>>Yeah, yeah. Welcome back to the third session in our building, A vibrant data ecosystem track. This session is unleash the power of your cloud data warehouse. So what comes after you've moved your data to the cloud in this session will explore White Enterprise Analytics is finally ready for the cloud, and we'll discuss how you can consume Enterprise Analytics in the very same way he would cloud services. We'll also explore where analytics meets cloud and see firsthand how thought spot is open for everyone. Let's get going. I'm happy to say we'll be hearing from two folks from thought spot today, Michael said Cassie, VP of strategic partnerships, and Vika Valentina, senior product marketing manager. And I'm very excited to welcome from our partner at AWS Gal Bar MIA, product engineering manager with Red Shift. We'll also be sharing a live demo of thought spot for BTC Marketing Analytics directly on Red Shift data. Gal, please kick us off. >>Thank you, Military. And thanks. The talks about team and everyone attending today for joining us. When we talk about data driven organizations, we hear that 85% of businesses want to be data driven. However, on Lee. 37% have been successful in We ask ourselves, Why is that and believe it or not, Ah, lot of customers tell us that they struggled with live in defining what being data driven it even means, and in particular aligning that definition between the business and the technology stakeholders. Let's talk a little bit. Let's look at our own definition. A data driven organization is an organization that harnesses data is an asset. The drive sustained innovation and create actionable insights. The super charge, the experience of their customers so they demand more. Let's focus on a few things here. One is data is an asset. Data is very much like a product needs to evolve sustained innovation. It's not just innovation innovation, it's sustained. We need to continuously innovate when it comes to data actionable insights. It's not just interesting insights these air actionable that the business can take and act upon, and obviously the actual experience we. Whether whether the customers are internal or external, we want them to request Mawr insights and as such, drive mawr innovation, and we call this the for the flywheel. We use the flywheel metaphor here where we created that data set. Okay, Our first product. Any focused on a specific use case? We build an initial NDP around that we provided with that with our customers, internal or external. They provide feedback, the request, more features. They want mawr insights that enables us to learn bringing more data and reach that actual data. And again we create MAWR insights. And as the flywheel spins faster, we improve on operational efficiencies, supporting greater data richness, and we reduce the cost of experimentation and legacy environments were never built for this kind of agility. In many cases, customers have struggled to keep momentum in their fleet, flywheel in particular around operational efficiency and experimentation. This is where Richie fits in and helps customer make the transition to a true data driven organization. Red Shift is the most widely used data warehouse with tens of thousands of customers. It allows you to analyze all your data. It is the only cloud data warehouse that sits, allows you to analyze data that sits in your data lake on Amazon, a street with no loading duplication or CTL required. It is also allows you to scale with the business with its hybrid architectures it also accelerates performance. It's a shared storage that provides the ability to scale toe unlimited concurrency. While the UN instant storage provides low late and say access to data it also provides three. Key asks that customers consistently tell us that matter the most when it comes to cost. One is usage based pricing Instead of license based pricing. Great value as you scale your data warehouse using, for example, reserved instances they can save up to 75% compared to on the mind demand prices. And as your data grows, infrequently accessed data can be stored. Cost effectively in S three encouraged through Amazon spectrum, and the third aspect is predictable. Month to month spend with no hitting charges and surprises. Unlike and unlike other cloud data warehouses, where you need premium versions for additional enterprise capabilities. Wretched spicing include building security compression and data transfer. >>Great Thanks. Scout um, eso. As you can see, everybody wins with the cloud data warehouses. Um, there's this evolution of movement of users and data and organizations to get value with these cloud data warehouses. And the key is the data has to be accessible by the users, and this data and the ability to make business decisions on the data. It ranges from users on the front line all the way up to the boardroom. So while we've seen this evolution to the Cloud Data Warehouse, as you can see from the statistic from Forrester, we're still struggling with how much of that data actually gets used for analytics. And so what is holding us back? One of the main reasons is old technology really trying to work with today's modern cloud data warehouses? They weren't built for it. So you run into issues of trying to do data replication, getting the data out of the cloud data warehouse. You can do analysis and then maintaining these middle layers of data so that you can access it quickly and get the answers you need. Another issue that's holding us back is this idea that you have to have your data in perfect shape with the perfect pipeline based on the exact dashboard unique. Um, this isn't true. Now, with Cloud data warehouse and the speed of important business data getting into those cloud data warehouses, you need a solution that allows you to access it right away without having everything to be perfect from the start, and I think this is a great opportunity for GAL and I have a little further discussion on what we're seeing in the marketplace. Um, one of the primary ones is like, What are the limiting factors, your Siegel of legacy technologies in the market when it comes to this cloud transformation we're talking about >>here? It's a great question, Michael and the variety of aspect when it comes to legacy, the other warehouses that are slowing down innovation for companies and businesses. I'll focus on 21 is performance right? We want faster insights. Companies want the ability to analyze MAWR data faster. And when it comes to on prem or legacy data warehouses, that's hard to achieve because the second aspect comes into display, which is the lack of flexibility, right. If you want to increase your capacity of your warehouse, you need to ensure request someone needs to go and bring an actual machine and install it and expand your data warehouse. When it comes to the cloud, it's literally a click of a button, which allows you to increase the capacity of your data warehouse and enable your internal and external users to perform analytics at scale and much faster. >>It falls right into the explanation you provided there, right as the speed of the data warehouses and the data gets faster and faster as it scales, older solutions aren't built toe leverage that, um, you know, they're either they're having to make technical, you know, technical cuts there, either looking at smaller amounts of data so that they can get to the data quicker. Um, or it's taking longer to get to the data when the data warehouse is ready, when it could just be live career to get the answers you need. And that's definitely an issue that we're seeing in the marketplace. I think the other one that you're looking at is things like governance, lineage, regulatory requirements. How is the cloud you know, making it easier? >>That's That's again an area where I think the cloud shines. Because AWS AWS scale allows significantly more investment in securing security policies and compliance, it allows customers. So, for example, Amazon redshift comes by default with suck 1 to 3 p. C. I. Aiso fared rampant HIPPA compliance, all of them out of the box and at our scale. We have the capacity to implement those by default for all of our customers and allow them to focus. Their very expensive, valuable ICTY resource is on actual applications that differentiate their business and transform the customer experience. >>That's a great point, gal. So we've talked about the, you know, limiting factors. Technology wise, we've mentioned things like governance. But what about the cultural aspect? Right? So what do you see? What do you see in team struggling in meeting? You know, their cloud data warehouse strategy today. >>And and that's true. One of the biggest challenges for large large organizations when they moved to the cloud is not about the technology. It's about people, process and culture, and we see differences between organizations that talk about moving to the cloud and ones that actually do it. And first of all, you wanna have senior leadership, drive and be aligned and committed to making the move to the cloud. But it's not just that you want. We see organizations sometimes Carol get paralyzed. If they can't figure out how to move each and every last work clothes, there's no need to boil the ocean, so we often work with organizations to find that iterative motion that relative process off identifying the use cases are date identifying workloads in migrating them one at a time and and through that allowed organization to grow its knowledge from a cloud perspective as well as adopt its tooling and learn about the new capabilities. >>And from an analytics perspective, we see the same right. You don't need a pixel perfect dashboard every single time to get value from your data. You don't need to wait until the data warehouse is perfect or the pipeline to the data warehouse is perfect. With today's technology, you should be able to look at the data in your cloud data warehouse immediately and get value from it. And that's the you know, that's that change that we're pushing and starting to see today. Thanks. God, that was That was really interesting. Um, you know, as we look through that, you know, this transformation we're seeing in analytics, um, isn't really that old? 20 years ago, data warehouses were primarily on Prem and the applications the B I tools used for analytics around them were on premise well, and so you saw things like applications like Salesforce. That live in the cloud. You start having to pull data from the cloud on Prem in order to do analytics with it. Um, you know, then we saw the shift about 10 years ago in the explosion of Cloud Data Warehouse Because of their scale, cost reduced, reduce shin reduction and speed. You know, we're seeing cloud data. Warehouses like Amazon Red Shift really take place, take hold of the marketplace and are the predominant ways of storing data moving forward. What we haven't seen is the B I tools catch up. And so when you have this new cloud data warehouse technology, you really need tools that were custom built for it to take advantage of it, to be able to query the cloud data warehouse directly and get results very quickly without having to worry about creating, you know, a middle layer of data or pipelines in order to manage it. And, you know, one company captures that really Well, um, chick fil A. I'm sure everybody has heard of is one of the largest food chains in America. And, you know, they made a huge investment in red shift and one of the purposes of that investment is they wanted to get access to the data mawr quickly, and they really wanted to give their business users, um, the ability to do some ad hoc analysis on the data that they were capturing. They found that with their older tools, the problems that they were finding was that all the data when they're trying to do this analysis was staying at the analyst level. So somebody needed to create a dashboard in order to share that data with a user. And if the user's requirements changed, the analysts were starting to become burdened with requests for changes and the time it took to reflect those changes. So they wanted to move to fought spot with embrace to connect to Red Shift so they could start giving business users that capability. Query the database right away. And with this, um, they were able to find, you know, very common things in in the supply chain analysis around the ability to figure out what store should get, what product that was selling better. The other part was they didn't have to wait for the data to get settled into some sort of repository or second level database. They were able to query it quickly. And then with that, they're able to make changes right in the red shift database that were then reflected to customers and the business users right away. So what they found from this is by adopting thought spot, they were actually able to arm business users with the ability to make decisions very quickly. And they cleared up the backlog that they were having and the delay with their analysts. And they're also putting their analysts toe work on different projects where they could get better value from. So when you look at the way we work with a cloud data warehouse, um, you have to think of thoughts about embrace as the tool that access that layer. The perfect analytic partner for the Cloud Data Warehouse. We will do the live query for the business user. You don't need to know how to script and sequel, um Thio access, you know, red shift. You can type the question that you want the answer to and thought spot will take care of that query. We will do the indexing so that the results come back faster for you and we will also do the analysis on. This is one of the things I wanted to cover, which is our spot i. Q. This is new for our ability to use this with embrace and our partners at Red Shift is now. We can give you the ability to do auto analysis to look at things like leading indicators, trends and anomalies. So to put this in perspective amount imagine somebody was doing forecasting for you know Q three in the western region. And they looked at how their stores were doing. And they saw that, you know, one store was performing well, Spot like, you might be able to look at that analysis and see if there's a leading product that is underperforming based on perhaps the last few quarters of data. And bring that up to the business user for analysis right away. They don't need to have to figure that out. And, um, you know, slice and dice to find that issue on their own. And then finally, all the work you do in data management and governance in your cloud data warehouse gets reflected in the results in embrace right away. So I've done a lot of talking about embrace, and I could do more, but I think it would be far better toe. Have Vika actually show you how the product works, Vika. >>Thanks, Michael. We learned a lot today about the power of leveraging your red shift data and thought spot. But now let me show you how it works. The coronavirus pandemic has presented extraordinary challenges for many businesses, and some industries have fared better than others. One industry that seems to weather the storm pretty well actually is streaming media. So companies like Netflix and who Lou. And in this demo, we're going to be looking at data from B to C marketing efforts. First streaming media company in 2020 lately, we've been running campaigns for comedy, drama, kids and family and reality content. Each of our campaigns last four weeks, and they're staggered on a weekly basis. Therefore, we always have four campaigns running, and we can focus on one campaign launch per >>week, >>and today we'll be digging into how our campaigns are performing. We'll be looking at things like impressions, conversions and users demographic data. So let's go ahead and look at that data. We'll see what we can learn from what's happened this year so far, and how we can apply those learnings to future decision making. As you can already see on the thoughts about homepage, I've created a few pin boards that I use for reporting purposes. The homepage also includes what others on my team and I have been looking at most recently. Now, before we dive into a search, will first take a look at how to make a direct connection to the customer database and red shift to save time. I've already pre built the connection Red Shift, but I'll show you how easy it is to make that connection in just three steps. So first we give the connection name and we select our connection type and was on red Shift. Then we enter our red shift credentials, and finally, we select the tables that we want to use Great now ready to start searching. So let's start in this data to get a better idea of how our marketing efforts have been affected either positively or negatively by this really challenging situation. When we think of ad based online marketing campaigns, we think of impressions, clicks and conversions. Let's >>look at those >>on a daily basis for our purposes. So all this data is available to us in Thought spot, and we can easily you search to create a nice line chart like this that shows US trends over the last few months and based on experience. We understand that we're going to have more clicks than impressions and more impressions and conversions. If we started the chart for a minute, we could see that while impressions appear to be pretty steady over the course of the year, clicks and especially conversions both get a nice boost in mid to late March, right around the time that pandemic related policies were being implemented. So right off the bat, we found something interesting, and we can come back to this now. There are few metrics that we're gonna focus on as we analyze our marketing data. Our overall goal is obviously to drive conversions, meaning that we bring new users into our streaming service. And in order to get a visitor to sign up in the first place, we need them to get into our sign up page. A compelling campaign is going to generate clicks, so if someone is interested in our ad, they're more likely to click on it, so we'll search for Click through Rape 5% and we'll look this up by campaign name. Now even compare all the campaigns that we've launched this year to see which have been most effective and bring visitors star site. And I mentioned earlier that we have four different types of campaign content, each one aligned with one of our most popular genres. So by adding campaign content, yeah, >>and I >>just want to see the top 10. I could limit my church. Just these top 10 campaigns automatically sorted by click through rate and assigned a color for each category so we could see right away that comedy and drama each of three of the top 10 campaigns by click through rate reality is, too, including the top spot and kids and family makes one appearance as well. Without spot. We know that any non technical user can ask a question and get an answer. They can explore the answer and ask another question. When you get an answer that you want to share, keep an eye on moving forward, you pin the answer to pin board. So the BBC Marketing Campaign Statistics PIN board gives us a solid overview of our campaign related activities and metrics throughout 2020. The visuals here keep us up to date on click through rate and cost per click, but also another really important metrics that conversions or cost proposition. Now it's important to our business that we evaluate the effectiveness of our spending. Let's do another search. We're going to look at how many new customers were getting so conversions and the price cost per acquisition that we're spending to get each of these by the campaign contact category. So >>this is a >>really telling chart. We can basically see how much each new users costing us, based on the content that they see prior to signing up to the service. Drama and reality users are actually relatively expensive compared to those who joined based on comedy and kids and family content that they saw. And if all the genres kids and family is actually giving us the best bang for our marketing >>buck. >>And that's good news because the genres providing the best value are also providing the most customers. We mentioned earlier that we actually saw a sizable uptick in conversions as stay at home policies were implemented across much of the country. So we're gonna remove cost per acquisition, and we're gonna take a daily look how our campaign content has trended over the years so far. Eso By doing this now, we can see a comparison of the different genres daily. Some campaigns have been more successful than others. Obviously, for example, kids and family contact has always fared pretty well Azaz comedy. But as we moved into the stay at home area of the line chart, we really saw these two genres begin to separate from the rest. And even here in June, as some states started to reopen, we're seeing that they're still trending up, and we're also seeing reality start to catch up around that time. And while the first pin board that we looked at included all sorts of campaign metrics, this is another PIN board that we've created so solely to focus on conversions. So not only can we see which campaigns drug significant conversions, we could also dig into the demographics of new users, like which campaigns and what content brought users from different parts of the country or from different age groups. And all this is just a quick search away without spot search directly on a red shift. Data Mhm. All right, Thank you. And back to you, Michael. >>Great. Thanks, Vika. That was excellent. Um, so as you can see, you can very quickly go from zero to search with thought Spot, um, connected to any cloud data warehouse. And I think it's important to understand that we mentioned it before. Not everything has to be perfect. In your doubt, in your cloud data warehouse, um, you can use thought spot as your initial for your initial tool. It's for investigatory purposes, A Z you can see here with star, Gento, imax and anthem. And a lot of these cases we were looking at billions of rows of data within minutes. And as you as your data warehouse maturity grows, you can start to add more and more thoughts about users to leverage the data and get better analysis from it. So we hope that you've enjoyed what you see today and take the step to either do one of two things. We have a free trial of thoughts about cloud. If you go to the website that you see below and register, we can get you access the thought spots so you can start searching today. Another option, by contacting our team, is to do a zero to search workshop where 90 minutes will work with you to connect your data source and start to build some insights and exactly what you're trying to find for your business. Um thanks, everybody. I would especially like to thank golf from AWS for joining us on this today. We appreciate your participation, and I hope everybody enjoyed what they saw. I think we have a few questions now. >>Thank you, Vika, Gal and Michael. It's always exciting to see a live demo. I know that I'm one of those comedy numbers. We have just a few minutes left, but I would love to ask a couple of last questions Before we go. Michael will give you the first question. Do I need to have all of my data cleaned and ready in my cloud data warehouse before I begin with thought spot? >>That's a great question, Mallory. No, you don't. You can really start using thought spot for search right away and start getting analysis and start understanding the data through the automatic search analysis and the way that we query the data and we've seen customers do that. Chick fil a example that we talked about earlier is where they were able to use thoughts bought to notice an anomaly in the Cloud Data Warehouse linking between product and store. They were able to fix that very quickly. Then that gets reflected across all of the users because our product queries the Cloud Data Warehouse directly so you can get started right away without it having to be perfect. And >>that's awesome. And gal will leave a fun one for you. What can we look forward to from Amazon Red Shift next year? >>That's a great question. And you know, the team has been innovating extremely fast. We released more than 200 features in the last year and a half, and we continue innovating. Um, one thing that stands out is aqua, which is a innovative new technology. Um, in fact, lovely stands for Advanced Square Accelerator, and it allows customers to achieve performance that up to 10 times faster, uh, than what they've seen really outstanding and and the way we've achieved that is through a shift in paradigm in the actual technological implementation section. Uh, aqua is a new distributed and hardware accelerated processing layer, which effectively allows us to push down operations analytics operations like compression, encryption, filtering and aggregations to the storage there layer and allow the aqua nodes that are built with custom. AWS designed analytics processors to perform these operations faster than traditional soup use. And we no longer need to bring, you know, scan the data and bring it all the way to the computational notes were able to apply these these predicates filtering and encourage encryption and compression and aggregations at the storage level. And likewise is going to be available for every are a three, um, customer out of the box with no changes to come. So I apologize for being getting out a little bit, but this is really exciting. >>No, that's why we invited you. Call. Thank you on. Thank you. Also to Michael and Vika. That was excellent. We really appreciate it. For all of you tuning in at home. The final session of this track is coming up shortly. You aren't gonna want to miss it. We're gonna end strong, come back and hear directly from our customer a T mobile on how T Mobile is building a data driven organization with thought spot in which >>pro, It's >>up next, see you then.

>>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

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by AWS Worldwide Public sector. >>Welcome to the Cube. Virtual. This is our coverage of aws reinvent 2020. Specialized programming for worldwide public sector. I'm Lisa Martin. Got a couple of guests here from No. Veta, please welcome Steven Adelman, principal computer scientists, and Kevin Healed, vice president of Information Exploitation. Gentlemen, welcome to the Cube. >>Thank you. >>Thank you for having us. >>Alright, guys. So? So, Kevin, we're going to start with you. Give our audience an introduction to Nevada. What do you What do you guys do? Who are you? How do you play in the public sector Government space, >>right? Yeah. Thank you, Lisa. Eso, Nevada Nevada is a technology services company focused on government solutions. So primarily national security solutions. Eso think customers such as Doody, the intelligence community, FBI, law enforcement and things like that about 13 1300 employees worldwide, primarily in our in our field. Clear resource is, um, that really focused on cloud for solutions for our customers. So solving the tough mission challenges our customers have, so that could be in technology solutions such as Data Analytics A I M L i O T. Secure Workloads, full spectrum cyber Cobb video processing. Really anything that's a high end technology solution or something we do for the government. We have been a privilege. We have. It's a privilege to be a partner with AWS for for some time now. In fact, I think the first reinvent we may have been to Stephen was six years ago. Five years ago, two >>1012 or 13 >>s So we've we've we've been around for a while, really kind of enjoying it and certainly sad that we're missing an in person reinvent this year, but looking forward to doing it virtually so, we're actually advanced your partner with AWS with a machine learning and government competency. Andi really kind of thio pump the m l side of that. That was one of our first companies with compasses with AWS and led by a center of excellence that I have in my division that really focuses on machine learning and how we applied for the Michigan. And so, um, really, we focus on protecting the nation and protecting our activities in the country >>and on behalf of the country. We thank you, Steven. Give me a little bit of information from a double click perspective as computer scientists. What are some of the key challenges that no, that helps its customers to solve. And how do you do that with a W s? >>Yeah, Thank you. So really as, ah, company, that is is data first. So our initial love and and still are kind of strongest competency is in applying solutions to large data sets. And as you can imagine, uh, the bigger the data set them or compute you need the the more resource is you need and the flexibility from those resource is is truly important, which led us very early, as especially in the government space and public sector space to be in early. A doctor of cloud resource is because of the fact that, you know, rather than standing up a 200 node cluster at at many millions of dollars, we could we could spend up a W s resource is process a big data set, and then and then get the answers an analyst or on operator needed and then spin down. Those resource is when When when that kind of compute wasn't needed. And that is really, uh, kind of informed how we do our work Azaz Nevadans that that cloud infrastructure and now pushing into the edge compute space. Still kind of keeping those cloud best practices in play to get access to more data. That the two, the two biggest, I think revolutions that we've seen with regards to using data to inform business processes and missions has been that that cloud resource that allows us to do so much with so less and so much more flexibly and then the idea of cheap compute making it to the edge and the ability to apply sensors thio places where you know it would been a would have been, you know, operational cost prohibitive to do that and then, ironically, those air to things that aren't necessarily data analytics or machine learning focused but man, did they make it easier to collect that data and process that data and then get the answers back out. So that really has has has kind of, uh, shaped a lot of the way Nevada has grown as a company and how we serve our customers. >>So coming back over to you lets. One of the things that we've been talking about almost all year is just the acceleration in digital transformation and how much faster organizations, private sector, public sector need to innovate to stay relevant, to stay competitive. How do you are you working with government customers to help them innovate so quickly? >>You know, we're very fortunate that a set of customers that focuses actually innovation it's focuses. I rad on. Do you know we can't do the cool things we do without those customer relationships that really encourage us to, um, to try new things out and, quite frankly, fail quickly when we need Thio. And so, by establishing that relationship, what we've been able to do is to blend agile development. Actual acquisition with government requirements process, right? If if you know the typical stereotype of government work is it's this very stovepiped hard core acquisition process, right? And so we have been fortunate to instead try quick win kind of projects. And so one of the biggest things we do is partner with our government customers and try to find it difficult, um, challenged to solve over 6 to 12 month time, right? So instead of making this long four or five year acquisition cycles like show me, right. How can we solve this problem? And then we partner with the mission partner show success in six months show that we can do it with a smaller part of money, and then as we're able to actually make that happen, it expands in something bigger, broader, and then we kind of bringing together a coalition of the willing, if you will in the government and saying, Okay, are there other stakeholders to care about this problem, bring them on, bring their problems and bringing together? You know, we can't do that with some of the passionate people we have, like Stevens. A perfect example. When we talk about a car in the projects we're doing here, Stevens passion for this technology partner with our customers having these challenges and try to enhance what they're doing is a powerful combination. And then the last thing that we're able to is a company is we actually spend a decent amount of our own dollar dollars on I rad S O. R and D that we fund ourselves. And so, while finding those problems and spending government dollars in doing that. We also have spent our own dollars on machine learning Coyote sensor next Gen five g and things like that and how those compartment together partner together to go back to the government. >>Yeah, yeah, So I would even say, You know, there's this. There's a conventional wisdom that government is slow in plotting and a little bit behind commercial best practices. But there are There are pockets in growing pockets across the government, Um, where they're really they're really jumping ahead of, ah, lot of processes and getting in front of this curve and actually are quite innovative. And and because they kind of started off from behind, they could jump over a lot of kind of middle ground legacy technologies. And they're really innovating. As Kevin said with With With the card platform, we're partnering with um P E O Digital in the Air Force in South C, D. M and Air Force security forces as that kind of trifecta of stakeholders who all want toe kind of saw a mission problem and wanted to move forward quickly and leave the legacy behind and and really take a quantum leap forward. And if anything, they're they're driving us Thio, Innovate Mawr Thio Introduce more of those kind of modern back practices on bond. Nevada as a company loves to find those spots in the government sector where we've got those great partners who love what we're doing. And it's this great feedback loop where, um, where we can solve hard technical problems but then see them deployed to some really important and really cool and impactful missions. And we tend to recruit that that set that kind of nexus of people who want to both solve a really difficult problem but want to see it executed in a really impactful way as well. I mean, that really grates a great bond for us, and and I'm really excited to say that that a lot of the government it is really taking a move forward in this this this realm. And I think it's it's just good for our country and good for the missions that they support. >>Absolutely. And it's also surprising because, as you both said, you know, there is this expectation that government processes or lengthy, you know, laborious, um, not able to be turned around quickly. But as Kevin, you just said, you know helping customers. Government agencies get impact within 6 to 12 months versus 4 to 5 years. So you talked about Picard? Interesting name. Kevin. Tell me a little bit more about that technology and what it is that you guys deliver. That's unique. >>Well, honestly, it's probably best to start with Stephen. I can give you the high level. This is Stevens vision. I have to give him credit for that. And I will say way have lots of fun. Acronym. So it isn't Actually, it isn't backward. Um, right. Stephen doesn't actually stand for something. >>It stands for Platform for Integrated, a C three and Responsive for defense on >>Guy. You know >>that the Star Trek theme is the leg up from the last set of programs I had, >>which were >>my little ponies. So >>Oh, wow. That's a definite stuff in a different direction. Like >>it? Part of the great thing about working in the government is you get to name things, cool things, so but t get to your question eso So Picard really sprung out of this idea that I had a few years ago that the world but for our spaces, the Department of defense and the federal government was going to see a massive influx of the desire to consume sensors from from areas of responsibility, from installations and, frankly, from battlefields. Um, but they were gonna have to do it. In a way, um, uh, that presented some real challenges that you couldn't just kind of throw compute editor, throw traditional I t processes at it. You know, we have legacy sensors that are 40 years old sitting on installations. You know, old program, a logical controllers or facilities control systems that were written in cobalt in the seventies, right in the world are not even I, p based, most of them bond. Then on the other end of the spectrum, you have seven figure sensors that air, you know, throwing out megabits of second of data that are mounted to the back of jeeps. Right, That that air bouncing through the desert today. But we'll be bouncing through the jungle tomorrow, and you have to find all of those kind of in combined all of those together, um, and kind of create a cohesive data center for data set set for you know, the mission for, um, you know what we call a user to find common operating picture for a person. Thio kind of combine all of those different resource is and make it work for them. And so we found a great partner with security forces. Um, they realized that they wanted Thio to make a quantum leap forward. They had this idea that the next defender So there are there, like a military police outfit that the next defender was going to be a data driven defender and they were gonna have to win the information war war as much as they had to kind of dominate physical space. And they immediately got what we were trying to achieve, and it was just just great synergy. And then we've piled on some other elements, and we're really moving that platform forward to to kind of take every little bit of information we can get from the areas of responsibility and get it into a you know, your modern Data Lake, where they can extract information from all that data. >>Kevin, as the VP of information exploitation, that's a very interesting title. How are you helping government organizations to win the war on information? Leverage that information to make a big impact fast. >>Yeah. I mean, I think a lot of it is is that we try to break down the barriers between systems on data so that we can actually enable that data to fuse together to find and get insights into it. You know, as ML and I have become trendy topics, you know, they're very data hungry operations. And I think what Steven has done with the card and his team is really we want to be able to make those sensors seamless from a plug and play perspective that Aiken plug in a new sensor. It's a standards based, uh, interface that sends that data back so that we can and take it back to the user to find Operation Picture and make some decisions based off of that data. Um, you know, what's more is that data could even refused with more than the data that Stevens collecting off the sensors. It could be commercial data, other government data and I think is Davis. As Stephen said earlier, you have to get it back. And as long as you've gotten back in Labour's share with some of our mission partners, then you can do amazing things with it. And, you know, Stephen, I know you have some pretty cool ideas and what we're gonna do on the edge, right? How do we do some of this work of the edge where a sensor doesn't allow us to pull out that data back? >>Yeah, and and Thio follow on to what you were kind of referring to with regards to thio handling heterogeneous data from different sensors. Um, one of the main things that our government customers and we have seen is that there are a lot of historically there are a lot of vertical solutions where you know, the sensor, the platform, and then the data Laker kind of all part of this proprietary stack. And we quickly realized that that just doesn't work. And so one of the major thrust of that card platform was to make sure that we had ah, platform by which we could consume data through adapters from essentially any sensor speaking. Any protocol with any style data object, Whether that was an industry standard or a proprietary protocol, we could quickly interested and bring it into our Data lake. And then to pile on to what Kevin was talking about with compute. Right? So you have, uh, like, almost like a mass locks hierarchy of needs when it comes to cyber data or thio this coyote data or kind of unified data, Um, you know, you wanna turn it into basic information, alerts alarms, then you want to do reporting on it, or analytics or some some higher level workflow function. And then finally, you probably want to perform some analytics or some trending or sort of anomaly detection on it. And and that gets more computational e intensive each step of the way. And so you gotta You gotta build a platform that allows you to to both take some of that high level compute down to the edge, but also then bring some of that data up into the clouds where you could do that processing, and you have to have kind of fun jubilate e between that and so that hard platform allows you to kind of bring GP use and high processing units down to the edge and and make that work. Um, but then also and then as maybe even a first passive to rule out some of the most you know, some of the boring gated in the video Analytics platform. We call it Blue Sky and Blue Ocean. Right, so you're recording lots of video. That's not that interesting. How do you filter that out? So you're only sending the information The interesting video up eso You're not wasting bandwidth on stuff that just doesn't matter on DSO. It's It's a lot of kind of tuning these knobs and having a flexible enough platform that you could bring Compute down when you need it. And you could bring data up to compute on Big Cloud while you need it, and just kind of finding a way to tune that that that really does. I mean it. You know, that's a lot of words about how you do that. But what that comes to is flexible hardware and being able to apply those dev ops and C I. C D platform characteristics to that edge hardware and having a unified platform that allows you to kind of orchestrate your applications in your services all the way up and down your stack, from micro controllers to a big cloud instant creation. >>You make it sound so easy. Steven Kevin. Let's wrap it up with you in terms of like making impacts and going forward. We know the edge has exploded, even mawr, during this very interesting year. And that's going to be something that's probably going to stay, um, stay as a permanent impact or effect. What are some of the things that we can expect in 2021 in terms of how you're able to help government organizations capitalize on that, find things faster, make impact faster? >>Yeah. I mean, I think the cool thing we're seeing is that there's a lot more commoditization of sensors. There's a lot more censored information. And so let's use lighters. Example. We you know, things were getting cheaper, and so we can all of a sudden doom or or more things at the edge, and we ever would have expected. Right when you know Steven's team is integrating camera data and fence data from 40 years ago, you know, it's just saying on off it's not do anything fancy. But now we you know, you know, Stephen, I camera whether Metro you gave him before was, but the cost of light are has dropped so significantly that we can now then deploy that we can actually roll it out there and not being locked in their proprietary, uh, system. Um, so I see that being very powerful, you know? Also, I can see where you start having sensors interact with each other, right? So one sensor finds one thing and then a good example that we've started thio experiment with. And I think Steve, you could touch on it is using triggering a sensor, triggers a drone to actually investigate what's going on and then therefore, hybrid video back and then automatically can investigate instead of having to deploy a defender to actually see what happened at that. At that end, Points dio e don't know. There's it's amore detail you can provide there. >>Yeah, No. So exactly that Kevin. So So the power of the sensor is is something something old that that gives you very uninteresting Data like a one or a zero on on or off can detect something very specific and then do something kind of high speed, like task a drone to give you a visual assessment and then run object detection or facial recognition on, you know, do object detection to find a person and do facial recognition on that person to find out if that's a patrol walking through a field or a bad guy trying Thio invade your space. Um and so it's really the confluence and the gestalt of all of these sensors in the analytics working together, Um, that really creates the power from very simple, simple delivery. I think, um, there's this, You know, this idea that you know, ah 100 bytes of data is not that important. But when you put a million sensors giving you 100 bytes of data, you can truly find something extremely powerful. And then when you kind of and you make those interactions sing, um, it's amazing. Tow us the productivity that we can produce and the kind of fidelity of response that we can give thio actors in the space whether that's a defender trying to defend the base or a maintenance person trying thio proactively replace the fan or clean the fan on an H vac system. So So you know, you know, there isn't a fire at a base or for, uh, interesting enough. One of the things that we we've been able to achieve is we've taken maintenance data for helicopter engines and And we've been able to proactively say, Hey, you need to You need to take care of this part of the helicopter engine. Um and it saves money. It saves downtimes. It keeps the birds in the air. And it's a relatively simple algorithm that we were able to achieve. And we were able to do that with the maintenance people, bring them along in this endeavor and create analytics that they understood and could trust on DSO. I think that's really the power of this base. >>Tremendous power. I wish we had more time to to dig into it. Guys, thank you so much for sharing. Not just your insights, what nobody is doing but your passion for what you're doing and how you're making such an impact. Your passion is definitely palpable. Steven. Kevin, Thank you for joining me today. >>Thank you >>for my guests. I'm Lisa Martin. You're watching the Cube? Virtual. Yeah,

>>from >>around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Hi. >>And welcome to the Cube. Virtual in our coverage of aws reinvent 2020. We have a cube virtual, and I'm your host, Justin Warren. And today, my guest is Shauna Wolverton, executive vice president of product at ZENDESK. And she's coming to us from Oakland, California. Shauna, welcome to the >>Cube. Thanks so much for having me. It is >>It is lovely to be here. How's the weather over there? In Oakland, >>we just suddenly went from summer to winter, which, uh, after the weather we've had is no complaints. >>All right, Well, as as a resident of Melbourne, where we have four seasons in one day, I am very familiar with rapid weather changes. So, uh, hopefully it's not too cold for you, and you get a little bit of nicer weather just before you go fully into winter. Absolutely. Now Zendesk and Amazon have a pretty close relationship is my understanding, and we know that Amazon is famous for its customer center at attitude. Wonderful thing about customers, of course, is that they're never really happy with everything that we have. So zendesk fit in with that with that relationship with Amazon. And how is your approach to customer? >>Yeah. I mean, the relationship we have with them is I'm really excited. Really Have gone all in on our move to the cloud. There are sole provider on DWI run all of our services, um, on AWS. And in addition, we have some great partnerships with, uh, Jacob Amazon Connect, which allows us to provide great telephony and call center services to our customers. We have a great partnership around event bridge and a zwelling app connect. So I think there is a fantastic relationship that we have where we're able to deliver not just our basic services, but to really take advantage of a lot of the services that Amazon on AWS provide s so that we can sort of accelerate our own roadmap and deliver great new features to our customers. >>Now, a lot of people have gone through a pretty similar adoption of the cloud of the moment. Unfortunate reason for doing so. But it certainly has driven the adoption very, very quickly. Uh, zendesk, of course, as you say, has been has been doing this for quite some time. So what have you noticed that stayed the same eso from last year to this year? What were you already doing that you're now noticing? Everyone else's discovering. Actually, this is pretty good. >>Well, you know, I think you know the rumors of of the call center and and the telephone as a channel. Their demise are greatly exactly. I think, um, for us. Much as we're all excited about chat and messaging and all of the different ways that we can connect with our customers, there's something about having a phone number and allowing people to pick up the phone and talk to a human that refuses to go out of style. And so I think, um, you know, our partnership with, uh with Amazon connection has been hugely powerful and even, you know, recently when a lot of this sort of acceleration has picked up, we've seen, um, you know, we saw a customer who had a power failure kind of massive failure of their own phone system. Be able thio, come to us, get, get, connect up and running incredibly quickly and start taking thousands of calls a day and that kind of sort of quick time to value fast start ability for our customers. Just this hugely important. Um, now. But really, you know, that's always been true, right? >>Yeah. I mean, when people want to call you and they want to talk to you, then they're not really happy If they can't get through that and particularly right now, being able to make that human human connection for me, I know that that that's been a really important part of getting through this. I work remotely most of the time. So actually, speaking to humans as we're doing now is is really refreshing change from just seeing everything on on a text screen. Um, so yeah, so it's It's interesting that the phone has actually has been so resilient, even though we were here from Ah, lot of young people say, Oh, we never answer the phone when someone calls, uh, but a lot of people are actually calling into businesses when they wanna make contact or when they when they don't see things on the website. So >>how does >>zendesk help, too, to integrate with what people are doing in their online and digital channels through to what they're doing with phone system. >>Yeah, but I think fundamentally people want their questions answered. One of my favorite studies that we did was around our benchmark study and we talked to Millennials. They said the first place they go to get help to their phone, but when you push it a little deeper, it was clear that they actually didn't know that the phone was for making phone calls. It was just all of the other help centers like like the first way that a lot of people today are looking for. Answers is, you know I wanna google it. And for that you need a really great help center has all that information out there and then you want toe have, you know, communities where people can talk to each other and get help. And then, you know, Mawr and Mawr. We're seeing the rise of messaging as a channel, both through the social channels like WhatsApp and Facebook Messenger Aziz Well, Azaz native messaging kind of ongoing conversations. He you ordered your dinner. It hasn't arrived. It's so great to be able to go into those applications and just message to the business and figure out what's what's going on and get that sort of instantaneous response as well, >>right? And you shared some stats with this regarding how much has moved across to some of these things phone based messaging channels. So tickets coming in has risen about 50% on DCA, paired to some gains on on live chat. So people are really embracing the idea of being about a message, not just individual talking to your friends in the group chat, but actually using that to engage with with the companies that they would normally use websites or or phone. It's like text chat is a thing. >>Yeah, I mean, it was funny to me. You know, I think we're still, uh, in the U. S. Not quite as far along as a lot of our international friends. When I when traveling was a thing that we did, you know, I was always like it was cool to see that there were billboards and ads that had what that phone numbers on them is a really, you know, way that businesses were wanting to engage. I mean, you think about be wanting to be where your customers are today. So many of us, um do have you know what's happened? Wechat and line and vibrant. They're all in our pocket. And being able to provide all of those two businesses is a new way to engage. I think we're finding is hugely powerful, >>right? So with with all of these dynamic changes that have been happening, and it sounds like it's actually just sort of riding the wave of what customers were already doing, we're just doing it just that little bit mawr. But have you noticed any other larger changes? Possibly ones that aren't related thio a pandemic, Just general shifts that have been happening that you've seen in your customer base? >>Yeah. I mean, like I said, I think so much of what we're seeing is that people, uh, in general want answers quickly, and whether it's a phone call is great. And like I said, people are not going to stop calling. But I think people want to make sure less than like, I need a human to have a conversation I want. I want the answer quickly, and that's where we're really focused in both thinking about how we provide tools around automating some of getting those answers using, uh, a i N m l so that people can come to us, ask questions and we can get them the best answer very quickly without, um, having Thio engage a person. I think things idea of quick resolution is clearly becoming one of the most important things in customer sentiment. I think we know that, um, Mawr and Mawr. This idea of how quickly I can get my question's resolved or how easy it is for me to do business with you is a huge differentiator in how people make buying >>choices. Mm. On that. That automation has long been a new track tive idea. I mean, I'm I'm old enough to remember expert systems and and having a go at doing this kind of heavily automated way of resolving particularly common issues. And I mean, we were familiar with Coulson, a chat scripts. Where there's here are the top three issues and or it will be in the I V. R. Where it's like we're currently experiencing this particular problems, so that resolves your question quite quickly. But there's been a big rise in things like chatbots and and the use of AI. How far advanced. Is that because I still remember some of the early forays into that were a little bit flaky, and that could actually exacerbate the poor customer experience. I'm already having a problem, and and now you're chatbots getting in the way. Have they gotten a lot better? Are they Are they up to the challenge? >>Yeah. I mean, I think what's really critical when you're thinking about automation? Um, in the conversations you're having with customers, it's it's two things. One Don't try to hide that. That you're a computer. No, no, my name is Chad. I am. I am a human. Um, you're not in the vault. Yeah, there's not anyone. Um, so I think being really clear. And then, um e think surfacing how thio very easily opt out of those flows. I think, um, you know, automation is great, but it's not away. You shouldn't think of it as a way to frustrate your users to keep them tied up until you can get to them. It really is. Give them some quick options. And if they don't? If those don't solve their problems, really make sure that your you've got an escape valve, right? We were putting out a new sort of flow build their product zendesk. And we have all of the different, uh, words that someone could say that air like smashing the zero button. That means please transfer me to a person, right? You're driving me crazy. Let me connect you to an agent. Eso We're really making sure that it's easy, um, for customers to provide the solution where their customers can get the help they need rather than I >>really like that. That's That's something I think that gets a little bit lost in the focus on computers and and on automation is that the reason we do this is to help the humans. So when we have these AI systems, it's not actually to replace. The human interaction is to make it better. It's to make mean that we can then get to that genuine connection. Computers a fabulous and when they work, it's when they don't when they frustrate things that that bothers us. And that's generally why we're calling is that something has already gone wrong and we're a bit frustrated. So adding more frustration, doesn't it? Sounds like a good approach. It sounds like zendesk really got that? That dolled in very, very well. Is that something that you've you've always had? Is it something that you've refined over time? And can you teach it to a bunch of other companies? >>Way would love to teach each other. People know, I think e think we have always thought about how the machines can help the humans. And I think one it's how can they help the customers, of course. But the other side that I don't think people talk about quite a much is how can we use computers to help agents? Right. So you're talking to a person, and how can we take sort of the best answers that they've given Thio other customers and surface those, um, when When a new agent is coming on board, how do we suggest, um, you know, the different kinds of work flows that they might want to use to solve this problem in a more dynamic way. So I really like to think of the computers never as a replacement but really as a sort of hidden superpower, Um, that organizations have to make every agent one of their best >>agents, right? Yes, it is a kind of external cyborg thing. I mean, I can't remember anything these days. I constantly right less and they all live in computers. But they are. That's the kind of society that we live with today. And I think we should remember to embrace that side of things. That ah, lot of life has actually gotten a lot better through the use of these computing systems. It's not all terrible. It's, um, and I think more companies could probably learn from zendesk. And the approach that you've taken to center the humans, both the customers and and your internal staff, the call center and and the people who are providing this service. No one enjoys it when things are breaking and and things have gone wrong being able to resolve that quickly. Thanks a better experience for everybody. >>Yeah. I mean, I think we find over and over again sometimes you know, if you can handle an issue that's gone wrong, Um well, you can actually induce more loyalty than you know. If someone never contacted. You'd also if you could really take advantage of the times you have, unfortunately, maybe messed up on bake those customers happy. You really do you know, put so much in the sort of loyalty piggy bank for later. It's really great. >>So for some of the companies that have maybe struggled with this a little bit and particularly under very trying conditions, is there's some advice that you could give to them. Is there some places that they should should start to investigate this when they want to improve the way that they handle customer service, perhaps with things like Zendesk. >>Yeah, I mean, I think a lot of what what we're focused on right now is the this channel that's coming. Like I said, we think a lot about social messaging, but also in native messaging. Andi, how you can have a sort of ongoing long term conversation for a long time customer service, sort of Holy Grail was chat, and you could have a agent online and a human online, and you could solve their problem and then move on right And and sometimes those things take a little longer to solve. Or, you know, you might have a big issue and a whole bunch of people who have an issue and maybe not enough agents to solve them. And so, with messaging. We've really changed the dynamic. So chat was this completely synchronous, Almost like a phone call. Kind of experience and more messaging. You're able to live in this sort of duality where we can have a conversation if we're both here. But just like with your friends, right? Sometimes you throw a message out to offend you. Put it in your pocket, you pick it up, and you could pick up the conversation right where you left off. So bring that paradigm into your customer support experience really allows you to take some of that fear out of handling the volume that might come from chat. To be able to sort of have these ongoing sort of back and forth conversations over time. Andi also and give that that persistent so that we're always both in the same place when we show up again together >>embracing what the technology does well and avoiding what it doesn't do. Well, that that sounds like a plan. >>Shawna, >>this has been fabulous. It is. It is always very edifying for me. Thio here, when companies are doing well and centering the humans to make the technology improve all of our lives. Um It has been wonderful to have you here on the Cube. >>Thanks so much. It was a lot of fun, right? >>And thank you for joining in and and watching us here of the Cube virtual and our special coverage off AWS reinvent 2020. Do come back and look for more coverage off. Reinvent 2020 right here on the Cube. Next time I've been your host, Justin Warren, and we'll see you again soon.

>>Hello, everyone. And welcome back to our wall to wall coverage of the data Cloud Summit. This is Dave a lot. And we're seeing the emergence of a next generation workload in the cloud were more facile access and governed. Sharing of data is accelerating. Time to insights and action. All right, allow me to introduce our next guest. Amy Irwin is here. She's the vice president of strategy for experience. And Matt Glickman is VP customer product strategy it snowflake with an emphasis on financial services. Folks, welcome to the Cube. Thanks so much for coming on. >>Thanks for >>having us >>nice to be here. Hey, >>So, Amy, I mean, obviously 2020 has been pretty unique and crazy and challenging time for a lot of people. I don't know why I've been checking my credit score a lot more for some reason. On the app I love the app I got hacked. I had a lock it the other day I locked my credit. Somebody tried to dio on and it worked. I was so happy. So thank you for that. But so we know experience, but there's a ton of data behind what you do. I wonder if you could share kind of where you sit in the data space and how you've seen organizations leverage data up to this point. And really, if you could address maybe some of the changes that you're seeing as a result of the pandemic, that would be great. >>Sure, sure. Well, Azaz, you mentioned experience Eyes best known as a credit bureau. Uh, I work in our marketing services business unit, and what we do is we really help brands leverage the power of data and technology to make the right marketing decisions and better understand and connect with consumers. Eso we offer markers products around data identity activation measurement. We have a consumer view data file that's based on off line P I and contains demographic interest, transaction data and other attributes on about 300 million people in the U. S. Uh, and on the identity side, we've always been known for our safe haven or privacy friendly matching that allows marketers to connect their first party data to experience or other third parties. Uh, but in today's world, with the growth and importance of digital advertising and consumer behavior shifting to digital, uh, experience also is working to connect that offline data to the digital world for a complete view of the customer you mentioned co vid, um, we actually we serve many different verticals. And what we're seeing from our clients during co vid is that there's a bearing impact of the pandemic. The common theme is that those that have successfully pivoted their businesses to digital are doing much better. Uh, as we all know, Kobe accelerated very strong trends to digital both in the commerce and immediate viewing habits. We work with a lot of retailers. Retail is a tale of two cities with big box and grocery growing and apparel retail really struggling. We've helped our clients leveraging our data to better understand the shifts in these consumer behaviors and better segment their customers during this really challenging time. Eso think about there's there's a group of customers that is still staying home that is sheltered in place. There's a group of customers starting that significantly varied their consumer behavior, but it's starting to venture out a little. And then there's a group of customers that's doing largely what they did before and a somewhat modified fashion. So we're helping our clients segment those customers into groups to try and understand the right messaging and right offers for each of those groups. And we're also helping them with at risk audiences. Eso That's more on the financial side. Which of your customers air really struggling? Do the endemic And how do you respond? >>It's awesome, thank you. You know, it's it's funny. I mean somebody I saw Twitter poll today asking if we measure our screen time and I said, Oh my no eso Matt, let me ask you. You spend a ton of time in financial services. You really kind of cut your teeth there, and it's always been very data oriented. You've seen a lot of changes tell us about how your customers are bringing together data, the skills that people obviously a big part of the equation and applications to really put data at the center of their universe. What's new and different that these companies were getting out of the investments in data and skills. >>That's a great question. Um, the acceleration that Amy mentioned Israel, Um, we're seeing it particularly this year, but I think even in the past few years, the reluctance of customers to embrace the cloud is behind us. And now there's this massive acceleration to be able to go faster on, and in some ways the new entrance into this category. Have an advantage versus, you know, the companies that have been in the space within its financial services or beyond. Um, and in a lot of ways they are are seeing the cloud and services like snowflake as a way toe not only catch up but leapfrog your competitors and really deliver a differentiated experience to your customers to your business, internally or externally. Um, and this past, you know, however long this crisis has been going on, has really only accelerated that, because now there's a new demand. Understand your customer better your your business better with with your traditional data sources and also new alternative data sources, Um, and also be able to take a pulse. One of things that we learned which was you know, I opening experience was as the crisis unfolded, one of our data partners decided to take the data sets about where the cases where were happening from the Johns Hopkins and World Health Organization and put that on our platform, and it became a runaway hit where now with thousands of our customers overnight, we're using this data to understand how their business was doing versus how the crisis was unfolding in real time. On this has been a game changer, and I think it's only it's only scratching the surface of what now the world will be able to do when data is really at their fingertips. You're not hindered by your legacy platforms. >>I wrote about that back in the early days of the pandemic when you guys did that and talked about some of the changes that you guys enabled and and, you know you're right about Cloud. I mean, financial services. Cloud used to be an evil word, and now it's almost become a mandate. Amy, I >>wonder if you >>could tell us a little bit more about what? What, you know your customers they're having to work through in order to achieve some of these outcomes. I mean, I'm interested in the starting point. I've been talking a lot and writing a lot on talking to practitioners about what I call the data lifecycle. Sometimes people call it the data pipeline. It za complicated matter, but those customers and companies that can put data at the center and really treat that pipeline is the heart of their organization, If you will, really succeeding. What are you seeing and what really is the starting point there? >>Yes, yes, that's a good question. And as you mentioned, first party, I mean, we start with first party data. Right? First party data is critical to understanding consumers on been in different verticals, different companies. Different brands have varying levels of first party data. So retailers gonna have a lot more first party data financial services company, then say an auto manufacturer. Uh, while many marketers have that first party data to really have a 3 60 view of the customer, they need third party data as well. And that's where experience comes in. We help brands connect those disparate data sets both 1st and 3rd party baked data to better understand consumers and create a single customer view, which has a number of applications. I think the last that I heard was that there's about eight devices on average per person. I always joke that we're gonna have these enormous. I mean, that that number is growing. We're gonna have these enormous charging stations in our house, and I think we're because all the different devices and way seamlessly move from device to device along our customer journey. And, um, if the brand doesn't understand who we are, it's much harder for the brand to connect with consumers and create a positive customer experience and way site that about 95% of companies are actually that they are looking to achieve that single customer view. They recognize, um, that they need that. And they've aligned various teams from e commerce to marketing to sales toe at a minimum in just their first party data and then connect that data to better understand, uh, consumers so consumers can interact with the brand through website and mobile app in store visits, um, by the phone, TV ads, etcetera. And a brand needs to use all of those touchpoints often collected by different parts of the organization and then adding that third party data to really understand the consumers in terms of specific use cases, Um, there's there's about three that come to mind, so there's first. There's relevant advertising and reaching the right customer. There's measurement s or being able to evaluate your advertising efforts. Uh, if you see an ad on the if I see it out of my mobile and then I by by visiting a desktop website understanding or get a direct mail piece, understanding that those connect those interactions are all connected to the same person is critical for measurement. And then there's, uh, there's personalization, um, which includes encourage customer experience amongst your own, um, touch points with that consumer personalized marketing communication and then, of course, um, analytics. So those are the use cases we're seeing? Great. >>Thank you, Amy. I'm out. You can't really talk about data without talking about, >>you know, >>governance and and and compliance. And I remember back in 2006, when the Federal Rules of Civil Procedure went in, it was easy. The lawyers just said, No, nobody can have access, but that's changed. One of things I like about what snowflakes doing with the data cloud is it's really about democratizing access, but doing so in a way that gives people confidence that they only have access to the right data. So maybe you could talk a little bit about how you're thinking about this topic, what you're doing to help customers navigate, which has traditionally been such a really challenging problem. >>No, it's another great question. Um, this is where I think the major disruption is happening. Um, and what Amy described being able to join together 1st and 3rd party data sets. Um, being able to do this was always a challenge because data had to be moved around, had a ship, my first party data to the other side. The third party data had to be shipped to me on being able to join those data sets together, um was problematic at best. And now, with the focus on privacy and protecting P, I, um, this is this is something that has to change. And the good news is with the data cloud data does not have to move. Data can stay where it belongs. Experiencing keep its data experience. Customers can hold on to their data. Yet the data can be joined together on this universal global platform that we call the data cloud. On top of that, and particularly with the regulations that are coming out that are gonna prevent data from being collected on either a mobile device or in wet warren as cookies and Web browsers, new approaches. And we're seeing this a lot in our space, both in financials and in media is to set up these data clean rooms where both sides can give access to one another, but not have to reveal any P i i to do that joint. Um, this is gonna be huge right now. You actually can protect your your customers, private your consumers, private identities, but still accomplish that. Join that Amy mentioned to be able to thio relate the cause and effect of these campaigns and really understand the signals. Um, that these data sets are trying to say about one another again without having to move data without having to reveal P. I We're seeing this happening now. This is this is the next big thing that we're gonna see explode over the next months and years to come. >>I totally agree. Massive changes coming in public policy in this area, and I wanted we only have a few minutes left. I wonder if for our audience members that you know, looking for some advice, what's the what's the one thing you'd recommend? They start doing differently or consider putting in place. That's going to set them up for success over the next decade. >>Yeah, that's a good question. Um, you know, I think e always say, you know, first harness all of your first party data across all touchpoints. Get that first party data in one place and working together Second back that data with trusted third parties and in mats, just in some ways to do that and then third, always with the customer first speak their language. Uh, where and when they want to be, uh, reached out thio on and use the information. You have to really create a better a better customer experience for your customers. >>Matt. What would you add to that? Bring us home if you would >>applications. Um, the idea that data can now be your data can now be pulled into your own business applications the same way that Netflix and Spotify are pulled into your consumer and lifestyle applications again without data moving these personalized applications experiences is what I encourage everyone to be thinking about from first principles. What would you do in your next app that you're gonna build? If you had all of your consumers, consumers had access to their data in the app and not having to think about things you know from scratch. Leverage the data cloud leverage these, you know, service providers like experience and build the applications of tomorrow. >>I'm super excited when I talked to practitioners like yourselves about the future of data Guys, Thanks so much for coming on. The Cube was really a pleasure having you and hope we can continue this conversation in the future. >>Thank you. >>All right. Thank you for watching. Keep it right there. We've got great content. Tons of content coming at the Snowflake Data Cloud Summit. This is Dave Volonte for the Cube. Keep it right there.

>>from around the globe. It's the Cube with coverage of Yukon and Cloud. Native Con North America. 2020. Virtual Brought to You by Red Hat, The Cloud, Native Computing Foundation and Ecosystem Partners. Hey, welcome back, everybody. Jeffrey here with the Cube coming to you from our Palo Alto studios with our ongoing coverage of Q. Khan Cloud, Native Con 2020 North America. Of course, it's virtual like everything else is in 2020 but we're excited to be back. It's a terrific show, and we're excited our next guest. So let's introduce him. And we've got Sam Warner, the VP of offering manager and business line executive for storage for IBM. Sam. Great to see you. >>Great to be here. >>And also joining us is Brent Compton. He's a senior director of data services for Redhead. Great. See you, Brent. >>Thank you. >>So let's let's jump into it. Cloud Native. Everything's about cloud native. Everything's about containers. Everything is about kind of container ization and flexibility. But then there's this thing in the back and called storage. We actually have toe keep this stuff and record this stuff and have data protection for this stuff in business resiliency love to jump into it, so lets you know where does storage fit within a container world? And how is the growth of containers and the adoption containers really had you rethink the way that you think about storage and how clients you think about stories saying, Let's start with you >>e mean, it's a great question. And first off, I'm really excited about another cube con. Uh, we did Europe now, uh, doing North America so very excited to be, you know, seeing all the you know, all the news and all the people talking about the advancements around kubernetes. And we're very excited about it now. You asked a very good question. Important question. We're seeing an acceleration of digital transformation, and the people that are going through this digital transformation are using containers to now modernize the rest of their infrastructure. The interesting thing about it, though, is those initiatives are being driven out of the application teams. The business lines in an organization, and a lot of them don't understand that there's a lot of complexity to this storage piece here. So the storage teams I talked to are all of a sudden getting these initiatives thrown on them or a kind of halfway their strategy. And they're scratching their heads, trying to figure out now how they can support these applications with persistent storage. Because that's not where containers started. They started with micro services, and now now they're in a quandary. They have to deliver a certain S L. A to their customers, and they're trying to figure out how they do it in this new environment, which in a lot of cases, has been designed outside of their scope. So they're seeing issues with data protection. Some of the kind of core things that they've been dealing with for years are now. They're now having to solve all over again. So that's what we're working on helping them with reinventing how storage is deployed to help them deliver the same level of security, availability and everything they have in the past. Uh, in these new environments, >>right? So, yeah, e say you've been involved in this for a long time. You know, you've worked in hyper converge. You've worked in big data. You know, the evolution of big data continues to change, as ultimately we want to get people the information to make good decisions, but we've gone through a lot of integrations over the years. So how is it different? You know? Now how is it different with containers? What can we finally do you as a as an architect that we couldn't do before? >>Infrastructure is code. That's, I think, one of the fundamental differences of the storage admin of yesteryear versus storage admin of today today, Azaz Sam mentioned As people are developing and deploying applications, those applications need to dynamically provisioned the infrastructure dynamically provisioned what they need from compute dynamically provisioned what they need from storage dynamically provisioned network paths and so that that that element of infrastructure is code. A dynamically provisioned infrastructure is very different from well from yesterday, when applications or teams needed to. Well, when they needed storage, they would you know, they would file a ticket and typically wait. Now they make an a p A. Now they make an A p. I call and storage is dynamically provisioned and provided to their application. >>But what what I think hard to understand for the layman. And maybe it's just me, right? I It's very easy to understand dynamic infrastructure around, um compute right, I'm Pepsi. I'm running it out for the Super Bowl. I need I know how much people are gonna hit by hit my site and it's kind of easy to understand. Dynamic provisioning around networking again for the same example. What's less easy to understand its dynamic provisioning for storage? It's one thing to say, you know, there's a there's a pool of storage resource is that I'm going to dynamically provisioned for this particular after this particular moment. But one of the whole things about the dynamic is not only is it available when you need it, but I could make it big, and conversely, I could make it smaller go away. I get that for servers, and I kind of get that for networking, supporting an application and that example I just talked about. But we can't It doesn't go away a lot of the time for storage, right? That's important data that's maybe feeding another process. There's all kinds of rules and regulations, So when you talk about dynamic infrastructure for storage, it makes a lot of sense for grabbing some to provision for some new application. But it's >>hard to >>understand in terms of true dynamics in terms of either scaling down or scaling up or turning off when I don't particularly need that much capacity or even that application right now, how does it work within storage versus No, just servers or I'm grabbing them and then I'm putting it back in the pool. >>Let me start on this one, and then I'm gonna hand it off to Brent. Um, you know, let's not forget, by the way, that enterprises have very significant investments in infrastructure and they're able to deliver six nines of availability on their storage. And they have d are worked out in all of their security, encryption, everything. It's already in place, and they're sure that they can deliver on their SLS. So they want to start with that. You have to leverage that investment. So first of all, you have to figure out how to automate that into the environment, that existing sand, and that's where things like uh, a P I s the container storage interface CS I drivers come in. IBM provides that across your entire portfolio, allowing you to integrate your storage into a kubernetes environment into an open shipped environment so that it can be automated, but you have to go beyond that and be able to extend that environment, then into other infrastructure, for example, into a public cloud. So with the IBM flash system, family with our spectrum virtualized software were actually able to deploy that storage layer not only on Prem on our award winning a race, but we can also do it in the cloud. So we allow you to take your existing infrastructure investments and integrate that into your communities environment and using things like danceable, fully automated environment. I'll get into data protection before we're done talking. But I do want Brent to talk a bit about how container native storage comes into that next as well. On how you can start building out new environments for, uh, for your applications. >>Yeah, What the two of you are alluding to is effectively kubernetes services layer, which is not storage. It consumes storage from the infrastructure, Assam said. Just because people deploy Kubernetes cluster doesn't mean that they go out and get an entirely new infrastructure for that. If they're deploying their kubernetes cluster on premises, they have servers. If they're deploying their kubernetes cluster on AWS or an azure on G C P. They have infrastructure there. Uh, what the two of you are alluding to is that services layer, which is independent of storage that can dynamically provisioned, provide data protection services. As I mentioned, we have good stuff to talk about their relative to data protection services for kubernetes clusters. But that's it's the abstraction layer or data services layer that sits on top of storage, which is different. So the basics of storage underneath in the infrastructure, you know, remain the same, Jeff. But the how that storage is provisioned and this abstraction layer of services which sits on top of the storage storage might be IBM flash system array storage, maybe E m c sand storage, maybe a W S E B s. That's the storage infrastructure. But this abstraction layer that sits on top this data services layer is what allows for the dynamic interaction of applications with the underlying storage infrastructure. >>And then again, just for people that aren't completely tuned in, Then what's the benefit to the application developer provider distributor with that type of an infrastructure behind And what can they do that they just couldn't do before? >>Well, I mean Look, we're, uh, e I mean, we're trying to solve the same problem over and over again, right? It's always about helping application developers build applications more quickly helps them be more agile. I t is always trying to keep up with the application developer and always struggles to. In fact, that's where the emergency cloud really came from. Just trying to keep up with the developer eso by giving them that automation. It gives them the ability to provision storage in real time, of course, without having open a ticket like friends said. But really, the Holy Grail here is getting to a developed once and deploy anywhere model. That's what they're trying to get to. So having an automated storage layer allows them to do that and ensure that they have access to storage and data, no matter where their application gets it >>right, Right, that pesky little detail. When I have to develop that up, it does have to sit somewhere and and I don't think storage really has gotten enough of of the bright light, really in kind of this app centric, developer centric world, we talk all the time about having compute available and and software defined networking. But you know, having this software defined storage that lives comfortably in this container world is pretty is pretty interesting. In a great development, I want to shift gears a >>little bit. Just one thing. Go >>ahead, >>plus one to Sam's comments. There all the application developer wants, they want an A P I and they want the same a p I to provision the storage regardless of where their app is running. The rest of the details they usually don't care about. Sure. They wanted to perform what not give him an A p I and make it the same regardless of where they're running the app. >>Because not only do they want to perform, they probably just presume performance, right? I mean, that's the other thing is that the best in class quickly becomes presumed baseline in a very short short period of time. So you've got to just you just got to just deliver the goods, right? They're gonna get frustrated and not be productive. But I wanted to shift gears up a little bit and talk about some of the macro trends. Right? We're here towards the end of 2020. Obviously, Cove It had a huge impact on business and a lot of different ways. And it's really evolved from March, this light switch moment. Everybody work from home, too. Now, this kind of extended time, that's probably gonna go on for a while. I'm just curious some of the things that you've seen with your customers not so much at the beginning, because that was that was a special and short period of time. But mawr, as we've extended and and are looking to, um, probably extended this for a while, you know, What is the impact of this increased work from home increase attack surface? You know, some of these macro things that we're seeing that cove it has caused and any other kind of macro trends beyond just this container ization that you guys were seeing impacting your world. Start with you, Sam. >>You know, I don't think it's actually changed what people were going to do or the strategy. What I've seen it do is accelerate things and maybe changed the way they're getting their, uh and so they're actually a lot of enterprises were running into challenges more quickly than they thought they would. And so they're coming to us and asking us to help them. Saw them, for example, backing up their data and these container environments as you move mission critical applications that maybe we're gonna move more slowly. They're realizing that as they've moved them, they can't get the level of data protection they need. And that's why actually we just announced it at the end of October. Updates to our modern data protection portfolio. It now is containerized. It could be deployed very easily in an automated fashion, but on top of that, it integrates down into the A P. I layer down into CSE drivers and allows you to do container where snapshots of your applications so you could do operational recovery. If there's some sort of an event you can recover from that you can do D R. And you can even use it for data migration. So we're helping them accelerate. So the biggest I think requests I'm getting from our customers, and how can you help us accelerate? And how can you help us fix these problems that we went running into as we tried to accelerate our digital transformation? >>Brent, Anyone that you wanna highlight? >>Mm. Okay. Ironically, one of my team was just speaking with one of the cruise lines, um, two days ago. We all know what's happened them. So if we just use them as an example, I'm clearly our customers need to do things differently now. So plus one to Sam's statement about acceleration on I would add another word to that which is agility, you know, frankly, they're having to do things in ways they never envisioned 10 months ago. So there need to cut cycle times to deploy effectively new ways of how they transact business has resulted in accelerated poll for these types of infrastructure is code technologies. >>That's great. The one that jumped in my mind. Sam, is you were talking. We've we've had a lot of conversations. Obvious security always comes up on baking security and is is a theme. But ransomware as a specific type of security threat and the fact that these guys not only wanna lock up your data, but they want to go in and find the backup copies and and you know and really mess you up so it sounds like that's even more important to have the safe. And we're hearing, you know, all these conversations about air gaps and dynamic air gaps and, you know, can we get air gaps and some of these infrastructure set up so that we can, you know, put put those backups? Um, and recovery data sets in a safe place so that if we have a ransomware issue, getting back online is a really, really important thing, and it seems to just be increasing every day. We're seeing things, you know, if you can actually break the law sometimes if you if you pay the ransom because where these people operate, there's all kind of weird stuff that's coming out of. Ransomware is a very specific, you know, kind of type of security threat that even elevates, you know, kind of business continuity and resiliency on a whole nother level for this one particular risk factor. When if you're seeing some of that as well, >>it's a great point. In fact, it's clearly an industry that was resilient to a pandemic because we've seen it increase things. Is organized crime at this point, right? This isn't the old days of hackers, you know, playing around this is organized crime and it is accelerating. And that's one thing. I'm really glad you brought up. It's an area we've been really focused on across our whole portfolio. Of course, IBM tape offers the best most of the actual riel air gapping, physical air gapping We could take a cartridge offline. But beyond that we offer you the ability to dio you know, different types of logical air gaps, whether it's to a cloud we support. In fact, we just announced Now the spectrum protect. We have support for Google Cloud. We already supported AWS Azure IBM Cloud. So we give you the ability to do logical air gapping off to those different cloud environments. We give you the ability to use worm capability so you can put your backups in a vault that can't be changed. So we give you lots of different ways to do it. In our high end enterprise storage, we offer something called Safeguarded copy where we'll actually take data off line that could be recovered almost instantly. Something very unique to our storage that gives you, for the most mission critical applications. The fastest path recovery. One of things we've seen is some of our customers have done a great job creating a copy. But when the event actually happens, they find is gonna take too long to recover the data and they end up having to pay the ransom anyway. So you really have to think through an Indian strategy on we're able to help customers do a kind of health checks of their environment and figure out the right strategy. We have some offerings to help come in and do that for our customers. >>Shift gears a little bit, uh, were unanswerable fest earlier this year and a lot of talk about automation. Obviously, answer was part of the Red Hat family, which is part of the IBM family. But, you know, we're seeing Mawr and Mawr conversations about automation about, you know, moving the mundane and the air prone and all the things that we shouldn't be doing as people and letting people doom or high value stuff. When if you could talk a little bit about the role of automation, that the kind of development of automation and how you're seeing that, you know, impact your deployments, >>right? You want to take that one first? >>Yeah, sure. Um, s o the first is, um when you think about individual kubernetes clusters. There's a level of automation that's required there. I mean, that's the fundamental. I mean, back to the infrastructure is code that's inherently. That's automation. To effectively declare the state of what you want your application, your cluster to be, and that's the essence of kubernetes. You declare what the state is, and then you pass that declaration to kubernetes, and it makes it so. So there's the kubernetes level automation. But then there's, You know what happens for larger enterprises when you have, you know, tens or hundreds of kubernetes clusters. Eso That's an area of Jeff you mentioned answerable. Now that's an area of with, you know, the work, the red hats doing the community for multi cluster management, actually in the community and together with IBM for automating the management of multiple clusters. And last thing I'll touch on here is that's particularly important as you go to the edge. I mean, this is all well and good when you're talking about, you know, safe raised floor data center environments. But what happens when you're tens or hundreds or even thousands of kubernetes clusters are running in an oil field somewhere? Automation becomes not only nice to have, but it's fundamental to the operation. >>Yeah, but let me just add onto that real quick. You know, it's funny, because actually, in this cove it era, you're starting to see that same requirement in the data center in the core data center. In fact, I would say that because there's less bodies now in the data center, more people working remotely. The automation in need for automation is actually actually accelerating as well. So I think what you said is actually true for the core data center now as well, >>right? So I wanna give you guys the last word before before we close the segment. Um, I'm gonna start with you, Brent. Really, From a perspective of big data and you've been involved again in big data for a long time. As you look back, it kind of the data warehouse era. And then we had kind of this whole rage with the Hadoop era, and, you know, we just continue to get more and more sophisticated with big data processes and applications. But at the end of the day, still about getting the right data to the right person at the right time to do something about it. I wonder if if you can, you know, kind of reflect over that journey and where we are now in terms of this mission of getting, you know, the right data to the right person at the right time so they could make the right decision. >>I think I'll close with accessibility. Um, that Z these days, we you know, the data scientists and data engineers that we work with. The key problem that they have is is accessibility and sharing of data. I mean, this has been wonderfully manifest. In fact, we did some work with the province of Ontario. You could look that stop hashtag house my flattening eso the work with them to get a pool of data. Scientists in the community in the province of Ontario, Canada, toe work together toe understand how to track co vid cases s such so that government could make intelligent responses and policy based on based on the fax so that that need highlights the accessibility that's required from today's, you know, yesteryear. It was maybe, uh, smaller groups of individual data scientists working in silos. Now it's people across industry as manifest by that That need accessibility as well as agility. They need to be able to spin up an environment that will allow them to in this case, um, to develop and deploy inference models using shared data sets without going through years of design. So accessibility on back to the back to the the acceleration and agility that Sam talked about. So I'll close with those words >>That's great. And the consistent with the democratization of two is another word that we're here, you know, over and over again in terms of, you know, getting it out of the hands of the data scientists and getting it into the hands of the people who are making frontline business decisions every day. And Sam for you, for your clothes. I love for you Thio reflect on kind of the changing environment in terms of your requirements for the types of workloads that you now are, you know, looking to support. So it's not just taking care of the data center and relatively straightforward stuff. But you've got hybrid. You've got multi cloud, not to mention all the media, the developments in the media between tape and obviously flash, um, spinning, spinning drives. But you know, really, We've seen this huge thing with flash. But now, with cloud and the increased kind of autumn autonomy ization of of units to be able to apply big batches in small batches to particular workloads across all these different requirements. When if you could just share a little bit about how you guys are thinking about, you know, modernizing storage and moving storage forward. What are some of your what are some of your your priorities? What are you looking forward to, uh, to be able to deliver, You know, basically the stuff underneath all these other applications. I mean, applications basically is data whether you I and some in some computer on top. You guys something underneath the whole package? >>Yeah. Yeah. You know, first of all, you know, back toe what Brent was saying, Uh, data could be the most valuable asset of an enterprise. You could give an enterprising, incredible, uh, competitive advantage as an incumbent if you could take advantage of that data using modern analytics and a I. So it could be your greatest asset. And it can also be the biggest inhibitor to digital transformation. If you don't figure out how to build a new type of modern infrastructure to support access to that data and support these new deployment models of your application. So you have to think that through. And that's not just for your big data, which the big data, of course, is extremely important and growing at incredible pace. All this unstructured data, You also have to think about your mission critical applications. We see a lot of people going through their transformation and modernization of S a p with move toe s four Hana. They have to think about how that fits into a multi cloud environment. They need to think about the life cycle of their data is they go into these new modern environments. And, yes, tape is still a very vibrant part of that deployment. So what we're working on an IBM has always been a leader in software defined storage. We have an incredible portfolio of capabilities. We're working on modernizing that software to help you automate your infrastructure. And sure, you can deliver enterprise class sls. There's no nobody's going to alleviate the requirements of having, you know, near perfect availability. You don't because you're moving into a kubernetes environment. Get a break on your downtime. So we're able to give that riel enterprise class support for doing that. One of the things we just announced that the end of October was we've containerized our spectrum scale client, allowing you now toe automate the deployment of your cluster file system through communities. So you'll see more and more of that. We're offering you leading modern native protection for kubernetes will be the first to integrate with OCP and open ship container storage for data protection. And our flashes from family will continue to be on the leading edge of the curve around answerable automation and C s I integration with who are already so we'll continue to focus on that and ensure that you could take advantage of our world class storage products in your new modern environment. And, of course, giving you that portability between on from in any cloud that you choose to run in >>exciting times. No, no shortage of job security for you, gentlemen, that's for sure. All right, Well, Brent, Sam, thanks for taking a few minutes and, uh, is great to catch up. And again. Congratulations on the success. Thank you. Thank you. Thank you. Alrighty, Sammy's Brent. I'm Jeff, You're watching the cubes. Continuing coverage of Q. Khan Cloud, Native Con North America 2020. Thanks for watching. We'll see you next time.

>>from around the globe. It's the Cube with coverage of Yukon and Cloud. Native Con North America 2020 Virtual brought to you by Red Hat The Cloud, Native Computing Foundation and Ecosystem Partners. Hello, everyone. And welcome back to the cubes Ongoing coverage of Cuba con North America. Joe Fernandez is here. He's with Stephanie, Cheras and Joe's, the V, P and GM for core cloud platforms. That red hat and Stephanie is this s VP and GM of the Red Hat Enterprise. Lennox bu. Two great friends of the Cube. Awesome seeing you guys. How you doing? >>It's great to be here, Dave. Yeah, thanks >>for the opportunity. >>Hey, so we all talked, you know, recently, uh, answerable fest Seems like a while ago, but But we talked about what's new? Red hat really coming at it from an automation perspective. But I wonder if we could take a view from open shift and what's new from the standpoint of you really focus on helping customers, you know, change their operations and operationalize. And Stephanie, Maybe you could start, and then, you know, Joe, you could bring in some added color. >>No, that's great. And I think you know one of the things we try and do it. Red hat clearly building off of open source. We have been focused on this open hybrid cloud strategy for, you know, really years. Now the beauty of it is that hybrid cloud and open hybrid cloud continues to evolve right with bringing in things like speed and stability and scale and now adding in other footprints, like manage services as well as edge and pulling that all together across the whole red hat portfolio from the platforms, right? Certainly with Lennox and roll into open shift in the platform with open shift and then adding automation, which certainly you need for scale. But it's ah, it's continues to evolve as the as the definition of open hybrid cloud evolves. >>Great. So thank you, Stephanie jokes. You guys got hard news here that you could maybe talk about 46? >>Yeah. Eso eso open shift is our enterprise kubernetes platform. With this announcement, we announced the release of open ship 4.6 Eso eso We're doing releases every quarter tracking the upstream kubernetes release cycle. So this brings communities 1.19, which is, um but itself brings a number of new innovations, some specific things to call out. We have this new automated installer for open shift on bare metal, and that's definitely a trend that we're seeing is more customers not only looking at containers but looking at running containers directly on bare metal environments. Open shift provides an abstraction, you know, which combines Cuban. And he's, uh, on top of Lennox with RL. I really across all environments, from bare metal to virtualization platforms to the various public clouds and out to the edge. But we're seeing a lot of interest in bare metal. This is basically increasing the really three automation to install seamlessly and manage upgrades in those environments. We're also seeing a number of other enhancements open shifts service mesh, which is our SDO based solution for managing, uh, the interactions between micro services being able to manage traffic against those services. Being able to do tracing. We have a new release of that on open shift Ford out six on then, um, some work specific to the public cloud that we started extending into the government clouds. So we already supported AWS and Azure. With this release, we added support for the A W s government cloud as well. Azaz Acela's Microsoft Azure government on dso again This is really important to like our public sector customers who are looking to move to the public cloud leveraging open shift as an abstraction but wanted thio support it on the specialized clouds that they need to use with azure gonna meet us Cup. >>So, joke, we stay there for a minute. So so bare metal talking performance there because, you know, you know what? You really want to run fast, right? So that's the attractiveness there. And then the point about SDO in the open, open shift service measure that makes things simpler. Maybe talk a little bit about sort of business impact and what customers should expect to get out of >>these two things. So So let me take them one at a time, right? So so running on bare metal certainly performances a consideration. You know, I think a lot of fixed today are still running containers, and Cuban is on top of some form of virtualization. Either a platform like this fear or open stack, or maybe VMS in the in one of the public clouds. But, you know containers don't depend on a virtualization layer. Containers only depend on Lennox and Lennox runs great on bare metal. So as we see customers moving more towards performance and Leighton see sensitive workloads, they want to get that Barry mental performance on running open shift on bare metal and their containerized applications on that, uh, platform certainly gives them that advantage. Others just want to reduce the cost right. They want to reduce their VM sprawl, the infrastructure and operational cost of managing avert layer beneath their careers clusters. And that's another benefit. So we see a lot of uptake in open shift on bare metal on the service match side. This is really about You know how we see applications evolving, right? Uh, customers are moving more towards these distributed architectures, taking, you know, formally monolithic or enter applications and splitting them out into ah, lots of different services. The challenge there becomes. Then how do you manage all those connections? Right, Because something that was a single stack is now comprised of tens or hundreds of services on DSO. You wanna be able to manage traffic to those services, so if the service goes down, you can redirect that those requests thio to an alternative or fail over service. Also tracing. If you're looking at performance issues, you need to know where in your architecture, er you're having those degradations and so forth. And, you know, those are some of the challenges that people can sort of overcome or get help with by using service mash, which is powered by SDO. >>And then I'm sorry, Stephanie ever get to in a minute. But which is 11 follow up on that Joe is so the rial differentiation between what you bring in what I can just if I'm in a mono cloud, for instance is you're gonna you're gonna bring this across clouds. I'm gonna You're gonna bring it on, Prem And we're gonna talk about the edge in in a minute. Is that right? From a differentiation standpoint, >>Yeah, that That's one of the key >>differentiations. You know, Read has been talking about the hybrid cloud for a long time. We've we've been articulating are open hybrid cloud strategy, Andi, >>even if that's >>not a strategy that you may be thinking about, it is ultimately where folks end up right, because all of our enterprise customers still have applications running in the data center. But they're also all starting to move applications out to the public cloud. As they expand their usage of public cloud, you start seeing them adopted multi cloud strategies because they don't want to put all their eggs in one basket. And then for certain classes of applications, they need to move those applications closer to the data. And and so you start to see EJ becoming part of that hybrid cloud picture on DSO. What we do is basically provide a consistency across all those environments, right? We want run great on Amazon, but also great on Azure on Google on bare metal in the data center during medal out at the edge on top of your favorite virtualization platform. And yeah, that that consistency to take a set of applications and run them the same way across all those environments. That is just one of the key benefits of going with red hat as your provider for open hybrid cloud solutions. >>All right, thank you. Stephanie would come back to you here, so I mean, we talk about rail a lot because your business unit that you manage, but we're starting to see red hats edge strategy unfolded. Kind of real is really the linchpin I wanna You could talk about how you're thinking about the edge and and particularly interested in how you're handling scale and why you feel like you're in a good position toe handle that massive scale on the requirements of the edge and versus hey, we need a new OS for the edge. >>Yeah, I think. And Joe did a great job of said and up it does come back to our view around this open hybrid cloud story has always been about consistency. It's about that language that you speak, no matter where you want to run your applications in between rela on on my side and Joe with open shift and and of course, you know we run the same Lennox underneath. So real core os is part of open shift that consistently see leads to a lot of flexibility, whether it's through a broad ecosystem or it's across footprints. And so now is we have been talking with customers about how they want to move their applications closer to data, you know, further out and away from their data center. So some of it is about distributing your data center, getting that compute closer to the data or closer to your customers. It drives, drives some different requirements right around. How you do updates, how you do over the air updates. And so we have been working in typical red hat fashion, right? We've been looking at what's being done in the upstream. So in the fedora upstream community, there is a lot of working that has been done in what's called the I. O. T Special Interest group. They have been really investigating what the requirements are for this use case and edge. So now we're really pleased in, um, in our most recent release of really aid relate 00.3. We have put in some key capabilities that we're seeing being driven by these edge use cases. So things like How do you do quick image generation? And that's important because, as you distribute, want that consistency created tailored image, be able to deploy that in a consistent way, allow that to address scale, meet security requirements that you may have also right updates become very important when you start to spread this out. So we put in things in order to allow remote device mirroring so that you can put code into production and then you can schedule it on those remote devices toe happen with the minimal disruption. Things like things like we all know now, right with all this virtual stuff, we often run into things like not ideal bandwidth and sometimes intermittent connectivity with all of those devices out there. So we put in, um, capabilities around, being able to use something called rpm Austria, Um, in order to be able to deliver efficient over the air updates. And then, of course, you got to do intelligent rollbacks for per chance that something goes wrong. How do you come back to a previous state? So it's all about being able to deploy at scale in a distributed way, be ready for that use case and have some predictability and consistency. And again, that's what we build our platforms for. It's all about predictability and consistency, and that gives you flexibility to add your innovation on top. >>I'm glad you mentioned intelligent rollbacks I learned a long time ago. You always ask the question. What happens when something goes wrong? You learn a lot from the answer to that, but You know, we talk a lot about cloud native. Sounds like you're adapting well to become edge native. >>Yeah. I mean, I mean, we're finding whether it's inthe e verticals, right in the very specific use cases or whether it's in sort of an enterprise edge use case. Having consistency brings a ton of flexibility. It was funny, one of our talking with a customer not too long ago. And they said, you know, agility is the new version of efficiency. So it's that having that sort of language be spoken everywhere from your core data center all the way out to the edge that allows you a lot of flexibility going forward. >>So what if you could talk? I mentioned just mentioned Cloud Native. I mean, I think people sometimes just underestimate the effort. It takes tow, make all this stuff run in all the different clouds the engineering efforts required. And I'm wondering what kind of engineering you do with if any with the cloud providers and and, of course, the balance of the ecosystem. But But maybe you could describe that a little bit. >>Yeah, so? So Red Hat works closely with all the major cloud providers you know, whether that's Amazon, Azure, Google or IBM Cloud. Obviously, Andi, we're you know, we're very keen on sort of making sure that we're providing the best environment to run enterprise applications across all those environments, whether you're running it directly just with Lennox on Ralph or whether you're running it in a containerized environment with Open Chef, which which includes route eso eso, our partnership includes work we do upstream, for example. You know, Red Hat help. Google launched the Cuban community, and I've been, you know, with Google. You know, we've been the top two contributors driving that product that project since inception, um, but then also extends into sort of our hosted services. So we run a jointly developed and jointly managed service called the Azure Red Hat Open Shift Service. Together with Microsoft were our joint customers can get access to open shift in an azure environment as a native azure service, meaning it's, you know, it's fully integrated, just like any other. As your service you can tied into as you're building and so forth. It's sold by by Azure Microsoft's sales reps. Um, but you know, we get the benefit of working together with our Microsoft counterparts and developing that service in managing that service and then in supporting our joint customers. We over the summer announced sort of a similar partnership with Amazon and we'll be launching are already doing pilots on the Amazon Red Hat Open ship service, which is which is, you know, the same concept now applied to the AWS cloud. So that will be coming out g a later this year, right? But again, whether it's working upstream or whether it's, you know, partnering on managed services. I know Stephanie team also do a lot of work with Microsoft, for example, on sequel server on Lenox dot net on Lenox. Whoever thought be running that applications on Linux. But that's, you know, a couple of years old now, a few years old, So eso again. It's been a great partnership, not just with Microsoft, but with all the cloud providers. >>So I think you just shared a little little He showed a little leg there, Joe, what's what's coming g A. Later this year. I want to circle back to >>that. Yeah, eso we way announced a preview earlier this year of of the Amazon Red Hat Open ships service. It's not generally available yet. We're you know, we're taking customers. We want toe, sort of be early access, get access to pilots and then that'll be generally available later this year. Although Red Hat does manage our own service Open ship dedicated that's available on AWS today. But that's a service that's, you know, solely, uh, operated by Red Hat. This new service will be jointly operated by Red Hat and Amazon together Idea. That would be sort of a service that we are delivering together as partners >>as a managed service and and okay, so that's in beta now. I presume if it's gonna be g a little, it's >>like, Yeah, that's yeah, >>that's probably running on bare metal. I would imagine that >>one is running >>on E. C. Two. That's running an A W C C T V exactly, and >>run again. You know, all of our all of >>our I mean, we you know, that open shift does offer bare metal cloud, and we do you know, we do have customers who can take the open shift software and deploy it there right now are managed. Offering is running on top of the C two and on top of Azure VM. But again, this is this is appealing to customers who, you know, like what we bring in terms of an enterprise kubernetes platform, but don't wanna, you know, operated themselves, right? So it's a fully managed service. You just come and build and deploy your APS, and then we manage all of the infrastructure and all the underlying platform for you >>that's going to explode. My prediction. Um, let's take an example of heart example of security. And I'm interested in how you guys ensure a consistent, you know, security experience across all these locations on Prem Cloud. Multiple clouds, the edge. Maybe you could talk about that. And Stephanie, I'm sure you have a perspective on this is Well, from the standpoint of of Ralph. So who wants to start? >>Yeah, Maybe I could start from the bottom and then I'll pass it over to Joe to talk a bit. I think one of these aspects about security it's clearly top of mind of all customers. Um, it does start with the very bottom and base selection in your OS. We continue to drive SC Lennox capabilities into rural to provide that foundational layer. And then as we run real core OS and open shift, we bring over that s C Lennox capability as well. Um, but, you know, there's a whole lot of ways to tackle this we've done. We've done a lot around our policies around, um see ve updates, etcetera around rail to make sure that we are continuing to provide on DCA mitt too. Mitigating all critical and importance, providing better transparency toe how we assess those CVS. So security is certainly top of mind for us. And then as we move forward, right there's also and joke and talk about the security work we do is also capabilities to do that in container ization. But you know, we we work. We work all the way from the base to doing things like these images in these easy to build images, which are tailored so you can make them smaller, less surface area for security. Security is one of those things. That's a lifestyle, right? You gotta look at it from all the way the base in the operating system, with things like sc Lennox toe how you build your images, which now we've added new capabilities. There And then, of course, in containers. There's, um there's a whole focus in the open shift area around container container security, >>Joe. Anything you want to add to that? >>Yeah, sure. I >>mean, I think, you know, obviously, Lennox is the foundation for, you know, for all public clouds. It's it's driving enterprise applications in the data center, part of keeping those applications. Security is keeping them up to date And, you know, through, you know, through real, we provide, you know, securing up to date foundation as a Stephanie mentioned as you move into open shift, you're also been able to take advantage of, uh, Thio to take advantage of essentially mutability. Right? So now the application that you're deploying isn't immutable unit that you build once as a container image, and then you deploy that out all your various environments. When you have to do an update, you don't go and update all those environments. You build a new image that includes those updates, and then you deploy those images out rolling fashion and, as you mentioned that you could go back if there's issues. So the idea, the notion of immutable application deployments has a lot to do with security, and it's enabled by containers. And then, obviously you have cured Panetti's and, you know, and all the rest of our capabilities as part of open Shift managing that for you. We've extended that concept to the entire platform. So Stephanie mentioned, real core West Open shift has always run on real. What we have done in open shift for is we've taken an immutable version of Ralph. So it's the same red hat enterprise Lennox that we've had for years. But now, in this latest version relate, we have a new way to package and deploy it as a relic or OS image, and then that becomes part of the platform. So when customers want toe in addition to keeping their applications up to date, they need to keep their platform up to dates. Need to keep, you know, up with the latest kubernetes patches up with the latest Lennox packages. What we're doing is delivering that as one platform, so when you get updates for open shift, they could include updates for kubernetes. They could include updates for Lennox itself as well as all the integrated services and again, all of this is just you know this is how you keep your applications secure. Is making sure your you know, taking care of that hygiene of, you know, managing your vulnerabilities, keeping everything patched in up to date and ultimately ensuring security for your application and users. >>I know I'm going a little bit over, but I have I have one question that I wanna ask you guys and a broad question about maybe a trends you see in the business. I mean, you look at what we talk a lot about cloud native, and you look at kubernetes and the interest in kubernetes off the charts. It's an area that has a lot of spending momentum. People are putting resource is behind it. But you know, really, to build these sort of modern applications, it's considered state of the art on. Do you see a lot of people trying to really bring that modern approach toe any cloud we've been talking about? EJ. You wanna bring it also on Prem And people generally associate this notion of cloud native with this kind of elite developers, right? But you're bringing it to the masses and there's 20 million plus software developers out there, and most you know, with all due respect that you know they may not be the the the elites of the elite. So how are you seeing this evolve in terms of re Skilling people to be able, handle and take advantage of all this? You know, cool new stuff that's coming out. >>Yeah, I can start, you know, open shift. Our focus from the beginning has been bringing kubernetes to the enterprise. So we think of open shift as the dominant enterprise kubernetes platform enterprises come in all shapes and sizes and and skill sets. As you mentioned, they have unique requirements in terms of how they need toe run stuff in their data center and then also bring that to production, whether it's in the data center across the public clouds eso So part of it is, you know, making sure that the technology meets the requirements and then part of it is working. The people process and and culture thio make them help them understand what it means to sort of take advantage of container ization and cloud native platforms and communities. Of course, this is nothing new to red hat, right? This is what we did 20 years ago when we first brought Lennox to the Enterprise with well, right on. In essence, Carozza is basically distributed. Lennox right Kubernetes builds on Lennox and brings it out to your cluster to your distributed systems on across the hybrid cloud. So So nothing new for Red Hat. But a lot of the same challenges apply to this new cloud native world. >>Awesome. Stephanie, we'll give you the last word, >>all right? And I think just a touch on what Joe talked about it. And Joe and I worked really closely on this, right? The ability to run containers right is someone launches down this because it is magical. What could be done with deploying applications? Using a container technology, we built the capabilities and the tools directly into rural in order to be able to build and deploy, leveraging things like pod man directly into rural. And that's exactly so, folks. Everyone who has a real subscription today can start on their container journey, start to build and deploy that, and then we work to help those skills then be transferrable as you movinto open shift in kubernetes and orchestration. So, you know, we work very closely to make sure that the skills building can be done directly on rail and then transfer into open shift. Because, as Joe said, at the end of the day, it's just a different way to deploy. Lennox, >>You guys are doing some good work. Keep it up. And thanks so much for coming back in. The Cube is great to talk to you today. >>Good to see you, Dave. >>Yes, Thank you. >>All right. Thank you for watching everybody. The cubes coverage of Cuba con en a continues right after this.

>>Hello, everyone. And welcome back to our wall to wall coverage of the data Cloud Summit. This is Dave a lot. And we're seeing the emergence of a next generation workload in the cloud were more facile access and governed. Sharing of data is accelerating. Time to insights and action. All right, allow me to introduce our next guest. Amy Irwin is here. She's the vice president of strategy for experience. And Matt Glickman is VP customer product strategy it snowflake with an emphasis on financial services. Folks, welcome to the Cube. Thanks so much for coming on. >>Thanks for >>having us >>nice to be here. Hey, >>So, Amy, I mean, obviously 2020 has been pretty unique and crazy and challenging time for a lot of people. I don't know why I've been checking my credit score a lot more for some reason. On the app I love the app I got hacked. I had a lock it the other day I locked my credit. Somebody tried to dio on and it worked. I was so happy. So thank you for that. But so we know experience, but there's a ton of data behind what you do. I wonder if you could share kind of where you sit in the data space and how you've seen organizations leverage data up to this point. And really, if you could address maybe some of the changes that you're seeing as a result of the pandemic, that would be great. >>Sure, sure. Well, Azaz, you mentioned experience Eyes best known as a credit bureau. Uh, I work in our marketing services business unit, and what we do is we really help brands leverage the power of data and technology to make the right marketing decisions and better understand and connect with consumers. Eso We offer marketers products around data identity activation measurement. We have a consumer view data file that's based on offline P I and contains demographic interest, transaction data and other attributes on about 300 million people in the U. S. Uh, and on the identity side, we've always been known for our safe haven or privacy friendly matching that allows marketers to connect their first party data to experience or other third parties. Uh, but in today's world, with the growth and importance of digital advertising and consumer behavior shifting to digital, uh, experience also is working to connect that offline data to the digital world for a complete view of the customer you mentioned co vid, um, we actually, we start of many different verticals. And what we're seeing from our clients during co vid is that there's a bearing impact of the pandemic. The common theme is that those that have successfully pivoted their businesses to digital are doing much better. Uh, as we all know, Kobe accelerated very strong trends to digital both in the commerce and immediately eating habits. We work with a lot of retailers. Retail is a tale of two cities with big box and grocery growing and apparel retail really struggling. We've helped our clients leveraging our data to better understand the shifts in these consumer behaviors and better segment their customers during this really challenging time. Eso think about there's there's a group of customers that it's still staying home that is sheltered in place. There's a group of customers starting that significantly varied their consumer behavior, but it's starting to venture out a little. And then there's a group of customers that's doing largely what they did before in a somewhat modified fashion. So we're helping our clients segment those customers into groups to try and understand the right messaging and right offers for each of those groups. And we're also helping them with at risk. Audi's is S O. That's more on the financial side. Which of your customers are really struggling due to the pandemic. And how do you respond? >>So it's awesome. Thank you. You know it Zafon e I mean somebody. I saw Twitter poll today asking if we measure our screen time and I said, Oh my no eso Matt, let me ask you. You spend a ton of time and financial services. You really kind of cut your teeth there, and it's always been very data oriented. You've seen a lot of changes tell us about how your customers are bringing together data, the skills that people obviously a big part of the equation and applications to really put data at the center of their universe. What's new and different that these companies are getting out of the investments in data and skills. >>That's a great question. Um, the acceleration that Amy mentioned Israel, Um, we're seeing a particularly this year, but I think even in the past few years, the reluctance of customers to embrace. The cloud is behind us. And now there's this massive acceleration to be able to go faster on, and in some ways the new entrance into this category have an advantage versus, you know, the companies that have been in the space, whether it's financial services or beyond. Um, and in a lot of ways they are are seeing the cloud and services like snowflakes as a way toe not only catch up but leapfrog your competitors and really deliver a differentiated experience to your customers to your business, internally or externally. Um, and this past, you know, however long this crisis has been going on, has really only accelerated that, because now there's a new demand. Understand your customer better your your business better with with your traditional data sources and also new alternative data sources, Um, and also be able to take a pulse. One of things that we learned which was you know, I opening experience was as the crisis unfolded, one of our data partners decided to take the data sets about where the cases where were happening from the Johns Hopkins and World Health Organization and put that on our platform and it became a runaway hit. Where now, with thousands of our customers overnight, we're using this data to understand how their business was doing versus how the crisis was unfolding in real time. On this has been a game changer, and I think it's only it's only scratching the surface of what now the world will be able to do when data is really at their fingertips. You're not hindered by your legacy platforms. >>I wrote about that back in the early days of the pandemic when you guys did that and talked about some of the changes that you guys enabled. And you know you're right about Cloud. I mean, financial services. Cloud used to be an evil word, and now it's almost become a mandate. Amy, I >>wonder if you >>could tell us a little bit more about what? What you know your customers they're having to work through in order to achieve some of these outcomes. I mean, I'm interested in the starting point. I've been talking a lot and writing a lot on talking to practitioners about what I call the data lifecycle. Sometimes people call it the data pipeline. It's it's a complicated matter, but those customers and companies that can put data at the center and really treat that pipeline is, you know, the heart of their organization, if you will, Really succeeding. What are you seeing and what really is the starting point there? >>Yes, yes, that's a good question. And as you mentioned, first party, I mean, we start with first party data. Right? First party data is critical to understanding consumers on been in different verticals, different companies. Different brands have varying levels of first party data. So retailers gonna have a lot more first party data financial services company, then say an auto manufacturer. Uh, while many marketers have that first party data to really have a 3 60 view of the customer, they need third party data as well. And that's where experience comes in. We help brands connect those disparate data sets both 1st and 3rd party baked data to better understand consumers and create a single customer view, which has a number of applications. I think the last that I heard was that there's about eight devices on average per person. I always joke that we're gonna have these enormous. I mean, that that number is growing we're gonna have these enormous charging stations in our house, and I think we're because all the different devices and way seamlessly move from device to device along our customer journey. And, um, if the brand doesn't understand who we are, it's much harder for the brand to connect with consumers and create a positive customer experience and way site that about 95% of companies are actually that they are looking to achieve that single customer view. They recognize, um, that they need that. And they've aligned various teams from e commerce to marketing to sales so at a minimum in just their first party data, and then connect that data to better understand, uh, consumers. So consumers can interact with the brand through website and mobile app in store visits, um, by the phone TV ad, etcetera. And a brand needs to use all of those touchpoints often collected by different parts of the organization and then adding that third party data to really understand the consumers in terms of specific use cases, Um, there's there's about three that come to mind. So there's first. There's relevant advertising and reaching the right customer. There's measurement s or being able to evaluate your advertising efforts. Uh, if you see an ad on if I see it out of my mobile and then I by by visiting a desktop website, understanding or I get a direct mail piece understanding that those connect those interactions are all connected to the same person is critical for measurement. And then there's, uh, there's personalization, um, which includes improved customer experience amongst your own, um, touch points with that consumer Parsons marketing communication and then, of course, um, analytics. So those are the use cases we're seeing? Great. >>Thank you, Amy. I'm at you Can't really talk about data without talking about, >>you know, >>governance and and and compliance. And I remember back in 2006 when the Federal Rules of Civil Procedure went in, it was easy. The lawyers just said, No, nobody can have access, but that's changed. One of things I like about what snowflakes doing with the data cloud is it's really about democratizing access, but doing so in a way that gives people confidence that they only have access to the right data. So maybe you could talk a little bit about how you're thinking about this topic what you're doing to help customers navigate, which has traditionally been such a really challenging problem. >>No, it's another great question. Um, this is where I think the major disruption is happening. Um, and what Amy described being able to join together 1st and 3rd party data sets. Um, being able to do this was always a challenge because data had to be moved around, had to ship my first party data to the other side. The third party data had to be shipped to me. And being able to join those data sets together, um was problematic at best. And now, with the focus on privacy and protecting P, I, um, this is this is something that has to change. And the good news is with the data cloud data does not have to move. Data can stay where it belongs experience and keep its data experience. Customers can hold on to their data. Yet the data can be joined together on this universal global platform that we call the data cloud. On top of that, and particularly with the regulations that are coming out that are going to prevent data from being collected on either a mobile device or in wet warn as cookies and Web browsers. New approaches and we're seeing this a lot in our space, both in financials and in media is to set up these data clean rooms where both sides can give access to one another but not have to reveal any P i i to do that joint. Um, this is gonna be huge right now. You actually can protect your your customers, private your consumers, private identities, but still accomplish that. Join that Amy mentioned to be able to thio, relate the cause and effect of these campaigns and really understand the signals that these data sets are trying to say about one another again without having to move data without having to reveal P. I We're seeing this happening now. This is this is the next big thing that we're gonna see explode over the next months and years to come. >>I totally agree massive changes coming in public policy in this area, and I wanted we only have a few minutes left. I wonder if for our audience members that you know, looking for some advice, what's the what's the one thing you'd recommend? They start doing differently or consider putting in place That's going to set them up for success over the next decade. >>Yeah, that's a good question. Um, you know, I think e always say, you know, first harness all of your first party data across all touchpoints. Get that first party data in one place and working together psychic back that data with trusted third parties and mats, just in some ways to do that and then third, always with the customer first speak their language, uh, where and when they want to be, uh, reached out thio on and use the information. You have to really create a better a better customer experience for your customers. >>Matt. What would you add to that? Bring us home if you would >>applications. Um, the idea that data can now be your data can now be pulled into your own business applications the same way that Netflix and Spotify are pulled into your consumer and lifestyle applications again without data moving these personalized applications experiences is what I encourage everyone to be thinking about from first principles. What would you do in your next app that you're going to build? If you had all of your consumers. Consumers had access to their data in the APP and not having to think about things, you know, from scratch. Leverage the data cloud leverage these, you know, service providers like experience and build the applications of tomorrow. >>I'm super excited when I talked to practitioners like yourselves about the future of data Guys. Thanks so much for coming on. The Cube was really a pleasure having you and hope we can continue this conversation in the future. >>Thank you. >>Anything. >>All right. Thank you for watching. Keep it right there. We've got great content. Tons of content coming at the Snowflake Data Cloud Summit. This is Dave Volonte for the Cube. Keep it right there.

>>from the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around >>the world. This is a cute conversation high, but this is Day Volonte. And as you know, we've been tracking the next generation of clouds. Sometimes we call it Cloud to two point. Frank's Lukman is here to really unpack this with me. Frank. Great to see you. Thanks for coming on. >>Yeah, you as well. They could see it >>s o obviously hot off your AIPO A lot of buzz around that. Uh, that's fine. We could we could talk about that, but I really want to talk about the future. What? Before we get off the I p o. That was something you told me when you're CEO service. Now you said, hey, we're priced to perfection, so it looks like snowflakes gonna be priced to perfection. It's a marathon, though. You You made that clear. I presume it's not any different here for you. Yeah, >>well, I think you know the service now. Journey was different in the sense that we were kind of under the underdogs, and people sort of discovered over the years the full potential of the company and I think there's stuff like they pretty much discovered a day. One. It's a little bit more, More sometimes it's nice to be an underdog. Were a bit of an over dog in this, uh, this particular scenario, but, you know, it is what it is, Andre. You know, it's all about execution delivering the results, delivering on our vision, Uh, you know, being great with our customers. And, uh, hopefully the chips will fall where they where they may. At that point, >>yeah, you're you're You're a poorly kept secret at this point, Frank. After a while, I wanted, you know, I've got some excerpts of your book that that I've been reading. And, of course, I've been following your career since the two thousands. You're off sailing. You mentioned in your book that you were kind of retired. You were done, and then you get sucked back in now. Why? I mean, are you in this for the sport? What's the story here? >>Uh, actually, that that's not a bad way of characterizing it. I think I am in that, uh, you know, for the sport, uh, you know the only way to become the best version of yourself is to be to be under the gun and, uh, you know, every single day. And that's that's certainly what we are. It sort of has its own rewards building great products, building great companies, regardless off you know what the spoils. Maybe it has its own rewards. And I It's hard for people like us to get off the field and, you know, hang it up. So here we are. >>You know, you're putting forth this vision now the data cloud, which obviously it's good marketing, but I'm really happy because I don't like the term Enterprise Data Warehouse. I don't think it reflects what you're trying to accomplish. E D. W. It's slow on Lee. A few people really know how to use it. The time value of data is gone by the time you know, your business is moving faster than the data in the D. W. And it really became a savior because of Sarbanes Oxley. That's really what it came a reporting mechanism. So I've never seen What you guys are doing is is e d w. So I want you to talk about the data cloud. I want to get into the to the vision a little bit and maybe challenge you on a couple things so our audience can better understand it. Yes. So >>the notion of a data cloud is is actually, uh, you know, type of cloud that we haven't had. I mean, data has been been fragmented and locked up in a million different places in different clouds. Different cloud regions, obviously on premise, um, And for data science teams, you know, they're trying thio drive analysis across datasets, which is incredibly hard, Which is why you know, a lot of this resorts to, you know, programming on bond things of that sort of. ITT's hardly scalable because the data is not optimized. The economics are not optimized. There's no governance model and so on. But a data cloud is actually the ability thio loosely couple and lightly Federated uh, data, regardless of where it is. So it doesn't have scale limitations or performance limitations. Uh, the way traditional data warehouses have had it. So we really have a fighting chance off really killing the silos and unlocking the bunkers and allowing the full promise of data sciences and ml On day I thio really happen. I mean, a lot of lot of the analysis that happens on data is on the single data set because it's just too damn hard, you know, to drive analysis across multiple data sets. And, you know, when we talk to our customers, they have very precise designs on what they're trying to do. They say, Look, we are trying to discover, you know, through through through deep learning You know what the patterns are that lead to transactions. You know, whether it's if you're streaming company. Maybe it's that you're signing up for a channel or you're buying a movie or whatever it is. What is the pattern you know, of data points that leads us to that desired outcome. Once you have a very accurate description of the data relationships, you know that results in that outcome, you can then search for it and scale it, you know, tens of million times over. That's what digital enterprises do, right? So in order to discover these patterns enriched the data to the point where the patterns become incredibly predictive. Uh, that's that's what snowflake is formed, right? But it requires a completely Federated Data mo because you're not gonna find a data pattern in the in the single data set per se right? So that's that's what it's all about. I mean, the outcomes of a data cloud are very, very closely related to the business outcomes that the user is seeking, right? It's not some infrastructure process. It has a very remote relationship with business outcome. This is very, very closely related. >>So it doesn't take a brain surgeon to look at the Trillion Years Club. And so I could see that I could see the big you know, trillion dollars apple $2 trillion market cap companies. They got data at the core, whereas most companies most incumbents. Yeah, it might be a bottling plant that the core, some manufacturing or some other processes they put, they put data around it in these silos. It seems like you're trying toe really? Bring that innovation and put data at the core. And you've got an architecture to do that. You talk about your multi cluster shared storage architecture. You mentioned you mentioned data sharing it. Will this, in your opinion, enable, for instance, incumbents to do what a lot of the startups were able to do with the cloud days? I mean they got access to data centers, which they they couldn't have before the cloud you're trying to do with something similar with data. >>Yeah, so So, you know, obviously there's no doubt that the cloud is a critical enabler. This wouldn't be happening. Uh, you know what? I was at the same time, the trails that have been blessed by the likes of Facebook and Google. Uh, e the reason those enterprises are so extraordinary valuable is is because of what they know. Uh, you know, through data and how they can monetize what they know through data. But that is now because that power is now becoming available, you know, to every single enterprise out there. Right, Because the data platform, the underlying cloud capabilities, we are now delivering that to anybody who wants it. Now, you still need to have strong date engineering data science capabilities. It's not like falling off a log, but fundamentally, those capabilities are now, you know, broadly accessible in the marketplace. >>So we're talking upfront about some of the differences between what you've done earlier in your career. Like I said, you're the worst kept secret, you know, Data domain. I would say it was sort of somewhat of a niche market. You you blew it up until it was very disruptive, but it was somewhat limited in what could be done. Uh, and and maybe some of that limitation, you know, wouldn't have occurred if you stay the price, uh, independent company service. Now you mop the table up because you really had no competition there, Not the case here. You you've got some of the biggest competitors in the world, so talk about that. And what gives you confidence that you can continue to dominate, >>But, you know, it's actually interesting that you bring up these companies. I mean, data. The man was a scenario where we were constrained on market and literally we were a data backup company. As you recall, we needed to move into backup software. Need to move the primary storage. While we knew it, we couldn't execute on it because it took tremendous resource is which, back in the day, it was much harder than one of this right now. So we ended up selling the company to E M. C and and now part of Dell. But way short, uh, we're left with some trauma from that experience, Uh, that, you know, why couldn't we, you know, execute on that transformation? So coming to service now, we were extremely. I'm certainly need personally, extremely attuned to the challenges that we have endured in our prior company. One of the reasons why you saw service now break out at scale at tremendous growth rights is because of what we have learned from the prior journey. We're not gonna ever get caught again in a situation where we could not sustain our markets and sustain our growth. So if service I was very much the execution model was very much a reaction to what we had encountered in the prior company. Now coming into snowflake totally different deal. Because not only is there's a large market, this is a developing market. I think you've pointed out in some of your broadcasting that this market is very much in flux on the reason is that you know, technology is now capable of doing things for for people and enterprises that they could never do before. So people are spending way mawr resource is than they ever thought possible on these new capability. So you can't think in terms of static markets and static data definitions, it means nothing. Okay, These things are so in transition right now, it's very difficult for people you know to to scope that the scale of this opportunity. >>Yeah. I wanna understand you're thinking around and, you know, I've written about the TAM, and can Snowflake grow into its valuation and the way I drew it, I said, Okay, you got data Lakes and you got Enterprise Data Warehouse. That's pretty well understood. But I called it data as a service to cover the closest analogy to your data cloud. And then even beyond that, when you start bringing in the edge and real time data, uh, talk about how you're thinking about that, Tam. And what what you have to do to participate. You have toe, you know, bring adjacent capabilities, ISAT this read data sharing that will get you there. In other words, you're not like a transaction system. You hear people talking about converge databases, you hear? Talk about real time inference at the edge that today anyway, isn't what snowflake is about. Does that vision of data sharing and the data cloud does that allow you to participate in that massive, multi $100 billion tam that that I laid out and probably others as well. >>Yeah, well, it is always difficult. Thio defined markets based on historical concept that probably not gonna apply whole lot for much longer. I mean, the way we think of it is that data is the beating heart of the digital enterprise on, uh, you know, digital enterprises today. What do you look at? People against the car door dash or so on. Um, they were built from the ground up to be digital on the prices and data Is the beating heart off their operation Data operations is their manufacturing, if you will, um, every other enterprise out there is is working very hard to become digital or part digital and is going to learn to develop data platforms like what we're talking about here to data Cloud Azaz. Well, as the expertise in terms of data engineering and data scientist to really fully become a digital enterprise, right. So, you know, we view data as driving operations off the digital enterprise. That's really what it iss right data, and it's completely data driven. And there's no people involved. People are developing and supporting the process. But in the execution, it is end to end. Data driven. Being that data is the is the signal that initiates the process is technol assess. Their there being a detective, and then they fully execute the entire machinery probe Problematic machinery, if you will, um, you know, of the processes that have been designed, for example, you know, I may fit a certain pattern. You know, that that leads to some transactional context. But I've not fully completed that pattern until I click on some Lincoln. And all of a sudden proof I have become, you know, a prime prospect system, the text that in the real time and then unleashes Oh, it's outreach and capabilities to get me to transact me. You and I are experiencing this every day. You know, when we're when we're online, you just may not fully re election. That's what's happening behind the scenes. That's really what this is all about. So and so to me, this is sort of the new online transaction processing is enter and, uh, you know, data digital. Uh, no process that is continually acquiring, analyzing and acting on data. >>Well, you've talked about the time time value of of data. It loses value over time. And to the extent that you can actually affect decisions, maybe before you lose the customer before you lose the patient even even more importantly or before you lose the battle. Uh, there's all kinds of, you know, mental models that you can apply this. So automation is a key part of that. And then again, I think a lot of people like you said, if you just try to look at historical markets, you can't really squint through those and apply them. You really have toe open up your mind and think about the new possibilities. And so I could see your your component of automation. I I see what's happening in the r P. A space and and I could see See these this massive opportunities Thio really change society, change business, your last thoughts. >>There's just there's just no scenario that I can envision where data is not completely core in central to a digital enterprise, period. >>Yeah, I think I really do think, Frank, your your your Your vision is misunderstood somewhat. I think people say Okay. Hey, we'll bet on salute men Scarpelli the team. That's great to do that. But I think this is gonna unfold in a way that people may be having predicted that maybe you guys, yourselves and your founders, you know, haven't have aren't able to predict as well. But you've got that good, strong architectural philosophy that you're pursuing and it just kind of feels right, doesn't it? >>You know, I mean, one of the 100 conversations and, uh, you know, things is the one of the reasons why we also wrote our book. You know, the rights of the data cloud is to convey to the marketplace that this is not an incremental evolution, that this is not sort of building on the past. There is a real step function here on the way to think about it is that typically enterprises and institutions will look at a platform like snowflakes from a workload context. In other words, I have this business. I have this workload. This is very much historically defined, by the way. And then they benchmark us, you know, against what they're what they're already doing on some legacy platform. And they decided, like, Yeah, this is a good fit. We're gonna put Snowflake here. Maybe there, but it's still very workload centric, which means that we are essentially perpetuating the mentality off the past. Right? We were doing it. Wanna work, load of the time We're creating the new silos and the new bunkers of data in the process. And we're really not approaching this with level of vision that the data science is really required to drive maximum benefit from data. So our arguments and this is this is not an easy arguments is to say, toc IOS on any other sea level person that wants to listen to that look, you know, just thinking about, you know, operational context and operational. Excellent. It's like we have toe have a platform that allows us unfettered access to the data that, you know, we may need to, you know, bring the analytical power to right. If you have to bring in political power to a diversity of data sets, how are we going to do that right? The data lives in, like, 500 different places. It's just not possible, right, other than with insane amounts of programming and complexity, and then we don't have the performance, and we don't have to economics, and we don't have the governance and so on. So you really want to set yourself up with a data cloud so that you can unleash your data science, uh, capabilities, your machine learning your deep learning capabilities, aan den, you really get the full throttle advantage. You know of what the technology can do if you're going to perpetuate the silo and bunkering of data by doing it won't work. Load of the time. You know, 5, 10 years from now, we're having the same conversation we've been having over the last 40 years, you know? >>Yeah. Operationalize ing your data is gonna require busting down those those silos, and it's gonna require something like the data cloud to really power that to the next decade and beyond. Frank's movement Thanks so much for coming in. The Cuban helping us do a preview here of what's to come. >>You bet, Dave. Thanks. >>All right. Thank you for watching. Everybody says Dave Volonte for the Cube will see you next time

>>from around the globe. It's the Cube with digital coverage of a new era and database management brought to you by Nutanix. >>Welcome back. I'm still minimum and we're covering Nutanix Is New Era database launch Of course, we had to do instead of conversation with Monica Ambala talking about era to Dato and to dig into it a little bit further. We have some new tennis guests as well as what? One of their close partners. So going across the channel, first of all, happy to welcome to the program. Uh, the new kid UPA she is the gsc strategy and go to market with Nutanix sitting in the middle chair we have on and Akila whose product marketing leader with Nutanix and then from HCL happy to welcome to the program Tasing who is the senior vice president with HCL Technologies. I mentioned all three of you. Thank you so much for joining us. >>Glad to be here, >>right? Uh they knew What? Why don't we start with you? You handle the relationship between Nutanix and HCL. As I said, some exciting announcements database services help us understand how Ah partner like HCL takes the technology and what will help bring it to market. >>Let me start by thanking used to for this opportunity. Head Seal is a very significant partner for Nutanix and we've had this partnership for a long time now. It's one of our long standing partnership. Over the five years we've closed over 100 accounts across all three theaters. Trained professionals both on the Nutanix side on the outside, on built a 3 60 relationships so we can deliver the best experience around solutions to our partners. In the very recent announcement, we're looking to build a database as a service offering. With that CL we want Thio leverage are intelligent technology that allows us to simplify off and increase operating efficiency. Andi Couple it with head seals ability to offer world class services on it. It's a scale to reach the go to market needs needed right. We're very confident that the solution is going to drive significant incremental business for both our companies. >>Excellent taste. We would love to hear from your standpoint. What is it that excites you? We we know HCL knows the data space real well. So I think you've got some customers that air looking to take advantage of some of these new offerings. >>Yeah, So if you look at where the focus has been so far, most of the focus is on taking applications to cloud and moving them from VM two probably containers one of the most. Uh, I won't say, uh, neglected, but the space that needs to change now is the entire database space on. If you look at how customers are managing databases today, they have taken hardware on a KPIX model. They have the operating system and the database licenses on L. A model from the E. M s on. Then they have, ah, teams which are siloed depending upon the database technology that is there in the environment and managing that I think that whole model is has to change, enabling customers to transform Onda accelerate the digital transformation journey on. That is where our offering off database as a service ises very unique because it offers a full stack off services which includes right from hardware and all the way to operations on a completely utility model powered by the Nutanix era. >>Yeah, on it might make sense if you could give us a little bit of a broader context for your users. Some of the data that you have around this offering, >>yeah, you know, attend effect. All the solution, our joint solutions. Our customers, uh, they are trying to deliver the best individual experience, right? That's at the heart of it. What they're trying to do, I'll give you a couple of customer examples. For example, Arbil Bank in India. You know, they deployed their database solutions and applications, and Nutanix got 16 fasters application response. That means like they used to take 180 seconds. Uh, Thio logging into the application. And now it's, uh, 20 seconds, 36 times faster. Another example I could give. I can give many examples, but when this one is really interesting, Delaware Valley community held, you know, at the time of Kobe they went remote. They started working from home and they had medical systems applications. EMR electronic medical record applications and used to take even before they were working from home, is take like 171 seconds to log into medical systems before they could, you know, talk to their patients and look at their, you know, health results and everything and that from 171 seconds, it went to 19 seconds. So these are some of the values that customers seeing when it comes to delivering the individual experience to their customers. >>Yeah, absolutely. We've seen police stage go ahead. >>Yeah, and I just had to What men? Who said that? It's also the ability tohave self service with dynamic provisioning capability that really brings the value toe the to the I T teams and to the application teams who are consuming these services. So we have cases where customers were waiting for about a week, 10 days for the environments to be provisioned to them. And now it's a matter of seconds or minutes where they can have a full fledged environments leading to develop a productivity. And that also really adds the whole acceleration that we just spoke about. >>Yeah, we we've absolutely seen such a transformation in database for the longest time. It was, you know, a database. It didn't change too much. That's what everything run on Now there's a lot of flexibility. Open source is a big piece of what's going on there. I'd like to come back to you and you know, they know. I know you're gonna want to chime in here. You know, HCL doesn't just, you know, take this off the shelf and, you know, resell it, help us understand. You know what is unique about the offering that that HCL brings market? Uh, with with >>Nutanix. Right. So one is that we have standardized reference architectures, which really x ray the time to consume the offering. We're not building anything from from from ground up. Three Nutanix is also part off our velocity framework, which helps customers deploy software defined infrastructure as the as a foundation element for their for their private cloud. Now, what is unique is also the ability toe not only provide operations on different databases that are there in the environment on a completely utility model, but also help customers, you know, move to cloud and adopt the database clouded of databases and then manage the whole show seamlessly using using the BP platform and that really, you know, if you look at the trend that is there, there's a short term impact on the long term impact off transformation. In the short term, there's hardly an industry which is not touched by by covert on most of our customers are either looking at cost or initiatives or are looking at ah platform, which will help them in a weight or find new business model to to sail through. In the long term, we strongly believe that the customers will be in a hybrid, multi cloud world where they will still have the heritage environments. The article and the Sequels on a lot off cloud native data business will also start coming into picture. How do you manage is also seamlessly is what will be the next challenge for for most of the customers. And that's where we come in, along with Nutanix, to solve the problem. >>Well, very simply put right, we have different categories of customers. One off them refers to buy the ingredients and make their own meal on some really large customers, and global customers prefer to buy the meal and pay for it on on as consumer basis. What that seal does is take era, which simplifies a lot of the database operations, puts it into a full stack solution and gives the customer the full stack solution. Everything from assessing that environment to deploying, to making sure that the designers I accurate and then of course, the day and through they do through and, uh, uh, environment, right. So literally the customer can Now I'll offload any off their data center, our database management and operation to hit cl from my perspective on do rest assured, run their projects toe, etc. Also, excel becomes their extended arm, the beauty off. It is also like working with dead C. Elgar now able to offer the entire solution on a pay as you go model or pay as you use model, which is very relevant to the existing times where everybody is trying to cut their Catholics costs and and optimized on the utilization. >>Well, great. Great to hear about that. You've mentioned that this partnership has been for many years, so I know you've got plenty of joint customers. Anything specifically could share about these new offerings on. And I know you've got a lot of the customer stories there. Maybe you could start would look love, freedom. The rest of you, >>Thio, I'll start what? You know, Like I talked about a couple of customers. But recently I'm really excited about. And this is something that to be a announcing today as well. Ah, study that we did with Forrester called Forrester T I study, which is what it means total economic impact study. And what they do is that they topped with customers, uh, interviewed them, four of them. And based on their experience, uh, you know what? They observe what kind of benefit they got, what challenges they had, what was cause they built an economic model. And based on that economic model, they found that customers were rolled all off them were able to get their payback within six months. So Bala talked about it earlier that, you know, like all the great experience, all the great value that we offer, but at a very, very good cost. So the six less than six months payback was used and the r y for the three years period and again, this is ah, model based on four enterprises was 2 91 100% almost like three times mawr. So whatever they invested, I think on an average day the cost was 2.3 million and the benefit was nine million or so so huge value customers have observed already. And with this new launch, I believe that it will just go to the next level. All the things about provisioning copy data saving that the stories All of that adds to the R Y that I'm talking about and our joint customers with SCL or otherwise, who are customers who are running their applications, their business critical applications on you can X Platform managed by era an era is built out off a bunch off best practices that over time that we have done. I talked about custom performance earlier, and a lot of the performance comes from fine tuning. You do that like a lot of tea tuning and to get to the right kind of performance. Uh, era comes with that, those best practices. So when your provisioning an application, you know, it gives you you don't have to do all that tuning. So that's the value customers are experiencing. And I'm really excited about the joint customers what they could experience and benefit out off the new expanded solution. >>Great Tiger. Any other customer examples that you'd like to share? >>Well, we got a lot of go ahead page, >>but it's okay. >>No, I was just saying that we've had a lot of success with Head cl across the board anywhere from data center organization Thio v. D. I. We had a very large manufacturing company in America where we partner together. They have a huge number of sub brands. We partnered together to go evaluate that environment and then also even that is a B infrastructure with databases. It's a relatively new offering we're announcing today. But we're leveraging the expertise that SCL has in the market, uh, to go to go deeper into that market with cl eso. I will leave it to page to give us the NCL examples. >>So one thing that is happening is the very definition off infrastructure and infrastructure operation itself is changing. So a couple of years ago, for many of our customers, it was about operating system management, hardware management, network management and all the use. Uh, the concept that you're going back to customer is about platform operations. That means everything to do with application operations. Downward is going to be done by one integrated unit. Now, with Nutanix, we can we can really bring a lot of change, and we're bringing a lot of change in our in the operations model for for lot off a large customers where earlier you had siloed teams around Compute network storage, offering system databases both at the Level two and level three, and you had a level one, which was basically command center. Now, we're saying is that with the artificial intelligence and machine learning driven OBS, you can practically eliminate the need for command center on the level two layer because the platform enables you toe be multi skilled. You need not have siloed engineers looking after databases separately on and operating system separately. You can have the same sort of people who are cross train, multi skilled, looking at the entire state. On at level three. You may want to keep people who are deep into databases as a separate team, then from people who are managing the Nutanix platform, which is a combination off compute storage and and and and the SCN. So that's the change that we're bringing. A lot of our customers were going about infrastructure, platform modernization, Azaz, the public cloud or hybrid clubs. >>Well, I think you're really articulated well, that modernization journey we've seen so many companies going through. The thing I've been saying with Nutanix for years is modernize the platform, then you can modernize everything that runs on top of it. All the applications on, of course, did databases a major piece of this on. And that brings up a point I want to get your take on. We haven't talked about developers, you know, the DEV ops trend. Something we've seen, you know, huge growth for for a number of years. So what >>does this >>mean from developers? This something that you know, mostly the infrastructure team's gonna handle. Or how do you bridge that gap to the people that really are? You know, building and building and building the APS. >>Yeah. And in this digital world, you know the cycle time from idea to production. Everyone is trying to reduce that. What that means is that things are moving left. People are trying to develop and test early in the life cycle when it is easy to find a problem and easy to and cheaper to fix. Right. So for that, you need a your application environment, your application and database available to test and develop in, uh, you know, like in volume. And that's where databases the service era helps developers and develops professionals to provision in the whole infrastructure for testing and involvement in hundreds and thousands of them at the same time without, you know, worrying about the storage back back and how much story it is consuming. So it is. It helps developers to to really expedite their development and testing left lifecycle ultimately resulting in excellent and unique experience. >>Yeah, absolutely way no. Of just moving faster. Being able to respond to the business so critically important. Uh, they know Tasia wanna let you have the final word Talk about the partnership and what we should expect, you know, in the coming months and quarters. >>So, uh, I'll go first. And then we can come in, uh, a salon and Nutanix you to share the same values where we believe that we need to provide a very innovative platform for our customers to accelerate their digital transformation journey. No matter what it is right, we share common values and way have a 3 60 degree relationship. It started way back in 2015 and we have come a long way since then. A C also does engineering services for for Nutanix, and we have closed about 850 r plus people who has prayed and 35 on Nutanix Solutions. Providing manage services to our customers on Nutanix is also part off our software defined infrastructure portfolio on we're taking it to our customers as part of our entire infrastructure platform modernization that, I suppose talk about earlier three recent announcement off Nutanix clusters running on AWS. I think it's a significant announcement and it will provide a lot off options to our customers. And as an S, I, uh, you know, we are able to bring a lot of value to our customers. We're looking at adopting cloud the database as a service offering. I think we're very excited about it. I I think we have about 300 plus customers, and many of them are still stuck with the way they are managing databases the old way. And we can bring in a lot of value to those customers, whether it is about reducing cars or increasing agility or helping them modern ice, The platform one ended up hybrid multi club >>business critical lapse are growing, are still growing, and data is pretty much gold in these scenarios, right? It's it's doubling every two years, if not more with every transaction being remote today with zeal. We actually look forward to addressing that market and optimizing the environment for our customers. Both of our companies believe in partnership crossed and the customer first mindset. And when you have that belief, trust comes with delivering the best experience to our customers. So we're looking forward to this partnership and you're looking forward to growing our joint revenue and modernizing our customers platforms with this often? >>Well, I wanna thank all three of you for for sharing the exciting news. Absolutely. It looks like a strong partnership. Lots of potential there for the future. So thank you so much for joining us. Thank you for >>having thank you. Mhm. >>All right, when I think the audience were watching this lot with Nutanix, the new era in database management personally, a big thank you to the Nutanix community has been a pleasure being able to host these interviews with Nutanix for for many years. So I'm still minimum and thank you as always for watching the Cube

>>from around the globe. It's the Cube with digital coverage of CONMEBOL. Future Ready 2020. Brought to you by combo. Hi, I'm Stew Minuteman. And this is the Cube's coverage of Con Volt Future ready event Welcoming back to the program. Fresh off the keynote stage. Sanjay Mirchandani. He's the CEO of Con Volt. Sanjay. Nice job on the keynote. And thanks so much for joining us. >>Thanks to Good to see you again. >>Nice to see you too. So, Sanjay, about a year and 1/2 into your journey with Conn Volt, you took over. And you know what it looks like? You've almost completely refreshed the portfolio there. Start a little bit, you know, future. Ready. Tell us how you're getting Conn Volt and its customers ready to be prepared for what happened today as well as the >>right. So, you know, we've we've given visit The past 18 months, have flown by in the past four or five. Even faster. Um, the change. You know, the change that we've had all deal with us as organizations has been tremendous. We've been hard at work. When I came on board, I should have talked about how we were setting out to simplify, innovate and execute all three of those pillars and, ah, future ready, which I love as a term completely embodies what I think the work we've been up to and what the world needs today, which is really getting it ready for whatever's next. And, you know, and it's coming together of innovation, simplification and and hopefully you'll agree some good execution to bring it all together. Yeah, so we've been busy. >>Sanjay, you talked a bit about just the moment in time that we're in. Wonder if you could bring us inside. You know your customers. So there's certain things that we saw for a couple of months. People put a pause on. Other things absolutely have been accelerated. We talk to customers about their adoption of cloud, you know, digital transformation. It's one of those things. That boy, I hope I'm through some of those or you know, can be as agile as possible. But, you know, what do you hearing specifically from our customer base and how they're dealing with things? >>You know, Cto, I touched a little bit on that during my keynote. And you know this this this this time that we're in has really caused, I think a couple of shifts. The first structural shift was Oh, hey, this thing is here to stay and let's get our employees Working and productive and keep the business is running and keeping them safe and everything else. That first shift happened right on. Honest about What was it that March, April and businesses small and big had to figure out how to take go from their their their operating model into, ah, remote. With the remote model, you re prioritize and you thought through what was important at the time and what it was was really getting laptops into the hands of your employees, getting them safe into their working environment, making sure your business processes leaning in that direction. You could take care of your customers. And so that was sort of the first structural faith, the second structural failures. Okay, how do we really drive productivity? One of the new priorities. What do we need to do, what you want to invest in? What do you want to pull back from? And from our vantage point from A from a technology and data point of view, what we're hearing is the themes that if I had a paraphrase of conversations I have with CIOs, it's NGOs. It's really around a simplification. This is a This is a great time to really simplify and, you know, and make sure that you're working with the tried and tested. This is not the time to experiment. This is not the time for esoteric. This is really about simplifying and working with the tried and tested. The second is really about focusing on skills, you know, this is you need you need to be able to leverage, and you need to be able to bring productivity from the from the people that you have an I t. And really focus around that that's, you know, that sometimes for gotten, you know that I like to call them. The unsung heroes of technology has just been pushed into their homes. They're now doing their jobs, longer hours, tougher scenarios. They have no access to their data centers. So it's over. So let's think about skills and the third, you know, the third thing, really that has been propelled into this conversation is cloud. So if you were on a journey, you're off the journey you need to get there quickly, okay? And you need to really newly leverage a light touch, low touch, remote sort of capability. A So fast is you can't call a digital transformation. Call it whatever you'd like to say. But it is about truly leveraging the cloud in a way that that was no longer, you know, a one year, two year three applying. You just have to bring it right to those kinds of things we're hearing and dealing with. >>Yeah, it's so important, Sanjay. Especially that simplicity piece. You know, I remember a few years ago there were certain customers that were adopting cloud, and it was the reminder. Oh, hey, your data protection in your security, you need to make sure you take care of that when you go to the cloud. And unfortunately, you know, some of the people that are now accelerating things you have to quickly say Oh, wait. I can't work this in a few months. I need to take care of this upfront, so help us understand a little bit. You know, the announcements that you've made. How are you making sure that you're ready for customers? The simplicity that they need to take advantage of the innovation and opportunity that the cloud on solutions provider >>absolutely and and make a mistake for me to. Simplification is not just the technology is easy to use, even though that is a big part of what we're working on and working and delivering through these announcements. But we've also got to make sure that the partnerships that we that we that we have lend themselves to what customers need, you know, engineered better its source not in the field, you know, and then and then the ecosystem to make the technology available and consumed commercially in the way that customers would like to keep that simple to. But today, if I just focus on the portfolio, you know, we've we've you could say we've completely rebuilt this incredible stack of technology that we've built this company out and, you know, and we weave in a nutshell. What we've done is announced A. We've taken our backup and recovery suite and be saying we've got a new company, backup and recovery product. We've got a brand new con Volt disaster recovery product. You can get them together as a unit Azaz the complete backup and recovery suite, if you would. So that's one big set of offerings. The second and you know the second is is we bought Hedvig sort of next generation software defined storage technology company last year, and we've been feverishly work quietly at work, integrating Hedvig into calm bolt not just as a company, but in the technology and our new hyper scale technology. Hyper scale. ECs is the embodiment of those two things coming together, the best of data protection from Con Volt and the best storage subsystem to drive that from Hedvig, also from console. So the two come together on all of this technology, whether it's the suite that I mentioned or the hyper scaler, all of it you can. You can mix and match any way you want with it with a world class user interface or user interfaces if you want command lines. If you want AP ICE will keep it open, all of it to you. In addition, we've got announcements or under Activate Suite on. Recently, we talked about our partnership with Microsoft with the metallic azure sort of combination for customers. So it's ah, it's a left to right set of announcement with simplification threatened right through it. >>Sanjay, you mentioned partnerships. Ah, a little bit before the show, you had, of course, the extended partnership with Microsoft with metallic. Maybe give us just a little bit more color about you know how, Con Volt make sure their position and working closely with those hyper scale >>hours. Yeah, you know, and we work with all the hyper scaler. So, you know, there we are probably the most prevalent data protection technology, if you would in the public cloud. And most of the way we talk about over an exabyte that we've helped customers, right, that the cloud is just one data point we've we've been, you know, seen is from the outside in as being the transport capability across across hybrid cloud scenarios. The partnership, the partnership with Microsoft and Microsoft Azure in particular, is the coming together of these things because customers, when we talk to customers and Microsoft office of customers be here from them, they want the ability to be, if you know, as they get more prevalent in the cloud as their workloads get more more pervasive in the cloud, they want to make sure that the same industrial strength data protection cloud in that they had well while they were on prayer for primarily on Prem. Our solutions are completely hybrid. And so the partnership really brings together again. You know, technology that's engineered better together, our data protection and their their cloud best in class our channels working, working together and making sure that it's easy for customers to work work with us. And we're available on the azure marketplace and our field forces also aligned around it. So it's again a 3 60 kind of conversation that we have with customers as much as much of today's announcements. >>Yeah, Sanjay, you talked about the hyper scale er's. You mentioned that the integration of the Hedwig Solution work with Dev Ops and really the cloud native type solutions. Of course, one of the things everybody's looking at when you were hired to this job is you've got background in the automation in developer world. So you know, how is that scene in the update? The portfolio really that embracing of cloud native and develop our environments? >>Cloud without automation is not a cloud, right? It's just it's just it's just infrastructure that's put somewhere else. It's deep, deep degrees of it off automation that really bring cloud to life. Right? And I was fortunate that have been in the Dev ops world for a while in a market leading with marketing product. And I was very pleasantly surprised when I when I came to convert and sell the deep degrees of automation and work flows that are core technology had, with Hedvig acquisition being a platform layer being the storage layer that is multi protocol and appeals incredibly to Dev Ops engineers because everything in the product you know is call a bill through an A p I for a set of AP eyes. It's it's Richard's got work flows and and it's multi critical. So whether you're using VMC or you're building the next generation container applications or you're just using object storage, it doesn't matter. We can mix and match it across, you know, private and public cloud environments, and it's all culpable and it's all programmable. It's all automated on as much as you want >>it. All right, So, Sanjay, I know we can't talk too much about Financial Piece is where we are in the quarter. But one of the things Dave Volante and I were discussing and looking at Kahn Volt. You know, there's some good data, you know, especially if you look at win rates against some of the some of the newer players in this space that the data that we have from ET R was showing, you know, increased win rates for Con Volt. Just could you give us a little bit of your competitive landscape view you talked about? Customers don't want to take too much risk, you know? How do you balance between being, you know, a company with a large install base? But you want to be, you know, more modern? >>Oh, yeah. And you know, the use cases we're talking about. The cloud that we're seeing those leaders are today's use cases, not yesterday's use cases, and we're winning in the base is the fact that we respect that customers are coming from Okay, There's a lot of stuff that runs that business that is still good. That isn't in the cloud that they're they're working their plants journey from that to something else as well. That's where we're leading in areas where they have it in the public cloud, and we always like to stay 1 to 2 steps ahead of the hard problems our customers going to encounter. So our portfolio is is absolutely cloud ready. Our portfolio is rich in that in that capability, and we're not slowing down. You know, we're winning because we have the breath of technology that we support. Both, You know, source source data that customers want o protect and target scenarios where maybe the hyper scaler or anything else where customers want to take it. And the flexibility, the second thing. And if you heard the interview I did with Run from from Johns Hopkins, it's the optimization off our technology around each of those cloud scenarios that gives our customer's true, you know, true value around the compute and storage decisions they have to make. And we helped them make through deep through deep degrees of AI and ML built in. So so it's not just about moving bits. It's about optimizing all of that on the entire life cycle of that data, from the point it's created to the point. >>Excellent. Well, Sunday. Want to let you have the final word? Give us what you want customers to have as the take away from today's future. Ready event? >>Sure. So, first of all, I wanted to, you know, I want to thank all our our audience here, our customers for being with us. It's being with us as a customer, being looking at us as a prospect for technology. We are investing like, you know, we've invested over a $1,000,000,000 over over a period of time as a company in data protection, and we're taking that to a whole new level with the innovations that we're bringing to the table. So, you know, we truly believe that the journey with as it pertains to data the journey to the cloud requires you to be able to think through the life cycle from storing, protecting, optimizing and using that data all the way through. And our solutions can be used independently. Best of class across each of them or together better together. And, you know, we I I urge you to take a few minutes and look at some of the some of the great innovations we've brought to table and rest assured that everything we're doing eyes with hybrid cloud in mind and is it is completely cloud optimized. >>All right. Well, Sanjay Mirchandani. Thank you so much for joining us. Congratulations to you and the team on the work on the updates. Definitely. Look forward to hearing more in the future. >>Thanks. Too good to be here. >>Alright, stay tuned. We've got more from Con vault Future ready on student a man. And thank you for watching the Cube. Yeah, yeah.

>>from around the globe. It's the Cube covering HP. Discover Virtual experience Brought to you by HP. >>Welcome to the Cube's coverage of HP Discover 2020 Virtual Experience. I'm Lisa Martin, and I'm pleased to be joined by two guests from HP longtime partner Tech Data. We have calling Blair the vice president of sales and marketing of I. O. T. And Data Solutions and David Smith, H P E Pre Sales Field Solutions are common. And David, Welcome to the Cube. Thanks, Lisa. Great to see. So let's start with the calling. HP and Technical have been partners for over 40 years, but tell our audience a little bit about tech data before we get into the specifics of what you're doing and some of the cool I o. T. Stuff with HP. I >>think that the Tech data is a Fortune 100 distributor. We continued to evolved to be a solutions aggregator in these next generation technology businesses. As you've mentioned, we've been serving the I T distribution markets globally for for 40 plus years, and we're now moving into next generation technologies like Wild Analytics, I O. T and Security bubble Lifecycle Management services. But to be able todo position ourselves with our customer base and the needs of their clients have. So I'm excited to be here today to talk a little bit about what we're doing in I, O. T. And Analytics with David on the HPC side >>and in addition to the 40 plus years of partnership calling that you mentioned that Detected and HP have you've got over 200 plus hp. Resource is David, you're one of those guys in the field. Talk to us about some of the things that you're working on with Channel Partners Table David to enable them, especially during such crazy times of living and now >>absolutely, absolutely so. What we can do is we can provide strong sales and technical enablement if your team, for example, wants to better understand how to position HP portfolio if they require assistance and architect ing a secure performance i o t. Solution. We can help ensure that you're technical team is fully capable of having that conversation, and it's one that they're able to have of confidence, weaken validate the proposed HP solutions with the customers, technical requirements and proposed use case. We can even exist on a customer calls, if it would, would benefit our partner to kind of extend out to that. We also have a a a deep technical bench that Colin can speak to in the OT space toe lean on as well. For so solution is that kind of span into the space beyond where HP typically operates, which would be edge, compute computing and network. Sic security. >>Excellent call and tell me a little bit about Tech Data's investments in I o. T. When did this start? What are you guys doing today? >>Sure, we started in the cloud space. First tackle this opportunity in data center modernization and hybrid cloud. That was about seven years ago. Shortly thereafter we started investing very materially in the security cyber security space. And then we follow that with Data Analytics and then the Internet of things. Now we've been in those spaces with our long term partners for some time. But now that we're seeing this movement to the intelligent edge and a real focus on business outcomes and specialization, we've kind of tracked with the market, and we feel like we've invested a little bit ahead of where the channel is in terms of supporting our ecosystem of partners in this space. >>So the intelligent edge has been growing for quite some time. Poland in the very unique times that we're living in in 2020 how are you seeing that intelligent edge expand even more? And what are some of the pressing opportunities that tech data and HPC i O T solutions together can address? >>So a couple. So the first is a Xai mentioned earlier just data center modernization. And so, in the middle of code 19 and perhaps postcode 19 we're going to see a lot of clients that are really focused on monetizing the things that they've got. But doing so to drive business outcomes. We believe that increasingly, the predominance of use cases and compute and analytics is going to move to the edge. And HP has got a great portfolio for not just on premise high performance computing but also hybrid cloud computing. And then when we get into the edge with edge line and networking with Aruba and devices that need to be a digitized and sense arised, it's a really great partnership. And then what we're able to do also, Lisa, is we've been investing in vertical markets since 2000 and seven, and I've been a long the ride with that team, most all of that way. So we've got deep specialization and healthcare and industrial manufacturing, retail and then public sector. And then the last thing we've kind of turned on here recently just last month is a strategic partnership in the smarter cities space. So we're able to leverage a lot of those vertical market capabilities. Couple that with our HP organization and really drive specialized repeatable solutions in these vertical markets, where we believe increasingly, customers are going to be more interested in a repeatable solutions that can drive quick proof of value proof of concepts with minimal viable what kinds of products. And that's that's kind of the apartment today with RHB Organization and the HP Corporation >>David. Let's double click into some of those of vertical markets that Colin mentioned some of the things that pop into minor healthcare manufacturing. As we know, supply chains have been very challenged during covered. Give us an insight into what you're hearing from channel partners now virtually, but what are some of the things that are pressing importance? >>So from a pressing and important to Collins exact point, and your exact point as well is really it's all about the edge computing space now from a product perspective Azaz Colin had mentioned earlier. HP has their edge line converged systems, which is kind of taking the functionality of OT and edge T Excuse me of OT and I t and combine it into a single edge processing compute solution. You kind of couple that with the ability to configure components such as Tesla GP, use in specific excellent offerings to offer an aid and things like realtime, video processing and analytics. Uh, and a perfect example of this is, ah so for dissing and covert space. If if I need to be able to analyze a group of people to ensure they're staying as far apart as possible or, you know within self distant guidelines, that is where kind of the real time that's like an aspect of things can be taken advantage of same things with with the leveraging cameras where you could actually take temperature detection as as well, so it's really kind of best to think of Edge Lines Solutions is data center computing at the edge kind of transition into the Aruba space. Uh Rubio says offerings aid in the island Security is such a clear pass device inside, which allows for device discovery of network and monitoring of wired and wireless devices. There's also Aruba asset tracking and real time location of solutions, and that's particularly important in the healthcare space as well. If I have a lot of high value assets, things like wheelchairs, things like ventilation devices, where these things low located within my facilities and how can I keep keep track of them? They also, and by that I mean HP. They also kind of leveraging expanse ecosystem of partners. As an example, they leverage thing works allow their i o t solutions as well, when you kind of tying it all together with HP Point. Next to the end, customers provided with comprehensive loyalty solution. >>So, Colin, how ready? Our channel partners and the end user customers to rapidly pivot and start either deploying more technologies at the edge to be able to deliver some of the capabilities that David talked about in terms of analytics and sensors for social distancing. How ready are the channel partners and customers to be able to understand, adopt and execute this technology. >>So I think on the understanding side, I think the partners are there. We've been talking about digital transformation in the channel for a couple of years now, and I think what's happened through the 19 Pandemic is that it's been a real spotlight on the need for those business outcomes to to solve for very specific problems. And that's one of the values that we serve in the channel. So we've got a solution offering that we call our solution factory. And what we do really says is we leverage a process to look outside the industry. At Gartner, Magic Quadrant Solutions forced a Wave G two crowd. You know, top leaders, visionaries and understand What are those solutions that are in demand in these vertical markets that we talked about? And then we do a lot of work with David and his team internally in the HP organization to be able to do that and then build out that reference architectures so that we know that there's a solution that drives a bill of materials and a reference architecture that's going to work that clients are going to need and then we can do it quickly. You know, Tech data. Everything's about being bold, acting now getting scale. And we've got a large ecosystem partners that already have great relationships. So we pride ourselves on being able to identify what are those solutions that we can take to our partners that they can quickly take to their end users where you know we've We've kind of developed out what we think the 70 or 80% of that solution is going to look like. And then we drive point next and other services capabilities to be able to complete that last mile, if you will, of some of the customization. So we're helping them. For those who aren't ready, we're helping them. For those who already have very specific use cases and a practice that they drive with repeatable solutions were coming alongside them and understanding. What can we do? Using a practice builder approach, which is our consultative approach to understand where our partners are going in the market, who their clients are, what skill sets do they have? What supplier affinities do they want to drive? What brand marketing or demand generation support do they need? And that's where we can take some of these solutions, bring them to bear and engage in that consultative engagement to accelerate being ready as, as you rightly say, >>so tech. It has a lot of partners. You in general. You also have a lot of partners in the i o T space calling What? How do you from a marketing hat perspective? How do you describe the differentiation that Tech data and HP ease Iot solutions delivered to the channel to the end user? >>A couple of different things? I think that's that's differentiation. And that's one of the things that we strive for in the channel is to be specialized and to be competitively differentiated. And so the first part, I say to all of my team, Lisa, is you know, whether it's our solution consultants or our technical consultants, our solutions to the developers or the software development team that works my organization. Our goal is to be specialized in such a way that we're having relevant value added conversations not only our channel partners, but also end users of our partners want to bring us into those conversations, and many do. The next is really education and enablement as you would expect. And so there's a lot of things that are specialized in our technical. We drive education certification programs, roadshows, seminars, one of the things that we're seeing a lot of interest now. Lisa is for a digital marketing, and we're driving. Some really need offerings around digital marketing platforms that not only educate our partners but also allow our partners to bring their end users and tour some of this some of these technologies. So whether it's at our Clearwater office, where we've got an I. O T. Solution center, that we we take our partners and their clients through or we're using our facilities Teoh to do executive briefings and ideation as a service that, you know, kind of understanding the art of the possible. With both our resellers and their clients work, we're using our solution. Our solution catalogs that we've built an interactive pdf that allows our partners to understand over 50 solutions that we've got and then be able to identify. Where would they like to bring in David and his team and then my consultants to do that, that deep planning on business development, uh, that we talked about a little bit earlier. >>So the engagement right now is maybe even more important than it has been in a while because it's all hands off and virtual David. Talk to me about some of the engagement and the enablement piece that call and talked about. How are you able to really keep a channel partner and their end user customers engaged and interested in what you're able to deliver through this from New Virtual World? >>That's a great, great question. And we work in conjunction with our marketing teams to make sure that as new technologies and quite in I O. T space as well as within the HP East base as well that that our channel partners are educated and aware that these solutions exist. I know for a fact that for the majority of them you kind of get this consistent bombardment of new technology. But being able to actually have someone go out and explain it and then being able to correspondingly position it's use case and it's functionality and why it would provide value for your end customer is one of the benefits of tech data ads to kind of build upon that previous statement. The fact that We have such a huge portfolio of partners, so you kind of have HP and the edge compute space. But we have so many different partners in the OT space where it's really just a phone call, an email, a Skype message, a way to have that conversation around interoperability and then provide those responses back to our partners. >>Excellent. One more question before we go. Colin for you, A lot of partners. Why HP fry Mt. >>So a couple of reasons? One of the one of the biggest reasons as HP is just a great partner. And so when you look at evaluating I. O. T solutions that tend to be pretty comprehensive in many cases, Lisa it takes 10 or 12 partners to complete a really i o t solution and address that use case that that's in the field. And so when you have a partner like HP who's investing in these programs, investing in demand generation, investing in the spectrum of technology, whether it's hybrid Cloud Data Center, compute storage or your edge devices and Iot gateways, then to be able to contextualize those into what we call market ready solutions in each one of these vertical markets where there's references and there's use cases. And there were coupling education that specific rest of solutions. You know HP can do all of those things, and that's very important. Because in this new world, no one can go it alone anymore. It takes it takes partnerships, and we're all better together. And HP really does embrace that philosophy. And they've been a great partner for us in the Iot space. >>Excellent. Well, Colin and David, thank you so much for joining me today on the Cube Tech data. H p e i o t better together. Thank you so much. It's been a pleasure talking with you. >>Thank you. >>Thank you. Lisa. >>And four Collet and David. I am Lisa Martin. You're watching the Cube's virtual coverage of HP Discover 2020. Thanks for watching. Yeah, yeah, yeah, yeah.

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AI has the potential to profoundly change our lives with Dell Technologies. AI is easy to adopt, easy to manage and easy to scale. And there's nothing artificial about that. Yeah, yeah, from >>the Cube Studios in Palo Alto and Boston >>connecting with >>thought leaders all around the world. This is a cube conversation. Hi, I'm Stew Minimum. And welcome to this special launch with our friends at Dell Technologies. We're gonna be talking about AI and the reality of making artificial intelligence real happy to welcome to the program. Two of our Cube alumni Rob, depending 90. He's the senior vice president of server product management and very Pellegrino vice president, data centric workloads and solutions in high performance computing, both with Dell Technologies. Thank you both for joining thanks to you. So you know, is the industry we watch? You know, the AI has been this huge buzz word, but one of things I've actually liked about one of the differences about what I see when I listen to the vendor community talking about AI versus what I saw too much in the big data world is you know, it used to be, you know Oh, there was the opportunity. And data is so important. Yes, that's really But it was. It was a very wonky conversation. And the promise and the translation of what has been to the real world didn't necessarily always connect and We saw many of the big data solutions, you know, failed over time with AI on. And I've seen this in meetings from Dell talking about, you know, the business outcomes in general overall in i t. But you know how ai is helping make things real. So maybe we can start there for another product announcements and things we're gonna get into. But Robbie Interior talk to us a little bit about you know, the customers that you've been seeing in the impact that AI is having on their business. >>Sure, Teoh, I'll take us a job in it. A couple of things. For example, if you start looking at, uh, you know, the autonomous vehicles industry of the manufacturing industry where people are building better tools for anything they need to do on their manufacturing both. For example, uh, this is a good example of where that honors makers and stuff you've got Xeon ut It's actually a world war balcony. Now it is using our whole product suite right from the hardware and software to do multiple iterations off, ensuring that the software and the hardware come together pretty seamlessly and more importantly, ingesting, you know, probably tens of petabytes of data to ensure that we've got the right. They're training and gardens in place. So that's a great example of how we are helping some of our customers today in ensuring that we can really meet is really in terms of moving away from just a morning scenario in something that customers are able to use like today. >>Well, if I can have one more, Ah Yanai, one of our core and more partners than just customers in Italy in the energy sector have been been really, really driving innovation with us. We just deployed a pretty large 8000 accelerator cluster with them, which is the largest commercial cluster in the world. And where they're focusing on is the digital transformation and the development of energy sources. And it's really important not be an age. You know, the plan. It's not getting younger, and we have to be really careful about the type of energies that we utilize to do what we do every day on they put a lot of innovation. We've helped set up the right solution for them, and we'll talk some more about what they've done with that cluster. Later, during our chat, but it is one of the example that is tangible with the appointment that is being used to help there. >>Great. Well, we love starting with some of the customer stories. Really glad we're gonna be able to share some of those, you know, actual here from some of the customers a little bit later in this launch. But, Robbie, you know, maybe give us a little bit as to what you're hearing from customers. You know, the overall climate in AI. You know, obviously you know, so many challenges facing, you know, people today. But you know, specifically around ai, what are some of the hurdles that they might need to overcome Be able to make ai. Really? >>I think the two important pieces I can choose to number one as much as we talk about AI machine learning. One of the biggest challenges that customers have today is ensuring that they have the right amount and the right quality of data to go out and do the analytics percent. Because if you don't do it, it's giggle garbage in garbage out. So the one of the biggest challenges our customers have today is ensuring that they have the most pristine data to go back on, and that takes quite a bit of an effort. Number two. A lot of times, I think one of the challenges they also have is having the right skill set to go out and have the execution phase of the AI pod. You know, work done. And I think those are the two big challenges we hear off. And that doesn't seem to be changing in the very near term, given the very fact that nothing Forbes recently had an article that said that less than 15% off, our customers probably are using AI machine learning today so that talks to the challenges and the opportunities ahead for me. All right, >>So, Ravi, give us the news. Tell us the updates from Dell Technologies how you're helping customers with AI today, >>going back to one of the challenges, as I mentioned, which is not having the right skin set. One of the things we are doing at Dell Technologies is making sure that we provide them not just the product but also the ready solutions that we're working with. For example, Tier and his team. We're also working on validated and things are called reference architectures. The whole idea behind this is we want to take the guesswork out for our customers and actually go ahead and destroying things that we have already tested to ensure that the integration is right. There's rightsizing attributes, so they know exactly the kind of a product that would pick up our not worry about me in time and the resources needed you get to that particular location. So those are probably the two of the biggest things we're doing to help our customers make the right decision and execute seamlessly and on time. >>Excellent. So teary, maybe give us a little bit of a broader look as to, you know, Dell's part participation in the overall ecosystem when it comes to what's happening in AI on and you know why is this a unique time for what's happening in the in the industry? >>Yeah, I mean, I think we all live it. I mean, I'm right here in my home, and I'm trying to ensure that the business continues to operate, and it's important to make sure that we're also there for our customers, right? The fight against covered 19 is eyes changing what's happening around the quarantines, etcetera. So Dell, as a participant not only in the AI the world that we live in on enabling AI is also a participant in all of the community's s. So we've recently joined the covered 19 High Performance Computing Consortium on. We also made a lot of resources available to researchers and scientists leveraging AI in order to make progress towards you're and potentially the vaccine against Corbyn. 19 examples are we have our own supercomputers in the lab here in Austin, Texas, and we've given access to some of our partners. T. Gen. Is one example. The beginning of our chat I mentioned and I So not only did they have barely deport the cluster with us earlier this year that could 19 started hitting, so they've done what's the right thing to do for community and humanity is they made the resource available to scientists in Europe on tack just down the road here, which had the largest I can't make supercomputer that we deployed with them to. Ai's doing exactly the same thing. So this is one of the real examples that are very timely, and it's it's it's happening right now we hadn't planned for it. A booth there with our customers, the other pieces. This is probably going to be a trend, but healthcare is going through and version of data you mentioned in the beginning. You're talking about 2.3000 exabytes, about 3000 times the content of the Library of Congress. It's incredible, and that data is useless. I mean, it's great we can We can put that on our great ice on storage, but you can also see it as an opportunity to get business value out of it. That's going to be we're a lot more resource is with AI so a lot happening here. That's that's really if I can get into more of the science of it because it's healthcare, because it's the industry we see now that our family members at the M. Ware, part of the Dell Technologies Portfolio, are getting even more relevance in the discussion. The industry is based on virtualization, and the M ware is the number one virtualization solution for the industry. So now we're trying to weave in the reality in the I T environment with the new nodes of AI and data science and HPC. So you will see the VM Ware just added kubernetes control plane. This fear Andi were leveraging that to have a very flexible environment On one side, we can do some data science on the other side. We can go back to running some enterprise class hardware class software on top of it. So this is is great. And we're capitalizing on it with validates solutions, validated design on. And I think that's going to be adding a lot of ah power in the hands of our customers and always based on their feedback. And they asked back, >>Yeah, I may ask you just to build on that interesting comment that you made on we're actually looking at very shortly will be talking about how we're gonna have the ability to, for example, read or V Sphere and Allah servers begin. That essentially means that we're going to cut down the time our customers need to go ahead and deploy on their sites. >>Yeah, excellent. Definitely been, you know, very strong feedback from the community. We did videos around some of the B sphere seven launch, you know, theory. You know, we actually had done an interview with you. Ah, while back at your big lab, Jeff Frick. Otto, See the supercomputers behind what you were doing. Maybe bring us in a little bit inside as who? You know, some of the new pieces that help enable AI. You know, it often gets lost on the industry. You know, it's like, Oh, yeah, well, we've got the best hardware to accelerate or enable these kind of workloads. So, you know, bring us in its But what, You know, the engineering solution sets that are helping toe make this a reality >>of today. Yeah, and truly still you've been there. You've seen the engineers in the lab, and that's more than AI being real. That that is double real because we spend a lot of time analyzing workloads customer needs. We have a lot of PhD engineers in there, and what we're working on right now is kind of the next wave of HPC enablement Azaz. We all know the consumption model or the way that we want to have access to resources is evolving from something that is directly in front of us. 1 to 1 ratio to when virtualization became more prevalent. We had a one to many ratio on genes historically have been allocated on a per user. Or sometimes it is study modified view to have more than one user GP. But with the addition of big confusion to the VM our portfolio and be treated not being part of these fear. We're building up a GPU as a service solutions through a VM ware validated design that we are launching, and that's gonna give them flexibility. And the key here is flexibility. We have the ability, as you know, with the VM Ware environment, to bring in also some security, some flexibility through moving the workloads. And let's be honest with some ties into cloud models on, we have our own set of partners. We all know that the big players in the industry to But that's all about flexibility and giving our customers what they need and what they expect in the world. But really, >>Yeah, Ravi, I guess that brings us to ah, you know, one of the key pieces we need to look at here is how do we manage across all of these environments? Uh, and you know, how does AI fit into this whole discussion between what Dell and VM ware doing things like v Sphere, you know, put pulling in new workloads >>stew, actually a couple of things. So there's really nothing artificial about the real intelligence that comes through with all that foolish intelligence we're working out. And so one of the crucial things I think we need to, you know, ensure that we talk about is it's not just about the fact that it's a problem. So here are our stories there, but I think the crucial thing is we're looking at it from an end to end perspective from everything from ensuring that we have direct workstations, right servers, the storage, making sure that is well protected and all the way to working with an ecosystem of software renders. So first and foremost, that's the whole integration piece, making sure they realized people system. But more importantly, it's also ensuring that we help our customers by taking the guess work out again. I can't emphasize the fact that there are customers who are looking at different aliens off entry, for example, somebody will be looking at an F G. A. Everybody looking at GP use. API is probably, as you know, are great because they're price points and normal. Or should I say that our needs our lot lesser than the GP use? But on the flip side, there's a need for them to have a set of folks who can actually program right. It is why it's called the no programming programmable gate arrays of Saas fee programmable. My point being in all this, it's important that we actually provide dried end to end perspective, making sure that we're able to show the integration, show the value and also provide the options, because it's really not a cookie cutter approach of where you can take a particular solution and think that it will put the needs of every single customer. He doesn't even happen in the same industry, for that matter. So the flexibility that we provide all the way to the services is truly our attempt. At Dell Technologies, you get the entire gamut of solutions available for the customer to go out and pick and choose what says their needs the best. >>Alright, well, Ravi interior Thank you so much for the update. So we're gonna turn it over to actually hear from some of your customers. Talk about the power of ai. You're from their viewpoint, how real these solutions are becoming. Love the plan words there about, you know, enabling really artificial intelligence. Thanks so much for joining after the customers looking forward to the VM Ware discussion, we want to >>put robots into the world's dullest, deadliest and dirtiest jobs. We think that if we can have machines doing the work that put people at risk than we can allow people to do better work. Dell Technologies is the foundation for a lot of the >>work that we've done here. Every single piece of software that we developed is simulated dozens >>or hundreds of thousands of times. And having reliable compute infrastructure is critical for this. Yeah, yeah, A lot of technology has >>matured to actually do something really useful that can be used by non >>experts. We try to predict one system fails. We try to predict the >>business impatience things into images. On the end of the day, it's that >>now we have machines that learn how to speak a language from from zero. Yeah, everything >>we do really, at Epsilon centered around data and our ability >>to get the right message to >>the right person at the right >>time. We apply machine learning and artificial intelligence. So in real time you can adjust those campaigns to ensure that you're getting the most optimized message theme. >>It is a joint venture between Well, cars on the Amir are your progress is automated driving on Advanced Driver Assistance Systems Centre is really based on safety on how we can actually make lives better for you. Typically gets warned on distracted in cars. If you can take those kind of situations away, it will bring the accidents down about 70 to 80%. So what I appreciate it with Dell Technologies is the overall solution that they have to live in being able to deliver the full package. That has been a major differentiator compared to your competitors. >>Yeah. Yeah, alright, welcome back to help us dig into this discussion and happy to welcome to the program Chris Facade. He is the senior vice president and general manager of the B sphere business and just Simon, chief technologist for the High performance computing group, both of them with VM ware. Gentlemen, thanks so much for joining. Thank >>you for having us. >>All right, Krish. When vm Ware made the bit fusion acquisition. Everybody was looking the You know what this will do for space Force? GPU is we're talking about things like AI and ML. So bring us up to speed. As to you know, the news today is the what being worth doing with fusion. Yeah. >>Today we have a big announcement. I'm excited to announce that, you know, we're taking the next big step in the AI ML and more than application strategy. With the launch off bit fusion, we're just now being fully integrated with VCF. They're in black home, and we'll be releasing this very shortly to the market. As you said when we acquire institution A year ago, we had a showcase that's capable days as part of the animal event. And at that time we laid out a strategy that part of our institution as the cornerstone off our capabilities in the black home in the Iot space. Since then, we have had many customers take a look at the technology and we have had feedback from them as well as from partners and analysts. And the feedback has been tremendous. >>Excellent. Well, Chris, what does this then mean for customers? You know What's the value proposition that diffusion brings the VC? Yeah, >>if you look at our customers, they are in the midst of a big ah journey in digital transformation. And basically, what that means is customers are building a ton of applications and most of those applications some kind of data analytics or machine learning embedded in it. And what this is doing is that in the harbor and infrastructure industry, this is driving a lot of innovation. So you see the advent off a lot off specialized? Absolutely. There's custom a six FPs. And of course, the views being used to accelerate the special algorithms that these AI ml type applications need. And unfortunately, customer environment. Most of these specialized accelerators uh um bare metal kind of set up, but they're not taking advantage off optimization and everything that it brings to that. Also, with fusion launched today, we are essentially doing the accelerator space. What we need to compute several years ago and that is essentially bringing organization to the accelerators. But we take it one step further, which is, you know, we use the customers the ability to pull these accelerators and essentially going to be couple it from the server so you can have a pool of these accelerators sitting in the network. And customers are able to then target their workloads and share the accelerators get better utilization by a lot of past improvements and, in essence, have a smaller pool that they can use for a whole bunch of different applications across the enterprise. That is a huge angle for our customers. And that's the tremendous positive feedback that we get getting both from customers as well. >>Excellent. Well, I'm glad we've got Josh here to dig into some of the thesis before we get to you. They got Chris. Uh, part of this announcement is the partnership of VM Ware in Dell. So tell us about what the partnership is in the solutions for for this long. Yeah. >>We have been working with the Dell in the in the AI and ML space for a long time. We have ah, good partnership there. This just takes the partnership to the next level and we will have ah, execution solution. Support in some of the key. I am el targeted words like the sea for 1 40 the r 7 40 Those are the centers that would be partnering with them on and providing solutions. >>Excellent. Eso John. You know, we've watched for a long time. You know, various technologies. Oh, it's not a fit for virtualized environment. And then, you know, VM Ware does does what it does. Make sure you know, performance is there. And make sure all the options there bring us inside a little bit. You know what this solution means for leveraging GPS? Yeah. So actually, before I before us, answer that question. Let me say that the the fusion acquisition and the diffusion technology fits into a larger strategy at VM Ware around AI and ML. That I think matches pretty nicely the overall Dell strategy as well, in the sense that we are really focused on delivering AI ml capabilities or the ability for our customers to run their am ai and ml workloads from edge before the cloud. And that means running it on CPU or running it on hardware accelerators like like G fuse. Whatever is really required by the customer in this specific case, we're quite excited about using technology as it really allows us. As Chris was describing to extend our capabilities especially in the deep learning space where GPU accelerators are critically important. And so what this technology really brings to the table is the ability to, as Chris was outlining, to pull those resources those hardware resource together and then allow organizations to drive up the utilization of those GP Resource is through that pooling and also increase the degree of sharing that we support that supported for the customer. Okay, Jeff, take us in a little bit further as how you know the mechanisms of diffusion work. Sure, Yeah, that's a great question. So think of it this way. There there is a client component that we're using a server component. The server component is running on a machine that actually has the physical GPU is installed in it. The client machine, which is running the bit fusion client software, is where the user of the data scientist is actually running their machine machine learning application. But there's no GPU actually in that host. And what is happening with fusion technology is that it is essentially intercepting the cuda calls that are being made by that machine learning app, patience and promoting those protocols over to the bit fusion server and then injecting them into the local GPU on the server. So it's actually, you know, we call it into a position in the ability that remote these protocols, but it's actually much more sophisticated than that. There are a lot of underlying capabilities that are being deployed in terms of optimization who takes maximum advantage of the the networking link that sits between the client machine and the server machine. But given all of that, once we've done it with diffusion, it's now possible for the data scientist. Either consume multiple GP use for single GPU use or even fractional defuse across that Internet using the using technology. Okay, maybe it would help illustrate some of these technologies. If you got a couple of customers, Sure, so one example would be a retail customer. I'm thinking of who is. Actually it's ah, grocery chain. That is the flowing, ah, large number of video cameras into their to their stores in order to do things like, um, watch for pilfering, uh, identify when storage store shelves could be restocked and even looking for cases where, for example, maybe a customer has fallen down in denial on someone needs to go and help those multiple video streams and then multiple app patients that are being run that part are consuming the data from those video streams and doing analytics and ml on them would be perfectly suited for this type of environment where you would like to be ableto have these multiple independent applications running but having them be able to efficiently share the hardware resources of the GP use. Another example would be retailers who are deploying ml Howard Check out registers who helped reduce fraud customers who are buying, buying things with, uh, fake barcodes, for example. So in that case, you would not necessarily want to employ a single dedicated GPU for every single check out line. Instead, what you would prefer to do is have a full set of resource. Is that each inference operation that's occurring within each one of those check out lines could then consume collectively. That would be two examples of the use of this kind of pull in technology. Okay, great. So, Josh, a lot last question for you is this technology is this only for use and anything else. You can give us a little bit of a look forward to as to what we should be expecting from the big fusion technology. Yeah. So currently, the target is specifically NVIDIA GPU use with Cuda. The team, actually even prior to acquisition, had done some work on enablement of PJs and also had done some work on open CL, which is more open standard for a device that so what you will see over time is an expansion of the diffusion capabilities to embrace devices like PJs. The domain specific a six that first was referring to earlier will roll out over time. But we are starting with the NVIDIA GPU, which totally makes sense, since that is the primary hardware acceleration and for deep learning currently excellent. Well, John and Chris, thank you so much for the updates to the audience. If you're watching this live, please throwing the crowd chat and ask your questions. This faith, If you're watching this on demand, you can also go to crowdchat dot net slash make ai really to be able to see the conversation that we had. Thanks so much for joining. >>Thank you very much. >>Thank you. Managing your data center requires around the clock. Attention Dell, EMC open manage mobile enables I t administrators to monitor data center issues and respond rapidly toe unexpected events anytime, anywhere. Open Manage Mobile provides a wealth of features within a comprehensive user interface, including >>server configuration, push notifications, remote desktop augmented reality and more. The latest release features an updated Our interface Power and Thermal Policy Review. Emergency Power Reduction, an internal storage monitoring download Open Manage Mobile today.

>> live from Anaheim, California. It's the queue covering nutanix dot next twenty nineteen. Brought to you by Nutanix. >> Welcome back, everyone to the cubes. Live coverage of dot Next at NUTANIX. We're here in Anaheim, California. I'm your host, Rebecca Knight were joined by Wendy M. Pfeiffer. She is the chief information officer at Nutanix. Thank you so much for coming on the Cube. Wendy, thank you for having me. And this is not your first time you this year. A Cube alum. >> I am a Cube alum. It's so much fun. It's kind of weird, though. We're inside of this Cuban outside of us is all the action in the Exposition Hall is kind of crazy and cool. >> It is that there's a lot of energy here. I want to start our conversation by taking you back in time to nineteen eighties. You growing up in Silicon Valley, you notice an advertisement in the newspaper that dead tree medium NASA wants ideas on how to organize its dashboard. Better for astronauts. Yeah, >> So they had a program called CD T I cockpit displays of traffic information and they were looking for innovative ideas to make what was really a very small display provide information for the shuttle astronauts as they were re entering the atmosphere. And so, if you can imagine coming back into the atmosphere, it very high speed. And there was concern that there would be a traffic in the area. Regular airplanes flying, you know, relatively much slower. And so how could the same air traffic displays that were used for aviators be sort of modified to give real time information? Teo the astronauts, I will tell you that I never contributed much to that project, but I discovered large scale computer systems. And I just love the idea of these things large networks, large computers on just the through the vast interconnectedness of things. And so that got me interested in technology, whereas before I thought I was interested in science and math. And it turns out, of course, there's some great synergy among those topics. >> So So the internship at NASA is what propelled your interest and really, what launched your career in technology? Yes. Now you are the CEO of Nutanix. This this amazing company thiss startup That's now billion dollars with the market cap in multiple billions of dollars. Yes. So talk a little bit about your experience as CEO and what and what in what you're hearing, particularly at this dot next show. Yeah, I think >> one of the things that's happening is we're all in the midst of a huge transformation in terms of how digital technology affects business and empowers and enables business and as CEOs were right in the middle of that Wei have. Many of us have tons of legacy equipment and things from vendors, but we also have this desire for leading digital transformation in our companies. And so companies like Nutanix and there aren't many companies like Nutanix, but technologies like ours bridge that gap. We can run the legacy workloads in on premise data centers on pick a vendor's hardware. But we can also run the same work loads on our operating system in public clouds. And so it's kind of the best of both worlds, and it bridges thes two worlds that CEOs have been struggling to bridge, and it does so in a way that doesn't require us to re train our people or find, you know, a small team of rocket scientists who are, you know, worth more than the GDP of small countries. So we're able Teo, actually execute. Still keep the lights on. Still do the the old school things that we need to do but also operate with excellence at that more modern end of the technology spectrum. That's huge. And I'm hearing that from so many folks all around the show, whether it's, you know, people who are responsible for infrastructure or Dev Ops kind of crosses all of those bridges. And and as Nutanix, the CEO, I get to represent how any company like ours a billion and a half dollars publicly traded company, can use technology to enable itself, because I use our technology to do all the things we need to do as a company. >> But that's exactly just what you're talking about. That balance that these companies need to strike with thinking about the maintenance, thinking about the storage, thinking about the protection, but then also thinking in a much more visionary in strategic way about how we really transform our business and get our and get the work done that we need to get done. Can you talk a little bit about the fact that these consumer technologies have really leapfrog the thie enterprise vendors and sort of embarrassing it, frankly, should be for these big technology behemoth that they haven't done more to make cooler, sleeker technologies? >> Absolutely. Oh, my gosh, this is my favorite topic. And it's why I have my smart here. So on this smartphone, this is a is an apple phone on this smartphone. I have a ton of applications and a ton of functionality, and you know, so I have Facebook on my smartphone, right? And I love Facebook. >> But when I >> downloaded and I started using Facebook, I didn't say, you know Oh my gosh, fall. Now I have my social media application. So there's no way I could use Twitter or Instagram or anything else because my standard is Facebook. And that's the only thing I'm going to use. No, no, no. I have a multitude of APS and I used them as I choose when I want to, in the way that I want Teo, those abs inherit things from this platform. They have access to my contact data. They understand my location if I allow them tio etcetera. So all of those things are unconsciously in what is actually a phone. Now try to get your desk phone to do that right? It doesn't. And yet in the enterprise space, we have vendors who are selling us for millions of dollars, desk phones, and those were supposed to be as performance delightful, interesting as this device. And then we have laptop computers and we have desktop computers. None of those things is even a third as interesting, engaging, useful and easy to use as this consumer attack, which, by the way, is a lot less expensive. I spend millions of dollars on a V audio visual room systems of conferencing technology, whereas when I go home I can se teoh Amazon or Google. Hey, you know Amazon. Show me my my shows. You know I can I can I can ask for any show I want to watch on TV. When I downloaded Pokey Mongo, I love playing video games and games. When I downloaded Pokemon go on my phone. I >> didn't have to >> watch, you know, five five minute video snippets to teach me how to install the application. Within minutes, I was, you know, catching all the Pokemon I could what in what is really a very complex application that also includes augmented reality. And so I think it's time that first of all the vendors who sell to us, who are so used to that every three years, the enterprise license agreement is renewed. Or, you know, Hey, we're a pick something, you know, a one hardware vendors shop. So we that's what we standardize on that is doing two things. One, they're killing their own industry, and they're also killing. They're they're ruining. It is ability to deliver and to be useful and transformative. Two companies way and it way also have to demand better way. Have to stop buying that Dunc. And we have to start finding ways whether we have to build it ourselves or using machine learning tools to train the machine on how to do these things that that enterprise it cos don't deliver to us. And we also need to look for vendors like Nutanix that build that bridge that allow us to stop worrying about Oh my gosh, You know, we've got to make this legacy thing work with this new thing. We don't have to worry about that so much anymore. And now we can focus on this user experience The interaction design what we might do within an ecosystem That is our own unique companies and our own unique set of systems and also ultimately allowing our people, which is what companies are made up of allowing our people to to have the experience that they want tohave, just like we do with our own devices. I can choose how I want to interact with this thing, and I can turn it off if I don't want to use it. >> So so much of what you're talking about is really about getting companies and then the leaders of these companies to think differently. And that is the biggest managerial challenge. And it's a challenge when you're in sales. And so how do you How do you approach that problem? Because it because you've really laid it out so clearly we are used, Teo, so much intuitiveness and ease and beauty in the technology that we use in our personal lives. And then we come to work way put up with a lot of junk. >> We do, right? I mean, like, I know you're not saying anything out loud, but I know you. You're agree without you here with your laptop on the table there. You know, first of >> all, our work forces are changing. Generally, we keep talking, at least in circles that I sit in about, you know, the millennials are entering the work force. No. You know, the Millennials and Jen Zy are already make up almost half of our workforce today and will be at that somewhere around. I think it's seventy percent by twenty, twenty five of the workforce, so >> they're already here. Those >> folks already have a different relationship with technology than my generation did my generation. And I'm a Magen axe, I think. Yeah. Um so my my hub to Exactly So the big >> hair A my generation. >> I >> watched the birth of some of these consumer technologies, but this next couple of generations grew up with him already in place. And so they don't even think about the fact that this is technology. This is dependent, just is just part of them. And so I think we need Thio, Throw off the old filters and get out of the way. It's a lot more about choice and self service and freedom and flexibility and a mixed portfolio. And there are so many ways to educate ourselves about those things if if we don't naturally have that instinct. But it starts with diverse thinking, diverse tools. I believe that whatever you know, PC Mac laptop tablet mobile device that you're comfortable with your company should enable you to use. And you should use the applications that that makes the most sense to that make you the most productive. And then it's his job or it's leaderships job to create that that really rich ecosystem, where those applications and tools have the nutrients that they need and the capabilities that they need to work together well, understanding how to create and maintain that ecosystem mean what is an ecosystem? It's this sort of happy accident of all sorts of creatures at various levels in the in the pyramid coming together and figuring out a way to cohabit and to survive and then, hopefully to thrive. And so no one can get too important. No one voice no one species. No one layer can be outsized compared to the others because of So what do you have? Well, you have a species collapse. They run out of the fuel that helps them to thrive. And so I think, of course, our planet at a macro level is an example of that. But our company's our families, our neighborhoods. All of those things are micro examples that that matched the macro and are dependant on the same laws of physics and science and so on in order to thrive in to function. >> Well, you're talking you You just highlighted the importance of diversity. And and you made this comment about No one person can get two important or no one part of the species. In fact, if you look at the tech landscape Ueno, who's too important and it's the pros who are who are running the show in a lot of ways. Still, I want to hear from you as a senior leader, a female senior leader in technology you noticed, >> and Theo the manicure. Yeah, >> but how? What? What do you see? What? Tell us what it's like. I mean, is it as bad as we hear? And, um, and and And how have you in your career overcome a lot of these challenges? And then how What do you see as your responsibility to the next generation who's coming up? >> Absolutely. So it is as bad as we hear. It's sometimes worse than we here. And I think that especially there are certain sectors of society and tech society where the bro culture that we've heard about is fully in play. What mitigates that is the human beings who make up the bro culture so often. These guys don't understand the the effect of all of them and mass, and so often they're just being natural. Many, especially start ups. The start of fuel. Silicon Valley, You know, they started with some great ideas and with some dreamers and often those those people with the great ideas and dreamers you know they are males, and what do you do? You get your buddies together. You know, when you get a little extra money, you get the next round of bodies. You invite people, you know, so >> there's a little >> bit of that syndrome that's happening. There are also wonderful incubators and fields where women are also in that start up mode, and I'm a member of the Board of Girls and Tech. We have a number of things like Way have an amplified competition that supports women, tech the entrepreneurs, so there's certainly more than just men. But the history has been that however, a lot of people talk about that For me, that's not the emphasis for me. The emphasis is on how we change our jobs and our definition of work in general. And this is so fascinating to me. >> I think we've been working for years >> and years on, you know, how do we get more women and stem and encourage girls to go through this path in school? You know, it turns out women and men are both equally interested in science and math and all those things. But the starting jobs and tech are are horrendous when it comes to matching women's interests in skills and this isthe stereo, I'm going to start stereotype here. I hate doing this, but in general terms, men tend to be able to work on things serially. They tend to have a singular focus and to appreciate the singular focus and so you can lay out a path first, your socks and your shoes and the guy will follow that, and we'LL master each step along the way. And that's that's a way that you know, it's stereotypically a lot of male brain brains. Progress for women, for female brains were multifaceted way sort of have this ability. I don't know if it's evolutionary or environment or whatever. I'm not like an expert, thank God. >> But we have this >> ability to multi task all the time. I could be, you know, holding my kid and, um, talking on the phone and, you know, making sure dinners cooking, okay. And, you know, maybe it's a business call, and I might be hiring someone or firing someone, and I'm giving equal focused attention to each very important task. And so we sort of have that that ability because we have that ability. That's the kind of job that you know. Okay, you enter college and you're taking a software development computer science, of course. And you take all computer science courses until you get that degree. And now you get your first software developer job and you sit in this little cubicle and all day long you write code. Well, you know, fine. If I've sort of have that single threaded mentality, I'm ready. All right. I guess I'm going to do this. I'm gonna Masters are >> gonna get through the layers >> of writing code as fast as I can and someday I'll rule the world or start my own company over on the female side, we say this is going to kill me. I don't want to do that. What a boring jobs. Because Because also, I'm interested in I'm interested in the Japanese language and I'm interested in design. And, you know, I love to cook. And also, you know, I'm just been working through, you know, theories of space and time and in my physics study, and to just have to focus my mind all by myself all day long in this cubicle on writing, you know, some part of a bigger program. It's not attractive. And so what we find is that women are dropping out of thes focus degree programs and they're dropping out of the early stages of technology careers. Which means that by the time you get to my stage, there is not a very few of us right, >> So you said we needed we need to change the definition of work. Yes, What does that mean? >> Well, the Millennials and Gen Z and countries that are that are very young, like some of the Eastern European countries that air, that air, just reinventing themselves. They've already done that. It's the gig economy. It's the idea that as an individual, I can choose the things I want to work on. We've tried Teo, sort of emulate that in in the agile methodologies right? I get to choose my tasks, but it's this sort of. It was taken the soul out of it. But this is really that independent contractors might be doing. You know a few things that once I might be designing shoes like one of my friends is she's she's created her own shoe company, and at the same time I might be writing code Azaz a gig for some other company. And you know what? I might also be involved in, you know, a charitable work. Or I might be volunteering at my kid's school and doing all of those things together at the same time in parallel is interesting to us. It's engaging to us. We put more. >> So how'd you do that? At your team at NUTANIX? How do you help your employees, uh, do all the things that they want to do in addition to obviously getting their work done? Yeah, well, It's always a >> balance right. One of the really important things is to create an environment of tools and technologies and processes that allow people to choose the things they want to choose. It's not always well understood. Some people say thank you. I get to use the tools I like. Other people say there's too many tools what we d'Oh. And so we try to find something down the middle for those guys. Exactly. Secondly, I hire and mentor leaders who are very diverse and open, and they're thinking so that we can constantly kind of reinvent ourselves as an I T organization. But ultimately it gets down to enabling culturally people to think differently, to raise their hand and say, You know, I am a network engineer, but I would like Tio automate this thing over here or, you know, I Yes, I'm a systems engineer, but I'd like to deploy the network, just allowing them to get out of their comfort zone and to experiment. It's also really important to understand the balance of it. People who choose it love engineering and love technology, but we'LL also love process and interaction, and so we're already this mash up of personality types. And, you know, I would say more multifaceted you are, the more you're able to play multiple sports or or have multiple skills or play offense and defense, then the more able you are to thrive in the new World in the new economy. And sometimes it's just finding those mavericks Or, you know, I like to say I'm a little civil, like, you know, I've >> got a little personalities and you know it. Sometimes you got >> to bring one of those personalities to the table. Sometimes you have to bring many of those personalities to the table, and it's gonna be okay for folks to do that. >> I love it. I love it. Great. Well, Wendy, thank you so much for coming on the Cube. It's always fun talking to you. Thank you. Appreciate it. I'm Rebecca Knight. You are watching the Cube. They'LL be much more to come

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Hello and welcome back to the Cubes. Live coverage here and savor still were alive for IBM. Think twenty nineteen. The Cubes Exclusive contract. Jon for a stimulant in our next two guests of the Cloud gurus and IBM and VM Where A. J. Patel senior vice president general manager Cloud Providers Software Business Unit. Good to see you again. Baron. Scram A general manager. IBM Cloud Guys. Thanks for Spend the time. Get to the cloud gurus. Get it? They're having What's going on? Having privilege. Osti Cloud's been around. We've seen the public Cloud Momentum hybrid Certainly been around for a while. Multi clouds of big conversation. People are having role of data that is super important. Aye, aye, anywhere you guys, an IBM have announced because I've been on this. I'm on >> a journey or a >> library for awhile. On premise. It was on VM, where all the good stuff's happening. This the customers customers want this talk about the relationship you guys have with IBM. >> You know, the broad of'em were IBM relationship over nine, ten years old. I had the privilege of being part of the cloud the last couple years. The momentum is amazing. Over seventeen hundred plus customers and the Enterprise customers, not your you know, one node trial customer. These are really mission critical enterprise customers using this at that scale, and the number one thing we hear from customers is make it easy for me to leverage Plowed right, operate in the world when I'm using my own prim and my public cloud assets make it seamless, and this is really what we've talked about a lot, right? How do we provide that ubiquitous digital platform for them to operate in this hybrid world? And we're privileged to have IBM Of the great partner in this journey >> are some of the IBM cloud, Ginny Rometty said on CNBC this morning. We saw the interview with my friend John Ford over there. Aye, aye. Anywhere means going run on any cloud. Watson with containers. That's cloud DNA. Sitting the cloud with good Burnett ease and containers is changing the game. Now you can run a lot of things everywhere. This's what customers want. End to end from on. Premise to wherever. How has that changed the IBM cloud posture? Its products? You share a little bit of that. >> You absolutely so look I mean, people have their data in different places, and as you know, it's a really expensive to move stuff around. You gotta make sure it's safe, etcetera, So we want to take our applications and run them against the data wherever they are right? And when you think about today's landscape in the cloud industry, I think it's a perfect storm, a good, perfect storm and that containers and Kubernetes, you know, everyone's rallying around at the ecosystem that consumers, the providers. And it just makes us easy for us to take that capability and really make it available on multicloud. And that's what we're doing. >> to talk about your joint customers. Because the BM where has a lot of operators running, running virtually change? For a long time, you guys have been big supporters of that and open source that really grew that whole generation that was seeing with cloud talk about your customers, your mo mentum, Howyou, guys air, just ballpark. How many customers you guys have together? And what if some of the things that they're doing >> all right? So I know this is a really interesting story. I was actually away from IBM for just over two years. But one of the last things I did when I was an IBM the first time around was actually start this Veum where partnership and seated the team that did it. So coming back, it's really interesting to see the uptake it's had, You know, we've got, like, seven hundred customers together over seventeen hundred customers. Together, we've moved tens of thousands of'em workloads, and as I just said, we've done it in a mission. Critical fashion across multiple zones across multiple regions. On now, you know, we want to take it to the next level. We want to make sure that these people that have moved their basic infrastructure and the mission critical infrastructure across the public cloud can extend those applications by leveraging the cloud near application that we have on our cloud. Plus, we want to make it possible for them to move their workloads to other parts of the IBM ecosystem in terms of our capabilities. >> Any one of the things we found was the notion of modernizer infrastructure, first lift and then transform. He's starting to materialize, and we used to talk about this has really the way the best way to use, cowed or use hybrid cloud was start by just uplifting your infrastructure and whether it's west back, you ask for some customers. I respect a great example. I think that we're talking about it in the Parisian. I joined presentation tomorrow or you look at, you know, Kaiser, who's going to be on stage tomorrow? We're seeing industries across the board are saying, You know, I have a lot of complexity sitting on aging hardware, older versions of infrastructure software. How do I modernize A platform first lifted, shifted to leverage a cloud. And then I could transform my application using more and more portable service that'S covering decides to provide a kind of infrastructure portability. But what about my data, Right. What about if I could run my application with the data? So I think we're starting to see the securing of the use of cloud based on workloads and averaging that's that's >> Yeah, a J. What wonder if we could dig a little love level deeper on that? Because, you know, I think backto, you know, fifteen years or so ago, it was bm where allowed me to not have to worry about my infrastructure. My, you know OS in my you know, server that I was running on might be going end of life. Well, let me shove it in a V M. And then I couldn't stand the life, and then I can manage how that happens. Course. The critique I would have is maybe it's time to update that that application anyway, so I like the message that you're saying about Okay, let me get a to a process where I'm a little bit freer of where, and then I can do the hard work of updating that data. Updating that application, you know, help us understand. >> It's no longer about just unlocking the compute right, which was worth trying the server. It's What about my network we talked about earlier? Do I need a suffered If our network well, the reality is, everything is going programmable. If you want a program of infrastructure, it's compute network storage all software defined. So the building block for us is a suffer to find data center running on the infrastructure that IBM pride sixty plus data centers bare metal at Scholastic and then leering that with IBM cloud private, whether it's hosted or on premise, fear gives you that full stack that nirvana, the people talk about supportable stack going, talk about >> right and adding to what he said, right? You said, You know, it's not about just moving your old stuff to the to the cloud. Absolutely. So as I said in one of the earlier conversations that we have, we had is we have a whole wealth of new services, whether it's Blockchain R. I o. T or the that used. You spoke about leveraging those capabilities to further extend your app and give it a new lease of life to provide new insights is what it's all about. >> What? Well, that that that's great, because it's one thing to just say, Okay, I get it there. Can I get better utilization? Is that change my pricing? But it's the services, and that's kind of the promise of the cloud is, you know, if I built something in my environment, that's great and I can update and I can get updates. But if I put it in your environment, you can help manage some of those things as well as I should have access to all of these services. IBM's got a broad ecosystem can you give us? You know what are some of the low hanging fruit is to people when they get there, that they're unlocking data that they're using things like a I What? What What are some of the most prevalent services that people are adding when they go to the IBM clouds? >> So when you look at people who first moved their work list of the cloud, typically they tend to dip their toe in the water. They take what's running on Prem. They used the IRS capabilities in the cloud and start to move it there. But the real innovation really starts to happen further up the stock, so to speak. The platform is a service, things like a II OT blocked and all the things that I mentioned, eso es very natural. Next movement is to start to modernize those applications and add to it. Capability is that it could never have before because, you know it was built in a monolith and it was on prim, and it was kind of stuck there. So now the composition that the cloud gives you with all of these rich services where innovation happens first, that is the real benefit to our customers. >> Every she said, you took a little hiatus from IBM and went out outside IBM. Where did you go and what did you learn? What was that? Goldman Jack. JP Morgan, Where were you? >> So it was a large bank. You know, I'm not not allowed to say the name of the bank. >> One of those two. It >> was a large bank on, and it wasn't the U S. So that narrows down the field. Some >> What is it like to go outside? They'll come inside. U C Davis for cutting edge bank. Now you got IBM Cloud. You feel good about where things are. >> Yeah. You know, if you look at what a lot of these banks are trying to do, they start to attack the cloud journey saying we're going to take everything that ran in the bank for years and years and years. And we're going to, you know, make them micro services and put them all on public cloud. And that's when you really hit the eighty twenty percent problem because you've got a large monolith that don't lend themselves to be re factored and moved out. Tio, eh, Public cloud. So you know again, Enter communities and containers, etcetera. These allow you a way to modernize your applications where you can either deploy those containerized You know, piers you go type models on prim or on public. And if you have a rich enough set of services both on Prem in on the public loud, you can pretty much decide how much of it runs on Trevor's is becoming much more clouds >> moment choice. So really, it's finding deployment. So basically, what you're saying is that we get this right. I want to get your reaction. This You don't have to kill the old to bring in the new containers and Cooper netease and now service measures around the corner. You can bring in new work clothes, take advantage of the cutting edge technology and manage your life cycle of the work loads on the old side or it just can play along. I >> think what we're finding is, you know, we moved from hybrid being a destination to an operating model, and it's no longer about doing this at scale like my multi clark. Any given applications tied to a cloud or destination? It's a late binding decision, but as an aggregate. I may be amusing multiple close, right. So that more model we're moving to is really about a loving developer. Super your workload centric and services centric to see Where do I want to run in Africa? >> Okay, what one of the challenges with multi cloud is their skill sets. I need to worry about it. It can be complex. I want to touch on three points and love to get both your viewpoints, networking, security and management. How do we help tackle that? Make that simple >> right off customers? >> Yeah, sure. So you know, I think when you think about clouds, public clouds especially it's beyond your data center and the mindset out there as if it's beyond my data center. It can be safe. But when you start to build those constructs in the modern era, you really do take care of a lot of things that perhaps you're on Prem pieces that not take into consideration when they were built like many decades ago. Right? So with the IBM public Cloud, for example, you know, security's at the heart of it. We have a leadership position. There was one of the things that we've announced is people keep protect for not only Veum, where workload visa and we sphere etcetera, but also for other applications making use off our public cloud services. Then, when you talk about our Z, you know we have a hardware as security model, which is fifty one forty, level two or dash to level four, which nobody else in the industry has. So when you put your key in there on ly, the customer can take it out, not him. Azaz clouds of his providers can touch it. It will basically disintegrate, you know, sort of speak >> H ey. Talk about VM wears customer base inside the IBM ecosystem. What's new? What should they pay attention to? As you guys continue the momentum. >> So I think if you look at the last two years, it's been around what we call these larger enterprise. Dedicated clouds. Exciting thing in the horizon is we're adding a multi tenant IRS on top of this BM, we're dedicated. So being able to provide that Brett off access thing with dedicated multi tenant public out I, as fully programmable, allows us to go downmarket. So expect the customer kind of go up being able to consume it on a pay as you go basis leveraging kind of multi tenant with dedicated, but it's highly secure or for depth test. So are the use cases kind of joke. We're going to see a much larger sort of use cases that I'm most excited about >> is the bottom line. Bottom line me. I'm the customer. Bottom line me. What's in it for me? What I got >> for the customers with a safest choice, right? It's the mission critical secure cloud. You can now run the same application on Prem in a dedicated environment in public, Claude on IBM or in a multi tenant >> world. And on the Klaxon match on the cloud sign. I could take advantage of all the things you have and take advantage of that. Watson A. I think that Rob Thomas has been talking about Oh yeah, >> absolutely. And again. You know the way that we built I c P forty, which is IBM plowed private for data. You know, it's all containerized. It's orchestrated by Coop, so you can not only build it. You can either run it on crime. You can run it on our public loud or you can run it on other people's public clouds as well >> nourished for customers and for people. They're looking at IBM Cloud and re evaluating you guys now again saying Or for the first time, what should they look at? Cloud private? What key thing would you point someone to look at, IBM? They were going to inspect your cloud offering >> so again, and it's back to my story in the bank. Right? It's, uh you can't do everything in the public cloud, right? There are just certain things that need to remain on creme On. We'll be so for the foreseeable future. So when you take a look at our hybrid story, the fact that it is has a consistent based on which it is built on. It is a industry standard open source base. You know, you build your application to suit the needs of an application, right? Is it low lately? See, Put it on. Crim. You need some cloud Native services. Put it on the public cloud. Do you need to be near your data that lives on somebody else's cloud? Go put it on their cloud. Right. So it really is not a one. Size fits all its whatever your business >> customer where he is, right? That's often >> the way flexibility, choice, flexibility. Enjoy the store for all things cloud. >> Yeah, last thing I want to ask is where to developers fit in tow this joint Solucion >> es O. So I think the biggest thing is that's trying to change for us is making these services available in a portable manner. When do I couldn't lock into the public cloud service with particular data and unlocking that from the infrastructures will be a key trend. So for us, it's about staying true to Coburn eddies and upstream with the distribution. So it's portable for wanting more and more services and making it easy for them to access a catalogue of services on a bagel manner but then making operation a viable. So then you're deployed. You can support the day two operations that are needed. So it's a full life cycle with developers not having to worry about the heavy burden of running an operating. What >> exactly? You know, it's all about the developers. As you well know in the cloud world, the developer is the operator. So as long as you can give him or her, the right set of tools to do C. I C. Dev ops on DH get things out there in a consistent fashion, whether it is on a tram or a public cloud. I think it's a win for all. >> That's exactly the trend We're seeing operations moving to more developers and more big time operational scale questions where your programming, the infrastructure. Absolutely. Developers. You don't want to deal with it >> and making it work. Listen tricks. So you know when to deploy. What workload? Having full control. That's part of the deployment >> exam. Alright, final question. I know we got a break. We're in tight on time. Final point share perspective of what's what's important here happening. And IBM. Think twenty nineteen people who didn't make it here in San Francisco are watching. You have to top cloud executives on VM wear and IBM here as biased towards cloud, of course. But you know, if you're watching, what's the most important story happening this week? What's what's going on with IBM? Think Why is this conference this week important? >> I think for us, it's basically saying We're here to meet you where you are, regardless, where you on your customer journey. It's all about choice. It's no longer only about public Cloud, and you now have a lot of capably of your finger trips to take your legacy workloads or your neck, new workplace or any app anywhere we can help you on that journey. That would be the case with >> you, and I wouldn't go that right, said it slightly differently. You know, a lot of the public service of public cloud service providers kind of bring you over to their public loud, and then you're kind of stuck over there and customers don't like that. I mean, you look at the statistics for everybody has at least two or more public clouds. They're worried about the connective ity, the interoperability, the security costs, the cost, the skills to manage all of it. And I think we have the perfect solution of solutions that really start Teo. Speak to that problem. >> So the world's getting more complex as more functionalities here, Software's gonna distract it away. Developers need clean environment to work in programmable infrastructure. >> And you know where an IBM Safe Choice, choice, choice. >> We have to go on top to cloud executives here. Inside the cue from IBM of'em were bringing all the coverage. Was the Cube here in the lobby of Mosconi North on Howard Street in San Francisco for IBM? Think twenty. Stay with us for more coverage after this short break. Thank you. Thank you.