>> Voiceover: From around the globe, it's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Hello and welcome back everyone to theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, your host of theCUBE. I'm excited to have this next guest, CUBE alumni, K.C. Choi, Corporate EVP, Executive Vice President and General Manager at Samsung Mobile the B2B/B2G Team. K.C., great to see you, how you've been? >> John, it is wonderful to see you and it's been way too long. Great to be back on theCUBE with you looking forward to our conversation and I hope you're safe. >> Yeah and same to you. Great to see you, I'm so excited. One of the things I've really admired about you and our conversations in the past is you've always had your finger on the pulse of the waves and you're always involved with some really great engineering work. And I want to dig into this now because your role is really hitting the industry for that kind of wave which is the confluence of tech, media, entertainment, every vertical, big data, IOT and with the distributed computing now called the Cloud and edge. It really sets the table for what is now going to be the preferred architecture probably for the next 20 plus years. So give us your view on how you see the changing landscape in the industry. >> Yeah, I think you covered all of the major seismic shifts that are happening here. And then as we've all experienced over the last, over a year with the COVID pandemic, that's actually accelerated a lot of the thinking around edge. We've certainly seen news cases proliferate whether it be in things such as healthcare, manufacturing's also taken I think, a real hard look at the applicability of these types of solutions. We've seen things like, for example 5G pickup in these industrial applications as the industrial companies have thought about worker safety, as they've thought about automation, as they thought about utilizing more protocols, as well as bringing these technologies and processes together in a way that will help to reinvent their particular economic base, as well as the learnings that we've seen over the last year, coming from these new safety protocols as well as the need for now with the economies is picking back up, the need for productivity, as well as greater efficiencies coming from these types of solutions. So we've seen that confluence happen. And then certainly on our end, as our network connectivity has become much stronger, lower latency, as well as the endpoint capabilities have increased dramatically over the last few years, as SOC and others have taken root, we've seen the edge, if you will, start be more extreme, in the sense that it's pushing further and further out beyond what we originally envisioned the edge to be. >> And the SOC trend actually highlights that it's not so much about Moore's law as it is more about more chips, more performance. If you look at actual performance, Dave Vellante just put out a report on this, where there's actually more performance now than ever before coming in from the combined energy and combined processing power out there. So it's super, super amazing what you can do at the edge. Before we get into the edge, I want to just clarify what is your new role there? I mean, Samsung is known for obviously the B2C with the phones and everything else, but you have a specific focus, what is your main focus there? >> Yeah, our mission's pretty straightforward. And as everyone knows, Samsung is a powerhouse consumer electronics company. We pride ourselves in obviously our position in that, but we also have a very significant role really in the business to business and in the government and financial services sector space with our mobile devices, as well as with our Knox security platform solution and device management platform. We actually provide a large portion of the security devices for governments worldwide as well as the Knox platform that is built into the majority of our, both, consumer as well as business devices that really allows for that, if you will, that next protective layer on top of the Android OS that allows for things such as, personal and professional profiles. So we produce those solutions out of my team as well as we provide really the go-to-market support, as well as the RnD support for that platform, including an area that's growing rapidly for us which is in the rugged category, which is one of the key products that we're using for some of these edge applications that we'll be talking about. >> Great, let's jump into that. What are you guys doing specifically in the edge computing space? Let's dig into it. >> Yeah, I think maybe the place to start on that is we're really reenvisioning what the edge is. And I mentioned a little earlier that with what's occurring in the performance profile and really the functional profile, what is being produced at the device level. We're talking about in the last few years, the fidelity and the capabilities are in, what I would call the computer class type functions, as well as obviously mobile devices have always been communication gateways for a number of functions, whether they be videos or photos. They're multisensory in nature. And as this has become more practical and the connective tissue has gotten there with 5G as well as all kinds of other fast low latency communications capabilities and Wi-Fi 6, UWB, included within that. What we're finding is that the use case to bring applications especially cloud native and container native applications to these devices to be augmenting the endpoint user, the frontline worker, really the knowledge worker and moving that capability further away from, if you will, an extension to cloud services as well as MEC type services, this is where we see it going. And really what we're trying to work on with IBM and with Red Hat is how do we continue to fortify this, not only from an actual processing AI/ML capability, but also equip these devices so that they can fully participate as part of a multi-hybrid cloud architecture. The endpoint is really one of the last bastions where we have not conquered bringing cloud first container native applications really to that point. And we believe the time is right because of the capabilities that are there along with, again, the connectivity that is becoming much more ubiquitous now to allow for that type of architecture to exist. And we're starting to call this the intelligent human edge as well. We think that the applications that we'll see for this are ones that will make the human operator more productive, safer, certainly more efficient. And we think that this augmentation of that frontline worker is an area that we are, put our stakes on in terms of pioneering, just because of again, our experience in that mobility space and in that consumer space. >> That's great you brought up Red Hat and IBM. Obviously Red Hat was bought by IBM. Arvin, the CEO who I interviewed in 2019 in theCUBE at Red Hat summit, ironically, a couple months later, buys the company and a smile on his face. He likes cloud. >> K.C.: Maybe you had something to do with that, John. >> No, he wanted to, I could see he wanted to say it, but he loves the cloud. Everyone who knows Arvin knows that he's into the cloud in a new way. And this edge piece that you mentioned that you're using Red Hat and IBM for hybrid, this is what the new operating system is going to look like. It's a completely distributed system and the edge is just part of that operating model. This is what their vision is, which I love by the way. I think that redefines what that is. Are you saying that you guys are working with Red Hat and IBM for that hybrid edge piece? How does that work? Can you take me through that? >> Yeah, that's exactly right. I mean, obviously the ecosystem is bigger than that, but IBM and Red Hat really bring the expertise really around container ecosystems, certainly the work that they have done in terms a multi hybrid cloud, certainly the work that OpenShift has brought forward in terms of, you know, multi-platform capability. We really love the concept of develop bonds run, any sort of a construct. And when you think about it, the mobile platforms specifically, you know, ours, as well as others, has really been that last baskin of areas where more of the development is on a particular platform, it's more bespoke. We think that by broaching this, you know in conjunction with IBM and Red Hat this is going to give us the ability to have these device architectures become a full voting member, if you will, of that hybrid cloud architecture and of that microservice container architecture that is becoming much more prevalent. So this is really the work that we're doing. And then obviously we're working at a vertical level to see where are the applicable use cases in places such as the design studio we have in Singapore, where with the Singaporean government we're looking at really bringing a Renaissance to industry 4.0 type applications, smart factory automation, public safety, these areas where we believe that this type of architecture can be deployed. >> That's awesome. And I totally believe that, you know the edge is still going to be pushed farther and further out, honestly, having that open standards of hybrid. So I got to ask you, on the edge just while I got you here, you know, one of the things that you see clearly as the industrial edge, it's called, factories and whatnot. You've mentioned some of those. And then you've got the human piece, which is like people have phones and wearables and other things are going to be happening. So as you start to have those end points, which are then going to be connected into a distributed network, AKA a hybrid cloud, soon to be multiple clouds. But that's the sub system within the cloud construct. The complaint has been, not complaint, but the observation has been and complaint, if you look at it that the edge is limited by power and connectivity, okay. These are like key basic concepts. How is the connectivity option? I know 5G is coming, it's here, we're seeing it being deployed. We got people saying, hey, this is our business application. Clearly got higher throughput, not as much range. Give us your take on this because this becomes important, obviously, power is battery that is driven, it's getting better and better and power is not really that much of a problem, but connectivity seems to be, what's your vision of this? >> Yeah and you know, there's a lot of ways to approach that. I will tell you on the industrial side, at least in some of the deployments and PLCs that we've been involved in over the last a year or two years, connectivity is an issue. And a lot of it has to do with the infrastructure that is available in many of these plants or factories, or points of distribution, they're not necessarily leading edge, in many cases we're dealing with what I would call sub par connectivity. It's not like an office complex where you may have state-of-the-art Wi-Fi capability or 10 gig capability or whatever it might be. So what we've found on that is it requires actually quite a bit of work, in terms of fine tuning, both, on the the network infrastructure side, whatever that might be or we've also found that on the device side, the programmability of the of the device, in terms of tuning it for whatever connective environment would be there. And we've worked with everything from, you know, Bluetooth, UWB to Wi-Fi 6 and everything in between and in many cases or multiple protocols or connectivity methods that are there. So, you know, one thing we've learned is that you can't necessarily assume that in a, especially in a factory environment that those conditions are going to allow for consistency. So you have to engineer around that, you know, in some of the things that we've done are really around making sure that we've got deployable programmability at the device as well as board dynamic network tuning capabilities that will allow for better connectivity and to handle things such as consistency. >> All right, K.C., great insight. Final question for you, why Samsung and IBM? What's the bottom line? >> Yeah, I think the bottom line is really straightforward. I mean, we've had a 30 year history of working together, you know, we've been mutual customers to each other. We do a lot of work for IBM, in regards to foundry type services and semiconductor services. And that we work very closely with them over many years on applications. So number one, there's been a natural relationship, just in the services that we provided to each other. But as we look at really the go-to-market, I mean, IBM brings so much credibility from a vertical market perspective. There's a trusted advisor type status that I think is a very profound and it's been built over many years, you know, delivering on the promises. And on our end, I think what we bring is really this cycle time that is driven by our passion in the consumer space. And when we start to apply that into more of these vertical industrial, you know, vertical sectors, I think that combination is very powerful. The services piece obviously comes into play with IBM. And then really, the Red Hat piece of this really just puts the icing on the cake with really the the market leadership in hybrid cloud and in the container native architecture, so it's just a very powerful combo and the cooperation there has been strong and we continue to look forward to delivering more through that partnership. >> K.C., great to see you, great thing to hear. You know, you got scalable infrastructure, you got modern applications, got the edge, all hybrid. Great partnership. K.C. Choi, Corporate Executive Vice President and General Manager of Samsung Mobile B2B Team. Great to see you and congratulations on your mission and it's an exciting project. Thanks for coming on theCUBE and sharing. >> Great to see you, John, take care of yourself and looking forward to seeing you again. >> Okay, this is theCUBE's coverage IBM Think 2021. I'm John Furrier, your host of theCUBE. Thanks for watching. (soft upbeat music) (melodious music)

(melodious music) >> Voiceover: From around the globe, it's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Hello and welcome back everyone to theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, your host of theCUBE. I'm excited to have this next guest, CUBE alumni, K.C. Choi, Corporate EVP, Executive Vice President and General Manager at Samsung Mobile the B2B/B2G Team. K.C., great to see you, how you've been? >> John, it is wonderful to see you and it's been way too long. Great to be back on theCUBE with you looking forward to our conversation and I hope you're safe. >> Yeah and same to you. Great to see you, I'm so excited. One of the things I've really admired about you and our conversations in the past is you've always had your finger on the pulse of the waves and you're always involved with some really great engineering work. And I want to dig into this now because your role is really hitting the industry for that kind of wave which is the confluence of tech, media, entertainment, every vertical, big data, IOT and with the distributed computing now called the Cloud and edge. It really sets the table for what is now going to be the preferred architecture probably for the next 20 plus years. So give us your view on how you see the changing landscape in the industry. >> Yeah, I think you covered all of the major seismic shifts that are happening here. And then as we've all experienced over the last, over a year with the COVID pandemic, that's actually accelerated a lot of the thinking around edge. We've certainly seen news cases proliferate whether it be in things such as healthcare, manufacturing's also taken I think, a real hard look at the applicability of these types of solutions. We've seen things like, for example 5G pickup in these industrial applications as the industrial companies have thought about worker safety, as they've thought about automation, as they thought about utilizing more protocols, as well as bringing these technologies and processes together in a way that will help to reinvent their particular economic base, as well as the learnings that we've seen over the last year, coming from these new safety protocols as well as the need for now with the economies is picking back up, the need for productivity, as well as greater efficiencies coming from these types of solutions. So we've seen that confluence happen. And then certainly on our end, as our network connectivity has become much stronger, lower latency, as well as the endpoint capabilities have increased dramatically over the last few years, as SOC and others have taken root, we've seen the edge, if you will, start be more extreme, in the sense that it's pushing further and further out beyond what we originally envisioned the edge to be. >> And the SOC trend actually highlights that it's not so much about Moore's law as it is more about more chips, more performance. If you look at actual performance, Dave Vellante just put out a report on this, where there's actually more performance now than ever before coming in from the combined energy and combined processing power out there. So it's super, super amazing what you can do at the edge. Before we get into the edge, I want to just clarify what is your new role there? I mean, Samsung is known for obviously the B2C with the phones and everything else, but you have a specific focus, what is your main focus there? >> Yeah, our mission's pretty straightforward. And as everyone knows, Samsung is a powerhouse consumer electronics company. We pride ourselves in obviously our position in that, but we also have a very significant role really in the business to business and in the government and financial services sector space with our mobile devices, as well as with our Knox security platform solution and device management platform. We actually provide a large portion of the security devices for governments worldwide as well as the Knox platform that is built into the majority of our, both, consumer as well as business devices that really allows for that, if you will, that next protective layer on top of the Android OS that allows for things such as, personal and professional profiles. So we produce those solutions out of my team as well as we provide really the go-to-market support, as well as the RnD support for that platform, including an area that's growing rapidly for us which is in the rugged category, which is one of the key products that we're using for some of these edge applications that we'll be talking about. >> Great, let's jump into that. What are you guys doing specifically in the edge computing space? Let's dig into it. >> Yeah, I think maybe the place to start on that is we're really reinvisioning what the edge is. And I mentioned a little earlier that with what's occurring in the performance profile and really the functional profile, what is being produced at the device level. We're talking about in the last few years, the fidelity and the capabilities are in, what I would call the computer class type functions, as well as obviously mobile devices have always been communication gateways for a number of functions, whether they be videos or photos. They're multisensory in nature. And as this has become more practical and the connective tissue has gotten there with 5G as well as all kinds of other fast low latency communications capabilities and Wi-Fi 6, UWB, included within that. What we're finding is that the used case to bring applications especially cloud native and container native applications to these devices to be augmenting the endpoint user, the frontline worker, really the knowledge worker and moving that capability further away from, if you will, an extension to cloud services as well as MEC type services, this is where we see it going. And really what we're trying to work on with IBM and with Red Hat is how do we continue to fortify this, not only from an actual processing AI ML capability, but also equip these devices so that they can fully participate as part of a multi hybrid cloud architecture. The endpoint is really one of the last baskins where we have not conquered bringing cloud first container native applications really to that point. And we believe the time is right because of the capabilities that are there along with, again, the connectivity that is becoming much more ubiquitous now to allow for that type of architecture to exist. And we're starting to call this the intelligent human edge as well. We think that the applications that we'll see for this are ones that will make the human operator more productive, safer, certainly more efficient. And we think that this augmentation of that frontline worker is an area that we are, put our stakes on in terms of pioneering, just because of again, our experience in that mobility space and in that consumer space. >> That's great you brought up Red Hat and IBM. Obviously Red Hat was bought by IBM. Arvin, the CEO who I interviewed in 2019 in theCUBE at Red Hat summit, ironically, a couple months later, buys the company and a smile on his face. He likes cloud. >> K.C.: Maybe you had something to do with that, John. >> No, he wanted to, I could see he wanted to say it, but he loves the cloud. Everyone who knows Arvin knows that he's into the cloud in a new way. And this edge piece that you mentioned that you're using Red Hat and IBM for hybrid, this is what the new operating system is going to look like. It's a completely distributed system and the edge is just part of that operating model. This is what their vision is, which I love by the way. I think that redefines what that is. Are you saying that you guys are working with Red Hat and IBM for that hybrid edge piece? How does that work? Can you take me through that? >> Yeah, that's exactly right. I mean, obviously the ecosystem is bigger than that, but IBM and Red Hat really bring the expertise really around container ecosystems, certainly the work that they have done in terms a multi hybrid cloud, certainly the work that OpenShift has brought forward in terms of, you know, multi-platform capability. We really love the concept of develop bonds run, any sort of a construct. And when you think about it, the mobile platforms specifically, you know, ours, as well as others, has really been that last baskin of areas where more of the development is on a particular platform, it's more bespoke. We think that by broaching this, you know in conjunction with IBM and Red Hat this is going to give us the ability to have these device architectures become a full voting member, if you will, of that hybrid cloud architecture and of that microservice container architecture that is becoming much more prevalent. So this is really the work that we're doing. And then obviously we're working at a vertical level to see where are the applicable use cases in places such as the design studio we have in Singapore, where with the Singaporean government we're looking at really bringing a Renaissance to industry 4.0 type applications, smart factory automation, public safety, these areas where we believe that this type of architecture can be deployed. >> That's awesome. And I totally believe that, you know the edge is still going to be pushed farther and further out, honestly, having that open standards of hybrid. So I got to ask you, on the edge just while I got you here, you know, one of the things that you see clearly as the industrial edge, it's called, factories and whatnot. You've mentioned some of those. And then you've got the human piece, which is like people have phones and wearables and other things are going to be happening. So as you start to have those end points, which are then going to be connected into a distributed network, AKA a hybrid cloud, soon to be multiple clouds. But that's the sub system within the cloud construct. The complaint has been, not complaint, but the observation has been and complaint, if you look at it that the edge is limited by power and connectivity, okay. These are like key basic concepts. How is the connectivity option? I know 5G is coming, it's here, we're seeing it being deployed. We got people saying, hey, this is our business application. Clearly got higher throughput, not as much range. Give us your take on this because this becomes important, obviously, power is battery that is driven, it's getting better and better and power is not really that much of a problem, but connectivity seems to be, what's your vision of this? >> Yeah and you know, there's a lot of ways to approach that. I will tell you on the industrial side, at least in some of the deployments and PLCs that we've been involved in over the last a year or two years, connectivity is an issue. And a lot of it has to do with the infrastructure that is available in many of these plants or factories, or points of distribution, they're not necessarily leading edge, in many cases we're dealing with what I would call sub par connectivity. It's not like an office complex where you may have state-of-the-art Wi-Fi capability or 10 gig capability or whatever it might be. So what we've found on that is it requires actually quite a bit of work, in terms of fine tuning, both, on the the network infrastructure side, whatever that might be or we've also found that on the device side, the programmability of the of the device, in terms of tuning it for whatever connective environment would be there. And we've worked with everything from, you know, Bluetooth, UWB to Wi-Fi 6 and everything in between and in many cases or multiple protocols or connectivity methods that are there. So, you know, one thing we've learned is that you can't necessarily assume that in a, especially in a factory environment that those conditions are going to allow for consistency. So you have to engineer around that, you know, in some of the things that we've done are really around making sure that we've got deployable programmability at the device as well as board dynamic network tuning capabilities that will allow for better connectivity and to handle things such as consistency. >> All right, K.C., great insight. Final question for you, why Samsung and IBM? What's the bottom line? >> Yeah, I think the bottom line is really straightforward. I mean, we've had a 30 year history of working together, you know, we've been mutual customers to each other. We do a lot of work for IBM, in regards to foundry type services and semiconductor services. And that we work very closely with them over many years on applications. So number one, there's been a natural relationship, just in the services that we provided to each other. But as we look at really the go-to-market, I mean, IBM brings so much credibility from a vertical market perspective. There's a trusted advisor type status that I think is a very profound and it's been built over many years, you know, delivering on the promises. And on our end, I think what we bring is really this cycle time that is driven by our passion in the consumer space. And when we start to apply that into more of these vertical industrial, you know, vertical sectors, I think that combination is very powerful. The services piece obviously comes into play with IBM. And then really, the Red Hat piece of this really just puts the icing on the cake with really the the market leadership in hybrid cloud and in the container native architecture, so it's just a very powerful combo and the cooperation there has been strong and we continue to look forward to delivering more through that partnership. >> K.C., great to see you, great thing to hear. You know, you got scalable infrastructure, you got modern applications, got the edge, all hybrid. Great partnership. K.C. Choi, Corporate Executive Vice President and General Manager of Samsung Mobile B2B Team. Great to see you and congratulations on your mission and it's an exciting project. Thanks for coming on theCUBE and sharing. >> Great to see you, John, take care of yourself and looking forward to seeing you again. >> Okay, this is theCUBE's coverage IBM Think 2021. I'm John Furrier, your host of theCUBE. Thanks for watching. (soft upbeat music) (melodious music)

>>from around >>The globe. It's the cube with digital coverage of IBM. Think 2021 brought to you by IBM Hello and welcome back everyone to the cubes coverage of IBM Think 2021 virtual. I'm john for your host of the cube. I'm excited to have this next guest cube alumni Casey choi corporate E V P. Executive vice president and general manager at Samsung Mobile, the B to B and B to G team Casey, great to see you how you been >>john it is wonderful to see you and it's been way too long. Great to be back on the cube with you. Looking forward to our conversation and hope you're safe >>and same to you. Great to see you. I'm so excited. One of the things I've really admired about you and our conversations in the past as you've always had your finger on the pulse of the waves and you've always involved with some really great engineering work and I want to dig into this now because um your role is really hitting the industry four dot oh kind of wave, which is the confluence of tech, media, entertainment, every vertical big data IOT and the the with the distributed computing now called the cloud and edge. It really sets the table for what is now going to be the preferred architecture probably for the next 20 plus years. So give us your view on how you see the the changing landscape in the industry. >>Yeah, I think I think you you covered you know, all of the major seismic shifts that are happening here and then, you know, as we've all experienced over the last, you know, over a year with the covid pandemic, that's actually accelerated a lot of the thinking around the edge. We've certainly seen use cases proliferate whether it be in things such as health care, Manufacturing is also taken. I think a real hard look at the applicability of these types of solutions. Uh we've seen things like for example 5G pick up in these sort of industrial applications as um you know as the industrial companies have thought about worker safety as they thought about automation as they thought about, you know, utilize being more protocols as well as you know, bringing these technologies and processes together in a way that will help to kind of reinvent their their particular economic base as well as kind of the learnings that we've seen over the last year coming from these new uh safety protocols as well as the need for now with the economy is picking back up the need for productivity as well as you know, greater efficiencies coming from these types of solutions. So we've seen that confluence happened and then certainly on our end as our network connectivity has become much stronger, lower latency as well as the endpoint capabilities have increased dramatically over the last few years, as S O C. S and others have taken root. We've seen the edge, if you will start to be more extreme in the sense that it's pushing further and further out beyond what we originally envisioned the edge to be. >>And the S O C trend actually highlights that it's not so much about moore's law as it is more about more chips, more more performance if you look at actual performance, David and they just put out a report on this where there's much more performance now than ever before coming in from the combined energy. So uh and combined processing power out there. So it's super, super amazing what you can do at the edge. Before we get into the edge. I want to just Clarify, what is your new role there? I mean Samsung is known for, I'll see the B2C with the phones and everything else, but you have a specific focus uh what is your main focus there? >>Yeah, our missions pretty straightforward and as everyone knows, you know, Samsung is this uh you know, powerhouse uh consumer electronics company we pride ourselves in and obviously uh our our position in that, but um we also have a very significant role really in the business to business and in the government and financial services sector space uh with our mobile devices as well as with our knock security platform solution and device management platform. We actually provide a large portion of the secure devices for governments worldwide, as well as the Knox platform that is built into the majority of our both consumer as well as business devices uh really allows for uh that uh if you will that next protective layer on top of the android. Os that allows for things such as personal and professional profile. So we produce those solutions out of my team um as well as we provide really the the go to market support as well as the R and D support for that platform, including uh an area that's growing rapidly for us, which is in the rugged category, which is, you know, one of the key products that we're using for some of these edge applications that will be talking about. >>Great, let's jump into that. What are you guys doing specifically on the edge computing space? Let's dig into it. >>Yeah, I think, you know, maybe the place to start on that is uh we're really kind of re envisioning what the edges and uh I mentioned a little earlier that uh with what's occurring in the performance profile and really the functional profile, what is being produced at the device level, You know, we're talking about in the last few years, the fidelity and the capabilities are, you know, in, you know, what I would call the the computer class type uh, functions as well as obviously mobile devices have always been um, communication gateways for a number of functions, whether they be, you know, videos or photos, their multi sensory in nature. And as this has become more practical and the connective tissue has gotten there with five G as well as all kinds of other, you know, fast, low latency communications capabilities and wifi six U w b, you know, included within that. What we're finding is that the use case to bring applications, especially cloud, native and container native applications uh, to these devices to be, you know, augmenting the the endpoint user, the frontline worker, uh really the Knowledge Worker and moving that capability further away from if you will and an extension to cloud services as well as the M E C type services. This is where we see it going and really what we're trying to to work on with IBM and with red hat is how do we, you know, continue to fortify this, not only from a actual processing ai Ml capability, but also equipped these devices so that they can fully participate as part of a multi hybrid cloud architecture. Uh the endpoint is really one of the last baskets where we have not uh kind of conquered bringing uh, you know, cloud first container native applications really to that point and we believe the time is right because of the capabilities that are there along with again, uh the connectivity that is becoming much more ubiquitous now to allow for that type of architecture to exist. And uh, we're starting to call this the intelligent human edge as well. We think that the applications that will see for this are you know, ones that will uh, you know, make the, the human operator more productive, safer, uh certainly more efficient and uh we think that this augmentation of that front line workers is an area that we, we are, you know, put put our, our steaks on in terms of pioneering just because of our experience in that mobility space and in the consumer space. >>That's great. You brought up red hat and IBM obviously red hat was bought by IBM Arvin Arvin Ceo. Well I interviewed in 2019 and the cube that red hat summit, ironically a couple months later by the company just smile on his face. He likes clowns. >>You had something to do with that. You know, >>he wanted to, I could see he wanted to say it, but but he loves the cloud. Everyone who knows Arvin knows that he's into the cloud in a new way in this edge piece that you mentioned that you're using red hat and IBM for hybrid. This is what the new operating system is going to look like. It's a completely distributed system and the edge is just part of that operating model. This is what their vision is, which I love by the way, I think that redefines what that is. Are you saying that you guys are working with red hat and IBM for that hybrid edge piece. How does that work? Can you take me through that? >>Yeah, that's exactly right. I mean this is a obviously the ecosystems bigger than that, but IBM and red Hat really bring the expertise really around uh container ecosystems, certainly the work that they have done in terms of multi hybrid cloud, uh certainly the work that open ship has brought forward in terms of, you know, multi platform capability. We really love the concept of developed once run any sort of a construct. And uh when you think about it, the mobile platforms specifically, you know, ours as well as others has really been that last bastion of, of areas where more of the development is on a particular platform, it's more bespoke. We think that by broaching this uh, you know, in conjunction with IBM and Red Hat, um this is going to give us the ability to have these device architecture has become a full voting member if you will of of that hybrid cloud architecture and of that microservices can contain architecture that is becoming much more prevalent. So this is really the work that we're doing. And then obviously we're working at a vertical level to see where are the applicable use cases in places such as the design studio we have in Singapore, where with the Singaporean government, we're looking at really bringing a renaissance to industry ford auto type application, smart factory automation, public safety. These areas where we believe that this type of architecture can be, can be deployed. >>That's awesome. And totally believe that the edge um it's still gonna be pushed further and further out, honestly having that open, open standards of of hybrid. So I gotta ask you on the edge just well I got you here, you know, one of the things that you see clearly as the industrial edge, it's called factories and whatnot. You mentioned some of those and then you got the human piece, which is like people have phones and wearables and other things are gonna be happening. So as you start to have those endpoints which are then gonna be connected into a distributed network, take a hybrid cloud, so to be multiple clouds. But yeah, that's the subsystem within the cloud construct. The complaint has been not complaint, but the observation has been and complain if you look at it that the edges limited by power and connectivity. Okay. These are like key basic concepts, How is the connectivity option? I know five Gs coming, it's here, we're seeing it being deployed, we got people saying, hey, this is our business application, clearly got higher throughput, not as much range, give us your take on this because this becomes important. I'll see powers battery driven, getting better and better and and power is getting uh is not really that much of a problem, but connectivity seems to be what's your vision of this? >>Yeah, and you know, there's a lot of ways to approach that, I will tell you on the industrial side, at least in some of the deployments and pOC is that we've been involved in over the last year to two years, um connectivity is an issue uh and a lot of it has to do with the infrastructure that is available in many of these uh you know, plants or factories or you know, points of distribution. Uh they're not necessarily, you know, leading edge in many cases we're dealing with uh you know what I would call subpar connectivity, it's not like an office complex where You may have, you know, kind of state of the art wifi capability or you know, 10 gig capability or whatever it might be. Um So what we've, what we've found on that is it requires actually quite a bit of work in terms of fine tuning both on the network infrastructure side, whatever that might be. Uh Or we've also found that on the device side, the program ability of the of the device in terms of tuning it for whatever connective environment would be there. And we worked with everything from, you know, bluetooth, you w b uh to wifi six and everything in between and in many cases they're multiple uh you know, protocols or connectivity methods that are there. So, you know, one thing we've learned is that um you can't you can't necessarily assume that in a especially in a factory environment that those conditions are going to allow for um uh you know, consistency, so you have to engineer around that, you know, and some of the things that we've done are really around making sure that we've got uh, you know, deployable program ability at the device as well as, you know, uh more dynamic network tuning capabilities that will allow for, you know, better connectivity and handle things such as consistency. >>All right, Casey, Great to incite final question for you why Samsung and IBM, what's the bottom line? >>Yeah, I think the bottom line is really straightforward. I mean we've had a, you know, 30 year history of working together, uh you know, we've been mutual customers to each other. We do a lot of work for IBM in regards to foundry type services and semiconductor services and then we work very closely with them over many years on applications. So number one, there's been a natural relationship just in the the the services that we provided to each other. But as as we look at really to go to market, I mean, IBM brings so much credibility from a vertical market perspective. Um there's a trusted advisor type status that I think is is very profound and it's been built over many years, you know, delivering on the promises and on our end. I think what we bring is really this uh this uh cycle time that is driven by our passion in the consumer space. And when we start to apply that into more of these vertical industrial, uh you know, vertical sectors, I think that combination is very powerful. Um the services piece obviously comes into play with IBM and then really the red hat piece of this really just puts the icing on the cake with really the market leadership in uh you know, hybrid cloud and in the container native architecture. So it's just a very powerful combo. And um you know, the cooperation there has been strong and we continue to look forward to delivering more through that partnership. >>Casey great to see a great, great thing to hear. You know, you got scalable infrastructure, you get modern applications at the edge, all of hybrid. Great, great partnership. Casey Choi Executive Vice Corporate Executive Vice President and General Manager of Samsung Mobile B two B team. Great to see you and congratulations on your mission. It's exciting project. Thanks for coming on the cube and sharing. >>Great to see you, jOHn take care of yourself and looking forward to seeing you again. >>Okay, this is the cubes coverage. IBM think 2021. I'm john for your host of the cube. Thanks for watching.

>> From Cambridge, Massachusetts. It's theCUBE, covering MIT Chief Data Officer and Information Quality Symposium 2019. Brought to you by SiliconANGLE Media. >> Welcome back to Cambridge, Massachusetts, everybody. We're here at MIT, sweltering Cambridge, Massachusetts. You're watching theCUBE, the leader in live tech coverage, my name is Dave Vellante. I'm here with my co-host, Paul Gillin. Special coverage of the MITCDOIQ. The Chief Data Officer event, this is the 13th year of the event, we started seven years ago covering it, Mark Ramsey is here. He's the Chief Data and Analytics Officer Advisor at Ramsey International, LLC and former Chief Data Officer of GlaxoSmithKline. Big pharma, Mark, thanks for coming onto theCUBE. >> Thanks for having me. >> You're very welcome, fresh off the keynote. Fascinating keynote this evening, or this morning. Lot of interest here, tons of questions. And we have some as well, but let's start with your history in data. I sat down after 10 years, but I could have I could have stretched it to 20. I'll sit down with the young guns. But there was some folks in there with 30 plus year careers. How about you, what does your data journey look like? >> Well, my data journey, of course I was able to stand up for the whole time because I was in the front, but I actually started about 32, a little over 32 years ago and I was involved with building. What I always tell folks is that Data and Analytics has been a long journey, and the name has changed over the years, but we've been really trying to tackle the same problems of using data as a strategic asset. So when I started I was with an insurance and financial services company, building one of the first data warehouse environments in the insurance industry, and that was in the 87, 88 range, and then once I was able to deliver that, I ended up transitioning into being in consulting for IBM and basically spent 18 years with IBM in consulting and services. When I joined, the name had evolved from Data Warehousing to Business Intelligence and then over the years it was Master Data Management, Customer 360. Analytics and Optimization, Big Data. And then in 2013, I joined Samsung Mobile as their first Chief Data Officer. So, moving out of consulting, I really wanted to own the end-to-end delivery of advanced solutions in the Data Analytics space and so that made the transition to Samsung quite interesting, very much into consumer electronics, mobile phones, tablets and things of that nature, and then in 2015 I joined GSK as their first Chief Data Officer to deliver a Data Analytics solution. >> So you have long data history and Paul, Mark took us through. And you're right, Mark-o, it's a lot of the same narrative, same wine, new bottle but the technology's obviously changed. The opportunities are greater today. But you took us through Enterprise Data Warehouse which was ETL and then MAP and then Master Data Management which is kind of this mapping and abstraction layer, then an Enterprise Data Model, top-down. And then that all failed, so we turned to Governance which has been very very difficult and then you came up with another solution that we're going to dig into, but is it the same wine, new bottle from the industry? >> I think it has been over the last 20, 30 years, which is why I kind of did the experiment at the beginning of how long folks have been in the industry. I think that certainly, the technology has advanced, moving to reduction in the amount of schema that's required to move data so you can kind of move away from the map and move type of an approach of a data warehouse but it is tackling the same type of problems and like I said in the session it's a little bit like Einstein's phrase of doing the same thing over and over again and expecting a different answer is certainly the definition of insanity and what I really proposed at the session was let's come at this from a very different perspective. Let's actually use Data Analytics on the data to make it available for these purposes, and I do think I think it's a different wine now and so I think it's just now a matter of if folks can really take off and head that direction. >> What struck me about, you were ticking off some of the issues that have failed like Data Warehouses, I was surprised to hear you say Data Governance really hasn't worked because there's a lot of talk around that right now, but all of those are top-down initiatives, and what you did at GSK was really invert that model and go from the bottom up. What were some of the barriers that you had to face organizationally to get the cooperation of all these people in this different approach? >> Yeah, I think it's still key. It's not a complete bottoms up because then you do end up really just doing data for the sake of data, which is also something that's been tried and does not work. I think it has to be a balance and that's really striking that right balance of really tackling the data at full perspective but also making sure that you have very definitive use cases to deliver value for the organization and then striking the balance of how you do that and I think of the things that becomes a struggle is you're talking about very large breadth and any time you're covering multiple functions within a business it's getting the support of those different business functions and I think part of that is really around executive support and what that means, I did mention it in the session, that executive support to me is really stepping up and saying that the data across the organization is the organization's data. It isn't owned by a particular person or a particular scientist, and I think in a lot of organization, that gatekeeper mentality really does put barriers up to really tackling the full breadth of the data. >> So I had a question around digital initiatives. Everywhere you go, every C-level Executive is trying to get digital right, and a lot of this is top-down, a lot of it is big ideas and it's kind of the North Star. Do you think that that's the wrong approach? That maybe there should be a more tactical line of business alignment with that threaded leader as opposed to this big picture. We're going to change and transform our company, what are your thoughts? >> I think one of the struggles is just I'm not sure that organizations really have a good appreciation of what they mean when they talk about digital transformation. I think there's in most of the industries it is an initiative that's getting a lot of press within the organizations and folks want to go through digital transformation but in some cases that means having a more interactive experience with consumers and it's maybe through sensors or different ways to capture data but if they haven't solved the data problem it just becomes another source of data that we're going to mismanage and so I do think there's a risk that we're going to see the same outcome from digital that we have when folks have tried other approaches to integrate information, and if you don't solve the basic blocking and tackling having data that has higher velocity and more granularity, if you're not able to solve that because you haven't tackled the bigger problem, I'm not sure it's going to have the impact that folks really expect. >> You mentioned that at GSK you collected 15 petabytes of data of which only one petabyte was structured. So you had to make sense of all that unstructured data. What did you learn about that process? About how to unlock value from unstructured data as a result of that? >> Yeah, and I think this is something. I think it's extremely important in the unstructured data to apply advanced analytics against the data to go through a process of making sense of that information and a lot of folks talk about or have talked about historically around text mining of trying to extract an entity out of unstructured data and using that for the value. There's a few steps before you even get to that point, and first of all it's classifying the information to understand which documents do you care about and which documents do you not care about and I always use the story that in this vast amount of documents there's going to be, somebody has probably uploaded the cafeteria menu from 10 years ago. That has no scientific value, whereas a protocol document for a clinical trial has significant value, you don't want to look through manually a billion documents to separate those, so you have to apply the technology even in that first step of classification, and then there's a number of steps that ultimately lead you to understanding the relationship of the knowledge that's in the documents. >> Side question on that, so you had discussed okay, if it's a menu, get rid of it but there's certain restrictions where you got to keep data for decades. It struck me, what about work in process? Especially in the pharmaceutical industry. I mean, post Federal Rules of Civil Procedure was everybody looking for a smoking gun. So, how are organizations dealing with what to keep and what to get rid of? >> Yeah, and I think certainly the thinking has been to remove the excess and it's to your point, how do you draw the line as to what is excess, right, so you don't want to just keep every document because then if an organization is involved in any type of litigation and there's disclosure requirements, you don't want to have to have thousands of documents. At the same time, there are requirements and so it's like a lot of things. It's figuring out how do you abide by the requirements, but that is not an easy thing to do, and it really is another driver, certainly document retention has been a big thing over a number of years but I think people have not applied advanced analytics to the level that they can to really help support that. >> Another Einstein bro-mahd, you know. Keep everything you must but no more. So, you put forth a proposal where you basically had this sort of three approaches, well, combined three approaches. The crawlers to go, the spiders to go out and do the discovery and I presume that's where the classification is done? >> That's really the identification of all of the source information >> Okay, so find out what you got, okay. >> so that's kind of the start. Find out what you have. >> Step two is the data repository. Putting that in, I thought it was when I heard you I said okay it must be a logical data repository, but you said you basically told the CIO we're copying all the data and putting it into essentially one place. >> A physical location, yes. >> Okay, and then so I got another question about that and then use bots in the pipeline to move the data and then you sort of drew the diagram of the back end to all the databases. Unstructured, structured, and then all the fun stuff up front, visualization. >> Which people love to focus on the fun stuff, right? Especially, you can't tell how many articles are on you got to apply deep learning and machine learning and that's where the answers are, we have to have the data and that's the piece that people are missing. >> So, my question there is you had this tactical mindset, it seems like you picked a good workload, the clinical trials and you had at least conceptually a good chance of success. Is that a fair statement? >> Well, the clinical trials was one aspect. Again, we tackled the entire data landscape. So it was all of the data across all of R&D. It wasn't limited to just, that's that top down and bottom up, so the bottom up is tackle everything in the landscape. The top down is what's important to the organization for decision making. >> So, that's actually the entire R&D application portfolio. >> Both internal and external. >> So my follow up question there is so that largely was kind of an inside the four walls of GSK, workload or not necessarily. My question was what about, you hear about these emerging Edge applications, and that's got to be a nightmare for what you described. In other words, putting all the data into one physical place, so it must be like a snake swallowing a basketball. Thoughts on that? >> I think some of it really does depend on you're always going to have these, IOT is another example where it's a large amount of streaming information, and so I'm not proposing that all data in every format in every location needs to be centralized and homogenized, I think you have to add some intelligence on top of that but certainly from an edge perspective or an IOT perspective or sensors. The data that you want to then make decisions around, so you're probably going to have a filter level that will impact those things coming in, then you filter it down to where you're going to really want to make decisions on that and then that comes together with the other-- >> So it's a prioritization exercise, and that presumably can be automated. >> Right, but I think we always have these cases where we can say well what about this case, and you know I guess what I'm saying is I've not seen organizations tackle their own data landscape challenges and really do it in an aggressive way to get value out of the data that's within their four walls. It's always like I mentioned in the keynote. It's always let's do a very small proof of concept, let's take a very narrow chunk. And what ultimately ends up happening is that becomes the only solution they build and then they go to another area and they build another solution and that's why we end up with 15 or 25-- (all talk over each other) >> The conventional wisdom is you start small. >> And fail. >> And you go on from there, you fail and that's now how you get big things done. >> Well that's not how you support analytic algorithms like machine learning and deep learning. You can't feed those just fragmented data of one aspect of your business and expect it to learn intelligent things to then make recommendations, you've got to have a much broader perspective. >> I want to ask you about one statistic you shared. You found 26 thousand relational database schemas for capturing experimental data and you standardized those into one. How? >> Yeah, I mean we took advantage of the Tamr technology that Michael Stonebraker created here at MIT a number of years ago which is really, again, it's applying advanced analytics to the data and using the content of the data and the characteristics of the data to go from dispersed schemas into a unified schema. So if you look across 26 thousand schemas using machine learning, you then can understand what's the consolidated view that gives you one perspective across all of those different schemas, 'cause ultimately when you give people flexibility they love to take advantage of it but it doesn't mean that they're actually doing things in an extremely different way, 'cause ultimately they're capturing the same kind of data. They're just calling things different names and they might be using different formats but in that particular case we use Tamr very heavily, and that again is back to my example of using advanced analytics on the data to make it available to do the fun stuff. The visualization and the advanced analytics. >> So Mark, the last question is you well know that the CDO role emerged in these highly regulated industries and I guess in the case of pharma quasi-regulated industries but now it seems to be permeating all industries. We have Goka-lan from McDonald's and virtually every industry is at least thinking about this role or has some kind of de facto CDO, so if you were slotted in to a CDO role, let's make it generic. I know it depends on the industry but where do you start as a CDO for an organization large company that doesn't have a CDO. Even a mid-sized organization, where do you start? >> Yeah, I mean my approach is that a true CDO is maximizing the strategic value of data within the organization. It isn't a regulatory requirement. I know a lot of the banks started there 'cause they needed someone to be responsible for data quality and data privacy but for me the most critical thing is understanding the strategic objectives of the organization and how will data be used differently in the future to drive decisions and actions and the effectiveness of the business. In some cases, there was a lot of discussion around monetizing the value of data. People immediately took that to can we sell our data and make money as a different revenue stream, I'm not a proponent of that. It's internally monetizing your data. How do you triple the size of the business by using data as a strategic advantage and how do you change the executives so what is good enough today is not good enough tomorrow because they are really focused on using data as their decision making tool, and that to me is the difference that a CDO needs to make is really using data to drive those strategic decision points. >> And that nuance you mentioned I think is really important. Inderpal Bhandari, who is the Chief Data Officer of IBM often says how can you monetize the data and you're right, I don't think he means selling data, it's how does data contribute, if I could rephrase what you said, contribute to the value of the organization, that can be cutting costs, that can be driving new revenue streams, that could be saving lives if you're a hospital, improving productivity. >> Yeah, and I think what I've shared typically shared with executives when I've been in the CDO role is that they need to change their behavior, right? If a CDO comes in to an organization and a year later, the executives are still making decisions on the same data PowerPoints with spinning logos and they said ooh, we've got to have 'em. If they're still making decisions that way then the CDO has not been successful. The executives have to change what their level of expectation is in order to make a decision. >> Change agents, top down, bottom up, last question. >> Going back to GSK, now that they've completed this massive data consolidation project how are things different for that business? >> Yeah, I mean you look how Barron joined as the President of R&D about a year and a half ago and his primary focus is using data and analytics and machine learning to drive the decision making in the discovery of a new medicine and the environment that has been created is a key component to that strategic initiative and so they are actually completely changing the way they're selecting new targets for new medicines based on data and analytics. >> Mark, thanks so much for coming on theCUBE. >> Thanks for having me. >> Great keynote this morning, you're welcome. All right, keep it right there everybody. We'll be back with our next guest. This is theCUBE, Dave Vellante with Paul Gillin. Be right back from MIT. 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