>>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.

(upbeat music) >> Hi everybody, this is Dave Volante. And with me is Sandeep Singh, he is the vice president of Storage Marketing at Hewlett Packard Enterprise. And we're going to riff on some of the trends in the industry, what we're seeing. And we got a little treat for you. Sandeep, great to see you man. >> Dave, it's a pleasure to be here. >> You and I've known each other for a long time. We've had some great discussions, some debates, some intriguing mind benders. What are you seeing out there in Storage? So much has changed. What are the key trends you're seeing and let's get into it. >> Yeah, across the board, as you said, so much has changed. When you reflect back at the underlying transformation that's taken place with data, cloud and AI across the board. First of all, for our customers they're seeing this massive data explosion that literally now spans edge to core to cloud. They're also seeing a diversity of the application workloads across the board. And the emphasis that it's placing is on the complexity that underlies overall infrastructure and data management. Across the board, we're hearing a lot from customers about just the underlying infrastructure complexity and the infrastructure sprawl. And then the second element of that is really extending into the complexity of data management. >> So it's interesting you're talking about data management. You remember you and I, we were in Andover. It was probably like five years ago and all we were talking about was media. Flash this and flash that, and at the time that was kind of the hot storage topic. Well, flash came in addressing some of the mics that we historically talked about it. Now the problem statement is really kind of quote unquote metaphorically moving up the stack if you will, you mentioned management but let's dig into that a little bit. I mean, what is management? I mean, a lot of people that means different things to different people. You talk to a database person or a backup person. How do you look at management? What does that mean to you? >> Yeah, Dave, you mentioned that the flash came in and it actually accelerated the overall speed and latency that storage was delivering to the application workloads. But fundamentally when you look back at storage over a couple of decades the underlying way of how you're managing storage hasn't fundamentally changed. There's still an incredible amount of complexity for IT. It's still a manual admin driven experience for customers. And what that's translating to is more often than not IT is in the world of firefighting and it's leaves them unable to help with them more strategic projects to innovate for the business. And basically IT has that pressure point of moving beyond that and helping bring greater levels of agility that line of business owners are asking for and to be able to deliver on more of the strategic projects. So that's one element of it. The second element that we're hearing from customers about is as more and more data just continues to explode from edge to core to cloud. And as basically the infrastructure has grown from just being on-Prem to being at the Edge to being in the cloud. Now that complexity is expanding from just being on-Prem to across multiple different clouds. So when you look across the date data life cycle how do you store it? How do you secure it? How do you basically protect it and archive it and analyze that data. That end to end life cycle management of data today resides on just a fragmented set of overall infrastructure and tools and processes and administrative boundaries. That's creating a massive challenge for customers. And the impact of that ultimately is essentially comes at a cost to agility, to innovation and ultimately business risk. >> Yeah, so we've seen obviously the cloud has addressed a lot of these problems but the problem is the cloud is in the cloud and much of my stuff, most of my stuff, isn't in the cloud. So I have all these other workloads that are either on-Prem and now you've got this emerging Edge. And so I wonder if we could just talk a little vision here for a minute. I mean what I've been envisioning is this abstraction layer that cuts across all weather. It doesn't really matter where it is. If it's on-Prem, if it's across cloud, if it's in the cloud, on the edge, we could talk about what that all means. But if customers that I talked to they're sort of done with the complexity of that underlying infrastructure. They want technology to take care of that. They want automation they want AI brought in to that equation. And it seems like we're from the cusp of the decade where that might happen. What's your take? >> Well, yeah, certainly I mentioned that data cloud and AI are really the disruptive forces, better propelling. The digital transformation for customers. Cloud has set the standard for agility and AI driven insights and intelligence are really helping to make the underlying infrastructure invisible and customers are looking for this notion of being able to get that cloud operational agility pretty much everywhere because they're discovering that that's a game changer. And yet a lot of their application workloads and data is on-Prem and is increasingly growing at the edge. So they want same experience to be able to truly bring that agility to wherever their data in absolute. And that's one of the things that we're continuing to hear from customers. >> And this problem is just going to get worse. I mean for decades we marched to the cadence of Moore's Law and everybody's going to forgets about Moore's Law. And say, "Ah, it's dying or whatever." But actually when you look at the processing power that's coming out now, it's more than doubling every two years, quadrupling every two years. So now you've got this capability in your hands and application design minors, storage companies, networking companies. They're going to have all this power to now bring in AI and do things that we've never even imagined before. So it's not about the box and the speeds and feeds of the box. It's really more about this abstraction layer that I was talking about. The management if you will that you were discussing and what we can do in terms of being able to power new workloads in machine intelligence, it's this kind of ubiquitous, call it the cloud but it's expanding pretty much everywhere in every part of our lives even to the edge you think about autonomous vehicles, you think about factories it's actually quite mind boggling where we're headed. >> It is and you touched upon AI. And certainly when you look at infrastructure, for example there's been a ton of complexity in infrastructure management. One of the studies that was done actually by IDC indicated that over 90% of the challenges that arise, for example ultimately down at the storage infrastructure layer that's powering the apps ultimately arises from way above the stack all the way from the server layer on down where even the virtual machine layer. And there, for example, AIOps for infrastructure has become a game changer for customers to be able to bring the power of AI and machine learning and multi-variate analysis to be able to predict and prevent issues. Dave, you also touched upon Edge and across the board. What we're seeing is the Enterprise Edge is becoming that frontier for customer experiences and the opportunity to reimagine customer experiences as well as just the frontier for commerce that's happening. When you look at retail and manufacturing and or financial services. So across the board with the data growth that's happening and this Edge becoming the strategic frontier for delivering the customer experiences how you power your application workloads there and how you deliver that data and protect that data and be able to seamlessly manage that overall infrastructure. As you mentioned abstracted away at a higher level becomes incredibly important for customers. >> So interesting to hear how the conversations changed. I'd like to say, I go back to whatever it was five years ago, we're talking about flash storage class memory, NVMe and those things are still there but your emphasis now you're talking about machine learning, AI, math around deep learning. It's really software is really what you're focusing on these days. >> Very much so. Certainly this notion of software and services that are delivering and unlocking a whole new experience for customers that's really the game changer going forward for customers. And that's what we're focused on. >> Well, I said we had a little surprise for you. So you guys are having an event on May 4th. It's called Unleash The Power of Data. What's that event all about Sandeep? >> Yeah. We are very much excited about our May 4th event. As you mentioned, it's called Unleash The Power of Data. And as most organizations today are data driven and data is at the heart of what they're doing. We're excited to invite everyone to join this event. And through this event we're unveiling a new vision for data that accelerates the data driven transformation from Edge to cloud. This event promises to be a pivotal event and one that IT admins, cloud architects, virtual machine admins, vice presidents, directors of IT and CIO really won't want to mess. Across the board this event is just bringing a new way of articulating the overall problem statement and in market in focused the articulation of the trends that we were just discussing. It's an event that's going to be hosted by a Business and Technology Journalist, Shabani Joshi. It will feature a market in panel with a focus on the crucial role that data is playing in customers digital transformation. It will also include and feature Antonio Neary, CEO of HPE and Tom black, senior vice president and general manager of HPE Storage Business and industry experts including Julia Palmer, research vice president at Gartner. We will unveil game changing HPE innovations that will make it possible for organizations across Edge to cloud to unleash the power of data. >> Sounds like great event. I presume I can go to hpe.com and get information, is it a registered event? How does that all work? Yeah, we invite everyone to visit hpe.com and by visiting there you can click and save the date of May 4th at 8:00 AM Pacific. We invite everyone to join us. We couldn't be more excited to get to this event and be able to share the vision and game-changing HPE innovations. >> Awesome. So I don't have to register, right? I don't have to give up my three children's name and my social security number to attend your event. Is that right? >> No registration required, come by, click on hpe.com. Save the date on your calendar. And we very much look forward to having everyone join us for this event. >> I love it, it's pure content event. I'm not going to get a phone call afterwards saying, "Hey, buy some stuff from me." That could come other channels but so that's good. Thank you for that. Thanks for providing that service to the industry. I'm excited to see what you guys are going to be announcing that day and look Sandeep. I mean, like I said, we've known each other a while. We've seen a lot of trends but the next 10 years it ain't going to look like the last 10 is it? >> It's going to be very different and we couldn't be more excited. >> Well, Sandeep, thanks so much for coming to theCube and riffing with me on the industry and giving us a preview for your event. Good luck with that. And always great to see you. >> Thanks a lot, Dave. Always great to see you as well. >> All right. And thank you everybody. This is Dave Volante for theCube and we'll see you next time. 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