>>Live from Miami, Florida. It's the cube covering IBM's data and AI forum brought to you by IBM. >>We're back in Miami. You're watching the cube, the leader in live tech coverage, and we're covering the IBM data and AI forum in the port of Miami. Mateus Fuka is here, he's the director of offering management for hybrid data management. Everything data. But see, it's great to see you. It's great to have you. So be here with you. We're going to talk database, we're gonna talk data warehouse, everything. Data, you know, did the database market, you know, 10 years ago, 12 years, it was kind of boring. Right. And now it's like data's everywhere. Database is exploding. What's your point of view on what's going on in the marketplace? You know, I mean it's funny too. You used to it boring because I think it's the boring stuff that really matters nowadays to get, get things to where you get people to value with the solutions you want to be or the modernization. >>Thea. Yeah. Seeking to do on the data estates. Um, the challenge that you have in embracing multi-cloud data architectures. So to get, to get to, well you have to, do, I have to take care of the boring stuff. How real is multi-cloud? I mean, I know multi-cloud is, is real and that everybody has multiple clouds. But is multi-cloud a strategy or is it a sort of a symptom of multi-vendor and it just, we could have ended up here with the shadow it and everything else. >> I think it's a reality and yes, it should be a strategy, but I think more more clients and not they find themselves being exposed to this as a reality with different lines of businesses, acquiring data, um, estates running on different locations, different clouds, you know, and then companies have challenge if you want to bring it all together and actually the value of that data, um, and make it available for analytics or AI solutions. >>You know, you've got to have a strategy. >> So IBM is one of the few companies that has both a cloud and an aggressive multi-cloud strategy. Um, you know, Amazon's got outpost a little bit here and Microsoft I guess has some stuff, uh, a but, but generally speaking, uh, Oracle has got a little bit here but IBM has both a cloud. So you'd love people to come into your cloud, but you recognize not everybody's gonna come in your club. So you have an aggressive multi-cloud strategy. Why is that? What's the underpinning of that strategy? Is it openness? Is it just market, you know, total available market? Why? So first of all, yes, we have a, we have a strong portfolio on IBM cloud and we think, you know, it's the best in terms of, you know, integration with other cloud services, the performance you get on the different data services. >>But we also have a strategy that says we want to be our clients want to go. And many clients might have committed already on a strategic level to a different cloud, whether that's AWS, you know, why IBM cloud or Asia. And so we want to be ready as clients want to go. And our commitment is to offer them a complete portfolio of data services that support different workloads. And a complete portfolio in terms of, um, your, the IBM, uh, hope heavy set of technologies as well as open source technologies, give clients choice but then make them available across that universe of multicloud hybrid cloud on premise in a way that they get a consistent experience. And you know, I mean you are familiar with the term. Oh, you divide and conquer, right? I like to talk about it as uh, you know, um, unify to conquer. >>So our, our mission is really unified experience and unified the access to different capabilities available across multicloud architects. So is that really the brand promise gotta unify across clouds? Absolutely. That's our mission. And what's the experience like today and what is sort of the optimal outcome that you guys are looking for? Uh, being able to run any database on any cloud anywhere. Describe that. >> So I think, um, you'd be talking about chapter one and two off the cloud, right? When it, when it comes to chapter one in my, in my view, chapter one was very much about attracting people to the cloud by offering them a set of managed services that take away the management headaches and you know, the, the infrastructure, uh, management aspects. Um, but when you think about chapter two, when you think about how to run, uh, mission critical workloads on, on a cloud or on premise, um, you know, you want to have the ability to integrate data States that run in different environments and we think that OpenShift is leveling the playing field by avoiding location, by, by giving clients the ability to basically abstract from PI, Teri cloud infrastructure services and mechanisms. >>And that gives them freedom of action. They can, they can deploy a certain workload in one in one place and then decide six months later that they are better off moving that workload somewhere else. Yes. >> So OpenShift is the linchpin, absolutely. That cross-cloud integration, is that right? Correct. And with the advent of the rise of the operator, I think you see, you know, you see, um, the industry closing the gap between the value proposition of a fully managed service and what a client managed open shift based environment can deliver in terms of automation, simplicity and annual Oh value. Let's talk about the database market and you're trying to, what's happening? You've got, you know, transactional database, you've got analytic database, you've got legacy data warehouses, you've got new, emerging, emerging, you know, databases that are handling unstructured data. You got to know sequel, not only sequel lay out the landscape and where, what's IBM strategy in the database space? >>So our strategy has, has, so starting with the DB to family, right? We have introduced about two one, two years ago we introduced somebody called Tacoma sequel engine. That gives you a consistent, um, experience in from an application and user perspective in the way you consume, um, data for different workload types. Whether that's transactional data, um, analytical use cases, speak data overdue or fast data solution events, different data architectures, everything, you know, with a consistent experience from a management perspective, from a, from a working behavior perspective in the way you interact with, with this as an application. And, and not only that, but also then make that available on premises in the cloud, fully managed or now open shift based on any cloud. Right. So our, our, I would say our commitment right now is very much focusing on leveraging OpenShift, leveraging cloud pick for data as a platform to deliver all these capabilities DB to an open source in a unified and consistent. >>Uh, I would say with a unified and consistent experience on anybody's cloud, it's like what's in any bag was first, you know, like six months ago when we announced it. And I think now for us doing the same with data and making that data, make it easy for people to access state our way every to the sides is really, but Ts, what's IBM's point of view on, on the degree of integration that you have to have in that stack from hardware and software. So people, some people would argue, well you have to have the same control plane, same data plane, same hardware, same software, same database on prem as you have in the cloud. What's your thoughts on that degree of homogeneity that's required to succeed? So I think it's certainly something that, uh, companies strive to get to simplify the data architectures, unify, consolidate, reduced the number of data sources that you have to deal with. >>But the reality is that the average enterprise client has 168 different data services they have to incorporate, right? So to me it's a moving target and while you want to consolidate, you will never fully get there. So I think our approach is we want to give to client choice best different choice in terms of technologies for for the same workload type. Potentially, whether it's a post test for four transactional workloads for TB, two for transactional workloads, whatever fits the bill, right? And then at the same time, um, at the same time abstract or unify on top of that by, by when you think about operators and OpenShift, for instance, we invest in a, in um, in operators leveraging a consistent framework that basically provides, you know, homogeneous set of interfaces by which people could deploy and life cycle manager Postgres instance or DB two instance. >>So you need only one skillset to manage all these different data services and you know, it reduces total cost of ownership is it provides more agility and, and you know, you know, accelerates time to value for this client. So you're saying that IBM strategy recognizes the heterogeneity within the client base, right? Um, you're not taking, even though you might have a box somewhere in the portfolio, but you're not a, you need this box only strategy. The God box. This is, this is the hammer and every opportunity is a nail. Yeah, we have way beyond that. So we, we are much more open in the way we embrace open source and we bring open source technologies to our enterprise clients and we invest in integration of these different technologies so they can, the value of those can be actuated much more in a much more straightforward fashion. >>The thing about cloud pay for data and the ability to access data insights in different open Sozo, different depositories, IBM, one third party, but then make that data accessible through data virtualization or full governance, applying governance to the data so that data scientists can actually get reef that data for, for his work. That is really important. Can you argue that that's less lock-in than say like they say the God box approach or the cloud only approach? Yeah, absolutely. Because how so? How so? Because, well, because we give you choice to begin with, right? And it's not only choice in terms of the data services and the different technologies that are available, but also in terms of the location where you deploy these data services and how you run them. Okay. So to me it's all about exit strategies. If I go down a path and a path doesn't work for me, how do I get out? >>Exactly. Um, is that a concern of customers in terms of risk management? Yeah. I think, look, every, every costume out there, I daresay, you know, has a data strategy and every customer needs to make some decisions. But you know, there's only so much information you have today to make that decision. But as you learn more, your decision might change six months down the road. And you know, how to preserve that agility as a business to do course corrections I think is really important. So, okay, a hypothetical that this happens every day. You've got a big portfolio companies, they've done a lot of M and a, they've got, you know, 10 different databases that they're running. They got different clouds that they're using, they've got different development teams using, using different tooling, certainly different physical infrastructure. And they really haven't had a strategy to bring it all together. >>Uh, you're hired as the, uh, the data architect or the CTO of the company and say, but Tia's, the CEO says, fix this problem. You're not, we're not taking advantage, uh, and leveraging our data. Where do you start? So of course, being IBM, I would recommend to start with clapping for data as the number one data platform out there because eventually every component will want to capitalize on the value that the data represents. It's not just about a data layer is not just about a database, it's about an indicated solutions tech that gets people to do analytics over the data, the life insights from the data. That's number one. But even if you are, you know, if, if, if it's not I the IBM stack, right, I would always recommend to the client to think about a strategy that that allows for the flexibility change to change course wide and move workloads from one location to another or move data from one technology stack to another. >>And I think that that kind of, you know, that agility and flexibility and, um, translate into, um, risk mitigation strategies that every client should think about. So cloud pack for data, it's okay, let's start there. I'm gonna, I'm gonna, I'm gonna install that, or I'm gonna access that in, into the cloud. And then what do I have to do as a customer to take advantage of that? Do I just have to point it at my data stores? What are the prerequisites? Yeah. So let's say you deploy that on IBM cloud, right? Then you have, you usually are invested already. So you have data, large data estates either residing on share is already in the cloud. You can pull those, those, those datasets in remotely without really moving the workload of the data sets into a cloud pixel, data managed environment by using technologies like data virtualization, right? >>Or using technologies like data stage and ETL capabilities, um, to access the data. But you can also, as you modernize and you build your next next generation application, you can do that within that managed environment with OpenShift. And, and that's what most people want to do. They want to do a digital transformation. They want to modernize the workloads, but we want to leverage the existing investments that they have been making over the last decade. Okay. So, but there's a discovery phase, right, where you bring in cloud pack for data to say, okay, what do I have? Yup, go find it. And then it's bringing in necessary tooling on the, on the diff with the development side with things like OpenShift and then, and then what it's magically virtualizes my data is that, so just on that point, I think you know, the, what made us much more going forward for his clients is how they can incorporate different datasets with adding insure in open source technologies or, or DB two on a third party vendor said, I don't want to mention right now, but, but what matters more is, so how do I make data accessible? >>How do I discover the data set in a way that I can automatically generate metadata? So I have a business glossary, I have metadata and I understand various data sets. Lyft, that's their vision objective business technology objectives. To be able to do that and to what's watching knowledge catalog, which is part of topic for data is a core component that helps you with dead auto discover the metadata generation basically generating, okay, adding data sets in a way that they are now visible to the data scientists and the ultimate end user. What really matters and I think what is our vision overall is the ability to service the ultimate end user medicine developer, a data scientist, so business analysts so that they can get a chip done without depending on it. Yeah, so that metadata catalog is part of the secret sauce that'll that that allows the system to know what data lives, where, how to get to it and and how to join it. >>Since one of the core elements of that, of that integrated platform and solution state board. What I think is really key here is the effort we spend in integrating these different components so that it is, it is, it looks seamlessly, it is happening in an automated fashion that as much as possible and it delivers on that promise of a self service experience for that person that sits at the very end of that. Oh, if that chain right, but to your sex so much for explaining that QA for coming on the cube. Great to meet you. All right. Keep it right there everybody. We'll be back with our next guest right after this short break. You're watching the cube from the IBM data and AI forum in Miami. We'll be right back.