>> Joy: Welcome to the Virtual Big Data Conference. Vertica is so excited to host this event. I'm Joy King, and I'll be your host for today's Big Data Conference Keynote Session. It's my honor and my genuine pleasure to lead Vertica's product and go-to-market strategy. And I'm so lucky to have a passionate and committed team who turned our Vertica BDC event, into a virtual event in a very short amount of time. I want to thank the thousands of people, and yes, that's our true number who have registered to attend this virtual event. We were determined to balance your health, safety and your peace of mind with the excitement of the Vertica BDC. This is a very unique event. Because as I hope you all know, we focus on engineering and architecture, best practice sharing and customer stories that will educate and inspire everyone. I also want to thank our top sponsors for the virtual BDC, Arrow, and Pure Storage. Our partnerships are so important to us and to everyone in the audience. Because together, we get things done faster and better. Now for today's keynote, you'll hear from three very important and energizing speakers. First, Colin Mahony, our SVP and General Manager for Vertica, will talk about the market trends that Vertica is betting on to win for our customers. And he'll share the exciting news about our Vertica 10 announcement and how this will benefit our customers. Then you'll hear from Amy Fowler, VP of strategy and solutions for FlashBlade at Pure Storage. Our partnership with Pure Storage is truly unique in the industry, because together modern infrastructure from Pure powers modern analytics from Vertica. And then you'll hear from John Yovanovich, Director of IT at AT&T, who will tell you about the Pure Vertica Symphony that plays live every day at AT&T. Here we go, Colin, over to you. >> Colin: Well, thanks a lot joy. And, I want to echo Joy's thanks to our sponsors, and so many of you who have helped make this happen. This is not an easy time for anyone. We were certainly looking forward to getting together in person in Boston during the Vertica Big Data Conference and Winning with Data. But I think all of you and our team have done a great job, scrambling and putting together a terrific virtual event. So really appreciate your time. I also want to remind people that we will make both the slides and the full recording available after this. So for any of those who weren't able to join live, that is still going to be available. Well, things have been pretty exciting here. And in the analytic space in general, certainly for Vertica, there's a lot happening. There are a lot of problems to solve, a lot of opportunities to make things better, and a lot of data that can really make every business stronger, more efficient, and frankly, more differentiated. For Vertica, though, we know that focusing on the challenges that we can directly address with our platform, and our people, and where we can actually make the biggest difference is where we ought to be putting our energy and our resources. I think one of the things that has made Vertica so strong over the years is our ability to focus on those areas where we can make a great difference. So for us as we look at the market, and we look at where we play, there are really three recent and some not so recent, but certainly picking up a lot of the market trends that have become critical for every industry that wants to Win Big With Data. We've heard this loud and clear from our customers and from the analysts that cover the market. If I were to summarize these three areas, this really is the core focus for us right now. We know that there's massive data growth. And if we can unify the data silos so that people can really take advantage of that data, we can make a huge difference. We know that public clouds offer tremendous advantages, but we also know that balance and flexibility is critical. And we all need the benefit that machine learning for all the types up to the end data science. We all need the benefits that they can bring to every single use case, but only if it can really be operationalized at scale, accurate and in real time. And the power of Vertica is, of course, how we're able to bring so many of these things together. Let me talk a little bit more about some of these trends. So one of the first industry trends that we've all been following probably now for over the last decade, is Hadoop and specifically HDFS. So many companies have invested, time, money, more importantly, people in leveraging the opportunity that HDFS brought to the market. HDFS is really part of a much broader storage disruption that we'll talk a little bit more about, more broadly than HDFS. But HDFS itself was really designed for petabytes of data, leveraging low cost commodity hardware and the ability to capture a wide variety of data formats, from a wide variety of data sources and applications. And I think what people really wanted, was to store that data before having to define exactly what structures they should go into. So over the last decade or so, the focus for most organizations is figuring out how to capture, store and frankly manage that data. And as a platform to do that, I think, Hadoop was pretty good. It certainly changed the way that a lot of enterprises think about their data and where it's locked up. In parallel with Hadoop, particularly over the last five years, Cloud Object Storage has also given every organization another option for collecting, storing and managing even more data. That has led to a huge growth in data storage, obviously, up on public clouds like Amazon and their S3, Google Cloud Storage and Azure Blob Storage just to name a few. And then when you consider regional and local object storage offered by cloud vendors all over the world, the explosion of that data, in leveraging this type of object storage is very real. And I think, as I mentioned, it's just part of this broader storage disruption that's been going on. But with all this growth in the data, in all these new places to put this data, every organization we talk to is facing even more challenges now around the data silo. Sure the data silos certainly getting bigger. And hopefully they're getting cheaper per bit. But as I said, the focus has really been on collecting, storing and managing the data. But between the new data lakes and many different cloud object storage combined with all sorts of data types from the complexity of managing all this, getting that business value has been very limited. This actually takes me to big bet number one for Team Vertica, which is to unify the data. Our goal, and some of the announcements we have made today plus roadmap announcements I'll share with you throughout this presentation. Our goal is to ensure that all the time, money and effort that has gone into storing that data, all the data turns into business value. So how are we going to do that? With a unified analytics platform that analyzes the data wherever it is HDFS, Cloud Object Storage, External tables in an any format ORC, Parquet, JSON, and of course, our own Native Roth Vertica format. Analyze the data in the right place in the right format, using a single unified tool. This is something that Vertica has always been committed to, and you'll see in some of our announcements today, we're just doubling down on that commitment. Let's talk a little bit more about the public cloud. This is certainly the second trend. It's the second wave maybe of data disruption with object storage. And there's a lot of advantages when it comes to public cloud. There's no question that the public clouds give rapid access to compute storage with the added benefit of eliminating data center maintenance that so many companies, want to get out of themselves. But maybe the biggest advantage that I see is the architectural innovation. The public clouds have introduced so many methodologies around how to provision quickly, separating compute and storage and really dialing-in the exact needs on demand, as you change workloads. When public clouds began, it made a lot of sense for the cloud providers and their customers to charge and pay for compute and storage in the ratio that each use case demanded. And I think you're seeing that trend, proliferate all over the place, not just up in public cloud. That architecture itself is really becoming the next generation architecture for on-premise data centers, as well. But there are a lot of concerns. I think we're all aware of them. They're out there many times for different workloads, there are higher costs. Especially if some of the workloads that are being run through analytics, which tend to run all the time. Just like some of the silo challenges that companies are facing with HDFS, data lakes and cloud storage, the public clouds have similar types of siloed challenges as well. Initially, there was a belief that they were cheaper than data centers, and when you added in all the costs, it looked that way. And again, for certain elastic workloads, that is the case. I don't think that's true across the board overall. Even to the point where a lot of the cloud vendors aren't just charging lower costs anymore. We hear from a lot of customers that they don't really want to tether themselves to any one cloud because of some of those uncertainties. Of course, security and privacy are a concern. We hear a lot of concerns with regards to cloud and even some SaaS vendors around shared data catalogs, across all the customers and not enough separation. But security concerns are out there, you can read about them. I'm not going to jump into that bandwagon. But we hear about them. And then, of course, I think one of the things we hear the most from our customers, is that each cloud stack is starting to feel even a lot more locked in than the traditional data warehouse appliance. And as everybody knows, the industry has been running away from appliances as fast as it can. And so they're not eager to get locked into another, quote, unquote, virtual appliance, if you will, up in the cloud. They really want to make sure they have flexibility in which clouds, they're going to today, tomorrow and in the future. And frankly, we hear from a lot of our customers that they're very interested in eventually mixing and matching, compute from one cloud with, say storage from another cloud, which I think is something that we'll hear a lot more about. And so for us, that's why we've got our big bet number two. we love the cloud. We love the public cloud. We love the private clouds on-premise, and other hosting providers. But our passion and commitment is for Vertica to be able to run in any of the clouds that our customers choose, and make it portable across those clouds. We have supported on-premises and all public clouds for years. And today, we have announced even more support for Vertica in Eon Mode, the deployment option that leverages the separation of compute from storage, with even more deployment choices, which I'm going to also touch more on as we go. So super excited about our big bet number two. And finally as I mentioned, for all the hype that there is around machine learning, I actually think that most importantly, this third trend that team Vertica is determined to address is the need to bring business critical, analytics, machine learning, data science projects into production. For so many years, there just wasn't enough data available to justify the investment in machine learning. Also, processing power was expensive, and storage was prohibitively expensive. But to train and score and evaluate all the different models to unlock the full power of predictive analytics was tough. Today you have those massive data volumes. You have the relatively cheap processing power and storage to make that dream a reality. And if you think about this, I mean with all the data that's available to every company, the real need is to operationalize the speed and the scale of machine learning so that these organizations can actually take advantage of it where they need to. I mean, we've seen this for years with Vertica, going back to some of the most advanced gaming companies in the early days, they were incorporating this with live data directly into their gaming experiences. Well, every organization wants to do that now. And the accuracy for clickability and real time actions are all key to separating the leaders from the rest of the pack in every industry when it comes to machine learning. But if you look at a lot of these projects, the reality is that there's a ton of buzz, there's a ton of hype spanning every acronym that you can imagine. But most companies are struggling, do the separate teams, different tools, silos and the limitation that many platforms are facing, driving, down sampling to get a small subset of the data, to try to create a model that then doesn't apply, or compromising accuracy and making it virtually impossible to replicate models, and understand decisions. And if there's one thing that we've learned when it comes to data, prescriptive data at the atomic level, being able to show end of one as we refer to it, meaning individually tailored data. No matter what it is healthcare, entertainment experiences, like gaming or other, being able to get at the granular data and make these decisions, make that scoring applies to machine learning just as much as it applies to giving somebody a next-best-offer. But the opportunity has never been greater. The need to integrate this end-to-end workflow and support the right tools without compromising on that accuracy. Think about it as no downsampling, using all the data, it really is key to machine learning success. Which should be no surprise then why the third big bet from Vertica is one that we've actually been working on for years. And we're so proud to be where we are today, helping the data disruptors across the world operationalize machine learning. This big bet has the potential to truly unlock, really the potential of machine learning. And today, we're announcing some very important new capabilities specifically focused on unifying the work being done by the data science community, with their preferred tools and platforms, and the volume of data and performance at scale, available in Vertica. Our strategy has been very consistent over the last several years. As I said in the beginning, we haven't deviated from our strategy. Of course, there's always things that we add. Most of the time, it's customer driven, it's based on what our customers are asking us to do. But I think we've also done a great job, not trying to be all things to all people. Especially as these hype cycles flare up around us, we absolutely love participating in these different areas without getting completely distracted. I mean, there's a variety of query tools and data warehouses and analytics platforms in the market. We all know that. There are tools and platforms that are offered by the public cloud vendors, by other vendors that support one or two specific clouds. There are appliance vendors, who I was referring to earlier who can deliver package data warehouse offerings for private data centers. And there's a ton of popular machine learning tools, languages and other kits. But Vertica is the only advanced analytic platform that can do all this, that can bring it together. We can analyze the data wherever it is, in HDFS, S3 Object Storage, or Vertica itself. Natively we support multiple clouds on-premise deployments, And maybe most importantly, we offer that choice of deployment modes to allow our customers to choose the architecture that works for them right now. It still also gives them the option to change move, evolve over time. And Vertica is the only analytics database with end-to-end machine learning that can truly operationalize ML at scale. And I know it's a mouthful. But it is not easy to do all these things. It is one of the things that highly differentiates Vertica from the rest of the pack. It is also why our customers, all of you continue to bet on us and see the value that we are delivering and we will continue to deliver. Here's a couple of examples of some of our customers who are powered by Vertica. It's the scale of data. It's the millisecond response times. Performance and scale have always been a huge part of what we have been about, not the only thing. I think the functionality all the capabilities that we add to the platform, the ease of use, the flexibility, obviously with the deployment. But if you look at some of the numbers they are under these customers on this slide. And I've shared a lot of different stories about these customers. Which, by the way, it still amaze me every time I talk to one and I get the updates, you can see the power and the difference that Vertica is making. Equally important, if you look at a lot of these customers, they are the epitome of being able to deploy Vertica in a lot of different environments. Many of the customers on this slide are not using Vertica just on-premise or just in the cloud. They're using it in a hybrid way. They're using it in multiple different clouds. And again, we've been with them on that journey throughout, which is what has made this product and frankly, our roadmap and our vision exactly what it is. It's been quite a journey. And that journey continues now with the Vertica 10 release. The Vertica 10 release is obviously a massive release for us. But if you look back, you can see that building on that native columnar architecture that started a long time ago, obviously, with the C-Store paper. We built it to leverage that commodity hardware, because it was an architecture that was never tightly integrated with any specific underlying infrastructure. I still remember hearing the initial pitch from Mike Stonebreaker, about the vision of Vertica as a software only solution and the importance of separating the company from hardware innovation. And at the time, Mike basically said to me, "there's so much R&D in innovation that's going to happen in hardware, we shouldn't bake hardware into our solution. We should do it in software, and we'll be able to take advantage of that hardware." And that is exactly what has happened. But one of the most recent innovations that we embraced with hardware is certainly that separation of compute and storage. As I said previously, the public cloud providers offered this next generation architecture, really to ensure that they can provide the customers exactly what they needed, more compute or more storage and charge for each, respectively. The separation of compute and storage, compute from storage is a major milestone in data center architectures. If you think about it, it's really not only a public cloud innovation, though. It fundamentally redefines the next generation data architecture for on-premise and for pretty much every way people are thinking about computing today. And that goes for software too. Object storage is an example of the cost effective means for storing data. And even more importantly, separating compute from storage for analytic workloads has a lot of advantages. Including the opportunity to manage much more dynamic, flexible workloads. And more importantly, truly isolate those workloads from others. And by the way, once you start having something that can truly isolate workloads, then you can have the conversations around autonomic computing, around setting up some nodes, some compute resources on the data that won't affect any of the other data to do some things on their own, maybe some self analytics, by the system, etc. A lot of things that many of you know we've already been exploring in terms of our own system data in the product. But it was May 2018, believe it or not, it seems like a long time ago where we first announced Eon Mode and I want to make something very clear, actually about Eon mode. It's a mode, it's a deployment option for Vertica customers. And I think this is another huge benefit that we don't talk about enough. But unlike a lot of vendors in the market who will dig you and charge you for every single add-on like hit-buy, you name it. You get this with the Vertica product. If you continue to pay support and maintenance, this comes with the upgrade. This comes as part of the new release. So any customer who owns or buys Vertica has the ability to set up either an Enterprise Mode or Eon Mode, which is a question I know that comes up sometimes. Our first announcement of Eon was obviously AWS customers, including the trade desk, AT&T. Most of whom will be speaking here later at the Virtual Big Data Conference. They saw a huge opportunity. Eon Mode, not only allowed Vertica to scale elastically with that specific compute and storage that was needed, but it really dramatically simplified database operations including things like workload balancing, node recovery, compute provisioning, etc. So one of the most popular functions is that ability to isolate the workloads and really allocate those resources without negatively affecting others. And even though traditional data warehouses, including Vertica Enterprise Mode have been able to do lots of different workload isolation, it's never been as strong as Eon Mode. Well, it certainly didn't take long for our customers to see that value across the board with Eon Mode. Not just up in the cloud, in partnership with one of our most valued partners and a platinum sponsor here. Joy mentioned at the beginning. We announced Vertica Eon Mode for Pure Storage FlashBlade in September 2019. And again, just to be clear, this is not a new product, it's one Vertica with yet more deployment options. With Pure Storage, Vertica in Eon mode is not limited in any way by variable cloud, network latency. The performance is actually amazing when you take the benefits of separate and compute from storage and you run it with a Pure environment on-premise. Vertica in Eon Mode has a super smart cache layer that we call the depot. It's a big part of our secret sauce around Eon mode. And combined with the power and performance of Pure's FlashBlade, Vertica became the industry's first advanced analytics platform that actually separates compute and storage for on-premises data centers. Something that a lot of our customers are already benefiting from, and we're super excited about it. But as I said, this is a journey. We don't stop, we're not going to stop. Our customers need the flexibility of multiple public clouds. So today with Vertica 10, we're super proud and excited to announce support for Vertica in Eon Mode on Google Cloud. This gives our customers the ability to use their Vertica licenses on Amazon AWS, on-premise with Pure Storage and on Google Cloud. Now, we were talking about HDFS and a lot of our customers who have invested quite a bit in HDFS as a place, especially to store data have been pushing us to support Eon Mode with HDFS. So as part of Vertica 10, we are also announcing support for Vertica in Eon Mode using HDFS as the communal storage. Vertica's own Roth format data can be stored in HDFS, and actually the full functionality of Vertica is complete analytics, geospatial pattern matching, time series, machine learning, everything that we have in there can be applied to this data. And on the same HDFS nodes, Vertica can actually also analyze data in ORC or Parquet format, using External tables. We can also execute joins between the Roth data the External table holds, which powers a much more comprehensive view. So again, it's that flexibility to be able to support our customers, wherever they need us to support them on whatever platform, they have. Vertica 10 gives us a lot more ways that we can deploy Eon Mode in various environments for our customers. It allows them to take advantage of Vertica in Eon Mode and the power that it brings with that separation, with that workload isolation, to whichever platform they are most comfortable with. Now, there's a lot that has come in Vertica 10. I'm definitely not going to be able to cover everything. But we also introduced complex types as an example. And complex data types fit very well into Eon as well in this separation. They significantly reduce the data pipeline, the cost of moving data between those, a much better support for unstructured data, which a lot of our customers have mixed with structured data, of course, and they leverage a lot of columnar execution that Vertica provides. So you get complex data types in Vertica now, a lot more data, stronger performance. It goes great with the announcement that we made with the broader Eon Mode. Let's talk a little bit more about machine learning. We've been actually doing work in and around machine learning with various extra regressions and a whole bunch of other algorithms for several years. We saw the huge advantage that MPP offered, not just as a sequel engine as a database, but for ML as well. Didn't take as long to realize that there's a lot more to operationalizing machine learning than just those algorithms. It's data preparation, it's that model trade training. It's the scoring, the shaping, the evaluation. That is so much of what machine learning and frankly, data science is about. You do know, everybody always wants to jump to the sexy algorithm and we handle those tasks very, very well. It makes Vertica a terrific platform to do that. A lot of work in data science and machine learning is done in other tools. I had mentioned that there's just so many tools out there. We want people to be able to take advantage of all that. We never believed we were going to be the best algorithm company or come up with the best models for people to use. So with Vertica 10, we support PMML. We can import now and export PMML models. It's a huge step for us around that operationalizing machine learning projects for our customers. Allowing the models to get built outside of Vertica yet be imported in and then applying to that full scale of data with all the performance that you would expect from Vertica. We also are more tightly integrating with Python. As many of you know, we've been doing a lot of open source projects with the community driven by many of our customers, like Uber. And so now with Python we've integrated with TensorFlow, allowing data scientists to build models in their preferred language, to take advantage of TensorFlow. But again, to store and deploy those models at scale with Vertica. I think both these announcements are proof of our big bet number three, and really our commitment to supporting innovation throughout the community by operationalizing ML with that accuracy, performance and scale of Vertica for our customers. Again, there's a lot of steps when it comes to the workflow of machine learning. These are some of them that you can see on the slide, and it's definitely not linear either. We see this as a circle. And companies that do it, well just continue to learn, they continue to rescore, they continue to redeploy and they want to operationalize all that within a single platform that can take advantage of all those capabilities. And that is the platform, with a very robust ecosystem that Vertica has always been committed to as an organization and will continue to be. This graphic, many of you have seen it evolve over the years. Frankly, if we put everything and everyone on here wouldn't fit on a slide. But it will absolutely continue to evolve and grow as we support our customers, where they need the support most. So, again, being able to deploy everywhere, being able to take advantage of Vertica, not just as a business analyst or a business user, but as a data scientists or as an operational or BI person. We want Vertica to be leveraged and used by the broader organization. So I think it's fair to say and I encourage everybody to learn more about Vertica 10, because I'm just highlighting some of the bigger aspects of it. But we talked about those three market trends. The need to unify the silos, the need for hybrid multiple cloud deployment options, the need to operationalize business critical machine learning projects. Vertica 10 has absolutely delivered on those. But again, we are not going to stop. It is our job not to, and this is how Team Vertica thrives. I always joke that the next release is the best release. And, of course, even after Vertica 10, that is also true, although Vertica 10 is pretty awesome. But, you know, from the first line of code, we've always been focused on performance and scale, right. And like any really strong data platform, the execution engine, the optimizer and the execution engine are the two core pieces of that. Beyond Vertica 10, some of the big things that we're already working on, next generation execution engine. We're already actually seeing incredible early performance from this. And this is just one example, of how important it is for an organization like Vertica to constantly go back and re-innovate. Every single release, we do the sit ups and crunches, our performance and scale. How do we improve? And there's so many parts of the core server, there's so many parts of our broader ecosystem. We are constantly looking at coverages of how we can go back to all the code lines that we have, and make them better in the current environment. And it's not an easy thing to do when you're doing that, and you're also expanding in the environment that we are expanding into to take advantage of the different deployments, which is a great segue to this slide. Because if you think about today, we're obviously already available with Eon Mode and Amazon, AWS and Pure and actually MinIO as well. As I talked about in Vertica 10 we're adding Google and HDFS. And coming next, obviously, Microsoft Azure, Alibaba cloud. So being able to expand into more of these environments is really important for the Vertica team and how we go forward. And it's not just running in these clouds, for us, we want it to be a SaaS like experience in all these clouds. We want you to be able to deploy Vertica in 15 minutes or less on these clouds. You can also consume Vertica, in a lot of different ways, on these clouds. As an example, in Amazon Vertica by the Hour. So for us, it's not just about running, it's about taking advantage of the ecosystems that all these cloud providers offer, and really optimizing the Vertica experience as part of them. Optimization, around automation, around self service capabilities, extending our management console, we now have products that like the Vertica Advisor Tool that our Customer Success Team has created to actually use our own smarts in Vertica. To take data from customers that give it to us and help them tune automatically their environment. You can imagine that we're taking that to the next level, in a lot of different endeavors that we're doing around how Vertica as a product can actually be smarter because we all know that simplicity is key. There just aren't enough people in the world who are good at managing data and taking it to the next level. And of course, other things that we all hear about, whether it's Kubernetes and containerization. You can imagine that that probably works very well with the Eon Mode and separating compute and storage. But innovation happens everywhere. We innovate around our community documentation. Many of you have taken advantage of the Vertica Academy. The numbers there are through the roof in terms of the number of people coming in and certifying on it. So there's a lot of things that are within the core products. There's a lot of activity and action beyond the core products that we're taking advantage of. And let's not forget why we're here, right? It's easy to talk about a platform, a data platform, it's easy to jump into all the functionality, the analytics, the flexibility, how we can offer it. But at the end of the day, somebody, a person, she's got to take advantage of this data, she's got to be able to take this data and use this information to make a critical business decision. And that doesn't happen unless we explore lots of different and frankly, new ways to get that predictive analytics UI and interface beyond just the standard BI tools in front of her at the right time. And so there's a lot of activity, I'll tease you with that going on in this organization right now about how we can do that and deliver that for our customers. We're in a great position to be able to see exactly how this data is consumed and used and start with this core platform that we have to go out. Look, I know, the plan wasn't to do this as a virtual BDC. But I really appreciate you tuning in. Really appreciate your support. I think if there's any silver lining to us, maybe not being able to do this in person, it's the fact that the reach has actually gone significantly higher than what we would have been able to do in person in Boston. We're certainly looking forward to doing a Big Data Conference in the future. But if I could leave you with anything, know this, since that first release for Vertica, and our very first customers, we have been very consistent. We respect all the innovation around us, whether it's open source or not. We understand the market trends. We embrace those new ideas and technologies and for us true north, and the most important thing is what does our customer need to do? What problem are they trying to solve? And how do we use the advantages that we have without disrupting our customers? But knowing that you depend on us to deliver that unified analytics strategy, it will deliver that performance of scale, not only today, but tomorrow and for years to come. We've added a lot of great features to Vertica. I think we've said no to a lot of things, frankly, that we just knew we wouldn't be the best company to deliver. When we say we're going to do things we do them. Vertica 10 is a perfect example of so many of those things that we from you, our customers have heard loud and clear, and we have delivered. I am incredibly proud of this team across the board. I think the culture of Vertica, a customer first culture, jumping in to help our customers win no matter what is also something that sets us massively apart. I hear horror stories about support experiences with other organizations. And people always seem to be amazed at Team Vertica's willingness to jump in or their aptitude for certain technical capabilities or understanding the business. And I think sometimes we take that for granted. But that is the team that we have as Team Vertica. We are incredibly excited about Vertica 10. I think you're going to love the Virtual Big Data Conference this year. I encourage you to tune in. Maybe one other benefit is I know some people were worried about not being able to see different sessions because they were going to overlap with each other well now, even if you can't do it live, you'll be able to do those sessions on demand. Please enjoy the Vertica Big Data Conference here in 2020. Please you and your families and your co-workers be safe during these times. I know we will get through it. And analytics is probably going to help with a lot of that and we already know it is helping in many different ways. So believe in the data, believe in data's ability to change the world for the better. And thank you for your time. And with that, I am delighted to now introduce Micro Focus CEO Stephen Murdoch to the Vertica Big Data Virtual Conference. Thank you Stephen. >> Stephen: Hi, everyone, my name is Stephen Murdoch. I have the pleasure and privilege of being the Chief Executive Officer here at Micro Focus. Please let me add my welcome to the Big Data Conference. And also my thanks for your support, as we've had to pivot to this being virtual rather than a physical conference. Its amazing how quickly we all reset to a new normal. I certainly didn't expect to be addressing you from my study. Vertica is an incredibly important part of Micro Focus family. Is key to our goal of trying to enable and help customers become much more data driven across all of their IT operations. Vertica 10 is a huge step forward, we believe. It allows for multi-cloud innovation, genuinely hybrid deployments, begin to leverage machine learning properly in the enterprise, and also allows the opportunity to unify currently siloed lakes of information. We operate in a very noisy, very competitive market, and there are people, who are in that market who can do some of those things. The reason we are so excited about Vertica is we genuinely believe that we are the best at doing all of those things. And that's why we've announced publicly, you're under executing internally, incremental investment into Vertica. That investments targeted at accelerating the roadmaps that already exist. And getting that innovation into your hands faster. This idea is speed is key. It's not a question of if companies have to become data driven organizations, it's a question of when. So that speed now is really important. And that's why we believe that the Big Data Conference gives a great opportunity for you to accelerate your own plans. You will have the opportunity to talk to some of our best architects, some of the best development brains that we have. But more importantly, you'll also get to hear from some of our phenomenal Roth Data customers. You'll hear from Uber, from the Trade Desk, from Philips, and from AT&T, as well as many many others. And just hearing how those customers are using the power of Vertica to accelerate their own, I think is the highlight. And I encourage you to use this opportunity to its full. Let me close by, again saying thank you, we genuinely hope that you get as much from this virtual conference as you could have from a physical conference. And we look forward to your engagement, and we look forward to hearing your feedback. With that, thank you very much. >> Joy: Thank you so much, Stephen, for joining us for the Vertica Big Data Conference. Your support and enthusiasm for Vertica is so clear, and it makes a big difference. Now, I'm delighted to introduce Amy Fowler, the VP of Strategy and Solutions for FlashBlade at Pure Storage, who was one of our BDC Platinum Sponsors, and one of our most valued partners. It was a proud moment for me, when we announced Vertica in Eon mode for Pure Storage FlashBlade and we became the first analytics data warehouse that separates compute from storage for on-premise data centers. Thank you so much, Amy, for joining us. Let's get started. >> Amy: Well, thank you, Joy so much for having us. And thank you all for joining us today, virtually, as we may all be. So, as we just heard from Colin Mahony, there are some really interesting trends that are happening right now in the big data analytics market. From the end of the Hadoop hype cycle, to the new cloud reality, and even the opportunity to help the many data science and machine learning projects move from labs to production. So let's talk about these trends in the context of infrastructure. And in particular, look at why a modern storage platform is relevant as organizations take on the challenges and opportunities associated with these trends. The answer is the Hadoop hype cycles left a lot of data in HDFS data lakes, or reservoirs or swamps depending upon the level of the data hygiene. But without the ability to get the value that was promised from Hadoop as a platform rather than a distributed file store. And when we combine that data with the massive volume of data in Cloud Object Storage, we find ourselves with a lot of data and a lot of silos, but without a way to unify that data and find value in it. Now when you look at the infrastructure data lakes are traditionally built on, it is often direct attached storage or data. The approach that Hadoop took when it entered the market was primarily bound by the limits of networking and storage technologies. One gig ethernet and slower spinning disk. But today, those barriers do not exist. And all FlashStorage has fundamentally transformed how data is accessed, managed and leveraged. The need for local data storage for significant volumes of data has been largely mitigated by the performance increases afforded by all Flash. At the same time, organizations can achieve superior economies of scale with that segregation of compute and storage. With compute and storage, you don't always scale in lockstep. Would you want to add an engine to the train every time you add another boxcar? Probably not. But from a Pure Storage perspective, FlashBlade is uniquely architected to allow customers to achieve better resource utilization for compute and storage, while at the same time, reducing complexity that has arisen from the siloed nature of the original big data solutions. The second and equally important recent trend we see is something I'll call cloud reality. The public clouds made a lot of promises and some of those promises were delivered. But cloud economics, especially usage based and elastic scaling, without the control that many companies need to manage the financial impact is causing a lot of issues. In addition, the risk of vendor lock-in from data egress, charges, to integrated software stacks that can't be moved or deployed on-premise is causing a lot of organizations to back off the all the way non-cloud strategy, and move toward hybrid deployments. Which is kind of funny in a way because it wasn't that long ago that there was a lot of talk about no more data centers. And for example, one large retailer, I won't name them, but I'll admit they are my favorites. They several years ago told us they were completely done with on-prem storage infrastructure, because they were going 100% to the cloud. But they just deployed FlashBlade for their data pipelines, because they need predictable performance at scale. And the all cloud TCO just didn't add up. Now, that being said, well, there are certainly challenges with the public cloud. It has also brought some things to the table that we see most organizations wanting. First of all, in a lot of cases applications have been built to leverage object storage platforms like S3. So they need that object protocol, but they may also need it to be fast. And the said object may be oxymoron only a few years ago, and this is an area of the market where Pure and FlashBlade have really taken a leadership position. Second, regardless of where the data is physically stored, organizations want the best elements of a cloud experience. And for us, that means two main things. Number one is simplicity and ease of use. If you need a bunch of storage experts to run the system, that should be considered a bug. The other big one is the consumption model. The ability to pay for what you need when you need it, and seamlessly grow your environment over time totally nondestructively. This is actually pretty huge and something that a lot of vendors try to solve for with finance programs. But no finance program can address the pain of a forklift upgrade, when you need to move to next gen hardware. To scale nondestructively over long periods of time, five to 10 years plus is a crucial architectural decisions need to be made at the outset. Plus, you need the ability to pay as you use it. And we offer something for FlashBlade called Pure as a Service, which delivers exactly that. The third cloud characteristic that many organizations want is the option for hybrid. Even if that is just a DR site in the cloud. In our case, that means supporting appplication of S3, at the AWS. And the final trend, which to me represents the biggest opportunity for all of us, is the need to help the many data science and machine learning projects move from labs to production. This means bringing all the machine learning functions and model training to the data, rather than moving samples or segments of data to separate platforms. As we all know, machine learning needs a ton of data for accuracy. And there is just too much data to retrieve from the cloud for every training job. At the same time, predictive analytics without accuracy is not going to deliver the business advantage that everyone is seeking. You can kind of visualize data analytics as it is traditionally deployed as being on a continuum. With that thing, we've been doing the longest, data warehousing on one end, and AI on the other end. But the way this manifests in most environments is a series of silos that get built up. So data is duplicated across all kinds of bespoke analytics and AI, environments and infrastructure. This creates an expensive and complex environment. So historically, there was no other way to do it because some level of performance is always table stakes. And each of these parts of the data pipeline has a different workload profile. A single platform to deliver on the multi dimensional performances, diverse set of applications required, that didn't exist three years ago. And that's why the application vendors pointed you towards bespoke things like DAS environments that we talked about earlier. And the fact that better options exists today is why we're seeing them move towards supporting this disaggregation of compute and storage. And when it comes to a platform that is a better option, one with a modern architecture that can address the diverse performance requirements of this continuum, and allow organizations to bring a model to the data instead of creating separate silos. That's exactly what FlashBlade is built for. Small files, large files, high throughput, low latency and scale to petabytes in a single namespace. And this is importantly a single rapid space is what we're focused on delivering for our customers. At Pure, we talk about it in the context of modern data experience because at the end of the day, that's what it's really all about. The experience for your teams in your organization. And together Pure Storage and Vertica have delivered that experience to a wide range of customers. From a SaaS analytics company, which uses Vertica on FlashBlade to authenticate the quality of digital media in real time, to a multinational car company, which uses Vertica on FlashBlade to make thousands of decisions per second for autonomous cars, or a healthcare organization, which uses Vertica on FlashBlade to enable healthcare providers to make real time decisions that impact lives. And I'm sure you're all looking forward to hearing from John Yavanovich from AT&T. To hear how he's been doing this with Vertica and FlashBlade as well. He's coming up soon. We have been really excited to build this partnership with Vertica. And we're proud to provide the only on-premise storage platform validated with Vertica Eon Mode. And deliver this modern data experience to our customers together. Thank you all so much for joining us today. >> Joy: Amy, thank you so much for your time and your insights. Modern infrastructure is key to modern analytics, especially as organizations leverage next generation data center architectures, and object storage for their on-premise data centers. Now, I'm delighted to introduce our last speaker in our Vertica Big Data Conference Keynote, John Yovanovich, Director of IT for AT&T. Vertica is so proud to serve AT&T, and especially proud of the harmonious impact we are having in partnership with Pure Storage. John, welcome to the Virtual Vertica BDC. >> John: Thank you joy. It's a pleasure to be here. And I'm excited to go through this presentation today. And in a unique fashion today 'cause as I was thinking through how I wanted to present the partnership that we have formed together between Pure Storage, Vertica and AT&T, I want to emphasize how well we all work together and how these three components have really driven home, my desire for a harmonious to use your word relationship. So, I'm going to move forward here and with. So here, what I'm going to do the theme of today's presentation is the Pure Vertica Symphony live at AT&T. And if anybody is a Westworld fan, you can appreciate the sheet music on the right hand side. What we're going to what I'm going to highlight here is in a musical fashion, is how we at AT&T leverage these technologies to save money to deliver a more efficient platform, and to actually just to make our customers happier overall. So as we look back, and back as early as just maybe a few years ago here at AT&T, I realized that we had many musicians to help the company. Or maybe you might want to call them data scientists, or data analysts. For the theme we'll stay with musicians. None of them were singing or playing from the same hymn book or sheet music. And so what we had was many organizations chasing a similar dream, but not exactly the same dream. And, best way to describe that is and I think with a lot of people this might resonate in your organizations. How many organizations are chasing a customer 360 view in your company? Well, I can tell you that I have at least four in my company. And I'm sure there are many that I don't know of. That is our problem because what we see is a repetitive sourcing of data. We see a repetitive copying of data. And there's just so much money to be spent. This is where I asked Pure Storage and Vertica to help me solve that problem with their technologies. What I also noticed was that there was no coordination between these departments. In fact, if you look here, nobody really wants to play with finance. Sales, marketing and care, sure that you all copied each other's data. But they actually didn't communicate with each other as they were copying the data. So the data became replicated and out of sync. This is a challenge throughout, not just my company, but all companies across the world. And that is, the more we replicate the data, the more problems we have at chasing or conquering the goal of single version of truth. In fact, I kid that I think that AT&T, we actually have adopted the multiple versions of truth, techno theory, which is not where we want to be, but this is where we are. But we are conquering that with the synergies between Pure Storage and Vertica. This is what it leaves us with. And this is where we are challenged and that if each one of our siloed business units had their own stories, their own dedicated stories, and some of them had more money than others so they bought more storage. Some of them anticipating storing more data, and then they really did. Others are running out of space, but can't put anymore because their bodies aren't been replenished. So if you look at it from this side view here, we have a limited amount of compute or fixed compute dedicated to each one of these silos. And that's because of the, wanting to own your own. And the other part is that you are limited or wasting space, depending on where you are in the organization. So there were the synergies aren't just about the data, but actually the compute and the storage. And I wanted to tackle that challenge as well. So I was tackling the data. I was tackling the storage, and I was tackling the compute all at the same time. So my ask across the company was can we just please play together okay. And to do that, I knew that I wasn't going to tackle this by getting everybody in the same room and getting them to agree that we needed one account table, because they will argue about whose account table is the best account table. But I knew that if I brought the account tables together, they would soon see that they had so much redundancy that I can now start retiring data sources. I also knew that if I brought all the compute together, that they would all be happy. But I didn't want them to tackle across tackle each other. And in fact that was one of the things that all business units really enjoy. Is they enjoy the silo of having their own compute, and more or less being able to control their own destiny. Well, Vertica's subclustering allows just that. And this is exactly what I was hoping for, and I'm glad they've brought through. And finally, how did I solve the problem of the single account table? Well when you don't have dedicated storage, and you can separate compute and storage as Vertica in Eon Mode does. And we store the data on FlashBlades, which you see on the left and right hand side, of our container, which I can describe in a moment. Okay, so what we have here, is we have a container full of compute with all the Vertica nodes sitting in the middle. Two loader, we'll call them loader subclusters, sitting on the sides, which are dedicated to just putting data onto the FlashBlades, which is sitting on both ends of the container. Now today, I have two dedicated storage or common dedicated might not be the right word, but two storage racks one on the left one on the right. And I treat them as separate storage racks. They could be one, but i created them separately for disaster recovery purposes, lashing work in case that rack were to go down. But that being said, there's no reason why I'm probably going to add a couple of them here in the future. So I can just have a, say five to 10, petabyte storage, setup, and I'll have my DR in another 'cause the DR shouldn't be in the same container. Okay, but I'll DR outside of this container. So I got them all together, I leveraged subclustering, I leveraged separate and compute. I was able to convince many of my clients that they didn't need their own account table, that they were better off having one. I eliminated, I reduced latency, I reduced our ticketing I reduce our data quality issues AKA ticketing okay. I was able to expand. What is this? As work. I was able to leverage elasticity within this cluster. As you can see, there are racks and racks of compute. We set up what we'll call the fixed capacity that each of the business units needed. And then I'm able to ramp up and release the compute that's necessary for each one of my clients based on their workloads throughout the day. And so while they compute to the right before you see that the instruments have already like, more or less, dedicated themselves towards all those are free for anybody to use. So in essence, what I have, is I have a concert hall with a lot of seats available. So if I want to run a 10 chair Symphony or 80, chairs, Symphony, I'm able to do that. And all the while, I can also do the same with my loader nodes. I can expand my loader nodes, to actually have their own Symphony or write all to themselves and not compete with any other workloads of the other clusters. What does that change for our organization? Well, it really changes the way our database administrators actually do their jobs. This has been a big transformation for them. They have actually become data conductors. Maybe you might even call them composers, which is interesting, because what I've asked them to do is morph into less technology and more workload analysis. And in doing so we're able to write auto-detect scripts, that watch the queues, watch the workloads so that we can help ramp up and trim down the cluster and subclusters as necessary. There has been an exciting transformation for our DBAs, who I need to now classify as something maybe like DCAs. I don't know, I have to work with HR on that. But I think it's an exciting future for their careers. And if we bring it all together, If we bring it all together, and then our clusters, start looking like this. Where everything is moving in harmonious, we have lots of seats open for extra musicians. And we are able to emulate a cloud experience on-prem. And so, I want you to sit back and enjoy the Pure Vertica Symphony live at AT&T. (soft music) >> Joy: Thank you so much, John, for an informative and very creative look at the benefits that AT&T is getting from its Pure Vertica symphony. I do really like the idea of engaging HR to change the title to Data Conductor. That's fantastic. I've always believed that music brings people together. And now it's clear that analytics at AT&T is part of that musical advantage. So, now it's time for a short break. And we'll be back for our breakout sessions, beginning at 12 pm Eastern Daylight Time. We have some really exciting sessions planned later today. And then again, as you can see on Wednesday. Now because all of you are already logged in and listening to this keynote, you already know the steps to continue to participate in the sessions that are listed here and on the previous slide. In addition, everyone received an email yesterday, today, and you'll get another one tomorrow, outlining the simple steps to register, login and choose your session. If you have any questions, check out the emails or go to www.vertica.com/bdc2020 for the logistics information. There are a lot of choices and that's always a good thing. Don't worry if you want to attend one or more or can't listen to these live sessions due to your timezone. All the sessions, including the Q&A sections will be available on demand and everyone will have access to the recordings as well as even more pre-recorded sessions that we'll post to the BDC website. Now I do want to leave you with two other important sites. First, our Vertica Academy. Vertica Academy is available to everyone. And there's a variety of very technical, self-paced, on-demand training, virtual instructor-led workshops, and Vertica Essentials Certification. And it's all free. Because we believe that Vertica expertise, helps everyone accelerate their Vertica projects and the advantage that those projects deliver. Now, if you have questions or want to engage with our Vertica engineering team now, we're waiting for you on the Vertica forum. We'll answer any questions or discuss any ideas that you might have. Thank you again for joining the Vertica Big Data Conference Keynote Session. Enjoy the rest of the BDC because there's a lot more to come

>> Innovation Day, brought to you by Comcast. >> Hey, welcome back everybody, Jeff Rick, here with theCube. We're at the Comcast Silicon Valley Innovation Center here in Sunnyvale. It's a very cool space, I think it's grown up over a number of years as they've originated with some acquired companies, and now they got a huge setup here, and we had a big day today talking about customer experience, and really, if you look at the Comcast Voice Remote, and there's a lot of stuff going on that's maybe under the covers, you don't really give Comcast credit for, but they're actually doing a lot. And we're excited to, kind of dive into it a little bit deeper with our next guest, she's Annie Weskesser, she's a CMO of Uniphore. Annie, welcome. >> Yeah, thank you for having me here today. >> Absolutely. So what is Uniphore, for people that aren't familiar with the company. >> So Uniphore is a global leader in conversational service automation, and our vision is to bridge the gap between human and machine, through voice AI and automation. >> That's a mouth full. >> Yes. >> Conversational... >> Service. >> Service. >> Yes. >> So, people talk, and so you guys are heavily involved in voice. So what are the applications where people are using your voice? >> Yep, well primarily our focus is call centers. >> Okay. >> So large enterprises who have massive call centers, where we want to go in and help them with AI and automation, to help better listen to their customers, help better listen to the customers voice, and solve the problems in a faster manner. >> So I don't have to repeat my account number six different times to six different agents. >> Exactly, right. >> Or caught an in IVR cycle, or perhaps the chat that you were talking to doesn't-- The person on the phone, you have to repeat your story. This is something where the AI and automation will actually assist the agent to become a superhero. >> So, it's pretty interesting cause you know there's a lot of conversation about AI and ML, but really you know where it's going to have its impact is applied AI. >> Yes. And you said the company started out really more just on a pure voice, but now you're applying more and more kind of AI in the back end. So what kind of opportunities do you have now beyond just simply being able to do voice conversion?. >> To the first part of your question, the company started at IIT Madras back in 2008. And originally the focus of the company was really centered on voice, voice being the lowest common denominator and in Indie where the languages are 260 you know, potential languages to understand and maybe 25 at the top. We set out really to focus on voice and then realize that customer service was a large market and somewhere we can have a big impact. >> Right, right. So you reckon as you said a 100 different languages. >> A 100 different languages through our platform which is pretty incredible when you think about it. All of the different people calling in to customer service potentially or maybe through a chatbot or a voicebot to get their issues solved. >> And then you integrate in whatever the core system is that the customer services agent are using. >> Yes. >> So what are the types of tips and tricks that the call agent gets by using your guys service? >> So think about it as a platform where the customer can help they agents be more affective agents. So one of the things that call centers struggle with is something called after call work, where agents may spend two to three minutes after a call, summarizing the call. One of the things that our technology does and this is primarily for one of our customers who's a health care client. They said "Wouldn't it be great if we can automate that completely". So we've taken the after call work for one customer client, taken that two to three minutes down to 10 seconds, where that work that the agent would have done is completely summarized and the agent validates it, can correct it if needed and its completely done. So that not only saves the agent time to either pick up more calls and help other customers or it can get them of the phone in a quicker manner to save the call center more money. >> So that's doing more than just simply providing a transcript of the call which is something a different track than actually listening into to provide suggestions is actually taking it to the next level in terms of what categorizing, what type of call, the outcome etc. >> it's actually quite interesting because often times less than 1% of calls are listened to somewhere between 1 and 10% of calls are listened to in calls centers. So we can listen to a 100% of those calls in addition we offer something called that's more along the line of like a live agent coach to where the agent can concentrate on the conversation with the customer which is the primary thing listening to the customer. And our technology will serve you up coaching mechanism in terms of getting to faster resolution for the customer and getting them better insights to be almost a superhero of a agent. >> Right, and I would imagine the accuracy in terms of recording what happened in the call to go back and do the analytics and have a text base search you can do all types of analysis on those calls which was data that was probably just lost before right into (mumbles) >> You're exactly right. I think the accuracy is clearly a lot lower than if you were to have the AI and automation and Machine learning technology there. >> So the other conversation in the sit down that we had earlier today was really about driving a customer centric culture in your own company, not only just enabling it but really building it inside. I wonder if you could share some of the things that you guys have done to help make sure that everybody stays focused on the objective, which is the customer. >> Yip, I think it really starts at the top it starts with the leader of the organization. So we have a CEO whose extremely focused on customer centricity and in fact its our number one core value within the organization. So you see everyone from the CEO down to the rest of the organization completely focused on the customer and their needs. >> What about when the customer doesn't know what they need? What about you know, you bringing a new technology and your inviting a slightly different process or a slightly different change and your saying "Hey, this is actually a better way to keep text and transactions and we actually have a really coach that can help", you know, kind of guy to people. How do you help move customers to a place they don't necessarily know they want to go? >> Yeah, I mean you find that a lot, right. Its not necessarily the technology that we're providing for today but its having the innovation and having the foresight to create a platform that will be future proof. So that's critical, you know, I think that there are a lot of customers who might not know what they need today but that's our job to help them innovate and push the envelope on all things AI and automation. >> Right, I'm just curious to in terms of the impact of your technology on kind of the tracking software for those call center agents, right. So this is a group of people that have to process a lot of calls, you know everything is track to the minute and you know its funny I had a demo with Westworld and you know when Westworld's funny cause we started treating machines like machines and they wanted to be treated like people sometimes I wonder on some of these technologies You know is it enabling them to have more time to be more thoughtful, is it enabling them to have more time to get the better outcomes or is it sometimes perceived as 'oh my gosh you just trying to jam' you know, 'four more calls on in my hour by taking care of my two more minutes that I used to spend wrapping up the call". Do you think about those things and the end customer? >> The time is really the premium, right. So the number one focus is giving people time back and whether that's the customer who's calling in and you want to solve an issue and get them faster resolution or whether that's the agent that wants to free up more time in having the conversation with the customer, solving their problem and then getting of the phone I think that's the most effective way of doing it. >> Final question in terms of voice and the evolution of voice. `Cause I don't think people are really completely tuned in certainly not people old like we are. What are some of the conversations when people finally get, you know, kind of the enabler that voice communications opens up that's not necessarily available with texts or not necessarily available with other types of channels? >> Yeah, I mean I see it most easily in my children they expect everything to be voice enabled and so everything from the Comcast remote that they pick up in our living room everywhere they go when they see a remote they expect everything to be voice enabled. So that's really the future and I think a lot of customer service will be listening to your customers voice however, they want to communicate with you, whatever channel they want to communicate on. >> Great, really cool story Annie and thanks for taking the few minutes and sharing it with us. >> Yeah, thanks for inviting me. >> All right, she's Annie, I'm Jeff your watching theCube with the Comcast CX Experience Innovation day here at the Sillicon Valley Innovation Center. Thanks for watching see you next time.

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation >> run. Welcome to this cube conversation here in Palo Alto, California. I have remote. Sarah Varney is the chief marketing officer Tulio Company. We've covered for many, many years one of the most successful A p I now public company. Um, Sarah, welcome to the Cube competition. Good to see you remotely. You're in San Francisco? Were in Palo Alto. Um, thanks for coming on. >> Yeah, thanks so much for having me. >> So you guys have been really a powerhouse company? Twilio. We've been following the rise and success. It just seems just success that the success of success go public stock keeps growing. Big acquisition would send grid for $2,000,000,000 in October. We covered that, but really kind of reading the tea leaves and connecting the dots. It's really the continued evolution of Cloud sas, where AP eyes are becoming Maur and Maur the lingua franca for the next generation way. That's coming, but is going into a whole nother direction. You guys are a big part of that. You're the chief marketing officer. It's >> a hard >> story to tell because it's it's kind of under the hood nerdy, but it's also really big business benefits. So as the c m o. How do you get your arms around that you've been in the business for a while? Take him in to explain the strategy around how you're handling. That's Willie. Oh, Marketing. >> Sure, Yeah. I mean, I do. I agree that, uh, you know, Tulio is >> very much an ingredient brand, but at the same time, everyone is interacting with with in some cheaper form, probably every day, whether or not they realize it or not. If you're getting an appointment reminder from your >> dentist's confirming an appointment, that's probably Tulio behind the scenes, >> if you are communicating with your uber driver to say that you are headed outside that is normally powered by Coolio technology. So even though it might be, ah, technology that exists lower in the stack and something you might not physically see, it is very much something that people everywhere getting every day and you know our goal really is to Leo is to make sure that we're helping companies across the globe from all different types of industries, of all shapes and sizes. to bridge the communication gap with their customers. You know, every day there's a new channel to keep up to speed with. There's a new way that people are customers that are demanding Thio be communicated with. And we want companies to be out in front of that s O that you know, they can connect with their customers on any channel, if that's what's up. If that's SMS. If that's voice, if that's even fax, we want to make that ah possibility. >> I love the Positioning Cloud Communications Company. That's kind of what you guys Air Corps, because you're bringing it all together. And I think you know, the mobile Revolution, starting with the iPhone and 2007. You look at that as a seminal moment and you say OK, mobile device. It's a phone, It's a computer. It's got applications on it. This is a device that's unique to the rest of the infrastructure, but developers and your programming on it, and those things all integrate together. That's where a lot of people kind of saw that for the first time. Then you add cloud to it. Amazon, Microsoft and Google, the top three Amazon dominating really kind of brings a P. I focus even more to make these service's. These Web service is go to a whole nother level on dhe. That's the big wave that we're seeing. I'd >> love to get >> your thoughts and you worked at salesforce dot com, which really pioneered sass. And they were the first real cloud company before you started to see Amazon really cloud infrastructure to service. So Platforms asserts and suffers of service evolve. You were there early. You had a lot of experience working with AP Exchange APP stores early on its sales force. How does that compare to now? What is the trajectory and how does it all connect? >> Yeah, I mean, I think that when I, you know my joke is always that when I started on the APP exchange, its sales force, the Apple App store didn't even exist. So the explosion of mobile devices was just we weren't even. We weren't even there quite yet, and I was working with Iess V's Thio to help them. I think about how they could launch big businesses in the cloud on, I think at that point people were were rotating hard away from the world of on premise, which required a ton of investment of a hardware perspective and service's perspective, and in the process of that, rotated very almost overcorrected towards package solutions. And I think over the last few years what we've seen and something that Tulio is definitely behind and you could see in the vision of our product roadmap he's coming back to the middle, where you have the benefits of the cloud, the speed, the ability to stand something out very quickly. But you also have unlimited customization ability, and you can really put that Theobald ity to build palette for applications that bring the best of different solutions in different applications through a p. I's in the hands of of your developers. Sorry. Go ahead. >> I think that's a great point. I want to just double down on that for a second and ask you how you guys are seeing the developer traction on this because one of the core things that were been reporting over the past couple years this year in particular is the rise of things like Kubernetes Cloud native, where developers now have a seamless way to program the infrastructure, the hard stuff. So you're seeing a faster development cycle for those application developers. Is that where the customization piece comes in? Is that where you guys see that connection point? And what does that mean for customers? >> Yeah, I mean, I think that's part of it. But at a higher level, we really want to empower developers. You create a custom connected journey across >> all different parts of how our customers interacting with the brand. You know, >> if you think about I. I had a recent incident with an airline that will remain nameless, but I I left my laptop on a plane in to get that laptop back. Took multiple calls. Thio the customer service desk. I was bounced around to a bunch of different people. The tracking of that computer was a near impossible. At one point, it traveled from New Jersey, Thio Ireland. You know, there was just so many different points of that journey where there was disconnection and I began to lose trust in this the ability of this customer service department, uh, you know, this This company had an A P I based approach. They could bring all of the data from these different systems from there. >> Your pee from their serum, you know, from their shipping vendor all in one place. And I wouldn't have had that that experience with that particular airline. >> So if you see a P Eyes is a data connector model, really, connecting data sets together fast and easy. >> Ideo. I think it's a way I think developers love working in AP eyes because they can bring all the they can pick the best of breed solutions and bring over that data into one customer united customer experience so that your customer doesn't have >> to do that heavy lifting. It's all there for them. >> You know, one of the things you see from companies like Salesforce pioneering the early days of Assassin Cloud. I mean, even Andy jassy it Amazon many times, and he always uses the expression that they use the Amazon cold you got. You have to be misunderstood for a long time. If you want to be a leader in an emerging Newmarket. You guys that twilio kind of have done that and continue to surpass expectations because you've been kind of skating to where the puck is now, which is the cloud Native Wave. Third party applications, Coyote security all kind of come together for developers. So as a company that's been different and been disruptive as the c m o. >> How do you >> take that? Uh, that that vision in Montreat the next level as you market the solution because you are kind of different. You are not new per se, but you're a new way to create value for customers. How do you go out and tell that story with some of the marketing things that you do? Um, take that twilio to the next level. >> I mean, I personally, in >> my experience, I think, uh, the easiest marking jobs are the ones where you have amazing customer stories and there is no shortage of amazing innovation and our customer base on. And, you know, I think if you think about the companies that are making the news, if that's lift, if that's, you know, cos like Airbnb, they're not. If you think about their business, they're not inventing something. Brando. The Hoover didn't invent the taxi, uh, air being beaten and then a hotel room. But they invented a new way to consume their product to communicate around their product. And, you know, I think it's very easy to show the power of Tulio and how we've evolved through some of these these customer stories. And it's not just the kind of Silicon Valley fast growing, you know, start ups that we're all familiar with here, just just living and being located in the region. But, you know, we're starting to see this more and more in the enterprise as well. Ah, and people really hardest in communication to make sure that that they themselves are not disrupted. >> Yeah, of course. We love that. The enterprise high we've been doing for 10 years now. Everyone talks enterprise because the confidence of consumer ization of I t. Is happening. It's the lines are blurring. Share some customers successors because I think this is a great, great example of just great marketing that the customers do the talking for you. You always got to do this thing. You know the standard operational things and have some a text back and all that good stuff. But at the end of the day, when you have your customer sharing their success, that's really the ultimate testimonial. So share some cool examples of notable customers, if you can. >> Yeah, well, look I mean, we have a wide range, I'll tell you. Three Medtronic, one of the largest medical device companies in the world. They provide a solution for Type one diabetes. They provide a pump that is constantly monitoring the glucose levels in someone's blood. What they've done with Julio's. Now they're layering on messaging capability. So if someone's glucose levels all to a level that's unsafe, they could be messaged. And you know, this is not just for the patient. But if you think of a young child who suffers from Type one diabetes, this could be a very stressful situation for their parents and their caregiving team. And now that team can constantly be in the loop, and they don't have to worry if they are at work and wondering, you know how they're chai that was doing at school. Or, you know, if they're on the soccer field and concerned about you know how, uh, their condition could be affected by them. Participating in that sport s so completely different from your more, um uh, straight down the middle startup that we see here in the Valley. >> So basically, messaging is to keep value. It's not so much a tech thing. It's more of a the outcome. It's a critical service piece toe. Have those kind of real time communications? >> Yes, absolutely. Because, I mean, if you think about >> it monitoring your your, uh, glucose levels, that's not a new phenomenon. People have been doing that for years, but layering on communications on top of this has brought a real time element Thio monitoring this, uh, this condition and has liberated people with this condition so that, you know, they can get back to the things that they've always going to do without having to worry about. You know, the state of their health. It's gone. >> It's like infrastructure is code for devil up you guys air for communications. You make it easy to do that for things like that. Talk about the impact of scale over the years because now you know, we're seeing the data tsunami happen Every day I ot devices air coming on. Everything's got. Ah, a sensor on it. You got doorbells. You got everything out there now has got an I P address and connected in that could potentially be a messaging unit of of data. This is just getting massive. How you guys see scale? And how do you guys getting around the next wave on that piece? >> Yeah. I mean, I think one of the >> huge benefits in working with polio is our super network. So we're constantly maintaining relationships with all the key carriers across the globe to make sure that we can get deliver our to our customers the best routes. And so that means also that they can stand up business virtually anywhere across the globe, a cz, their entry in new markets and coyote. This is especially true for anyone who is in the eye ot space. If you think about the dock Ellis category, companies like lime, uh, who are, you know, delivering rental bike service is where and you know, a market where market share just grabbing as much market share is possible. It seems to be the name of the game. They're able to partner with Julio in bed sim cards and all of their bicycles, and now be able to you track all of those all of those bicycles across the globe as well as scooters. Ah, and then take that information, uh, figure out how customers are engaging with their product and ultimately build a better solution. Long term, >> real time messaging will never go away as values. I see just like data. So it's gonna get faster and larger amounts of messaging making sense of it. Do. The heavy lifting is great story. You guys done a great job. Thanks for coming on and sharing your perspective. Get the plug in for twilio real quick. What's new with the company employees out? See the public companies? You really can't talk about futures, but what's on your plate? What's on the horizon for Tulio? What's the update? >> Yeah, I mean, the company is >> growing extremely quickly. We're really excited about the context, but center market especially. We launched our flex contact center Solution, uh, was made generally available just this past October. On a CZ you've mentioned we're super excited to welcome sing grid into the family of products you know, really, round out our full set communication in the eyes of people communicate with their customers in any way possible. And I would be, uh, it would be a crime for me, not to mention our user conference coming up this August August 6th and seventh at Mosconi West and that's called Signal s O. I highly encourage you to attend. It's a great opportunity to hear from experts in the communications space and also our customers. >> Well, we love the name signal. Extracting the signal from the noise was our original kind of tag line. Really appreciate it. And with all those customers, must be a hard challenge to have a cup conference, doing the keynote selections and figuring out what to do. What you're gonna have breakout sessions. Just get a little more detail on the event. You're gonna see the stage and customer story's going to break out sections. What's the format for the event? >> Yeah, so it's It's a two day, um, session. At most witty West. We have a number of breakouts. We have hands on training, which we call super class. We have, uh, keynotes. Last year we had an interactive performance with the band. OK, go. Uh, we had the creators of Westworld onstage. Geoff Lawson, our CEO, always kicked the Hoff ER, and it's just a great, exciting two days on, and we also this year, given that were hosting it during the summer time frame, we have ah camp experience for your children. And if you're looking to combine it with a summer vacation so we're super excited about signal, it's, uh, it's, Ah, two of my favorite days of the year from, Ah, Giulio perspective. And I'd love for everyone to come join us. >> We got a great customer success over the years, and great names congratulate Sarah. Thanks for been the time here in the Cube. I'm John Furry here in Palo Alto. Ceremony the chief marketing officer with Julio in San Francisco via remote. Thanks for watching this cute conversation.

>> [Narrator] Live from Los Angeles, it's The Cube, covering E3 2018. Brought to you by SiliconANGLE Media. >> Hey, welcome back, everybody. Jeff Frick here with The Cube. We're actually in the Warner Brothers games booth. This humongous booth, we're kind of in the inner sanctum here at E3 in the LA Convention Center. Lot of stuff going on with Warner Brother Games. A lot of really cool combinations of brands and games and movies. But this is a very special one, Hitman 2. We're all excited to be here and learn more about it with Jacob Mikkelsen. He's actually the game director for IO Interactive. Jacob, great to see you. >> Oh, thank you. >> So let's just get to the basics. First off, when is Hitman 2 coming out? What do people need to know, we'll get that out of the way, and then we'll get into it. >> Hitman 2 is out November 13. And if you pre-order now, you have a special pre-order bonus where you get access to a new game mode called Sniper Assassin, which is a sniper-only mission. And then for the first time in Hitman history, we also have a co-op mode where you can snipe alongside a friend, into the mission and create all sorts of havoc. It's still deeply founded in the roots of the game's DNA, where it's all about getting away with the sniping without anyone noticing that you're there. So it has a very, very strong puzzle element to it. So it's about peeling off the layers of an onion, without anyone noticing you're there. >> So you talked a little bit before we turned on the cameras about the freedom that a player gets, not like in a traditional game, where they can can choose a lot of different options of how they're gonna do the mission. So how do you guys come up with that? How is that all determined? And how do you actually still keep the game true to the mission? >> Well, the thing is that as you say, it's very much, we call that hyper-detailed sandbox. So when you play a Hitman mission, we don't give you a linear path through the level that you follow. We give you an open sandbox where you have to figure out how do you want to approach this mission. And in the case of the mission we're showing here at E3, it's a race event in Miami. And your target is one of the race drivers, actually. That's our half of the mission. And she's roaming around the track. So the whole thing in the demo today is like, "Okay, so how do you get close to Sierra's car?" And then in order to do that, then you need to obtain disguises, which is a key element in the Hitman franchise, that you can disguise as the characters you meet in the scene. So you can knock them out and become, take their uniforms on, and then infiltrate the areas. Some guards are more suspicious of you than others, so you have to mingle your way through the level. So it's very much up to you if you want to sneak in and try not to do the disguise stuff, or you can go for the disguise stuff and then make your way. And then the game adapts, in a way, because we have to foresee all these different permutations of play. So there's a lot of things you can do in the game, in terms of which way you take and how you get there. >> So I'm just curious from a game development point of view, in terms of building in difficulty, 'cause you want to have enough difficulties that it's a challenge and people feel satisfaction in rising to the challenge, but clearly you could make it so they just got wiped out every time. You could make it an impossible game. So how do you find that balance? How do you tune that balance? What are some of the things you think about when you're trying to get in degree of difficulty? >> Well, that's a really, how difficult should it be, that's a really hard question to answer in a Hitman game, because of the many ways that the players can do it. So we have an initial idea about where we want to challenge the players and where we want to give them a bit more leash where they can just roam around. But once you get a new disguise, then it's a different scenario. And we have to account for that in our design. So we do a lot of iterations on this. Okay, so if I went to the right and went this way in through the level but there was no resistance, I didn't have to do anything, I could just walk straight in the main door, then we have to go back to the drawing board and then jiggle around the characters, maybe add some new ones, remove some, and change the amount of guards, so the player will have challenges no matter how they approach it. But in the end, the crazy thing is, no matter how hard we make it or how challenging we make it, they will always find crazy ways of bypassing the systems and bending the rules of the game so much. And that's what makes Hitman great, is that you can do all of these things. Just, okay, can I do this? Yes, and you go and try it, and maybe it worked out, maybe it was not a good idea in the end. But it's very much up to you, as the player, to figure out how you want to be creative in this. >> So we're doing this series as part of the Western Digital data makes possible. And data is such a bit part of what you guys do. And really, as gaming has moved off of the pure console into the connected world, gives you an opportunity as a developer to see really, how are people interacting with the game? How are they making decisions? So how did you guys look at the analytics? You must be doing more and more and more analytics on all these various movements and potential options that they have. >> We have systems in place to figure out where people get spotted, so we can actually see that. The tricky part about metrics is that during development, there's actually not that many people playing the game besides ourselves. So we rely heavily on user testing, where we subdue people to the, we place people in front of the game in very early stages, to see if our core ideas are working. And then based on that, we then look at video footage, interviews, and all that stuff. That feeds back into the design loop of the process. >> And have you mapped every potential option, or are you using AI? You just used the example, some guy's too smart, we really need to have more guards for this guy. Is there AI and intelligence in the game that you can make little fine-tuned adjustments along the path as people actually play the game? 'Cause you're gonna have a whole lot more data by December first than you have today. >> Precisely, the amount of data we get is pretty wild in the end. But the core of the game, the characters are AI-driven. They have their own plans that they want to do. And the way it works is that we then build stories on top of this core AI. So the designers, they have freedom to create custom moments. But at some point when things go in the fence for the player, you get spotted or someone sees through your disguise, then the AI takes over. And I dare to say that we have some of the most complex AI systems in the industry. We go to great lengths to have them be very living and communicating a lot. So if one guy finds a body, then it's one situation. If he has a friend, then they begin to talk about what they've just experienced. And they work together to figure out what is actually going on. So there's a very high level of AI running behind the scenes in the Hitman game. >> Now, do you do that at the level of the characters? So it's really how a character responds to different stimuli-- >> Yes. >> Versus just a generic overlay for the whole game? >> Well, it's a mix. Some of them are different kinds of characters, guards or civilians, and they have different behaviors, based on what happens. But each character is more or less himself. And then he is not hive-mind controlled. It is a lot of agents that are running around in the world, trying to figure out what this player's up to, creating havoc behind the scenes. So it's a lot of fun to work with it, because it's also so unpredictable. And then all of a sudden, something happens that you didn't expect. >> Right, 'cause you can't possibly scenario every potential outcome, right? >> Exactly, we have some control, but it's systemically based. So we kind of, the way we normally say it is, we encourage the characters to do things. And then they might do it. For instance, you and I having an interview right now, that requires that you're standing in your spot and I'm standing in my spot. If I were to create that scene in the game, then there is a certain chance that one of us is lying in a dumpster somewhere and never shows up for the interview. And then the next question is, okay, so what do you do? So we have to construct the game in a way so that you won't break down and stop here. I don't know if you remember in season one of Westworld, if you've seen that? >> I have seen season one. I haven't caught up on season two yet, but yeah, season one. >> I haven't seen season two yet. But in season one, there's this scene where there's a bonfire scene that breaks down, where all the characters just stop. And then it turns out that the guy who went for firewood has been killed. So he never returned with the firewood, and thereby, the entire bonfire scene just grinds to a halt. >> [Jeff] Just freezes. >> That is Hitman gave development in a nutshell. Then we have a bug when that thing happens. And that can happen during development, we do that stuff. >> It's gotta be so cool, to discover how people actually work their way through the game. >> Absolutely. >> 'Cause the other thing I think it's interesting that you guys always have to balance is you have narrative, you want to have a narrative. You have a story, you have characters, and a look and feel. At the same time, you have individual operators, the players, that bring in their own point of view to the game. So how do you balance? When does one take priority to the other? How do you keep it on that narrative flow? >> It's been one of these returning challenges of making a Hitman game. And with the previous game, we narrowed in on, okay, so how do we do this? So we have a main story that is told outside the levels, which the levels don't directly affect. So the overall main arc and storyline is set. But what happens in the levels stays in the levels, so to speak. So in season one, we actually managed to go through the main story with some characters left alive, which is good. Because now in the second, in Hitman 2, we're going to get closer to them. And the story evolves around Agent 47, and we get a glimpse into his past, which is a bit of some things we haven't told yet. So that's going to be very exciting to see that, as well. >> Right, well Jacob, thanks for spending a few minutes. And good luck with the launch, congrats on the new product. >> Thank you very much, nice talking to you. >> He's Jacob, I'm Jeff, you're watching The Cube. We're in the Warner Brothers games booth at E3, LA Convention Center. Thanks for watching. (upbeat electronic music)