.98+ |
Jetsons | ORGANIZATION | 0.98+ |
this week | DATE | 0.98+ |
Day 3 | QUANTITY | 0.97+ |
single application | QUANTITY | 0.97+ |
2k | QUANTITY | 0.97+ |
four terabytes | QUANTITY | 0.96+ |
today | DATE | 0.96+ |
HPUX | ORGANIZATION | 0.96+ |
One | QUANTITY | 0.96+ |
Bluemix | ORGANIZATION | 0.95+ |
this year | DATE | 0.94+ |
DevOps | ORGANIZATION | 0.94+ |