(upbeat music) >> Hello, everybody. This is Dave Vellante. Welcome back to Supercloud2, where we're exploring the intersection of data analytics and the future of cloud. In this segment, we're going to look at how the Supercloud will support a new class of applications, not just work that runs on multiple clouds, but rather a new breed of apps that can orchestrate things in the real world. Think Uber for many types of businesses. These applications, they're not about codifying forms or business processes. They're about orchestrating people, places, and things in a business ecosystem. And I'm pleased to welcome my colleague and friend, George Gilbert, former Gartner Analyst, Wiki Bond market analyst, former equities analyst as my co-host. And we're thrilled to have Tristan Handy, who's the founder and CEO of DBT Labs and Bob Muglia, who's the former President of Microsoft's Enterprise business and former CEO of Snowflake. Welcome all, gentlemen. Thank you for coming on the program. >> Good to be here. >> Thanks for having us. >> Hey, look, I'm going to start actually with the SuperCloud because both Tristan and Bob, you've read the definition. Thank you for doing that. And Bob, you have some really good input, some thoughts on maybe some of the drawbacks and how we can advance this. So what are your thoughts in reading that definition around SuperCloud? >> Well, I thought first of all that you did a very good job of laying out all of the characteristics of it and helping to define it overall. But I do think it can be tightened a bit, and I think it's helpful to do it in as short a way as possible. And so in the last day I've spent a little time thinking about how to take it and write a crisp definition. And here's my go at it. This is one day old, so gimme a break if it's going to change. And of course we have to follow the industry, and so that, and whatever the industry decides, but let's give this a try. So in the way I think you're defining it, what I would say is a SuperCloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. >> Boom. Nice. Okay, great. I'm going to go back and read the script on that one and tighten that up a bit. Thank you for spending the time thinking about that. Tristan, would you add anything to that or what are your thoughts on the whole SuperCloud concept? >> So as I read through this, I fully realize that we need a word for this thing because I have experienced the inability to talk about it as well. But for many of us who have been living in the Confluence, Snowflake, you know, this world of like new infrastructure, this seems fairly uncontroversial. Like I read through this, and I'm just like, yeah, this is like the world I've been living in for years now. And I noticed that you called out Snowflake for being an example of this, but I think that there are like many folks, myself included, for whom this world like fully exists today. >> Yeah, I think that's a fair, I dunno if it's criticism, but people observe, well, what's the big deal here? It's just kind of what we're living in today. It reminds me of, you know, Tim Burns Lee saying, well, this is what the internet was supposed to be. It was supposed to be Web 2.0, so maybe this is what multi-cloud was supposed to be. Let's turn our attention to apps. Bob first and then go to Tristan. Bob, what are data apps to you? When people talk about data products, is that what they mean? Are we talking about something more, different? What are data apps to you? >> Well, to understand data apps, it's useful to contrast them to something, and I just use the simple term people apps. I know that's a little bit awkward, but it's clear. And almost everything we work with, almost every application that we're familiar with, be it email or Salesforce or any consumer app, those are applications that are targeted at responding to people. You know, in contrast, a data application reacts to changes in data and uses some set of analytic services to autonomously take action. So where applications that we're familiar with respond to people, data apps respond to changes in data. And they both do something, but they do it for different reasons. >> Got it. You know, George, you and I were talking about, you know, it comes back to SuperCloud, broad definition, narrow definition. Tristan, how do you see it? Do you see it the same way? Do you have a different take on data apps? >> Oh, geez. This is like a conversation that I don't know has an end. It's like been, I write a substack, and there's like this little community of people who all write substack. We argue with each other about these kinds of things. Like, you know, as many different takes on this question as you can find, but the way that I think about it is that data products are atomic units of functionality that are fundamentally data driven in nature. So a data product can be as simple as an interactive dashboard that is like actually had design thinking put into it and serves a particular user group and has like actually gone through kind of a product development life cycle. And then a data app or data application is a kind of cohesive end-to-end experience that often encompasses like many different data products. So from my perspective there, this is very, very related to the way that these things are produced, the kinds of experiences that they're provided, that like data innovates every product that we've been building in, you know, software engineering for, you know, as long as there have been computers. >> You know, Jamak Dagani oftentimes uses the, you know, she doesn't name Spotify, but I think it's Spotify as that kind of example she uses. But I wonder if we can maybe try to take some examples. If you take, like George, if you take a CRM system today, you're inputting leads, you got opportunities, it's driven by humans, they're really inputting the data, and then you got this system that kind of orchestrates the business process, like runs a forecast. But in this data driven future, are we talking about the app itself pulling data in and automatically looking at data from the transaction systems, the call center, the supply chain and then actually building a plan? George, is that how you see it? >> I go back to the example of Uber, may not be the most sophisticated data app that we build now, but it was like one of the first where you do have users interacting with their devices as riders trying to call a car or driver. But the app then looks at the location of all the drivers in proximity, and it matches a driver to a rider. It calculates an ETA to the rider. It calculates an ETA then to the destination, and it calculates a price. Those are all activities that are done sort of autonomously that don't require a human to type something into a form. The application is using changes in data to calculate an analytic product and then to operationalize that, to assign the driver to, you know, calculate a price. Those are, that's an example of what I would think of as a data app. And my question then I guess for Tristan is if we don't have all the pieces in place for sort of mainstream companies to build those sorts of apps easily yet, like how would we get started? What's the role of a semantic layer in making that easier for mainstream companies to build? And how do we get started, you know, say with metrics? How does that, how does that take us down that path? >> So what we've seen in the past, I dunno, decade or so, is that one of the most successful business models in infrastructure is taking hard things and rolling 'em up behind APIs. You take messaging, you take payments, and you all of a sudden increase the capability of kind of your median application developer. And you say, you know, previously you were spending all your time being focused on how do you accept credit cards, how do you send SMS payments, and now you can focus on your business logic, and just create the thing. One of, interestingly, one of the things that we still don't know how to API-ify is concepts that live inside of your data warehouse, inside of your data lake. These are core concepts that, you know, you would imagine that the business would be able to create applications around very easily, but in fact that's not the case. It's actually quite challenging to, and involves a lot of data engineering pipeline and all this work to make these available. And so if you really want to make it very easy to create some of these data experiences for users, you need to have an ability to describe these metrics and then to turn them into APIs to make them accessible to application developers who have literally no idea how they're calculated behind the scenes, and they don't need to. >> So how rich can that API layer grow if you start with metric definitions that you've defined? And DBT has, you know, the metric, the dimensions, the time grain, things like that, that's a well scoped sort of API that people can work within. How much can you extend that to say non-calculated business rules or governance information like data reliability rules, things like that, or even, you know, features for an AIML feature store. In other words, it starts, you started pragmatically, but how far can you grow? >> Bob is waiting with bated breath to answer this question. I'm, just really quickly, I think that we as a company and DBT as a product tend to be very pragmatic. We try to release the simplest possible version of a thing, get it out there, and see if people use it. But the idea that, the concept of a metric is really just a first landing pad. The really, there is a physical manifestation of the data and then there's a logical manifestation of the data. And what we're trying to do here is make it very easy to access the logical manifestation of the data, and metric is a way to look at that. Maybe an entity, a customer, a user is another way to look at that. And I'm sure that there will be more kind of logical structures as well. >> So, Bob, chime in on this. You know, what's your thoughts on the right architecture behind this, and how do we get there? >> Yeah, well first of all, I think one of the ways we get there is by what companies like DBT Labs and Tristan is doing, which is incrementally taking and building on the modern data stack and extending that to add a semantic layer that describes the data. Now the way I tend to think about this is a fairly major shift in the way we think about writing applications, which is today a code first approach to moving to a world that is model driven. And I think that's what the big change will be is that where today we think about data, we think about writing code, and we use that to produce APIs as Tristan said, which encapsulates those things together in some form of services that are useful for organizations. And that idea of that encapsulation is never going to go away. It's very, that concept of an API is incredibly useful and will exist well into the future. But what I think will happen is that in the next 10 years, we're going to move to a world where organizations are defining models first of their data, but then ultimately of their business process, their entire business process. Now the concept of a model driven world is a very old concept. I mean, I first started thinking about this and playing around with some early model driven tools, probably before Tristan was born in the early 1980s. And those tools didn't work because the semantics associated with executing the model were too complex to be written in anything other than a procedural language. We're now reaching a time where that is changing, and you see it everywhere. You see it first of all in the world of machine learning and machine learning models, which are taking over more and more of what applications are doing. And I think that's an incredibly important step. And learned models are an important part of what people will do. But if you look at the world today, I will claim that we've always been modeling. Modeling has existed in computers since there have been integrated circuits and any form of computers. But what we do is what I would call implicit modeling, which means that it's the model is written on a whiteboard. It's in a bunch of Slack messages. It's on a set of napkins in conversations that happen and during Zoom. That's where the model gets defined today. It's implicit. There is one in the system. It is hard coded inside application logic that exists across many applications with humans being the glue that connects those models together. And really there is no central place you can go to understand the full attributes of the business, all of the business rules, all of the business logic, the business data. That's going to change in the next 10 years. And we'll start to have a world where we can define models about what we're doing. Now in the short run, the most important models to build are data models and to describe all of the attributes of the data and their relationships. And that's work that DBT Labs is doing. A number of other companies are doing that. We're taking steps along that way with catalogs. People are trying to build more complete ontologies associated with that. The underlying infrastructure is still super, super nascent. But what I think we'll see is this infrastructure that exists today that's building learned models in the form of machine learning programs. You know, some of these incredible machine learning programs in foundation models like GPT and DALL-E and all of the things that are happening in these global scale models, but also all of that needs to get applied to the domains that are appropriate for a business. And I think we'll see the infrastructure developing for that, that can take this concept of learned models and put it together with more explicitly defined models. And this is where the concept of knowledge graphs come in and then the technology that underlies that to actually implement and execute that, which I believe are relational knowledge graphs. >> Oh, oh wow. There's a lot to unpack there. So let me ask the Colombo question, Tristan, we've been making fun of your youth. We're just, we're just jealous. Colombo, I'll explain it offline maybe. >> I watch Colombo. >> Okay. All right, good. So but today if you think about the application stack and the data stack, which is largely an analytics pipeline. They're separate. Do they, those worlds, do they have to come together in order to achieve Bob's vision? When I talk to practitioners about that, they're like, well, I don't want to complexify the application stack cause the data stack today is so, you know, hard to manage. But but do those worlds have to come together? And you know, through that model, I guess abstraction or translation that Bob was just describing, how do you guys think about that? Who wants to take that? >> I think it's inevitable that data and AI are going to become closer together? I think that the infrastructure there has been moving in that direction for a long time. Whether you want to use the Lakehouse portmanteau or not. There's also, there's a next generation of data tech that is still in the like early stage of being developed. There's a company that I love that is essentially Cross Cloud Lambda, and it's just a wonderful abstraction for computing. So I think that, you know, people have been predicting that these worlds are going to come together for awhile. A16Z wrote a great post on this back in I think 2020, predicting this, and I've been predicting this since since 2020. But what's not clear is the timeline, but I think that this is still just as inevitable as it's been. >> Who's that that does Cross Cloud? >> Let me follow up on. >> Who's that, Tristan, that does Cross Cloud Lambda? Can you name names? >> Oh, they're called Modal Labs. >> Modal Labs, yeah, of course. All right, go ahead, George. >> Let me ask about this vision of trying to put the semantics or the code that represents the business with the data. It gets us to a world that's sort of more data centric, where data's not locked inside or behind the APIs of different applications so that we don't have silos. But at the same time, Bob, I've heard you talk about building the semantics gradually on top of, into a knowledge graph that maybe grows out of a data catalog. And the vision of getting to that point, essentially the enterprise's metadata and then the semantics you're going to add onto it are really stored in something that's separate from the underlying operational and analytic data. So at the same time then why couldn't we gradually build semantics beyond the metric definitions that DBT has today? In other words, you build more and more of the semantics in some layer that DBT defines and that sits above the data management layer, but any requests for data have to go through the DBT layer. Is that a workable alternative? Or where, what type of limitations would you face? >> Well, I think that it is the way the world will evolve is to start with the modern data stack and, you know, which is operational applications going through a data pipeline into some form of data lake, data warehouse, the Lakehouse, whatever you want to call it. And then, you know, this wide variety of analytics services that are built together. To the point that Tristan made about machine learning and data coming together, you see that in every major data cloud provider. Snowflake certainly now supports Python and Java. Databricks is of course building their data warehouse. Certainly Google, Microsoft and Amazon are doing very, very similar things in terms of building complete solutions that bring together an analytics stack that typically supports languages like Python together with the data stack and the data warehouse. I mean, all of those things are going to evolve, and they're not going to go away because that infrastructure is relatively new. It's just being deployed by companies, and it solves the problem of working with petabytes of data if you need to work with petabytes of data, and nothing will do that for a long time. What's missing is a layer that understands and can model the semantics of all of this. And if you need to, if you want to model all, if you want to talk about all the semantics of even data, you need to think about all of the relationships. You need to think about how these things connect together. And unfortunately, there really is no platform today. None of our existing platforms are ultimately sufficient for this. It was interesting, I was just talking to a customer yesterday, you know, a large financial organization that is building out these semantic layers. They're further along than many companies are. And you know, I asked what they're building it on, and you know, it's not surprising they're using a, they're using combinations of some form of search together with, you know, textual based search together with a document oriented database. In this case it was Cosmos. And that really is kind of the state of the art right now. And yet those products were not built for this. They don't really, they can't manage the complicated relationships that are required. They can't issue the queries that are required. And so a new generation of database needs to be developed. And fortunately, you know, that is happening. The world is developing a new set of relational algorithms that will be able to work with hundreds of different relations. If you look at a SQL database like Snowflake or a big query, you know, you get tens of different joins coming together, and that query is going to take a really long time. Well, fortunately, technology is evolving, and it's possible with new join algorithms, worst case, optimal join algorithms they're called, where you can join hundreds of different relations together and run semantic queries that you simply couldn't run. Now that technology is nascent, but it's really important, and I think that will be a requirement to have this semantically reach its full potential. In the meantime, Tristan can do a lot of great things by building up on what he's got today and solve some problems that are very real. But in the long run I think we'll see a new set of databases to support these models. >> So Tristan, you got to respond to that, right? You got to, so take the example of Snowflake. We know it doesn't deal well with complex joins, but they're, they've got big aspirations. They're building an ecosystem to really solve some of these problems. Tristan, you guys are part of that ecosystem, and others, but please, your thoughts on what Bob just shared. >> Bob, I'm curious if, I would have no idea what you were talking about except that you introduced me to somebody who gave me a demo of a thing and do you not want to go there right now? >> No, I can talk about it. I mean, we can talk about it. Look, the company I've been working with is Relational AI, and they're doing this work to actually first of all work across the industry with academics and research, you know, across many, many different, over 20 different research institutions across the world to develop this new set of algorithms. They're all fully published, just like SQL, the underlying algorithms that are used by SQL databases are. If you look today, every single SQL database uses a similar set of relational algorithms underneath that. And those algorithms actually go back to system R and what IBM developed in the 1970s. We're just, there's an opportunity for us to build something new that allows you to take, for example, instead of taking data and grouping it together in tables, treat all data as individual relations, you know, a key and a set of values and then be able to perform purely relational operations on it. If you go back to what, to Codd, and what he wrote, he defined two things. He defined a relational calculus and relational algebra. And essentially SQL is a query language that is translated by the query processor into relational algebra. But however, the calculus of SQL is not even close to the full semantics of the relational mathematics. And it's possible to have systems that can do everything and that can store all of the attributes of the data model or ultimately the business model in a form that is much more natural to work with. >> So here's like my short answer to this. I think that we're dealing in different time scales. I think that there is actually a tremendous amount of work to do in the semantic layer using the kind of technology that we have on the ground today. And I think that there's, I don't know, let's say five years of like really solid work that there is to do for the entire industry, if not more. But the wonderful thing about DBT is that it's independent of what the compute substrate is beneath it. And so if we develop new platforms, new capabilities to describe semantic models in more fine grain detail, more procedural, then we're going to support that too. And so I'm excited about all of it. >> Yeah, so interpreting that short answer, you're basically saying, cause Bob was just kind of pointing to you as incremental, but you're saying, yeah, okay, we're applying it for incremental use cases today, but we can accommodate a much broader set of examples in the future. Is that correct, Tristan? >> I think you're using the word incremental as if it's not good, but I think that incremental is great. We have always been about applying incremental improvement on top of what exists today, but allowing practitioners to like use different workflows to actually make use of that technology. So yeah, yeah, we are a very incremental company. We're going to continue being that way. >> Well, I think Bob was using incremental as a pejorative. I mean, I, but to your point, a lot. >> No, I don't think so. I want to stop that. No, I don't think it's pejorative at all. I think incremental, incremental is usually the most successful path. >> Yes, of course. >> In my experience. >> We agree, we agree on that. >> Having tried many, many moonshot things in my Microsoft days, I can tell you that being incremental is a good thing. And I'm a very big believer that that's the way the world's going to go. I just think that there is a need for us to build something new and that ultimately that will be the solution. Now you can argue whether it's two years, three years, five years, or 10 years, but I'd be shocked if it didn't happen in 10 years. >> Yeah, so we all agree that incremental is less disruptive. Boom, but Tristan, you're, I think I'm inferring that you believe you have the architecture to accommodate Bob's vision, and then Bob, and I'm inferring from Bob's comments that maybe you don't think that's the case, but please. >> No, no, no. I think that, so Bob, let me put words into your mouth and you tell me if you disagree, DBT is completely useless in a world where a large scale cloud data warehouse doesn't exist. We were not able to bring the power of Python to our users until these platforms started supporting Python. Like DBT is a layer on top of large scale computing platforms. And to the extent that those platforms extend their functionality to bring more capabilities, we will also service those capabilities. >> Let me try and bridge the two. >> Yeah, yeah, so Bob, Bob, Bob, do you concur with what Tristan just said? >> Absolutely, I mean there's nothing to argue with in what Tristan just said. >> I wanted. >> And it's what he's doing. It'll continue to, I believe he'll continue to do it, and I think it's a very good thing for the industry. You know, I'm just simply saying that on top of that, I would like to provide Tristan and all of those who are following similar paths to him with a new type of database that can actually solve these problems in a much more architected way. And when I talk about Cosmos with something like Mongo or Cosmos together with Elastic, you're using Elastic as the join engine, okay. That's the purpose of it. It becomes a poor man's join engine. And I kind of go, I know there's a better answer than that. I know there is, but that's kind of where we are state of the art right now. >> George, we got to wrap it. So give us the last word here. Go ahead, George. >> Okay, I just, I think there's a way to tie together what Tristan and Bob are both talking about, and I want them to validate it, which is for five years we're going to be adding or some number of years more and more semantics to the operational and analytic data that we have, starting with metric definitions. My question is for Bob, as DBT accumulates more and more of those semantics for different enterprises, can that layer not run on top of a relational knowledge graph? And what would we lose by not having, by having the knowledge graph store sort of the joins, all the complex relationships among the data, but having the semantics in the DBT layer? >> Well, I think this, okay, I think first of all that DBT will be an environment where many of these semantics are defined. The question we're asking is how are they stored and how are they processed? And what I predict will happen is that over time, as companies like DBT begin to build more and more richness into their semantic layer, they will begin to experience challenges that customers want to run queries, they want to ask questions, they want to use this for things where the underlying infrastructure becomes an obstacle. I mean, this has happened in always in the history, right? I mean, you see major advances in computer science when the data model changes. And I think we're on the verge of a very significant change in the way data is stored and structured, or at least metadata is stored and structured. Again, I'm not saying that anytime in the next 10 years, SQL is going to go away. In fact, more SQL will be written in the future than has been written in the past. And those platforms will mature to become the engines, the slicer dicers of data. I mean that's what they are today. They're incredibly powerful at working with large amounts of data, and that infrastructure is maturing very rapidly. What is not maturing is the infrastructure to handle all of the metadata and the semantics that that requires. And that's where I say knowledge graphs are what I believe will be the solution to that. >> But Tristan, bring us home here. It sounds like, let me put pause at this, is that whatever happens in the future, we're going to leverage the vast system that has become cloud that we're talking about a supercloud, sort of where data lives irrespective of physical location. We're going to have to tap that data. It's not necessarily going to be in one place, but give us your final thoughts, please. >> 100% agree. I think that the data is going to live everywhere. It is the responsibility for both the metadata systems and the data processing engines themselves to make sure that we can join data across cloud providers, that we can join data across different physical regions and that we as practitioners are going to kind of start forgetting about details like that. And we're going to start thinking more about how we want to arrange our teams, how does the tooling that we use support our team structures? And that's when data mesh I think really starts to get very, very critical as a concept. >> Guys, great conversation. It was really awesome to have you. I can't thank you enough for spending time with us. Really appreciate it. >> Thanks a lot. >> All right. This is Dave Vellante for George Gilbert, John Furrier, and the entire Cube community. Keep it right there for more content. You're watching SuperCloud2. (upbeat music)

>> From the Cube studios in Palo Alto and Boston, bringing you data driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> While the precise direction of VMware's future is unknown, given the plan Broadcom acquisition, one thing is clear. The topic of what Broadcom plans will not be the main focus of the agenda at the upcoming VMware Explore event next week in San Francisco. We believe that despite any uncertainty, VMware will lay out for its customers what it sees as its future. And that future is multi-cloud or cross-cloud services, what we call Supercloud. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we drill into the latest survey data on VMware from ETR. And we'll share with you the next iteration of the Supercloud definition based on feedback from dozens of contributors. And we'll give you our take on what to expect next week at VMware Explorer 2022. Well, VMware is maturing. You can see it in the numbers. VMware had a solid quarter just this week, which was announced beating earnings and growing the top line by 6%. But it's clear from its financials and the ETR data that we're showing here that VMware's Halcion glory days are behind it. This chart shows the spending profile from ETR's July survey of nearly 1500 IT buyers and CIOs. The survey included 722 VMware customers with the green bars showing elevated spending momentum, ie: growth, either new or growing at more than 6%. And the red bars show lower spending, either down 6% or worse or defections. The gray bars, that's the flat spending crowd, and it really tells a story. Look, nobody's throwing away their VMware platforms. They're just not investing as rapidly as in previous years. The blue line shows net score or spending momentum and subtracts the reds from the greens. The yellow line shows market penetration or pervasiveness in the survey. So the data is pretty clear. It's steady, but it's not remarkable. Now, the timing of the acquisition, quite rightly, is quite good, I would say. Now, this next chart shows the net score and pervasiveness juxtaposed on an XY graph and breaks down the VMware portfolio in those dimensions, the product portfolio. And you can see the dominance of respondents citing VMware as the platform. They might not know exactly which services they use, but they just respond VMware. That's on the X axis. You can see it way to the right. And the spending momentum or the net score is on the Y axis. That red dotted line at 4%, that indicates elevated levels and only VMware cloud on AWS is above that line. Notably, Tanzu has jumped up significantly from previous quarters, with the rest of the portfolio showing steady, as you would expect from a maturing platform. Only carbon black is hovering in the red zone, kind of ironic given the name. We believe that VMware is going to be a major player in cross cloud services, what we refer to as Supercloud. For months, we've been refining the concept and the definition. At Supercloud '22, we had discussions with more than 30 technology and business experts, and we've gathered input from many more. Based on that feedback, here's the definition we've landed on. It's somewhat refined from our earlier definition that we published a couple weeks ago. Supercloud is an emerging computing architecture that comprises a set of services abstracted from the underlying primitives of hyperscale clouds, e.g. compute, storage, networking, security, and other native resources, to create a global system spanning more than one cloud. Supercloud is three essential properties, three deployment models, and three service models. So what are those essential elements, those properties? We've simplified the picture from our last report. We show them here. I'll review them briefly. We're not going to go super in depth here because we've covered this topic a lot. But supercloud, it runs on more than one cloud. It creates that common or identical experience across clouds. It contains a necessary capability that we call a superPaaS that acts as a cloud interpreter, and it has metadata intelligence to optimize for a specific purpose. We'll publish this definition in detail. So again, we're not going to spend a ton of time here today. Now, we've identified three deployment models for Supercloud. The first is a single instantiation, where a control plane runs on one cloud but supports interactions with multiple other clouds. An example we use is Kubernetes cluster management service that runs on one cloud but can deploy and manage clusters on other clouds. The second model is a multi-cloud, multi-region instantiation where a full stack of services is instantiated on multiple clouds and multiple cloud regions with a common interface across them. We've used cohesity as one example of this. And then a single global instance that spans multiple cloud providers. That's our snowflake example. Again, we'll publish this in detail. So we're not going to spend a ton of time here today. Finally, the service models. The feedback we've had is IaaS, PaaS, and SaaS work fine to describe the service models for Supercloud. NetApp's Cloud Volume is a good example in IaaS. VMware cloud foundation and what we expect at VMware Explore is a good PaaS example. And SAP HANA Cloud is a good example of SaaS running as a Supercloud service. That's the SAP HANA multi-cloud. So what is it that we expect from VMware Explore 2022? Well, along with what will be an exciting and speculation filled gathering of the VMware community at the Moscone Center, we believe VMware will lay out its future architectural direction. And we expect it will fit the Supercloud definition that we just described. We think VMware will show its hand on a set of cross-cloud services and will promise a common experience for users and developers alike. As we talked about at Supercloud '22, VMware kind of wants to have its cake, eat it too, and lose weight. And by that, we mean that it will not only abstract the underlying primitives of each of the individual clouds, but if developers want access to them, they will allow that and actually facilitate that. Now, we don't expect VMware to use the term Supercloud, but it will be a cross-cloud multi-cloud services model that they put forth, we think, at VMworld Explore. With IaaS comprising compute, storage, and networking, a very strong emphasis, we believe, on security, of course, a governance and a comprehensive set of data protection services. Now, very importantly, we believe Tanzu will play a leading role in any announcements this coming week, as a purpose-built PaaS layer, specifically designed to create a common experience for cross clouds for data and application services. This, we believe, will be VMware's most significant offering to date in cross-cloud services. And it will position VMware to be a leader in what we call Supercloud. Now, while it remains to be seen what Broadcom exactly intends to do with VMware, we've speculated, others have speculated. We think this Supercloud is a substantial market opportunity generally and for VMware specifically. Look, if you don't own a public cloud, and very few companies do, in the tech business, we believe you better be supporting the build out of superclouds or building a supercloud yourself on top of hyperscale infrastructure. And we believe that as cloud matures, hyperscalers will increasingly I cross cloud services as an opportunity. We asked David Floyer to take a stab at a market model for super cloud. He's really good at these types of things. What he did is he took the known players in cloud and estimated their IaaS and PaaS cloud services, their total revenue, and then took a percentage. So this is super set of just the public cloud and the hyperscalers. And then what he did is he took a percentage to fit the Supercloud definition, as we just shared above. He then added another 20% on top to cover the long tail of Other. Other over time is most likely going to grow to let's say 30%. That's kind of how these markets work. Okay, so this is obviously an estimate, but it's an informed estimate by an individual who has done this many, many times and is pretty well respected in these types of forecasts, these long term forecasts. Now, by the definition we just shared, Supercloud revenue was estimated at about $3 billion in 2022 worldwide, growing to nearly $80 billion by 2030. Now remember, there's not one Supercloud market. It comprises a bunch of purpose-built superclouds that solve a specific problem. But the common attribute is it's built on top of hyperscale infrastructure. So overall, cloud services, including Supercloud, peak by the end of the decade. But Supercloud continues to grow and will take a higher percentage of the cloud market. The reasoning here is that the market will change and compute, will increasingly become distributed and embedded into edge devices, such as automobiles and robots and factory equipment, et cetera, and not necessarily be a discreet... I mean, it still will be, of course, but it's not going to be as much of a discrete component that is consumed via services like EZ2, that will mature. And this will be a key shift to watch in spending dynamics and really importantly, computing economics, the things we've talked about around arm and edge and AI inferencing and new low cost computing architectures at the edge. We're talking not the near edge, like, Lowes and Home Depot, we're talking far edge and embedded devices. Now, whether this becomes a seamless part of Supercloud remains to be seen. Look, if that's how we see it, the current and the future state of Supercloud, and we're committed to keeping the discussion going with an inclusive model that gathers input from all parts of the industry. Okay, that's it for today. Thanks to Alex Morrison, who's on production, and he also manages the podcast. Ken Schiffman, as well, is on production in our Boston office. Kristin Martin and Cheryl Knight, they help us get the word out on social media and in our newsletters. And Rob Hoffe is our editor in chief over at Silicon Angle and does some helpful editing. Thank you, all. Remember these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis Podcast. I publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me @Dvellante or comment on our LinkedIn posts. Please do check out etr.ai. They've got some great enterprise survey research. So please go there and poke around, And if you need any assistance, let them know. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis. (lively music)

(theme music) >> Okay, welcome back everyone, theCUBE's live coverage here in Boston, Massachusetts for AWS re:Inforce '22. Big show for ground security, Amazon re:Invent's coming up. That's the big event of all time for AWS. re:MARS was another one, re:Inforce, the re:Shows, they call them, theCUBE's got you covered. I'm John Furrier, host of theCUBE with Dave Vellante, who's in an analyst session right now. He'll be back shortly. We've got 2 great guests from an amazing company, HackerOne, been on theCUBE many times, (mumbles) Marten Mickos, of course, a big time, (mumbles) We got two great guests. Sean Ryan, Sr. Principal Product Marketing Manager Will Kapcio, Senior Sales Engineer. Gents, welcome to theCUBE. >> Thanks for having us John. >> So Marten's been on many times, he's such a character. He's such a legend. >> Yeah. >> Your company has had great traction, great community, just this phenomenal example of community meets technology and problem solver. >> Yeah. >> He's been part of that organization. Here at re:Inforce they're just kind of getting wind of it now, right? You hear an open, teamwork, breaking down the silos, a big theme is this whole idea of open community, but yet be hardcore with the security. It's been a big part of the re:Inforce. What do you guys think of the show so far? >> Loving it. Partly too, we're both local here in the Boston area. So the commute was pretty nice. (everyone laughs) And the heat wave broke the other day so that's wonderful, but yeah, great show. It's good to be back in person doing this kind of stuff and just, it's really lively. You get a lot of good energy. We've had a bunch of people stopping by trying to learn what we're all about and so, it's really fun. Great show so far. >> And you guys have a great company. Take a minute to explain for the folks who may not know HackerOne. Tell them what you guys do real quick in one minute. >> Okay, the quick elevator pitch. (chuckles) So really we're making the internet safer using a community of ethical hackers. And so our platform enables that so we can skill match the best talent that's out there around the world to help find all the vulnerabilities that your company needs to discover. So you can plug those holes and keep yourself safe. >> So in an era of a talent gap, Will, you know the technologies out there, but sometimes the skills are not there. So you guys can feel the void kind of a crowdsourced vibe, right? >> Yeah, exactly. If you're trying to build a security program, and apply defense in depth, we offer a terrific way to engage additional security talent either because you can't hire enough or your team is simply overloaded, too much to do, so. >> Hackers like to be a little bit, white hat hackers like to be independent, might want some flexibility in their schedule, live around the world. >> Yes. No question for hackers that do it full time, that do it part-time and then everything in between. >> Well, you guys are in the middle here with some real products. So talk about what's going on here. How vulnerable are the surface areas in organizations that you're seeing? >> Yeah, probably more so than you would think. So we ran a survey earlier this year, 800 security and IT professionals across North America and Europe. And one of the findings from that survey was that nearly a third, actually over a third, 37% of the attack surfaces, not secured. Some of it's not even known. They don't know what they don't know. They just have this entire area. And you can imagine, I mean there's a lot of reasons you know, real legitimate reasons that this happens. One of those really being that we don't know what we don't know. We haven't scanned our attack surface. >> And also it's about a decade of no perimeter anymore. >> Yes. >> Welcome to the cloud. >> For sure. Absolutely. And people are moving quick, right? You know, the Cloud perfect example. Cloud people are building new applications on top of these new underlying configurations happening on a constant basis. Acquisitions, you know, that's just a fast moving thing. Nobody can keep track of it. There's a lot of different skill sets you need you know. And yeah, skill shortage out there too. As we talked about. >> What's the attacker solution you guys have? You guys have this HackerOne attack resistance component, what's that about? >> That's right. So that is to solve what we call the attack resistance gap. So that area that's not protected, hasn't been secured, on top of just not knowing what those assets are, or how vulnerable they are. The other thing that happens is people are sort of doing status quo testing, or they're not able to keep up with effective testing. So scanners are great. They can catch common vulnerabilities, but they're not going to catch those really hard to find vulnerabilities. The thing that the really sophisticated attackers are going to go after. >> Yeah. >> So we use... This large community that we have of ethical hackers around the world to be able to skill match them and get them doing bug bounties, doing pen tests, really bulletproofing the organization, and helping them risk-rank what they find. >> Yeah. >> Triage these, do the retesting, you know, get it very secure. So that's how we do it on a high level. Will, you might have a-- >> Yeah. I mean there's a tremendous amount of automation out there, right? But you can't quite at least not yet replace critical thinking. >> Yeah. >> From smart security minds. So HackerOne has a number of solutions where we can apply those minds in different ways at different parts of the software life cycle at different cadences, to fit our customers' needs, to fit their security needs, and make sure that there's more complete human coverage throughout their software lifecycle, and not just automation. >> Yeah. I think that's a great point, Will and Sean, because you think about open source is like not only grown significantly, it's like's it is the software industry. If you believe that, which I do. Open source is there it's all software free. The integration is creating a DevOps movement that's going the whole level. So Devs are doing great. They're pumping out codes. In fact, I heard a quote here on theCUBE earlier this morning from the CTO Sequence Security that said: "Shift left but shield right." So shifting left is build your security into the code, but still you got to have a shield. You guys have this shielding capability with your attack module management service. So you now you got the Devs thinking: "I got to get better security native" So but they're pumping out so much code. >> Yep. >> There's more use cases, so there's going to be code reviews needed for stuff that she said, "What is this? We got to code review new stuff. A developer created something." >> Yes. >> I mean, that's what happened. That's what's going on everywhere, right? >> Exactly. We often hear that for every 100 developers, you've got one security professional. (John laughs) You know, talk about skill shortage that's just not sustainable. How are you going to keep up with that? >> Yeah. >> So-- >> Your phone is ringing off the hook. There's no phones anymore, but like technically-- >> Yeah, yeah, exactly. So, you know, yeah, you need to go external find some experts who can help you figure that out, and keep up with that cadence, you know keeps going and going. >> So, HackerOne. I love the ethical thing. I mean, you know, I'm a big fan. Everyone who watches theCUBE knows I'm a big fan of Marten and your company, but it's not just bug bounties that you do. That's just people think of, they see that in the news. "Oh, I made a million dollars from saving Microsoft teams from being exploited" or something like that, or weird things big numbers. But you do more than that. There's code reviews, there's assessments, like a variety of different things, right? >> Yes, exactly. Exactly. >> What are the hottest areas? >> Yeah, I mean, that's exactly why we coined the term, Attack Resistance Management really is to help describe all those areas that we cover, so you're right, bug bounty is our flagship product. It's what we're best known for. And it's a terrific solution. But on top of that, we're able to layer things like vulnerability disclosure, pen testing and code review. >> Pen test is actually really important-- >> Attack surface management, you know, a whole suite of complimentary offerings to help you engage these hackers in new and interesting ways. >> Yeah. >> The bug bounty is very popular because it's fun. >> Yeah. >> I mean if your going to work on something... It's fun for the hackers but the white hat hackers, the companies they can see where's my bugs it's the fear of missing out and the fear of getting screwed over. That's the biggest driver, right, you Know-- >> Yes, definitely and we now have a product called assets. So this is attack surface management. And what we're able to do with that is bring that in leverage the ethical hackers to risk-rank. What's your assets out there? How vulnerable are these? What's critical? Feed that in, and then you know, as Will was saying we've got all kinds of different testing options. Sometimes bug bounty continuous that works. Sometimes you want pen test, you know, you want it bound. >> Well, the thing about the thing about the pen test, well the soccer report, Amazon's got soccer reports but pen test is a moving train. >> Yeah >> Cause if you're pushing new code, you got to pen test it all the time. It's not a one and done. >> Exactly. >> You got to keep it running. Just one and run, right? >> You can't do the old school penetration test once a year, big monolithic thing. You know, this is just a check the box for compliances like, no, you need to be focusing this on the assets that you're releasing, which are constantly changing. And doing ongoing smaller cadences of pen testing. >> I had someone at a conference had a few cocktails in them, confessed to me, that they forged a pen test report. >> Oh man. >> Wow! (everyone laughs) >> Because he's like, "Oh! It was three months ago. Don't Worry about it." Like, but a lot can happen in three months. No, this is reality, they are like, "I can't turn it around fast enough" They had an Apsec review... >> Yeah. >> In their company and... >> And that's it. >> I mean, I'm not saying everyone's doing bad behavior, but like people can look the other way that creates more vulnerabilities. >> It can happen. And even just that time space. Let's say you're only doing a pen test once a year or once every two years. That's a long time. It's a lot of dwell time, you can have an attacker inside mulling around your network. >> All right. So we get a big service here. This one, AWS, we're here at re:Inforce the trend that you see Amazon getting closer to the ecosystem, lot more integration. How are you guys taking HackerOne's attack surface area product management software, closer to Amazon? What's going involved? Because at the end of the day they're enabling a lot of value and their partners are growing and becoming platforms within of themselves. What is the connection with Amazon? Keeping those apps running? How do you guys do that? >> Yeah. So we've got a specific assessment type for AWS. So... On the one hand, we're bringing in the right group of ethical hack hackers who are AWS certified. They have the right skillset, we're matching them. We've got the right assessment type for them to be able to track against and find the right vulnerabilities, report on those. So this is our pen test offering geared particularly towards the AWS platform. And then we also have an AWS security hub integration. So if customers are using the AWS security hub, we can plug into that, feed that information. And that gets more to it, the defense and depth for your AWS. >> And you guys verify all the ethical hackers? Everything's verified? >> Oh yes, absolutely. Fully. >> Yep. So they're verified for their pen testing experience, and skills and of course their AWS skills in particular. And their work experience, making sure that it's long enough that it's good, background check, the whole nine, so. >> How far has Amazon come from your perspective, over the past few years with the security partnerships? I mean their services have grown every year. I mean, every Amazon re:Invent, thousands of new announcements, new services. I mean if they update the DNS server, it's a new thing. Right? So like everything's happening. >> Yeah. >> What's different now? >> It's great to see. I mean, you look around at how many different types of security solutions there are here how many different types of partners, and it just shows you that defense in depth again, it's a really critical thing. Been a wonderful partner for us. I mean that, they're a big fan of us. They tell us that all the time. >> Yeah, 'cause the customers use you. >> Cause they're customers too. Right. Exactly. Exactly. But no, it's, it's been great. So we're looking at, we've got some things on the roadmap, some continued integrations that we look forward to doing with AWS, but you know, again it's a great powerful platform. It gives customers a lot of freedom, but with that freedom comes the responsibility that's needed to actually-- >> Will, what's your take? We hear hybrid security keys, management systems, announced today, encrypt everything, don't have over permissive environments. Obviously they're talking about more platform and that type of stuff >> Absolutely. My take would be, I think our own partnership with the AWS security team is great evidence that they're thinking about the right things. We worked within conjunction with them to develop our pen test methodology. So that combined for proprietary HackerOne platform data and findings across all of our customers that are common issues found in AWS environments with their own knowledge and their own experiences from the AWS security team directly. So it's a pretty powerful checklist that we're able to run through on some of these customers and make sure that all of the most common miss-configurations and such are covered. >> Yeah. They're highly motivated to do that. 'Cause they get blamed for the S3 buckets being kept open. It's not even their fault. >> Right. (crosstalk) >> We got hack over in Amazon. Amazon's terrible! >> Yeah. You know, one of the things we like to talk about is the fact that, you know, cloud is really about automation, right? >> Yeah. >> Yep. >> But you can't automate that human ingenuity the skills that come with an actual human who has the experience and the know how to fix these things. >> It's a lot going on in Amazon. It's always been kind of like, you just described earlier in theCUBE. An erector set, not Lego blocks yet, but still kind of, you still got to build it. It's getting better in the Lego model, but there are challenges in protecting cloud, Will. I mean this is a big part of protecting cloud platforms like AWS. What are some of those challenges? >> I think some of the challenges are the ephemeral nature of the cloud can really result in developers, and you know really business units across an organization spinning up assets that IT or security don't know about. And so that's where things like HackerOne assets in those attack surface management style solutions come into play, trying to identify those assets proactively and make sure that they're receiving some sort of attention from the security team whether it's automated or manual or ideally both. >> You guys got a good solution. So how about the partnership? We got one minute left. Talk about your partnership with AWS. You guys are certified in their security group, with their team and marketplace, right? Talk about some of those things. >> Yeah, we've been in marketplace over a year. We've had that the specific solution that I mentioned the App Pen test for AWS in place and integrated with security hub for some time now. There's some other stats that we could probably share around the ethical hackers that we have working on that. We have a number of certified AWS hackers, who again they have the right skill set for AWS, and they've been a great partner. We are very focused on continuing to work with them, and build out some new offerings going forward. >> Well, you guys have done a great job. Will, tell your team congratulations on the tech side, on the product side, very strong community. You guys had a lot of success. Congratulations! And thanks for sharing on theCUBE, appreciate it. >> Thanks for having us John. >> Thank you for your time-- We're here at re:Inforce where all the access tab is open, it's team oriented, we got cloud scale, data, encryption on everything. Big news coming out of re:Inforce, well, theCUBE's got it covered here. I'm John Furrier, your host. Thanks for watching. We'll be right back with more coverage after this short break. (theme music)

(electronic music) >> Welcome to theCUBE. This is the AWS Executive Summit presented by Accenture and our coverage of this great event continues. Lisa Martin here, I've got two guests with me here to talk about Amazon Connect. Please welcome from Hawaiian Airlines, Will Van Devender, Senior Director of IT Engineering. Will, welcome to the program. >> Thanks for having me here. >> And from Accenture, Erich Chen is here as well, the Hawaii Regional Lead at Accenture. Erich, it's great to have you on the program. >> It's great to be here. >> I feel very overdressed. You can tell I'm on the mainland with my turtleneck and you guys are on Oahu, which is fantastic. And I'm excited that I have a seat on Hawaiian Airlines in just a few weeks. So you guys, let's talk about this technology solution that you put together. Will, I want to start with you. Talk to me about some of the challenges that Hawaiian Airlines was having prior to working with Accenture and Amazon. >> Well, nothing really unique to us. We had the challenges that everybody had with the pandemic and scaling out to work from home, as well as an old legacy stack that had been around for a long, long time. The specific ones that drove us to launch this particular project was we had been running into some talent acquisition issues. We're not of size where we have a huge telecom team that can specialize in IDRs and other things like that. So we need folks that can play a lot of different spaces. And in this particular case, we had a situation where we had really old technology and the people we were bringing in were a lot more savvy on Cloud and those kinds of things. And so AWS Connect was a way for us to take talent that traditionally wasn't inside the telephony space and use them and bring them to bear for that business need. So it kept us from having to scale up to do this. The other thing we had was a big issue with work from home that actually predated COVID. So we had been, we're in a hurricane zone, we had been doing hurricane preparedness exercises and we realized that we had a difficult time scaling our environment to large scale work from home. So even prior to COVID, we had been started looking at the technologies that we had, which ones worked well outside of an office for a distributed workforce. And we had been moving technology in that direction. And so telephony was one of the ones that we had to beef up. And so it was nice to have a good leg up on it when the pandemic hit us. >> Absolutely. I can't imagine how advantageous that was when it struck. And of course we all know how much the airlines were affected. Talk to me about an interesting catalyst for this solution in terms of challenge with talent acquisition and work from home. Interesting impetus for this solution. Talk to me about, are you long time partners, Hawaiian Airlines with Accenture? Talk to me about how you went about looking for the right solution with them as a partner. >> Ah, okay. So Hawaiian Airlines and Accenture had been partnering for many years, but in a much bigger way in 2019, when we solidified a new managed services deal. So Accenture came in to help us out with our day to day operations. And one of the big reasons for that was actually cloud adoption. So we needed a partner that was much more up to date technology wise. And as we started ramping up our engineering and architecture designs and releasing things on new stacks, we needed folks in the operation side that could keep up with that. And not only that, actually enable and push us in those directions. And so when we went out to RFP, Accenture kind of stood out in that area and that's been a good thing. We've had very little friction as we've been going out and acquiring new technology with being able to bring that out to our run and operation space. >> That's critical, especially given the tumultuous times in which we are still living. Erich, let's go ahead and bring you into the conversation. Now, talk to me about you guys at Accenture developed and deployed this solution quickly. We're talking an eight week timeframe. Talk to me about the solution that you architected, about that delivery, and what some of the challenges were along the way that you tackled and mitigated. >> Yeah. Thanks Lisa. I mean, it was, you know, eight weeks when you look back on it, it's hard to believe we did complete it in that timeframe, but, you know, we were able to do it with some strong experts from our side. Some of the challenges we ran into along the way were probably at the very beginning, just securing the right team for Hawaiian to deliver the kind of the proper designs and development upfront, and then helping to kind of manage through the delivery process itself. You know, they were great. They had some great people with some deep expertise, kind of from a business process side of things, kind of paired with our technical and then also industry knowledge of the airlines as well. It made for a really nice, you know, strong partnership where we could get it through in eight weeks. So it was pretty amazing. >> And then walk me through the actual, oh Will, sorry. Did you want to say something? >> Yeah, I was actually going to comment on that, that was exactly what we were looking for was that sort of wholesale partner. So when we went out to modernize our entire telephony stack, it wasn't just call centers. It was the conference rooms, it was the telephony, we went to new phone providers and circuit providers, we moved everyone off of Skype over on to Teams, all the desk phones. And so there was this scope of work that was simply larger than our team. And so what we were looking for from a partner was one, who's done this before, and then two, could you manage the whole piece of work? And so what was nice for Accenture, because they owned our existing operation space, they not only did the AWS Connect piece, they got on the old systems and they brought up all the specs of how the call queues worked, how the call flows worked, they found the old voice talent, they brought those, imported them without us having to do anything over onto the new stack, and then brought it over for testing. So it was just a very minimal lift from the Hawaiian Airlines side. And since they ran our operations, they then moved it over to the run space. And it was just very few man hours on the Hawaiian Airlines side expended for that outcome. >> Wow. It sounds fairly seamless. Erich, how did you guys accomplish that? >> I mean, that's a type of experience and partnership we like to have with our clients, more of an all-inclusive type service. But we're sometimes accused of not having the cheapest prices on the block, but you know, you do get a great, you know, a pretty holistic experience with us and we do try to make it as easy as possible for our clients and bring kind of the full breadth of Accenture to fill in a lot of gaps. >> Well, one of the things, Will, that you mentioned is we were looking for a partner that had done this before, where there's actual proof in the pudding, especially given the, like I mentioned before, the tumultuous market. Erich talk to me about, if we look at Hawaiian Airlines as an example, as a template here, how common or how often are you seeing these same challenges with respect to talent acquisition and work from home? Is that something that really skyrocketed in the last year and a half? >> Sure. I mean, it's maybe a blessing in the type of business that we're in, right. But whenever there are, you know, big, you know, kind of market issues and kind of pandemics as an example, right. Our clients do turn to us for, you know, support to help them through, you know, smaller times of need. And, you know, maybe very compressed issues. So we're very happy to, you know, reach into our larger organization to make sure that we can bring the best of Accenture to them and help them get through these tough times. >> Will, let's talk about how this solution is helping employees, agents get through these tough times. As we know, Hawaii had some really strict travel restrictions on COVID. And of course, one of the things that a lot of people lost during this time, was patience. Talk to me about how the workforce is improving, the employees, the agents, now that you have this solution implemented and a leg up probably on your competitors. >> Yeah, the whole pandemic hit us in a hard way. So we found ourselves, you know, all of a sudden one day waking up and finding that our customer facing support desks couldn't be staffed. People couldn't get into the office and actually get there. At the same time, as you and everyone else knows, flights were getting canceled and customers were calling at a level we'd never seen before trying to reschedule their flights or get credit back or get money back. And so AWS Connect was interesting in that it was one of the things we could ramp up new call centers very quickly. And so we knew we wanted something that was consumption-based because we didn't know how long it was going to last. And we wanted to be able to spin it up, get new agents going, respond to our customers, scale up to the volume, and then be able to decrease it out. So it was a good win there. What wasn't talked about much was the reliability aspect of it. Being on a really old system, our telephony was pretty stable, but our call center internal business facing ones were not. We had a series of outages out there and those outages directly impact our ability to get planes out in the air. There's the sort of customers calling about tickets and about help with flights, but there's also things like cruise, trying to get cruise scheduling done, trying to get staffing to a plane, trying to get things moved around in an airport. And there's a lot of internal desks that deal with those kinds of things. And having that on an incredibly stable technology and stack is key for us. And so we were able to get Connect deployed, and we were also able to front that with a number of other technologies that allowed us to have DR plans. So even if we lost that desk, how can we quickly move that over to manual calls and desk phones and those kinds of things. And so that's been, that part has been very well received. That has helped us out a lot. Our confidence, knowing that if anything should happen, our ability to recover and get back into full operations now is just night and day from where it was 12 months ago. And so thank you all very much for your assistance in getting us to this point. >> Getting that stability and that reliability during a time of chaos that's, and also in a time that can really affect brand reputation, it sounds to me like IT is really helping drive the business forward. This is something that you did in partnership with the business side, because of course during the last year and a half, so many brands have had challenges with reputation and the ability to not do things. Talk to me about that business IT relationship. And was this a facilitator of making that even better? >> Well, it's certainly better. Yeah, we have far better conversations internally than I can ever remember in my time here in Hawaiian Airlines. But you know, when these kinds of emergencies hit, I don't think about it as IT or business. I mean, there's a problem and you got to go fix it. And so we're all in there and IT is one piece of that. How do we get a solution stood up almost overnight in this, you know, very, very difficult pandemic business time? But you know, the business is trying to get talent together and trying to get agents trained and being able to do things like handle these customer calls is very, very skill intensive. So there's a lot of partnership coming in and getting solutions, demoing with the business, dialing them in back and forth, and a lot of collaboration there. And so that builds stronger teams. And that's one of the outcomes I like more than anything else, is we're working together and dialing in the IT and the business needs very much in unison. >> That's probably one of the best outcomes you can hope for. Erich, talk to me about, are you seeing similar things with customers in other industries? Are you seeing that business IT coming together, especially during these challenging times we've been living through? >> Yeah, to varying degrees, you know, that's always the crux of, you know, a successful IT department, right. You know, you're there to serve and support the business side of things, right. We don't do technology for technology sake. But yeah, I think the better ones are getting better, better at, you know, being more fully integrated and it's not a business or IT decision, right, it's a collective kind of team decision. And I think as long as you have people who respect and understand the other side of the coin sometimes, easier the conversation will go. And I think that's what our team was able to do is express, you know, very clearly and concisely kind of what the decisions they had to make were and they could make a decision a little bit easier that way. >> And talk to me, Erich, about the solution, what impressed you? What are you most excited about in terms of what Accenture has helped to accomplish for Hawaiian Airlines? >> Yeah, I was really happy that even, you know, within a short eight week period itself, you know, things always come up as you go throughout a project. And I think the business team was getting excited about the possibilities once they saw kind of the potential of the platform. And so some, you know, requests came up in the middle of the way, you know, in flight. And, you know, our team was able to accommodate a number of the kind of minor enhancements or tweaks to the system to make it even better and serve the business in a better fashion there. >> Gotcha. Will, what is next for Hawaiian Airlines, besides my flight on it in a few weeks? Talk to me about where you guys are going from an IT perspective. >> Well we've rolled out a solution quickly 'cause we needed to, but there's a lot still to be done to dial it in for the business. Where reliability and speed were key, we got those done, but there was some aspects of the old system that were still a little easier. For those call centers where people needed to dial in, get ahold of an agent, and then pass it onto an internal employee, there's still a disconnect between our call center technology, AWS Connect, and the internal collaboration, Microsoft Teams. And that's because Teams really wasn't up to all of the call center technology needs at the time we started this. Things like call recording and things like that just weren't there at the time. So we've got some of our internal desks that still need to be tweaked and integrated more seamlessly between the two platforms or maybe as Teams gets ready, moved back over onto that. So that's, again, the part of it, being able to have this deep conversation with the business, understand their needs, having a partner where you can quickly go respond and go dial it in. And so we don't look at it as our telephony migration is complete. We look at it as we got our first big hurdle done, moving off decades old tech onto our modern stack. And now we're looking at refining it with our partners over the future. >> Right. Phase one, it's always that journey that we talk about. Erich, last question for you. What are some of the things that are coming up next as you help Hawaiian Airlines to continue on this modernization journey? >> Yeah, so more broadly we're really excited because this effort was one of the first or probably more platform centric system integration type projects we've done for Hawaiian. We've been on the operation side, we've done some business consulting worked with them for various business functions already, but this was really more on the application modernization side of things. And, you know, we see that Hawaiian has a number of areas that they're looking to kind of modernize and improve along the way. And we're very excited about, you know, being a strong partner for them in that journey coming up. >> Awesome guys, great work. Congratulations on a huge transformation accomplished during a very chaotic world time period and done so quickly. We appreciate your comments, your feedback, and look forward to seeing what you dial in next. Thanks for joining me today. >> Thank you. >> Thanks very much. >> For Will Van Devender and Erich Chen, I'm Lisa Martin. You're watching theCUBE's coverage of the AWS Executive Summit presented by Accenture. (soft music)

(upbeat music) >> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Everyone, welcome to this CUBE conversation. I'm John Furrier with theCUBE, host of theCUBE here in our Palo Alto office for remote interviews during this time of COVID-19. We're here with the quarantine crew here in our studio. We've got a great guest here from Google, Will Grannis, managing director, head of the office of the CTO with Google Cloud. Thanks for coming on, Will. Appreciate you spending some time with me. >> Oh, John, it's great to be with you. And as you said, in these times, more important than ever to stay connected. >> Yeah, and I'm really glad you came on because a couple of things. One, congratulations to Google Cloud for the success you guys had. Saw a lot of big wins under your belt, both on the momentum side, on the business side, but also on the technical side. Meet is available now for folks. Anthos is doing very, very well. Partner ecosystem's developing. Got some nice use cases in vertical markets, so I want to get in and unpack with you. But really, the bigger story here is that the world has seen the future before it was ready for it. And that is the at-scale challenge that the COVID-19 has shown everyone. We're seeing the future has been pulled forward. We're living in a virtualized environment. It's funny to say that, virtualization (laughs). Server virtualization is a tech term, but that enabled a lot of things. We're living in a virtualized world now 'cause we have to, but this is going to set in motion a series of new realities that you guys have been experiencing and supporting for many, many years. But now as a provider of Google Cloud, you guys have to operate at scale, you have. And now the whole world realizes that scale is a big deal. And so you guys have had some successes. I want to get your thoughts on the this at scale problem that the world now realizes. I mean, everyone's at home. That's a disruption that was unforecasted. Whether it's under-provisioning VPNs in IT to a surface area for security, to just work and play. And activities are now confined, so people aren't convening anymore and it's a huge issue. What's your take on all this? >> Well, I mean, to your point just now, the fact that we can have this conversation and we can have it fluidly from our respective remote locations just goes to show you the power of information technology that underlies so many of the things that we do today. And for Google Cloud, this is not a new thing. And for Google, this is not a new thing. For Google Cloud, we had a mission of trying to help companies accelerate their transformation and enable them in these new digital environments. And so many companies that we've been working with, they've already been on the path to operating in environments that are digital, that are fluid. And when you think about the cloud, that's one of the great benefits of cloud, is that scalability in common with the business demand. And it also helps the scale situation without having to do the typical, "Oh wait, "you need to find the procurement people. "We need to find the server vendors. "We need to get the storage lined up." It really allows a much more fluid response to unexpected and unforecasted situations. Whether that's customer demand or in this case a global pandemic. >> Yeah, one of the things I want to get in with you on, you have explained what your job is there 'cause obviously Google's got a new CEO now for over a year. Thomas Kurian came from Oracle, knows the enterprise up and down. You had Diane Greene before that. Again, another enterprise leader. Google Cloud has essentially rebuilt itself from the original Google Cloud to be very enterprise centric. You guys have great momentum, and this is a world where cloud-native is going to be required. I mean, everyone now sees it. The tide has been pulled out, everything's exposed, all the gaps in business from a tech standpoint is kind of exposed. And so the smart managers and companies are looking at things and saying, "Double down on that. "Let's kill that. "We don't want to pay that supplier. "They're not core to our business." This is going to be a very rapid acceleration of what I call a vetting of the new set of players that are going to emerge because the folks who don't adapt to this new cloud-native reality, whether it's app workloads for banking to whatever are going to have to reinvent themselves now and reset and tweak to come out of this crisis. So it's going to be very cloud-native. This is a big deal. Can you share your reaction to that? >> Absolutely. And so as you pointed out, there are kind of two worlds that exist right now. Companies that are moving to become more digital and transform, and you mentioned the momentum in Google Cloud just over the last year, greater than 50% revenue growth. And in a greater than $10 billion run rate business and adding customers at a really quick clip, including just yesterday, Splunk, and along the way, Telecom Italia, Major League Baseball, Vodafone, Lowe's, Wayfair, Activision Blizzard. This transformation and this digitization is not just for a few or just for any one industry. It's happening across the board. And then you add that to the implementations that have been happening across Shopify and the Spotify and HSBC, which was a early customer of ours in the cloud and it already has a little bit of a headstart into this transformation. So you see these new companies coming in and seeing the value of digital transformation. And then these other companies that have kind of lit the path for others to consider. And Shopify is a really good example of how seeing drastic uptick in demand, they're able to respond and keep roughly half a million shops up and running during a period of time where many retailers are trying to figure out how to stay online or even get online. >> Well, what is your role at Google? Obviously, you're the managing director. Title is managing director, head of the office of the CTO. We've seen these roles before, head of the CTO, obviously a technical role. Is it partnering with the CEO on strategy? Is it you're tire kicking new things? Are you overseeing any strategic initiatives? What is your role? >> So a little bit of all of those things combined into one. So I spent the first couple of decades of my career on the other side of the fence in the non-tech community, both in the enterprise. But we were still building technology and we were still digitally minded. But not the way that people view technology in Silicon Valley. And so spending a couple of decades in that environment really gave me insights into how to take technology and apply them to a specific problem. And when I came to Google five years ago, selfishly, it was because I knew the potential of Google's technology having been on the other side. And I was really interested in forming a better bridge between Google's technology and people like me who were CTOs of public companies and really wanted to leverage that technology for problems that I was solving. Whether it was aerospace, public sector, manufacturing, what have you. And so it's been great. It's the role of a lifetime. I've been able to build the team that I wanted as an enterprise technologist for decades and the entire span of technologies at our disposal. And we do two things. One is we help our most strategic customers accelerate their path to cloud. And two, we create these signals by working with the top companies moving to the cloud and digitally transforming. We learned so much, John, about what we need to build as an organization. So it also helps balance out the Google driven innovation with our customer driven innovation. >> Yeah, and I can attest. I've been watching you guys from day one. Hired a lot of great enterprise people that I personally know. So you get in the enterprise chops and stuff and you've seen some progress. I have to ask you though, because first of all, big fan of Google at scale from knowing them from when they were just a little search engine to what they are now. There was an expression a few years ago I heard from enterprise customers. It goes along the lines like this. "I want to be like Google," because you guys had a great network, you had large scale. You had all these things that were like awesome. And then they realized, "Well, we can't be like Google. "We don't have SREs. "We don't have large scale data centers." So there was a little bit of a translation, and I want to say a little bit of a overplay of the Google hand, and you guys had since realized that it wasn't just people are going to bang at your doorstep and be adopting Google Cloud because there was a little bit of a cultural disconnect from wanting to be like Google, then leveraging Google in their business as they transform. So as you guys have moved from that, what's changed? They still want to be like Google in the sense you have great security, got a great network, and you've got that scale. Enterprises are a little bit slower to adopt that, which you're focused on now. What is the story there? Because I think that's kind of the theme that I'm hearing. Okay, Google now understands me. They know I'm not as fast as Google. They got super great people (laughs). We are training our people. We're retraining them. This is the transformation that they're going through. So you might be a little bit ahead of them certainly, but now they need to level up. How do you respond to that? >> Well, a lot of this is the transformation that Thomas has been enacting over the last year plus. And it comes in kind of three very operational or tactical pillars that I think of. First, we expanded our customer and we continue to expand our customer facing teams. Three times what they were before because we need to be there. We need to be in those situations. We need to hear from the customer. We need to learn more about the problems they're trying to solve. So we don't just take a theoretical principle and try to overlay it onto a problem. We actually get very visceral understanding of what they're trying to solve. But you have to be there to gain that empathy and that understanding. And so one is showing up, and that has been mobilizing a much larger engine of customer facing personnel from Google. Second, it's also been really important that we evolve our own. Just as Google brought SRE principles and principles of distributed systems and software design out to the world, we also had a little bit to learn about transitioning from typical customer support and moving to more customer experience. So you've seen that evolution under Thomas as well with cloud changing... Moving from talking about support to talking about customer experience, that white glove experience that our customers get and our partners get from the beginning of their journey with us all the way through. And then finally making sure that our product roadmap has the solutions that are relevant across key priority industries for us. Again, that only comes from being present from having a focus in those industries and then developing the solutions that progress those companies. This isn't about taking a principle and trying to apply it blindly. This is about adding that connection, that really deep connection to our customers and our partners and letting that connection manifest the things that we have to do as a product company to best support them over a long period of time. I mean, look at some of these deals we've been announcing. These are 10-year, five-year, multi-year strategic partnerships that go across the canvas of all of Google. And those are the really exciting scaled partnerships. But to your point, you can't just take SRE from Google and apply it to company X, but you can things like error budgets or how we think about the principles of SRE, and you can apply them over the course of developing technology, collaborating, innovating together. >> Yeah, and I think cloud-native is going to be a key thing. It's just my opinion, but I think one of those situations where the better mouse trap will win. If you're cloud-native and you have APIs and you have the kind of services, people will beat it to your doorstep. So I got to ask you, with Thomas Kurian on board, obviously, we've been following his career as well at Oracle. He knows what he's doing. Comes into Google, it's being built out. It's like a rocket ship at this point. What bet is he making and what bet are you guys making on behalf of your customers? If you had to boil it down to Google Cloud's big bet, what is the bet on the technology side? And what's the bet on the business side? >> Sure. Well, I've already mentioned... I've already hinted at the big strategy that Thomas has brought in. And that's, again, those three pillars. Making sure that we show up and that we're present by having a scaled customer facing organization. Again, making sure that we transition from a typical support mindset into more of a customer experience mindset and then making sure that those solutions are tailored and available for our priority industries. If I was to add more color to that, I think one of the most important changes that Thomas has personally been driving is he's been converting us to a partner-led business and a partner-led organization. And this means a lot of investments in large global systems integrators like Accenture and Deloitte. But this also means that... Like the Splunk announcement from yesterday, that isn't just a sell to. This is a partnership that goes deep across go-to market product and sell to. And then we also bring in very specific partners like Temenos in Europe for financial services or a CETA or a Rackspace for migrations. And as a result, already, we're seeing really incredible lifts. So for example, nearly 200% year over year increase in partner influenced revenue in Google Cloud and almost like a 13X year over year increase in new customers won by partners. That's the kind of engine that builds a real hyper-scale business. >> Interesting you mentioned Splunk. I want to get to that in a second, but I also noticed there was a deal with TELUS Group on eSIM subscriptions, which kind of leads me into the edge piece. There's a real edge component here with Google Cloud, and I think I had a conversation with Jennifer Lynn a few years ago, really digging into the built-in security and the value of the Google network. I mean, a lot of the scuttlebutt around the Valley and the industry is Google's got an amazing network. Software-defined networking is going to be a hot programmable area. So you got programmable networking and you got edge and edge security. These are killer areas that need innovation. Could you comment on what you guys are doing there and do you agree? Obviously, you have a killer network and you're leveraging it. Can you just give some insight into what's going on in those two areas? Network and then the edge. >> Yeah, I think what you're seeing is the manifestation of the progression of cloud generally. And what do I mean by that? It started out as like get everything to the data center. We kind of had this thought that maybe we could take all the workloads and we could get them to these centralized hubs and that we could redistribute out the results and drive the latency down over time so we can expand the portfolio of applications and services that would become relevant over time. And what we've seen over the last decade really in cloud is an evolution to more of a layered architecture. And that layered architecture includes kind of core data centers. It includes CDN capacity, points of presence, it includes edge. And just in that list of customers over the last year I mentioned, there were at least three or four telcos in there. And you've also probably heard and seen quite a bit of telco momentum coming from us in recent announcements. I think that's an indication that a lot of us are thinking about, how can we take technology like Anthos, for example, and how could we orchestrate workloads, create a common control plane, manage services across those three shells, if you will, of the architecture? And that's a very strategic and important area for us. And I think generally for the cloud industry, is expanding beyond the data center as the place where everything happens. And you can look at Google Fi, you can look at Stadia. You can look at examples within Google that go well beyond cloud as to how we think about new ways to leverage that kind of criteria. >> All right, so we saw some earnings come out on Amazon side as Google, both groups and Microsoft as well, all three clouds are crushing it on the cloud side. That's a tailwind, I get that. But as it continues, we're expecting post-COVID some redistribution of development dollars in projects. Whether it's IT going cloud-native or whatever new workloads. We are predicting a Cambrian explosion of new things from core to edge. And this is going to create some lifts. So I want to get your thoughts on you guys' strategy with go-to market, as well as your customers as they now have the ability to build workloads and apps with AI and data. There seems to be a trend towards the verticalization of whether it's sales and go-to market and/or specialism because you have horizontal scalability with cloud and you now have data that has distinct (chuckles) value in these verticals. So it's really seems to be... I won't say ratification, but in a way, that seems to be the norm. Whether you come into a market and you have specialization, but the data is there so apps can be more agile. Are you guys seeing that? And is that something that you guys are considering from an organization standpoint? And how do customers think about targeting vertical industries and their customers? >> Yeah, I bring this to... And where you started going there at the end of the question is exactly the way that we think about it as well. Which is we've moved from, "Here are storage offers for everybody, "and here's basic infrastructure for everybody." And now we've said, "How can we make sure "that we have solutions that are tailored "to the very specific problems that customers "are trying to solve?" And we're getting to the point now where performance and variety of technologies are available to be able to impose very specific solutions. And if you think about the substrate that has to be there, we mentioned you have to have some really great partners, and you have to have a roadmap that is focused on priority solution. So for example, at Google Cloud, we're very focused on six priority vertical areas. So retail, financial services, healthcare, manufacturing and industrials, healthcare life sciences, public sector. And as a result of being very focused in those areas, we can make more targeted investments and also align our entire go-to market system and our entire partner ecosystem... Excuse me, ecosystem around those bare specific priority areas. So for example, we work with CETA and HDA Healthcare very recently to develop and maintain a national response portal for COVID-19. And that's to help better inform communities and hospitals. We can use Looker to help with like a Commonwealth Care Alliance nonprofit and that helps monitor patient symptoms and risk factors. So we're using a very specific focus in healthcare and a partner ecosystem to develop very tailored solutions. You can also look at... I mentioned Shopify earlier. That's another great example of how in retail, they can use something like Google Meet, inherent reliability, scalability, security, to connect their employees during these interesting times. But then they can also use GCP, Google Cloud Platform to scale out. And as they come up with new apps and experiences for their shoppers, for their shops, they can rapidly deploy, to your point. And those solutions and how the database performs and how those tiers perform, that's a very tight-knit feedback loop with our engineering teams. >> Yeah, one of the things I'm seeing obviously with the virtualization of the COVID is that when the world gets back to normal, it'll be a hybrid. And it'll be a hybrid between reality, not physical and a hundred percent virtual, hybrid. And that's going to impact events too, media, to everything. Every vertical will be impacted. And I want to point out the Splunk deal and bring that back in because I want you to comment on the relevance of the Splunk deal in context to Splunk has a cloud. And they've got a great slogan, "Data for everywhere." "Data to everywhere," I think it is. But theCUBE, we have a cloud. Every company will have a cloud scale. At some level, we'll progress to having some sort of cloud because they have data. How are you guys powering those clouds? Because I think the Splunk deal is interesting. Their partner, their stock price was up out on the news of the deal. Nice bump there for Splunk, shout out to those guys. But they're a data company and now they're cross-platform. But they're not Google, but they have a cloud. So you know what I'm saying? So they need to play in all the clouds, but they need infrastructure (laughs), they need support. So how do you guys talk to that customer that says, "Hey, the next pandemic that comes, "the next crisis that's going to cause some "either social disruption or workflow disruption "or supply chain disruption. "I need to be agile. "I need to have full cloud scale. "And so I need to talk to Google." What do you say to them? What's the pitch? And does the Splunk deal mirror some of those capabilities? Or tie that together for us, the Splunk deal and how it relates to how to proof themselves for the future. Sorry. >> For example, with the Splunk cloud deal, if you take a look at what Google is already really good at, data processing at scale, log analytics, and you take a look at what Splunk is doing with their events and security incident monitoring and the rest, it's a really great mashup because they see by platforming on Google Cloud, not only do they get highly performing infrastructure. But they also get the opportunity to leverage data tools, data analytics tools, machine learning and AI that can help them provide enhanced services. So not just about capacity going up and down through periods of demand, but also enhancing services and continuing to offer more value to their customers. And we see that as a really big trend. And this gets at something, John, a little bit bigger, which is kind of the two views of the world. And we talked about very tailored, focused solutions. Splunk is an example of taking a very methodical approach to a partnership, building a solution specifically with partners. And in this case, Splunk on the security event management side. But we're always going to provide our data processing platform, our infrastructure for companies across many different industries. And I think that addresses one part of the topic, which is, how do we make sure that in periods of demand rapidly changing, and this goes back to the foundational elements of infrastructure as a service and elasticity. We're going to provide a platform and infrastructure that can help companies move through periods of... It's hard to forecast, and/or demand may rise and fall in very interesting ways. But then there's going to be times where we... Because we're not necessarily a focused use case where it may just be generalized platform versus a focused solution. So for example, in the oil and gas industry, we don't develop custom AI, ML solutions that facilitate upstream extraction, for example. But what we do do is work with renewable energy companies to figure out how they might be able to leverage some of our AI machine learning algorithms from our own data centers to make their operations more efficient and to help those renewable energy companies learn from what we've learned building out what I consider to be a world leading renewable energy strategy and infrastructure. >> It's a classic enablement model where you're enabling your platform for your customers. Okay, so I've got to ask the question. I asked this to the Microsoft guys as well because Amazon has their own SaaS stuff. But really more of end to end. The better product's usually on the ecosystem side. You guys have some killer SaaS. G Suite, we're a customer. We use the G Suite really deeply. We also use some Bigtable as well. I want to build a cloud, we have a cloud, CUBE cloud. But you guys have Meet. So I want to build my product on Google Cloud. How do I know you're not going to compete with me? Do you guys have those conversations around the trade-off between the pure Google services, which provide great value for the areas where the ecosystem needs to develop those new areas that are going to be great markets, potentially huge markets that are out there. >> Well, this is the power of partnership. I mentioned earlier that one of the really big moves that Thomas has made has been developing a sense of partners. And it kind of blurs the line between traditional, what you would call a customer and what you would call a partner. And so having a really strong sense of which industries we're in, which we prioritize, plus having a really strong sense of where we want to add value and where our customers and partners want to add that value. That's the foundational, that's the beginning of that conversation that you just mentioned. And it's important that we have an ability to engage not just in a, "Here's the cloud infrastructure piece of the puzzle." But one of the things Thomas has also done and a key strategy of his has been to make sure that the Google Cloud relationship is also a way to access all amazing innovation happening across all of Google. And also help bring a strategic conversation in that includes multiple properties from across Google so that an HSBC and Google and have a conversation about how to move forward together that is comprehensive rather than having to wonder and have that uncertainty sit behind the projects that we're trying to get out and have high velocity on because they offer so much to retail bank, for example. >> Well, I've got a couple more questions and then I'll let you go. I know you got some other things going on. I really appreciate you taking the time, sharing this great insight and updates. As a builder, you've been on the other side of the table. Now you're at Google heading up the CTO. Also working with Thomas, understanding the go-to market across the board and the product mix. As you talk to customers and they're thinking... The good customers are thinking, "Hey, "I want to come out of this COVID on an upward trajectory "and I want to use this opportunity "to reset and realign for the future." What advice do you have for those enterprises? They could be small, medium-sized enterprises to the full large big guys. And obviously, cloud-native, we've talked some of that already, but what advice would you have for them as they start to really prioritize, as some things are now exposed? The collaboration, the tooling, the scale, all these things are out there. What have you seen and what advice would you give a CXO or CSO or a leader in the industry to think about and how they should come out of this thing, how they should plan, execute, and move forward? >> Well, I appreciate the question because this is the crux of most of my day job, which is interacting with the C-suite and boards of companies and partners around the world. And they're obviously very interested to learn or get a data point from someone at Google. And the advice generally goes in a couple of different directions. One, collaboration is part of the secret sauce that makes Google what it is. And I think you're seeing this right now across every industry, and whether you're a small, medium-sized business or you're a large company, the ability to connect people with each other to collaborate in very meaningful ways, to share information rapidly, to do it securely with high reliability, that's the foundation that enables all of the projects that you might choose to... Applications to build, services to enable, to actually succeed in production and over the long haul. Is that culture of innovation and collaboration. So absolutely number one is having a really strong sense of what they want to achieve from a cultural perspective and collaboration perspective and the people because that's the thing that fuels everything else. Second piece of advice, especially in these times where there's so much uncertainty, is where can you buy down uncertainty with...? You can learn without a high penalty. This is why cloud I think is really, really finding super scale. It was already on the rise, but what you're seeing now as you've laid back to me during this conversation, we're seeing the same thing, which is a high increase in demand of, "Let's get this implemented now. "How can we do this more? "This is clearly one way to move through uncertainty." And so look for those opportunities. I'll give you a really good example. Mainframes, (chuckles) one of the classic workloads of the on-premise enterprise. There are all sorts of potential magic solves for getting mainframes to the cloud and getting out of mainframes. But a practical consideration might be maybe you just front-end it with some Java. Or maybe you just get closer to other data centers within a certain amount of milliseconds that's required to have a performant workload. Maybe you start chunking at art and treat the workload a little bit differently rather than just one thing. But there are a lot of years and investments in our workload that might run on a mainframe. And that's a perfect example of how biting off too much might be a little bit dangerous, but there is a path to... So for example, we brought in a company called Cornerstone to help with those migrations. But we also have partnerships with data center providers and others globally plus our own built infrastructure to allow even a smaller step per se for more close proximity location of the workload. >> It's great. Everything kind of has a technical metaphor connection these days when you have a internet, digitally connected world. We're living in the notion of a digital business, was a research buzzword that's been kicked around for years. But I think now COVID-19, you're seeing the virtual or digital, it's really digital, but virtual reality, augmented reality is going to come fast too. Really get people to go, "Wow. "Virtualization of my business." So we've been kind of kicking around this term business virtualization just almost as a joke, but it's really more about, okay, this is about a new world, new opportunity to think about when we come out of this, we're going to still go back to our physical world. Now, the hybrid now kicks in. This kind of connects all aspects of business in every vertical. It's not like, "Hey, I'm targeting this industry." So there might be unique solutions in those industries, but now the world is virtualized. It's connected, it's a digital environment. These are huge concepts that I think has kind of been a lunatic fringe idea, but now it's brought mainstream. This is going to be a huge tailwind for you guys as well as developers and entrepreneurs and application software. This is going to be, we think, a big thing. What's your reaction to that? Based on your experience, what do you see happening? Do you agree with it? And do you have anything you might want to add to that? >> Maybe one kind of philosophical statement and then one more... I bruised my shins a lot in this world and maybe share some of the black and blue coloration. First from a philosophical standpoint, the greater the crisis, the more open-minded people become and the more creative people get. And so I'm really excited about the creativity that I'm seeing with all of the customers that I work with directly, plus our partners, Googlers. Everybody is rallying together to think about this world differently. So to your point, a shift in mindset, there are very few moments where you get this pronounced change and everyone is going through it all at the same time. So that creates an opportunity, a scenario where you're bold thinking new strategies, creativity. Bringing people in in new ways, collaborating in new ways and offer a lot of benefits. More practically speaking and from my experience, building technology for a couple decades, it has an interesting parallel to building tightly coupled, really large maybe monoliths versus microservices and the debate around, "Do we build small things "that can be reconfigured and built out by others "or built upon by others more easily? "Or do we create a golden path and a more understood development environment?" And I'm not here to answer the question of which one's better because that's still a raging debate. But I can tell you that the process of going through and taking a service or an application or a thing that we want to deliver to a customer, that one of our customers wants to deliver to their customer. And thinking about it so comprehensively that you're able to think about it in, what are its core functions? And then thinking methodically about how to enable those core functions. That's a real opportunity, and I think technology to your point is getting to the place where if you want to run across multiple clouds, this is the Anthos conversation were recently GA'ed. Global scale platform, multicloud platform, that's a pretty big moment in technology. And that opens up the aperture to think differently about architectures and that process of taking an application service and making it real. >> Well, I think you're right on the money. I think philosophically, it's a flashpoints opportunity. I think that's going to prove to be accelerating and to see people win faster and lose faster. You're going to to see that quickly happen. But to your point about the monolith versus service or decoupled based systems, I think we now live in a world where it's a systems view now. You can have a monolith combined with decoupled systems. That's distributed computing. I think this is the trend, it's a system. It's not one thing or the other. So I think the debate will continue just like VI versus Emacs (chuckles). We don't know, right? People are going to have the debate, but if you think about it as a system, the use case defines your architecture. That's the beautiful thing about the cloud. So great insight, I really appreciate it. And how's everything going over there at Google Cloud? You've got Meet that's available. How's your staff? What's it like inside the Googleplex and the Google Cloud team? Tell us what's going on over there. People still working, working remote? How's everyone doing? >> Well, as you can tell from my scenario here, my backdrop, yes, still part at work. And we take this as a huge responsibility. These moments as a huge responsibility because there are educators, loved ones, medical professionals, critical life services that run on services that Google provides. And so I can tell you we're humbled by the opportunity to provide the backbone and the platform and the people and the curiosity and the sincere desire to help. And I mentioned a couple of ways already just in this conversation where we've been able to leverage some of our investments technology to help form people that really gets at the root of who we are. So while we just like any other humans are going through a process of understanding our new reality, what really fires us up and what really charges us up is because this is a moment where what we do really well is very, very important for the world in every geo, in every vertical, in every use case, in every solution type. We're taking that responsibility very seriously. And at the same time, we're trying to make sure that all of our teams as well as all of the teams that we work with and our customers and partners are making it through the human moment, not just the technology moment. >> Well, congratulations and thanks for spending the time. Great insight, Will. Appreciate, Will Grannis, managing director, head of technology office of the CTO at Google Cloud. This certainly brings to the mainstream what we've been in the industry been into for a long time, which is DevOps, large scale, role of data and technology. Now we think it's going to be even more acute around societal benefits. And thank God we have all those services for the frontline workers. So thank you so much for all that effort and thanks for spending the time here in theCUBE Conversation. Appreciate it. >> Thanks for having me, John. >> Okay, I'm John Furrier here in Palo Alto studios for remote CUBE Conversation with Google Cloud, getting the update. Really looking at the future as it unfolds. We are going to see this moment in time as an opportunity to move to the next level, cloud-native and change not only the tech industry but society. I'm John Furrier, thanks for watching. (upbeat music)

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation run welcome to this cube conversation I'm John Fourier with the cube host the cube here in our Palo Alto office for remote interviews during this time of covin 19 we're here with the quarantine crew here in our studio we got a great guest here from Google we'll Grannis managing director head of the office of the CTO with Google cloud thanks for coming on we'll appreciate you you spend some time with me Oh John's great to be with you and as you said in these times more important than ever to stay connected yeah and I'm really glad you came on because a couple things one congratulations to Google cloud for the success you guys had so a lot of big wins under your belt both on the momentum side on the business side but also on the technical side meat is available now for folks anthos is doing very very well partner ecosystem is developing got some nice used cases in vertical marker so I want to get in and unpack with you but really the bigger story here is that the world has seen the future before was ready for it and that is the at scale challenge that the Cova 19 has shown everyone we're seeing you know the future has been pulled forward we're living in a virtualized environment it's funny to say that virtualization has a server virtualization is a tech term but that enabled a lot of things we're living in a virtualized world now because we have to but this is gonna set in motion a series of new realities that you guys have been experiencing and supporting for many many years but now as a provider of Google cloud you guys have to operate at scale you have and now the whole world realizes that scale is a big deal and so you guys have had some successes I want to get your thoughts on the this at scale problem that the world now realizes I mean everyone's at home that's a disruption that was unfortunate whether it's under provisioning VPNs NIT to a surface area for security to just work and play and activities are now confined so people aren't convening anymore and it's a huge issue what's your take on all this well I mean to your point just now the fact that we can have this conversation we can have it blue idli from our respective remote locations just goes to show you the power of information technology that underlies so many of the things that we say and for Google Cloud this is not a new thing and for Google this is not a new thing for Google cloud we add a mission of trying to help companies accelerate their transformation and enable them in these new digital environments and so many companies that we've been working with they've already been on the path to operating an environments that are digital that are fluid and you think about the cloud that's one of the great benefits loud is that scalability income with the business demand and it also helps the scale situation without having to you know do the typical what you need to find the procurement people we need to find server vendors we need to get the storage lined up it really allows a much more fluid response to unexpected and unfortunate situations whether that's customer demand or you know in this case the global endemic yeah one of the things I want to get in with you I want to get you have explained your job is there because I see Google's got a new CEO now for over a year Tom's Korean came from Oracle knows the enterprise up and down you had Diane Greene before that again another enterprise leader Google Cloud has essentially rebuilt itself from the original Google cloud to be very enterprise centric you guys have great momentum and and this is a world where cloud native is going to be required I mean everyone now sees it the the tide has been pulled out there everything's exposed all the gaps in business from a tech standpoint it's kind of exposed and so the smart managers and companies are looking at things and saying double down on that let's kill that we don't want to pay that supplier they're not core to our business this is going to be a very rapid acceleration of what I call a vetting of the new the new set of players that are going to emerge because the folks who don't adapt to this new cloud native reality whether it's app workloads for banking to whatever they're gonna have to have to reinvent themselves now and reset and tweek to come out of this crisis so it's gonna be very cloud native this is a big deal can you share your your reaction to that absolutely and so as you pointed out there are kind of two worlds that exist right now companies that are moving to become more digital and transform and you mentioned the momentum I mean in Google cloud just over the last year greater than 50 percent revenue growth and you know and I greater than 10 billion dollar run rate business and adding customers that are really quick flip you know including you know just yesterday slung and you know along the way Telecom Italia Major League Baseball Vodafone Lowe's Wayfarer Activision Blizzard's so this is not you this transformation and this digitization is not just for you know a few or just for any one industry it's happening across the board and then you add that to the implementations that have been happening across you know Shopify and the Spotify and HSBC which was a early customer of ours in the cloud and it you know already has a little bit of a head start of this transformation so you see these new companies coming in and seeing the value of digital transformation and then these other companies that have kind of lit the path for others to consider and you know Shopify is a really good example of how seeing you know drastic uptick in demand they're able to responding you know roughly half a million shops up and running you know during a period of time where many retailers are trying to figure out how to stay online or you can get online well what is your role at Google I see you're the managing director title is managing director ahead of the office of the CTO we've seen these roles before you know head of this CTO you're off see technical role is it partnering with the CEO on strategy is it you kick tire kicking new things are you overseeing any strategic initiatives what is what is your role so a little bit of all those things combined into one so I I spent the first couple decades of my career on the other side of the in the non-tech you know community no in the enterprise where we were still building technology and we were still you know digitally minded but not the way that people view technology in Silicon Valley and so you know spending a couple decades in that environment really gave me insights into how to take technology and apply them to a specific problem and when I came to Google five years ago yeah selfishly it was because I knew the potential of Google's technology having been on the other side and I was really interested in forming a better bridge between Google's technology and people like me who were CTOs of public companies and really wanted the leverage that technology for problems that I was solving whether it was aerospace public sector manufacturing what-have-you and so it's been great it's the it's the role of a lifetime I've been able to build the team that I wanted as an enterprise technologist for decades and the entire span of technologies at our disposal and we do two things one is we help our most strategic customers accelerate their path loud and 2 we create these signals by working with the top companies moving to the cloud and digitally transforming we learned so much John about what we need to build as an organization so it also helps balance out the Google driven innovation with our customer driven innovation yeah and I could I can attest that we didn't watching you guys from the from day one hired a lot of great enterprise people that I personally know so you getting the enterprise chops and staff and getting you seeing some progress I have to ask you though because I first of all a big fan of Google at the scale from knowing them from when they were just a little search engine to what they are now the there was an expression a few years ago I heard from enterprise customers it was goes along the lines like this I want to be like Google because you guys had a great network you had large-scale you've had all these things that were like awesome and then they realized what we can't be like Google we don't have that sorry we don't have large-scale data centers so there was a little bit of a translation and I want to say a little bit of a overplay of the Google hand and you guys had since realized that you didn't it wasn't just people gonna bang your doorstep and be adopting Google cloud because there was a little bit of a cultural disconnect from wanting to be like Google then leveraging Google in their business as they transform so as you guys have moved from that what's changed they still want to be like Google in the sense you have great security got a great network you got that scale and it prizes a little bit slower to adopt that which you're focused on now what is that the story there because I think that's kind of the theme that I'm hearing okay Google now understands me they know I'm not as fast as Google they got super great people we are training our people we're treating you know retrain them this is the transformation that they're going through so you might be a little bit ahead of them certainly but now they need to level up how do you respond to that well a lot of this is the transformation that Thomas has been enacting you know over the last year plus and it comes in kind of three very operation or technical pillars that I think the first we expanded our customer and we continue to expand our customer facing themes you know three times what they were before because we need to be there we need to be in those situations we need to hear from the customer mean to learn more about the problems they're trying to solve so we don't just take a theoretical principle and try to overlay it onto a problem we actually get very visceral understanding of what trying to solve but you have to be there the game that empathy and that understanding and so one is showing up and that you know has been mobilizing a much larger engine the customer facing out personnel from Google second it's also been really important that we evolve our own you know just as Google brought sre principles and principles of distributed systems and software design out for the world we also had a little bit to learn about transitioning from typical customer support and moving to more customer experience so you've seen you know that evolution under on this as well with cloud changing you know moving from talking about support to talking about customer experience that white glove experience that our customers get our partners get from the beginning of their journey with us all the way through and then finally making sure that our product roadmap has the solutions that are relevant across be priority industries for us and you know that's again that only comes from being present from having a focus in those industry and then developing the solutions that progress those companies so again not this isn't about taking you know a principle and trying to apply it blindly this is about adding that connection that really deep connections to our customers and our partners and letting that connection manifest the things that we have to do as a product company the best support them over a long period some of these deals we've been announcing these are 10-year five-year multi-year strategic partnerships they go across the campus of you know all of you and you know those are the really exciting scaled partnerships but you know to your point you can't just take SR re from Google and apply it to company X but you can take things like error budgets or how we think about the principles of sree and you can apply them over the course of developing technology collaborating innovating together yeah and I think cloud native is gonna be a key thing and yeah I think what it's just my opinion but I think one of those situations where the better mousetrap will win if your cloud native and you have api's and you have the kind of services that people will will know beaded to your doorstep so I have to ask you with Thomas Korean on board obviously we've been following his career as well at Oracle he knows what he's doing comes in to Google it's being built out it's like a rocket ship at this point what bet is he making and what bet are you guys making on behalf of your customers what's the if you have to boil it down to Google clouds big bet what is the bet on the technology side and what's the bet on the business side sure well I've already mentioned you know I've already Internet's you know the big strategy that Thomas is brought in and you know that is the that's again those three pillars making sure that we show up and that we're present by having a scaled customer facing organization and making sure that we transitioned from you know a typical support mindset into more of customer experience mindset and then making sure that those solutions are tailored and available for our priority industries if I was to add you know more color to that I think one of the most important changes that Thomas has personally been driving as he's been converting us to a partner LED is and a partner led organization and this means a lot of investments in large mobile systems integrators like Accenture and Deloitte but this also means that like the Splunk announcement from yesterday that isn't just the cell >> this is a partnership it goes deep across go-to-market product and self do and then we also bring in very specific partners like Temenos in Europe for financial services or a SATA or a rack space for migrations and as a result the already we're seeing really incredible lifts so for example nearly 200 percent year-over-year increase in partner influenced revenue Google cloud and almost like a 13 X year-over-year increase in new customers one-bite partners that's the kind of engine that builds a real hyper scale does it's just saying you mentioned Splunk I want to get that in a second but I also notice there was a deal with Dallas group on ECM subscriptions which kind of leads me into the edge piece there's a real edge component here with Google cloud and I think I'd Akashi edge with Jennifer Lynn a few years ago really digging into the built-in security and the value of the Google Network I mean a lot of the scuttlebutt around the valley and the industry is you know Google's got an amazing network store a software-defined networking is gonna be a hot program programmable area so you got programmable networking and you got edge and edge security these are killer areas that need innovation could you comment on what you guys are doing there and do you agree I'm out see with you have a killer Network and you're leveraging it what's the can you just give some insight into what's going on those those two areas network and then the edge yeah I think what you're seeing is the manifestation of an of the progression of cloud generally what do I mean by that you know started out as like get everything to the data center you know we kind of had this thought that maybe we could take all the workloads and we could get them to these centralized hubs and they could redistribute out the results and you know drive the latency down over time so we span the portfolio of applications and services that would be relevant over time and what we've seen over the last decade really in cloud is an evolution >> more of a layered architecture and that layered architecture includes you know poor data centers that includes CDN capacity points of presence that includes edge and just in that list of customers over the last year I there were at least three or four telcos in there and you've also probably heard and seen quite a bit of telco momentum coming from asks in recent announcements I think that's an indication that a lot of us are thinking about how can we pick big technology like anthos for example and how could we orchestrate workloads create a common control play and you know manage services across those three shells if you will of the architecture and that's a that's a very strategic and important area for us and I think generally for the cloud industry easy it was expanding beyond the data center as the place where everything happens and you can look at you know Google Phi you look at stadia you can look at examples within Google they go well beyond cloud as to how we think about new ways to leverage that kind of creature all right so we saw some earnings come out on Amazon side as Google both groups and Microsoft well all three clouds are crushing it on the cloud side that's a tailwind I get that but as it continues we're expecting post kovat some you know redistribution of development dollars and projects whether it's IT going cloud native or whatever new workloads we are predicting a Cambrian explosion of new things from core to edge and this is gonna create some lift so I want to get your thoughts on you guys strategy with go-to market as well as your customers as they now have the ability to build workloads and apps with ai and data there seems to be a trend towards the vertical ization of whether its sales and go to market and/or specialism because you have horizontal scalability with cloud and you now have data that has distinct value in these verticals so it really seems to be a I won't say ratification but in a way that seems to be the norm whether you come into a market you have specialization but the date is there so apps can be more agile do you are you guys seeing that and is that something that you guys are considering from from an organization standpoint and how do customers think about targeting vertical industries and their customers yeah I I bring this to and where you started going there at the end of the question is exactly the way that we think about it as well which is we've moved from you know here are storage offers for everybody and here's you know basic infrastructure everybody and now we've said how can we make sure that we have solutions that are tailored with very specific problems that customers are trying to solve and we're getting to the point now where your performance and variety of technologies are available to be able to compose very specific solutions and if you think about the substrate that has to be there you know we mentioned you have to have some really great partners and you have to have you know roadmap that is focused on priority solution area so for example at Google cloud you know we're very focused on six priority vertical areas so retail financial services health care manufacturing and industrials health care life sciences public sector and you know as a result of being very focused in those areas we can make more target investments and also align our entire go-to-market system and our entire partner ecosystem ecosystem around those beers specific priority areas so for example we worked with SATA and HDA Healthcare Rob very recently to develop and maintain a national response portal Berko vat19 and that's to help better inform communities and hospitals we can use looker to help with like a Commonwealth Care Alliance on nonprofit and that helps monitor patient system symptoms and risk factors so you know we're using you know a very specific focus in healthcare and a partner ecosystem - you know ferry tailored solutions you know you can also look at I mentioned Shopify earlier that's another great example of how in retail they can use something like Google meat inherent reliability scalability security to connect their employees during these interesting times but then they can also use GCP at Google cloud platform to scale out and as they come up with new apps and experiences for their shoppers for their shops they can rapidly deploy to your point and those you know those solutions and you know how the database performs and how those tiers perform you that's a very tight-knit feedback loop with our engineering teams yeah one of the things I'm seeing obviously with the virtualization of the kovat is that you know when the world gets back to normal it'll be hybrid and it'll be a hybrid between reality not physical and 100% virtual hybrid and that's going to impact events to media to everything every vertical will be impacted and I want to point out the Splunk team bring that back in because I want you to comment on the relevance of the Splunk to you and in context to Splunk has a cloud they got a great slogan data for every everywhere everywhere dated to everywhere I think it is but the cube we have a cloud every company will have a cloud scale at some level will progress to having some sort of cloud because they have data how are you guys powering those clouds because I think the Splunk deal is interesting their partner their stock price was up out on the news of the deal a nice bump their first Blunk shout out to those guys but they're a data company now they're cross-platform but they're not Google but they have a cloud so you know saying so they need to play in all the clouds but they need infrastructure they need support so how do you guys talk to that customer and that says hey the next pandemic that comes the next crisis that's going to cause some either social disruption or workflow disruption or work supply chain disruption I need to be agile I need have full cloud scale and so I need to talk to Google what do you say to them what's the pitch and as does a Splunk deal Samir some of those capabilities or tie that together for us the spunk deal and how it relates to sure for example proof themselves for the future sorry for example with the cloud deal you take a look at what Google is already really good at data processing at scale log analytics you take a look at what Splunk is doing you know with their events and security incident monitoring and the rest it a really great mashup because they see by platforming on Google cloud not only they get highly performant infrastructure but they also get the opportunity to leverage data tools data analytics tools machine learning and AI that can help them provide enhance services so not just about acity going up and down your periods of band but also enhancing services and continuing to offer more value to their customers and we see that you know it's a really big trend and you know this gets it something you know John a little bit bigger which is the two views of the world and we talked about very tailored focused solutions Splunk is an example of making a very methodical approach to a partnership developing a solution specifically you know with partners and you know in this case Splunk on the security event management side but we're always going to provide our data processing platform our infrastructure for companies across many different industries and I think that addresses one part of the topic which is you know how do we make sure that in periods of demand rapidly changing this deals back to the foundational elements of like AI infrastructure as a service and elasticity and we're gonna provide a platform infrastructure that can help companies move through periods of you know it's hard to forecast and/or demand may rise and fall you know in very interesting ways but then there's going to be funds where you know we we because they're not a necessarily a focused use case where it may just be generalized platform versus a focused solution so for example like in the oil and gas industry we don't develop custom AI ml solutions the facility upstream extraction for example but what we do do is work with renewable energy companies to figure out how they might be able to leverage some of our AI machine learning algorithms from our own data centers to make their operations more efficient and to help those renewable energy companies learn from what we've learned building out the but I consider to be a world leading renewable energy strategy and so classic and able mint model where you're enabling your platform for your customers okay so I got to ask the question I asked this to the Microsoft guys as well because Amazon you know has their own sass stuff but but really more of an tend the better products usually on the ecosystem side you guys have some killer sass cheap tree-sweet where customer if we use the g sqweep really deeply we also use some BigTable as well I want to build a cloud we have a cloud cube cloud but you guys have meat so I want to build my product on Google cloud how do I know you're not going to compete with me do you guys have those conversations around the trade-off between you know the pure Google services which provide great value for the areas where the ecosystem needs to develop those new areas that are gonna be great markets potentially huge markets that are out there well this is the power of partnership I mentioned earlier that one of the really big moves that Thomas is made has been developing a sense of partners and it kind of blurs the line between traditional what you would call a customer what you would call a partner and so having a really strong sense of which industries were in which we prioritize Plus having a really strong sense of where we want to add value and where you know our customers and partners want to add that value that's that's the foundational that's the beginning of that conversation that you just mentioned it's important that we have an ability to engage not just in a you know here's the cloud infrastructure piece of the puzzle but one of the things Thomas has also done in the East rata jia is has been to make sure that you know the Google cloud relationship is also a way to access all amazing innovation happening across all of Google and also help bring a strategic conversation in that includes multiple properties from across Google so that an HSBC and Google and have a conversation about how to move forward together that is comprehensive rather than you know having to wonder and have that uncertainty sit behind the projects that we're trying to get out and have high velocity on because they offer so much to retail bank for example well I got a couple more questions and then I'll let you go I know you got some other things going I really appreciate you digging the time sharing this great insight and updates as a builder you've been on the other side of the table now you're at Google heading up the CTO I was working with Thomas understanding them go to market across the board and the product mix as you talk to customers and they're thinking the good customers are thinking hey you know I want to come out of this Cove in on an upward trajectory and I want to use this opportunity to reset and realign for the future what advice do you have for those enterprises there could be small medium sized enterprises to the full large big guys and obviously cloud native we talked some of that already but what advice would you have for them as they start to really prioritize as some things are now exposed the collaboration the tooling the scale all these things are out there what have you seen and what advice would you give a CX o or C so or leader in the industry to think about and how they should come out of this thing how they should plan execute and move forward well I appreciate the question because this is the crux of most of my day job which is interacting with the c-suite and boards of you know companies and partners around the world and they're obviously very interested to learn or you know get a data point from someone at Google and the the advice generally goes in a couple of different directions out one collaboration is part of the secret sauce that makes Google what it is and I think you're seeing this right now across every industry and it you know whether you're a small medium-sized business or you're a large company if the ability to connect people with each other to collaborate in very meaningful ways to share information rapidly to do it securely with high reliability that that's the foundation that enables all of the projects that you might choose to you know applications to build services to enable actually succeed in production and over the long haul is that culture of innovation and collaboration so absolutely number one is you're having a really strong sense of what they want to achieve from a cultural perspective a collaboration perspective and the and the people because that's the thing that fuels everything else second piece of the you know advice especially in these times where there's so much uncertainty is where can you buy down uncertainty with vets that aren't you know that art you can you can learn without a high penalty and this is a this is why cloud I think is really really you know finding you know super scale it was our it was already on the rise but what you're seeing now and you know as you've linked back to me during this conversation we're seeing the same thing which is a high increase in demand of let's get this implemented now how can we do this more this is you know clearly one way to move through uncertainty and so look for those opportunities I'll give you a really good example mainframes one of the classic workloads of the you know on-premise enterprise and you know there's all sorts of there are all sorts of potential magic solves for getting mainframes to the cloud and getting out of mainframes but a practical consideration might be maybe you just front-end it with some Java or maybe you just get closer to other data centers within a certain amount of milliseconds that's required to have performant workload maybe you start chunking at a part and treat the workload a little bit differently rather than you know just one thing but there are a lot of years and investments in a workload that might run on a mainframe and that's a perfect example of out you know biting off too much it might be a little bit dangerous but there is a path to and so for example like we brought in a company called cornerstone to help with those migrations but we also have you know partnerships with you know data center providers and others globally from us our own built infrastructure to allow even you know a smaller stuff per site or more like post proximity location in the workload it's great you know everything had as a technical metaphor connection these days when you have a Internet digitally connected world we're living in you know the notion of a digital business was a research buzzword that's been kicked around for years but I think now kovat 19 you're seeing the virtual or digital it's really digital but you know virtual reality augmented reality is going to come fast to really get people to go WOW virtual virtualization of my business so you know we've been kind of kicking around this term business virtualization just almost as a joke but it's really more about okay this is about a new world a new opportunity to think about when we come out of this we're gonna still go back to our physical world now the hybrid now kicks in this kind of connects all aspects of business in every verticals not leahey I'm targeting like the this industry so there might be unique solutions in those industries but now the world is virtualized it's connected it's a digital environment these are huge concepts that I think has kind of been a fringe lunatic fringe idea but now it's brought mainstream this is gonna be a huge tailwind for you guys as well as developers and entrepreneurs and app application software this is gonna be we think a big thing what's your reaction to that which your based on your experience what do you see happening do you agree with it and you have any thing you might want to add maybe you know one kind of philosophical statement and then one more you know I bruised my shins a lot in this world and maybe share some of the black and blue coloration first from a philosophical standpoint the greater the crisis the more open-minded people become and the more creative people get and so I'm really excited about the creativity that I'm seeing you know with all of the customers that I work with directly plus our partners you know Googlers everybody's rallying together to think about this world differently and so to your point you know a shift in mindset you know there are there are very few moments where you get this pronounced a change and everyone is going through it all at the same time so that creates a you know an opportunity a scenario where the old thinking new strategies creativity you know bringing people in in new ways collaborating a new way and offer a lot of benefits more you know practically speaking and from my experience you know building technology for a couple decades you this is a it has an interesting parallel to you know building like tightly coupled really large maybe monoliths versus micro services and debate around you know do we build small things that can be reconfigured and you know built out by others or built on by others more easily or do we credit Golden Path and a more understood you know development environment and I'm not here to answer the question of which one's better is that's what's still a raging debate and I can tell you that the process of going through and taking a service or an application or a thing that we want to deliver the customer that one of our customers wants to deliver to their cost and thinking about it so comprehensively that you're able to think about it in its what its power its core functions and then thinking methodically about how to enable those core functions that is a you know that's a real opportunity and I think technology to your point is getting to the place where you know if you want to run across multiple clouds yeah this is the anthos conversation where you know recently g8 you know a global scale platform you know multi cloud platform that's a pretty big moment in technology and that opens up the aperture to think differently about architectures and that process of taking you know an application service and making it real well I think you're right on the money I think philosophically it's a flashpoints opportunity I think that's going to prove to be accelerating gonna see people win faster and lose faster you can see that quickly happen but to your point about the monolith versus you know service or decoupled based systems I think we allow a live in a world where it's a systems of you now you can have a monolith combined with decoupled systems that's distributed computing I think this is that the trend it's a system it's not one thing or the other so I think the debate will continue just like you know VI versus Emacs we know you don't know right so you know if people gonna have this debate but it's just if you think about as a system the use case defines the architecture that's the beautiful thing about the cloud so great insight I really appreciate it and how's everything going over there Google Cloud you got meat that's available how's your staff what's it like inside the Googleplex and the Google cloud team tell us what's going on over there people still working working remote how's everyone doing well as you can as you can tell from my scenario here my my backdrop yes still hard at work and we take this as a huge responsibility you know these moments is a huge responsibility because there are you know educators loved ones medical professionals you know critical life services that run on services that Google provides and so I can tell you were humbled by the opportunity to provide you know the backbone and the platform and the people and the curiosity and the sincere desire to help and I mentioned a couple of ways already just in this conversation where we've been able to leverage some of our investment in technology to help or people that really gets at the root of who we are so while we just like any other humans are going through a process of understanding our new reality what really fires us up and what really a chart is because is that this is a moment where what we do really well is very very important for the world in every geo in every vertical in every use case and every solution type so we're just take we're taking that responsibility very seriously and at the same time we're trying to make sure that you know all of our teams as well as all the teams that we work with our customers and partners are making it a human moment not just the technology moment well congratulations and thanks for spending the time great insight will appreciate will Grannis Managing Director head of Technology office of the CTO at Google cloud this certainly brings to the mainstream what we've been in the industry been into for a long time which is DevOps large-scale role of data and technology now we think it's going to be even more acute around societal benefits and thank God we have all those services for the frontline workers so thank you so much for all that way effort and thanks for spending the time here in the cube conversation appreciate it thanks for having John okay I'm John Farah here in Palo Alto Studios for remote cube conversation with Google cloud get in the update really looking at the future as it unfolds we are going to see this moment in time as an opportunity to move to the next level cloud native and change not only the tech industry but society I'm John Fourier thanks for watching

>>long from Las Vegas. It's the Q covering a ws re invent 2019. Brought to you by Amazon Web service is and in along with its ecosystem partners. >>Hey, welcome back to the Cube. Lisa Martin at AWS Reinvent 19. This is Day three of the Cubes coverage. We have two sets here. Lots of cute content are joined by Justin Warren, the founder and chief analyst at Pivot nine. Justin. How's it going? Great, right? You still have a voice? Three days? >>Just barely. I've been I've been trying to take care of it. >>Impressed. And you probably have talked to at least half of the 65,000 attendees. >>I'm trying to talk to as many as I can. >>Well, we're gonna talk to another guy here. Joining us from data ICU is well, Novak, the solutions architect will be the Cube. >>Thanks for having me. >>You have a good voice too. After a three day is that you >>have been doing the best I can. >>Yeah, he's good. So did ICU. Interesting name. Let's start off by sharing with our audience. Who did a coup is and what you guys do in technology. >>Yes. So the Entomology of date ICU. It's like hi cooze for data. So we say we take your data and, you know, we make poetry out of it. Make your data so beautiful. Wow, Now, But for those who are unaware Day like it was an enterprise data science platform. Eso we provide a collaborative environment for we say coders and clickers kind of business analyst and native data scientists to make use of organizations, data bill reports and Bill productive machine learning base models and deploy them. >>I'm only the guy's been around around for eight years. Eight years. Okay, >>so start up. Still >>mourning the cloud, the opportunity there That data is no longer a liability. It's an asset or should be. >>So we've been server based from the start, which is one of our differentiators. And so by that we see ourselves as a collaborative platform. Users access it through a Web browser, log into a shared space and share code, can share visual recipes, as we call them to prepare data. >>Okay, so what customers using the platform to do with machine learning is pretty hot at the moment. I think it might be nearing the peak of the life cycle pretty hot. Yeah, what a customer is actually actually doing on the platform, >>you know, So we really focus on enabling the enterprise. So, for example, G has been a customer for some time now, and Sergey is a great prototypical example on that. They have many disparate use cases, like simple things like doing customer segmentation for, you know, marketing campaigns but also stuff like Coyote predicted maintenance. So use cases kind of run the gamut, and so did ICU. Based on open source, we're enabling all of G's users to come into a centralized platform, access their data manipulated for whatever purposes. Maybe >>nobody talked about marketing campaigns for a second. I'm wondering. Are, is their integration with serum technologies? Or how would a customer like wanting to understand customer segmentation or had a segment it for marketing campaign? How would they work in conjunction with a serum and data ICU, for example? >>It's a great question. So again, us being a platform way sit on a single server, something like an Amazon ec2 instance, and then we make connections into an organization's data sources. So if using something like Salesforce weaken seamlessly, pull in data from Salesforce Yuka manipulated in date ICU, but the same time. Maybe also have some excel file someone you know me. I can bring that into my data to work environment. And I also have a red shift data table. All those things would come into the same environment. I can visualize. I can analyze, and I can prepare the data. I see. >>So you tell you it's based on open source? I'm a longtime fan of over. It's always been involved in it for longer than I care to remember. Actually, that's an interesting way t base your product on that. So maybe talk us through how you how you came to found the company based on basic an open source. What? What led to that choice? What? What was that decision based on? >>Yeah, for sure. So you talked about how you know the hype cycle? A. I saw how hot is a I and so I think again, our founders astutely recognize that this is a very fast moving place to be. And so I'm kind of betting on one particular technology can be risky. So instead, by being a platform, we say, like sequel has been the data transformation language do jour for many days now. So, of course, that you can easily write Sequel and a lot of our visual data Transformations are based on the sequel language, but also something like Python again. It's like the language de jour for machine law machine learning model building right now, so you can easily code in python. Maintain your python libraries in date, ICU And so by leveraging open source, we figured we're making our clients more future proof as long as they're staying in date ICU. But using data ICU to leverage the best in breed and open source, they'll always be kind of where they want to be in the technological landscape by supposed to locked into some tech that is now out of date. >>What's been the appetite for making data beautiful for a legacy enterprise, like a G E that's been around for a very long time versus a more modern either. Born in the Cloud er's our CEO says, reborn in the cloud. What are some of the differences but also similarities that you see in terms of we have to be able to use emerging tech. Otherwise someone's gonna come in behind us and replace us. >>Yeah, I mean, I think it's complicated in that there's still a lot of value to be had in someone says, like a bar chart you can rely on right, So it's maybe not sexy. But having good reporting and analytics is something that both you know, 200 year old enterprise organizations and data native organizations startups needs. At the same time, building predicted machine learning models and deploying those is rest a p i n points that developers can use in your organization to provide a data driven product for your consumers. Like that's amore advanced use case that everyone kind of wants to be a part of again data. Who's a nice tool, which says Maybe you don't have developers who are very fluent in turning out flashed applications. We could give you a place to build a predictive model and deploy that predictive model, saving you time to write all that code on the back end. >>One of the themes of the show has been transformation, so it sounds like data ICU would be It's something that you can dip your toes in and start to get used to using. Even if you're not particularly familiar with Time machine learning model a model building. >>Yeah, that's exactly right. So a big part of our product and encourage watchers to go try it out themselves and go to our website. Download a free version pretrial, but is enablement. So if you're the most sophisticated applied math PhD there is, like, Who's a great environment for you to Code and Bill predictive models. If you never built the machine learning model before you can use data ICU to run visual machine learning recipes, we call them, and also we give you documentation, which is, Hey, this is a random forest model. What is a random forest model? We'll tell you a little bit about it. And that's another thing that some of these enterprises have really appreciated about date I could. It is helping up skill there user base >>in terms of that transformation theme that Justin just mention which we're hearing a lot about, not visit this show. It's a big thing, but we hear it all the time, right? But in terms of customers transformation, journey, whatever you wanna call it, cloud is gonna be an essential enabler of being able to really love it value from a I. So I'm just wondering from a strategic positioning standpoint. Is did ICU positioned as a facilitator or as fuel for a cloud transformation that on enterprise would undergo >>again? Yes, great point. So for us, I can't take the credit. This credit goes to our founders, but we've thought from the start the clouds and exciting proposition Not everyone is. They're still in 2019. Most people, if not all of them, want to get there. Also, people want too many of our clients want the multi cloud on a day. Like who says, If you want to be on prim, if you want to be in a single cloud subscription. If you want to be multi cloud again as a platform, we're just gonna give you connection to your underlying infrastructure. You could use the infrastructure that you like and just use our front end to help your analyst get value. They can. I >>think I think a lot of vendors across the entire ecosystem around to say the customer choice is really important, and the customers, particularly enterprise customers, want to be able to have lots of different options, and not all of them will be ready to go completely. All in on cloud today. They made it may take them years, possibly decades, to get there. So having that choice is like it's something that it would work with you today and we'll work with you tomorrow, depending on what choices you make. >>It's exactly right. Another thing we've seen a lot of to that day, like who helps with and whether it's like you or other tools. Like, of course, you want best in breed, but you also want particularly for a large enterprise. You don't want people operating kind of in a wild West, particularly in like the ML data science space. So you know we integrate with Jupiter notebooks, but some of our clients come to us initially. Just have I won't say rogues that has a negative connotation. But maybe I will say Road road data Scientists are just tapping into some day the store. They're using Jupiter notebooks to build a predictive model, but then to actually production allies that to get sustainable value out of it like it's to one off and so having a centralized platform like date ICU, where you can say this is where we're going to use our central model depository, that something where businesses like they can sleep easier at night because they know where is my ML development happening? It's happening in one ecosystem. What tools that happening with, well, best in breed of open source. So again, you kind of get best of both worlds like they like you. >>It sounds like it's more about the operations of machine learning. It is really, really important rather than just. It's the pure technology. Yes, that's important as well, and you need to have the data Sinus to build it, but having something that allows you to operationalize it so that you can just bake it into what we do every day as a business. >>Yeah, I think in a conference like this all about tech, it's easy to forget what we firmly believe, which is a I and maybe tech. More broadly, it's still human problems at the core, right? Once you get the tech right, the code runs corrected. The code is written correctly. Therefore, like human interactions, project management model deployment in an organization. These are really hard, human centered problems, but so having tech that enables that human centric collaboration helps with that, we find >>Let's talk about some of the things that we can't ever go to an event and not talk about. Nut is respected data quality, reliability and security. Understood? I could facilitate those three cornerstones. >>Yeah, sure. So, again, viewers, I would encourage you to check out the date. ICU has some nice visual indications of data quality. So an analyst or data scientists and come in very easily understand, you know, is this quality to conform to the standards that my organization has set and what I mean by standards that could be configured. Right? So does this column have the appropriate schema? Does it have the appropriate carnality? These are things that an individual might decide to use on then for security. So Data has its own security mechanisms. However, we also to this point about incorporating best Retek. We'll work with whatever underlying security mechanisms organizations organizations have in place. So, for instance, if you're using a W s, you have, I am rolls to manage your security. Did ICU comport those that apply those to the date ICU environment or using something like on prime miss, uh, duke waken you something like Kerberos has the technology to again manage access to resources. So we're taking the best in breed that this organization already has invested time, energy and resources into and saying We're not trying to compete with them but rather were trying to enable organizations to use these technologies efficiently. >>Yeah, I like that consistency of customer choice. We spoke about that just before. I'm seeing that here with their choices around. Well, if you're on this particular platform will integrate with whatever the tools are there. People underestimate how important that is for enterprises, that it has to be ahead. Virginia's environment, playing well with others is actually quite important. >>Yeah, I don't know that point. Like the combination of heterogeneity but also uniformity. It's a hard balance to strike, and I think it's really important, giving someone a unified environment but still choice. At the same time. A good restaurant or something like you won't be able to pick your dish, but you want to know that the entire quality is high. And so having that consistent ecosystem, I think, really helps >>what are, in your opinion, some of the next industries that you see there really right to start Really leveraging machine learning to transfer You mentioned g e a very old legacy business. If we think of you know what happened with the ride hailing industry uber, for example, or fitness with Saletan or pinchers with visible Serge, what do you think is the next industry? That's like you guys taking advantage of machine learning will completely transform this and our lives. >>I mean, the easy answer that I'll give because it's easy to say it's gonna transform. But hard to operationalize is health care, right? So there is structured data, but the data quality is so desperate and had a row genius s, I think you know, if organizations in a lot of this again it's a human centered problem. If people could decide on data standards and also data privacy is, of course, a huge issue. We talked about data security internally, but also as a customer. What day to do I want you know, this hospital, this health care provider, to have access to that human issues we have to result but conditional on that being resolved that staring out a way to anonymous eyes data and respect data privacy but have consistent data structure. And we could say, Hey, let's really set these a I M L models loose and figure out things like personalized medicine which were starting to get to. But I feel like there's still a lot of room to go. That >>sounds like it's exciting time to be in machine learning. People should definitely check out products such as Dead Rock you and see what happens. >>Last question for you is so much news has come out in the last three days. It's mind boggling sum of the takeaways, that of some of the things that you've heard from Andy Jassy to border This'll Morning. >>Yeah, I think a big thing for me, which was something for me before this week. But it's always nice to hear an Amazon reassures the concept of white box. Aye, aye. We've been talking about that a date ICU for some time, but everyone wants performance A. I R ml solutions, but increasing. There's a really appetite publicly for interpret ability, and so you have to be responsible. You have to have interpret belay I and so it's nice to hear a leader like Amazon echo that day like you. That's something we've been talking about since our start. >>A little bit validating them for data ICU, for sure, for sure. Well, thank you for joining. Just to be on the kid, the suffering. And we appreciate it. Appreciate it. All right. For my co host, Justin Warren, I'm Lisa Martin and your work to the Cube from Vegas. It's AWS reinvent 19.

>>live from Washington, D. C. It's the Cube covering Bumi World >>19 Do you buy movie? >>Welcome to the Cube of Leader in live tech coverage on Lisa Martin John for years with me were a Bumi World in d. C this year Excited to have there could be four really chatty people in this segment warning you now we've got Mandy Dollar while the cmo abou me Anibal Corker s V p of sales guys welcome thistles been in Austin. This is day one of the main event partner event started yesterday Partner Summit One of the things that is always very resonant with Bhumi events as you get this sense of collaboration with your partners with your customers and it's very symbiotic. So some of the numbers that came out today I wanted to kind of geek out on numbers because last boom, the world was on the 11 months ago, and I think the numbers we were talking about where 7500 customers adding five new a day. Now it's over 9000 in over 80 countries. Your partner program is blowing up 580 partners, incredible growth. And Chris McNab told Jonah me earlier today. This event? Actually, no, he said in the keynote five x What? It was the first event. Wow. You guys all look very refreshed for being this busy facade. Mandy, talk to us about what's going on. Abou me from your perspective. The new branding is really cool to have that represent what booby is delivering. We're at a >>growth trajectory and we had to refresh our brand to put a new face on this business so we could accelerate our growth. This is a whole new boo me to the world. When I stood up, it sails kick off earlier this year. In February, we reposition the company and focused ourselves on selling solutions. And as a part of that strategy, to start to amplify this brand to really become more of a known entity in the market, it was time for us to polish the brand up. You know, we had tremendous product market fit for many years. We just forgot to tell the world. So when I came on board, I can't keep a secret. Here I am Brandy. Look and feel. Lots of new customer stories. We're accelerating outcomes. >>Very clean. Logo queen branding. What's the brand promise. Where do you want to take the brand? What's next? Where's this going? Take us through the vision. >>Great question. The vision for the business Is that why we exist? We went through and, you know, we deliver a connected business experience that the real reason why we exist is to accelerate business outcomes for our customers. That is our vision, all right. We're connecting and unifying everything in a ditch. Digital ecosystem. The world has gone digital. No longer is software eating the world digital. Is the new game in town gloomy as well. Poised to go do that? That is the vision. And it's all about the customer and sharing their stories and the winds that they have worthy, enabling technology that drives that outcome faster and better than anybody else >>we had on earlier the founder of Bumi sharing early successes, Lisa asked him the background behind all started, and he said, we made a big bet and self aware Founder said We got lucky and he got lucky. Made a big bet on cloud. Now you guys have 9000 customers. Last year, your number one number one priority was customer success equation then the keynote again this year. You guys are crazy about customer outcomes. What >>is >>that mean? You hear customer success equation? What is the equation? Because the math equation isn't like, is it? What? What is the formula? >>Well, I think it entails a couple of key things. It starts with the product right, and it doing exactly what people are looking for it to do. And the reality is most people come in and they have an idea that they want to do X, and they really end up doing X plus y Times E. And and that becomes that's a big part of it. So getting to understand the platform and then showing them, you know that we really care about their success, that in fact it's either win, win relationship or lose lose, we have to make them successful. We have a tremendous muscle when it comes to customer success and our support efforts and those types of things. So just making sure that they're on the right journey, that they're leveraging the platform that's doing what they wanted to do. And again, we're seeing so many customers come back in now because of that and thinking that they can solve so many more problems than what they originally anticipate >>talking on our opening around. Um, you're successful business model like you talk more about that. But in contrast to what we've been reporting on our sites and silken angle in the Cube is Wall Street sees we work pulled their I p o uber, all these big companies, they buy market share, get a position, and then they try to crank the monetization. They're not being looked upon favorably right now, because that entails extracts from the customer. You guys are more on the other side, the Cloud SAS model, which is provide value if you need more, buy more, lower price fits increased. That's an Amazon like flywheel. Yeah, So you guys are on the positive side of the SAS formula as you have that first you guys agree with that's happening. But what do you say to customers who is booming? Because now you're you have leverage software business. Yeah, we have the professional service is what does this mean for customers? >>We'll get I would say that what it means is that they can come in and solve a problem so much faster than they ever thought they could solve it before. They're thinking they want to go on a journey. Everyone talks about the journey right, and it all. It comes in about 1000 different shapes and sizes. And with Bumi having a layer like this to be able to connect, what you need to connect when you need to connect it, how you need to connect it, that's and doing that in such in a fashion that no one ever really thought. And again. You said you had Rick Nucci and in the Founder where they thought I just talked to a minute ago. And I always say he was talking about how he was listening to some of the customers success stories. And I looked at him. I said You didn't think they were ever going to do all this stuff, that they could do all these things And he said, You know what? We didn't anticipate. It really didn't and so getting them to do that. But the key, to be honest, a big part of our growth, although we're acquiring lots of new logo. Certainly, as you mentioned, let's new customers a huge part of our growth is that again people are going, man. OK, I I brought in a new SAS application service now, or something like that. Okay, that's good. But I've got all these FTP problems and I've got this database issue and I need to be able to leverage this existing on Premiere P. And now I'm going to work Day and I have to be able to, and it's just it's just we see them just starting to get very creative about how they're leveraging the fact >>it's opening up. You say, you know, from a marketing perspective, unlocking potential. But it's really true. I I saw yesterday first and the manifestation of the Bumi fandom. That's rial. I was talking to one of your customers who integrated use integration for a particular opportunity. I thought there might be some, you know? Wow, there's gonna be a lot of data coming out. What can we do with this? And all of the, um, kind of side benefits that came from that they couldn't have predicted. Neither could have Rick Nucci, but how they're able to become even, you know, as a transportation logistics provider, trusted advisors to the carriers and the shippers that work with them. And then they're realizing, Oh, actually what we're doing, you know, under the hood with Bhumi is making a carrier more productive because the workload is less less clicks, etcetera. So it's really it shows the transformation doesn't just stay within your customer, their customers as well. The sort of this snowball effect. It really got that resoundingly yesterday from summer combo, >>where we see the people, the customers figure out if this becomes a common data layer for their monetization journey, right. So now they have control of all this data, no matter where it is and how it's going out in public cloud private clouds, public's ask, whatever it is, and then they now they've got control. They can become creative with the data. Now they can provide new service is to customers and suppliers and partners and internal stakeholders, whatever it might be. And I think that's that's it. Haven't clicked for us a couple years ago, and Mandy has been great about making that really how we send the message and it's really seen takeoff. >>We really speak about transformation, right? That's business processes. That's customer experience. How do you take that data and build upon it using our flow capabilities and take thes wrote processes and start to have them automated in a way that you're driving new customer experiences. Right? Employees on boarding is one that we use internally. We talked about it before our MPs went from a negative. I don't know, two incredibly positive, right? That's what this technology can do. Once you have that data layer in, we become that enabling technology to to go drive these additional >>out. And he has net promoter score for the folks at the jargon that this piece of a good point with the new branding we saw, it resonates. Well, it's gonna create a lot of brand impressions. I know you've done a great job of getting it out there. It's only gonna get better. But you get the brain of pressure. Then I want to know who is booming. If they know Bhumi, who what's the new room? We're gonna be like, What's the plan? How we're going to scale up the messaging? How you gonna take it? The market with the brand, There >>s O. Our core strategic initiatives are really what's on top of mind for Cee Io's right connection is important. That the stuff that will talked about in terms of on Prem and multi hybrid cloud scenarios right modernization, right? Getting stuff off of legacy Fed has a massive opportunity in terms of modernization. We're seeing that already. You know, we were Fed RAM certified in August. We've already got her for stealing the door. Congratulations. A fantastic opportunity on modernization, transformation. The stuff I spoke about customer experience, the one I'm particularly excited about. This is the marketing strategy coming through the innovation layer. We have a quick serve retailer that is now taking facial recognition. When I go through a drive thru triangulating my data with Maya vehicle license plate, making me on the spot loyalty offers and also saying, Oh, Mandy, would you like your regular breath breakfast sandwich Order That is the artist >>or not, you're in a good mood or Rolls Express. Oh, >>yes, >>minutes late today she's going to storm through here, right? Like that level of sentiment analysis based on my voice. The other stuff we heard this morning, right? We're triangulating all of that to go Dr whole new ways of doing business. So that's what I find hard. Your >>ecosystem is a key part of any growth strategy. I have to get the customer equation I loved. Loved the business model. You know, a big fan Disclose that everyone knows that. But be successful. You guys have a challenge. You have to grow the brand. You had to build the ecosystem, build the community with education pieces again. They're these >>air >>real blocking and tackling things. What? You guys, what's your opinion? What do you guys gonna do with that? Give us the playbook. >>We've brought it all together under one brand now, right Community saw this morning the boom Evers. The >>asked 1000 people in that community manager. >>Absolutely. And now we are ready for exponential growth, right? We have a way to game. If I We have a way to certify and train more people are partners. Demand it. There's a skills gap in the market in technology. That's a known fact for many years. So how do we quickly enable intelligence around the Bumi platform and mind trust and share? So that's something that's gonna happen. So we're creating this in waves were creating a viral ality component to our community right, all under the Bumi brand. So it all becomes additive. And that was important for us, as far as a growing up as a business is. Well, we're We're on this fast growth trajectory and everybody's off doing their thing. So I came in and said, All right, guys, let's let's build some cohesion here and that is going to help us as we scale this business >>will. On the sales side, you're gonna get a lot of pull now from the marketing Digital's. A lot of organic stuff goes on digital. We know we do a lot of cubes that we see the data. You guys still get the lead. You got too close sale cycles. This is kind of the business side of it. How's that going? What's that? What's an engagement looked like? How fast do Customs committees that word of mouth they talk to each other? What if some of the dynamics in the field? >>Well, we're seeing some of those times shrink. It's weird. I've been here seven years, so it's, you know, my team then was like 10. Now it's 470 or something, and so we've grown very fast, but it's on. We came in before. It was kind of like a connection deal. Last minute I thought, you know Oh gosh, I got an immigration problem. But now, a couple years later, it started really extending because it became a little more strategic. But now we're starting to see it shrink because people realize they're bringing it in, and they know that it's something that's key to what they have to do. What we're seeing is, is it's it's It's something that all of our partners are partners air so critical to helping us with the journey because we're really still just talking about one little piece of that larger pie. And so they come in and become with Come in with us every single time and we're globalizing as you mentioned all the countries that we're doing this in. But you know, France and Germany, or big efforts for Japan, the Fed those were like four areas. If I could pick that partners and how we're going to those markets >>are credible. Follow up on that. Just as you guys are getting these deals. Whats When does a customer know they have a Bumi opportunity? What is their problems? or a moment Is that a certain use cases? It like, Wow, I got integration problem. Is it integration? Problem called Boo me. What's that? What's the success pattern that you're seeing for the winds? >>You know, I'm gonna go back to the four that we talked about because, you know, part of part of my challenges, the sales leader for seven years was I've said this is the most organic technology I've ever I've ever dealt with. Representative. Because when we walked in, it could go anywhere. People wanted to do Data Analytics. They wanted to solve that TP problem. They wanted to do front. And you heard Olive from Sky. And she's thinking front end customer support stuff. So it really could go anywhere now is always always about managing data and collecting it. But, I mean, it really was. It comes from so many places, and the sale cycle has been, you know, has changed because of it. >>So as the marketing and the brand have evolved since Mandy spent on board, how much are you time? Are you still spending describing? Okay. So Bumi is how much more brand awareness and recognition do you have now? And how is that making the job easier? Because the attention the renewal rate is really high. 97%. >>Yeah, what's actually almost 99% from our field customers, and then we get over AM customers as well, about 97%. So how do we How do we keep the customers >>in terms of brand awareness, all the recognition? How much if you compared to seven years ago, when you were having to say, Well, buoy is now with Chris, McNall said, Hey, there's gonna be 100 different mentions of customer stories at this event alone. How much easier is your job? Enough sense? Because people are now much more aware of Bloomie's capability. >>I think people realize they need. This is what I say to all of our partners and even we're talking Deltek people. Every single customer will invest in this type of technology over the next several years. It might be a very tactical thing to do, but but call it a night pass. Call it a simpler way to connect and manage and access your data. So, yes, we're proud we're over that bridge to say OK, this is what was legitimate I think we're still having conversations about how strategic it is. But again, that's typically an interpretive process. We weigh very rarely come in and say Someone says, Oh, I'm going to replace all of this So it is. It's I'm going to solve this problem And then they go, Oh, all right now And its architects and leaders are going, Oh, well, we could solve all of these other problems that we've had >>Well, and if I may, they say, normally it would have taken me months to do this and you did it in days. Yes, we're interested. So that's that's the value. Proper >>the equation. Accelerate, right? >>Well, they were. The thing that we're observing is that the projects are increasing, not decreasing, and the number of project because they could be little things. That's right. That time to value is the proof points versus the long monolith proposal. It's up and running, and the jet states for months and months. >>Well, you talk about the integrators that we have so many integrators that we work with. We were worried at first years ago. Are we taking their business from them a little bit right? Because they have a lot of folks who are focused on that. But what they found is they're solving problems faster. But they're just doing the time. More problems, right? There's that there's this. Projects are growing. >>What I love about your business model is that the trend that we're covering is it's not I t setting the pace of projects. It's the projects themselves that then dictate to the cloud scale. And so I think you guys are tipping on this new we call Cloud to point out, which is it's completely flipped around anyone. If it's a mission based organization or for profit, there's a project to do something valid. You That's right. I t is just has to support it, not dictate terms. So this is a whole different level of thinking. Having the SAS business model >>well and layer in the usability of the product, right? The interface We go after citizen integrators lines of business. I can go build something for my marketing text back that's powerful, >>and the veterans examples of great one of the key No. Two people have to get done and they make a difference. They create value, >>absolutely speaking of value, this event is five x bigger then it was two years ago. Mandy, congratulations on everything that you guys have done. The voices of your customers are couldn't be stronger. That's the best friend validation that you can get. We're excited to be here. We've had a great day. One can't wait for day two tomorrow. >>Yeah. What are you doing? The product. >>Yes, I do. And more customers as well. We could all live on from sky, for example. Jillian is on. I think candy dot com hopefully is gonna bring in some candy. >>Yes, they well, two ton can. Absolutely. There's candy right back >>here. Awesome, guys. Thank you, Will and Mandy. So much for having the cube here and joining with us today. >>Thank you for your support. It's always great to chat with you about >>our pleasure. See, I told you it's gonna be chatty. John Ferrier. I'm Lisa Martin. You're watching the Cube from Bhumi World 2019. Thanks for watching

>> From San Francisco, it's theCUBE covering Conga Connect West 2018. Brought to you by Conga. >> Hey, welcome back everybody, Jeff Rick here with theCube. The Mark Benny office finished this portion of the keynote, so we can get back to business here. Special event outside of sales force, the 171,000 people over watching Mark and the keynote. We're here at a special Conga event, it's called Conga Connect West. It's about 3,000 people they said they had last year, 3 days of taking over the thirsty bear, they've got free food, free drink, free entertainment, lot of demos, come on over. The invitation is open. Just make sure you come early because the line is really long, but we're excited to get into it with a practitioner, we love to talk to customers. So, really excited to have our next guest, Susan O'Leary, she's a continuous improvement leader 6and program manager for Abiomed. Great to see you. >> Hey Jeff, thank you so much for that introduction. I'm so excited to be here. >> Excellent, and with her is Will Spindla, the VP of marketing from Conga. Will, great to see you. Warming up before your panel tomorrow. >> Exactly. (laughs) >> So, first off, impressions of this show, it never fails to amaze me when we come to Dreamforce, what happens to downtown San Francisco. >> It's insane, isn't it? >> It is crazy. It never disappoints, there is so much going on at every moment, and especially right here at Connect West. >> Right. So, what is Abiomed, for folks that aren't familiar with the company? >> So, Abiomed, we're a class-3 medical device company. We make the world's smallest heart pump and our corporate mission is to recover hearts and save lives. And more recently, we have some commercials for our flagship product, the Impella product, on T.V. So I feel like we've really arrived at some point in the company's maturity that we have television commercials. >> Right, so what does class-3 mean? >> So, it's a certain level of classification within the FDA, and class-3 means essentially, in the simplest way, that it goes inside the body. >> Okay. >> So, the rigor at which it's controlled, and how products are introduced into market, have a very rigorous path for patient quality and compliance and safety, it's a pretty exciting space to be, but it's not easy to bring a product to market. >> And you've got hardware, I imagine you've got all kinds of crazy software, you probably have all types of continuous monitoring, not a simple device. >> No. >> And a very important one. >> A very important one. That's right. >> So we're here at Conga, Connect West, what do you guys do with Conga, where does Conga play in your world? >> So Conga has enabled Abiomed to do amazing things. We're here at Dreamforce, obviously as Salesforce customers, and we began our journey with Salesforce back in 2009, and we discovered that we had some business processes that still resided outside of Salesforce, that people were struggling with these PowerPoint presentations and putting together their sales forecast, and all the data that would really drive that lives in the Salesforce orb. A tour on the app exchange back probably 2010 I would say, Will, and Jeff, I found the composer product, and it was a pretty easy sell to our VP of sales, a quick proof of concept, taking certain data that people were manually manipulating and with the click of a button, here is your forecast blown up in all kinds of colors and charts and graphs, it was a game changer. >> All right, so that's early intro, right, 'cause the biggest knock on Salesforce, always, is getting sales people to use it, right, and changing behavior is much harder than writing software or developing software. So, did you find that that app was the killer app to get the sales team to actually use the tool? >> Well, so they were using- >> 'Cause everybody's got the same story, right, everyone's got PowerPoint, and a lot of times people use Salesforce for reporting, not actually working, and now it's double data entry, I can't stand it, but it sounds like this composer was really a game-changer for you. >> Well, it brought the best of both worlds together because our field organization was using Salesforce, they're doing their work in that application, and yet the model that leadership wanted for delivering their weekly forecast in their update was very, very specific, and you couldn't do that in any Salesforce report. You can do it in Excel. >> So the forecast model was outside of Salesforce driven by the executive leadership, even though the day-to-day work was happening inside of Salesforce? >> You're right, you're right. >> And this was like, "Oh, it happens over and over again?" >> (laughs) It was the visualization that was impossible in standard Salesforce reports, but you could build it in Excel, and then merge the data with the composer product, so that was our first use case, and we have invented so many more, but that got us in the door, so to speak. >> So, Will, have you ever heard that story before? >> Well, what I was going to say, I think it's interesting because I worked at Salesforce for about six years before I came to Conga, and one of the things that we often saw was that sales people sometimes put their data in Salesforce, unless they're coaxed very greatly, but what they actually don't do a lot of the time is leverage the data that's inside there once it's there. And so the nice part about having a tool like Conga is that you can make it so the sales people don't have to do anything with the data, right? You can automate- >> Exactly. >> Creation of reports and charts and PowerPoint presentations, so that the sales reps, they don't have to do anything. >> They just click a button. >> Click a button. >> They click a button, they have the relationships with their customers, they know how to win the deals, they know how to take all those conversations to the next level, and why do we want them crunching numbers and doing that? We don't want them doing that. There's no value in that. So, you find great tools that take the data and put it in a button, and game changed. >> Yeah, and then you can ensure that whatever process or policy your company, like Abiomed has, every single sales rep is within that guideline, so they're not making their own decisions, they're doing what the organization wants them to. >> That's right, they're following a tested and validated model that delivers what leadership wants. And I'm probably not joking if I say half a day on Friday, if you were a cardiology account manager, you would be trying to cobble this together in a PowerPoint and then turn it in to the office. Half a day. >> So the office is asking for a PowerPoint presentation on the updated status of your pipeline, basically? >> This very specific visualization model. And, with Composer, with how people are with data, they think that this is all they really need, but once they saw what we could put in that output document from Composer, it has grown to be an enormous analytic tool set for the field team that drives their forecast. >> I'm just curious in terms of the scale and the size of team, don't tell me anything out of school but, are you talking tens of reps, hundreds of reps? >> Hundreds of reps. >> Hundreds of reps. >> Globally, we have over 100 sales territories, and so we have easily 450 feet on the street. And certain people have different roles, right, so the cardiology account manager role is that forecasting leader in the company, that person is really clicking that button to generate that document, and there's well over 100 in our organization. >> So, Will, you hear these stories all the time, I'm sure, is Composer the killer app to get people to start to embrace this tool? Do you see that time and time again? >> Yeah, I think one of the nice parts about Composer is that you can, in some respects, direct your entire sales or organization on the way the company wants to showcase themselves, whether it's in reporting, whether it's highly branded and pixel-perfect documents, what we've seen a lot of people do is you may have a monthly or a quarterly business review. >> Oh, we do that! We have Composer for that. We have this beautifully crafted merge template that delivers a business review to our customers. Yeah, that was the second thing we did with Composer. >> That's right. >> Where we first did the forecast then we did the business review. >> Business review. >> Wow! >> And you can do that in Excel, or in PowerPoint, or in Word, or even in HTML, it just gives you the ability to take data, that sits inside Salesforce, and push it out in any format you want. And the nice part, too, is you can pull data from other systems. >> Right. >> So it can be in your ERP or your accounting system and brings it all into one spot. >> I just can't help but think of the poor guy on the receiving end of the 450 PowerPoint decks on Friday afternoon, I mean how did that get rolled up? >> Yeah, we had another process for that. >> I don't want to hear that one, that one sounds scary. >> There's the regional, there's a country base- >> Too much. >> And it's all Composer. It's all Composer. >> Last question for you, Susan. So, have you been able to leverage the success of Composer to basically expand into more applications in the Salesforce suite with Conga or other, to actually get your adoption up, and now start to add more and more applications? >> Yeah, that's a great question, Jeff, and certainly Composer was that early-adoption product that was such an easy sell, it had win-win written over it in capital letters, everybody really got it right away. "We're buying this, we're doing this." And then over the years, Conga in its development life cycle put out a couple other game-changing products that we also have, we have their Action Grid product, and their contract solution. >> Was that as easy of a sell? >> Yes. >> Okay. (laughs) >> Well, it wasn't IT organizations selling solution on business, business is saying, "We want a quoting platform, and we need something better than standard Salesforce." So, we started looking at what is now CPQ, but it was called Steelwork at the time, and then we needed to solve for the contract life cycle management part of that, and a contract product didn't even exist at the time. And we were looking at other solutions, and we were trying to make something work, and we learned about the contract product through a Connect event that a colleague of mine attended, and came back from that event, and just said "Sue, you've got to stop everything you're doing, you've got to go talk to Pete Castro at Conga, and you have to see this contract tool. Because I know we're almost at the end of this project, but literally you're going to rip out everything that we did before and you're going to want to do this." So guess what we did? We did it! >> Will, you can't let this one off your hip, I'm telling you. She's awesome. >> It was a tough timeline and that was part of the promise that we needed to hear back when we went to the table, was we can't miss our launch. >> Yeah, yeah. >> To do this pivot and switch and can we do it? >> But that's easy compared to getting sales people to change behavior, timelines are one thing, but if you got people to actually use the tool the way the tool is supposed to be used, then the ancillary benefits are tremendous. Thank you for sharing that story with us, Sue. >> You're very welcome, Jeff. We do have the Action Grid product, but I'm not the expert in that space, but I've seen some amazing things. >> You've got the sales people using Salesforce on a weekly basis, plant the flag and call it enough. Come on now! All right, so thanks again. He's Will, she's Sue, I'm Jeff, you're watching theCube for Conga Connect West at Salesforce Dreamforce in San Francisco, thanks for watching. (electronic music)

>>Hey everyone. Hello from Las Vegas. Lisa Martin here with you, and I'm on the show floor at Reinvent. But we have a very special program series that the Cube has been doing called Women of the Cloud. It's brought to you by aws and I'm so pleased to have an excellent panel of women leaders in technology and in cloud to talk about their tactical recommendations for you, what they see as found, where they've helped organizations be successful with cloud. Please welcome my three guests, Tara Kapor, president and Chief Revenue Officer, consulting and Digital Transformations, NTT Data. We have Rachel Mu, aws, head of North America, partner sales from aws, and Jimmy Barnes joins us as well, managing director, investment banking engineering at Goldman Sachs. It is so great to have you guys on this power panel. I love it. Thank you for joining me. >>Thank >>You. Let's start with you. Give us a little bit of, of your background at NTT Data and I, and I understand NTT has a big focus on women in technology and in stem. Talk to us a little bit about that and then we'll go around the table. >>Perfect, thank you. Thank you. So brand new role for me at Entity Data. I started three months back and it's a fascinating company. We are about 22 billion in size. We work across industries on multiple innovative use cases. So we are doing a ton of work on edge analytics in the cloud, and that's where we are here with aws. We are also doing a ton of work on the private 5G that we are rolling out and essentially building out industry-wide use cases across financial services, manufacturing, tech, et cetera. Lots of women identity. We essentially have women run cloud program today. We have a gal called Nore Hanson who is our practice leader for cloud. We have Matine who's Latifa, who's our AWS cloud leader. We have Molly Ward who leads up a solutions on the cloud. We have an amazing lady in Mona who leads up our marketing programs. So a fantastic plethora of diverse women driving amazing work identity on cloud. >>That's outstanding to hear because it's one of those things that you can't be what you can't see. Right. We all talk about that. Rachel, talk a little bit about your role and some of the focus that AWS has. I know they're big customer obsession, I'm sure obsessed with other things as well. >>Sure. So Rachel Muir, pleased to be here again. I think this will be my third time. So a big fan of the Cube. I'm fortunate enough to lead our North America partner and channel business, and I'll tell you, I've been at AWS for a little under two years, and honestly, it's been probably the best two years of my career. Just in terms of where the cloud is, where it's headed, the business outcomes that we can deliver with our customers and with our partners is absolutely remarkable. We get to, you know, make the impossible possible every day. So I'm, I'm thrilled to be here and I'm thrilled to, to be part of this inaugural Women of the Cloud panel. >>Oh, I'm prepared to have all three of you. One of the things that feedback, kind of pivoting off what, Rachel, one of the things that you said that one of our guests, some of several of our guests have said is that coming out of Adams keynote this morning, it just seems limitless what AWS can do and I love that it gives me kind of chills what they can do with cloud computing and technology, with its ecosystem of partners with its customers like Goldman Sachs. Jimmy, talk to us a little bit about you, your role at Goldman Sachs. You know, we think of Goldman Sachs is a, is a huge financial institution, but it's also a technology company. >>Yeah. I mean, since the age of 15 I've been super passionate about how we can use technology to transform business and simplify modernized business processes. And it's, I'm so thrilled that I have the opportunity to do that at Goldman Sachs as an engineer. I recently moved about two years ago into the investment banking business and it's, you know, it's best in class, one of the top companies in terms of mergers and acquisitions, IPOs, et cetera. But what surprised me is how technology enables all the businesses across the board. Right? And I get to be leading the digital platform for building out the digital platform for in the investment banking business where we're modernizing and transforming existing businesses. These are not new businesses. It's like sometimes I liken it to trying to change the train while it's moving, right? These are existing businesses, but now we get to modernize and transform on the cloud. Right. Not just efficiency for the business by efficiency for technologists as >>Well. Right, right. Sticking with you, Jimmy. I wanna understand, so you've been, you've been interested in tech since you were young. I only got into tech and accidentally as an adult. I'm curious about your career path, but talk to us about that. What are some of the recommendations that you would have for other women who might be looking at, I wanna be in technology, but I wanna work for some of the big companies and they don't think about the Goldman Sachs or some of the other companies like Walmart that are absolutely technology driven. What's your advice for those women who want to grow their career? >>I also, growing up, I was, I was interested in various things. I, I loved doing hair. I used to do my own hair and I used to do hair for other students at school and I was also interested in running an entertainment company. And I used actually go around performing and singing and dancing with a group of friends, especially at church. But what amazed me is when I landed my first job at a real estate agent and everything was being done manually on paper, I was like, wow, technology can bring transformation anywhere and everywhere. And so whilst I have a myriad of interest, there's so many ways that technology can be applied. There's so many different types of disciplines within technology. It's not, there's hands on, like I'm colder, I like to code, but they're product managers, there are business analysts, there are infrastructure specialist. They're a security specialist. And I think it's about pursuing your passion, right? Pursuing your passion and identifying which aspects of technology peak your interest. And then diving in. >>Love that. Diving in. Rachel, you're shaking your head. You definitely are in alignment with a lot of what >>Duties I am. So, you know, interesting enough, I actually started my career as a civil engineer and eventually made it into, into technology. So very similar. I saw in, you know, heavy highway construction how manual some of these processes were. And mind you, this was before the cloud. And I sat down and wrote a little computer program to automate a lot of these manual tasks. And for me it was about simplification of the customer journey and really figuring out how do you deliver value. You know, on fast forward, say 20 plus years, here I am with AWS who has got this amazing cloud platform with over 200 services. And when I think about what we do in tech, from business transformation to modernizing to helping customers think about how do they create new business models, I've really found, I've really found my sweet spot, and I'll say for anyone who wants to get into tech or even switch careers, there's just a couple words of advice that I have. And it's really two words, just start. >>Yes, >>That's it. Just start. Because sometimes later becomes never. And you know, fuel your passion, be curious, think about new things. Yes. And just >>Start, I love that. Just start, you should get t-shirts made with that. Tell me a little bit about some of your recommendations. Obviously just start is great when follow your passion. What would you say to those out there looking to plan the letter? >>So, you know, my, my story's a little bit like jus because I did not want to be in tech. You know, I wanted an easy life. I did well in school and I wanted to actually be an air hostess. And when I broke that to my father, you know, the standard Indian person, now he did, he, you know, he wanted me to go in and be an engineer. Okay? So I was actually push into computer engineering, graduated. But then really two things today, right? When I look back, really two pieces, two areas I believe, which are really important for success. One is, you know, we need to be competent. And the second is we need to be confident, right? Yes, yes. It's so much easier to be competent because a lot of us diverse women, diverse people tend to over rotate on knowing their technical skills, right? Knowing technical skills important, but you need to know how to potentially apply those to business, right? Be able to define a business roi. And I see Julie nodding because she wants people to come in and give her a business ROI for programs that you're executing at Goldman Sachs. I presume the more difficult part though is confidence. >>Absolutely. It's so hard, especially when, when we're younger, we don't know. Raise your hand because I guarantee you either half the people in the, in the room or on the zoom these days weren't listening or have the same question and are too afraid to ask because they don't have the confidence. That's right. Give me, let's pivot on confidence for a minute, Jim, and let's go back to how would you advise your younger self to find your confidence? >>That's, that's a tough one because I feel like even this older self is still finding exercise to, to be real. But I think it's about, I would say it's not praise. I think it's about praising yourself, like recognizing your accomplishments. When I think about my younger self, I think I, I like to focus more on what I didn't do or what I didn't accomplish, instead of majoring and focusing on all the accomplishments and the achievements and reminding myself of those day after day after day. And I think it's about celebrating your wins. >>I love that. Celebrating your wins. Do you agree, Rachel? >>I do. Here's the hard part, and I look around this table of amazing business leaders and I can guarantee that every single one of us sometime this year woke up and said, oh my gosh, I don't know how to do that. Oh >>Yeah. But >>What we haven't followed that by is, I don't know how to do that yet. Right. And here's the other thing I would tell my younger self is there will be days where every single one of us falls apart. There will be days when we feel like we failed at work. There will be days when you feel like you failed as a parent or you failed as a spouse. There'll be days where you have a kid in the middle of target screaming and crying while you're trying to close a big business deal and you just like, oh my gosh, is this really my life? But what I would tell my younger self is, look, the crying, the chaos, the second guessing yourself, the successes, every single one of those are milestones. And it's triumphant, it's tragic, but every single thing that we have been through is fiercely worthwhile. And it's what got us >>Here. Absolutely. Absolutely. Think of all the trials and tribulations and six and Zacks that got you to this table right now. Yep. So Terry, you brought up confidence. How would you advise the women out there won't say you're gonna know stuff. The women out there now that are watching those that are watching right there. Hi. How would you advise them to really find their, their ability to praise themselves, recognize all of the trials and the tribulations as milestones as Rachel said, and really give themselves a seat at the table, raise their hand regardless of who else is in the room? >>You know, it's a, it's a more complex question just because confidence stems from courage, right? Confidence also stems from the belief that you're going to be treated fairly right now in an organization for you to be treated fairly. You need to have, be surrounded by supporters that are going to promote your voice. And very often women don't invest enough in building that support system around them. Yeah. Right. We have mentors, and mentors are great because they come in and they advise us and they'll tell us what we need to go out and do. We really need a team of sponsors Yes. Who come in and support us in the moment in the business. Give us the informal channel because very often we are not plugged into the informal channel, right. So we don't get those special projects or assignments or even opportunities to prove that we can do the tough task. Yeah. So, you know, my, my advice would be to go out and build a network of sponsors. Yes. And if you don't have one, be a sponsor for someone else. That's right. I love that. Great way to win sponsorship is by extending it todos. >>And sometimes too, it's about, honestly, I didn't even know the difference between a mentor and a sponsor until a few years ago. And I started thinking, who are I? And then I started realizing who they were. That's right. And some of the conversations that we've had on the cube about women in technology, women of the cloud with some of the women leaders have said, build, and this is kind of like, sort of what you were saying, build your own personal board of directors. Yeah. And that, oh, it gives me chills. It's just, it's so important for, for not just women, but anybody, for everybody. But it's so important to do that. And if you, you think about LinkedIn as an example, you have a network, it's there, utilize it, figure out who your mentors are, who your sponsors are, who are gonna help you land the next thing, start building that reputation. But having that board of directors that you can kind of answer to or have some accountability towards, I think is hugely very >>Important. Yeah. >>Very important. I think, you know, just for, just for those that are listening, a really important distinction for me was mentors are people that you have that help you with, Hey, here's the situation that you were just in. They advise you on the situation. Sponsors are the people that stick up for you when you're not in the room to them. Right. Sponsors are the ones that say, Hey, I think so and so not only needs to have a seat at the table, but they need to build the table. And that's a really important delineation. Yeah. Between mentors and sponsors. And everybody's gotta have a sponsor both within their company and outside of their company. Someone that's advocating for them on their behalf when they don't even know it. Yeah. Yeah. >>I love that you said that. Build the table. It reminds me of a quote that I heard from Will I am, I know, very random. It was a podcast he did with Oprah Winfrey on ai. He's very into ai and I was doing a panel on ai, so I was doing a lot of research and he said, similar for Rachel to build the table, don't wait for a door to open. You go build a door. And I just thought, God, that is such brilliant advice. It is. It's hard to do. It is. Especially when, you know, the four of us in this room, there's a lot of women around here, but we are in an environment where we are the minority women of color are also the minority. What do you guys think where tech is in terms of de and I and really focusing on De and I as as really a very focused strategic initiative. Turner, what do you think? >>So, you know, I just, I, I spoke earlier about the women that we have at Entity Data, right? We have a fabulous team of women. And joining this team has been a moment of revelation for me coming in. I think to promote dni, we all need to start giving back, right? Yes. So today, I would love to announce that we at Entity would like to welcome all of you out there. You know, folks that have diverse ideas, you know, ISV, partners with diverse solutions, thought leaders out there who want to contribute into the ecosystem, right? Customers out there who want to work with companies that are socially responsible, right? We want to work with all of you, come back, reach out to us and be a part of the ecosystem because we can build this together, right? AWS has an amazing platform that gives us an opportunity to do things differently. Yes. Right. Entity data is building a women powered cloud team. And I want to really extend that out to everyone else to be a part this ecosystem, >>But a fantastic opportunity. You know, when we talk about diversity and inclusion and equity, it needs to be intentional for organization. It sounds very intentional at ntt. I know that that intention is definitely there at AWS as well. What are your thoughts on where tech is with respect to diversity? Even thought diversity? Because a lot of times we tend to go to our comfort zones. We do. And so we tend to start creating these circles of kind of like, you know, think tanks and they think alike people to go outside of that comfort zone. It's part of building the table, of building the, is the table and getting people from outside your comfort zone to come in and bring in diverse thought. Because can you imagine the potential of technology if we have true thought diversity in an organization? >>Right? It's, it's incredible. So one of the things that I always share with my team is we've got the opportunity to really change the outcome, right? As you know, you talked about Will I am I'm gonna talk about Bono from you too, right? One of, one of his favorite quotes is, we are the people we've been waiting for. Oh, I love that. And when you think about that, that is us. There is no one else that's gonna change the outcome and continue to deliver some of the business outcomes and the innovation that we are if we don't continue to raise our hand and we don't continue to, to inspire the next generation of leaders to do the same thing. And what I've found is when you start openly sharing what your innovation ideas are or how you're leveraging your engineering background, your stories and your successes, and, and frankly, some of your failures become the inspiration for someone you might not even know. Absolutely. And that's the, you know, that's the key. You're right. Inclusion, diversity, equity and accessibility, yes. Have to be at the forefront of every business decision. And I think too often companies think that, you know, inclusion, diversity, equity and accessibility is one thing, and business outcomes are another. And they're not. No, they are one in the same. You can't build business outcomes without also focusing on inclusion, diversity, equity, accessibility. That's the deliberate piece. >>And, and it has to be deliberate. Jimmy, I wanna ask you, we only have a couple of minutes left, but you're a woman in tech, you're a woman of color. What was that like for you? You, you were very intentional knowing when you were quite young. Yeah. What you wanted to do, but how have you navigated that? Because I can't imagine that was easy. >>It wasn't. I remember, I always tell the story and the, the two things that I really wanted to emphasize today when I thought about this panel is rep representation matters and showing up matters, right? And there's a statement, there's a flow, I don't know who it's attributed to, but be the change you want to see. And I remember walking through the doors of Goldman Sachs 15 years ago and not seeing a black female engineer leader, right? And at that point in time, I had a choice. I could be like, oh, there's no one look like, there's no one that looks like me. I don't belong here. Or I could do what I actually did and say, well, I'm gonna be that person. >>Good, >>Right? I'm going to be the chain. I'm going to show up and I am going to have a seat at the table so that other people behind me can also have a seat at the table. And I think that I've had the privilege to work for a company who has been inclusive, who has had the right support system, the right structures in place, so that I can be that person who is the first black woman tech fellow at Goldman Sachs, who is one of the first black females to be promoted up the rank as a, from analysts to managing director at the company. You know, that was not just because I determined that I belong here, but because the company ensure that I felt that I belong. >>Right. >>That's a great point. They ensure that you felt that. Yeah. You need to be able to feel that. Last question, we've only got about a minute left. 2023 is just around the corner. What comes to your mind, Jimmy will stick with you as you head into the new year. >>Sorry, can you repeat >>What comes to mind priorities for 2023 that you're excited about? >>I'm excited about the democratization of data. Yeah. I'm excited about a lot of the announcements today and I, I think there is a, a huge shift going on with this whole concept of marketplaces and data exchanges and data sharing. And I think both internally and externally, people are coming together more. Companies are coming together more to really de democratize and make data available. And data is power. But a lot of our businesses are running, running on insights, right? And we need to bring that data together and I'm really excited about the trends that's going on in cloud, in technology to actually bring the data sets together. >>Touro, what are you most excited about as we head to 2023? >>I think I'm really excited about the possibilities that entity data has right here, right now, city of Las Vegas, we've actually rolled out a smart city project. So saving citizens life, using data edge analytics, machine learning, being able to predict adverse incidents before they happen, and then being able to take remediation action, right? So that's technology actually working in real time to give us tangible results. We also sponsor the Incar races. Lots of work happening there in delivering amazing customer experience across the platform to millions of users real time. So I think I'm just excited about technology coming together, but while that's happening, I think we really need to be mindful at this time that we don't push our planet into per right. We need to be sustainable, we need to be responsible. >>Absolutely. Rachel, take us out. What are you most excited about going into 2023? >>So, you know, there are so many trends that are, that we could talk about, but I'll tell you at aws, you know, we're big. We, we impact the world. So we've gotta be really thoughtful and humble about what it is that we do. So for me, what I'm most excited about is, you know, one of our leadership principles is about, you know, with what broad responsibility brings, you know, you've got to impact sustainability and many of those other things. And for me, I think it's about waking up every day for our customers, for our partners, and for the younger generations. And being better, doing better, and making better for this planet and for, you know, the future generations to come. So >>I think your tag line just start applies to all of that. It does. It has been an absolute pleasure. And then really an honor to talk to you on the program. Thank you all for joining me, sharing your experiences, sharing what you've accomplished, your recommendations for those others who might be our same generation or older or younger. All really beautiful advice. Thank you so much for your time and your insights. We appreciate it. >>Thank you. Thank you. >>For my guests, I'm Lisa Martin. You're watching The Cube, the leader in live enterprise and emerging tech coverage. Thanks for watching.

>> From theCUBE studios in Palo Alto in Boston bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> The term Supercloud is somewhat new, but the concepts behind it have been bubbling for years, early last decade when NIST put forth a definition of cloud computing it said services had to be accessible over a public network essentially cutting the on-prem crowd out of the cloud conversation. Now a guy named Chuck Hollis, who was a field CTO at EMC at the time and a prolific blogger objected to that criterion and laid out his vision for what he termed a private cloud. Now, in that post, he showed a workload running both on premises and in a public cloud sharing the underlying resources in an automated and seamless manner. What later became known more broadly as hybrid cloud that vision as we now know, really never materialized, and we were left with multi-cloud sets of largely incompatible and disconnected cloud services running in separate silos. The point is what Hollis laid out, IE the ability to abstract underlying infrastructure complexity and run workloads across multiple heterogeneous estates with an identical experience is what super cloud is all about. Hello and welcome to this week's Wikibon cube insights powered by ETR and this breaking analysis. We share what we hope to learn from super cloud 22 next week, next Tuesday at 9:00 AM Pacific. The community is gathering for Supercloud 22 an inclusive pilot symposium hosted by theCUBE and made possible by VMware and other founding partners. It's a one day single track event with more than 25 speakers digging into the architectural, the technical, structural and business aspects of Supercloud. This is a hybrid event with a live program in the morning running out of our Palo Alto studio and pre-recorded content in the afternoon featuring industry leaders, technologists, analysts and investors up and down the technology stack. Now, as I said up front the seeds of super cloud were sewn early last decade. After the very first reinvent we published our Amazon gorilla post, that scene in the upper right corner here. And we talked about how to differentiate from Amazon and form ecosystems around industries and data and how the cloud would change IT permanently. And then up in the upper left we put up a post on the old Wikibon Wiki. Yeah, it used to be a Wiki. Check out my hair by the way way no gray, that's how long ago this was. And we talked about in that post how to compete in the Amazon economy. And we showed a graph of how IT economics were changing. And cloud services had marginal economics that looked more like software than hardware at scale. And this would reset, we said opportunities for both technology sellers and buyers for the next 20 years. And this came into sharper focus in the ensuing years culminating in a milestone post by Greylock's Jerry Chen called Castles in the Cloud. It was an inspiration and catalyst for us using the term Supercloud in John Furrier's post prior to reinvent 2021. So we started to flesh out this idea of Supercloud where companies of all types build services on top of hyperscale infrastructure and across multiple clouds, going beyond multicloud 1.0, if you will, which was really a symptom, as we said, many times of multi-vendor at least that's what we argued. And despite its fuzzy definition, it resonated with people because they knew something was brewing, Keith Townsend the CTO advisor, even though he frankly, wasn't a big fan of the buzzy nature of the term Supercloud posted this awesome Blackboard on Twitter take a listen to how he framed it. Please play the clip. >> Is VMware the right company to make the super cloud work, term that Wikibon came up with to describe the taking of discreet services. So it says RDS from AWS, cloud compute engines from GCP and authentication from Azure to build SaaS applications or enterprise applications that connect back to your data center, is VMware's cross cloud vision 'cause it is just a vision today, the right approach. Or should you be looking towards companies like HashiCorp to provide this overall capability that we all agree, or maybe you don't that we need in an enterprise comment below your thoughts. >> So I really like that Keith has deep practitioner knowledge and lays out a couple of options. I especially like the examples he uses of cloud services. He recognizes the need for cross cloud services and he notes this capability is aspirational today. Remember this was eight or nine months ago and he brings HashiCorp into the conversation as they're one of the speakers at Supercloud 22 and he asks the community, what they think, the thing is we're trying to really test out this concept and people like Keith are instrumental as collaborators. Now I'm sure you're not surprised to hear that mot everyone is on board with the Supercloud meme, in particular Charles Fitzgerald has been a wonderful collaborator just by his hilarious criticisms of the concept. After a couple of super cloud posts, Charles put up his second rendition of "Supercloudifragilisticexpialidoucious". I mean, it's just beautiful, but to boot, he put up this picture of Baghdad Bob asking us to just stop, Bob's real name is Mohamed Said al-Sahaf. He was the minister of propaganda for Sadam Husein during the 2003 invasion of Iraq. And he made these outrageous claims of, you know US troops running in fear and putting down their arms and so forth. So anyway, Charles laid out several frankly very helpful critiques of Supercloud which has led us to really advance the definition and catalyze the community's thinking on the topic. Now, one of his issues and there are many is we said a prerequisite of super cloud was a super PaaS layer. Gartner's Lydia Leong chimed in saying there were many examples of successful PaaS vendors built on top of a hyperscaler some having the option to run in more than one cloud provider. But the key point we're trying to explore is the degree to which that PaaS layer is purpose built for a specific super cloud function. And not only runs in more than one cloud provider, Lydia but runs across multiple clouds simultaneously creating an identical developer experience irrespective of a state. Now, maybe that's what Lydia meant. It's hard to say from just a tweet and she's a sharp lady, so, and knows more about that market, that PaaS market, than I do. But to the former point at Supercloud 22, we have several examples. We're going to test. One is Oracle and Microsoft's recent announcement to run database services on OCI and Azure, making them appear as one rather than use an off the shelf platform. Oracle claims to have developed a capability for developers specifically built to ensure high performance low latency, and a common experience for developers across clouds. Another example we're going to test is Snowflake. I'll be interviewing Benoit Dageville co-founder of Snowflake to understand the degree to which Snowflake's recent announcement of an application development platform is perfect built, purpose built for the Snowflake data cloud. Is it just a plain old pass, big whoop as Lydia claims or is it something new and innovative, by the way we invited Charles Fitz to participate in Supercloud 22 and he decline saying in addition to a few other somewhat insulting things there's definitely interesting new stuff brewing that isn't traditional cloud or SaaS but branding at all super cloud doesn't help either. Well, indeed, we agree with part of that and we'll see if it helps advanced thinking and helps customers really plan for the future. And that's why Supercloud 22 has going to feature some of the best analysts in the business in The Great Supercloud Debate. In addition to Keith Townsend and Maribel Lopez of Lopez research and Sanjeev Mohan from former Gartner analyst and principal at SanjMo participated in this session. Now we don't want to mislead you. We don't want to imply that these analysts are hopping on the super cloud bandwagon but they're more than willing to go through the thought experiment and mental exercise. And, we had a great conversation that you don't want to miss. Maribel Lopez had what I thought was a really excellent way to think about this. She used TCP/IP as an historical example, listen to what she said. >> And Sanjeev Mohan has some excellent thoughts on the feasibility of an open versus de facto standard getting us to the vision of Supercloud, what's possible and what's likely now, again, I don't want to imply that these analysts are out banging the Supercloud drum. They're not necessarily doing that, but they do I think it's fair to say believe that something new is bubbling and whether it's called Supercloud or multicloud 2.0 or cross cloud services or whatever name you choose it's not multicloud of the 2010s and we chose Supercloud. So our goal here is to advance the discussion on what's next in cloud and Supercloud is meant to be a term to describe that future of cloud and specifically the cloud opportunities that can be built on top of hyperscale, compute, storage, networking machine learning, and other services at scale. And that is why we posted this piece on Answering the top 10 questions about Supercloud. Many of which were floated by Charles Fitzgerald and others in the community. Why does the industry need another term what's really new and different? And what is hype? What specific problems does Supercloud solve? What are the salient characteristics of Supercloud? What's different beyond multicloud? What is a super pass? Is it necessary to have a Supercloud? How will applications evolve on superclouds? What workloads will run? All these questions will be addressed in detail as a way to advance the discussion and help practitioners and business people understand what's real today. And what's possible with cloud in the near future. And one other question we'll address is who will build super clouds? And what new entrance we can expect. This is an ETR graphic that we showed in a previous episode of breaking analysis, and it lays out some of the companies we think are building super clouds or in a position to do so, by the way the Y axis shows net score or spending velocity and the X axis depicts presence in the ETR survey of more than 1200 respondents. But the key callouts to this slide in addition to some of the smaller firms that aren't yet showing up in the ETR data like Chaossearch and Starburst and Aviatrix and Clumio but the really interesting additions are industry players Walmart with Azure, Capital one and Goldman Sachs with AWS, Oracle, with Cerner. These we think are early examples, bubbling up of industry clouds that will eventually become super clouds. So we'll explore these and other trends to get the community's input on how this will all play out. These are the things we hope you'll take away from Supercloud 22. And we have an amazing lineup of experts to answer your question. Technologists like Kit Colbert, Adrian Cockcroft, Mariana Tessel, Chris Hoff, Will DeForest, Ali Ghodsi, Benoit Dageville, Muddu Sudhakar and many other tech athletes, investors like Jerry Chen and In Sik Rhee the analyst we featured earlier, Paula Hansen talking about go to market in a multi-cloud world Gee Rittenhouse talking about cloud security, David McJannet, Bhaskar Gorti of Platform9 and many, many more. And of course you, so please go to theCUBE.net and register for Supercloud 22, really lightweight reg. We're not doing this for lead gen. We're doing it for collaboration. If you sign in you can get the chat and ask questions in real time. So don't miss this inaugural event Supercloud 22 on August 9th at 9:00 AM Pacific. We'll see you there. Okay. That's it for today. Thanks for watching. Thank you to Alex Myerson who's on production and manages the podcast. Kristen Martin and Cheryl Knight. They help get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE. Does some really wonderful editing. Thank you to all. Remember these episodes are all available as podcasts wherever you listen, just search breaking analysis podcast. I publish each week on wikibon.com and Siliconangle.com. And you can email me at David.Vellantesiliconangle.com or DM me at Dvellante, comment on my LinkedIn post. Please do check out ETR.AI for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE insights powered by ETR. Thanks for watching. And we'll see you next week in Palo Alto at Supercloud 22 or next time on breaking analysis. (calm music)

>>Welcome back to Vegas guys, Lisa Martin and Dave Lanta here wrapping up our coverage of day two of snowflake summit. We have given you a lot of content in the last couple of days. We've had a lot of great conversations with snowflake folks with their customers and with partners. And we have an alumni back with us. Please. Welcome back to the queue. Mike Palmer, CEO of Sigma computing. Mike. It's great to see you. >>Thanks for having me. And I guess again >>Exactly. >>It's fantastic me. >>So talk to the audience about Sigma before we get into the snowflake partnership and what you guys are doing from a technical perspective, give us that overview of the vision and some of the differentiators. >>Sure. You know, you've over the last 12 years, companies have benefited from enormous investments and improvements in technology in particular, starting with cloud technologies, obviously going through companies like snowflake, but in terms of the normal user, the one that makes the business decision in the marketing department and the finance team, you know, in the works in the back room of the supply chain, doing inventory very little has changed for those people. And the time had come where the data availability, the ability to organize it, the ability to secure it was all there, but the ability to access it for those people was not. And so what Sigma's all about is taking great technology, finding the skillset they have, which happens to be spreadsheets. There are billion license spreadsheet users in the world and connecting that skillset with all of the power of the cloud. >>And how do you work with snowflake? What are some of the, the what's the joint value proposition? >>How are they as an investor? That's what I wanna know. Ah, >>Quiet, which is the way we like them. No, I'm just kidding. Snowflake is, well, first of all, investment is great, but partnership is even better. Right. You know, and I think snowflake themselves are going through some evolution, but let's start with the basics of technology where this all starts because you know, all of the rest doesn't matter if the product is not great, we work directly on snowflake. And what that means is as an end user, when I, when I sit on that marketing team and I want to understand and, and connect, how did I get a, a customer where I had a pay to add? And they showed up on my website and from my website, they went to a trial. And from there, they touched a piece of syndicated contents. All of that data sits in snowflake and I, as a marketer, understand what it means to me. >>So for the first time, I want to be able to see that data in one place. And I want to understand conversion rates. I want to understand how I can impact those conversion rates. I can make predictions. What that user is doing is going to, to Sigma accessing live data in snowflake, they're able to ask ad hoc questions, questions that were never asked questions, that they don't exist in a filter that were never prepped by a data engineer. So they could truly do something creative and novel in a very independent sort of way. And the connection with Snowflake's live data, the performance, the security and governance that we inherit. These are all facilitators to really expand that access across the enterprise. So at, at a product level, we were built by a team of people, frankly, that also were the original investors in snowflake by two amazing engineers and founders, Rob will and Jason France, they understood how snowflake worked and that shows up in the product for our end customers. >>So, but if I may just to follow up on that, I mean, you could do that without snowflake, but what, it would be harder, more expensive. Describe what you'd have to go through to accomplish that outcome. >>And I think snowflake does a good job of enabling the ecosystem at large. Right. But you know, you always appreciate seeing early access to understand what the architecture's going to look like. You know, some of the things that I will, you know, leaning forward that we've heard here that we're very excited about is snowflake going to attack the TP market, right? The transactional market, one of the transactional database market. I, yeah. Right. You know, one of the things that we see coming, and, and one of the bigger things that we'll be talking about in Sigma is not just that you can do analytics out of snowflake. I think that's something that we do exceptionally well on an ad hoc basis, but we're gonna be the first that allow you to write into snowflake and to do that with good performance. And to do that reliably, we go away from OAP, which is the terminology for data warehousing. >>And we go toward transactional databases. And in that world, understanding snowflake and working collaboratively with them creates again, a much better experience for the end customer. So they, they allow us into those programs, even coming to these conferences, we talk to folks that run the industry teams, trying to up level that message and not just talk database and, and analytics, but talk about inventory management. How do we cut down the gap that exists between POS systems and inventory ordering, right? So that we get fewer stockouts, but also that we don't overorder. So that's another benefit, >>Strong business use cases. >>That's correct. >>And you're enabling those business users to have access to that data. I presume in near real time or near real time, so that they can make decisions that drive marketing forward or finance forward or legal >>Forward. Exactly. We had a customer panel yesterday. An example of that go puff is hopefully most of the viewers are familiar with, as a delivery company. This is a complicated business to run. It's run on the fringes. When we think about how to make money at it, which means that the decisions need to be accurate. They need to be real time. You can't have a batch upload for delivery when they're people are on the street, and then there's an issue. They need to understand the exact order at that time, not in 10 minutes, not from five minutes ago, right. Then they need to understand, do I have inventory in the warehouse when the order comes in? If they don't, what's a replacement product. We had a Mike came in from go puff and walked us through all of the complexity of that and how they're using Sigma to really just shorten those decision cycles and make them more accurate. You know, that's where the business actually benefits and, >>And actually create a viable business model. Cuz you think back to the early, think back to the.com days and you had pets.com, right? They couldn't make any money. Yeah. Without chewy. Okay. They appears to be a viable business model. Right? Part of that is just the efficiencies. And it's sort of a, I dunno if those are customers that they may or may not be, but they should be if they're not >>Chewy is, but okay. You know, and that's another example, but I'll even pivot to the various REI and other retailers. What do they care about cohorts? I'm trying to understand who's buying my product. What can I sell to them next? That, that idea of again, I'm sitting in a department, that's not data engineering, that's not BI now working collaboratively where they can get addend engineer, putting data sets together. They have a BI person that can help in the analytics process. But now it's in a spreadsheet where I understand it as a marketer. So I can think about new hierarchies. I wanna know it by customer, by region, by product type. I wanna see it by all of those things. I want to be able to do that on the fly because then it creates new questions that sort of flow. If you' ever worked in development, we use the word flow constantly, right? And as people that flow is when we have a question, we get an answer that generates a question. We have, we just keep doing that iteratively. That that is where Sigma really shines for them. >>What does a company have to do to really take advantage of, of this? I, if they're kind of starting from a company that's somewhat immature, what are the sort of expectations, maybe even outta scope expectations so they can move faster, accelerate analytics, a lot of the themes that we've heard today, >>What does an immature company is actually even a question in, in and of itself? You know, I think a lot of companies consider themselves to be immature simply because for various constraint reasons, they haven't leveraged the data in the way that they thought possible. Good, >>Good, good definition. Okay. So not, not, >>Not, I use this definition for digital transformation. It very simple. It is. Do you make better decisions, faster McKenzie calls this corporate metabolism, right? Can you speed up the metabolism of, of an enterprise and for me and for the Sigma customer base, there's really not much you have to do once. You've adopted snowflake because for the first time the barriers and the silos that existed in terms of accessing data are gone. So I think the biggest barrier that customers have is curiosity. Because once you have curiosity and you have access, you can start building artifacts and assets and asking questions. Our customers are up and running in the product in hours. And I mean that literally in hours, we are a user in snowflake, that's a direct live connection. They are able to explore tables, raw. They can do joins themselves if they want to. They can obviously work with their data engineering team to, to create data sets. If that's the preferred method. And once they're there and they've ever built a pivot table, they can be working in Sigma. So our customers are getting insights in the first one to two days, you referenced some, those of us are old enough to remember pest.com. Also old enough to remember shelfware that we would buy. We are very good at showing customers that within hours they're getting value from their investment in Sigma. And that, that just creates momentum, right? Oh, >>Tremendous momentum and >>Trust and trust and expansion opportunities for Sigma. Because when you're in one of those departments, someone else says, well, you know, why do you get access to that data? But I don't, how are you doing this? Yeah. So we're, you know, I think that there's a big movement here. People, I often compare data to communication. If you go back a hundred years, our communication was not limited. As it turns out by our desire to communicate, it was limited by the infrastructure. We had the typewriter, a letter and the us postal service and a telephone that was wired. And now we have walk around here. We, everything is, is enabled for us. And we send, you know, hundreds and thousands of messages a day and probably could do more. You will find that is true. And we're seeing it in our product is true of data. If you give people access, they have 10 times as many questions as they thought they had. And that's the change that we're gonna see in business over the next few years, >>Frank Salman's first book, what he was was CEO of snowflake was rise of the data cloud. And he talked about network effects. Basically what he described was Metcalf's law. Again, go back to the.com days, right? And he, Bob Metcalf used the phone system. You know, if there's two people in the phone system, it's not that valuable, right. >>You know, exactly, >>You know, grow it. And that's where the value is. And that's what we're seeing now applied to data. >>And even more than that, I think that's a great analogy. In fact, the direct comparison to what Sigma is doing actually goes one step beyond everything that I've been talking about, which is great at the individual level, but now the finance team and the marketing team can collaborate in the platform. They can see data lineage. In fact, one of our, our big emphasis points here is to eliminate the sweet products. You know, the ones where, you know, you think you're buying something, but you really have a spreadsheet product here and a document product there and a slide product over there. And they, you know, you can do all of that in Sigma. You can write a narrative. You can real time live, edit on numbers. You, you know, if you want to, you could put a picture in it. But you know, at Sigma we present everything out of our product. Every meeting is live data. Every question is answered on the spot. And that's when, you know, you know, to your point about met cap's law. Now everybody's involved in the decision making. They're doing it real time. Your meetings are more productive. You have fewer of them because they're no action items, right. We're answering our questions there and we're, and we're moving forward. >>You know, view were meeting sounds good. Productivity is, is weird now with the, the pandemic. But you know, if you go back to the nineties here am I'm, I'm dating myself again, but that's okay. You know, you, you didn't see much productivity going on when the PC boom started in the eighties, but the nineties, it kicked in and pre pandemic, you know, productivity in the us and Europe anyway has been going down. But I feel like Mike, listen to what you just described. I, how many meetings have we been in where people are arguing about them numbers, what are the assumptions on the numbers wasting so much time? And then nothing gets done and they, then they, they bolt cut that away and you drive in productivity. So I feel like we're on a Renaissance of productivity and a lot of that's gonna be driven by, by data. Yeah. And obviously communications the whole 5g thing. We'll see how that builds out. But data is really the main spring of, I think, a new, new Renaissance in productivity. >>Well, first of all, if you could find an enterprise where you ask the question, would you rather use your data better? And they say, no, like, you know, show me, tell me that I'll short their stock immediately. But I do agree. And I, unfortunately I have a career history in that meeting that you just described where someone doesn't like, what you're showing them. And their first reaction is to say, where'd you get that data? You know, I don't trust it. You know? So they just undermined your entire argument with an invalid way of doing so. Right. When you walk into a meeting with Sigma where'd, where'd you get that data? I was like, that's the live data right now? What question do you want answer >>Lineage, right. Yeah. And you know, it's a Sen's book about, you know, gotta move faster. I mean, this is an example of just cutting through making decisions faster because you're right. Mike and the P the P and L manager in a meeting can, can kill the entire conversation, you know, throw FUD at it. Yeah. You know, protect his or her agenda. >>True. But now to be fair to the person, who's tended to do that. Part of the reason they've done that is that they haven't had access to that data before the meeting and they're getting blindsided. Right. So going back to the collaboration point. Yes. Right. The fact we're coming to this discussion more informed in and of itself takes care of some of that problem. Yeah. >>For sure. And if, and if everybody then agrees, we can move on and now talk about the really important stuff. Yeah. That's good. It >>Seems to me that Sigma is an enabler of that curiosity that you mentioned that that's been lacking. People need to be able to hire for that, but you've got a platform that's going here. You go ask >>Away. That's right in the we're very good. You know, we love being a SaaS platform. There's a lot of telemetry. We can watch what we call our mouse to Dows, you know, which is our monthly average users to our daily average users. We can see what level of user they are, what type of artifacts they build. Are they, you know, someone that creates things from scratch, are they people that tend to increment them, which by the way, is helpful to our customers because we can then advise them, Hey, here's, what's really going on. You might wanna work with this team over here. They could probably be a little better of us using the data, but look at this team over here, you know, they've originated five workbooks in the last, you know, six days they're really on it. There's, there's, you know, that ability to even train for the curiosity that you're referring to is now there, >>Where are your customer conversations? Are they at the lines of business? Are they with the chief data officer? What does that look like these days? >>Great question. So stepping back a bit, what, what is Sigma here to do? And, and our first phase is really to replace spreadsheets, right? And so one of the interesting things about the company is that there isn't a department where a spreadsheet isn't used. So Sigma has an enormous Tam, but also isn't necessarily associated with any particular department or any particular vertical. So when we tend to have conversations, it really depends on, you know, either what kind of investment are you making? A lot of mid-market companies are making best technology investments. They're on a public cloud, they're buying snowflake and they wanna understand what's, what's built to really make this work best over the next number of years. And those are very short sales for us because we, we prove that, you know, in, in minutes to hours, if you're working at a large enterprise and you have three or four other tools, you're asking a different question. >>And often you're asking a question of what I call exploration. We have a product that has dashboards and they've been working for us and we don't wanna replace the dashboard. But when we have a question about the data in the dashboard, we're stuck, how do we get to the raw data? How do we get to the example that we can actually manage? You can't manage a dashboard. You can't manage a trend line, but if you get into the data behind the trend line, you can make decisions to change business process, to change quality, accuracy, to change speed of execution. That is what we're trying to enable. Those conversations happen between the it team who runs technology and the business teams who are responsible for the decisions. So we are, you know, we have a cross departmental sale, but across every department, >>One of the things we're not talking about at this event, which is kind of interesting, cause it's all we've been talking about is the macro supply chain challenges, Ukraine, blah, blah, blah, and the stock market. But, but how are you thinking about that? Macro? The impacts you're seeing, you know, a lot of private companies being, you know, recapped, et cetera, you guys obviously very well funded. Yeah. But how do you think about, I mean, I asked Frank a similar question. He's like, look, it's a marathon. We don't worry about it. We, you know, they made the public market, they get 5 billion in cash. Yeah. Yeah. How are you thinking about it? >>You know, first of all, what's the expression, right? You never, never waste a good, you know, in this case recession, no, we don't have one yet, but the impetus is there, right. People are worried. And when they're worried, they're thinking about their bottom lines, they're thinking about where they're going to get efficiency and their costs. They're already dealing with the supply chain issues of inventory. We all have it in our personal lives. If you've ordered anything in the last six months, you're used to getting it in, you know, days to weeks. And now you're getting in months, you know, we had customers like us foods as a good example, like they're constantly trying to align inventory. They have with transportation that gets that inventory to their end customers, right? And they do that with better data accuracy at the end point, working with us on what we are launching. >>And I mentioned earlier, having more people be able to update that data creates more data, accuracy creates better decisions. We align that then with them and better collaboration with the folks that then coordinate the trucks with Prologis and the panel yesterday, they're the only commercial public company that reports their, their valuations on a quarterly basis. They work with Sigma to trim the amount of time it takes their finance team to produce that data that creates investor confidence that holds up your stock price. So I mean the, the importance of data relative to all the stakeholders in enterprise cannot be overstated. Supply chain is a great example. And yes, it's a marathon because a lot of the technology that drives supply chain is old, but you don't have to rip out those systems to put your data into snowflake, to get better access through Sigma, to enable the people in your environment to make better decisions. And that's the good news. So for me, while I agree, there's a marathon. I think that most of the, I dunno if I could continue this metaphor, but I think we could run quite far down that marathon without an awful lot of energy by just making those couple of changes. >>Awesome. Mike, this has been fantastic. Last question. I, I can tell, I know a lot of growth for Sigma. I can feel it in your energy alone. What are some of the key priorities that you're gonna be focusing on for the rest of the year? >>Our number one priority, our number two priority and number three priority are always build the best product on the market, right? We, we want customers to increase usage. We want them to be delighted. You know, we want them to be RA. Like we have customers at our booth that walk up and it's like, you're building a great company. We love your product. I, if you want to show up happy at work, have customers come up proactively and tell you how your products changed their life. And that is, that is the absolute, most important thing because the real marathon here is that enablement over the long term, right? It is being a great provider to a bunch of great companies under that. We are growing, you know, we've been tripling the company for the fast few years, every year, that takes a lot of hiring. So I would've alongside product is building a great culture with bringing the best people to the company that I guess have my energy level. >>You know, if you could get paid in energy, we would've more than tripled it, you know, but that's always gonna be number two, where we're focused on the segment side, you know, is really the large enterprise customer. At this point, we are doing a great job in the mid-market. We have customer, we have hundreds of customers in our free trial on a constant basis. I think that without wanting to seem over confident or arrogant, I think our technology speaks for itself and the product experience for those users, making a great ROI case to a large enterprise takes effort. It's a different motion. We're, we're very committed to building that motion. We're very committed to building out the partner ecosystem that has been doing that for years. And that is now coming around to the, the snowflake and all of the ecosystem changes around snowflake because they've learned these customers for decades and now have a new opportunity to bring to them. How do we enable them? That is where you're gonna see Sigma going over the next couple of years. >>Wow, fantastic. Good stuff. And a lot of momentum, Mike, thank you so much for joining Dave and me talking about Sigma, the momentum, the flywheel of what you're doing with snowflake and what you're enabling customers to achieve the massive business outcomes. Really cool stuff. >>Thank you. And thank you for continuing to give us a platform to do this and glad to be back in conferences, doing it face to face. It's fantastic. >>It it's the best. Awesome. Mike, thank you for Mike Palmer and Dave ante. I'm Lisa Martin. You've been watching the cube hopefully all day. We've been here since eight o'clock this morning, Pacific time giving you wall the wall coverage of snowflake summit 22 signing off for today. Dave and I will see you right bright and early tomorrow morning. I will take care guys.

>>Oh, well, the back to the cubes coverage of ADA bus reinvent, 2021 executive seminar, I'm John ferry hosts of the cube. We've got a great segment here on the modernization. We were ringing in the success with Amazon web services, Vodafone digital in the UK, an example of modern engineering examples using Amazon, the cloud, looking at where we're cloud native is actually changing the game two great guests, Ben Collie, head, head of digital engineering, Vodafone UK, and Maynard Williams, managing director of center. Gentlemen, thank you for coming on the cube and sharing the story. >>Thanks, John. Appreciate it. So >>I gotta, I gotta ask you guys one of the main themes that we've been covering all year and even even pre pandemic, we, we saw the cloud native wave coming pretty hard containers. Great for modernization sets the table. You seeing things like Kubernetes and now serverless changing the game on all aspects of how modernization is happening. And everyone's talking about application modernization shift left all great for business, but you have to, you have to kind of take care of things under the, under the covers a little bit, the infrastructure, making sure the engineering teams are all set. So this has been a top topic. This is kind of what you guys are doing. Can you guys explain to me the needs that Vodafone has, um, that brought about this transformation? >>Yeah, sure. Um, so we we've been on this transformation for around four years, but you're absolutely right. The, uh, the pandemic has been a real catalyst for, for all kinds of organizations like ours around the world. Uh, so we were really driving a digital first agenda for quite a long time. Uh, and that, that came as, as you just said, John, it, it really did start with the, uh, the cloud hosted, uh, and then, uh, and then moving and realizing the difference between that and become native to the, to the cloud and really leveraging the services, uh, like AWS, um, in order to really drive pace, uh, and, and the outcomes that we needed for the business. Uh, we've seen a huge change over the last, uh, purely over the last 18 months, really. Um, our daily traffic, uh, these days is as it was on our highest ever, uh, uh, like an iPhone launch day, for example, um, before the pandemic, is I a daily traffic these days. And so that scalability and flexibility and that leveraging those services has been absolutely fundamental to supporting the, the changing needs and expectations of our customers. >>You know, back in the old days, uh, Maynard, you know, it's oh yeah, black Friday surge, you need the cloud to scale up and be flexible. Agile elastic, you know, scale is definitely now table stakes. And if you're not dealing with scale and some sort of either SRE fashion or whatever, you, you really ain't going to be behind the curve, but the next level that's being discussed is how do you leverage the scale for not just customer experience and business value, but we're talking about system architecture, kind of thinking there's kind of, this is our system design is now a big part of it. Can you talk about how this kind of threads together? Because we always talk about consumer experience, customer experience CX, but now there's a new system was mindset out there. Can you kind of share your vision on that >>Thing that stands out for me is if I look at digital, we've designed it to a point where the scale is just as you say, it's the table stakes, and only for launch with something that two years ago needed to be planned and thought about. And it's now absolutely routine. We think about the business side of it, but a big increase in scale really is seamless. But if I look at the full stack, we're still connected into some of the older backend systems, um, where any production, uh, they were on prime actually tasks. This is on AWS now, which is a big step forward, but when you've got to manage scaling in a way that translates from backend systems that are on premises on prime, and therefore we can't lastingly scale through to the front tab where we have to be able to scale up very seamlessly and balancing that across with, uh, an architecture that supports that level of scale and makes it so seamless on something like, as you say, iPhone launches or back Friday, any product coming out is actually key to the way we've architected that. >>So you're saying that essentially AWS combined with Vodafone worked on this solution that was more of a cloud native solutions that the innovation here, can you just summarize and unpack a little bit of what is the innovation, what problems did you solve together with essentially those and Vodafone? What was the core challenge? Yes. >>I think that the core is actually, how do you get to the point where, um, at the scaling is seamless, where you can move from being on the cloud to cloud native has been, just touched on what the same time you're actually connected into an enterprise state where the production systems are all on prem and don't have that ability to scale in the same fraction. So you can't, for example, push you to load into, uh, an on-prem backend system and, and simply expected to scale in the same fashion. So between our three organizations architecting something that is robust scales, we usable and takes away a load of pieces that actually were quite complex two years ago. And turns them into just routine has been a big step forward. >>And I want to get your reaction to this because, you know, you're, you're the you're on the, on the front line saying, Hey, be more agile at Basel saying, be agile, do different left, take that hill. Um, it's, it's easier said than done. Talk about what goes on when you have to implement and the stakes involved. Again, there's always the old way, new way. Can you just kind of give some color on what's going on? What's your perspective showing? >>And as I just said, that the real benefits and the story behind this was the ability to launch an iPhone. For example, as a event for Vodafone previously was weeks and months of preparation and design and testing and confidence building. And now it really is, it just happens. Uh, and we watched things scale and, and, and then down again, gracefully, um, and really do celebrate the, the another level up, if you like the leveling up of us as an organization, allowing our commercial colleagues to, to launch propositions or to launch campaigns without needing us to be involved anymore, because they're confident, we're all that things will, will flex like that. But you're absolutely right, that, that the changes and the demands of us as a, as a team, but also the, the expectations of our stakeholders, uh, have been changing for quite a long time now. Uh, and we're really excited now to be able to meet them by leveraging the services that we're discussing. >>Yeah. So the guys say said launched the iPhone, no big deal routine, hit the pub. Everyone's happy having a good day. >>Uh, >>Let's get into the solution, how it works. Talk about what's going on with the covers. How does this all work? Can you take us through, what's the state of the art of the, of the solution? Sure. >>Well, uh, as you mentioned earlier, we were very much inclined to serverless these days. So we rolled out fire gate, um, a few, uh, uh, started about 18 months ago. Um, and that really has, um, freed us up in, into all kinds of, um, uh, scalability, uh, measures, but also really about, about reusing and applying this across much more than just the, the engineering or the digital part of Vodafone, where we, where we began. So that's been a really big part of our agenda, uh, and that's, that's informed all kinds of things, the ability to scale and flex like that, and the architecture beneath us, um, and the containerization and orchestration that that goes along with that has really enabled us to, um, to flex that, uh, ability to, to reuse it across other areas. And because of that, now it's driven our hiring policy or tooling and, uh, technical, uh, our procedural approaches, uh, it all now leverages that ability to move a patient, to be able to scale, uh, not just in, um, uh, infrastructure or ability to serve customers, but in ability to deliver for the business commercially as well. Uh, and this is all now informed on our direction. I think, as an organization, >>It's interesting, you mentioned far you far gate than a trigger of events happens. People get excited, opens up new doors of opportunities as a chain reaction from that. Um, talk about the impact to the staff and the operations, because you almost, it's motivating at some level you get new things happening, but you're actually making things go better and faster, cheaper. >>Yeah. Uh, well, the, the impact is one, uh, because we're on a journey at Vodafone of this transformation, really becoming a technology business first and foremost, rather than a telco classically like our competitors, uh, we're able to really drive cultural change as well. So the impact on our people is a really, it's been particularly engaging. One with, we've also been part of, uh, a real recruitment drive. We've just announced 7,000 new, uh, roles, uh, joining our team across Europe and that these are engineering roles, um, driving more of the same, uh, behaviors and principles of a modern software engineering business like ours. Uh, and that really is fueled by our, our ability to experiment and try, but become cloud native and, and, uh, employ these services in the way that they're designed to be >>Maynard. I'd like to get your take on this and, and, and shift to a topic around how, what this all means. Um, if you zoom out and you say, okay, with the pandemic, it's become a mobile virtual hybrid. Now world around work play, all those lines are kind of blurring. It's not as clean as it used to be. Oh, the network segmented over here. This is over here. These legacy systems were built around the notion of things when nicely segmented. Um, now you have this whole kind of mashup, if you will, of how you just want to work, right. There's mobilization is a huge thing. So access identity, these are things that we're all kind of set up nicely before the pandemic, or at least, you know, not as, uh, stable, maybe not scalable, but what's your take on this? What's the big picture what's all happening. >>I think, I mean, the pandemic has accelerated a set of changes that were already happening anyway. And I'd say the other particles is under the covers. A lot of the work's been done has been to create the microservices that stitch together to produce those journeys, but, you know, running the containers. And so that, that opens up an omni-channel future that starts to move away from saying actually businesses are organized around the environment in which they're serving. Is it a retail store? Is it, is it online that additional and so on, and actually into much more of a space where you're building the best journeys and those journeys come and are served through digital or through a call center or through a store and so on. And that makes a huge difference because the focus on improving the customer's experience has been enormous. And I think that's one of the other parts that come out of the whole cloud native setup. >>And the ability to experiment has been iteratively and endlessly improving the experience for the customer. And that's, that's a, that's a massive step forward. So we can talk about the fact that we deploy a huge number of times more frequently than we did even a year ago, uh, or the, you know, our quality has improved by a massive percentage and so on. And I think the thing that's really interesting is the improvement in the experience and the endless improvement and iteration of that, because we can make lots and lots of small changes and do every day. That's a big one, >>You know, what's interesting Ben, and let's get your reaction on this. And if you don't mind to just add a little color to this, this is just another example of reports that we've been talking with folks on where it's not about just replatforming to the cloud. It's refactoring the business, uh, with, with the engineering, the modernization. And so there's two things that go on one, you see the efficiencies and new doors open up new things are happening. People are getting excited, good, some good Mo morale boosting things are becoming clear, but then there's actually new business, new business value being created or new propositions engineering propositions. Can you share from a digital standpoint, because this seems to be the new role of the digital person, whether it's engineering or on the business side, make things run faster, cheaper, and better, and then create new opportunities, new propositions, what's your >>Absolutely. Yeah. Yeah. It's fundamentally around pace of delivery. Uh, being able to, as, as may not says, uh, moving from a world, uh, two or three years ago where we were deploying once every two or three months, uh, this is a website once every two or three months where we were, uh, to now it's happening all the time every day. Uh, it's, it's, it's a skill that we've given us as an organization that we couldn't have leveraged before. And what we're able to do with that now is experiment our way and iterate our way to new value streams, as you say, but also trial and error. What we already know, uh, or expects to be true with our customers much, much more easily and much, much more frequently, very little a barrier to production or friction between us and the customer these days, and the almost instant response and feedback we get from customers. Um, we, we learn constantly about because of that. And it's, uh, it's become much less of a stab in the dark with large business cases where they work well, they worked and are much more experimental initiative. Uh, we, most of the propositions we know about, but also to the experiments, um, and unknowns in our future. Um, that also now unlocked, >>That's a great point. You mentioned about the whole timing of, you know, the old way, months, weeks, just for website stuff, uh, Maynard. And if you guys can share this new world order is actually pretty exciting, but also daunting if you're not like in the water, so to speak, right? So, you know, some people are actually, you know, putting their toe in the water, they're experimenting, but it's a game changer. I mean, a significant step up of value. What's your advice about solutions and they're not easy. I mean, you just got to get your hands around the sensor. You guys have been doing a lot more of these projects is seeing more and more of these, these kinds of partnerships, uh, and the value is there. Can you guys share your, your, uh, opinion and advice to folks out there watching saying, how do I do this and is it going to be worth it? Is that bridge to the future there? >>I mean, I think there's a mechanical piece. How do I enable this? And we can talk about dev ops and moving to cloud native, and actually some of the, some of the process side of as an organization, how do I get really comfortable with deploying very frequently and it being low risk and routine. And so the other part for me, which we sort of haven't touched on is as much as we talk about experimentation, it's about the data and the analytics and the knowledge that we create of that. So the, the, the small changes we're making are highly scientific. And when we think about actually understanding how we're optimizing experiences, that's all about the whole set of data points that I'm pinning up. And so I'll take two parts is know the, the journey we've been on here is, is about enablement. It's about moving the architecture. It's about moving the ways of working so that a lot of things that were hard or required thinking about two years ago on that quality team. But the other part of it is understanding the data and having the analytics capability and being able to make a very scientific experiment where you can see the result in the day-to-day >>Ben, what's your reaction advice to folks watching as they modernize exciting, challenging. It's a lot of hard work, but what's it look, it's the end game, >>All of those things, yes. I'd say it's, um, more than anything, it's a necessity these days we have to embark on this journey. It is, it is daunting. And, and of course, a lot of large organizations like ours, we were successful for doing things in a particular way, uh, have built up a lot of, uh, protection mechanisms for doing, for making sure we protect that. And so to come at it from a new angle is, is obviously daunting. And it's very challenging as well. There is an immune system in all of our organizations that is real, but I'll deal with it. Um, but the, the real, um, success behind, uh, the real, I think the reasons behind a lot of our success has been beat by being able to quickly prove value to quickly prove that outcomes are deliverable and achievable. Um, and then to build on those and iterate on it. And as, as I said, it's, it's about being able to move at pace for us in Vodafone. It's about leveraging our scale. We're a huge organization. Um, and we're, we're now coming together as one to really make sure that we do just lean on that scale more than we have them. Yeah, that's really about iterating, as I said, and, and, um, finding things that work, keep doing it, finding things that hold you back and get rid of them as quickly as you can, uh, is what I would say for us. >>It's interesting. You mentioned the scale. The thing about the cloud is when I hear the common pattern is it takes advantage of the strengths of your environment. You know, so every environment is a bit different, but you guys have the scale. I have to ask you while you're here. What are some of the anecdotal comments that kind of, you hear from folks that make you happy? When about the results? I think saying, Hey man, I'm not even seeing this anymore, or, wow. This is faster. What's some of the sound bites that you guys take as proof points of the success of this project. >>Yeah. It's, uh, I'd say it's mainly an R there's two things I would say, uh, the ability to rely less on it delivery if you like. So empowering our commercial business to make changes for themselves in a safe and secure manner. So providing these self-service capabilities, we've started to see a real pace about our commercial business, as well as our technology business. Uh, but also the, the time it takes to get things out is probably one of the biggest, uh, really tangible results and outcomes for us at the moment. Um, just the sheer amount of things we can release to production, uh, in, in sorts of short space, space of time really does bring to life, our ability to now trial and error, to AB test a Canary deploy. Things like that is really, um, it's been a real superpower for our, um, transformation, I think yes. >>Kind of kidding about can't make time to go to the pub, but in reality, it's free time freeing up people from doing those tasks that were slower shifting that value. >>Yeah. Whereas as you mentioned, Johnny, it really is much more than a technical journey. This is a cultural one as well for a lot of organizations and, um, by being more connected, by being more connected to the outcomes or the value that you add into production, uh, it really does drive a new culture and engagement across our teams. You know, if it's six months between writing a line of code and seeing it in production by up no sense of ownership or pride in what I've done there, but if I can deploy code immediately see an impact good or bad, um, then, uh, I really do feel connected to the outcomes and the value that I'm driving to, to the business and to our customers. So there really is a great cultural, >>Yeah. I remember Andy Jassy last year when he was a sea of AWS on stage and talked about that dynamic of the teamwork, people rowing in the right direction. Um, feeling part of it may know this is a cultural shift on how companies do business. I know center I've covered probably a dozen or so killer projects that have just been awesomely new and kind of different, but successful built on the cloud. So a lot of replatforming refactoring you're in the front lines, working with, uh, companies that essentially what's the pattern that you see that's that's happening right now. What's the, what's your view of the current market? >>Um, I mean, I think there's a huge shift to this, that this journey too has been part of the move from being on the cloud to being proud nature. I'm really getting that value because there's a, um, a kind of, almost a example. I see there's a light bulb moment where ownership of what you put in production means that you move away from a model of we change code because either the business tell us too, because they have a functional requirement or because something's broken. When we get into the model of that, I want to improve the thing that I feel ownership of. That's not leave. And you suddenly see how much difference that makes to the experience of it, the quality of it, the stability, all of those things improving. And so if, if I look more generally that cultural shift is it is an evolution that organizations go through and it starts with actually delivering it in a more agile way. At some large scale, you see agility moving up into kind of business agility and starting to affect things like budgeting cycles and the kind of corporate functions. If you like that tend to sit around, uh, you know, supporting Pete pieces of delivery. And there's a lot more of that happening at the moment, a load with more organizations pushing into being properly cloud native and transforming rather than the kind of first wave, which was the shift onto the cloud. Now it's actually, that's really leveraged what we've got with the, >>Yeah. And you guys essentially have been riding on the wave of AWS and the cloud for many, many years. We've been covering it. Ben great success story. Thanks for coming on the cube, a head of digital engineering, Vodafone UK, great example of modern engineering at work using AWS in Europe. Uh, thanks for coming on the Cuban, sharing your story. Maynor thank you for also coming on and the work you're doing at Accenture and AWS. Thank you. Thanks John. The cube coverage of AWS reinvent 2021 executive summit. I'm John furry, your host. Thanks for watching.

>>Good day. And thanks for joining us as we continue our series here on the Coupa, the AWS startup showcase featuring today, big ID and what this is, will Murphy was the vice president of business development and alliances at big idea. Well, good day to you. How are you going today? Thanks John. I'm doing well. I'm glad to be here. That's great. And acute belong to, I might add, so it's nice to have you back. Um, let's first off, let's share the big ID story. Uh, you've been around for just a handful of years accolades coming from every which direction. So obviously, uh, what you're doing, you're doing very well, but for our viewers who might not be too familiar with big ID, just give us a 30,000 foot level of your core competence. Yeah, absolutely. So actually we just had our five-year anniversary for big ID, uh, which we're quite excited about. >>Um, and that five-year comes with some pretty big red marks. We've raised over $200 million for a unicorn now. Um, but where that comes to and how that came about was that, um, we're dealing with, um, longstanding problems with modern data landscape security governance, privacy initiatives, um, and starting in 2016 with the, uh, authorship of GDPR, the European privacy law organizations, how to treat data differently than they did before they couldn't afford to just sit on all this data that was collected for a couple of reasons, right? Uh, one of them being that it's expensive. So you're constantly storing data, whether that's on-prem or in the cloud is we're going to talk about there's expense that you have to pay to secure the data and keep it from being leaked. You have to pay for access control. It's paid for a lot of different things and you're not getting any value out of that. >>And then there's the idea of like the customer trust piece, which is like, if anything happens to that data, um, your reputational, uh, your reputation as a company and the trust you have between your customers and your organization is broken. So big ID. What we did is we decided that there was a foundation that needed to be built. The foundation was data discovery. If you even an organization knows where its data is, whose data it is, where it is, um, and what it is, and also who has access to it, they can start to make actionable decisions based on the data and based on this new data intelligence. So we're trying to help organizations keep up with modern data initiatives and we're empowering organizations to handle their data sensitive, personal regulated. And what's actually quite interesting is we allow organizations to define what's sensitive to them because like people, organizations are all different. >>And so what's sensitive to one organization might not be to another, it goes beyond the wall. And so we're giving organizations that new power and flexibility, and this is what I still find striking is that obviously with this exponential growth of data and machine learning, just bringing billions of inputs, it seems like right. All of a sudden you have this fast reservoir data, is that the companies in large part, um, don't know a lot about the data that they're harvest state and where it is. And so it's not actionable, it's kind of dark data, right. Just out there reciting. >>Um, and so as I understand it, this, this is your focus basically is tell people, Hey, here's your landscape. Uh, here's how you can better put it to action, why it's valuable and we're going to help them protect it. Um, and they're not aware of these things, which I still find a little striking in this day and age, >>And it goes even further. So, you know, when you start to, when you start to reveal the truth and what's going on with data, there's a couple things that some organizations do. Uh, and I think human instincts, some organizations want to bury their head in the sand. I'm like, everything's fine. Uh, which is, as we know, and we've seen the news frequently, not a sustainable approach. Uh, there's the, there's the, like, let's be a, we're overwhelmed. We don't, we don't even know. We don't even know where to start. Then there's the natural reaction, which is okay. We have to centralize and control everything which defeats the purpose of having, um, shared drives and collaboration and, um, geographically disparate workforces, which we've seen particularly over the last year, how important that resiliency within organizations is to be able to work in different areas. And so, um, it really restricts the value that, um, organizations can get from their data, which is important. And it's important in a ton of ways. Um, and for customers that have allowed their, their data to be, to be stored and harvested by these organizations, they're not getting value out of it either. It's just risk. And we've got to move data from the liability side of the balance sheet, um, to the assets out of the balance sheet. And that comes first and foremost with knowledge. >>So everybody's vote cloud, right? Everybody was on prem and also we build a bigger house and build a bigger house, better security, right in front of us, got it, got to grow. And that's where I assume AWS has come in with you. And, and this was a two year partnership that you've been engaged with in AWS. So maybe shine a little light on that, about the partnership that you've created with AWS, and then how you then in turn transition that, to leverage that for the betterment of your >>Customer base. Yeah. So AWS has been a great partner. Um, they are very forward-looking for an organization, as large as they are very forward looking that they can't do everything that their customers need. And it's better for the ecosystem as a whole to enable small companies like us. And we were very small when we started our relationship with them, uh, to, to join their partner organization. So we're an advanced partner. Now we're part of ISV accelerate. So it's a slightly more lead partner organization. Um, and we're there because our customers are there and AWS like us, but we both have a customer obsessed culture. Um, but organizations are embracing the cloud and there's fear of the cloud. There's there really shouldn't be in the, in the way that we thought of it, maybe five or 10 years ago. And that, um, companies like AWS are spending a lot more money on security than most organizations can. >>So like they have huge security teams, they're building massive infrastructure. And then on top of that, companies themselves can do, can use, uh, products like big ID and other products to make themselves more secure, um, from outside threats and from, from inside threats as well. So, um, we are trying to with them approach modern data challenge as well. So even within AWS, if you put all the information in, like, let's say S3 buckets, that doesn't really tell you anything. It's like, you know, I, I make this analogy. Sometimes I live in Manhattan. If I were to collect all the keys of everybody that lived in a 10 block radius around me and put it into a dumpster, uh, and keep doing that, I would theoretically know where all the keys were there in the dumpster. Now, if somebody asked me, I'd like my keys back, uh, I'd have a really hard time giving them that because I've got to sort through, you know, 10,000 people's keys. >>And I don't really know a lot about it, but those key sale a lot, you know, it says, are you in an old building, are you in a new building? You have a bike, do you have a car? Do you have a gym locker? There's all sorts of information. And I think this analogy holds up for data because of the way you store your data is important, but, um, you can gain a lot of theoretically innocuous, but valuable information from the data that's there while not compromising the sensitive data. And as an AWS has been a fabulous partner in this, they've helped us build a AWS security, have integration out of the box. Um, we now work with over 12 different AWS native, uh, applications from anything like S3 Redshift and Sienna, uh, Kinesis, as well as, um, apps built on AWS like snowflake and Databricks that we, that we connect to. >>And AWS, the technical team of department teams have been an enormous part of our success there. We're very proud of joining the marketplace to be where our customers want to buy enterprise software more and more. Um, and that's another area that we're collaborating, uh, in, in, in joint accounts now to bring more value in simplicity to our joint customers. What's your process in terms of your customer and, uh, evaluating their needs because you just talked about earlier, you had different approaches to security. Some people put their head in the sand, right? Some people admit that there's a problem. Some people fully engaged. So I assume there's also different levels of sophistication in terms of whatever you have in place and then what their needs are. So if you would shine a little light on that, you know, where they are in terms of their data landscape and AWS and its tools, but you just touched them on multiple tools you have in your service. >>Now, all that comes together to develop what would be, I guess, a unique program for a company's specific needs. It is. We started talking to the largest enterprise accounts when we were founded and we still have a real proclivity and expertise in that area. So the issues with the large enterprise accounts and the uniqueness there is scale. They have a tremendous amount of data, HR data, financial data, customer data, you name it, right? Like, we'll go. We can, we can go dry mouth talking about how many you're saying data. So many times with, with these large customers, um, freight Ws scale, wasn't an issue. They can store it, they can analyze it. They can do tons. It where we were helping is that we could make that safer. So if you want to perform data analytics, you want to ensure that sensitive data is not being, or that you want to make sure you're not violating local, not national or industry specific regulations. >>Financial services is a great example. There's dozens of regulations at the federal level in the United States and each state has their own regulations. This becomes increasingly complex. So AWS handles this by, by allowing an amazing amount of customization for their customers. They have data centers in the right places. They have experts on, on, uh, vertical, specific issues. Big ID handles this similarly in some ways, but we handle it through ostensive ability. So one of our big things is we have to be able to connect to every everywhere where our customers have data. So we want to build a foundation of like, let's say first let's understand the goals is the goal compliance with the law, which it should be for everybody that should just be like, we need to, we need to comply with the law. Like that's, that's easy. Yeah. Then as the next piece, like, are we dealing with something legacy? >>Was there a breach? Do we need to understand what happened? Are we trying to be forward-looking and understanding? We want to make sure we can lock down our most sensitive data, tier our storage tier, our security tier are our analytics efforts, which also is cost-effective. So you don't have to do, uh, everything everywhere, um, or is the goal a little bit like we needed to get a return on investment faster, and we can't do that without de-risking some of that. So we've taken those lessons from the enterprise where it's exceedingly difficult, uh, to work because of the strict requirements, because the customers expect more. And I think like AWS, we're bringing a down market. Uh, we have some, a new product coming out. Uh, it's exclusive for, uh, AWS now called small ID, which is a cloud native, a smaller version, lighter weight version of our product for customers in the more commercial space in the SMB space where they can start to build a foundation of understanding their data or, um, protection for security for, for, for privacy. >>And, and before I let you go here, what I'd like to hear about is practical application. You know, somebody that, that you've, you know, that you were able to help and assist you evaluated. Cause you've talked about the format here. You've talked about your process and talk about some future, I guess, challenges, opportunities, but, but just to give our viewers an idea of maybe the kind of success you've already had to, uh, give them a perspective on that, this share a couple stories. If you wouldn't mind with some work that you guys did and rolled up your sleeves and, and, uh, created that additional value >>For your customers. Yeah, absolutely. So I'll give a couple examples. I'm going to, I'm going to keep everyone anonymized, uh, as a privacy based company, in many ways, what we, we try to respect colors. Um, but let's talk about different types of sensitive data. So we have customers that, um, intellectual property is their biggest concern. So they, they do care about compliance. They want to comply with all local and national laws where they, where they, their company resides all their offices are, but they were very concerned about sensitive data sprawl around intellectual property. They have a lot of patents. They have a lot of sensitive data that way. So one of the things we did is we were able to provide custom tags and classifications for their sensitive data based on intellectual property. And they could see across their cloud environment, across their on-premise environment across shared drives, et cetera. >>We're sensitive data had sprawl where it had moved, who's having access to it. And they were able to start realigning their storage strategy and their content management strategy, data governance strategy, based on that, and start to, uh, move sensitive data back to certain locations, lock that down on a higher level could create more access control there, um, but also proliferate and, uh, share data that more teams needed access to. Um, and so that's an example of a use case that I don't think we imagined necessarily in 2016 when we were focused on privacy, but we've seen that the value can come from it. Um, so yeah, no, I mean, the other piece is, so we've worked with some of the largest AWS customers in the world. Their concern is how do we even start to scan the Tedder, terabytes and petabytes of data in any reasonable fashion? >>Uh, without it being out of date, if we create this data map, if we prayed this data inventory, uh, it's going to be out of date day one, as soon as we say, it's complete, we've already added more. That's where our scalability fit Sam. We were able to do a full scan of their entire AWS environment and, uh, months, and then keep up with the new data that was going into their AWS environment. This is a, this is huge. This was groundbreaking for them. So our hyper scan capability, uh, that we've wrote, brought out that we rolled out to AWS first, um, was a game changer for them to understand what data they had and where it is who's it is et cetera at a way that they never thought they could keep up with. You know, I I'm, I brought back to the beginning of code when the British government was keeping track of all the COVID cases on spreadsheets and spreadsheet broke. >>Um, it was also out of date, as soon as they entered something else. It was already out of date. They couldn't keep up with them. Like there's better ways to do that. Uh, luckily they think they've moved on from, from that, uh, manual system, but automation using the correct human inputs when necessary, then let, let machine learning, let, uh, big data take care of things that it can, uh, don't waste human hours that are precious and expensive unnecessarily and make better decisions based on that data. You know, you raised a great point too, which I hadn't thought of about the fact is you do your snapshot today and you start evaluating all their needs for today. And by the time you're going to get that done, their needs have now exponentially grown. It's like painting the golden gate bridge, right. You get that year and now you've got to pay it again. I said it got bigger, but anyway, they will. Thanks for the time. We certainly appreciate it. Thanks for joining us here on the sort of showcase and just remind me that if you ever asked for my keys, keep them out of that dumpster to be here.

(upbeat music) >> Well, good day and thank you for joining us as we continue our series here on theCUBE of the AWS Startup Showcase featuring today BigID. And with us is Will Murphy, who's the Vice President of the Business Development and Alliances at BigID. Will, good day to you, how are you doing today? >> Thanks John, I'm doing well. I'm glad to be here. >> Yeah, that's great. And theCUBE alum too, I might add so it's nice to have you back. Let's first off, let's share the BigID story. You've been around for just a handful of years. Accolades coming from every which direction so obviously what you're doing, you're doing very well. But for our viewers who might not be too familiar with BigID, just give us a 30,000 foot level of your core competence. >> Yeah absolutely. So actually we just had our five-year anniversary for BigID, which we're quite excited about. And that five year comes with some pretty big red marks. We've raised over $200 million for a unicorn now. But where that comes to and how that came about was that we're dealing with longstanding problems with modern data landscapes, security governance, privacy initiatives. And starting in 2016 with the authorship of GDPR, the European privacy law organizations had to treat data differently than they did before. They couldn't afford to just sit on all this data that was collected. For a couple reasons, right? One of them being that it's expensive. So you're constantly storing data whether that's on-prem or in the cloud as we're going to talk about. There's expense to that. You have to pay to secure the data and keep it from being leaked, You have to pay for access control, you have to pay for a lot of different things. And you're not getting any value out of that. And then there's the idea of the customer trust piece, which is like if anything happens to that data, your reputation as a company and the trust you have between your customers and your organization is broken. So BigID, what we did is we decided that there was a foundation that needed to be built. The foundation was data discovery. If an organization knows where its data is, whose data it is, where it is, and what it is and also who has access to it, they can start to make actionable decisions based on the data and based on this new data intelligence. So, we're trying to help organizations keep up with modern data initiatives. And we're empowering organizations to handle their data, sensitive, personal regulated. What's actually quite interesting is we allow organizations to define what's sensitive to them because like people, organizations are all different. And so what's sensitive to one organization might not be to another. It goes beyond the wall. And so we're giving organizations that new power and flexibility. >> And this is what I still find striking is that obviously with this exponential growth of data you got machine learning, just bringing billions of inputs. It seems like right now. Also you had this vast reservoir of data. Is that the companies in large part don't know a lot about the data that they're harvesting and where it is, and so it's not actionable. It's kind of dark data, right? Just out there residing. And so as I understand it, this is your focus basically is to tell people, hey here's your landscape, here's how you can better put it to action why it's valuable and we're going to help you protect it. And they're not aware of these things which I still find a little striking in this day and age >> And it goes even further. So you know, when you start to reveal the truth and what's going on with data, there's a couple things that some organizations do. And enter the human instincts. Some organizations want to bury their head in the sand like everything's fine. Which is as we know and we've seen the news frequently not a sustainable approach. There's the like let's be we're overwhelmed. Yeah. We don't even know where to start. Then there's the unnatural reaction, which is okay, we have to centralize and control everything. Which defeats the purpose of having shared drives and collaboration in geographically disparate workforces, which we've seen in particularly over the last year, how important that resiliency within organizations is to be able to work in different areas. And so it really restricts the value that organizations can get from their data, which is important. And it's important in a ton of ways. And for customers that have allowed their data to be stored and harvested by these organizations, like they're not getting value out of it neither. It's just risk. And we've got to move data from the liability side of the balance sheet to the assets side of the balance sheet. And that comes first and foremost with knowledge. >> So everybody's going cloud, right? Used to be, you know, everybody's on prem. And all of a sudden we build a bigger house. And so because you build a bigger house, you need better security, right? Your perimeter's got to grow. And that's where I assume AWS has come in with you. And this is a two year partnership that you've been engaged with in AWS. So maybe shine a little light on that. About the partnership that you've created with AWS and then how you then in turn transition that to leverage that for the benefit of your customer base. >> Yeah. So AWS has been a great partner. They are very forward-looking for an organization as large as they are. Very forward looking that they can't do everything that their customers need. And it's better for the ecosystem as a whole to enable small companies like us, and we were very small when we started our relationship with them, to join their partner organization. So we're an advanced partner now. We're part of ISV Accelerate. So it's a slightly more lead partner organization. And we're there because our customers are there. And AWS like us, we both have a customer obsessed culture. But organizations are embracing the cloud. And there's fear of the cloud, but there really shouldn't be in the way that we thought of it maybe five or 10 years ago. And that companies like AWS are spending a lot more money on security than most organizations can. So like they have huge security teams, they're building massive infrastructure. And then on top of that, companies themselves can can use products like big ID and other products to make themselves more secure from outside threats and from inside threats as well. So we are trying to with them approach modern data challenges well. So even within AWS, if you put all the information in like let's say S3 buckets, it doesn't really tell you anything. It's like, you know, I make this analogy sometimes. I live in Manhattan and if I were to collect all the keys of everybody that lived in a 10 block radius around me and put it into a dumpster and keep doing that, I would theoretically know where all the keys were. They're in the dumpster. Now, if somebody asked me, I'd like my keys back, I'd have a really hard time giving them that. Because I've got to sort through, you know, 10,000 people's keys. And I don't really know a lot about it. But those key say a lot, you know? It says like, are you in an old building? Are you in a new building? Do you have a bike? Do you have a car? Do you have a gym locker? There's all sorts of information. And I think that this analogy holds up for data but ifs of the way you store your data is important. But you can gain a lot of theoretically innocuous but valuable information from the data that's there, while not compromising the sensitive data. And as an AWS has been a fabulous partner in this. They've helped us build a AWS security, have integration out of the box. We now work with over 12 different AWS native applications from anything like S3, Redshift, Athena, Kinesis, as well as apps built on AWS, like Snowflake and Databricks that we connect to. And in AWS, the technical teams, department teams have been an enormous part of our success there. We're very proud to have joined the marketplace, to be where our customers want to buy enterprise software more and more. And that's another area that we're collaborating in joint accounts now to bring more value and simplicity to our joint customers. >> So what's your process in terms of your customer and evaluating their needs? 'Cause you just talked about it earlier that you had different approaches to security. Some people put their head in the sand, right? Some people admit that there's a problem. Some people fully are engaged. So I assume there's also a different level of sophistication in terms of what they already have in place and then what their needs are. So if you were to shine a little light on that, about assessing where they are in terms of their data landscape. And now AWS and its tools, which you just touched on. You know, the multiple tools you have in your service. Now, all that comes together to develop what would be I guess, a unique program for a company's specific needs. >> It is. We started talking to the largest enterprise accounts when we were founded and we still have a real proclivity and expertise in that area. So the issues with the large enterprise accounts and the uniqueness there is scale. They have a tremendous amount of data: HR data financial data, customer data, you name it. Right? Like, we could go dry mouth talking about how many insane data so many times with these large customers. For AWS, scale wasn't an issue. They can store it. They can analyze it. They can do tons with it. Where we were helping is that we could make that safer. So if you want to perform data analytics, you want to ensure that sensitive data is not being part of that. You want to make sure you're not violating local, national or industry specific regulations. Financial services is a great example. There's dozens of regulations at the federal level in United States. And each state has their own regulations. This becomes increasingly complex. So AWS handles this by allowing an amazing amount of customization for their customers. They have data centers in the right places. They have experts on vertical specific issues. BigID handles this similarly in some ways, but we handle it through extensibility. So one of our big things is we have to be able to connect to everywhere where our customers have data. So we want to build a foundation of like let's say first, let's understand the goals. Is the goal compliant with the law? Which it should be for everybody. That should just be like, we need to comply with the law. Like that's easy. Yeah. Then there's the next piece, like are we dealing with something legacy? Was there a breach? Do we need to understand what happened? Are we trying to be forward-looking and understanding? We want to make sure we can lock down our most sensitive data. Tier our storage, tier our security, tier are our analytics efforts which also is cost-effective. So you don't have to do everything everywhere. Or is the goal a little bit like we needed to get our return on investment faster. And we can't do that without de-risking some of that. So we've taken those lessons from the enterprise where it's exceedingly difficult to work because of the strict requirements because the customers expect more. And I think like AWS, we're bringing it down market. We have some new product coming out. It's exclusive for AWS now called SmallID, which is a cloud native. A smaller version, lighter weight version of our product for customers in the more commercial space. In the SMB space where they can start to build a foundation of understanding their data for protection and for security, for privacy. >> Will, and before I let you go here what I'd like to hear about is practical application. You know, somebody that you've, you know, that you were able to help and assist, you evaluated. 'Cause you've talked about the format here. You talked about your process and talked about some future, I guess, challenges, opportunities. But just to give our viewers an idea of maybe the kind of success you've already had. To give them a perspective on that. Just share a couple of stories, if you wouldn't mind. Whether there's some work that you guys did and rolled up your sleeves and created that additional value for your customers. >> Yeah, absolutely. So I'll give a couple examples. I'm going to keep everyone anonymized. As a privacy based company, in many ways, we try to respect-- >> Probably a good idea, right? (Will chuckles) >> But let's talk about different types of sensitive data. So we have customers that intellectual property is their biggest concern. So they do care about compliance. They want to comply with all the local and national laws where their company resides and all their offices are. But they were very concerned about sensitive data sprawl around intellectual property. They have a lot of patents. They have a lot of sensitive data that way. So one of the things we did is we were able to provide custom tags and classifications for their sensitive data based on intellectual property. And they could see across their cloud environment, across their on-premise environment, across shared drives et cetera, where sensitive data had sprawl. Where it had moved, who's having access to it. And they were able to start realigning their storage strategy and their content management strategy, data governance strategy, based on that. And start to move sensitive data back to certain locations, lock that down on a higher level. Could create more access control there, but also proliferate and share data that more teams needed access to. And so that's an example of a use case that I don't think we imagined necessarily in 2016 when we were focused on privacy but we've seen that the value can come from it. Yeah. >> So it's a good... Please, yeah, go ahead. >> No, I mean, the other (mumbles). So we've worked with some of the largest AWS customers in the world. Their concern is how do we even start to scan the Tedder terabytes and petabytes of data in any reasonable fashion without it being out of date. If we create this data map, if we create this data inventory, it's going to be out of date day one. As soon as we say, it's complete, we've already added more. >> John: Right. >> That's where our scalability fits in. We were able to do a full scan of their entire AWS environment in months. And then keep up with the new data that was going into their AWS environment. This is huge. This was groundbreaking for them. So our hyper scan capability that we brought out, that we rolled out to AWS first, was a game changer for them. To understand what data they had, where it is, who's it is et cetera, at a way that they never thought they could keep up with. You know, I brought back to the beginning of code when the British government was keeping track of all the COVID cases on spreadsheets and spreadsheets broke. It was also out of date. As soon as they entered something else it was already out of date. They couldn't keep up with it. Like there's better ways to do that. Luckily they think they've moved on from that manual system. But automation using the correct human inputs when necessary. Then let machine learning, let big data take care of things that it can. Don't waste human hours that are precious and expensive unnecessarily. And make better decisions based on that data. >> Yeah. You raised a great point too which I hadn't thought of about. The fact is, you do your snapshot today and you start evaluating all their needs for today. And by the time you're able to get that done their needs have now exponentially grown. It's like painting the golden gate bridge. Right? You get done and now you got to paint it again, except it got bigger. We added lanes, but anyway. Hey, Will. Thanks for the time. We certainly appreciate it. Thanks for joining us here on the startup showcase. And just remind me that if you ever asked for my keys keep them out of that dumpster. Okay? (Will chuckles) >> Thanks, John. Glad to be here. >> Pleasure. (soft music)