>>from around the globe. It's the Cube with digital coverage of workplace next made possible by Hewlett Packard Enterprise. >>Hello, everyone. We're here covering workplace next on the Cube For years, you know, we've talked about new ways to work, and it was great thought exercise. And then overnight the pandemic heightened the challenges of creating an effective work force. Most of the executives that we talked to in our survey say that productivity actually has improved since the work from Home Mandate was initiative. But, you know, we're talking not just about productivity, but the well being of our associates and managing the unknown. We're going to shift gears a little bit now. We've heard some interesting real world examples of how organizations are dealing with the rapid change in workplace, and we've heard about some lessons to take into the future. But now we're going to get more practical and look at some of the tools that are available to help you navigate. The changes that we've been discussing and with me to talk about these trends related to the future of work are are are Qadoura, who's the vice president of worldwide sales and go to market for Green Lake at HP Sadat Malik is the VP of I O t and Intelligent Edge at HP and Satish Yarra Valley is the global cloud and infrastructure practice Head at Whip Probe guys welcomes. Good to see you. Thanks for coming on. >>Thanks for having us. >>You're very welcome. Let me start with Sadat. You're coming from Austin, Texas here. So thank you. Stay crazy. As they say in Austin, for the uninitiated, maybe you could talk a little bit about h p E point. Next. It's a strategic component of H p. E. And maybe tell us a little bit about those services. >>Thank you so much for taking the time today. Appreciate everybody's participation here. So absolutely so point Next is HP Services on. This is the 23,000 strong organization globally spread out, and we have a very strong ecosystem of partners that be leveraged to deliver services to our customers. Um, our organization differentiates itself in the market by focusing on digital digital transformation journeys for our customers. For customers looking toe move to a different way off, engaging with its customers, transforming the way its employees work, figuring out a different way off producing the products that it sells to. His customers are changing the way it operationalize these things. For example, moving to the cloud going to a hybrid model, we help them achieve any of these four transformation outcomes. So point next job is toe point. What is next in this digital transformation journey and then partner with our customers to make that happen? So that's what we do. >>Thank you for that. I mean, obviously, you're gonna be seeing a lot of activity around workplace with shift from work from home, changes in the network changes in security. I mean the whole deal. What are some of your top takeaways that you can share with our audience? >>Yeah, they're >>so a lot has been happening in the workplace arena lately. So this is not new, right? This is not something that all of a sudden side happening when Kobe 19 hit, uh, the digital workplace was already transforming before over 19 happened. What over 19 has done is that it has massively accelerated the pace at which this change was happening. So, for example, right remote work was already there before over 19. But now everybody is working remotely so, in many ways, the solution that we have for remote work. They have been strained to appoint, never seen before. Networks that support these remote work environments have been pushed to their limits. Security was already there, right? So security was a critical piece off any off the thinking, any of the frameworks that we had. But now security is pivotal and central. Any discussion that we're having about the workplace environment data is being generated all across the all across the environment that we operated, right? So it's no longer being generated. One place being stored. Another. It's all over the place now. So what Kobe, 19 has done is that the transformation that was already underway in the digital workplace, it has taken that and accelerated it massive. The key take away for me is right that we have to make sure that when we're working with our customers, our clients, we don't just look at the technology aspect of things. We have to look at all the other aspect as well the people in the process aspect off this environment. It is critical that we don't assume that just because the technology is there to address these challenges that I just mentioned. Our people and our processes would be able to handle that as well. We need to bring everybody along. Everybody has different needs, and we need to be able to cater to those needs effectively. So that's my biggest take away. Make sure that the process and the people aspect of things was hand in glove with the technology that we were able to bring to bear here. >>Got it. Thank you. So, ah, let's go to San Francisco, bringing our war to the conversation. You're one of your areas of focus is is HP Green Lake. You guys were early on with the as a service model. Clearly, we've seen Mawr interest in cloud and cloud like models. I wonder if you could just start by sharing. What's Green Lake all about? Where does it fit into this whole workplace? Next, Uh, conversation that we're having? >>Yeah, absolutely. Um HP Green lake effectively is the cloud that comes to your data center to your Coehlo or to your edge, right? We saw with Public Cloud. The public cloud brought a ton of innovations, um, into the sort of hyper scale model. Now, with HP. What we've done is we've said, Look, customers need this level of innovation and this level of, you know, pay as you go economics the, you know, management layer the automation layer not just in a public cloud environment, but also in our customers data center or to the other potential edges or Coehlo scenarios. And what we've done is we've brought together Asada just mentioned the best of our point next services our software management layer as well as H. P. E s rich portfolio of hardware to come together to create that cloud experience. Um, of course, we can't do this without the rich ecosystem around us as well. And so everything from you know, some of our big S I partners like we bro, who also have the virtual desktop expertise or virtual desk that then come together to start helping us launch some of these new workloads supported cloud services such as D. D i eso for my perspective, v. D. I is the most important topic for a lot of our customers right now, especially in sectors like financial services, um, advanced engineering scenarios and health care where they need access to those, uh to their data centers in a very secure way and in a highly cost optimized way as well. >>Well, okay. Thank you. And then let's let's bring in, uh, petition talk a little bit about the ecosystem. I mean, we're pro. That's really kind of your wheelhouse. We've been talking a lot on the cube about moving from an industry of point products to platforms and now ecosystem innovation, Uh, are are mentioned VD I we saw that exploding eso teach. Maybe you could weigh in here and and share with us what you're seeing in the market and specifically around ecosystem. >>As we all know, the pandemic has redefined the way we collaborate to support this collaboration. We have set up huge campuses and office infrastructure In summary, our industry has centralized approach. Now, the very premise of the centralization bringing people together for work has changed. This evolving workspace dynamics have triggered the agency to reimagine the workspace strategy. CEO, CEO S and C H R ose are all coming together to redefine the business process and find new ways off engaging with customers and employees as organizations embrace work from home for the foreseeable future. Customer need to create secure by design workspaces for remote working environments. With the pro virtual disk platform, we can help create such seamless distal workspaces and enable customers to connect, collaborate and communicate with ease from anywhere securely. They're consistent user experience. Through this platform led approach, we are able to utter the market demands which are focused on business outcomes. >>Okay, and this is the specifics of this hard news that you're talking about Video on demand and Citrix coming together with your ecosystem. H p E were pro and again, the many partners that you work with is that correct? >>Well, actually, Dave, we see a strong playoff ecosystem partners coming together to achieve transformative business outcomes. As Arbor said earlier, HP and Wipro have long standing partnership, and today's announcement around HP Green Lake is an extension off this collaboration, where we provide leverage HP Green Leg Andre Pro, which elders platform to offer video as a service in a paper user model. Our aim is to enable customers fast track there. It is still works based transformation efforts by eliminating the need to support upfront capital investments and old provisioning costs while allowing customers to enjoy the benefit off compromise, control, security and compliance. Together, we have implemented our solution across various industry segments and deliver exceptional customer experiences by helping customer businesses in their workspace. Transformation journeys by defining their workspace strategy with an intelligent, platform led approach that enables responsiveness, scalability and resilience. It's known that Wipro is recognized as a global leader in the distal workspace and video I, with HP being a technology leader, enabling us with high level of program ability on integration capabilities. We see tremendous potential to jointly address the industry challenges as we move forward. >>Excellent. Uh, sad. I wanna come back to you. We talk a lot about the digital business, the mandate for digital business, especially with the pandemic. Let's talk about data. Earlier this year, HP announced the number of solutions that used data to help organizations work more productively safely. You know, the gamut talk about data and the importance of data and what you guys were doing there specifically, >>Yeah, that's a great question. So that is fundamental to everything that we're doing in the workplace arena, right? So from a technology perspective that provides us with the wherewithal to be able to make all the changes that we want to make happen for the people in the process side of things. So the journey that we've been on this past year is a very interesting one. Let me share with the audience a little bit of what's been going on on the ground with our customers. Um, what's what's been happening in the field? So when the when Kobe 19 hit right, a lot of our customers were subjected to these shutdown, which were very pervasive, and they had to stop their operations. In many cases, they had to send their employees home. So at that point, HB stepped in the point. Next organization stepped in and helped these customers set up remote work out options, which allowed them to keep their businesses going while they handle these shutdowns. Fast forward. Six months and the shutdown. We're starting to get lifted and our customers were coming back to us and saying to us that Hey, we would now like to get a least a portion off our workforce back to the normal place of work. But we're concerned that if we do that, it's gonna jeopardize their safety because off the infection concerned that were there. So what we did was that we built a cities or five solutions using various types of video analytics and data analysis analysis technologies that allowed these customers to make that move. So these five solutions, uh, let me walk, walk our customers and our clients and audience through those. The first two of these solutions are touchless entry and fever detection. So this is the access control off your premise, right? So to make sure that whoever is entering the building that's in a safe manner and any infection concerned, we stop it at the very get go once the employees inside the workplace, the next thing that we have is a set of two solutions. What one is social distance tracing and tracking, and the other one is workplace alerting. What these two solutions do is that they use video analytics and data technology is to figure out if there is a concern with employees adhering to the various guidelines that are in place on alerting the employees and the employers if there is any infringement happening which could risk overall environment. Finally, we realized right that irrespective off how much technology and process we put in place. Not everybody will be able to come into the normal place of work. So what we have done is that the first solution that we have is augmented reality and visual remote guidance. This solution uses a our technologies allow. People were on site to take advantage of the expertise that resides offsite to undertake complex task task, which could be as complex as overhauling a machine on ah factory floor using augmented reality where somebody off site who's an expert in that machine is helping somebody on site data has become central to a lot of the things that we do. But as I said, technology is one aspect of things. So ultimately the people process technology continuum has to come together to make these solutions real for our customers. >>Thank you, Arwa. We just have just about 30 seconds left and I wonder if you could close on. We're talking about cloud hybrid. Uh, everybody's talking about hybrid. We're talking about the hybrid workplace. What do you see for the for the future over the next 2345 years? >>Absolutely. And I think you're right, Dave. It is, ah, hybrid world. It's a multi cloud world. Ultimately, what our customers want is the choice and the flexibility to bring in the capabilities that drive the business outcomes that they need to support. And that has multiple dimensions, right? It's making sure that they are minimizing their egress costs, right. And many of our on Prem solutions do give them that flexibility. It is the paper use economics that we talked about. It is about our collective capability as an ecosystem to come together. You know, with Citrix and NVIDIA with R s I partner we pro and the rich heritage of HP es services as well as hardware to bring together these solutions that are fully managed on behalf of our customers so that they can focus their staff their i t capabilities on the products and services they need to deliver to their customers. >>Awesome. Guys, I wish we had more time. We got to go day volonte for the cube. Keep it right there. Lots of great more content coming your way. >>Yeah,

>>from around the globe. It's the Cube with digital coverage of enterprise data automation an event Siri's brought to you by Iot. Tahoe. >>Okay, we're back. Welcome back to data Automated. A J ahora is CEO of I o Ta ho, JJ. Good to see you. How have things in London? >>Big thing. Well, thinking well, where we're making progress, I could see you hope you're doing well and pleasure being back here on the Cube. >>Yeah, it's always great to talk to. You were talking enterprise data automation. As you know, with within our community, we've been pounding the whole data ops conversation. Little different, though. We're gonna We're gonna dig into that a little bit. But let's start with a J how you've seen the response to Covert and I'm especially interested in the role that data has played in this pandemic. >>Yeah, absolutely. I think everyone's adapting both essentially, um, and and in business, the customers that I speak to on day in, day out that we partner with, um they're busy adapting their businesses to serve their customers. It's very much a game of and showing the week and serve our customers to help their customers um, you know, the adaptation that's happening here is, um, trying to be more agile, kind of the most flexible. Um, a lot of pressure on data. A lot of demand on data and to deliver more value to the business, too. Serve that customer. >>Yeah. I mean, data machine intelligence and cloud, or really three huge factors that have helped organizations in this pandemic. And, you know, the machine intelligence or AI piece? That's what automation is all about. How do you see automation helping organizations evolve maybe faster than they thought they might have to >>Sure. I think the necessity of these times, um, there's there's a says a lot of demand doing something with data data. Uh huh. A lot of a lot of businesses talk about being data driven. Um, so interesting. I sort of look behind that when we work with our customers, and it's all about the customer. You know, the mic is cios invested shareholders. The common theme here is the customer. That customer experience starts and ends with data being able to move from a point that is reacting. So what the customer is expecting and taking it to that step forward where you can be proactive to serve what that customer's expectation to and that's definitely come alive now with they, um, the current time. >>Yes. So, as I said, we've been talking about data ops a lot. The idea being Dev Ops applied to the data pipeline. But talk about enterprise data automation. What is it to you and how is it different from data off? >>Yeah, Great question. Thank you. I am. I think we're all familiar with felt more more awareness around. So as it's applied, Teoh, uh, processes methodologies that have become more mature of the past five years around devil that managing change, managing an application, life cycles, managing software development data about, you know, has been great. But breaking down those silos between different roles functions and bringing people together to collaborate. Andi, you know, we definitely see that those tools, those methodologies, those processes, that kind of thinking, um, landing itself to data with data is exciting. We're excited about that, Andi shifting the focus from being I t versus business users to you know who are the data producers. And here the data consumers in a lot of cases, it concert in many different lines of business. So in data role, those methods those tools and processes well we look to do is build on top of that with data automation. It's the is the nuts and bolts of the the algorithms, the models behind machine learning that the functions. That's where we investors our R and D and bringing that in to build on top of the the methods, the ways of thinking that break down those silos on injecting that automation into the business processes that are going to drive a business to serve its customers. It's, um, a layer beyond Dev ops data ops. They can get to that point where well, I think about it is, Is the automation behind the automation we can take? I'll give you an example. Okay, a bank where we did a lot of work to do make move them into accelerating that digital transformation. And what we're finding is that as we're able to automate the jobs related to data a managing that data and serving that data that's going into them as a business automating their processes for their customer. Um, so it's it's definitely having a compound effect. >>Yeah, I mean I think that you did. Data ops for a lot of people is somewhat new to the whole Dev Ops. The data ops thing is is good and it's a nice framework. Good methodology. There is obviously a level of automation in there and collaboration across different roles. But it sounds like you're talking about so supercharging it, if you will, the automation behind the automation. You know, I think organizations talk about being data driven. You hear that? They have thrown around a lot of times. People sit back and say, We don't make decisions without data. Okay? But really, being data driven is there's a lot of aspects there. There's cultural, but it's also putting data at the core of your organization, understanding how it effects monetization. And, as you know, well, silos have been built up, whether it's through M and a, you know, data sprawl outside data sources. So I'm interested in your thoughts on what data driven means and specifically Hi, how Iot Tahoe plays >>there. Yeah, I'm sure we'll be happy. That look that three David, we've We've come a long way in the last four years. We started out with automating some of those simple, um, to codify. Um, I have a high impact on organization across the data, a data warehouse. There's data related tasks that classify data on and a lot of our original pattern. Senai people value that were built up is is very much around. They're automating, classifying data across different sources and then going out to so that for some purpose originally, you know, some of those simpler I'm challenges that we have. Ah, custom itself, um, around data privacy. You know, I've got a huge data lake here. I'm a telecoms business. I've got millions of six subscribers. Um, quite often the chief data office challenges. How do I cover the operational risk? Where, um, I got so much data I need to simplify my approach to automating, classifying that data. Recent is you can't do that manually. We can for people at it. And the the scale of that is is prohibitive, right? Often, if you had to do it manually by the time you got a good picture of it, it's already out of date. Then, starting with those those simple challenges that we've been able to address, we're then going on and build on that to say, What else do we serve? What else do we serve? The chief data officer, Chief marketing officer on the CFO. Within these times, um, where those decision makers are looking for having a lot of choices in the platform options that they say that the tooling they're very much looking for We're that Swiss army. Not being able to do one thing really well is is great, but more more. Where that cost pressure challenge is coming in is about how do we, um, offer more across the organization, bring in those business lines of business activities that depend on data to not just with a T. Okay, >>so we like the cube. Sometimes we like to talk about Okay, what is it? And then how does it work? And what's the business impact? We kind of covered what it is but love to get into the tech a little bit in terms of how it works. And I think we have a graphic here that gets into that a little bit. So, guys, if you bring that up, I wonder if you could tell us and what is the secret sauce behind Iot Tahoe? And if you could take us through this slot. >>Sure. I mean, right there in the middle that the heart of what we do It is the intellectual property. Yeah, that was built up over time. That takes from Petra genius data sources Your Oracle relational database, your your mainframe. If they lay in increasingly AP eyes and devices that produce data and that creates the ability to automatically discover that data, classify that data after it's classified them have the ability to form relationships across those different, uh, source systems, silos, different lines of business. And once we've automated that that we can start to do some cool things that just puts a contact and meaning around that data. So it's moving it now from bringing data driven on increasingly well. We have really smile, right people in our customer organizations you want do some of those advanced knowledge tasks, data scientists and, uh, quants in some of the banks that we work with. The the onus is on, then, putting everything we've done there with automation, pacifying it, relationship, understanding that equality policies that you apply to that data. I'm putting it in context once you've got the ability to power. A a professional is using data, um, to be able to put that data and contacts and search across the entire enterprise estate. Then then they can start to do some exciting things and piece together the tapestry that fabric across that different systems could be crm air P system such as s AP on some of the newer cloud databases that we work with. Snowflake is a great Well, >>yes. So this is you're describing sort of one of the one of the reasons why there's so many stove pipes and organizations because data is gonna locked in the silos of applications. I also want to point out, you know, previously to do discovery to do that classification that you talked about form those relationship to glean context from data. A lot of that, if not most of that in some cases all that would have been manual. And of course, it's out of date so quickly. Nobody wants to do it because it's so hard. So this again is where automation comes into the the the to the idea of really becoming data driven. >>Sure. I mean the the efforts. If we if I look back, maybe five years ago, we had a prevalence of daily technologies at the cutting edge. Those have said converging me to some of these cloud platforms. So we work with Google and AWS, and I think very much is, as you said it, those manual attempts to try and grasp. But it is such a complex challenge at scale. I quickly runs out of steam because once, um, once you've got your hat, once you've got your fingers on the details Oh, um, what's what's in your data estate? It's changed, you know, you've onboard a new customer. You signed up a new partner, Um, customer has no adopted a new product that you just Lawrence and there that that slew of data it's keeps coming. So it's keeping pace with that. The only answer really is is some form of automation. And what we found is if we can tie automation with what I said before the expertise the, um, the subject matter expertise that sometimes goes back many years within an organization's people that augmentation between machine learning ai on and on that knowledge that sits within inside the organization really tends to involve a lot of value in data? >>Yes, So you know Well, a J you can't be is a smaller company, all things to all people. So your ecosystem is critical. You working with AWS? You're working with Google. You got red hat. IBM is as partners. What is attracting those folks to your ecosystem and give us your thoughts on the importance of ecosystem? >>Yeah, that's that's fundamental. So I mean, when I caimans, we tell her here is the CEO of one of the, um, trends that I wanted us to to be part of was being open, having an open architecture that allowed one thing that was nice to my heart, which is as a CEO, um, a C I O where you've got a budget vision and you've already made investments into your organization, and some of those are pretty long term bets. They should be going out 5 10 years, sometimes with CRM system training up your people, getting everybody working together around a common business platform. What I wanted to ensure is that we could openly like it using ap eyes that were available, the love that some investment on the cost that has already gone into managing in organizations I t. But business users to before So part of the reason why we've been able to be successful with, um, the partners like Google AWS and increasingly, a number of technology players. That red hat mongo DB is another one where we're doing a lot of good work with, um, and snowflake here is, um it's those investments have been made by the organizations that are our customers, and we want to make sure we're adding to that, and they're leveraging the value that they've already committed to. >>Okay, so we've talked about kind of what it is and how it works, and I want to get into the business impact. I would say what I would be looking for from from this would be Can you help me lower my operational risk? I've got I've got tasks that I do many year sequential, some who are in parallel. But can you reduce my time to task? And can you help me reduce the labor intensity and ultimately, my labor costs? And I put those resources elsewhere, and ultimately, I want to reduce the end and cycle time because that is going to drive Telephone number R. A. Y So, um, I missing anything? Can you do those things? And maybe you could give us some examples of the tiara y and the business impact. >>Yeah. I mean, the r a y David is is built upon on three things that I mentioned is a combination off leveraging the existing investment with the existing state, whether that's home, Microsoft, Azure or AWS or Google IBM. And I'm putting that to work because, yeah, the customers that we work with have had made those choices. On top of that, it's, um, is ensuring that we have you got the automation that is working right down to the level off data, a column level or the file level so we don't do with meta data. It is being very specific to be at the most granular level. So as we've grown our processes and on the automation, gasification tagging, applying policies from across different compliance and regulatory needs, that an organization has to the data, everything that then happens downstream from that is ready to serve a business outcome. It could be a customer who wants that experience on a mobile device. A tablet oh, face to face within, within the store. I mean game. Would you provision the right data and enable our customers do that? But their customers, with the right data that they can trust at the right time, just in that real time moment where decision or an action is being expected? That's, um, that's driving the r a y two b in some cases, 20 x but and that's that's really satisfying to see that that kind of impact it is taking years down to months and in many cases, months of work down to days. In some cases, our is the time to value. I'm I'm impressed with how quickly out of the box with very little training a customer and think about, too. And you speak just such a search. They discovery knowledge graph on DM. I don't find duplicates. Onda Redundant data right off the bat within hours. >>Well, it's why investors are interested in this space. I mean, they're looking for a big, total available market. They're looking for a significant return. 10 X is you gotta have 10 x 20 x is better. So so that's exciting and obviously strong management and a strong team. I want to ask you about people and culture. So you got people process technology we've seen with this pandemic that processes you know are really unpredictable. And the technology has to be able to adapt to any process, not the reverse. You can't force your process into some static software, so that's very, very important. But the end of the day you got to get people on board. So I wonder if you could talk about this notion of culture and a data driven culture. >>Yeah, that's that's so important. I mean, current times is forcing the necessity of the moment to adapt. But as we start to work their way through these changes on adapt ah, what with our customers, But that is changing economic times. What? What we're saying here is the ability >>to I >>have, um, the technology Cartman, in a really smart way, what those business uses an I T knowledge workers are looking to achieve together. So I'll give you an example. We have quite often with the data operations teams in the companies that we, um, partnering with, um, I have a lot of inbound enquiries on the day to day level. I really need this set of data they think it can help my data scientists run a particular model? Or that what would happen if we combine these two different silence of data and gets the Richmond going now, those requests you can, sometimes weeks to to realize what we've been able to do with the power is to get those answers being addressed by the business users themselves. And now, without without customers, they're coming to the data. And I t folks saying, Hey, I've now built something in the development environment. Why don't we see how that can scale up with these sets of data? I don't need terabytes of it. I know exactly the columns and the feet in the data that I'm going to use on that gets seller wasted in time, um, angle to innovate. >>Well, that's huge. I mean, the whole notion of self service and the lines of business actually feeling like they have ownership of the data as opposed to, you know, I t or some technology group owning the data because then you've got data quality issues or if it doesn't line up there their agenda, you're gonna get a lot of finger pointing. So so that is a really important. You know a piece of it. I'll give you last word A J. Your final thoughts, if you would. >>Yeah, we're excited to be the only path. And I think we've built great customer examples here where we're having a real impact in in a really fast pace, whether it helping them migrate to the cloud, helping the bean up their legacy, Data lake on and write off there. Now the conversation is around data quality as more of the applications that we enable to a more efficiently could be data are be a very robotic process automation along the AP, eyes that are now available in the cloud platforms. A lot of those they're dependent on data quality on and being able to automate. So business users, um, to take accountability off being able to so look at the trend of their data quality over time and get the signals is is really driving trust. And that trust in data is helping in time. Um, the I T teams, the data operations team, with do more and more quickly that comes back to culture being out, supply this technology in such a way that it's visual insensitive. Andi. How being? Just like Dev Ops tests with with a tty Dave drops putting intelligence in at the data level to drive that collaboration. We're excited, >>you know? You remind me of something. I lied. I don't want to go yet. It's OK, so I know we're tight on time, but you mentioned migration to the cloud. And I'm thinking about conversation with Paula from Webster Webster. Bank migrations. Migrations are, you know, they're they're a nasty word for for organizations. So our and we saw this with Webster. How are you able to help minimize the migration pain and and why is that something that you guys are good at? >>Yeah. I mean, there were many large, successful companies that we've worked with. What's There's a great example where, you know, I'd like to give you the analogy where, um, you've got a lot of people in your teams if you're running a business as a CEO on this bit like a living living grade. But imagine if those different parts of your brain we're not connected, that with, um, so diminish how you're able to perform. So what we're seeing, particularly with migration, is where banks retailers. Manufacturers have grown over the last 10 years through acquisition on through different initiatives, too. Um, drive customer value that sprawl in their data estate hasn't been fully dealt with. It sometimes been a good thing, too. Leave whatever you're fired off the agent incent you a side by side with that legacy mainframe on your oracle, happy and what we're able to do very quickly with that migration challenges shine a light on all the different parts. Oh, data application at the column level or higher level if it's a day late and show an enterprise architect a CDO how everything's connected, where they may not be any documentation. The bright people that created some of those systems long since moved on or retired or been promoted into so in the rose on within days, being out to automatically generate Anke refreshed the states of that data across that man's game on and put it into context, then allows you to look at a migration from a confidence that you did it with the back rather than what we've often seen in the past is teams of consultant and business analysts. Data around this spend months getting an approximation and and a good idea of what it could be in the current state and try their very best to map that to the future Target state. Now, without all hoping out, run those processes within hours of getting started on, um well, that picture visualize that picture and bring it to life. You know, the Yarra. Why, that's off the bat with finding data that should have been deleted data that was copies off on and being able to allow the architect whether it's we're working on gcb or migration to any other clouds such as AWS or a multi cloud landscape right now with yeah, >>that visibility is key. Teoh sort of reducing operational risks, giving people confidence that they can move forward and being able to do that and update that on an ongoing basis, that means you can scale a J. Thanks so much for coming on the Cube and sharing your insights and your experience is great to have >>you. Thank you, David. Look towards smoking in. >>Alright, keep it right there, everybody. We're here with data automated on the Cube. This is Dave Volante and we'll be right back. Short break. >>Yeah, yeah, yeah, yeah