(upbeat music) >> Hey everyone, welcome to theCUBE's special program series Women of the Cloud, brought to you by AWS. I'm your host, Lisa Martin. Very pleased to welcome Angie Perez Thomas the area sales leader from AWS as my next guest. Angie, welcome to theCUBE. It's great to have you here. >> I'm super excited. Thank you so much, Lisa. >> Of course. Talk to me a little bit about you a little bit about your role in sales at AWS. >> Yeah, absolutely. So I'm a tenure Amazonian so I've been with AWS for about 10 years here. And as you mentioned, I'm the area sales leader and so my team supports new enterprise customers and executives who are just starting their journey into the cloud. >> Talk a little bit about some of your career paths. Did you have a linear path? You said tenure Amazonian, linear path maybe more Zig-zaggy. I'd love to get some of your recommendations for those who may be early in their tech careers looking to grow their careers. What are some of the experiences that you've had that you think are have shaped your career? >> Yeah, absolutely. So, you know, mine have, I've gone back and forth through different roles, both in leadership and as an IC and I'd probably say I've got three recommendations for those looking to grow their career in technology. So the first one is prioritize your time to actually think about what career experiences you want in in your fullness of your career. And so this actually may look like sitting down reserving time to actually deep think about what are those experiences you're looking to gain but also doing research on other careers of those who may inspire you and kind of collecting those ideas. My second recommendation is around documenting, writing down those career aspirations and actually putting it within and memorializing it within a document. So I've applied Amazon's working backwards methodology myself and applied that on my career and writing my own career press release. And so it's dated in 2029. It's got a headline and you know, it's a physical document of my own career aspirations. And third, I recommend sharing this documentation with others. You know, I really enjoy receiving and reading what others are wanting to do with their career aspirations and helping provide feedback and guidance. And so what we find is people genuinely want to help others. >> I agree. I love your recommendations for really being mindful, being thoughtful about what it is that you want to do doing that research, and then actually documenting it. I think it's so wonderful that you're taking Amazon's working backward approach from the press release going this is where I want to be in five years or in 10 years. And then putting that on paper. I still connect a lot with things like you that you put down on paper that you want to accomplish or something about writing it down that actually helps to you bring it to fruition. And then to your point is great about sharing it with others that can be mentors, that can be sponsors. I'm sure you've had some great mentors and sponsors along your career path that have probably helped you pretty successful. >> Yeah, absolutely. It's been really an effective tool for communicating with those who have helped me navigate as well. >> Talk a little bit about some of the successes now we'll switch gears but we'll continue on the success train. Some of the successes that you've had helping organizations really navigate, migrate to the cloud and and become successful businesses as a result. >> Yeah, no, absolutely. So across my tenure at AWS, you know I've truly enjoyed working with our customer executives and helping them deliver on their business outcomes. And so just recently I met with the COO of a real estate firm here in the Pacific Northwest and the COO has an initiative to identify and modify home titles and deeds with decades old discriminatory language and restrictions. So, although not invisible, due to the Fair Housing Act of 1968, racial covenants they're still present in millions of home titles across the United States today. And so partnering with AWS and using our cloud technology, you know, our teams together were able to build an application that was able to where homeowners are able to look up their titles you know, analyze it for discriminatory language and be able to submit it for modification. And so this, you know, today it can be done manually, but partnering with AWS, our teams were able to address modifying titles and deeds at scale. And so it's truly incredible what cloud computing has enabled just all of us to accomplish together. And so I kind of think of it like this our a catalyst for change is our customers and AWS and our partners is the how to accelerate that change. So it's really this partnership >> I love that accelerating change is so important across so many aspects of life, but the example that you gave is so, it's such an interesting use case. I wouldn't think that there is discriminatory language in deeds for houses, but the fact that it's probably a pervasive problem globally and the ability to help organizations to be able to change that for the better with cloud, with automation at scale is huge. I can imagine that's a use case that can be replicated surely across the states and more. >> Yeah, it's definitely gained interest across with different real estate forms across the United States. So we're really excited to be partnering and having impact on this change. >> And it's also an example of tech for good. I mean, we talk about that all the time but the fact that there's discriminatory language and housing deeds is still kind of blows my mind. But and we've seen so much in tech in terms of diversity and equity and inclusion but from a diversity perspective there's still a lot more to do. I'd love to get your opinion on what you think some of the the present day challenges are with respect to diversity in tech and maybe some of the things you think can be changed to for the better. >> Yeah, so you know, there's been a huge focus on, you know hiring for diverse talent in the tech industry for a number of years. And where I think we as an industry have an opportunity is to improve in investing and developing in this diverse talent and try to really think about how are we building up the skillsets to build today's and tomorrow's leaders. And so when I think about this it requires senior leaders to be really intentional about building a diverse ecosystem of talent and investing in this diverse talent. And let me clarify a little bit when I talk about investing in diverse talent, you know, this expands outside of just mentoring. This includes sponsoring, coaching, really providing opportunities where this talent has the ability to have a seat at the table. Getting into the room where it all happens. And so by doing so we're helping this talent build their skillsets to learn what questions are being asked within, the room? How are others communicating with each other? So that they can build the skillset so not only have a seat at the table but can be really leading with that seat at the table. And I would say last, we as companies we tend to or you know, we in the industry, we tend to just focus on developing those within our companies. And where I see a need is to really challenge the industry to reach outside of our own companies in diverse talent. And so developing just that ecosystem because not just thinking about the roles that are open today but really building the skillsets for the roles and and senior level positions that are going to be open tomorrow and making sure we're developing this talent to raise their hand and be the leading candidate for those opportunities. >> I love how you said kind of really a couple things that you know, with all the women in this program that I've spoken to is a common theme in terms of diversity and it's really about senior leaders making investments. And another thing that you said that's spot on is doing it with intention. There's so much to be gained by having an intention with diversity, thought diversity. To your point, going outside, it sounds to me like kind of let's go outside of our comfort zones to bring in different thoughts, different perspectives be able to grow them in their career because of course technologies and products and solutions can only get better the more diversity of thought we have. >> Yeah, no, absolutely. It's really being intentional. We as senior leaders, we have a law on our plate. And so yes this is an additional thing to be thinking about but it really has impact and change in driving the right things both for our customers and for the industry as well. And so it's an investment that's worth making. >> And speaking of that investment worth making I liked how you said, let's have some forethought about what are some of the roles that are going to be there in the future. How are some of the roles today going to be evolving? How do you see your role evolving in the next few years? How do you see cloud evolving and what excites you about that? >> Yeah, well, cloud has really been helping our customers move faster and adapt to just the ever changing landscape. I mean it's over the last couple years it's been very real for all of us to see. And so my role has moved from just being an advisor to a CIO to actually being an advisor to both the CEO and board of directors and when they come speak to us, cost or cloud is not just about cost savings, it truly is about helping a CEO deliver on their business outcomes. So I'll give an example. We're working with a growing community bank and their executive team has embarked on a transformation to becoming a digital first bank. And so when we think about the economic factors that they're working with them to come to mind. The first, their move towards online banking has it's accelerated with the pandemic really creating that customer experience of which when you think about local banks, you think about community where everybody knows your name over in the brick and mortar down the road. Well they have to bridge that community and trust into the digital world. And second, they needed to improve on operational efficiencies. And so they have to strategically think about what investments they're going to make to balance inflation while driving growth. And so where I've been finding both myself and my teams is having a seat at the table with these executives, helping them make these strategic business decisions. And we know we're successful when our customers are able to deliver on those business outcomes. They meet those objectives, they exceed those objectives. And then we know we've just exceeded customer expectation when our partnership actually shows up in their next earnings call. You know, it's really special. >> Oh, I bet it is. I mean, being able to be that influential in terms of an organization's success I love how you talked about kind of a career evolution that your career has evolved from now you're really with the board of directors having a seat at the table there. My last question for you is kind of on that front Angie is what are some of the changes in in the tech workforce that you've seen the last few years and what are some of the things that you're excited about that are down the road? >> Yeah, so a couple things where I've really seen change and evolution has been in the leadership level. We are needing to lead with empathy and really think about inclusion as a cornerstone skillset. So for our customers, our partners, our employees we've really moved into this hybrid environment. We're both leaders and team norms. We're challenged to change. We have to adapt. And so really having inclusion as that foundational skillset is a requirement for both today and tomorrow's leaders. What I'm really excited about is on the innovation front. Anyone can innovate now, you don't need to be a part of the R&D division of a company. We're seeing that cloud is providing tools all the way down to the elementary student level. So when you think about that, just think the imagination of our youth, brought to life with cloud technology. I mean, the future really is bright. >> It is. That horizon is endless. And I'm going to take some of your advice, Angie I loved that you talked about from your own perspective and your recommendations for the audience. Write that down, write your own press release in terms of what you want to see down the road. I'm going to take your advice, I'm going to do that. I thank you so much for joining me on the program. You've been so inspiring. Your career path has been impressive. What you're seeing in terms of innovation and cloud coming next is incredibly exciting. Thank you so much for your time, Angie. >> Thank you Lisa. >> For Angie Perez Thomas. I'm Lisa Martin. You're watching theCUBE's special program series Women of the Cloud, brought to you by AWS. We'll see you soon. (upbeat music)

(upbeat music) >> Narrator: Live from Copenhagen, Denmark, it's theCUBE covering Nutanix.NEXT 2019. Brought to you by, Nutanix. >> Welcome back everyone to the cube's live coverage of Nutanix.NEXT here at the Bella Center in Copenhagen. I'm your host Rebecca Knight, alongside of my co-host Stu Miniman, Analyst. We have two guests for this segment. We have Angie Cusworth, she is the COO of Hardy Fisher Services. >> Hi. >> Thank you so much for coming on Angie. >> Hi. >> And we have David Cusworth SVP sales at Hardy Fisher Services. Thank you so much! >> Thank you. >> And husband and wife. >> And a husband and wife team! >> I believe we have done it before, I know we've had twins on the program. >> Right, yes. >> Uh, but uh, yeah. >> Couples who work, I like it! We'll get into how you make it all work. But David, I want to start with you. Describe Hardy Fisher Services for our viewers who may be unfamiliar with your company. >> Yeah, so we own and operate a large data center based in Leeds, so it's a 400 watt capacity data center previously built for BT house NHS patient records in the UK. And we operate that as a reseller base data center, so we are a very clear go-to market. We have our co-location, we have money services and then obviously cloud which is based on Nutanix. >> So, wait Angie what are the biggest business challenges that you face in your world. >> So I think it's trying to convince customers to move to the cloud. Obviously, you know, we've been doing cloud for some time now. I don't know how to-- >> Yeah, so David, we're talking about that move to cloud. It help it put where, you know, your services built both now Nutanix fit in the customers overall picture. Cause you know, you've SAS, you've got public cloud people are building private clouds off Nutanix or other type of hardware, so you know how do you play with some of those other components and position yourself? >> I think a lot of the challenges that we've seen is people are comfortable with Azure so a lot of resellers that we deal with. Azure is a safe bet. Nutanix is still quite a new name in the marketplace. There's people who don't want to move to the cloud because they don't understand it. So, a lot of the time, we show them the cloud platform in our data centers, and can touch and feel it they can actually see it. Which gives them a bit more confidence. And then, from our side it's the service wrap, so it's holding them the hands on the journey to the cloud. So it's given our technical ability to say, you know, we'll do it for you, we'll hold your hands, we'll get you working. And at the end of the day, the cloud is people's businesses. So if the cloud doesn't work, it affects their business and we're trying to put our hats on as a customer. >> Yeah, it's funny. It reminds me, we used to have the joke, there is no cloud, there is just you know, your computer somewhere else. Angie, bring us inside, a little bit? Your customers, it sounds like they're still a little bit of trepidation about them making changes there? >> Yeah, I think one of the reasons that we've been so successful, is that we follow IT Service Management very well. So we help our customers through the whole journey. So people that are new to cloud, we have excellent technical people, that can help them. We have a fantastic data center, as well. So, they know their kits are safe with us. >> Yeah, bring us inside a little bit. You talked about how many racks there. What differentiates your data center? There's you know, most companies, you know, we tell the average enterprise out there, you know. Friends don't let friends build data centers. There's other people that know what they're doing. So, give us a little bit of a virtual tour, if you would. >> Yeah, so our data center. Like I said, It was originally built for BT and for the NHS. And as they moved to cloud, the need for their data center shrunk. Leeds as a city is growing city and there's not many data centers in Leeds, so we took the opportunity to really re-launch the data center. We knew it was a very high spec data center, cause it cost a lot of money to build. And it gives the customers confidence that when they are going in there, it's very secure. It's very high resilience. And from a cloud platform, we've gone completely Nutanix. So it is literally, you can come in, you can touch Nutanix, you can play with it. And it's just the whole journey really, that to make sure they're in a safe pair of hands. >> Talk a little bit more about how Nutanix comes into play with your organization. >> We went with Nutanix because we're looking for something to be different. There's a lot of people who've got this UA to be WES in that V seller market. So we wanted something that was focused on SME. So we've got very, very much SME focus. And cost comes into it. Having that support, so being able to ring somebody up and not being in a big call center in Asia or in Europe. Somebody who can actually talk them through, what the issues are, also be very responsive, and put the customer first. >> Yeah, it's interesting, and when I think about kind of the traditional service provider. It's like they've build out their management stack, they build something at a scale, so that, you know, they can do something that their customer couldn't. It sounds like Nutanix is a different type of offering. We've been talking about it all week. It's not thriving in that complexity, but you know you just have a simple offering. And then, of course, you know price and easy to manage. Is something that service providers need, so, It sounds as if you built this ten years ago, you might have had to do something very different then how you do it today. >> Yeah, no, absolutely. It's given us a market that really hasn't been there in the past. You know, we can help resellers on the journey, we can give them a bit of a lift up, so. If their too small or they've just got going in cloud and they can't afford to get their own Nutanix platform, then we can get them going and then they can start going into Nutanix. But it's a real differentiate. It's like I say, to a lot of people, it's the safe bet it's your AWS. It's you know a Microsoft name. No one ever gets sacked for by Microsoft kind of conversation. >> I think one of the other compelling things is the cost of it as well. A lot of people think it's cheaper to go as your AWS. Actually it's mechanics are very cost effective for our customers and that's why it appeals for, you know the kind of smaller resellers that we deal with. >> You know, are you starting to do any connection now that you think about as your AWS have their direct connect. When you have people's environment, sometimes they might want to access those services or are you starting to look that, in that environment? Where some of the Nutanix hybrid solutions? >> Yeah, so what we do at the moment is we backup mainly to Azure. So we've, we've a central core platform with Nutanix and then, we're back up as a failover to Azure. But, again, customers don't like the complexity of even doing that as a back up. So it's been great coming to the event and seeing the Nutanix backup and the options there because our customers love Nutanix. >> So are you interested in the mine solution, that has been rolling out? >> Yes, absolutely. >> Yeah, yeah absolutely. That's one of the things that we're really looking forward to going back to explore. And that will be next on our road map. >> Are you starting to look out as to which solution with mine you're going to use or are you still under discussion? >> Yeah, we'll leave that to our technical director. I'm sure he'll point us in the right direction. >> One of the things we hear a lot about at this conference is Nutanix's culture. It's people first culture. It's humble, honest, hungry. How does that come into play in terms of your interactions with the company? >> I think for us, that's a culture that we have as well in our own business. And that really does shine through for every person that we've ever dealt with at Nutanix. There it's always customer first. I can't fault them, they're amazing. >> I think for us, it doesn't feel like you're a big company because it's such of a personal relationship. So it doesn't feel like you're talking to a big corporate company where you're not heard, you know, if you're not a a big customer. The relationships we've got with people work and just pick up the phone it might be a really senior position and they'll help us, and that's something that's really good in Nutanix. >> I'm wondering if you've had any experience with Nutanix support, so we know uptime is, is super critical. So what is your experience? >> Yeah, fantastic. I mean, from an operational perspective, I love the self healing, that's built into the platform. Anyway, I love the fact that my technical guys don't have to be uber technical to be able to operate. That's one of the other benefits in Nutanix for us. It ticks all the boxes from an operational perspective. >> I think from our side as well, the technical guys, so, our first and second line guys can understand Nutanix. They can get their head around it, so it's very easy to train and more with Nutanix as opposed to other platforms where it can take up to a year to really understand how the platform works. It is very, very simple for our support desk. Which means, it is less demand on the support that's got Angie then. >> Training in the skills gap is a hugely important issue in the technology world. It's in the United States and also in Europe. How are you finding it, what is it like to be a Leeds based company, are you finding the people you need to fill the roles you have open? >> We're really lucky actually, because our technical director is an ex-trainer, so we can do a lot of the training on site. But Nutanix training is something that we're definitely going to be tapping into. I've been speaking to the guys here, and that's another useful thing for us to take back to the UK. >> Give our audience a little bit of insight, so you know, what you get out of coming out to the Nutanix conference, you came last year to London, you came out here to Copenhagen. What were you hoping to accomplish? What are the conversations been, give us a little bit of a flavor. >> I think it's been good to network with other Nutanix customers to understand their journey. Definitely to learn about what Nutanix is doing now and in the future. When you're running a business it's kind of head down sometimes. Allowance, you know, you don't get time to really sit and look up what the market is doing. So for us, it's also to be part of our journey, you know, we went to event four or five years ago when it was much smaller, much newer name. And to see how fast Nutanix has gone is amazing. It really is. >> Absolutely, I think it's given us clarity on what we need to do next year. Like I say, you've helped us by coming here today and yesterday, seeing the presentations on how we can implement that into our own business. And how we can really take Nutanix forward. >> In terms of the future, you said you are going to, you're looking into Mine. You're thinking about using some of the Nutanix training, capabilities. >> Frames, Beam. >> So, there's a lot there. >> So yeah, we've really honestly taken so much back and I can't wait now. I think for me personally, it's re-energized me. I'm excited about going back and just working out where we can really take Nutanix forward. >> And what's next for Hardy Fisher? >> It's just growth, we're at an early journey now. So we're kind of at the start of our journey, over the next five years, it's all about growth. We see Leeds as a bit a city that's growing itself. We've had a lot of changes in Leeds as a city. It's still quite small. It's a digital city, but it's got massive focus on growing. We're having a big part of that because we're one of three data centers in Leeds. So, it's not a heavily populated area for data centers. And we're all about helping local resellers, you know, get on that ladder for Nutanix. >> So that will be a big driver for us, you know help the small MSPs. You know, let them touch and feel Nutanix in our data center. And then hopefully give them the leg up for them to buy their own boxes, and then co-locate that in the data centers as well. >> So, as as as devoted Nutanix customers, any advice for Dirige Pandey? He's got, he's under a lot pressure. It's a competitive landscape. You love Nutanix. >> Angie: He's nailed it. >> David: I think, just keep doing what they're doing. >> Rebecca: Stick to your knitting. >> Don't get sold to one of the bigger boys and keep the-- >> Yeah, absolutely, keep the culture. And the, everything that you're doing technically wise it's just unreal. We're blown away. >> I think the culture as well, keep it to grow as big as you are now, keep that culture which has been very hard. I mean, we try doing it in our businesses. You know we have a very hardworking ethic. But we want people to enjoy where they work. We want to have a good work flow, life balance. And it's very difficult to do in a big company. >> Is it, do you like working with each other, in your husband and wife team? >> Yeah, it has it's challenges. (laughing) It has it's challenges but we've worked together for 12 years now, so. >> It's gotten better at work. >> All right. >> It's very hard because, I sell it and I support it, so unless I sell it properly I get in trouble. (laughing) >> Dog house. >> I have to reign him in. >> Exactly, well David an Angie, thank you so much. It has been an absolute pleasure having you on the show. >> Thank you very much for having us. Thank you. >> I'm Rebecca Knight for Stu Miniman. We'll have more for Nutanix.NEXT in Copenhagen coming up in just a little bit.

>> Narrator: From Seattle, Washington it's the CUBE covering AWS Imagine non-profit. Brought to you by Amazon web services. >> Hey welcome back everybody, Jeff Frick here with the CUBE. We're on the waterfront in Seattle, it's an absolutely gorgeous couple of days here at the AWS Imagine Nonprofit Conference. We went to the AWS Imagine Education Conference, this is really all about nonprofits and we're hearing all kinds of interesting stories about how these people are using AWS to help conquer really big problems. We're going to shift gears a little bit from the two footed problems to the four footed problems and that's animals and everybody likes animals but nobody likes animal shelters and nobody likes the ultimate solution that many animal shelters used to use to take care of problems. But thank you to our next guest, that is not quite the case so much anymore. So we're really happy to have Angie Embree on. She is the CIO of Best Friends Animal Society, Angie great to see you. >> It's great to see you as well and thank you for having me. >> Oh absolutely! So before we got on I just heard this crazy, crazy statistic that when your organization started in 1984 approximately 17 million animals were killed in US shelters per year. That number is now down to 700 thousand, that is a giant, giant reduction. And yet you, with big audacious goals really are looking to get that to zero. So, that's a giant goal, give us a little bit of background on the organization and how you decided to go after a goal like that and some of the ways you are actually going to achieve it. >> Well, the organization started in 1984 and it started with a group of friends in Southern Utah who decided that, you know the killing in America's shelters just had to go. So really the Best Friends founders started the no-kill movement along with a gentleman in San Francisco by the name of Rich Avanzino. And as you said, they took you know the killing down from 17 million in 1984 to approximately 733 thousand now. The organization started as just the sanctuary, we have the largest no-kill companion animal sanctuary in the country where we hold about 17 hundred animals every day. And we also have, you know, knowing that we needed to help out the rest of the country we have built life saving centers in Houston, Texas. Or we're working on Houston, Texas but Los Angels, California, New York City, Salt Lake City, Atlanta, Georgia, it seems like I've left somebody out but, >> Probably, but that's okay. >> We have life saving centers all over the country. So it was really, you know, when they realized what was going on in America's shelters it was really the idea that we should not be killing animals for space. So, just recently in fact, I will say recently but in the last few years, Julie Castle our CEO put kind of, did our moon shot, put that stake in the ground and said we're going to take this country no-kill by the year 2025. >> Right. >> So it's super exciting. >> So it's really interesting because you guys are trying to execute your vision, and it's easy to execute your own vision, but it's a whole different thing when you're trying to execute your vision through this huge infrastructure of shelters that have been around forever. So, I wonder if you can explain kind of what's your relationship with shelters that you don't own. I guess, I think you said before we turned on the cameras there are affiliates, so how does that relationship work? How do you help them achieve your goal which is no-kill. >> Yeah, so we have over 27 hundred network partners around the country. And what we do is we help to educate them on, you know we understand their problems, we have creative programs to solve those problems. So we help to educate them on, you know, how they can implement these programs within their shelters. We provide them grant funding, we have an annual conference every year where they can come and learn. But they're really our partners and you know we know we can't do it alone. It's going to take us, it's going to take them and it's going to take everybody in every community to really step up and help solve the problem. >> Right, and what was the biggest thing that changed in terms of kind of attitude in terms of the way they operate the shelter because I think you said before that a lot of the killing was done to make room. >> Right, killing is done usually for space. >> So what do they do know? Clearly the space demands probably haven't changed so what are they doing alternatively where before they would put the animal down? >> Well alternatively we're doing transport programs. So there are areas in the country that actually have a demand for animals. So instead of killing the animals, we put them on some sort of transport vehicle and we take them to the areas that are in demand. We also do what's called a trap-neuter-return program. So one of the biggest problems across the country are community cats so those, a lot of people call them feral cats but they're community cats and usually have a caretaker. But what we do is we trap those cats, we take them into the shelter, we neuter them and vaccinate them and then return them to their home. That keeps them from making a lot of other little cats. >> Making babies (laughs) >> So yeah, cat's are one of the biggest problems in shelters today because of the community cats, they're feral cats and they're not adoptable. So if we can, we don't have to kill them. We can, you know, we can keep them from reproducing as I said and then we can put them back in their habitat where they live a long healthy life, happy life. >> Right, so you said you've joined the organization 5 years ago, 5 and 1/2 years ago and you're the CIO, first ever CIO. >> I am (laughs) >> What brought you here and then now that you're here with kind of a CIO hat, what are some of the new perspective that you can bring to the organization that didn't necessarily, that they had had before from kind of a technical perspective? >> Well, what brought me here was, I never expected to be here, if you would have told me I would be the CIO at Best Friends Animal Society you know 10 years ago I would have said you're kidding because I didn't really realize that there were professional positions in organizations like Best Friends. But I, you know, my journey begins the same as, began the same as a lot of peoples did. I was that little kid always bringing home animals and you know my mother hated it. You know it was always something showing up at our doorstep with me, you know. And I just loved animals all my life and as I went through college and got my degree and started my professional career, then I thought well I'm going to of course have animals because I can have as many as I want now, right! (laughs) So I started adopting, and I didn't even realize until I was in my 30s that they were killing in shelters and I learned that in Houston, Texas when I lived there. I was working for IBM at the time, and one day a lady came on the television and she said they were doing a new segment and she said we're a no-kill shelter and I thought oh my god if there are no-kill shelters then there are kill shelters, right? >> There must be the other. >> Yeah so, to make a long story short then I started not working in animal welfare but doing more to support the movement and donating. Adopting from shelters and fostering animals and then one day I had been to Best Friends as a visitor vacationing in this beautiful part of Utah. But I saw the CIO ... >> Position. >> position open and I said I'm going for it. >> Good for you. >> Yeah. >> Good for you, so now you're there so what are some of the things you've implemented from kind of a techy, you know kind of data perspective that they didn't have before? >> Well, they didn't have a lot. >> They probably didn't have a lot, besides email and the obvious things. >> Being the first CIO I don't know that I knew what I was walking into at the time because I got to Kanab, and Kanab Utah where the sanctuary is, is the headquarters. And Kanab is very infrastructure challenged. >> (laughs) Infrastructure challenged, I like that. >> There is one ISP in Kanab and there is no redundancy in networks so we really don't have, you know, you come from the city and you think, you take these things for granted and you find out oh my god, what am I going to do? And Kanab is you know the hub of our network, so if Kanab goes down, you know the whole organization is down so one of the first decisions I made was that we were going to the cloud. >> Right, right. >> Because we had to get Kanab out of that position and that was one of our, one of the first major decisions I made and we chose AWS as our partner to do that so that was very very exciting. We knew that they had infrastructure we couldn't dream of providing. >> Right, right. >> And, you know we could really make our whole network more robust, our applications would be available and we could really do some great things. >> You're not worried about the one ISP provider in Kanab because of an accident that knocks a phone pole down. >> Yeah, yeah. >> All right but then you're talking about some new things that you're working on and a new thing you talked about before we turned the cameras on community lifesaving dashboards, what is that all about? >> Okay, so a couple of years ago the community lifesaving dashboard is the culmination of two years of work. From all across the Best Friends organization not just the IT department, in fact it was the brainchild of our Chief Mission Officer Holly Sizemore. But it's really, in animal welfare there's never been a national picture of what the problem really is regarding killing animals in shelters. So we did this big. >> Because they're all regional right? They're all regional shelters, very local. >> They're all local community shelters, yes. And transparency isn't forced, so you know some states force transparency, they reinforce in the report numbers but a lot of states don't. >> At the state level. >> Yeah, a lot of states don't, so. You know when you're killing animals in shelters you really don't want people to know that. >> Yeah, yeah it's not something you want to advertise. >> Because the American public doesn't believe in it. So anyway we worked really hard to collect all this data from across the country and we put it all into this dashboard and it is now a tool where anybody in the public, it's on our website, can look at it and they can see that where we're at from a national level. They can see where they're at from a state level, they can drill down into their community and they can drill down to an individual shelter. >> Wow. >> And the idea behind the dashboard is to really, is to get communities behind helping their shelters. Because as I said earlier, it's going to take us all. >> Right. >> And not only Best Friends and our partners but the public plays a big part of this. >> Right, and so when did that roll out? Do you have any kind of feedback, how's it working? >> It's working wonderfully, we rolled it out at our conference in July. >> So recently, so it's a pretty new initiative. >> Yeah it's just a few weeks old. >> Okay. >> We rolled it out at our national conference and we were all a bit nervous about it, you know especially from a technology perspective. >> Right, right. >> We knew that being the first of it's kind ever in animal welfare that you know it was going to get a lot of publicity both inside and outside the movement. >> (laughs) How you want to say both pro and con. >> Yeah, and it's sitting on our website, well really pro and con. >> Right, right. >> But it's sitting on our website and we're like okay, we don't know what kind of traffic we're going to get, you know what are we going to do about this? So we spent a lot of time with Amazon prior to the launch, you know having them look at our environment and getting advice, discussing it with them. >> Not going to bring down that ISP in Utah. >> No, thank god! (laughs) >> (laughs) >> No it wasn't, thank god we were in the cloud. So Amazon really helped us prepare and then the day of the launch, we knew the time of the launch. So we actually had a war room set up, a virtual war room and we had Amazon employees participating in our war room. We watched the traffic and we did get huge spikes in traffic at all times through the day when certain things were happening. And I'm happy to say from a technology perspective it was a non-event because we did not crash we stayed up, we handled all the traffic, we scaled when we needed to, and we did it you know, virtually at the press of a button. >> Awesome. >> Or the flick of a switch, whatever you want to say. >> That's what you want right? >> Yeah, exactly. >> You just don't want anyone to know, I was like give a good ref, nobody's talking about you you probably did a good job. >> Yeah, exactly yeah. >> Good, so before I let you go so what are some of your initiatives now looking forward. You've got this great partner in AWS, you have basically as much horsepower as you need to get done what you need to get done. What are some of the things that you see, you know kind of next for your roadmap? >> Well, we have a lot. >> Don't give me the whole list (laughs) >> No I'm just going to hit on a few key points. I think, you know we used Amazon initially as our cloud infrastructure but I think the biggest thing we're looking at is platform as a service. There is so much capability out there with predictive analytics, machine learning, artificial intelligence, ARVR, you name it facial recognitions, so we're really investigating those technologies because we think they have you know they could have a huge impact on our movement and really help us achieve life saving. >> Right, right. >> And, I think that, you know we're starting we have our fledgling data science program. We're using the Amazon data lake technology, Athena, Glue, they were just telling me about data lake formation which I just a few minutes ago emailed my data guy and said start looking at data lake formation. >> Right, right. >> So, I mean we're really investing in the platform as a service. The other thing I see is that we're, animal welfare is sort of broken from a technology perspective and a data perspective. In that we have no interoperability and you know we don't have the data available. So lets say you want to adopt a 5-year old animal. Well, you go to a shelter you can't get 5 years of history on a 5 year old animal. So it's really starting to fix the foundation for the movement as a whole, not just Best Friends. So, making sure that you know the veterinary data is there, all the data from the pet ecosystem is there. So we're investigating with AWS they're actually coming to our sanctuary in a couple of months, we're going to do a workshop to figure out how we do this, how we really fix it so that we have interoperability between every shelter when an animal moves from shelter to rescue or whatever so that their data follows them wherever they go. So adopters are fully informed when adopting an animal. >> Because you're in a pretty interesting position, because you're not with any one particular shelter you kind of cross many many boundaries. So you're in a good position to be that aggregator of that data. >> Yeah, I don't know that we want to be the aggregator but we want to lead the movement towards doing that. Just getting the technology players, the shelter management systems, the other people who play a role in technology for animal welfare, getting them in a room and talking and figuring out this problem is huge. >> Right. >> And with a partner like Amazon we feel it can be solved. >> Right. Well Angie thank you for taking a few minutes and sharing your story, really really enjoyed hearing it. >> All right thank you so much. >> All right, she's Angie, I'm Jeff you're watching the CUBE we're at AWS Imagine in Seattle, thanks for watching we'll see you next time. (upbeat music)

>>mhm mhm. Mhm Welcome back to convert connections 2021. This is the power panel. My name is Dave vellante joined by Reza more like a body was the ceo of calm vault. Isabel geese is the CMO of calm vault and john Gallagher he leads global enterprise infrastructure at sing Creon. And folks welcome to the cube. Thanks for coming on. >>Thank you. >>Thank you. >>So john we heard you this morning. You know, great job you guys are in the industrial logistics business. So supply chains at all a hot topic today. It's got to be challenging. Maybe you could talk about what you're seeing there, but specifically how are you thinking about data management in the context of your overall IT strategy. >>Okay, thank you. So in terms of data management, Synchrotron has 100 sites globally. So if we were to rewind by say 10 years we had data residing a lot out of those remote sites. Uh so over the last few years were basically consolidated a lot of that data and also centralist. So we've brought that into our data centers that we now have, which is a very, very centralist model. So that, that makes it a lot easier to understand where all of that data resides. >>So in the decision pie, as it relates to data, it sounds like cost efficiency is pretty, pretty ranks pretty highly. How does that impact your data management strategy and approach? I mean, is is that like the number one consideration? Is that one of many factors. How should we think about that? >>I would say cost is one of many factors. So obviously cost is key, but you don't want to introduce unnecessary risks. So you've got to keep costs at the forefront. But that's just one of the factors. Obviously data protection is one of the factors ensuring that data is protected and safe. And also understanding, is that exactly where that data resides, making sure that data is encrypted. So I would say that cost is just one of the factors. >>So Isabel good to see you again. I wonder if you could talk about how you're seeing your customers and what they're thinking about, how they're thinking differently about data management today, Are they changing the way they manage data giving given the escalation of ransomware that comprise the called the forced march to digital over the last 18, 19 months, but you've got new threats, new business dynamics, how is that affecting organizations? >>It does, it does affect them a lot. It's um we see a lot more. Actually, I asked a lot of virtual coffee talks with our customers so they can share best practices and a lot of C IOS network ending end with sizzles and they have a readiness plan because they know the question is not if they're going to have an attack, but when and how to recover from it is critical. So all the security team is really looking at the prevention but they know that if they can't stop it all, then they have a plan of end of to the data team for recovery. I see a lot more thoughtfulness because not all data is created equal. So which one is in the cloud and you can recover which one you need fast for minimum business was sorry, minimum business disruption and you keep on prime and which one you cannot lose and you have a go. So we see a lot more planning, a lot more collaboration across all verticals. We have also new services that help customers before the attacks to design and plan and also helping them post attack to recover so very much and to end and as we've seen the king out right now it's all about the people enabling them to do the business while you're risking the business too. So >>All right, thank you for that. So Reza and the fact that your Ceo is C I O. Uh so you must have some interesting conversations there but and you can be a sort of tap Sanjay's brain, how did you handle this kind of thing? And and uh that's a nice collaboration I bet. But what advice can you give to other, see IOS or grappling with cyber threats, data volumes and just the ongoing pressure to do more with less that never changes does it? >>It doesn't. And you're absolutely right. And I obviously as part of my job attracted benchmarks about budgets and everything else that before the pandemic used to track about like 3% growth year over year which is a hard to kind of do a whole lot with them. Um What what I can tell you is not for C I O not two areas the areas of investments are not created equal and from my perspective the biggest areas of investment for somebody like me in my position should be data and protecting the data. So that means that you have to find ways of on the budget side, find ways of shifting money whether you reallocate resources, whether you reform or a really organized differently, automate simplified etcetera. My background is operation so when you talk about people process technology outside of things, I leave the technology to the people that are really good at it and I focus on people and process side and for me that's about again efficiencies and finding ways that you can reorganize, you probably have the people that do the work that you want them to do and you just have to think about reorganizing them differently. And the last thing I said is prioritize prioritize initiatives across the board and it is like partner in crime in these things and we don't always say yes to her and what she wants because we need to be transparent so where we put our money >>so rest, I want to stay with you for me, I want to talk about data sprawl was interesting john during your session this morning I was sort of laying down some of my thoughts because I I feel like data sprawl, it's like social change. You can't fight it. You can maybe, you know for a period of time control it. But data is is out of control. So how do you address data sprawl in an organization? Both from a management perspective there's obviously risk. Somebody said this morning we used to keep, I think it was the C. I. A. In New Jersey. We used to keep everything forever. But that's risky. So how do you deal with that result from an organizational and management perspective? >>Yeah. You again, I'm gonna have to agree with you. As as I said in in a morning session, I like it's a natural phenomenon for a company to go through it. I've seen it in companies that are 150% people and I've seen it in companies that have tens of thousands of people. It's like a foundation onto what what entropy is in thermodynamics. It's the natural order of events. If you don't apply structure, organization data is going to go haywire and everything else. The only way. The best way that I know when the pendulum is here and everybody is doing the wrong thing is to push the pedal on the other side at least for a while to centralize, pick a few of your brightest people that know the data in and out, put them in a team and say you're responsible for making sense out of these things. Identify sources of truth for us and architect them differently. But but start with executive level metrics and board level metrics and push them down. >>So I see. I I agree with that with that. I think the people who have the data context are in the best position to add value as to whether it's data quality and how to get the most out of that data. But the problem is uh john I'd love to pick your brain on this. Especially your urine mia. You got all these different regulations and data silos, which I believe are a byproduct of how we organize. Uh, but but anyway, you have a lot of the considerations to deal with whether it's G. D. P. R. Or or or or data sovereignty etcetera. How do you approach that? >>So one of the first approaches we took when we moved over to con vault with our data protection was to reduce the number of products we used for the data protection. So we had six products through various acquisitions that we, we've done over the last 10-15 years. We've now reduced that six products down to one single product. So it means that all of your data is managed through a sort of single pane, which definitely gives you a much better insight. And also just going back to the costs that you mentioned in the previous question. Obviously going down from six products to one product, we managed to strip around $500,000 out of our costs over three years. We also moved data like I said into the center and allowed us to also concentrate the teams. So also the teams became more efficient because less people were dealing with that data as well. But yes you are right around GDP are there is definitely compliance to be considered and you just have to make sure you're up to date on all of those compliance regulations. >>So it's interesting resident here you talk about you know Isabelle, she's got needs but I would say Isabel that you probably know in your team, you know the marketing data better than anybody but there's got to be Federated governance, you've got to enforce policy in this data sprawl world. So anyway this is sort of a side but Sanjay Isabelle talk today about as a service growing like crazy and given your background I wonder if you can share any insights about how and why you think customers are going to be looking towards SAs I mean the whole world is becoming SAs ified you had some data on that this morning from, from Gardner. What are your thoughts? >>Yeah, no, absolutely, you're right experience this percent coming from cell phones and yes angie mentioned in the keynote by I think 2025 85% of business will be delivered through SAAS apps and that's very simple look at the world today the market dynamics of business changes. You mentioned the supply chain is you were talking you know all the line of business people of the business executives have to change fast. And the fastest way to do that is SAS because it has speed agility and you get the value faster problem being then it becomes very complex or I. T. Because you have workloads in multiple clouds on premise multiple apps and and what convo stands for and what everybody should look at is being able to enable all this innovation but at the same time removing the complexity for I. T. To protect this data to recover it and that's really where you know we're focusing our attention that is unavoidable. It's all about business and gT but it doesn't mean that you should compromise on data management. Yeah. >>Yeah I think you know we gotta we have to wrap here but I think the model, you know again it's about you coming from salesforce, we've contextualized our operational systems. You know, whether it's you know the sales cloud, the logistics, cloud, it's the lines of business actually have a good handle on this. And where I see the role of calm vault is that that notion of Federated governance, you've got to have centralized policy but you've got to programmatically and automate that out to the lines of business and I think that is kind of where the where the future is headed. Uh And I think that's really kind of controlled strategy. I'm hearing a lot on automation cloud like services and pushing that out. Um And so I see a new era in data coming and you guys talked a lot about this but but Isabelle will give you the last word. Put a put a bumper sticker on the on the panel for us. >>Well absolutely. I mean you said it's not left for no workload, sorry, it should be left behind and that's why you know you need a single architecture. I think businesses is changing fast and it's exciting. Uh And as long as you know you got a great I. T. Team with a great plan to have your back as a business leader. Every company should really embrace um all the change and innovation. So thank you day for for giving me the last world >>go. Thank you guys. I really appreciate you coming on the cube has been a fun day. We got more here that convulsed connections, keep it right there. We're gonna come back right after this short break my nose and I are going to wrap up and summarize the day. Yeah

>>from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>And we're back with the data automation. Siri's. In this episode, we're gonna learn more about what I owe Tahoe is doing in the field of adaptive data governance how it can help achieve business outcomes and mitigate data security risks. I'm Lisa Martin, and I'm joined by a J. Bihar on the CEO of Iot Tahoe and Lester Waters, the CEO of Bio Tahoe. Gentlemen, it's great to have you on the program. >>Thank you. Lisa is good to be back. >>Great. Staley's >>likewise very socially distant. Of course as we are. Listen, we're gonna start with you. What's going on? And I am Tahoe. What's name? Well, >>I've been with Iot Tahoe for a little over the year, and one thing I've learned is every customer needs air just a bit different. So we've been working on our next major release of the I O. Tahoe product. But to really try to address these customer concerns because, you know, we wanna we wanna be flexible enough in order to come in and not just profile the date and not just understand data quality and lineage, but also to address the unique needs of each and every customer that we have. And so that required a platform rewrite of our product so that we could, uh, extend the product without building a new version of the product. We wanted to be able to have plausible modules. We also focused a lot on performance. That's very important with the bulk of data that we deal with that we're able to pass through that data in a single pass and do the analytics that are needed, whether it's, uh, lineage, data quality or just identifying the underlying data. And we're incorporating all that we've learned. We're tuning up our machine learning we're analyzing on MAWR dimensions than we've ever done before. We're able to do data quality without doing a Nen initial rejects for, for example, just out of the box. So I think it's all of these things were coming together to form our next version of our product. We're really excited by it, >>So it's exciting a J from the CEO's level. What's going on? >>Wow, I think just building on that. But let's still just mentioned there. It's were growing pretty quickly with our partners. And today, here with Oracle are excited. Thio explain how that shaping up lots of collaboration already with Oracle in government, in insurance, on in banking and we're excited because we get to have an impact. It's real satisfying to see how we're able. Thio. Help businesses transform, Redefine what's possible with their data on bond. Having I recall there is a partner, uh, to lean in with is definitely helping. >>Excellent. We're gonna dig into that a little bit later. Let's let's go back over to you. Explain adaptive data governance. Help us understand that >>really adaptive data governance is about achieving business outcomes through automation. It's really also about establishing a data driven culture and pushing what's traditionally managed in I t out to the business. And to do that, you've got to you've got Thio. You've got to enable an environment where people can actually access and look at the information about the data, not necessarily access the underlying data because we've got privacy concerns itself. But they need to understand what kind of data they have, what shape it's in what's dependent on it upstream and downstream, and so that they could make their educated decisions on on what they need to do to achieve those business outcomes. >>Ah, >>lot of a lot of frameworks these days are hardwired, so you can set up a set of business rules, and that set of business rules works for a very specific database and a specific schema. But imagine a world where you could just >>say, you >>know, the start date of alone must always be before the end date of alone and having that generic rule, regardless of the underlying database and applying it even when a new database comes online and having those rules applied. That's what adaptive data governance about I like to think of. It is the intersection of three circles, Really. It's the technical metadata coming together with policies and rules and coming together with the business ontology ease that are that are unique to that particular business. And this all of this. Bringing this all together allows you to enable rapid change in your environment. So it's a mouthful, adaptive data governance. But that's what it kind of comes down to. >>So, Angie, help me understand this. Is this book enterprise companies are doing now? Are they not quite there yet. >>Well, you know, Lisa, I think every organization is is going at its pace. But, you know, markets are changing the economy and the speed at which, um, some of the changes in the economy happening is is compelling more businesses to look at being more digital in how they serve their own customers. Eh? So what we're seeing is a number of trends here from heads of data Chief Data Officers, CEO, stepping back from, ah, one size fits all approach because they've tried that before, and it it just hasn't worked. They've spent millions of dollars on I T programs China Dr Value from that data on Bennett. And they've ended up with large teams of manual processing around data to try and hardwire these policies to fit with the context and each line of business and on that hasn't worked. So the trends that we're seeing emerge really relate. Thio, How do I There's a chief data officer as a CEO. Inject more automation into a lot of these common tax. Andi, you know, we've been able toc that impact. I think the news here is you know, if you're trying to create a knowledge graph a data catalog or Ah, business glossary. And you're trying to do that manually will stop you. You don't have to do that manually anymore. I think best example I can give is Lester and I We we like Chinese food and Japanese food on. If you were sitting there with your chopsticks, you wouldn't eat the bowl of rice with the chopsticks, one grain at a time. What you'd want to do is to find a more productive way to to enjoy that meal before it gets cold. Andi, that's similar to how we're able to help the organizations to digest their data is to get through it faster, enjoy the benefits of putting that data to work. >>And if it was me eating that food with you guys, I would be not using chopsticks. I would be using a fork and probably a spoon. So eso Lester, how then does iota who go about doing this and enabling customers to achieve this? >>Let me, uh, let me show you a little story have here. So if you take a look at the challenges the most customers have, they're very similar, but every customers on a different data journey, so but it all starts with what data do I have? What questions or what shape is that data in? Uh, how is it structured? What's dependent on it? Upstream and downstream. Um, what insights can I derive from that data? And how can I answer all of those questions automatically? So if you look at the challenges for these data professionals, you know, they're either on a journey to the cloud. Maybe they're doing a migration oracle. Maybe they're doing some data governance changes on bits about enabling this. So if you look at these challenges and I'm gonna take you through a >>story here, E, >>I want to introduce Amanda. Man does not live like, uh, anyone in any large organization. She's looking around and she just sees stacks of data. I mean, different databases, the one she knows about, the one she doesn't know about what should know about various different kinds of databases. And a man is just tasking with understanding all of this so that they can embark on her data journey program. So So a man who goes through and she's great. I've got some handy tools. I can start looking at these databases and getting an idea of what we've got. Well, as she digs into the databases, she starts to see that not everything is as clear as she might have hoped it would be. You know, property names or column names, or have ambiguous names like Attribute one and attribute to or maybe date one and date to s Oh, man is starting to struggle, even though she's get tools to visualize. And look what look at these databases. She still No, she's got a long road ahead. And with 2000 databases in her large enterprise, yes, it's gonna be a long turkey but Amanda Smart. So she pulls out her trusty spreadsheet to track all of her findings on what she doesn't know about. She raises a ticket or maybe tries to track down the owner to find what the data means. And she's tracking all this information. Clearly, this doesn't scale that well for Amanda, you know? So maybe organization will get 10 Amanda's to sort of divide and conquer that work. But even that doesn't work that well because they're still ambiguities in the data with Iota ho. What we do is we actually profile the underlying data. By looking at the underlying data, we can quickly see that attribute. One looks very much like a U. S. Social Security number and attribute to looks like a I c D 10 medical code. And we do this by using anthologies and dictionaries and algorithms to help identify the underlying data and then tag it. Key Thio Doing, uh, this automation is really being able to normalize things across different databases, so that where there's differences in column names, I know that in fact, they contain contain the same data. And by going through this exercise with a Tahoe, not only can we identify the data, but we also could gain insights about the data. So, for example, we can see that 97% of that time that column named Attribute one that's got us Social Security numbers has something that looks like a Social Security number. But 3% of the time, it doesn't quite look right. Maybe there's a dash missing. Maybe there's a digit dropped. Or maybe there's even characters embedded in it. So there may be that may be indicative of a data quality issues, so we try to find those kind of things going a step further. We also try to identify data quality relationships. So, for example, we have two columns, one date, one date to through Ah, observation. We can see that date 1 99% of the time is less than date, too. 1% of the time. It's not probably indicative of a data quality issue, but going a step further, we can also build a business rule that says Day one is less than date to. And so then when it pops up again, we can quickly identify and re mediate that problem. So these are the kinds of things that we could do with with iota going even a step further. You could take your your favorite data science solution production ISAT and incorporated into our next version a zey what we call a worker process to do your own bespoke analytics. >>We spoke analytics. Excellent, Lester. Thank you. So a J talk us through some examples of where you're putting this to use. And also what is some of the feedback from >>some customers? But I think it helped do this Bring it to life a little bit. Lisa is just to talk through a case study way. Pull something together. I know it's available for download, but in ah, well known telecommunications media company, they had a lot of the issues that lasted. You spoke about lots of teams of Amanda's, um, super bright data practitioners, um, on baby looking to to get more productivity out of their day on, deliver a good result for their own customers for cell phone subscribers, Um, on broadband users. So you know that some of the examples that we can see here is how we went about auto generating a lot of that understanding off that data within hours. So Amanda had her data catalog populated automatically. A business class three built up on it. Really? Then start to see. Okay, where do I want Thio? Apply some policies to the data to to set in place some controls where they want to adapt, how different lines of business, maybe tax versus customer operations have different access or permissions to that data on What we've been able to do there is, is to build up that picture to see how does data move across the entire organization across the state. Andi on monitor that overtime for improvement, so have taken it from being a reactive. Let's do something Thio. Fix something. Thio, Now more proactive. We can see what's happening with our data. Who's using it? Who's accessing it, how it's being used, how it's being combined. Um, on from there. Taking a proactive approach is a real smart use of of the talents in in that telco organization Onda folks that worked there with data. >>Okay, Jason, dig into that a little bit deeper. And one of the things I was thinking when you were talking through some of those outcomes that you're helping customers achieve is our ally. How do customers measure are? Why? What are they seeing with iota host >>solution? Yeah, right now that the big ticket item is time to value on. And I think in data, a lot of the upfront investment cause quite expensive. They have been today with a lot of the larger vendors and technologies. So what a CEO and economic bio really needs to be certain of is how quickly can I get that are away. I think we've got something we can show. Just pull up a before and after, and it really comes down to hours, days and weeks. Um, where we've been able Thio have that impact on in this playbook that we pulled together before and after picture really shows. You know, those savings that committed a bit through providing data into some actionable form within hours and days to to drive agility, but at the same time being out and forced the controls to protect the use of that data who has access to it. So these are the number one thing I'd have to say. It's time on. We can see that on the the graphic that we've just pulled up here. >>We talk about achieving adaptive data governance. Lester, you guys talk about automation. You talk about machine learning. How are you seeing those technologies being a facilitator of organizations adopting adaptive data governance? Well, >>Azaz, we see Mitt Emmanuel day. The days of manual effort are so I think you know this >>is a >>multi step process. But the very first step is understanding what you have in normalizing that across your data estate. So you couple this with the ontology, that air unique to your business. There is no algorithms, and you basically go across and you identify and tag tag that data that allows for the next steps toe happen. So now I can write business rules not in terms of columns named columns, but I could write him in terms of the tags being able to automate. That is a huge time saver and the fact that we can suggest that as a rule, rather than waiting for a person to come along and say, Oh, wow. Okay, I need this rule. I need this will thes air steps that increased that are, I should say, decrease that time to value that A. J talked about and then, lastly, a couple of machine learning because even with even with great automation and being able to profile all of your data and getting a good understanding, that brings you to a certain point. But there's still ambiguities in the data. So, for example, I might have to columns date one and date to. I may have even observed the date. One should be less than day two, but I don't really know what date one and date to our other than a date. So this is where it comes in, and I might ask the user said, >>Can >>you help me identify what date? One and date You are in this in this table. Turns out they're a start date and an end date for alone That gets remembered, cycled into the machine learning. So if I start to see this pattern of date one day to elsewhere, I'm going to say, Is it start dating and date? And these Bringing all these things together with this all this automation is really what's key to enabling this This'll data governance. Yeah, >>great. Thanks. Lester and a j wanna wrap things up with something that you mentioned in the beginning about what you guys were doing with Oracle. Take us out by telling us what you're doing there. How are you guys working together? >>Yeah, I think those of us who worked in i t for many years we've We've learned Thio trust articles technology that they're shifting now to ah, hybrid on Prohm Cloud Generation to platform, which is exciting. Andi on their existing customers and new customers moving to article on a journey. So? So Oracle came to us and said, you know, we can see how quickly you're able to help us change mindsets Ondas mindsets are locked in a way of thinking around operating models of I t. That there may be no agile and what siloed on day wanting to break free of that and adopt a more agile A p I at driven approach. A lot of the work that we're doing with our recall no is around, uh, accelerating what customers conduce with understanding their data and to build digital APS by identifying the the underlying data that has value. Onda at the time were able to do that in in in hours, days and weeks. Rather many months. Is opening up the eyes to Chief Data Officers CEO to say, Well, maybe we can do this whole digital transformation this year. Maybe we can bring that forward and and transform who we are as a company on that's driving innovation, which we're excited about it. I know Oracle, a keen Thio to drive through and >>helping businesses transformed digitally is so incredibly important in this time as we look Thio things changing in 2021 a. J. Lester thank you so much for joining me on this segment explaining adaptive data governance, how organizations can use it benefit from it and achieve our Oi. Thanks so much, guys. >>Thank you. Thanks again, Lisa. >>In a moment, we'll look a adaptive data governance in banking. This is the Cube, your global leader in high tech coverage. >>Innovation, impact influence. Welcome to the Cube. Disruptors. Developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe. Enjoy the best this community has to offer on the Cube, your global leader in high tech digital coverage. >>Our next segment here is an interesting panel you're gonna hear from three gentlemen about adaptive data. Governments want to talk a lot about that. Please welcome Yusuf Khan, the global director of data services for Iot Tahoe. We also have Santiago Castor, the chief data officer at the First Bank of Nigeria, and good John Vander Wal, Oracle's senior manager of digital transformation and industries. Gentlemen, it's great to have you joining us in this in this panel. Great >>to be >>tried for me. >>Alright, Santiago, we're going to start with you. Can you talk to the audience a little bit about the first Bank of Nigeria and its scale? This is beyond Nigeria. Talk to us about that. >>Yes, eso First Bank of Nigeria was created 125 years ago. One of the oldest ignored the old in Africa because of the history he grew everywhere in the region on beyond the region. I am calling based in London, where it's kind of the headquarters and it really promotes trade, finance, institutional banking, corporate banking, private banking around the world in particular, in relationship to Africa. We are also in Asia in in the Middle East. >>So, Sanjay, go talk to me about what adaptive data governance means to you. And how does it help the first Bank of Nigeria to be able to innovate faster with the data that you have? >>Yes, I like that concept off adaptive data governor, because it's kind of Ah, I would say an approach that can really happen today with the new technologies before it was much more difficult to implement. So just to give you a little bit of context, I I used to work in consulting for 16, 17 years before joining the president of Nigeria, and I saw many organizations trying to apply different type of approaches in the governance on by the beginning early days was really kind of a year. A Chicago A. A top down approach where data governance was seeing as implement a set of rules, policies and procedures. But really, from the top down on is important. It's important to have the battle off your sea level of your of your director. Whatever I saw, just the way it fails, you really need to have a complimentary approach. You can say bottom are actually as a CEO are really trying to decentralize the governor's. Really, Instead of imposing a framework that some people in the business don't understand or don't care about it, it really needs to come from them. So what I'm trying to say is that data basically support business objectives on what you need to do is every business area needs information on the detector decisions toe actually be able to be more efficient or create value etcetera. Now, depending on the business questions they have to solve, they will need certain data set. So they need actually to be ableto have data quality for their own. For us now, when they understand that they become the stores naturally on their own data sets. And that is where my bottom line is meeting my top down. You can guide them from the top, but they need themselves to be also empower and be actually, in a way flexible to adapt the different questions that they have in orderto be able to respond to the business needs. Now I cannot impose at the finish for everyone. I need them to adapt and to bring their answers toe their own business questions. That is adaptive data governor and all That is possible because we have. And I was saying at the very beginning just to finalize the point, we have new technologies that allow you to do this method data classifications, uh, in a very sophisticated way that you can actually create analitico of your metadata. You can understand your different data sources in order to be able to create those classifications like nationalities, a way of classifying your customers, your products, etcetera. >>So one of the things that you just said Santa kind of struck me to enable the users to be adaptive. They probably don't want to be logging in support ticket. So how do you support that sort of self service to meet the demand of the users so that they can be adaptive. >>More and more business users wants autonomy, and they want to basically be ableto grab the data and answer their own question. Now when you have, that is great, because then you have demand of businesses asking for data. They're asking for the insight. Eso How do you actually support that? I would say there is a changing culture that is happening more and more. I would say even the current pandemic has helped a lot into that because you have had, in a way, off course, technology is one of the biggest winners without technology. We couldn't have been working remotely without these technologies where people can actually looking from their homes and still have a market data marketplaces where they self serve their their information. But even beyond that data is a big winner. Data because the pandemic has shown us that crisis happened, that we cannot predict everything and that we are actually facing a new kind of situation out of our comfort zone, where we need to explore that we need to adapt and we need to be flexible. How do we do that with data. Every single company either saw the revenue going down or the revenue going very up For those companies that are very digital already. Now it changed the reality, so they needed to adapt. But for that they needed information. In order to think on innovate, try toe, create responses So that type of, uh, self service off data Haider for data in order to be able to understand what's happening when the prospect is changing is something that is becoming more, uh, the topic today because off the condemning because of the new abilities, the technologies that allow that and then you then are allowed to basically help your data. Citizens that call them in the organization people that no other business and can actually start playing and an answer their own questions. Eso so these technologies that gives more accessibility to the data that is some cataloging so they can understand where to go or what to find lineage and relationships. All this is is basically the new type of platforms and tools that allow you to create what are called a data marketplace. I think these new tools are really strong because they are now allowing for people that are not technology or I t people to be able to play with data because it comes in the digital world There. Used to a given example without your who You have a very interesting search functionality. Where if you want to find your data you want to sell, Sir, you go there in that search and you actually go on book for your data. Everybody knows how to search in Google, everybody's searching Internet. So this is part of the data culture, the digital culture. They know how to use those schools. Now, similarly, that data marketplace is, uh, in you can, for example, see which data sources they're mostly used >>and enabling that speed that we're all demanding today during these unprecedented times. Goodwin, I wanted to go to you as we talk about in the spirit of evolution, technology is changing. Talk to us a little bit about Oracle Digital. What are you guys doing there? >>Yeah, Thank you. Um, well, Oracle Digital is a business unit that Oracle EMEA on. We focus on emerging countries as well as low and enterprises in the mid market, in more developed countries and four years ago. This started with the idea to engage digital with our customers. Fear Central helps across EMEA. That means engaging with video, having conference calls, having a wall, a green wall where we stand in front and engage with our customers. No one at that time could have foreseen how this is the situation today, and this helps us to engage with our customers in the way we were already doing and then about my team. The focus of my team is to have early stage conversations with our with our customers on digital transformation and innovation. And we also have a team off industry experts who engaged with our customers and share expertise across EMEA, and we inspire our customers. The outcome of these conversations for Oracle is a deep understanding of our customer needs, which is very important so we can help the customer and for the customer means that we will help them with our technology and our resource is to achieve their goals. >>It's all about outcomes, right? Good Ron. So in terms of automation, what are some of the things Oracle's doing there to help your clients leverage automation to improve agility? So that they can innovate faster, which in these interesting times it's demanded. >>Yeah, thank you. Well, traditionally, Oracle is known for their databases, which have bean innovated year over year. So here's the first lunch on the latest innovation is the autonomous database and autonomous data warehouse. For our customers, this means a reduction in operational costs by 90% with a multi medal converts, database and machine learning based automation for full life cycle management. Our databases self driving. This means we automate database provisioning, tuning and scaling. The database is self securing. This means ultimate data protection and security, and it's self repairing the automates failure, detection fail over and repair. And then the question is for our customers, What does it mean? It means they can focus on their on their business instead off maintaining their infrastructure and their operations. >>That's absolutely critical use if I want to go over to you now. Some of the things that we've talked about, just the massive progression and technology, the evolution of that. But we know that whether we're talking about beta management or digital transformation, a one size fits all approach doesn't work to address the challenges that the business has, um that the i t folks have, as you're looking through the industry with what Santiago told us about first Bank of Nigeria. What are some of the changes that you're seeing that I owe Tahoe seeing throughout the industry? >>Uh, well, Lisa, I think the first way I'd characterize it is to say, the traditional kind of top down approach to data where you have almost a data Policeman who tells you what you can and can't do, just doesn't work anymore. It's too slow. It's too resource intensive. Uh, data management data, governments, digital transformation itself. It has to be collaborative on. There has to be in a personalization to data users. Um, in the environment we find ourselves in. Now, it has to be about enabling self service as well. Um, a one size fits all model when it comes to those things around. Data doesn't work. As Santiago was saying, it needs to be adapted toe how the data is used. Andi, who is using it on in order to do this cos enterprises organizations really need to know their data. They need to understand what data they hold, where it is on what the sensitivity of it is they can then any more agile way apply appropriate controls on access so that people themselves are and groups within businesses are our job and could innovate. Otherwise, everything grinds to a halt, and you risk falling behind your competitors. >>Yeah, that one size fits all term just doesn't apply when you're talking about adaptive and agility. So we heard from Santiago about some of the impact that they're making with First Bank of Nigeria. Used to talk to us about some of the business outcomes that you're seeing other customers make leveraging automation that they could not do >>before it's it's automatically being able to classify terabytes, terabytes of data or even petabytes of data across different sources to find duplicates, which you can then re mediate on. Deletes now, with the capabilities that iota offers on the Oracle offers, you can do things not just where the five times or 10 times improvement, but it actually enables you to do projects for Stop that otherwise would fail or you would just not be able to dio I mean, uh, classifying multi terrible and multi petabytes states across different sources, formats very large volumes of data in many scenarios. You just can't do that manually. I mean, we've worked with government departments on the issues there is expect are the result of fragmented data. There's a lot of different sources. There's lot of different formats and without these newer technologies to address it with automation on machine learning, the project isn't durable. But now it is on that that could lead to a revolution in some of these businesses organizations >>to enable that revolution that there's got to be the right cultural mindset. And one of the when Santiago was talking about folks really kind of adapted that. The thing I always call that getting comfortably uncomfortable. But that's hard for organizations to. The technology is here to enable that. But well, you're talking with customers use. How do you help them build the trust in the confidence that the new technologies and a new approaches can deliver what they need? How do you help drive the kind of a tech in the culture? >>It's really good question is because it can be quite scary. I think the first thing we'd start with is to say, Look, the technology is here with businesses like I Tahoe. Unlike Oracle, it's already arrived. What you need to be comfortable doing is experimenting being agile around it, Andi trying new ways of doing things. Uh, if you don't wanna get less behind that Santiago on the team that fbn are a great example off embracing it, testing it on a small scale on, then scaling up a Toyota, we offer what we call a data health check, which can actually be done very quickly in a matter of a few weeks. So we'll work with a customer. Picky use case, install the application, uh, analyzed data. Drive out Cem Cem quick winds. So we worked in the last few weeks of a large entity energy supplier, and in about 20 days, we were able to give them an accurate understanding of their critical data. Elements apply. Helping apply data protection policies. Minimize copies of the data on work out what data they needed to delete to reduce their infrastructure. Spend eso. It's about experimenting on that small scale, being agile on, then scaling up in a kind of very modern way. >>Great advice. Uh, Santiago, I'd like to go back to Is we kind of look at again that that topic of culture and the need to get that mindset there to facilitate these rapid changes, I want to understand kind of last question for you about how you're doing that from a digital transformation perspective. We know everything is accelerating in 2020. So how are you building resilience into your data architecture and also driving that cultural change that can help everyone in this shift to remote working and a lot of the the digital challenges and changes that we're all going through? >>The new technologies allowed us to discover the dating anyway. Toe flawed and see very quickly Information toe. Have new models off over in the data on giving autonomy to our different data units. Now, from that autonomy, they can then compose an innovator own ways. So for me now, we're talking about resilience because in a way, autonomy and flexibility in a organization in a data structure with platform gives you resilience. The organizations and the business units that I have experienced in the pandemic are working well. Are those that actually because they're not physically present during more in the office, you need to give them their autonomy and let them actually engaged on their own side that do their own job and trust them in a way on as you give them, that they start innovating and they start having a really interesting ideas. So autonomy and flexibility. I think this is a key component off the new infrastructure. But even the new reality that on then it show us that, yes, we used to be very kind off structure, policies, procedures as very important. But now we learn flexibility and adaptability of the same side. Now, when you have that a key, other components of resiliency speed, because people want, you know, to access the data and access it fast and on the site fast, especially changes are changing so quickly nowadays that you need to be ableto do you know, interact. Reiterate with your information to answer your questions. Pretty, um, so technology that allows you toe be flexible iterating on in a very fast job way continue will allow you toe actually be resilient in that way, because you are flexible, you adapt your job and you continue answering questions as they come without having everything, setting a structure that is too hard. We also are a partner off Oracle and Oracle. Embodies is great. They have embedded within the transactional system many algorithms that are allowing us to calculate as the transactions happened. What happened there is that when our customers engaged with algorithms and again without your powers, well, the machine learning that is there for for speeding the automation of how you find your data allows you to create a new alliance with the machine. The machine is their toe, actually, in a way to your best friend to actually have more volume of data calculated faster. In a way, it's cover more variety. I mean, we couldn't hope without being connected to this algorithm on >>that engagement is absolutely critical. Santiago. Thank you for sharing that. I do wanna rap really quickly. Good On one last question for you, Santiago talked about Oracle. You've talked about a little bit. As we look at digital resilience, talk to us a little bit in the last minute about the evolution of Oracle. What you guys were doing there to help your customers get the resilience that they have toe have to be not just survive but thrive. >>Yeah. Oracle has a cloud offering for infrastructure, database, platform service and a complete solutions offered a South on Daz. As Santiago also mentioned, We are using AI across our entire portfolio and by this will help our customers to focus on their business innovation and capitalize on data by enabling new business models. Um, and Oracle has a global conference with our cloud regions. It's massively investing and innovating and expanding their clouds. And by offering clouds as public cloud in our data centers and also as private cloud with clouded customer, we can meet every sovereignty and security requirements. And in this way we help people to see data in new ways. We discover insights and unlock endless possibilities. And and maybe 11 of my takeaways is if I If I speak with customers, I always tell them you better start collecting your data. Now we enable this partners like Iota help us as well. If you collect your data now, you are ready for tomorrow. You can never collect your data backwards, So that is my take away for today. >>You can't collect your data backwards. Excellently, John. Gentlemen, thank you for sharing all of your insights. Very informative conversation in a moment, we'll address the question. Do you know your data? >>Are you interested in test driving the iota Ho platform kick Start the benefits of data automation for your business through the Iota Ho Data Health check program. Ah, flexible, scalable sandbox environment on the cloud of your choice with set up service and support provided by Iota ho. Look time with a data engineer to learn more and see Io Tahoe in action from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>In this next segment, we're gonna be talking to you about getting to know your data. And specifically you're gonna hear from two folks at Io Tahoe. We've got enterprise account execs to be to Davis here, as well as Enterprise Data engineer Patrick Simon. They're gonna be sharing insights and tips and tricks for how you could get to know your data and quickly on. We also want to encourage you to engage with the media and Patrick, use the chat feature to the right, send comments, questions or feedback so you can participate. All right, Patrick Savita, take it away. Alright. >>Thankfully saw great to be here as Lisa mentioned guys, I'm the enterprise account executive here in Ohio. Tahoe you Pat? >>Yeah. Hey, everyone so great to be here. I said my name is Patrick Samit. I'm the enterprise data engineer here in Ohio Tahoe. And we're so excited to be here and talk about this topic as one thing we're really trying to perpetuate is that data is everyone's business. >>So, guys, what patent I got? I've actually had multiple discussions with clients from different organizations with different roles. So we spoke with both your technical and your non technical audience. So while they were interested in different aspects of our platform, we found that what they had in common was they wanted to make data easy to understand and usable. So that comes back. The pats point off to being everybody's business because no matter your role, we're all dependent on data. So what Pan I wanted to do today was wanted to walk you guys through some of those client questions, slash pain points that we're hearing from different industries and different rules and demo how our platform here, like Tahoe, is used for automating Dozier related tasks. So with that said are you ready for the first one, Pat? >>Yeah, Let's do it. >>Great. So I'm gonna put my technical hat on for this one. So I'm a data practitioner. I just started my job. ABC Bank. I have, like, over 100 different data sources. So I have data kept in Data Lakes, legacy data, sources, even the cloud. So my issue is I don't know what those data sources hold. I don't know what data sensitive, and I don't even understand how that data is connected. So how can I saw who help? >>Yeah, I think that's a very common experience many are facing and definitely something I've encountered in my past. Typically, the first step is to catalog the data and then start mapping the relationships between your various data stores. Now, more often than not, this has tackled through numerous meetings and a combination of excel and something similar to video which are too great tools in their own part. But they're very difficult to maintain. Just due to the rate that we are creating data in the modern world. It starts to beg for an idea that can scale with your business needs. And this is where a platform like Io Tahoe becomes so appealing, you can see here visualization of the data relationships created by the I. O. Tahoe service. Now, what is fantastic about this is it's not only laid out in a very human and digestible format in the same action of creating this view, the data catalog was constructed. >>Um so is the data catalog automatically populated? Correct. Okay, so So what I'm using Iota hope at what I'm getting is this complete, unified automated platform without the added cost? Of course. >>Exactly. And that's at the heart of Iota Ho. A great feature with that data catalog is that Iota Ho will also profile your data as it creates the catalog, assigning some meaning to those pesky column underscore ones and custom variable underscore tents. They're always such a joy to deal with. Now, by leveraging this interface, we can start to answer the first part of your question and understand where the core relationships within our data exists. Uh, personally, I'm a big fan of this view, as it really just helps the i b naturally John to these focal points that coincide with these key columns following that train of thought, Let's examine the customer I D column that seems to be at the center of a lot of these relationships. We can see that it's a fairly important column as it's maintaining the relationship between at least three other tables. >>Now you >>notice all the connectors are in this blue color. This means that their system defined relationships. But I hope Tahoe goes that extra mile and actually creates thes orange colored connectors as well. These air ones that are machine learning algorithms have predicted to be relationships on. You can leverage to try and make new and powerful relationships within your data. >>Eso So this is really cool, and I can see how this could be leverage quickly now. What if I added new data sources or your multiple data sources and need toe identify what data sensitive can iota who detect that? >>Yeah, definitely. Within the hotel platform. There, already over 300 pre defined policies such as hip for C, C, P. A and the like one can choose which of these policies to run against their data along for flexibility and efficiency and running the policies that affect organization. >>Okay, so so 300 is an exceptional number. I'll give you that. But what about internal policies that apply to my organization? Is there any ability for me to write custom policies? >>Yeah, that's no issue. And it's something that clients leverage fairly often to utilize this function when simply has to write a rejects that our team has helped many deploy. After that, the custom policy is stored for future use to profile sensitive data. One then selects the data sources they're interested in and select the policies that meet your particular needs. The interface will automatically take your data according to the policies of detects, after which you can review the discoveries confirming or rejecting the tagging. All of these insights are easily exported through the interface. Someone can work these into the action items within your project management systems, and I think this lends to the collaboration as a team can work through the discovery simultaneously, and as each item is confirmed or rejected, they can see it ni instantaneously. All this translates to a confidence that with iota hope, you can be sure you're in compliance. >>So I'm glad you mentioned compliance because that's extremely important to my organization. So what you're saying when I use the eye a Tahoe automated platform, we'd be 90% more compliant that before were other than if you were going to be using a human. >>Yeah, definitely the collaboration and documentation that the Iot Tahoe interface lends itself to really help you build that confidence that your compliance is sound. >>So we're planning a migration. Andi, I have a set of reports I need to migrate. But what I need to know is, uh well, what what data sources? Those report those reports are dependent on. And what's feeding those tables? >>Yeah, it's a fantastic questions to be toe identifying critical data elements, and the interdependencies within the various databases could be a time consuming but vital process and the migration initiative. Luckily, Iota Ho does have an answer, and again, it's presented in a very visual format. >>Eso So what I'm looking at here is my entire day landscape. >>Yes, exactly. >>Let's say I add another data source. I can still see that unified 3 60 view. >>Yeah, One future that is particularly helpful is the ability to add data sources after the data lineage. Discovery has finished alone for the flexibility and scope necessary for any data migration project. If you only need need to select a few databases or your entirety, this service will provide the answers. You're looking for things. Visual representation of the connectivity makes the identification of critical data elements a simple matter. The connections air driven by both system defined flows as well as those predicted by our algorithms, the confidence of which, uh, can actually be customized to make sure that they're meeting the needs of the initiative that you have in place. This also provides tabular output in case you needed for your own internal documentation or for your action items, which we can see right here. Uh, in this interface, you can actually also confirm or deny the pair rejection the pair directions, allowing to make sure that the data is as accurate as possible. Does that help with your data lineage needs? >>Definitely. So So, Pat, My next big question here is So now I know a little bit about my data. How do I know I can trust >>it? So >>what I'm interested in knowing, really is is it in a fit state for me to use it? Is it accurate? Does it conform to the right format? >>Yeah, that's a great question. And I think that is a pain point felt across the board, be it by data practitioners or data consumers alike. Another service that I owe Tahoe provides is the ability to write custom data quality rules and understand how well the data pertains to these rules. This dashboard gives a unified view of the strength of these rules, and your dad is overall quality. >>Okay, so Pat s o on on the accuracy scores there. So if my marketing team needs to run, a campaign can read dependent those accuracy scores to know what what tables have quality data to use for our marketing campaign. >>Yeah, this view would allow you to understand your overall accuracy as well as dive into the minutia to see which data elements are of the highest quality. So for that marketing campaign, if you need everything in a strong form, you'll be able to see very quickly with these high level numbers. But if you're only dependent on a few columns to get that information out the door, you can find that within this view, eso >>you >>no longer have to rely on reports about reports, but instead just come to this one platform to help drive conversations between stakeholders and data practitioners. >>So I get now the value of IATA who brings by automatically capturing all those technical metadata from sources. But how do we match that with the business glossary? >>Yeah, within the same data quality service that we just reviewed, one can actually add business rules detailing the definitions and the business domains that these fall into. What's more is that the data quality rules were just looking at can then be tied into these definitions. Allowing insight into the strength of these business rules is this service that empowers stakeholders across the business to be involved with the data life cycle and take ownership over the rules that fall within their domain. >>Okay, >>so those custom rules can I apply that across data sources? >>Yeah, you could bring in as many data sources as you need, so long as you could tie them to that unified definition. >>Okay, great. Thanks so much bad. And we just want to quickly say to everyone working in data, we understand your pain, so please feel free to reach out to us. we are Website the chapel. Oh, Arlington. And let's get a conversation started on how iota Who can help you guys automate all those manual task to help save you time and money. Thank you. Thank >>you. Your Honor, >>if I could ask you one quick question, how do you advise customers? You just walk in this great example this banking example that you instantly to talk through. How do you advise customers get started? >>Yeah, I think the number one thing that customers could do to get started with our platform is to just run the tag discovery and build up that data catalog. It lends itself very quickly to the other needs you might have, such as thes quality rules. A swell is identifying those kind of tricky columns that might exist in your data. Those custom variable underscore tens I mentioned before >>last questions to be to anything to add to what Pat just described as a starting place. >>I'm no, I think actually passed something that pretty well, I mean, just just by automating all those manual task. I mean, it definitely can save your company a lot of time and money, so we we encourage you just reach out to us. Let's get that conversation >>started. Excellent. So, Pete and Pat, thank you so much. We hope you have learned a lot from these folks about how to get to know your data. Make sure that it's quality, something you can maximize the value of it. Thanks >>for watching. Thanks again, Lisa, for that very insightful and useful deep dive into the world of adaptive data governance with Iota Ho Oracle First Bank of Nigeria This is Dave a lot You won't wanna mess Iota, whose fifth episode in the data automation Siri's in that we'll talk to experts from Red Hat and Happiest Minds about their best practices for managing data across hybrid cloud Inter Cloud multi Cloud I T environment So market calendar for Wednesday, January 27th That's Episode five. You're watching the Cube Global Leader digital event technique

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Welcome to this cube conversation. I'm Lisa Martin, and I'm joined by two guests from Ivanti, today. Please welcome its President, Jeff Abbot and its Chief Product Officer, Nayaki Nayyar. Jeff and Nayaki, it's so great to talk to you today. >> Pleasure to speak to you, Lisa. >> Pleasure to be here, Lisa, look forward to this. >> Me too. So Jeff, let's start with you, transformation, you got some big news that you're going to be sharing and breaking through theCUBE Conversation today which we're going to dig into but there's been a lot of transformation at the top at Ivanti, you're new, tell me about that and what's the shake up that's been going on there to really drive this company forward? >> Yeah. We have got a lot of transformation going on, Lisa. And it's been an exciting ride for the first six months of my tenure at Ivanti. I came in January as president along with our new CEO, who has been Chairman, Jim Schaper. And when Jim and I started talking about Ivanti last fall, the challenges were pretty clear. It's a company that's had outstanding employees, fantastic customers, and a real heritage of innovation. But they had leveled off a little bit. And the idea behind the new executive team was to bring in a team of veterans to take it to the next level, really to grow to a billion dollars and beyond, both organically and through acquisitions. So you're right, we brought in a fantastic team of veterans people that Jim and I have both worked with: Angie Gunter, new Chief Marketing Officer, Mary Trick, new Chief Customer Officer, we recently hired Nayaki Nayyar, who's with us today, our Chief Product Officer, John Flavin, the Head of our Industry Business Unit, and a host of others that have all come in with a single mission to take Ivanti to the next level. >> So Nayaki, let's dig into Ivanti's vision, lot of change, lot of momentum, I imagine with that change, but what's your vision? >> So let's take a step back, Lisa and you look at, what I call Ivanti's position of strength. And when you look at the entire portfolio Ivanti has, one of the key strengths Ivanti has is its ability to discover, secure, manage and service the endpoints. And if you look at the entire marketplace, there is no vendor in the market today, most of them UEM vendors don't have service management, service management don't have UEM, our ability, Ivanti's ability to do this end to end management of endpoints all the way from discovery to security to service management is what our key strength is. That's our competitive advantage, bringing these three pillars together under one umbrella and having a holistic story. Especially in this day and age of COVID and post COVID, where everyone is trying to manage those endpoints, secure those endpoints, and have almost a seamless experience as remote becomes the next normal going forward for every enterprise, Lisa. >> Yeah, the next normal. Well, there's data scatter, there's device scatter and it's now almost like so many people working from home overnight a few months ago that now will have almost a relationship with our devices because they're our lifeline. So for an organization to be able to understand where all those devices are, people are now working from home, but as you shared, Nayaki, with me the other day, there's some gartner data that demonstrates that 3.6% of the workforce before COVID was working from home. It might be 10X that post COVID So the amount of device scatter and data scatter and need to secure, that challenge is even going up. So how does Ivanti help? How do you solve that challenge? >> So Lisa, if you put yourself in any large enterprise and organization that is dealing with this post COVID or addressing the needs of a remote worker, the remote workers are going through, I would say, explosive growth where they used to be single digits 3% 4% before COVID, and now, during COVID, and after COVID, it's probably going to be I would say, 30, 40% of remote workers that every enterprise has to now provide that service, that seamless service experience as they're working from home, they could be on the move. So providing that seamless experience is, I would say, number one priority and a key challenge for every enterprise. So what we are going to be releasing and launching and announcing to the market given our position of strength in managing endpoints is how we help that seamless experience and what I call the ambient experience for an end user independent of where they are working from, they could be working from home, they could be on the move, or office. >> Which is critical these days. But before we dig into the announcement, Jeff, I wanted to ask you, some of the stats that I've been seeing in terms of the C suite and the amount of decisions that the C suite has had to make in the last four months has been more than over the last five or so years. Talk to us a little bit about how Ivanti got together this new C suite to make the decision to announce what you're going to talk about today so quickly. >> Now, that's a great point. And it's one that we had to, quite frankly, Lisa. The market is demanding a hyper-automation, it's demanding more agnostic deployment, it needs more flexibility in terms of the ability to be self driven and sense and service without a whole lot of intervention. So we knew that when we came in as a new leadership team, the first thing we had to do was get the go-to-market strategy in order, which we did. We balanced our direct sales strategy with our partner strategy. We made some changes in the marketing organization to a more contemporary content-focused demand generation style, and we reset the company's focus on customer outcomes. And in so doing, we changed the mentality to success as measured by are we meeting our customers intended business goals? And that led us very quickly to say, "Listen, the unified IT message we've been using for the last few years has been great, and our customers have responded well to it, and we've acquired a lot of new customers with that message, but the game has changed." And as Nayaki was leading up to, the expectation has changed. And the entire IT space is relatively mature but the expectations and the pressure on that space has grown tremendously, as you pointed out, in the last few years. Just think of the number of devices we all now have to manage as a company, and it's growing. And as Nayaki pointed out as she discusses our launch, it's growing almost exponentially. So we knew that we had to have a new product strategy, we had to take the unified IT message and start to think differently about how the IT leaders in the field and our various customers around the world, how their game has changed and lean in to what they need in terms of automation, AI, bot technology, and so on. And that's what we're announcing with this latest release. >> All right, Nayaki, take it away. What are you announcing? >> Yeah, so what we're super-excited about, Lisa, is to Jeff's point, to handle this explosive growth, growth of devices, growth of data that is being generated from those devices, and also this explosive growth of remote workers. Meaning the only way to handle this growth is through what we call automation and we are taking that next, advanced automation, that leap frog strategy of what we call hyper-automation, embedding that into our entire stack, into our UEM endpoint management stack, into our security stack and also service management to help customers, what we call, self-heal, discover all the devices continuously, optimize the performance, optimize any configuration drifts, and proactively predictively remediate any issues, any issues that you see on those devices, and get into a world of what we call self-healing autonomous edge. Where it's continuously detecting every issue and being able to predictively and cognitively self-heal that edge. And this is what we are launching, is what we branded as Ivanti Neurons, is the brand that we are launching for these automation, this hyper-automation bots, that every company can deploy these hyper-automation bots into their network that will constantly discover every device you have across your entire network, discover any performance issues, configuration drift issues, security issues, vulnerabilities, anomalies, and really get into what we call self-healing, self-securing and providing a service experience that we are used to in our day to day life or in our consumer world. So that's what we are announcing, super-excited about the overall launch. The fact that every enterprise, every company, and it's not tied to any single vertical, Lisa, any vertical organization can leverage these neurons and get that closer to self-healing of those devices that they have to now manage every organization that has to now manage. >> I know Ivanti has a lot of strengths and several verticals, one of them being healthcare. And I can imagine right now, the last five months, the hyper status that every hospital and clinic is in, I'm curious, though, about the name. Jeff, talk to me about in this new, the next normal that we're living in, Neurons, what does that mean and what does it mean to your customers? >> Yeah, great question. And I know this will resonate with you, Lisa, as an accomplished biologist. With the idea is with what we're providing and what we're launching with Neurons, there's a sense of hyper-scale, hyper-automation, like the synapses in your brain, handles so much information at once. So we wanted to personalize the launch of these solutions. When you see the announcement next week, you'll see a series of products across the spectrum Ivanti solutions; the ITSM, endpoint management, security and so on. And we address in each of those areas, the self-sensing, self-healing, self-servicing, each of those business processes. But like your synapses or your neurons in your brain, there'll be a lot of super-fast automation, super-fast sensing of challenges and addressing those challenges. And that's why we went with Neurons. It was actually a pretty fun contest in the company and we really believe Neurons will connect with our target market. >> I love it. And the biologist part of me is gone, "That makes sense." So Nayaki, over to you. And in terms of that connectivity perspective, there's so many disparate data sources out there, it's only growing. And Jeff, you mentioned this, how can one of your existing 25,000 customers, use, deploy, this on top of their existing infrastructure to start connecting data sources that they may not even know they can connect or that they may not know does it make even sense to connect them? >> Yeah, so the beauty of the entire Neuron network is it uses MQTT protocol, Lisa, which is the protocol that immediately detects every device, be it endpoint desktops, laptops, mobile devices, or even, I was suggesting IoT devices, that it automatically detects. And senses if there is anything happening on those devices, predicts if there is any issue that may happen, like I said, performance issues, configuration drift issues, security issues and pulls that data in real time. The beauty of this is the speed at which it pulls its data, I've seen customers who can deploy this across their entire network around the world and within seconds, it's able to pull the data into a centri console, and give ourselves a full 360 view of every device you have, every user that's using those devices all the applications that are running on those devices and the services that are being delivered to those devices. So just the power of being able to pull that much data in seconds and provide that 360 view of what we call, a Neuron Workspace, for any IT organization to have that full 360 view, and detect and predict that there's any issue and almost like get into a self-healing remediated before it interrupts your productivity or interrupts your... Any service disruption. I think you were trying to say something, go ahead. >> I was just going to add to that, Nayaki. And you asked this or made this point, Lisa, Nayaki and I are speaking to the healthcare industry almost every day. We are very in tune with the challenges they're experiencing, obviously, with what's happening right now around the world. And as Nayaki is describing, the Neurons we intend to be a very seamless improvement to their existing IT processes and so on. In fact, when I described this to some of the hospitals I've been speaking to, and certainly the IT staff and leaders within, they are fascinated and very excited about what we're describing. Because if you think about it, IT challenges down at the device level in the healthcare industry can be life critical. And they need to solve those IT challenges very fast. They need to know when their new endpoints are online, they need to know when they need servicing, and then they know when their software needs patching. We're not talking about just being at home and being frustrated if you're having an IT challenge, we're talking about life and death. So Neurons is absolutely what the healthcare industry is asking for in terms of self-healing, self-sensing, self-securing and so on, they need those attributes in their business model, now definitely more than ever. >> Absolutely, they do. So Nayaki, talking to customers in healthcare, whatnot, I can see this being a great tool for the IT analyst but also maybe even helping the IT analysts and business users have better relationships that overall help drive a business forward. >> Yeah, so you put yourself in an end user or line of business, they expect, and especially in this day and age of post COVID, Lisa, they expect a consumer grade experience to be delivered to them. They expect their service provider to know exactly where they're working from, what devices they have, how all those devices are not just secure, but understands the preferences I need as an individual and provides that service experience to me. So I mean that, I would say, a close tie in between what the business wants, the end users in those lines of business want and how IT or any service organization can provide that service to employees, customers, and consumers is what really Neurons, I would really... Helps us get closer and closer to consumer grade experience that we all are used to in our day to day life. And to Jeff's point, in addition to healthcare, which is a strong industry vertical for us, some other industries, retail is another big industry that we are very strong in, Lisa, and also supply chain rugged devices in a warehouse. So it really gives us a huge expansion opportunity beyond just managing the IT devices or endpoints to also managing the IoT devices by industry vertical, in those segments, where we already have a very, very strong foothold, because of the technology that we have that powers this whole thing in the backend. >> And we're seeing some of the numbers of 40+ Billion, connected devices in the next few years. So Jeff, let's end this with you. I know there's more coming, but you probably have a great partnership suite that you're working with to enable this, talk to us a little bit about the partners, and then what's next? >> Yeah, no, great point, Lisa. I come from a heritage of companies that have leveraged our partners. And we continue to grow our partner network. We believe strongly in the strength of the extended ecosystem, solution partners, delivery partners, global systems integrators, they all have a role in Neurons. And we're excited to continue to provide the platform for mutual growth between us and those partners. And what's really important is, these are companies that our customers really love as well. So we're going to continue to, in some cases, tie our solutions together, in some cases, extend our services organization through partners, and in some cases, we'll actually service our customers through our channel partner network. We actually went through a little bit of a rationalization to really zero in on our most strategic partners, we've done that, we've finished that in the first six months of coming on board. And now we are hitting the gas pedal and going full speed to market with a great group of partners and again, you'll see that ecosystem more and more as part of our strategy. >> Excellent. So Neurons announced, what's next? >> Well, there's quite a bit behind Neurons. So it will take us probably into at least 2021 getting all the solutions launched, and getting them ingrained with our customers out there. Well, we fully intend to continue to innovate. And if there's one thing I leave you with, Lisa, it's that that's our big announcement more than anything. I mean, Ivanti's had a history of innovation, it's a company that practically invented patching, and keeping all of the devices up to speed on the latest virus protection software and so on, there's a lot of legacy companies within our footprint that are now completely tied together and under the Neuron strategy under Nayaki's leadership we intended to put innovation out in the marketplace, quarter after quarter after quarter, but Neurons for now will keep us quite busy. So we're very excited. >> Well, congratulations on that. Ivanti, innovation, hyper-automation. Jeff, Nayaki, it's been such a pleasure talking to you. Thank you for joining me on theCUBE today. Thank you, Lisa. >> Thank you for having us. >> For my guests, I am Lisa Martin, you're watching theCUBE Conversation. (upbeat music)

>>live from Atlanta, Georgia. It's the Q covering answerable best 2019. Brought to you by Red hat. >>Hey, welcome back to the Cuban Live coverage in simple fest. Two days of coverage. Day one, wrapping up. I'm John forwards. Accused Too many men. My guest co host today, our next two guests at his van. Van Velzen. Okay, welcome to the Cube. You're an engineer at I n G Bank and Robert de Bock, product owner, engineer I n g. Bank. Hey, guys, Thanks for coming on. Thank you. Have the practitioner on. Well, first of all, we have a lot of great feedback from the practitioners here. And also people in deploying answerable and other other cool Dev ops Tools on automation is at the top of the list. Yes, More efficient. Getting things done. Focus. You got satisfaction in job because things go awaiting time savings. I'm saving security drives a conversation and re skilling opportunities. Love. These are cutting edge. Things you got to do is take a minute to explain what you guys do. What a night. What a night. Angie bank. >>Yeah. I work in a team that provides redhead images for other teams. in 90 to consume to use two insane she ate way. Also live from playbooks, amendable code and rolls to manage those things. And he's very scattered, which sort of decentralized, which is a good thing. In my opinion, it's ready for scaling. In that case, I used to work with Dennis are lots in the tower team, so take it away. >>Okay, so I still work at the answer, built our squad What we do, it's ah, We make sure that the instable tower service keeps running 24 7 and we also ensure that we, uh, provide updates next to all this. We also have unanswerable community where we basically support our end users, which are their love. So, uh, from some numbers, I heard we have 1200 applications teams that are using our service. Um, and they all have, like, answerable playbook, sensible rolls, questions, difficulties with, uh, with anything. And we're basically there to support them as well. >>So 1200 teams are using answerable, Yes, inside the bank. Yes. Yeah, like >>it's set up very decentralized. And I think what I hear from instable fest that is not very common. I still think it's very good thing to do. We try to basically give these teams all the tools they need to do their stuff on. What I hear hear mostly is that there's essential team off administrators pushing the buttons for them. Towers. Great answer was great in that case, I think, for our case is really it's a perfect fit. >>E guess help Explain. Is this do you provide? You know, he said it's not centralized, but is this you know, here's best practices here. Some play boat out. How do you end? You support them? Because they're a little bit those relationships. >>Okay. Okay. Um so what we do is we basically all the rules and get ah ah, good lap. So it's an own premise. Get environment. You can search in this. Get for rules. Uh, not like all rules are easily to be found when searching for them. So that's why there are these communities to share what you have made. Um, >>plus these teams, they can themselves pick and choose. Some will try to rewrite everything That's fine. Others can can benefit from existing coat, so it's just a good trick. Thio enable these team to participate on it really different. Some people make it all themselves another >>next to this. So we basically have these 12 on the teams do their own thing. But next to this, we also have a self service portal where they can choose, like from, uh, generic finks like us. But your machine at new disc. So New capacity Cp use memory. That's all being done through a portal s so they don't need to do anything on their own for this they can, but most of them choose the easy way off using this portal. This portal basically doesn't a vehicle to instable tower, which executes a sensible playbook and some other stuffs. Maybe some AP eyes. And this is one of the things you guys create A manage these books. So, um >>and if you go back in time so the alternative way, which we happily got rid off, is to do it ourselves. I think it was before we we work together. Way had batch weekends, for example, and it >>was no very different. No life. Oh, that's working on weekends, >>weekends and, for example, he used to patch machine some 10,000 or so, and we were not aware what was important. What? Not so you you'd stop the whole pitch. Oh, this machine has a problem. Let's stop everything in focus and that's >>not important. Was like a complete order. >>And the other way around Also this machine. I guess it's not that important. Let's just >>continue this >>Sunday morning. Oh, my God. Everything's broken. >>Can you give us a little flavor of kind of the spectrum of solutions that you leverage answerable on >>tap? Yeah. We, uh I think what we see Moses for Lennox machines, eso fetching is a big one. We got a second operation, so there's a few of them. The deployment also depends on and small. So if you order a new machine, answer was involved somewhere to do to make it happen on network on board and the Windows teams are very interested. I'm not sure if we notice on board yet. To >>be honest, I know we did some book in the boss so a couple of months ago, using wind around when you needed set on policies there, But you can see that the networking teams were getting more momentum. Uh, five. There's some suffer suffer to find switches Bob. I don't know. The, uh Never mind the name, but ah, you can see some momentum in the in the networking. Uh, it's not Morgan departments >>configuration network networking with the activists. So that's where the action is in the >>network. Um, there were some cool talks also here on five workshops. So you can see there is, um, that there is some attention on these modules and integrations as well. >>What's your guy's goal here for the show? What brought you here? I'll see Big user. >>Yeah. So what do you think was like sharing our own thing? We did. They talk this morning. Ah, regarding and programming A really cool we wanted to share. It is this behavioral thing, and and >>we'll talk about take a minute and programming. >>So, um, basically, it's, ah programming with the whole team and making sure that you get something done with all the knowledge in the team. So you don't have to align off the words or if some other if you're Kulik says from basically session, you can do better using this staying. It's all, um it's It's all done during the decision >>as basically a good way to get a team up to speed. So in a team that's probably a few few people that are very quick and understand the concept and few starters or so So >>you guys decentralized, which makes sense for scale. I get that. So this sounds like you can operate decentralized, but where danceable. You can still have that common a book Switch >>teams, for example. So it used to be very specific. H team would have their own type of coat. Now that more answers used people can switch a little easier to to another product of surface because the languages have lied, shared, steal it, steal. It's quite >>well happy with this, right? I am. I really, really have to work on the weekend. That's good. I think >>the good thing is that you have one generic way of working. So his playbook is readable by all engineers. And if you want to learn this thing, you just do the inevitable course. So you know what this thing is? A mosque and roll, and it's all like >>way. We do see horrible >>koto. Come on, don't throw your college under the bus. But here's the international tough question can see is what we have been here. I want you guys to test this. We hear that there's a lot of time savings involved. Yes, with answer. True or false. That's true order of magnitude. What? What kind of saving way talking about? I >>think it depends on the thing because we saw a huge I don't know, except numbers. But this this os patching that Really? Really Uh, >>yes. Now, especially waas. Two people working a full time basically collecting, who needs to do what? The win. And then for a weekend, 10 15 people or so. So, uh, that's reduced now to sort of nothing. Yes, some maintenance to that playbook and roll. But I mean, yeah, it's difficult to express what message? So >>no one's getting phone call? Hey, come in on the weekend. So 15 people on the weekend jam and then to Fulton will just managing it all Go away. >>Yeah, not needed, but not needed. But they basically they can do something else, so those people are still there. But now they're not doing Os patching and doing all the excel sheets and keeping order off. The systems are important, and this shall be the first, and then they because way are basically doing the thing they know better. This application team knows their dependency, so they know they. But first I need to patch the database machine and then there during the front end or Andi. It's difficult to do this so they do it themselves. >>That's Dev Ops. That's that's the way it's supposed to be, right? >>So you've matured this thes deployments over time. As you look back, What key learnings do you have that maybe you'd recommend to your peers toe? You know how things could run a little bit smoother >>next time, a good amount of time. So they're stools. That's not the problem, So answer is great, but there's others to their great Give it time to sink in with the people. So you start something and you have to have a pretty strong team to do the long the long stretch with it and give it some time, maybe a year or so before everyone's on board it. In our case, in the beginning, we spend lots of time on this community model where we basically organized small meet ups or get together, too, show things or to hear problems and try to express them. That really helped a lot. And by now it's starting to get normal, more normal. So all the teams do sensible, basically. And problem starts slowly disappearing. Also. So So >>one of the things, um, that will be better. Probably in our scenario. Housekeeping metrics. So what are the improvements over time? I don't know how to measure this. No, no, no aspect. But it will be better if you had, like, better numbers like we did hair Very good. Or this is something like, what did the community thing bring way indirectly what the results are Because the engineers are doing things really, really things. They're really patching the replication. And they're really, um, restarting their own machines, for example, when there is something wrong. Whatever. Um, but our days related to our community thing or all that's really related to Sensible Tower >>last. I think we we are very technical focus. So So we like it as a nerd, so to say, to do things but what the business value is, for example, I'm not so interested or less interested so way typically, like the technology, so it could be good to have some someone onboard and your team that says, Yeah, but this is the problem. It's crossed. This amount of money and that solved now are improved. >>Well, they assume the applications are doing a good job. So you guys helped those guys out. They get to do their own thing. They do the heavy lifting. They're doing the coding anyway for those guys that were coming in managing full time on the 15 or so on the weekend. What are they doing now? >>Most are spread across. All the application teams go back. But the other side there is now it's our team that was not there s. So that's the price you have to pay. And that's a serious team. I mean, it's far six people now 86 people and 100 machines or so. So it is a serious amount of time, but it makes it at least much more constant. So people are not surprised by machines being patched, and Monday they come back into the half broken or so. So it's a lot more control now, so I don't know if you can express it in price, but at least it's more stable >>more consistent. >>Well, one of the things that we hear here and I want to get your thoughts as we wrap up is as you go forward, you got answerable 1200 teams using it. You got a lot of collaboration. The work cultures change. Sounds like a shower. Team steps service everything else. So some scale building out what's next? Because as it becomes a platform. Okay, you have to enable something. There has value there. Okay, technical nerd value and then business value >>scaling, uh, because we continuously see this thing growing like more application teams are adapting answerable, invincible tower. So, um, right now we have, like, a cluster. We have different clusters running. Go into much detail, but we can see that the load is getting higher and higher, so we need to skill. Um, and this is sort of difficult, but red. That is really supporting in this because they're going to change some things at the application level two to allow scaling even better. Um, >>plus, also, for most teams, they're starting their configuration. Everything is coat process. They're not there yet. As soon as they discover the power of it, I'm sure that's being used a lot. A lot more. And plus, there's other countries that are going to be connected. So you have a lot of work >>because your engineering doing some getting down and dirty with the code, automating everything. >>Yeah. Yeah. So, um, what else do we >>Oh, what's the coolest thing you've done that you've automated? >>Uh >>uh, Pick your favorite. >>So but the child during Encircle Tower and with answerable, um, let me think about this. >>I I really like the patching that saved us so much work. And, uh, I think also one of the next goes to make much more simpler. So we as a company, we're complex and the people also like complexity. That's wrong. We should change >>that. Patching up our >>offense, Melissa Simplicity. So we should really use that. >>You don't want any open holes in the network housely and assistance >>about your previous question. Like I have sort of a finger and all these small things. So it's sort of what I did. It's more like an A team thing. We created the OS patch playbooks, the configure stuff, the second day offs. So we did this as a team >>like sports but the playbooks together run the play. Some defense on security >>and programming. So you're doing >>this as a team, which is very cool. Has a scoreboard look good? Winning? >>Yeah, Yeah, yeah, yeah. We're looking at the graphite. Uh, it's girl. >>Final question. How you enjoying the show here? Having a good time? What's the vibe here? What's it like here? Share for the people who aren't here. What's going on? What's the vibe with >>a conversation? It's great. We went to some sessions yesterday really technical stuff with developers. And this was really amazing because you heard details that that are not in the India in the talks today and tomorrow. Um, yeah, it's great. It's great community. It's just I really I really enjoy it because you can. It's You can have, like one on one conversations go into depth. I was showing something I created, and this guy's we'll hold. This is really great in the It's cool. It's just if you it's really great. It's really >>cool. Really? Yeah, for me also, it feels like coming home, So I know these people and I think the first day, the collaboration day, what's it called and I'm not sure you community, that's it's great because it's been a bit rough and unpolished in today's more polished and more presented and prepared to, uh, both are great. >>Good. Give the hard feedback. >>Yeah, you meet all the people. So, for example, I used instable a lot, and then I'm getting up. I see all these names. Like, who would that be there walking here and shake hands like, Oh, that's >>why guys like your code looking good. Yeah. Looks good. A contributor. Summit contributed. Okay. Sorry. After it for >>anyone that goes to visit that day, too. That's just great. >>It's great to see people face to face that, you know, online for their digital identity or the code >>you can You can't complain about stuff out on. Do you know that you don't hurt them or something with just commenting on get like after this issue and this issue and this issue. Then you can see them in person. And then you >>him a high five assault, you know? Hey, >>it's really very cool. >>Guys. Great conversations were coming on cue. Thanks, Dennis. Appreciate Robert. Thanks for coming on. Skew coverage here Day one of two days of live coverage here inside the Cube here in Atlanta, Georgia for Ansel Fest is the cute I'm John 1st 2 minute. Thanks for watching.

>> Announcer: Live from Las Vegas! It's theCUBE. Covering Edge 2016. Brought to you by IBM. Here's your host, Dave Vellante. >> Welcome back to IBM Edge everybody. This is theCUBE's fifth year covering IBM Edge. We were at the inaugural Edge five years ago in Orlando. Marc Linster is here and he's joined by Lenley Hensarling. Marc is the Senior Vice President of Product Development. And Lenley is the Senior Vice President of Product Management and Strategy at EDB, Enterprise Database. Gentlemen, welcome to theCUBE. Thanks for coming on. >> Male Voice: Thank you. >> Okay, who wants to start. Enterprise Database, tell us about the company and what you guys are all about. >> Well the company has been around for little over 10 years now. And our job is really to give companies the ability to use Postgres as the platform for their digital business. So think about this, Postgres is a great open source database. Great capabilities for transactional management of data. But also multi-model data management. So think about standard SQL data but think also about document oriented, think about key-value pair. Think about GIS. So a great capability that is very, very robust. Has been around for quite a few years. And is really ready to allow companies to build on them for the new digital business but also to migrate off their existing commercial databases that are too expensive. >> What's the history of Postgres? Can you sort of educate me on that? >> Sort of the same roots back with System R, where DB2 came from, Oracle came from. So Berkeley, that's where the whole thing started out. Postgres is really the successor to Ingres. >> Dave: Umhmm. >> And then it turned into PostgreSQL. And it has been licensed under open source license, the Postgres license since 1996. And it's a very, very vibrant open source community that has been driving forward for many years now. And our view is the best available relational and multi-model database today. >> It's the mainspring of relational database management systems essentially >> Marc: Yeah. >> is what you're saying. And Lindley, from a product standpoint, how do you productize that, open source. >> Open source really, companies that have a distribution of open source for database and operating system, whatever the open source company most people are acquainted with, is Red Hat and Linux right. And so, we do the same thing that they do but for Postgres database. We take the distribution, we add testing, we add some other functionality around it so you can run Postgres responsively as Marc likes to say. So high availability, capability, fail-over management, replication, a backup solution. And instead of leaving it as an exercise for a customer, who wants to use open source, we test all this together. And then we validate it and we give them a complete package with documentation and services that they can access to help them be successful it. >> So if Michael Stonebraker were sitting right here, I say Michael, what do you think about Postgres? I'd say I had to start Vertica because we needed a new way. Yet, sort of PostgreSQL, is the killer remains the killer platform in the industry, doesn't it? >> Male Voice: Umhmm. Why is that? It's interesting when you talk to guys like Stonebraker, it's sort of dogma almost. But yet, customers, talk with their wallet. >> And it is, >> He did a very, very nice job of architecting it. It is a database that is extensible. The reason we add the first JSONB or document oriented implementation in the relational database space is because it was designed to make it easy to add new capabilities, new datatypes, new indexes, et cetera, into the same transactional model. That's why we have JSONB. That's why we have PostGIS. That's why we have key-value pair. So it was really well architected. And when you think about who else, not just Vertica has taken this engine >> Dave: Yeah. >> It is in Netezza, it is in a bunch of other. >> Dave: Master Data. >> Lenley: Greenplum. >> Greenplum yes. So it's a really robust architecture. Very, very nicely designed. It just does the job and it does it really well. Which is, what you want a database to do, right. It's not that exciting but it's really stable. It really works. The data is still there tomorrow. That's what really the requirements are. >> And to translate a little bit, Marc mentioned PostGIS, which is geo spacial capability for the Postgres database. And so we distribute that along with Postgres and test it so that you know it works. And he mentioned H-Store, so that's how you can actually store internet of things data really well into Postgres. And we talk about SQL, noSQL databases, so they're document databases. And the ability to have personalization at the same level you can in a document oriented database but in a structured SQL database are the kinds of things that have been added to Postgres over the years. Again, it's because of the basic architecture that Stonebraker put in place as an object relational database. >> It's so interesting to look at the history of database. Talk about Stonebraker, he's been on a number of times. It's just fascinating to listen to one of the fathers of this industry. But 10 years ago, database was like such a boring topic. And now it's exploded. Now you got Amazon going after Oracle. Oracle fighting the good fight. So many noSQL databases coming in. SQL becoming the killer big data app if you will. >> Male Voice: Umhmm. >> Why all of a sudden did database get so interesting? >> What happened was, application models changed. Led by Facebook, led by Amazon and Google. They said, let's refactor the applications and let's refactor the way we handle storage. >> Dave: Umhmm. >> And that led to the rise of the polyglot of databases is what a lot of people are saying. You have fit for purpose solutions and you may have three or four or five of them in your overall architecture. One thing about Postgres is, we're able to, because of the datatypes support that Marc mentioned, fit into that well. We don't try and do everything so if somebody says, I'm going to use Mongo for data capture, or I'm going to use Cassandra for capturing my internet of things data. We have what we call foreign data wrappers in the Postgres world. We call them just Enterprise DB Adapters but to Mongo, to Casandra, to Hadoop and can do bidirectional data there and just keep that data at rest over there in the other world. But be able to project relational schema onto it. We can push our data into those. We've got a great use case we've been talking about with a customer who had over a petabyte of data. And in the past what you do is, you'd go buy an expensive archiving solution and add that to it. Now, you just use Hadoop distributed file system. Push the data off there as it ages and have a foreign data wrapper that allows you to still query that data when it's out of your basic operational dataset. And move forward. >> Can I call that a connector or? >> Lenley: Yeah, a connector, that's not a bad idea. >> And it's interesting because If you guys remember Hadapt, probably. [Male Voices] Yeah. Yes. >> They came out, they were the connector killer. >> Male Voice: Umhmm. >> And it failed. >> Male Voice: Yeah. >> Seems like connectors are just fine. >> Male Voice: Yeah. >> And one of the really interesting things is, we call it data federation right. With philosophy here is, leave the data where it is. There are some data that should live in Hadoop or Cassandra. If I'm doing an e-commerce site with transactions and click streams, well, the click streams really should live in Hadoop. That the night natural place for them. The transactions should be in a transactional database. With the foreign data wrapper, I can run queries without moving the data, that will allow me to say, well, before you bought the brown teddy bear, which pages did you look at? >> Dave: Yeah. >> And I can do that integrated system and I can do a fit for purpose architecture. And that's what we think is really exciting. >> And that's fundamental to this new sort of programming or application models. >> Male Voice: That's right. >> The one that you were talking about is moving five megabytes of code to a petabyte of data. As opposed to moving data which we know has gravity and speed of light issues and so forth. >> Thank you for that little brief education. Appreciate it. So let's get into your business now, your relationship with IBM. What customers are doing. You mentioned IoT data so talk more about your business and your relationship with IBM and what you guys are doing for customers. >> There are a couple of things. We mentioned Oracle. And there are all the new databases. And then there's your, dare we say, legacy, proprietary databases as well. And people are looking to become more efficient in how they spend. We've done another thing with Postgres. We've added Oracle compatibility in terms of datatypes. So we support all the datatypes that Oracle does. And we support PL/SQL, they're sort of variant of stored procedure language. And implemented a lot of the packages that they have as well. So we can migrate workloads from Oracle over into an open source based solution. And give a lot cost effectiveness options to customers. >> Dave: Steal. This is a way that I can sort of have Oracle licensed database licensed and maintenance avoidance. >> Lenley: Yes. Yeah. >> Where possible, right. >> Where it makes sense. Where it makes sense. >> Obvious my quorum, I keep, but let's face it, the number one cost component of a TCO analysis of an Oracle customer is the database license and maintenance cost. >> Male Voice: That's right. >> It's not the people. One of the few examples I can think of where that's the case. There's always the people cost. [Male Voice] That's right, that's right. IT is very labor intensive. But for an Oracle customer, it's the database license. Cuz they license by Core. >> Male Voice: Yup. Cores are going through the roof. >> Male Voice: That's right. It's been great for Oracle's business. Although, wouldn't you agree, Oracle sees the writing on the wall that the SAS is really sort of the new control point for the industry. You see the acquisition of NetSuite and competition with Workday >> Male Voice: Yup. >> and the like. >> But the database remains the heart of the business. >> And really it's movement to the cloud, both private cloud and public cloud. And so we've been doing work there. We've had public cloud database as a service solution on Amazon for, what, [Marc] Four years. >> Four years, Marc. And have gained a lot experience with that. And were running that sort of running a retail, you can license the database and we'll provision it there. And so what we've done recently is change our perspective and said, let's put this into hands of customers. And let them standup their own database as a service. But also do it in a way that they can choose what workload should go to Amazon and what workload might go to their private cloud, built on open stack. And be able to arbitrage that if you will. Because they now have a way to provision the databases and make a choice about where to put it. >> So that's a bring your own license model that you just talked about? >> Bring your own license model or >> Are you in the Marketplace and, >> We're in the Marketplace in Amazon, where we can supply it that way. But customers have shown a preference for bring your own license. They want to make the best enterprise deal they can with a vendor like us or whomever else. And then have control over it. >> Amazon obviously wants you to be in the Marketplace. I won't even mention but I talked to some CEOs of database companies and they say, you know, we're in the Marketplace but we get in the Marketplace, next thing you know, Amazon is pushing them towards DynamoDB or you know. >> Male Voice: That's right, that's right. >> Now Amazon's come out with Aurora and Oracle migration and you know the intent to go after that business. Amazon's moving up the stack and you got to be careful. >> They are. But the thing about Amazon is that, they're a pure play in the cloud company. >> Dave: Yup. >> And all of the data shows that it's like a mix, it's going to be a hybrid cloud. Half the company in this world [Dave] Not Angie Jassie's data >> Eighty percent of the people in the cloud are going to be on-prem, still continuing their journey through virtualization. >> Dave: Yeah, that's right. >> Let along going to the cloud. But we want to be something that let's them put what they want in the public cloud and let's them manage on the private cloud in the same manner. So they can provision databases with a few clicks. Just like they do on Amazon. But do it in their data center. >> You doing that with Softlayer as well or not yet? >> Lenley: Not yet. >> Marc: Not yet. >> We've built this provisioning capability ourselves. And it came out of the work we did putting up databases on Amazon. >> So what are you guys doing here at Edge. Edge is kind of infrastructure show. Database is infrastructure. >> We're talking about our work with Power. >> Power is a big partner for us. Power is I think very, very interesting for our database customers. Because of the much higher clock speeds and the capabilities that the Power processor has. When I'm looking at Power, I get more oomph out of a single core which really for a database customer is very, very interesting. Because all databases are licensed by Core. >> Dave: Right. >> So it's a much better deal for the customer. And specifically for Postgres, Postgres scales very well with higher clock speeds. So by having, let's say, by growing performance, not by adding more cores but by making the individual cores faster, that plays very, very well to the Postgres capabilities. >> Okay, so you are a Power partner, part of that ecosystem that IBM is appealing to to grow the OpenPOWER base. And what kind of workloads are you seeing your customers demand and where you're having success? >> Across the board. Database is mostly infrastructure capabilities so there's a lot of interest that we're seeing that, for all kinds of applications really. >> What's the typical Power customer look like these days? You got some Oracle, you got some DB2, you guys are running on there, what's the mix? Paint the picture for us. >> I think the typical Power customer is the typical enterprise company. And, [Dave] Little bit of everything. >> It's a little bit of everything. But one of the key things is that, people are also looking at what they've got and the skills they have in place. You were talking about people cost right. [Dave] Yeah. >> And their understanding of management. Their understanding of how to manage the relationship with the vendor even. And then saying, look, how can I move into the new world of digital transformation and start my own private cloud options and things like that in an efficient way. That makes efficient use of hardware I have in place and has a growth curve and new hardware that's coming out that fits my workloads. >> Dave: Umhmm. >> And the profiles that Marc was talking about. >> And also the resources. Which is very interesting when we look at these new digital applications with Postgres. Because you can do so much in Postgres from geographic information systems to document oriented to key-value. But you can do that with your existing developers through existing DBAs. They don't need to go to school to learn a new database. And that's also a very, very, interesting capability. So you can use your existing team to do new stuff. [Male Voice] Yup. >> What's happening in IoT, what problems are you solving there and where's the limit? >> Sensor data collection. >> Lenley: Yeah. Real interesting because sensor data tends to come in all different forms. We have customer who collects temperature sensor, temperature data. But the sensors are all sending different data packets. So because we can do document oriented or key-value, we can easily accommodate that. In the old days with the relational model, I had to do all kinds of tricks to sort of stuff all that into a relational table. My table would be almost empty at the end because I'd have to add columns for every vendor et cetera. Here, now I can use put all that into the same format and provide it for analysis. So that's a real interesting capability. >> And it's interesting too because we've got really strong geo spacial data support. And the intersection of that, with IoT is a big deal. They track your iPhone, they know where we are. They know what's going on. That's sensor data. They know which lights in which building, which you know, louvers that are controlling HVAC are malfunctioning or not. They want to know specifically where it is, not just what the sensor is. And some of that stuff moves around. And it gets replaced in a new place in the building and such. So we're well setup to handle those types of workloads. >> What's interesting, when IBM bought the weather company, [Lenley] Yeah. >> And they thought okay great, they're getting all these data scientists and weather data, that's cool. They can monetize that but it's an IoT play, isn't it? [Male Voice] Right. Right. >> Talk about sensor. >> It's reference data. It's reference data for other company specific IoT plays. To have a broader set of sensors out there in their region and understand what's happening with weather and things. And then play that against what their experience is, managing new building or manufacturing processes, everything. >> So what's the engagement model. I'm a customer, I want to do business with you. How do I do it, how do I engage? >> Well, a lot of our businesses direct with us. Others through partners. And then a lot of customers come to us because they want to get off legacy systems. But really, what they do is, once they understand the database and the capabilities, they say, okay yeah, you can do the Oracle stuff. But what I'm really going to do with you is my new things. Because that's really exciting and it helps me kind of put a lid on the commercial license growth. So maybe I'm not going to get off it, but I will stop growing it. So I will start doing my new stuff on Postgres. Whenever I modernize something, Postgres is going to be my database of choice. If I already open up an application with its whole stack, this is one of the changes I'm going to make. And then the database as service, is very, very interesting. So these four entry vectors and what happens is, quite a few customers after a short time when they started with project or applications, they end up making Postgres as one of their database standards. Not the only one. But they make it one of the database standards so it gets into the catalog and every new project then has to consider Postgres. >> It's interesting, there's a space created as Microsoft sort of put all their wood behind the era of becoming a competitor to high end Oracle. And with this last release, they probably are on there, arguable. But they've also raised their prices too. And they've made the solution more complex. So there's this space that was vacated for like a ton of workloads and Postgres fits in there just about perfectly. We see enterprise after enterprise come to us with a sheet that says, now we're going to get some of this noSQL stuff. We're going to keep Oracle or DB2 over here for these really high end things. Run my financials, run my sales order processing, my manufacturing. And then we got this space in here. We got a slot for relational database and we want to go open source. Because of the cost savings. Because of other factors. It's ability to grow and not be bound to, hey, what if the vendor decides they're going to go for a new cooler thing and make me upgrade. >> Dave: Right. >> And I want to stay there and know that there's still being an investment made. And so there's a vibrant community around it. And it just fits that slot perfectly. >> You got to pay for that digital transformation and all these IoT initiates. You can't just keep pouring [Male Voice] Somehow. >> down to database licenses. [Male Voice] That's right. >> Tell me, we have to leave it there. >> Thanks very much >> Male Voice: Alright. >> for coming to theCUBE. >> Thanks so much. >> We appreciate the time. You welcome. [Male Voice] Enjoy it. Keep it right there buddy. We'll be right back with our next guest. This is theCUBE. We're live from IBM Edge 2016, be right back. (upbeat music)