>>Mhm. Mhm Hello and welcome back to the cubes coverage of AWS summit here. Public sector summit here in Washington, D. C. I'm john for your host, We're live at a physical event. People face to face. We're here with the cube on the ground back in business. Of course we have a virtual cube. We got the cube studios in Palo alto in boston. We're gonna bring you all the great coverage and our next guest is parallel casa, Anita Casanova got it. Chief of Channels at Pegasystems, also known as mega official titles, head of global partner ecosystem. But you're known as the Chief of channels. >>Absolutely, thank >>you for coming on. >>Absolutely nice to be here face to face in an event. >>Feel happy, feels good. It feels great. People are happy. I'm still good attendance. Considering what it is about 5, 6000 people roughly give or take maybe up to 7000, who knows. But you guys have a really strong relationship with AWS, you're the chief of the channel. You guys have a great enabling product that crashes itself, as you guys say. So let's get into it before explain what PEG A does. >>Okay, so paga he's a $1 billion dollar company. It's a software company and we call it that software built itself Because we are definitely here to crash customer complexity. So we do it by three doing three things, 1-1 customer engagement customers, customer service and also intelligent automation. So we are a platform and we are helping any single client that has a complex solution to make it simple and to have a good customer experience. >>So I got it wrong. It doesn't crash itself, it crashes complexity, It builds itself okay there it is. All right, I got that out of the way. Software that crashes itself actually doesn't really kind of doesn't sound like a compelling products, but it's not the case. So I gotta ask you So ecosystems are a big part of the cloud amazon has a great ecosystem but the ecosystem has ecosystem is starting to see an expansion of the cloud business with the software model. With cloud scale. What are you guys doing in the channel within the public sector? How do you guys work, how do people engage with you? >>Okay, so first of all we we were always very friendly channel partner but we were using our partners only for implementation because our product is so so uh built for each of the clients, there's a lot of services opportunity and we have very strong peg a practices in the different partners. But last year when I came in I came in almost 16 months ago we decided that we wanted also to improve our our sales with the partners. So we are engaging with partners and to and from the beginning of a sale cycle and brainstorming on what the client needs in order to be more efficient to reduce cost to the moment of the implementation. So we have been working with several uh system integrators, some resellers and with aws as our cloud platform. So we have been moving everything we can to the peg, a cloud that is on aws and clients are are really happy to be modernized in there because there you have the security, the scalability then you the new versions of the product without having to be worrying about it because it's done by our support. >>So it's software on amazon. So customers can buy your software through the marketplace or whatever through a partner or the marketplace and then they can still use the higher level services at in AWS, correct? >>They can use a high services in AWS or with any other partner system Integrator that also works with AWS and we have many cases where we are we we use the power of three. Right. We work with AWS accenture and and for example, Peg or we can use lay does or or booz allen or a parrot on any of the partners that are here in government. >>So you know, the channel equation, you're the chief of the channel. Channel channels love simplicity, simple products to buy. They love products that can throw off gross profit. And you said services, how is that going? Are you guys seeing a good economic equation with your partners? >>Well, our partners do between five and 10 IX of uh, of the revenue that we do on software on services. So that equation definitely works and they love it for that. At the same time we have invested five x the quantity of people that we have supporting the channel. For example, here in government we have invested also two or three times on the rest of the of the business. But there has been definitely good investments for partners. The partners are happy with us because again they not only they can do a good business one off, they can then radiate one. You usually clients one day once they buy peg for one of their use cases or case management as we call it, they usually want to replicate it in other cases and that is where the partners are doing enormous money because they are replicating the same use case in different departments. >>That's the way it's supposed to be, it's their touching the customer, they're adding value on top of your product. So they get to have the best of both worlds high margins on the profits and the services but yet worked with the customer directly to engage, make sure they get the right solution from you and a W. S together. >>Absolutely. Okay, >>what are the key challenges that you find that partners need to solve and overcome to keep this this this equation going. What do you guys focus on? You mentioned more people, what are some of the trends in the public cloud? I mean public sector area? What's this with the dynamics? >>So in in this moment the whole world is with a huge need of digital transformation the every single client but especially in government, they had all digital transformation projects. But they were going at slow motion because of the situation of the pandemic that I don't even want to name it again because everybody's talking about it but it's a reality. These projects have to accelerate 10 times. So whatever it was going to be done in five years has been done in one. So the biggest challenge that we are having is to ensure that we have that capacity to support all these projects that are being done very fast and and for that that's why we also need our partners right Because they have big mega practices. They have been investing as well as we are to ensure that we cover all those needs and but for now we are doing well and so that's that's right. We are growing as a company and with the partners >>carol great to have you on board with the company now kicking some butt now in the channel, Chief of channel good margins happy customers growth. What are some of the use case successes that you've had. Can you name a few customers and what they've done and what's their best practice? >>Well we have, I will name some government because we are in a public secretary event but we have and I will name north America although we also have in the rest of the world. So U. S. Census. That is something that everybody has done right. Even if you did in your mobile, you did it on paper, you did it on the phone. All of that was managed by paga And for the first time ever there was zero than downtime. Not a single problem to access the web. For example, the the US census took us 50% less expense than the one that we did in 2010 just because we use this digital approach And then we also were 50% more efficient because we needed, we didn't need to use all that paper storage that was used in the past. So we taxpayers have to be happy because they really spend less than what they should have spent on this topic. So definitely that was one of the biggest cases that we have in 2020. We have other, we took big big projects like the US and or we do smaller projects and there's one that is not small but that is smaller, that is the New Jersey court that caught my attention because I imagine myself in a situation like that that you are like my mistake taken to the court and you and they are, they are you have to defend yourself that was taking three hours and it's stressful, right? And you don't have to be there if you don't need to And this process got to 20 minutes, that is also reduction and expenses even jail expenses sometimes. So that was one that we did as well. And and that was just by making four legacy systems getting to one having a much faster experience on that. So >>a lot of migrations, a lot of cloud native re factoring going on in the applications sounds like >>yes. What we do is whatever legacy systems you have, we managed to ensure that we connect them all and to have a front line so that you can access information real time and that you can as a user and that you can really have a better experience whatever you do today, whatever company telco company you have, bank you use, I can guarantee you have you have, you speak to you just don't know about >>that. It's under the covers. I gotta ask you my final question. So you guys really doing some good business out here, what if people watching here trying to understand the dynamics of public sector market? What's your take, what's your what do you what would you say, that person? What's the big story happening in public sector? >>Well, to begin with, I'm not a public sector experts, I'm sure that there's a lot of public sector experts out there that can tell me, oh no, you missed this point. But what I have seen in these days that I have been here with the team is that the government needs to act fast in order to digitalized all these projects. So one of our partners yesterday was telling me that there is a mandate in in the army for example to move everything to cloud. How do you do it? They don't even know they're there, there are people that they don't they don't know how to do this. So our partners are building solutions to help them faster get into the cloud because they have to do it by the end of the year. And these are the key things that we are working on with partners to build solutions that can really can access for robust and they can >>escape. It's a very robust ecosystem. Yes, So amazon is an ecosystem you guys and you have an ecosystem. >>It's an ecosystem of ecosystems and that is what works right because Amazon has very good sellers for example, very good people that know the clients and they have a lot of experience but they are not specialized in what to do >>with the channel. These >>other partners have a peg a practice, they are experts and as I told you this is about crushing complexity. So it's making you need to understand the technology and the details behind it to make the best solution to the client. >>Corolla. Great to have you on very dynamic. Love, Love chatting with you Corolla Cazenove >>Cazenove >>Cazenove chief of channels that Pegasystems also known as peg a great to have you on, congratulations on your success. Ecosystems within an ecosystem crushing complexity. Mr que bringing you all the signal out there from the noise. I'm john Kerry. Thanks for watching. Mhm. Mhm.

>>Hello, buddy. And welcome back to the cubes. Coverage of Snowflake Data Cloud Summer 2020. We're tracking the rise of the data cloud and fresh off the keynotes. Hear Frank's Luqman, the chairman and CEO of Snowflake, and Anita Lynch, the vice president of data governance at Disney Streaming Services. Folks. Welcome E Need a Disney plus. Awesome. You know, we signed up early. Watched all the Marvel movies. Hamilton, the new Pixar movie Soul. I haven't gotten to the man DeLorean yet. Your favorite, but I really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud because I never liked the term Enterprise Data Warehouse. What you're doing is is so different from the sort of that legacy world that I've known all these years. But start with why the data cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing? >>Yeah, I know. You know, we have We've come a long way in terms of workload execution, right? In terms of scale and performance and, you know, concurrent execution. We really taking the lid off sort of the physical constraints that that have existed on these types of operations. But there's one problem, uh, that were not yet, uh solving. And that is the silo ing and bunkering of data. Essentially, you know, data is locked in applications. It's locked in data centers that's locked in cloud cloud regions incredibly hard for for data science teams to really, you know, unlocked the true value of data. When you when you can address patterns that that exists across data set. So we're perpetuate, Ah, status we've had for for ever since the beginning off computing. If we don't start Thio, crack that problem now we have that opportunity. But the notion of a data cloud is like basically saying, Look, folks, you know, we we have to start inside, lowing and unlocking the data on bring it into a place where we can access it. Uh, you know, across all these parameters and boundaries that have historically existed, it's It's very much a step level function. Customers have always looked at things won't workload at that time. That mentality really has to go. You really have to have a data cloud mentality as well as a workload orientation towards towards managing data. Yeah, >>Anita is great here in your role at Disney, and you're in your keynote and the work. You're doing the governance work, and you're you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. You know, maybe you can expand on some of these initiatives here and share what you you're seeing as some of the biggest challenges to success. And, of course, the opportunities that you're unlocking. >>Sure. I mean, in my role leading data to governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them, they can also understand really easily and quickly whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance. And a lot of the work that we would normally have to do manually is actually done for us through the data. Clean rooms. >>Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you could elucidate on that. >>Sure, I mean data complexities air going to evolve over time in any traditional data architecture. Er, simply because you often have different teams at different periods in time trying thio, analyze and gather data across Ah, whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders, their time constraints. And quite often, um, it's not always clear how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down the silos is allow individuals to see up front how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away, and by ensuring that essentially, as they're continuing to kind of scale the use cases that they're focused on. They're no longer required. Thio make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world, >>for sure. I mean, copy creep, because it be the silent killer. Frank, I followed you for a number of years. You know, your big thinker. You and I have had a lot of conversations about the near term midterm and long term. I wonder if you could talk about you know, when you're Kino. You talk about eliminating silos and connecting across data sources, which really powerful concept. But really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe What are some of the blockers there? >>Well, there's there's certainly, ah natural friction there. I still remember when we first started to talk to to Salesforce, you know, they had discovered that we were top three destination off sales first data, and they were wondering, you know why that was. And and the reason is, of course, that people take salesforce data, push it to snowflake because they wanna overlay it with what data outside of Salesforce. You know, whether it's adobe or any other marketing data set. And then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS is always like, no, we're an island were planning down to ourselves. Everybody needs to come with us as opposed to we We go, you know, to a different platform to run these type of processes. It's no different for the for the public club. Venter Day didn't mean they have, you know, massive moats around there. Uh, you know, their stories to, you know, really prevent data from from leaving their their orbit. Eso there is natural friction in in terms off for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on on the power and potential of data unless we allow it to come together. Uh, snowflake is the platform that allows that to happen. You know, we were pleased with our relationship with Salesforce because they did appreciate you know why this was important and why this was necessary. And we think you know, other parts of the industry will gradually come around to it as well. So the the idea of a data cloud has really come, right? People are recognizing, you know, why does this matters now? It's not gonna happen overnight, And there's a step global function of very big change in mentality and orientation. You know, >>it's almost as though the SAS ification of our industries sort of repeated some of the application silos, and you build a hardened top around it. All the processes are hardened around it, and Okay, here we go. And you're really trying to break that, aren't you? Yeah, Exactly. Anita. Again, I wanna come back to this notion of governance. It's so it's so important. It's the first role in your title, and it really underscores the importance of this. Um, you know, Frank was just talking about some of the hurdles, and and this is this is a big one. I mean, we saw this in the early days of big data. Where governance was this after thought it was like, bolted on kind of wild, Wild West. I'm interested in your governance journey, and maybe you can share a little bit about what role Snowflake has played there in terms of supporting that agenda. Bond. Kind of What's next on that journey? >>Sure. Well, you know, I've I've led data teams in a numerous, uh, in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance. And what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >>Well, I mean a big part of what you were talking about, at least my inference in your your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it. But they're not the wonder about and and about the privacy, the concerns, etcetera. You've taken care of all that. It's sort of transparent to them. Is that >>yeah, right. That's right. Absolutely. So we focus on ensuring compliance across all the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring, you know, that we're able Thio do this. We don't We don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these air really important components of our strategy. >>I got. So I have a question. Maybe each of you can answer. I I sort of see this our industry moving from, you know, products. So then the platforms and platforms even involving into ecosystems. And then there's this ecosystem of of data. You guys both talked a lot about data sharing. But maybe Frank, you could start in Anita. You can add on to Frank's answer. You're obviously both both passionate about the use of of data and trying to do so in a responsible way. That's critical, but it's also gonna have business impact. Frank, where's this passion come from? On your side. And how are you putting in tow action in your own organization? >>Well, you know, I'm really gonna date myself here, but, you know, many, many years ago, you know, I saw the first glimpse off, uh, multidimensional databases that were used for reporting. Really, On IBM mainframes on debt was extraordinarily difficult. We didn't even have the words back then. In terms of data, warehouses and business. All these terms didn't exist. People just knew that they wanted to have, um, or flexible way of reporting and being able Thio pivot data dimensionally and all these kinds of things. And I just whatever this predates, you know, Windows 3.1, which, really, you know, set off the whole sort of graphical in a way of dealing with systems which there's not a whole generations of people that don't know any different. Right? So I I've lived the pain off this problem on sort of been had a front row seat to watching this This transpire over a very long period of time. And that's that's one of the reasons um, you know why I'm here? Because I finally seen, you know, a glimpse off, you know, also as an industry fully fully just unleashing and unlocking the potential were not in a place where the technology is ahead of people's ability to harness it right, which we've We've never been there before, right? It was always like we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just heads are spinning with what's now possible, which is why you see markets evolved very rapidly right now. Way we were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on the world. The world's changing right in front of your eyes right now. >>Sonita. Maybe you could add on to what Frank just said and share some of the business impacts and and outcomes that air notable since you're really applied your your love of data and maybe maybe touch on culture, your data culture. You know any words of wisdom for folks in the audience who might be thinking about embarking on a data cloud journey similar to what you've been on? >>Yeah, sure, I think for me. I fell in love with technology first, and then I fell in love with data, and I fell in love with data because of the impact the data can have on both the business and the technology strategy. And so it's sort of that nexus, you know, between all three and in terms of my career journey and and some of the impacts that I've seen I mean, I think with the advent of the cloud, you know before, Well, how do I say that before the cloud actually became, you know, so prevalent in such a common part of the strategy that's required? It was so difficult, you know, so painful. It took so many hours to actually be able to calculate, you know, the volumes of data that we had. Now we have that accessibility, and then on top of it with the snowflake data cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have toe have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact has has only been possible with the volumes of data that we have available to us today. And it's just it's phenomenal to see the speed at which we can operate and really, truly understand our customers, interests and their preferences, and then tailor the experiences that they really want and deserve for them. Um, it's It's been a great feeling. Thio, get to this point in time. >>That's fantastic. So, Frank, I gotta ask you if you're still in your spare time, you decided to write a book? I'm loving it. Um, I don't have a signed copy, so I'm gonna have to send it back and have you sign it. But you're I love the inside baseball. It's just awesome. Eso really appreciate that. So But why did you decide to write a book? >>Well, there were a couple of reasons. Obviously, we thought it was an interesting tale to tell for anybody you know who is interested in, You know what's going on. How did this come about, You know, where the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, because this is such a step function, it's so non incremental. We felt like, you know, we really needed quite a bit of real estate to really lay out what the full narrative and context is on. Do you know we thought books titled The Rise of the Data Cloud. That's exactly what it ISS and We're trying to make the case for that mindset, that mentality, that strategy. Because all of us, you know, I think is an industry or were risk off persisting, perpetuating, You know, where we've been since the beginning off computing. So we're really trying to make a pretty forceful case for Look, you know, there is an enormous opportunity out there, The different choices you have to make along the way. >>Guys, we got to leave it there. Frank. I know you and I are gonna talk again. Anita. I hope we have a chance to meet face to face and and talking the Cube live someday. You're phenomenal, guest. And what a great story. Thank you both for coming on. And thank you for watching. Keep it right there. You're watching the Snowflake Data Cloud Summit on the Cube.

>>Hi, I'm Frank's Luqman CEO of Snowflake. And welcome to the Snowflake Data Cloud Summit. I'd like to take the next few minutes to introduce you to >>the data cloud on why it matters to the modern enterprise. As an industry, we have struggled to mobilize our data, meaning that has been hard to put data into service of our enterprises. We're not living in a data economy and for most data central how we run our lives, our businesses and our institutions, every single interaction we have now, whether it's in social media, e commerce or any other service, engagement generates critical data. You multiply this out with the number of actors and transactions. The volume is overwhelming, growing in leaps and bounds every day. There was a time when data operations focused mostly on running reports and populating dashboards to inform people in the enterprise of what had happened on what was going on. And we still do a ton of that. But the emphasis is shifting to data driving operations from just data informing people. There is such a thing as the time value off data meaning that the faster data becomes available, the more impactful and valuable it ISS. As data ages, it loses much of its actionable value. Digital transformation is an overused term in our industry, but the snowflake it means the end to end automation of business processes, from selling to transacting to supporting to servicing customers. Digital processes are entirely disinter mediated in terms of people. Involvement in are driven into end by data. Of course, many businesses have both physical and digital processes, and they are >>intertwined. Think of retail, logistics, delivery services and so on. So a data centric operating discipline is no longer optional data operations Air now the beating heart >>of the modern enterprise that requires a massively scalable data platform talented data engineering and data science teams to fully exploit the technology that now is becoming available. Enter snowflake. Chances are that, you know, snowflake as a >>world class execution platform for a diverse set of workloads. Among them data warehousing, data engineering, data, lakes, data, science, data applications and data sharing. Snowflake was architected from scratch for cloud scale computing. No legacy technology was carried forward in the process. Snowflake reimagined many aspects of data management data operations. The result was a cloud data platform with massive scale, blistering performance, superior economics and world class data governance. Snowflake innovated on a number of vectors that wants to deliver this breakthrough. First scale and performance. Snowflake is completely designed for cloud scale computing, both in terms of data volume, computational performance and concurrent workload. Execution snowflake features numerous distinct innovations in this category, but none stands up more than the multi cluster shared stories. Architectural Removing the control plane from the individual cluster led to a dramatically different approach that has yielded tremendous benefits. But our customers love about Snowflake is to spin up new workloads without limitation and provisioned these workloads with his little or as much compute as they see fit. No longer do they fear hidden capacity limits or encroaching on other workloads. Customers can have also scale storage and compute independent of each other, something that was not possible before second utility and elasticity. Not only can snowflake customer spin up much capacity for as long as they deem necessary. Three. Utility model in church, they only get charged for what they consumed by the machine. Second, highly granular measurement of utilization. Ah, lot of the economic impact of snowflake comes from the fact that customers no longer manage capacity. What they do now is focused on consumption. In snowflake is managing the capacity. Performance and economics now go hand in hand because faster is now also cheaper. Snowflake contracts with the public cloud vendors for capacity at considerable scale, which then translates to a good economic value at the retail level is, well, third ease of use and simplicity. Snowflake is a platform that scales from the smallest workloads to the largest data estates in the world. It is unusual in this offer industry to have a platform that controversy the entire spectrum of scale, a database technology snowflake is dramatically simple fire. To compare to previous generations, our founders were bent on making snowflake, a self managing platform that didn't require expert knowledge to run. The role of the Deba has evolved into snowflake world, more focused on data model insights and business value, not tuning and keeping the infrastructure up and running. This has expanded the marketplace to nearly any scale. No job too small or too large. Fourth, multi cloud and Cross Cloud or snowflake was first available on AWS. It now also runs very successfully on mark yourself. Azure and Google Cloud Snowflake is a cloud agnostic platform, meaning that it doesn't know what it's running on. Snowflake completely abstracts the underlying cloud platform. The user doesn't need to see or touch it directly and also does not receive a separate bill from the cloud vendor for capacity consumed by snowflake. Being multi cloud capable customers have a choice and also the flexibility to change over time snowflakes. Relationships with Amazon and Microsoft also allow customers to transact through their marketplaces and burned down their cloud commit with their snowflakes. Spend Snowflake is also capable of replicating across cloud regions and cloud platforms. It's not unusual to see >>the same snowflake data on more than one public cloud at the time. Also, for disaster recovery purposes, it is desirable to have access to snowflake on a completely different public cloud >>platform. Fifth, data Security and privacy, security and privacy are commonly grouped under the moniker of data governance. As a highly managed cloud data platform, snowflake designed and deploys a comprehensive and coherent security model. While privacy requirements are newer and still emerging in many areas, snowflake as a platform is evolving to help customers steer clear from costly violations. Our data sharing model has already enabled many customers to exchange data without surrendering custody of data. Key privacy concerns There's no doubt that the strong governance and compliance framework is critical to extracting you analytical value of data directly following the session. Police Stay tuned to hear from Anita Lynch at Disney Streaming services about how >>to date a cloud enables data governance at Disney. The world beat a >>path to our door snowflake unleashed to move from UN promised data centers to the public cloud platforms, notably AWS, Azure and Google Cloud. Snowflake now has thousands of enterprise customers averaging over 500 million queries >>today across all customer accounts, and it's one of the fastest growing enterprise software companies in a generation. Our recent listing on the New York Stock Exchange was built is the largest software AIPO in history. But the data cloth conversation is bigger. There is another frontier workload. Execution is a huge part of it, but it's not the entire story. There is another elephant in the room, and that is that The world's data is incredibly fragmented in siloed, across clouds of old sorts and data centers all over the place. Basically, data lives in a million places, and it's incredibly hard to analyze data across the silos. Most intelligence analytics and learning models deploy on single data sets because it has been next to impossible to analyze data across sources. Until now, Snowflake Data Cloud is a data platform shared by all snowflake users. If you are on snowflake, you are already plugged into it. It's like being part of a Global Data Federation data orbit, if you will, where all other data can now be part of your scope. Historically, technology limitations led us to build systems and services that siloed the data behind systems, software and network perimeters. To analyze data across silos, we resorted to building special purpose data warehouses force fed by multiple data sources empowered by expensive proprietary hardware. The scale limitations lead to even more silos. The onslaught of the public cloud opened the gateway to unleashing the world's data for access for sharing a monetization. But it didn't happen. Pretty soon they were new silos, different public clouds, regions within the and a huge collection of SAS applications hoarding their data all in their own formats on the East NC ations whole industries exist just to move data from A to B customer behavior precipitated the silo ing of data with what we call a war clothes at a time mentality. Customers focused on the applications in isolation of one another and then deploy data platforms for their workload characteristics and not much else, thereby throwing up new rules between data. Pretty soon, we don't just have our old Silas, but new wants to content with as well. Meanwhile, the promise of data science remains elusive. With all this silo ing and bunkering of data workload performance is necessary but not sufficient to enable the promise of data science. We must think about unfettered data access with ease, zero agency and zero friction. There's no doubt that the needs of data science and data engineering should be leading, not an afterthought. And those needs air centered on accessing and analyzing data across sources. It is now more the norm than the exception that data patterns transcend data sources. Data silos have no meaning to data science. They are just remnants of legacy computing. Architectures doesn't make sense to evaluate strictly on the basis of existing workloads. The world changes, and it changes quickly. So how does the data cloud enabled unfettered data access? It's not just a function of being in the public cloud. Public Cloud is an enabler, no doubt about it. But it introduces new silos recommendation by cloud, platform by cloud region by Data Lake and by data format, it once again triggered technical grandstands and a lot of programming to bring a single analytical perspective to a diversity of data. Data was not analytics ready, not optimized for performance or efficiency and clearly lacking on data governance. Snowflake, address these limitations, thereby combining great execution with great data >>access. But, snowflake, we can have the best of both. So how does it all work when you join Snowflake and have your snowflake account? You don't just >>avail yourself of unlimited stories. And compute resource is along with a world class execution platform. You also plug into the snowflake data cloud, meaning that old snowflake accounts across clouds, regions and geography are part of a single snowflake data universe. That is the data clouds. It is based on our global data sharing architectures. Any snowflake data can be exposed and access by any other snowflake user. It's seamless and frictionless data is generally not copied. Her moves but access in place, subject to the same snowflake governance model. Accessing the data cloth can be a tactical one on one sharing relationship. For example, imagine how retailer would share data with a consumer back. It's good company, but then it easily proliferate from 1 to 1. Too many too many. The data cloud has become a beehive of data supply and demand. It has attracted hundreds of professional data listings to the Snowflake Data Marketplace, which fuels the data cloud with a rich supply of options. For example, our partner Star Schema, listed a very detailed covert 19 incident and fatality data set on the Snowflake Data Marketplace. It became an instant hit with snowflake customers. Scar schema is not raw data. It is also platform optimize, meaning that it was analytics ready for all snowflake accounts. Snowflake users were accessing, joining and overlaying this new data within a short time of it becoming available. That is the power of platform in financial services. It's common to see snowflake users access data from snowflake marketplace listings like fax set and Standard and Poor's on, then messed it up against for example. Salesforce data There are now over 100 suppliers of data listings on the snowflake marketplace That is, in addition to thousands of enterprise and institutional snowflake users with their own data sets. Best part of the snowflake data cloud is this. You don't need to do or buy anything different. If your own snowflake you're already plugged into the data clouds. A whole world data access options awaits you on data silos. Become a thing of the past, enjoy today's presentations. By the end of it, you should have a better sense in a bigger context for your choices of data platforms. Thank you for joining us.

(lively music) >> Thank you, Frank, for kicking us off, setting the stage, and providing the vision for the Snowflake Data Cloud. Hi, everyone, I hope you're all doing well and staying safe. Thank you for joining me at the Snowflake Summit today to dive into the role of the Data Cloud in mobilizing data at Disney Streaming. Together, we're going to discuss data governance and how to leverage some of the unique benefits of Snowflake's data platform to unlock business value for better customer experiences. I am Anita Lynch, Vice President of Data Governance at Disney Streaming, home of Disney+. I fell in love with technology at an early age. My family is originally from Chicago and we came to the Bay Area when my dad's sales career led him to Silicon Valley. Because of the exciting advancements he saw in the devices he sold and the engineers he worked with, I am so fortunate that my father created the early opportunities for me to learn about technology, like starting to code when I was 10. Decades later, over the course of my career spanning tech startups, business school, strategy consulting, and leading data at global enterprises, I have learned it is not enough to create a technology solution. It takes a real understanding of what problems your customers are trying to solve, and what resources or capabilities they can mobilize to do it. Today, this is the focus of my career in data. At Disney Streaming, we pride ourselves on delighting our customers. We commit each day to bringing beloved characters, timeless stories, and epic sporting events to a global audience. I am one member of a global data team at Disney Streaming, continuing to work through these challenging times for our world. We are deeply appreciative to be able to continue doing our part to deliver the entertainment people love on Disney+, including my new, personal favorite series, "The Mandalorian." It is important to all of us that we maintain our viewers' highest level of trust. As our data volume grows continuously on a daily basis, we need to ensure data is compliant, secure, and well-governed. Therefore, how we execute is critical. Our work ensures our business is guiding decisions with high-quality data. Doing this empowers us to challenge convention and innovate, which brings us to the role of the organization I lead at Disney Streaming. I lead data governance, which includes instrumentation, compliance, integrations, and data architecture. Collectively, we are responsible for the value, protection, and mobilization of data for Disney+. With data volumes in the thousands of petabytes after just one year and global teams depending on us to be able to perform their analysis, data science modeling, and machine learning, it is critical to maintain compliance protocols and governance standards. However, our approach to locking down the data and limiting access without becoming a blocker to critical information needs is key. Poorly informed business decisions could ultimately lead to suboptimal customer experiences. Recognizing this, I've established eight operating principles to maintain a balance between technology, people, and process. Data lifecycle, stewardship, and data quality together define the mechanisms by which we maintain, measure, and improve the value of data as an asset. Regulatory compliance and data access establish key partnerships with our legal and information security to help us ensure data complies with internal and external legal guidelines in each region. Auditability, traceability, and risk management ensure we monitor, educate, influence, and enforce best practices. And lastly, data sharing, which serves to socialize valuable datasets and shared definitions in a secure, easy way that allows us to keep pace with the fast-moving and rapidly changing nature of our world today. Principles serve only as guardrails. In real practice, we measure the value data governance delivers based on these six, quantifiable goals for the teams we serve. Underpinning all of them is the Snowflake Data Cloud. It is our platform to store, secure, integrate, and mobilize data across the organization. It enables us to make compliant data accessible for teams to collaborate without copying, moving, or reprocessing. Going beyond the notion of a single source of truth, Snowflake's Data Cloud allows us to truly have a single copy of the data, plus the ability to scale to support a near-unlimited number of concurrent users without contention for resources, and the flexibility to prioritize or deprioritize compute workloads where concurrency matters less than our ability to manage cost. What does this mean to me? Put simply, it means the ability to support business intelligence, analytics, data science, and machine learning use cases on-demand, exceeding expectations for speed and performance where they matter without sacrificing anything on governance. And that is how we deliver value through data governance for Disney+. Data sharing is at the heart of how we make this work. We'll look at three important use cases, data clean rooms that enable restricted data sharing, data discovery that ensures data is easily found and understood, and partner data management for collaboration outside of our team. Data sharing creates the opportunity to access the power of the integrated dataset in an environment that ensures both quality and compliance. Let's start with data clean rooms and the example of restricted data sharing. Better understanding the interests and preferences of our audience through analysis is how we improve experiences for our customers, such as in-app personalization or making a recommendation on what to watch. The challenge is to mobilize the right data as it is needed while blocking distribution of any data that is not required, preventing the disclosure of sensitive information and prohibiting the merging of data that should not be combined. Simultaneously, while we seek to deliver compliance, we also want to avoid the typical process delays and enormous manual repetitive work that often comes with it. Data clean rooms enable the secure sharing of data, again, without creating copies, the combining of datasets without PII or sensitive information, and the restricting of queries by use of parameterized inputs and filtered query outputs, so only permissible data can be extracted. Outlining in advance how data will be used properly ensures consistency and execution of our compliance workflows and improves transparency on constraints, so teams don't waste their valuable time. This accelerates our ability to act on data insights. Decisions can be made for the benefit of our customers. For example, for me on Disney+, I would see right away the season two trailer for "The Mandalorian," including exciting scenes with Baby Yoda, more formerly known to some of you as the Child. Sometimes unintended data silos arise due to architectural complexities. In a traditional model for data infrastructure, complexity can evolve over time as various teams need to access, integrate, and transform data from different data sources in ways that uniquely serve their specific stakeholders. This proliferation in the analytical supply chain could result in multiple instances of copying, loading, and transforming the same data and introduce significant risks to data quality throughout the system, such as a lack of traceability. For example, changing one data pipeline may create unforeseen consequences in the calculations that occur in downstream tables and reports with no clear resolution. In the spirit of challenging convention to innovate, we knew we had to do better. With the Snowflake Data Cloud, our teams are able to discover the data sources they need through a centrally organized platform for data management and data sharing. Each user knows the data visible to them is available to them. They know they can trust it, and they know how it can properly be used to drive broader customer insights. And if a team wants to share their insights for further collaboration, they can easily publish those datasets to the Data Cloud, where they benefit from the protection of our managed platform, making sure all governance protocols are in place, including who can access for what purpose and at what level of granularity. This facilitates data sharing without the administration worry that comes with sharing files. And since there is one single copy, future updates happen at once for all consumers of the data, keeping it fresh for everyone without sacrificing business continuity. Finally, data sharing improves the performance of our partner relationships with the same degree of simplicity. In this model, our partner teams can also participate in the Data Cloud by invitation to access data specifically shared to them. Or conversely, a partner can request to share their data, and upon authorization for quality and compliance, we can safely publish that data, making it simultaneously available to all the right teams who need it. As a thought exercise, one way for us to envision making it easier to work with partners is in the way we collect and analyze data from media serving and content distribution networks. Today, customer stream Disney+ on more than 13 different types of devices. Their streaming is made possible through a collection of services that vary by geography and consumer choice. Better understanding the experience for an individual client may require integration of data collected across the unique combination of services available to that customer. To better serve our content and delight our customers, data-driven analysis to detect anomalies and service impacts might benefit from a data management platform for partner data that requires a high level of data governance similar to what we do today through our Snowflake Data Cloud. Now in closing, data is at the core of our mission at Disney Streaming to delight our customers. And when it comes to data governance, we strive to always hold ourselves to the highest standard. With the Data Cloud, we power our business with a single source of truth. As we grow, it enables data sharing with data governance at massive scale and performance. I will also leave you with this often quoted African proverb I like. "If you want to go fast, go alone. But if you want to go far, go together." We share an important cultural value. Commitment to innovation accelerated our ability to address unique use cases and the successful growth of Disney+. It was both the technology and the commitment to meet our data governance needs that has resulted in more than just another cloud data platform. We have a solution that works for us. Thank you for joining me on this journey, and thank you to Snowflake for the ongoing partnership. With the product keynote coming up next, I'm excited to see how future innovation will continue to enable us to challenge convention going forward.

>> Hello everybody. And welcome back to, theCUBE coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the Data Cloud, and fresh off the keynotes here, Frank Slootman, the Chairman and CEO of Snowflake and Anita Lynch, the Vice President of data governance at Disney streaming services. Folks Welcome. >> Thank you >> Thanks for having us Dave. >> Anita Disney plus awesome. You know, we signed up early, watched all the Marvel movies, Hamilton, the new Pixar movie soul. I haven't gotten it to the Mandalorian yet, your favorite. But really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the Data Cloud, because I never liked the term enterprise data warehouse. What you're doing is so different from the sort of that legacy world that I've known all these years. But start with why the Data Cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing. >> Yeah, you know, we have a, we've come a long way in terms of workload execution. Right? In terms of scale and performance, and concurrent execution. We've really taken the lid off, sort of the physical constraints that have existed on these type of operations. But there's one problem that we're not yet solving, and that is the siloing and bunkering of data. And essentially, data is locked in applications, it's locked in data centers, it's locked in cloud, cloud regions. Incredibly hard for data science teams to really unlock the true value of data, when you can't address patterns that exist across data sets. So where we perpetuate a status we've had for forever since the beginning of computing. If we don't start to crack that problem now we have that opportunity. But the notion of a Data Cloud is like basically saying, "Look folks, we have to start on siloing and unlocking the data, and bring it into a place, where we can access it across all these perimeters, and boundaries that have historically existed. It's very much a step level function. Like the customers have always looked at things, one workload at a time, that mentality really has to go. You really have to have a Data Cloud mentality, as well as a workload orientation towards managing data. >> Anita, it was great hearing your role at Disney and in your keynote, and the work you're doing, the governance work. and you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. Maybe you can expand on some of these initiatives here, and share what you're seeing as some of the biggest challenges to success, and of course, the opportunities that you're unlocking. >> Sure. In my role leading data governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them. They can also understand really easily and quickly, whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance, and a lot of the work that we would normally have to do manually is actually done for us through the data clean rooms. >> Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you can elucidate on that. >> Sure. I mean, data complexities are going to evolve over time in any traditional data architecture simply because you often have different teams at different periods and time trying to analyze and gather data across a whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders. There are time constraints and quite often, it's not always clear how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down those silos is allow individuals to see upfront how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away. And by ensuring that essentially as they're continuing to kind of scale the use cases that they're focused on, they're no longer required to make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world. >> Yeah, for sure. I'm a copy Creek because it'd be the silent killer. Frank I followed you for a number of years, you're a big thinker, you and I have had a lot of conversations about the near-term, mid-term and long-term, I wonder if you could talk about, in your keynote you're talking about eliminating silos and connecting across data sources. Which is really powerful concept but really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe what are some of the blockers there? >> Well, there's certainly a natural friction there. I still remember when we first started to talk to, Salesforce, you know, they had discovered that we were a top three destination of Salesforce data and they were wondering why that was, and the reason is of course, that people take Salesforce data push it to snowflake because they want to overlay it with what data outside of Salesforce. Whether it's Adobe or any other marketing dataset. And then they want to run very highly scaled processes on it. But the reflexes in the world of SaaS is always like no, we're an Island, we're a planet down to ourselves. Everybody needs to come with us, as opposed to we go to a different platform to run these types of processes. It's no different for the public cloud vendor. They didn't only, they have massive moats around their storage to really prevent data from leaving their orbit. So there is natural friction in terms for this to happen. But on the other hand there is an enormous need. We can't deliver on the power and potential of data unless we allow it to come together. Snowflake is the platform that allows that to happen. We were pleased with our relationship with Salesforce because they did appreciate why this was important and why this was necessary. And we think, other parts of the industry will gradually come around to it as well. So the idea of a Data Cloud has really come, right. When people are recognizing why this matters now. It's not going to happen overnight. It is a step while will function a very big change in mentality and orientation. >> Yeah. It's almost as though the the SaaS suffocation of our industry sort of repeated some of the application silos and you build a hardened top around it, all the processes are hardened around it and okay, here we go. And you're really trying to break that, aren't you? >> Yep, exactly. >> Anita, again, I want to come back to this notion of governance. It's so it's so important. It's the first role in your title and it really underscores the importance of this. You know, Frank was just talking about some of the hurdles and this is a big one. I mean, we saw this in the early days of big data where governance was just afterthought. It was like bolted on the kind of wild wild West. I'm interested in your governance journey. And maybe you can share a little bit about what role snowflake has played there in terms of supporting that agenda and kind of what's next on that journey. >> Sure. Well, I've led data teams in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance and what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >> Well, I mean, a big part of what you were talking about at least my inference in your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it, but they don't have to wonder about, and about the privacy concerns, et cetera. You've taken care of all that it's sort of transparent to them. Is that right?| >> Yea That's right absolutely. So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring that we're able to do this. we don't do it alone. But governance includes not just the compliance and the privacy, it's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these are really important components of our strategy. >> I got a...So I have a question maybe each of you can answer. I sort of see this, our industry moving from products, to then, to platforms and platforms even evolving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing but maybe Frank, you can start, Anita you can add on to Frank's answer. You're obviously both passionate about the use of data and trying to do so in a responsible way. That's critical but it's also going to have business impact. Frank, where's this passion come from on your side. And how are you putting into action in your own organization? >> Well, you know I'm really going to date myself here, but many, many years ago, I saw the first glimpse of multidimensional databases that were used for reporting really on IBM mainframes. And it was extraordinarily difficult. We didn't even have the words back then in terms of data warehouses and business. All these terms didn't exist. People just knew that they wanted to have a more flexible in way of reporting and being able to pivot data dimensionally and all these kinds of things. And I just bought whatever this predates windows 3.1, which really, set off the whole sort of graphical, way of dealing with systems which there's now a whole generations of people that don't know any different right? So I've lived the pain of this problem and sort of had a front row seat to watching this transpire over a very long period of time. And that's one of the reasons, why I'm here, because I finally seen, a glimpse of, I also, as an industry fully, fully just unleashing and unlocking to potential. We're now in a place where the technology is ahead of people's ability to harness it. Which we've never been there before. It was always like, we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just, their heads are spinning with what's now possible, which is why you see markets evolve, very rapidly right now we were talking earlier about how you can't take past definitions and concepts and apply them to what's going on in the world. because the world's changing right in front of your eyes right now. >> So Anita maybe you could add on to what Frank just said and share some of the business impacts and outcomes that are notable since you've really applied your your love of data and maybe, maybe touch on, on culture. Data culture, any words of wisdom for folks in the audience who might be thinking about embarking on a Data Cloud journey, similar to what you've been on. >> Yeah sure. I think for me, I fell in love with technology first and then I fell in love with data. And I fell in love with data because of the impact that data can have on both the business and the technology strategy. And so it's sort of that nexus, between all three. And in terms of my career journey and some of the impacts that I've seen. I mean, I think with the advent of the cloud, before, well, how do I say that. Before the cloud actually became so prevalent and such a common part of the strategy that's required it was so difficult, you know, so painful. It took so many hours to actually be able to calculate the volumes of data that we had. Now we have that accessibility, and then on top of it, with the snowflake Data Cloud it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have to have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact, has only been possible with the volumes of data that we have available to us today. And it's just, it's phenomenal to see the speed at which we can operate. And really, truly understand our customer's interests and their preferences and then tailor the experiences that they really want and deserve for them. It's, been a great feeling to get to this point in time. >> That's fantastic. So, Frank, I got to ask you this. So in your spare time you decided to write a book, I'm loving it. I don't have a signed copy so I'm going to have to send it back and have you sign it. But, and you're, I love the inside baseball. It's just awesome. So really appreciate that. So, but why did you decide to write a book? >> Well, there were a couple of reasons, obviously we thought of as an interesting tale to tell for anybody, who is interested in what's going on, how did this come about? Who are the characters behind the scenes and all this stuff. But from a business standpoint because this is such a step function it's so non incremental, we felt like, we really needed quite a bit of real estate to really lay out what the full narrative and context is. And, we thought, the books titled the "Rise of the Data Cloud." That's exactly what it is. And we're trying to make the case for that mindset, that mentality, that strategy because all of us, I think as an industry, were at risk of, persisting, perpetuating where we've been since the beginning of computing. So we're really trying to make a pretty forceful case for a look. There's an enormous opportunity out there but there's some choices you have to make along the way. >> Guys, we got to leave it there. Frank, I know you and I are going to talk again Anita, I hope we have a chance to meet face to face and talk in theCUBE live someday. You're phenomenal guests and what a great story. Thank you both for coming on. And thank you for watching. Keep it right there. You're watching the, Snowflake Data Cloud Summit, on theCUBE.

>>Hello, buddy. And welcome back to the cubes. Coverage of Snowflake Data Cloud Summer 2020. We're tracking the rise of the data cloud and fresh off the keynotes. Hear Frank's Luqman, the chairman and CEO of Snowflake, and Anita Lynch, the vice president of data governance at Disney Streaming Services. Folks. Welcome E Need a Disney plus. Awesome. You know, we signed up early. Watched all the Marvel movies. Hamilton, the new Pixar movie Soul. I haven't gotten to the man DeLorean yet. Your favorite, but I really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud because I never liked the term Enterprise Data Warehouse. What you're doing is is so different from the sort of that legacy world that I've known all these years. But start with why the data cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing? >>Yeah. You know, we have We've come a long way in terms of workload, execution, right? In terms of scale and performance and concurrent execution. We really taking the lid off. Sort of the physical constraints that that have existed on these types of operations. But there's one problem, uh, that were not yet, uh solving. And that is the silo ing and bunkering of data essentially in the data is locked in applications. It's locked in data centers. It's locked in cloud cloud regions incredibly hard for for data science teams to really unlock the true value of data when you when you can address patterns that that exists across data set. So we're perpetuate, uh, status we've had for for ever since the beginning off computing. If we don't start Thio, crack that problem now we have that opportunity. But the notion of a data cloud is like basically saying, Look, folks, you know, we we have to start inside, lowing and unlocking the data on bring it into a place where we can access it. Uh, you know, across all these parameters and boundaries that have historically existed, it's very much a step level function. Customers have always looked at things won't workload at that time. That mentality really has to go. You really have to have a data club mentality as well as a workload orientation towards towards managing data. >>Anita is great here in your role at Disney and you're in your keynote and the work you're doing the governance work and you're you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. You know, maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest challenges to success. And, of course, the opportunities that you're unlocking. >>Sure, I mean, in my role leading data to governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them, they can also understand really easily and quickly whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance. And a lot of the work that we would normally have to do manually is actually done for us through the data Clean rooms. >>Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you could elucidate on that. >>Sure, I mean data complexities air going to evolve over time in any traditional data architecture. Er, simply because you often have different teams at different periods in time trying thio, analyze and gather data across Ah, whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders, their time constraints. And quite often, um, it's not always clear how much value they're gonna be able to extract from the data at the outset. So what we've tried to do to help break down the silos is allow individuals to see up front how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away, and by ensuring that essentially, as they're continuing to kind of scale, the use cases that they're focused on their no longer required Thio make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world, >>for sure. I mean, copy creep, because it be the silent killer. Frank, I've followed you for a number of years. Your big thinker. You and I have had a lot of conversations about the near term midterm and long term. I wonder if you could talk about you know, when you're Kino. You talk about eliminating silos and connecting across data sources, which really powerful concept. But really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe What are some of the blockers there? >>Well, there's there's certainly, ah, natural friction there. I still remember when we first started to talk to to Salesforce, you know, they had discovered that we were top three destination off sales first data, and they were wondering why that was. And the reason is, of course, that people take salesforce data, push it to snowflake because they wanna overlay it with what data? Outside of Salesforce, you know, whether it's adobe or any other marketing data set and then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS is always like, No, we're an island were planning down to ourselves. Everybody needs to come with us as opposed to we We go, you know, to a different platform to run these type of processes. It's no different for the for the public club. Better day didn't mean they have, you know, massive moats around there. Uh, you know, their stories to, you know, really prevent data from from leaving their their orbit. Eso there is natural friction in, uh, in terms off for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on on the power and potential of data unless we allow it to come together. Uh, snowflake is the platform that allows that to happen. Uh, you know, we were pleased with our relationship with Salesforce because they did appreciate you know why this was important and why this was necessary. And we think you know, other parts of the industry will gradually come around to it as well. So the the idea of a data cloud has really come, right? Uh, people are recognizing, you know, why does this matter now? It's not gonna happen overnight. There's a step global function of very big change in mentality and orientation. >>Yeah. It's almost as though the SAS ification of our industry sort of repeated some of the application silos and you build a hardened top around it. All the processes are hard around. OK, here we go. And you're really trying to break that, aren't you? Yeah, Exactly. Anita. Again, I wanna come back to this notion of governance. It's so it's so important. It's the first role in your title, and it really underscores the importance of this. Um, you know, Frank was just talking about some of the hurdles, and this is this is a big one. I mean, we saw this in the early days of big data. Where governance was this after thought it was like, bolted on kind of wild, Wild West. I'm interested in your governance journey. And maybe you could share a little bit about what role snowflake has played there in terms of supporting that agenda. Bond. Kind of What's next on that journey? >>Sure. Well, you know, I've I've led data teams in a numerous, uh, in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance. And what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >>Well, I mean a big part of what you were talking about. At least my inference in your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it. But they're not the wonder about and and about the privacy, the concerns, etcetera. You've taken care of all that. It's sort of transparent to them. Is that >>yeah, right. That's right. Absolutely So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring, you know, that were ableto do this. We don't we don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these air really important components of our strategy. >>I got. So I have a question. Maybe each of you can answer. I I sort of see this our industry moving from, you know, products toe, then two platforms and platforms, even involving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing, But maybe Frank, you could start in Anita. You can add on to Frank's answer. You're obviously both both passionate about the use of data and trying to do so in a responsible way. That's critical, but it's also gonna have business impact. Frank, where's this passion come from? On your side. And how are you putting in tow action in your own organization? >>Well, you know, I'm really gonna date myself here, but, you know, uh, many, many years ago, uh, I saw the first glimpse off, uh, multidimensional databases that were used for reporting really on IBM mainframes on git was extraordinarily difficult. We didn't even have the words back then in terms of data, warehouses and all these terms didn't exist. People just knew that they wanted to have, um, or flexible way of reporting and being able Thio pivot data dimensionally and all these kinds of things. And I just whatever this predates, you know, Windows 3.1, which really set off the whole sort of graphical in a way of dealing with systems which there's not a whole generations of people that don't know any different, Right? So I I've lived the pain off. This problem on sort of had a front row seat to watching this this transpire over a very long period of time. And that's that's one of the reasons you know why I'm here. Because I finally seen a glimpse off. You know, I also as an industry fully fully just unleashing and unlocking the potential were not in a place where the technology is ahead of people's ability to harness it right, which we've never been there before, right? It was always like we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just heads are spinning with what's now possible, which is why you see markets evolved very rapidly right now. We were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on the world. The world's changing right in front of your eyes right now. >>Sonita. Maybe you could add on to what Frank just said and share some of the business impacts and and outcomes that are notable since you're really applied your your love of data and maybe maybe touch on culture, data, culture, any words of wisdom for folks in the audience who might be thinking about embarking on a data cloud journey similar to what you've been on? >>Yeah, sure, I think for me. I fell in love with technology first, and then I fell in love with data, and I fell in love with data because of the impact the data can have on both the business and the technology strategy. And so it's sort of that nexus, you know, between all three and in terms of my career journey and some of the impacts that I've seen. I mean, I think with the advent of the cloud you know before. Well, how do I say that before the cloud actually became, you know, so prevalent and such a common part of the strategy that's required It was so difficult, you know, so painful. It took so many hours to actually be able to calculate, you know, the volumes of data that we had. Now we have that accessibility, and then on top of it with the snowflake data cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have toe have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact has has only been possible with the volumes of data that we have available to us today. And it's just it's phenomenal to see the speed at which we can operate and really, truly understand our customers, interests and their preferences, and then tailor the experiences that they really want and deserve for them. Um, it's it's been a great feeling. Thio, get to this point in time. >>That's fantastic. So, Frank, I gotta ask you if you're still in your spare time. You decided to write a book? I'm loving it. Um, I don't have a signed copy, so I'm gonna have to send it back and have you sign it. But your love, the inside baseball, it's just awesome. Eso really appreciate that. So but why did you decide to write a book? >>Well, there were a couple of reasons. Obviously, uh, we thought it was an interesting tale to tell for anybody who's interested in, you know what's going on. How did this come about, You know, where the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, because this is such a step function, it's so non incremental. We felt like, you know, we really needed quite a bit of real estate to really lay out what the full narrative in context is on. Do you know, we thought books titled The Rise of the Data Cloud. That's exactly what it iss. And we're trying to make the case for that mindset, that mentality, that strategy. Uh, because all of us, you know, I think it's an industry were risk off, you know, persisting, perpetuating. Uh, you know, where we've been since the beginning off computing. So we're really trying to make a pretty forceful case for Look, there's an enormous opportunity out there. The different choices you have to make along the way. >>Guys, we got to leave it there. Frank. I know you and I are gonna talk again. Anita. I hope we have a chance to meet face to face and and talking the Cube live someday. You're phenomenal guests. And what a great story. Thank you both for coming on. Thank you. All right, you're welcome. And keep it right there, buddy. We'll be back for the next guest right after this short break and we're clear. All right. Not bad.

>> Hello everybody and welcome back to the cubes coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the Data Cloud, and fresh off the keynotes here, Frank Slootman, the chairman and CEO of Snowflake and Anita Lynch, the vice president of Data Governance at Disney Streaming Services. Folks, welcome. >> Thank you Thanks for having us, Dave, >> I need a Disney plus awesome. You know, we signed up early, watched all the Marvel movies, Hamilton, the new Pixar Movie saw, I haven't gotten into the Mandalorian yet, your favorite, but, (woman laughing) really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud, because I never liked the term Enterprise Data Warehouse, what you're doing is so different from the sort of that legacy world that I've known all these years, but start with why the Data Cloud, what problems are you trying to solve? And maybe some of the harder challenges you're seeing. >> Yeah I know, you know we've come a long way in terms of workload execution, right? In terms of scale and performance, you know, concurrent execution, we really taken the lid off sort of the physical constraints that have existed on these types of operations. But there's one problem, that we're not yet solving. And that is the siloing and bunkering of data. And especially in a data is locked in application it is locked data centers, is locked in cloud regions, incredibly hard for data science teams to really, you know, unlock the true value of data. When you can address patterns that exist across a data set. So we're perpetuate, a status we've had forever since the beginning of computing. If we don't start to crack that problem now we have that opportunity. But the notion of a Data Cloud is like basically saying, look folks, you know, we have to start unsiloing and unlocking the data, and bring it into a place, you know, where we can access it, you know, across all these parameters and boundaries that have historically existed. It's very much a step level function. Now the customers have always looked at things one workload at a time, that mentality really has to go. You really have to have a Data Cloud mentality, as well as a workload orientation towards managing data. >> Anita was great hearing your role at Disney, and your keynote, and the work you're doing, the governance work, and you're serving a great number of stakeholders, enabling things like data sharing, you got really laser focused on trust, compliance, privacy. Is this idea of a data clean room is really interesting. You maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest challenges to success. And of course, the opportunities that you're unlocking. >> Sure. I mean, in my role, leading Data Governance, it's really critical to make sure that all of our stakeholders, not only know what data is available and accessible to them, they can also understand really easily and quickly, whether or not the data that they're using is for the appropriate use case. And so, that's a big part of how we scale data governance, and a lot of the work that we would normally have to do manually, is actually done for us through the data clean rooms. >> Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos, and obviously you can relate to that, having been in the data business for awhile, but wonder if you can elucidate on that. >> Sure. I mean, data complexities are going to evolve over time in any traditional data architecture, simply because you often have different teams at different periods in time, trying to analyze and gather data across a whole lot of different sources. And the complexity that just arises out of that, is, due to the different needs of specific stakeholders. There are time constraints, and quite often it's not always clear, how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down those silos, is, allow individuals to see upfront how much value they're going to get from the data, by knowing that it's trustworthy right away . By knowing that it's something that they can use in their specific use case right away. And by ensuring that essentially, as they're continuing to kind of scale the use cases that they're focused on, they're no longer required to make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world. >> Yeah, for sure. I mean copy creek, cause it'd be the silent killer. Frank I followed you for a number of years. You're a big thinker. You and I have had a lot of conversations about the near term, mid term and long term. I wonder if you could talk about, you know, when your keynote, you talked about eliminating silos, and connecting across data sources, which really powerful concept, but it really only, if people are willing and able to connect and collaborate, where do you see that happening? Maybe what are some of the blockers there? >> Well, there's certainly a natural friction there. I still remember when we first started to talk to Salesforce, you know, they had, discovered that we were a top three destination of Salesforce data and they were wondering, you know, why that was? And the reason is of course that people take Salesforce data, push it to Snowflake, because they want to overlay it with data outside of Salesforce. You know what it is Adobe or any 6other marketing dataset. And then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS, is always like, no, we're an Island, we're a planet onto ourselves. Everybody needs to come with us as opposed to, we go to a different platform to run these types of processes. It's no different for thee public cloud vendor. They did only, they have, you know, massive moats around, you know, their storage to, you know, to really prevent data from leaving their orbit. So there is natural friction in terms of for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on the power and potential of data, unless we allow it to come together. Snowflake is the platform that allows that to happen. You know, we were pleased with our relationship with Salesforce because they did appreciate, you know, why this was important and why this was necessary. And we think, you know, other parts of the industry will gradually come around to it as well. So the idea of a Data Cloud has really come. Right, people are recognizing, you know, why does this matters now. It's not going to happen overnight. It is a step what will function a very big change in mentality and orientation. You know? >> Yeah. It's almost as though the sussification of our industry sort of repeated some of the application silos, and build a heart on to and all the processes of(mummers) Okay, here we go. And you're really trying to break that aren't you? >> Yep, exactly. >> Anita, again, I want to come back to this notion of governance. It's so important. It's the first rule in your title, and it really underscores the importance of this. You know, Frank was just talking about some of the hurdles and this is a big one. I mean we saw this in the early days of big data where governance was this afterthought. It was like bolted on kind of wild west. I'm interested in your governance journey. And maybe you can share a little bit about what role Snowflake has played there in terms of supporting that agenda, and kind of what's next on that journey. >> Sure. Well, you know, I've led data teams, in numerous ways over my career, this is the first time, that I've actually had the opportunity to focus on governance. And what it's done, is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >> Well, I mean, a big part of what you were talking about, at least my inference in your talk, was really that the business folks didn't have to care about, your wonder about they cared about it, but they don't have to wonder about, and about the privacy concerns, et cetera, you've taken care of all that. It's sort of transparent to them. >> Yeah, that's right. Absolutely. So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical, to ensuring you know, that we're able to do this. We don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access. And it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data, we focus on the infrastructure, and making sure that we've architected for scale , and all of these are really important components of our strategy. >> So I have a question maybe each of you can answer it. I sort of see this, our industry moving from products to then, to the platforms and platforms even evolving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing, but, but maybe Frank, you can start and Anita you can add onto Frank's answer. You obviously both passionate about the use of data and trying to do so in a responsible way, that's critical, but it's also going to have business impact. Frank, where's this passion come from on your side? And how are you putting into action in your own organization? >> Well, you know, I'm really going to date myself here, but you know many years ago, you know, I saw the first glimpse of multidimensional databases that were used for reporting really on IBM mainframes. And it was extraordinarily difficult. We didn't even have the words back then in terms of data, warehouses and business, all these terms didn't exist. People just knew that they want to have a more flexible way of reporting and being able to pivot data, dimensionally, all these kinds of things. And I just by whatever this predates, you know, windows 3.1, which really, you know, set off the whole sort of graphical, you know, way of dealing with systems, which there's not whole generations of people that don't know any different. Right? So I've lived the pain of this problem, and sort of had a front row seat, to watching this transpire over a very long period of time. And that's one of the reasons, you know, why I'm here because I finally seen, you know, a glimpse of, you know, I also, as an industry fully, just unleashing and unlocking the potential. We're not at a place where the technology is ahead of people's ability to harness it. Right. Which we'd never been there before. Right. It was always like we wanted to do things and technology wouldn't let us, it's different now. I mean, people are just, heads are spinning with what's now possible, which is why you see Marcus evolve, you know, very rapidly right now, we were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on in the world. The world's changing right in front of your eyes right now, >> So Anita maybe you could add on to what Frank just said and share some of the business impacts, and outcomes that are notable since you've really applied your love of data and maybe touch culture, data culture. Any words of wisdom for folks in the audience who might be thinking about embarking on a Data Cloud journey, similar to what you've been on. >> Yeah Sure. I think for me, I fell in love with technology first, and then I fell in love with data and I fell in love with data because of the impact that data can have, on both the business, and the technology strategy. And so it's sort of that nexus between all three. And in terms of my career journey and some of the impacts that I've seen. I think with the advent of the Cloud, you know, before, well, how do I say this? Before the cloud actually became so prevalent and such a common part of the strategy that's required, it was so difficult, you know, so painful. It took so many hours to actually, be able to calculate, you know, the volumes of data that we had. Now we have that accessibility. And then on top of it, with the Snowflake Data Cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have to have multiple copies of the data. And I think, moving beyond some of the traditional mechanisms for measuring business impact, has only been possible with the volumes of data that we have available to us today. And it's just, it's phenomenal to see the speed at which we can operate and really, truly understand our customer's interests and their preferences, and then tailor the experiences that they really want and deserve for them. It's been a great feeling to get to this point in time. >> That's fantastic. So, Frank, I got to ask you to do so in your spare time you decided to write a book am loving it. I have a signed copy, so I'm going to have to send it back and have you sign it. But, and I love the inside baseball. It's just awesome. So really appreciate that. So, but why did you decide to write a book? >> Well, there were a couple of reasons. Obviously we thought it was an interesting tale to tell for anybody, you know, who is interested in, you know, what's going on? How did this come about? You know, or the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, you know, because this is such a step function, it's so non incremental, we felt like we really needed quite a bit of real estate to really lay out, what the full narrative and context is. And, you know, we thought, you know, books titled the rise of the Data Cloud. That's exactly what it is. And we're trying to make the case for that mindset, that mentality, that strategy, because all of us, you know, I think as an industry we're at risk of, you know, persisting, perpetuating, you know, where we've been since the beginning of computing. So we're really trying to make a pretty forceful case for look, you know, there's an enormous opportunity out there, but there's some choices you have to make along the way. >> Guys, we got to leave it there. Frank. I know you and I are going to talk again, Anita, I hope we have a chance to meet face to face and in the cube live someday, your phenomenal guest and what a great story. Thank you both for coming on. Thanks Dave, >> Thank you >> You're welcome to keep it right there, buddy. We'll be back with the next guest right after this short break. (upbeat music)

>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service, is >> Welcome back. Rush hours started a little bit early here in New York City, with over 10,000 people in attendance for any of US Summit in New York City. I'm stupid, and my co host for today is Corey Quinn. Having a welcome to the program to first time guests from our host Amazon Web service is to my right. Here is Deepak Singh, who is the director of Compute Service's. To his right is Aaron Cow, Who's the senior manager product marketing Gentlemen, thanks so much for joining us. Thank >> you for having us >> for having us, all right, so we know that every day we wake up and there's new announcements coming from Amazon, and the only way most of us keep up with it is trying to re Cory's newsletter here. But in your group and computer, we know there's a lot going on and quite a few announcements. So, Aaron, what do you kick us off with? Some of the hard news that went >> through this morning? Yeah, we just launched Amazon event. Bridgette's Ah, serverless event boss that allows youto connect your applications with data from sources like sass applications. A devious resource is in your own applications. >> All right, So Deepak would look to dig into that a little bit. I like you said, you that Amazon. You learned a lot from cloudwatch in building this tool. Everybody looking at kind of lambda and the service faces, Like Okay, how all these pieces together is that all? Amazon service is all the time. And, of course, Amazon has a huge ecosystem. But help help us understand a layer down. You know how this works. >> Yeah. So, you know, a dress service send events watchman consumer event from one of the best ways to do it is through Lando. Lando. One of London's biggest trends is the number off integration we have with events both taking in events and triggering event. But to your point there already events inside database system. I think one of the things as a service owner, that really excites me about event. How now? Customers of access, not just two ventricles inside eight of us were awesome apartments extended so that the application you can build will be really exciting. >> Quite a few other announcements maybe August or someone CK >> is another announcement where it's open. Source. Software development framework allows you to model your applications using programming language like typescript Job a python and got that. You know the whole thing with building in the cloud. It's slightly different. You usedto take your coat. Put it on a servant. Run it. Now people are building things a little more distributed. Using a lot of different resource is for their applications, so it's getting provisioning. Your infrastructure is a little bit harder, right? Either Have to do a lot of things manually. Are maybe you're writing. A lot of scripts are using a domain specific language, But with CD Kay, you're now able to use the programming languages that you're hurting your applications with two model and provisions your infrastructure. So it's super helpful. Really think it's gonna help developers increase their development velocity? They're able to use things like loops, conditions, object oriented programming. They don't have to do context switching and just a few lines of code. They're able to do a lot more. All right, >> I want I want a playing with it a little bit when it was in review, and one of things that I found that it was extremely helpful was it was a lot easier for me to write something in using CD kay and then see what that rendered down to in terms of cloud formation. And then, oh, I guess that's how I do it in cloud formation, which was great. The counterpoint, though, is it also felt, at times like it was super wordy. So if I read that what it generates compared to what I normally right, which is admittedly awful. But it's all right, we'll start to feel like I'm doing it wrong with that. And then with amplify and with Sam and the rest. There's a lot of higher level abstractions that build cloud formation for you. But then it renders down in a few different key ways under the hood. How much are these products that you're coming out with starting to shape the direction of confirmation itself? Or is that mostly baked and done? >> There's a lot of products that we're building that you know are complimenting information. Information is the template ing modeling language to provisional abusive resource is put on top of that. We have things like Sam, right? That provides a declared of ATM or high level abstracted declared way to build on topical information. You know, we have amplified also use this information to help you build mobile applications in front development and then finally have see decay for general use other things. They're all complimenting and you know are things customers are asking for helping us >> get the ecosystem. Deepak. The container space, of course, has been You know what one of these tidal waves that we've been watching on It's fundamentally changing the way people architect their applications. That huge impact on your product line Give us the update. If you could just start with some of the high level. Remember first when I talk to you. A couple of years ago, the whole kubernetes piece was sorting out. So you know, e c s E. K s usedto have a much longer name that Cory >> Cory. Finally, you fix the compensation problem where someone was getting compensated based upon number of syllables in a service name. So good on you on that one. >> Right on. Uh, you know, acronym, am I? Maybe you can you know, settle once and for all. You know how how we pronounce that >> I'm old school in love with the Army. >> But what what walk us through? Kind of. You know, your container service is, >> I think, the great thing about container, I said, adoption is everywhere on what we find. It brought a VCs the growth of cares where they're running it on to our fargate. Everything is growing like crazy because people find new interesting ways to run applications based on what they know. One what they're comfortable with their customers. Customers like Snap. There's no community well, and they're building on their building a big chunk of their new infrastructure on kneecaps or need to be with, and it basically helped develop a velocity. On the flip side, your customers like Turner Broadcasting that run a lot of their Web service is the comedy central content properties like that on Fargate because they can just stamp them out. They all you know, it's about time. It's a service that you can just keep expanding. So it boils down to one of the key things that you're comfortable with. One of the reasons you fix something if you are running like snap across. You know, in many different looks places you are likely to choose community and standardize on that. So that's the best part for me is people have choices and then the pic based on what they need. At that point in time, it can be two different teams at the same place. Picking a different solution. I will add that one of the areas that we are focused on now is a dub ability and develop experience, though the areas that our customers have been asking for CD Kay played into that record in the demo this morning. And with the probability with container inside on with the fluid that be announced, I think though that area, they do a lot more >> going forward, right? That was one of those cloudwatch container insights. Just explain what that one is >> so historically, when you do cloudwatch look very bm centric, you're looking at CPU memory. You're zooming application. We are instances run for a particular period of time. At the container world you have service is with the underlying tasks. Come and go all you know, a very different rate container inside. It's meant to be a world aware of the fact that you're containerized application that fast service is and part, they're able to get more fine grained metrics on the things that container customers care about. And you're not trying to use the BM centric language to look at the content. That's the biggest reason for doing that. And then on the floor in bedside Boy, our customers want loud rounding to whatever they want to do it on where they understand three or elasticsearch. We do that with data borrows. So we basically wrote a bunch of open source plug in for fluent, but they just end your log where you want them to go. That's kind of maybe a >> Yeah, I view it as more of a log router than I do. Almost anything else? Yeah, a question of where did it come from? Where does it go? How do you do? Keep straight. It's at this point. What is it out? What is it output to these days of their various destination options? Third party vendors cloudwatch history >> to plug in 14315413 because so many people in the center there with three the other one was like Anita. There. Apart from there, you can send it to read, Chef, you can send it todo you can send it to elasticsearch. So based on what however you want and I'll analyze it, you can send it to a custom resource. So you want you're using some third party provider. You can just send your logs over to those. >> Corey, you know, you're dealing with a lot of customers. You know, there's so many, you know, different instance types and some of some of the pieces. You know, what's the feedback you're giving? You know, Amazon these days >> entire depends upon the service teams, and it ranges from This is amazing. Excellent job, too. Okay, it's a good start, and it's always a question, though. It's when you have what 200 service options are darn near. It at this point aren't 70. It's impossible to wind up with something that is evenly consistent, and you have service is that air sub components of other service is built on top. I mean, I think the uh, I guess the feedback I've been giving almost universally across the board is assume that I am about 20% as smart as you right now seem to think I am and then explain it to me, and then I'll probably understand it a lot better. It comes down to service the storytelling more or less of meeting people of various points along their journey, and that I was mentioning in our editorial session just before this segment that that's something that AWS has markedly improved on the last two or three years, where you have customer stories that are rapidly moving up the up the stack as Faras Leverage Service's It's not just we took the EMS, and now we run them somewhere else. Now it's about building of extremely volume intensive applications on top of a whole bunch of managed service is and these air serious cos these air regulators. It's not just Twitter for pets anymore. >> Nothing wrong with that. No, >> So way were discussing like Enron was a great case this morning, and they talked about in the four years that they've been on, they re architected three times, you know, how do you balance all of these new wins is coming out with, you know, how do we make sure that I deploy something today that I've got the flexibility to change. But, you know, I want to be able to lock in my pricing and make it easier. >> Actually, we think about that quite a bit. One of the reasons we met, the way we did something that sits outside a container orchestrator. What? It doesn't lock you into choosing one or the other or even using an architecture. You can start over the monolith, start putting sidecars on it. It's getting with the ability to all your traffic portions of applications. You can start breaking out. You can put them on target. You can put them on PCs. You can put them on it, too. I think that is something we did very consciously because so many of our customers are in that position. And I think more and more are going to go higher up the stock using managed databases. You think lambda. But it's not decision they need to make all up front. They can do it piecemeal, and we see a custom fender. The good example there done that. >> I think one of the >> philosophies of like eight of us is giving customers building blocks the buildings on, so the whole thing is here's a new primitive that you can use. Then you can take it out, replace something with something else, depending on your needs. So we give customers flexibility and choice. >> And part of the problem is that that very much becomes a double edged sword. I mean, most recently you've had effectively declared war on alphabet. I don't mean the large cloud provider that turns things off for a living. I'm talking about the English alphabet where you take a look at all the different ec2 instance types. I think in US East one. Now there's over. What is it? 100 90 different instances you can pick from. It leads to analysis paralysis. Which one do I pick? What's the right answer? What am I committing to? What am I not? And you see that? That's a microcosm. The larger service problem. I want to build a Web app that does a thing. Which service is do I use? You open up the service listing and you just get this sort of sinking sensation. I get that. I can't imagine what someone new to the space is getting to >> you, and this is where things like amplify fargate aws patch. You don't need to select an instance where you just tell us for your requirements are on Batch makes that collection for you the core building. What's important because you can't really figure out what to do. But then you see us too much more about the attack to help people get there. It's an ongoing thing that will keep trying to tackle, but you see a lot more of that. >> It's controversial. One of my favorite things about Lambda, for example, is there's one knob ram, and as you turn that up, other performance characteristics increase and people complain about it. But I love the simplicity because I don't have to sit and think and make all these different decisions. It's one access, >> but if you want more knob, you can you fuck it. So I think that that's the beauty ofit that you do have that choice. >> Yeah, one lines there, and I really liked it. Borders keynote. Is he said way? Really? You know my words, commoditized. I t We all have access to all of the tools now, you know that was you know what big date originally file. It also was used to have to be a nation state 4100 to be able to do some of these things. So, you know, what do you hear from customers? How do they make sure you know, they're staying competitive and ahead on their four in that relationship between the business and I T. What do you hear from your customers these days? >> In terms of that? Well, I think, um, for you know, for customers like I think of Emperor age is a, uh, a pretty good example off that in terms of customers asking us for ability to, you know, integrate their SAS providers and a great a lot of different things and not have thio you No, no, no. >> I have >> to do a lot of undifferentiated heavy lifting and things like that. And customers are increasingly moving towards, like avenger oven architectures. And they asked us, Hey, we really like cloudwatch events and how you do things with a iittie automation and then bringing SAS providers and on way wantto you know, we don't want to build a polling infrastructure and orderto access athe eyes and do all all the heavy lifting. What we did was we built out way took cloudwatch events and added new features for SAS applications and build that into a separate service for people to use. That's like, you know, a lot of the relationships we have our customers listening to what they need and giving them what they want. >> I think that that's a very valuable thing. We used to say, You know, five years ago you would talk about, you know, let's get rid of indifferent, heavy lifting Well, now it's like, No, no, let's enable you know some thing that you would have thought was heavy lifting and we're daunted to be able to do it. But now hopefully it's easier because a lot of this stuff, you know, he said, This is still a little bit daunting, and you know, you've got a lot of ecosystem and service providers, and service is help us. You take care of, you know, because it's the paradox of choice. With all the options that you >> have on. I think that's the beauty of what I'm in a customer that smart. They managed to find interesting ways to keep challenging us and keep us busy. But I also think that really, really many of them the ones who've been able to be successful. I figured out what it needs to be. Take all the tools to give them which other ones where they want to completely hand it over to AWS and give us the responsibility. And then which ones today really feeling, get they care about and the ones who can find their balance of the ones that we see moving faster. I think that's what we're trying to >> write that one thing that does absolutely permeates virtually every service team I've worked with that AWS. I mean, I've had this experience with you where I talk about how my use case isn't a terrific fit for your product, and your response is always well, what is your use case? It's not. Is starting off on the baseline assumption that my use cases ridiculous, which, let's face it, it probably is. But being able to address a customer need to understand that even if it doesn't dictate, road map is incredibly valuable, and I don't find there are too many players in any space, let alone this one that are willing to have the patience to listen to. Frankly, some loud person wearing a suit. >> Way try. I mean, I think you heard me say this so much like a big junk. 85 90% of a road map. Customer request. I would say that even though remember remaining 10% maybe not think that they're directly asked for but think that you observed their running to or that we run into working with, you know, the one of the customers go ahead of the pack. Okay. They have this problem, Baker. How do you generalize that? And we try and understand what it means. One of the reasons to be made the container road map public was This space is moving so quickly. It's almost impossible for us to talk to enough customers to figure that out. So, like, okay, that gives us an avenue for them to come to us and just tell us and get have >> issues. Yeah, s o right. Final question for both of you directions. Looking forward, you know, the road map we love when there is publicly facing material, not under the NBA's that we normally have to be able to hear. So what are you hearing from your customers? What direction are they pulling you towards and that we should expect tow watch aws kind of a cz we head towards reinvent later this year. Yeah, >> like customers are asking us for different things for developer experience, especially event driven architectures. I think there's gonna be a lot of interesting things happening in the land of space and that entire space >> on to add to that. I think your point earlier helping the simplified choices is going to be a big part of it. Meeting them where they are in their ideas with the cooling is a big part of what you'll see us do. So you know, I think you saw examples today. We'll keep building on top of >> All right. Well, send our congratulations to the two pizza teams that worked on all of the projects that were announced today. Look forward to seeing you. You know, down the road in tracking down. Thanks so much. And welcome to be in Cuba one night having us Deepak, you know, from AWS. He's Cory Quinn on student back with lots more coverage from 80 West Summit here in New York City. Thanks for watching

>> Live from Barcelona, Spain. It's the cue covering Sisqo, Live Europe, Brought to you by Cisco and its ecosystem partners. >> All right, welcome back to the Cubes. Live coverage in Barcelona for Sisqo Live twenty nineteen. John for Rico's Cube with David Lantz. Our next guest is Wendy Marches, the President of Cisco, E. M. R. Europe, Middle East in Africa and Russia. Welcome to the Cube. >> Thank you. >> Thanks for joining us. >> Great to be here. >> So one of the things themes this year certainly is cloud data center coming together. But the other backdrop is besides security and all of the things going on with data is the global landscape. So Cisco, see, North American Windows were going on their school live? What's happening in Europe? Actually, GPR has been hot in the past year. What's new? What's the scene like here? >> You know, I think that certainly the scene is one of huge excitement, you know, from our customers across the whole region of Europe, Middle East, Africa, Russia. It's an incredibly diverse region. But you know, if you look at the different countries, the different markets one thing that absolutely is a constant theme that we hear is the desire and the appetite to gain the benefit from transformation. You know, in the digital transformation and what that value can be and realizing that. And if we look for ours, you know within within Cisco and the positioning around realizing the secure intelligent platform is absolutely resonating, you know, so things like multi cloud and realizing that reinventing the network, the security challenge and dealing with that, how you address it with the multi domain architecture approach so our customers are really engaged in the conversation, want to learn more, but most importantly, want help with how. Show me how to do it. >> You guys must be leading the conversation within Cisco as your team in Europe, Miller's nephew in Russia. Because the complexity around compliance and data has been front and center Now for twenty four months now hitting mainstream global landscape, this >> is really >> impacting the architecture. We look at the how intent based NETWORKINGS developing policy based fill in the blank two. Connecting to multiple clouds so kind of complex. A whole new architecture. Reimagining networking. How are you guys seeing them? Trends now is it's still at the tipping point is it's still early. What's your? What's your assessment of the role of data as it gets more complex, more compliant, driven? >> So I think that it's certainly if you look for organizations, the power of being able to understand the importance of your data where it resides, being able to demonstrate that having the integrity and the quality of that data is extremely important as well. So there's a heightened awareness in the market for organizations, global organizations who conduct business in a mere, you know, of course, and we are one of those as well. So a knowledge and understanding and appreciation ofthe compliance regulation. It's only going to become Mohr intense, you know, as we go for. So for organizations to really have robust and rigorous processes around, all of that on technology could be an enabler in the process as well. What >> are the >> unique aspects? Wendy Inn in the region, you obviously have visibility. And on what goes on in North America, what's different in Europe, especially in the context of cloud multi cloud? Obviously GPR, although it's a framework now for for for everybody get on the world. But what's unique in the region? >> So I think the uniqueness is, you know, if you look from a multi cloud standpoint, for example, where you know organizations are, have been, I would say depending on some of the countries and markets a little bit more hesitant around a movement to cloud. And now there is a movement. But it's more one of, well, what is appropriate for me. And how do I ensure I can embrace multi cloud in a way that makes sense for my business. So, rather than a full move to public, there has been a selected, you know, based on application of workload environments and also understanding the security, back to compliance. And also the regulation impacts have some of those movements as well. And of course, that depends upon the vertical or the industry in which those organizations are operating. So for those who are highly regulated, like health care, you're the pharmaceutical sector. There's a deep inspect that goes on there as well, so I think there's a further requirement for due diligence around some of those topics as well. >> Well, in the you know, the Snowden backlash had some paranoia for sure, with everybody saw going to go to two or three clouds. And that's clearly not been the case. Yeah, you have no many dozens and hundreds of service providers that air that air specialists obviously in the region. So we heard today about a million end to end architecture, which is a a bold and ambitious vision. You have a technical background as well. I wonder if you could just describe sort of how that's all going toe transpire. How do you take the customers on their journey? What are they asking you for help with? And where do you see it going? >> Yeah. So if you look at, you know from David this morning, David, get clear on what he talks about. So really, you know, for those different domains, there are competencies, you know, if you think so. There's the data center. There is the edge. There was security world, the collaboration world. So the reality of it is, though, that as a cousin, enterprise or any organization indeed consumes those things. They want to be able to work across all of those areas. And they want the innovation to work in a seamless manner. Is that the end of the day? The problem to solve. To simplify for me, Anita automate reduced complexity. I wanna roll and deploy policy and a consistent in cohesive way. So in order to make that happen, you have to have these environments able to talk to each other, but more importantly, pushed that policy in a cohesive manor across these environments. So for us, it's a journey, eh? So it's not something you could do over Nice. You have to work within your engineering teams and your ecosystem in order to bring that to life and do it in a way where the custom consider could consume it. >> I think you really nailed that. We see in the trend as well. This cross domain component with AP Eyes now but you're open are pushing data around you, moving data from point A to Point B. Sounds like networking. To me, policy is important, but the configuration the deployment, which used to be hard, is now being automated. So the question I have for you here in the definite zone means packed People are learning about programming. >> What is the >> impact of all this to developers were trying to build APS and your ecosystem. There's gotta be an opportunity there some Mike go the way of the old guard fade away and some new kinds of providers might rise up. >> Yeah, you know, this huge opportunity here, and I think it's opportunity around the requirement for new skills, new competencies, but also around you capability to bring this the life. Because if you look from a development standpoint, if you look at how you realize value with organizations and where does the money flow between some of these environments is interesting and the ecosystem itself. You know, Francisco, what What I believe makes us even more powerful is bringing to life on them and accelerating with the ecosystem, because at the end of the day, the customer will buy an ecosystem style environment. So for us to be able to work with all of those parties as we have over many years and there will be new players, the I s. P community, the developer community that we work with that will be really powerful >> forces with system growing significantly, ecosystem grow >> Absolutely, absolutely awesome. Example. Just lookit here because of the organizations that are here. >> I think the development trends clearly intersecting with networking as more programmable right? >> Yeah. >> That's the big takeaway for us. You can program the network. You have infrastructure as code. That's the devil. Promise that now here. Question we're looking at is okay. What's it going to be? The impact of value creation. So from a customer, what does it mean to me? So so, as we look at that, I sent the thing about the Cisco original business model enabling technology. How would you answer that Question of what's being enabled today. What's the big half a customer's? What are you guys enabling for your partners in your >> S o? I think a big part of it is we see now a lot of the conversation there's around What is is the use case. So it's not just a I've got some cool stuff. Show me the cost ofthe that work is how do I apply that into my environment to derive value and that value, maybe around efficiency and maybe a brand provisioning in a more rapid manner, automating in a more realized manner. Lots of different instances where organizations they don't see the benefit associated with that, but also it allows them to free up time of their people. And their teams to move into new areas as well as they move their own business models. Because, you know, it's a massive transition that's happening in the industry. Overall, it's not just were not just changing for the sake of change were changing because the market is asking us to do that >> well. And so customers have to make bets on who they're multi cloud providers, maybe, and obviously Cisco's coming out that from a position of networking strength, which is a good place to come from. But there are other there alternatives because the Bigg market headed strategic. What gives you confidence that Cisco's the right solution? What are you telling your customers in that regard? >> So you know, if I look at the, what gives me confidence is the fact that we have an openness. You know, if you look from A from a P I standpoint of developer standpoint, we've always operated in a mode of an openness so that you have an environment where anyone could write to that's people want that it's incredibly importance or not. Having a proprietary stance is very powerful, but I think also being able to work with a ecosystem that's there where you are a dependency on others, and you meet with the meat in the channel on certain solutions and innovations as well. So you empower a greater community to start to drive that acceleration with you? A swell. You know, I will. Look at the you know, we talk about reinventing the network. It's happening. It's happening now, you see, is doing it. And just how important the network is more than ever before in this transition, you know, ran a number of areas with security with policy, and it's way see it come to life now. >> Well, the old saying the network is the computer will do you no. Cisco's the network. Yeah. I gotta ask you about Brexit is someone who's based in the UK thoughts on effects that that has. I mean, obviously, sir Francisco Global Company. But your perspectives on Brexit >> s So if I look for, you know, as someone who lives in the U. K. You know, clearly we hear about brexit a loss, you know, you do in your country as well. And I would say four words. We over. You know what Cisco is? A global company were very fair. We're very familiar with working with these types of instances and situations. The UK remains for us is an incredibly important market and will continue to be on We'll, you know, we'll continue to invest from a capabilities and a skill standpoint, and I think just force now, you know, working with our teams there. I'm making sure that there's we minimize any impacts based on scenarios, you know, to our customers and apartments. The rules get through. >> Rules change. Adept. I >> could ask >> you about our The Russia piece rushes of GDP is about the size of Spain from correct, interesting that you carve that out of a distinct opportunity. How's the business going there and maybe some comments around >> you're so I can't talk directly about business performances were in quiet period. But I guess we call it out specifically because it is not part of Europe, Middle Eastern Africa, but is a very important part of our region of Vermeer. And if I look for cores of, you know, we believe that there is significant opportunity for us in that market. We have a fantastic team that were closely where there again with our customers and partners. And, you know, we believe there's, you know, absolutely opportunity for Sisko in that market >> development team there as well. Our way >> have we have capability there that works locally with all of our all of our teams and, you know, engineering Competent sale steams etcetera as well. Yeah. >> Good. Good math. >> Wendy, how are you guys organized in your territory? How do you guys maintain close to the customer in the countries? Is the country strategy had just people don't. >> It is a country strategy. So we have, you know, about one hundred twenty three countries within a mere on, we have teams that live and operate in all of those countries. That's Avery close to us from a regional perspective. So want team, you know, that really drives that scale. I'm a fantastic opportunity to go and visit those teams. You know, I spent a lot of time on the road on DH. You know, I enjoy Ascend and they do to, you know, >> is there anything you could talk to your customers that are watching here? Anyone interested, as you guys have transformed as a company, Certainly looking what Cisco is done over the past few years a complete transformation building on your base You've been through You've been agile getting nimble being Mohr use case driven Central, Central. What have you learned? What's your learnings? And what would you pay it forward in terms of advice? >> Yeah, So, you know, if I if I look at it, we're not through, we're still you know we're still on the journey and I think a big part of it is accepting and acknowledging a need for change is really important. But a big part of this change is culture. You're a friend of Ford's within Sisko, and the culture of our teams are people on having an attitude in a style of a desire, a curiosity, Onda willingness for change is really, really important. And as we talk about the transformation topic, you need both. You know, technology's incredibly important and powerful, but you need a spirit and a culture and your people in your teams you want to drive that change with you >> in their culture starts in trouble. Thank you for taking the time. >> Thank you >> for the following your progress as we take our cue. Global next couple of years. Looking forward to keeping an eye on. You guys are doing. Thanks for joining. >> Thank you. Thank you. See you >> here. Live in Barcelona. Francisco live twenty nineteen. We're back with more after this short break.

>> From the Palace of Fine Arts in San Francisco, it's theCUBE, covering AT&T Spark. Now here's Jeff Frick. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're at the Palace of Fine Arts in San Francisco at the AT&T Spark event. It's really all about 5G and what 5G is going to enable. You know, this is a really big technology that's very, very close. I think a lot closer than most people understand. And one of the most important components of 5G is it was designed from the ground up really not so much for people-to-people communications as much as machine-to-machine communications. So we're really excited to have someone who's right in the thick of that and talk about the implications, especially another topic that we hear all the time, which is Edge computing. So it's Alicia Abella. She is the VP of Operational Automation in Program Management from AT&T Labs. Alicia, welcome. >> Thank you for having me, Jeff. >> Absolutely. So we were talking a little bit before we turn on the cameras about 5G and Edge computing. And how the two, while not directly tied together, are huge enablers of one another. I wonder if you can unpack a little bit about why is 5G such an important component to kind of the vision of Edge computing? >> Sure, absolutely. Yeah, happy to do so. So Edge computing is really about bringing processing power closer to the end device, closer to the end user, where a lot of the processing data analytics has to occur. And you want to do that because you want to be able to deliver the services and applications close to the edge, close to where the customer is, so that you can deliver on the speeds that those applications need. 5G plays a role because 5G is promising to be very fast and also very reliable and very secure. So now you've got three things to your advantage paired up with Edge to be able to deliver on a lot of these use cases that we hear a lot about when we talk about 5G, when we talk about Edge. Some example use cases are the autonomous vehicle. The autonomous vehicle is a classic example for Edge computing as well as 5G. And in fact, it illustrates a kind of continuum, because you can have processing that always has to remain in the car. Anything related to safety? That processing has to happen right on that device. The device in this case being the car. But there are other processing capabilities, like maybe updates to real-time maps. That could happen on the Edge. You still have to be near real-time, so you want to have that kind of processing and updating happening at the Edge. Then maybe you have something where you want to download some new entertainment, a movie to your car. Well, that can reside back at the data center, further away from where the device or the car is. So you've got this continuum. >> So really, what the 5G does is really open up the balance of how you can distribute that store computing and communications. It's always about latency. At the end of the day, it's always about latency. And as much as we want to get as much compute close, oh, and also, I guess power. Power and latency. >> Power and Edge actually go hand-in-hand as well. >> It's a big deal, right? >> Mhm. >> So what you're saying is, because of 5G, and the fact that now you have a much lower latency, faster connectivity port, you can now have some of that stuff maybe not at the Edge and enable that Edge device to do more, other things? >> Yes, so I often like to say that we are unleashing the device away from having it be tethered to the compute processor that's handling it and now you can go mobile. Because now what you do is, if the processing is happening on the Edge and not on the device, you save on battery life, but you also make the device more lightweight, easier to manage, easier to move around. The form factor can become smaller. So there's also an advantage to Edge computing to the device as well. >> Right. It's pretty interesting. There was an NVIDIA demo in the keynote of running a video game on the NVIDIA chips in a data center and pumping a really high resolution experience back out to the laptop screen I think is what he was using it for. And it's a really interesting use case in how when you do have these fast, reliable networks, you can shift the compute, and not just a peer compute, but the graphics, et cetera, and really start to redistribute that in lots of different ways that were just not even fathomable before. Before you had to buy the big gaming machine. You had to buy the big, giant GPU. You had to have that locally, and all that was running on your local machine. You just showed a demo where it's all running back in their data center in Santa Clara. Really opens up a huge amount of opportunity. >> That's right. So Edge computing is really distributed in nature. I mean, it is all about distribution. And distributing that compute power wherever you need it. Sprinkling it across the country of where you need it. So we've gone, there's been this pendulum shift, where we started with the mainframe, big rooms, lots of air conditioning, and then the pendulum swung over to the PC. And that client-server model. Where now you had your PC and you did your computing locally. And then it swung back the other way for Cloud computing where everything was centralized again and all that compute power was centralized. And now the pendulum is swinging back again the other way to this distributed model where now you've got your compute capabilities distributed across the country where you need it. >> Right. So interesting. I mean, networking was the last of the virtualized platform between storage and compute, and then finally networking. But if you really start to think of a world with basically infinite power, compute, infinite store, and infinite networking, basically asymptotically approaching zero pricing. Think of the world from that way. We're not there. We're never going to get to that absolute place, but it really opens up a lot of different ways to think about what you could do with that power. So I wonder if there's some other things you can share with us. At Labs, you guys are looking forward to this 5G world. What are some of the things that you see that just, wow, I would have never even thought that was even in the realm of possibility that some people are coming up with? >> Yeah. >> Any favorites? >> Oh, I think one of our favorites is certainly looking at the case of manufacturing. Even though you would think of manufacturing as very fixed, the challenge with manufacturing is that a lot of those robotics capabilities that are in the manufacturing assembly lines, for example, they're all based on wires and they can't change and upgrade what they're doing very quickly. So being able to deliver 5G, have things that are wireless, and have Edge compute capabilities that are very powerful means that they can now shift and move around their assembly lines very quickly. So that's going to help the economy. Help those businesses be able to adapt more quickly to changes in their businesses. And so that's one that is quite exciting to us. And I would say the next one that's also exciting for us would be, we talked about autonomous vehicles already, 'cause that one's kind of far out, right? >> I don't think it's as far as most people think, actually. We covered a lot of autonomous vehicle companies, and there's just so much research being done now. I don't think it's as far out as people think. >> Yes, and so I think we are definitely committed to deploying Edge compute. And in the process, from a more technical perspective, I think one of the things that we are going to be interested in doing is, and you alluded to it before, is how do you manage all of those applications and services and distribute them in a way that is economical, that we can do it at scale, that we can do it on demand? So that too is part of what's exciting about being able to deploy Edge. >> Yeah. It's pretty interesting, the manufacturing example, 'cause it came up again in the keynote to really embracing software-defined, embracing open source. And the takeaway was moving at the speed of software development, not moving at the speed of hardware development. Because software moves a lot faster. And can be more flexible. It's easy to respond to market demands, or competitive demands, or just to innovate a lot faster. So really taking that approach, and obviously a lot of conversation about you guys in the open Stack community and the open-source projects enables you and your customers to start to adapt to software-defined innovation as opposed to just pure hardware-defined innovation. >> That's right. That's right, yup. >> Alright, Alicia, I'll give you the final word. Any surprises? Oh, no, you've got a chat coming up, so why don't you give us a quick preview for what your conversation is going to be about later today? >> Yeah, thank you, Jeff. So yeah, later I'll be talking about AT&T's initiatives around encouraging women to pursue stem fields. In particular, computer science. It turns out that the number of women getting undergraduate degrees in computer science peaked in the mid-80s. And it's been going downhill since. Last year, only 17% of women were getting degrees in computer science So AT&T's mission, and what we announced today was a million dollar donation to the Girls Who Code organization. That's one of many different non-profit organizations that AT&T is involved with to make sure that we continue to encourage young women and also underrepresented minorities and others who want to get in the stem fields to get involved because technology is changing very quickly. We need people who can understand the technology, who can develop the software we talked about, and we need to get that pipeline filled up. And so we're very committed to helping the community and helping to encourage young girls to pursue degrees in stem. >> That's great. Girls Who Code is a fantastic organization. We've had 'em on. Anita Borg, I mean, there's so much good work that goes on out there, so that's a great announcement. And congratulations. >> Thank you. >> And I'm sure that's a meaningful contribution. >> Yeah, thank you. >> So Alicia, thanks for stopping by, and good luck this afternoon, and we'll see you next time. >> Thank you, Jeff. >> Alright. >> Appreciate it. >> She's Alicia, I'm Jeff. You're watching theCUBE. We're at AT&T Spark in downtown San Francisco. Thanks for watching. (upbeat electronic music)

>> Announcer: From San Mateo, California, it's theCUBE! Covering SnapLogic, Innovation Day, 2018. Brought to you by SnapLogic. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are in San Mateo, at what they call the crossroads, it's 92 and 101. If you're coming by and probably sitting in a traffic, look up and you'll see SnapLogic. It's their new offices. We're really excited to be here for Innovation Day. We're excited to have this CTO, James Markarian. James, great to see you and I guess, we we last talked was a couple years ago in New York City. >> Yeah that's right, and why was I there? It was like a big data show. >> That's right. >> And we we are two years later talking about big data. >> Big data, big data is fading a little bit, because now big data is really an engine, that's powering this new thing that's so exciting, which is all about analytics, and machine learning, and we're going to eventually stop saying artificial intelligence and say augmented intelligence, 'cause there's really nothing artificial about it. >> Yeah and we might stop saying big data and just talk about data because it's becoming so ubiquitous. >> Jeff: Right. >> I know that big data, it's not necessarily going away but it's sort of how we're thinking about handling it is, like kind of evolved over time, especially in the last couple of years. >> Right. >> That's what we're kind of seeing from our customers. >> 'Cause there's kind of an ingredient now, right? It's no longer this new shiny object now. It's just part of the infrastructure that helps you get everything else done. >> Yeah, and I think when you think about it, from like, an enterprise point of view, that that shift is going from experimentation to operationalizing. I think that the things you look for in experimentation, there's like, one set of things here looking for proving out the overall value, regardless maybe of cost and uptime and other things and as you operationalize you start thinking about other considerations that obviously Enterprise IT has to think about. >> Right, so if you think back to like, Hadoop Summit and Hadoop World who were first cracking their teeth, like in 2010 or around that time frame, one of the big discussions that always comes up and that was before kind of the rise of public cloud, you know which has really taken off over the last several years, there's this kind of ongoing debate between, do you move the data to the compute or do you move the compute to the data? There was always like, this monster data gravity issue which was almost insurmountable and many would say, oh, you're never going to get all your data into the cloud. It's just way too hard and way too expensive. But, now Amazon has Snowball and Snowball isn't big enough. They actually had a diesel truck that'll come and help you come move your data. Amazon rolled that thing across the stage a couple of years ago. The data gravity thing seems to be less and if you think of a world with infinite compute, infinite stored, infinite networking asyndetically approaching zero, not necessarily good news for some vendors out there but that's a world that we're eventually getting to that changes the way that you organize all this stuff. >> Yeah, I think so and so much has changed. I was fortunate to be one of the early speakers, like I used to do Worlds and everything, and I was adamantly proclaiming you know, the destiny of Hadoop as bright and shiny and there's this question about what really happened. I think that there's a kind of a few different variables that kind of shifted at the same time. One, is of course, this like glut of computing in the cloud happened and there are so many variables moving at once. It's like, How much time do you have Jeff? >> Ask them to get a couple more drinks for us. >> Seeing our lovely new headquarters here and one of the things is that there is no big data center. We have a little closet with some of the servers we keep around but mostly, everything we do is on Amazon. You're even looking at things like, commercial real estate is changing because I don't need all the cooling and the power and the space for my data center that I once had. >> Jeff: Right, right. >> I become a lot more space efficient than I used to be and so the cloud is really kind of changing everything. On the data side, you mention this like, interesting philosophical shift, going from I couldn't possibly do it in the cloud to why in the world would we not do things in the cloud. Maybe the one stall word in there being some fears about security. Obviously there's been a lot of breaches. I think that there's still a lot of introspection everyone needs to do about, are my on premise systems actually more secure than some of these cloud providers? It's really not clear that we know the answer to that. In fact, we suspect that some of the cloud providers are actually more secure because they are professionals about it and they have the best practice. >> And a whole lot of money. >> The other thing that happened that you didn't mention, that's approaching infinity and we're not quite there yet, is interconnect speeds. So it used to be the case that I have a bunch of mainframes and I have a tier rating system and I have a high speed interconnect that puts the two together. Now with fiber networks and just in general, you can run super high speed, like WAN. Especially if you don't care quite as much about latency. So if 500 millisecond latency is still okay with you. >> Great. >> You can do a heck of a lot and move a lot to the cloud. In fact, it's so good, that we went from worrying, could I do this in the cloud at all to well, why wouldn't I do somethings in Amazon and some things in Microsoft and some things in Google? Even if it meant replicating my data across all these environments. The backdrop for some of that is, we had a lot of customers and I was thinking that people would approach it this way, they would install on premise Hadoop, whether it's like Apache or Cloud Air or the other vendors and I would hire a bunch of folks that are the administrators and retire terra data and I'm going to put all my ETL jobs on there, etc. It turned out to be a great theory and the practice is real for some folks but it turned out to be moving a lot of things to kind of shifting sands because Hadoop was evolving at the time. A lot of customers were putting a lot of pressure on it, operational pressure. Again, moving from experimentation phase over to like, operational phase. >> Jeff: Right, right. >> When you don't have the uptime guarantee and I can't just hire somebody off the street to administer this, it has to be a very sharp, knowledgeable person that's very expensive, people start saying, what am I really getting from this and can I just dump it all in S3 and apply a bunch of technology there and let Amazon worry about keeping this thing up and running? People start to say, I used to reject that idea and now it's sounding like a very smart idea. >> It's so funny we talk about people processing tech all the time, right? But they call them tech shows, they don't call them people in process shows. >> Right. >> At least not the ones we go to but time and time again I remember talking to some people about the Hadoop situation and there's just like, no Hadoop people. Sometimes technology all day long. There just aren't enough people with the skills to actually implement it. It's probably changed now but I remember that was such a big problem. It's funny you talk about security and cloud security. You know, at AWS, on Tuesday night of Reinvent, they have a special, kind of a technical keynote speak and like, James Hamilton would go. In the amount of resources, and I just remember one talk he gave just on their cabling across the ocean, and the amount of resources that he can bring to bear, relative to any individual company, is so different; much less a mid-tier company or a small company. I mean, you can bring so much more resources, expertise and knowledge. >> Yeah, the economy is a scale, their just there. >> They're just crazy. >> That's right and that why you know, you sort of assume that the cloud sort of, eventually eats everything. >> Right, right. >> So there's no reason to believe this won't be one of those cases. >> So you guys are getting Extreme. So what is Snaplogic Extreme? >> Well, Snaplogic Extreme is kind of like a response to this trend of data moving from on premise to the cloud and there are some interesting dynamics of that movement. First of all, you need to get data into the cloud, first of all and we've been doing that for years. Connect to everything, dump it in S3, ADLS, etc. No problem. The thing we're seeing with cloud computing is like, there's another interesting shift. Not only is it kind of like mess for less, and let Amazon manage all this, and I probably refer to Amazon more than other vendors would appreciate. >> Right, right. They're the leaders so let's call a spade a spade. >> Yeah. >> Certainly Google and Microsoft are out there as well so those are the top three and we've acknowledged that. >> One of the interesting things about it is that you couldn't really adequately achieve on premises is the burstiness of your compute. I run at a steady state where I need, you know, 10 servers or a 100 servers, but every once in a while, I need like, 1,000 or 10,000 servers to apply to something. So what's the on premise model? Rack and stack, 10,000 machines, and it's like waiting for the great pumpkin, waiting for that workload to come that I've been waiting months and months for and maybe it never comes but I've been paying for it. I paid for a software license for the thing that I need to run there. I'm paying for the cabling and the racking and everything and the person administering. Make sure the disks are all operating in the case where it gets used. Now, all of a sudden, we are taking Amazon and they're saying, hey, pay us for what you're using. You can use reserved pricing and pay a lower rate for the things you might actually care about on a consistent basis but then I'm going to allow you to spike, and I'll just run the meter. So this has caused software vendors like us, to look at the way we charge and the way that we deploy our resources and say, hey, that's a very good model. We want to follow that and so we introduced Snaplogic Extreme, which has a few different components. Basically, it enables us to operate in these elastic environments, shift our thinking in pricing so that we don't think about like, node based or god forbid, core based pricing and say like, hey, basically pay us for what you do with your data and don't worry about how many servers it's running on. Let Snaplogic worry about spinning up and spinning down these machines because a lot of these workloads are data integration or application workloads that we know lots about. >> Right. >> So first of all, we manage these ephemeral, what we call ephemeral or elastic clusters. Second of all, the way that we distribute our workload is by generating Spark code currently. We use the same graphic environment that you use for everything but instead of running on our engines, we kind of spit out Spark code on the end that takes advantage of the massive scale out potential for these ephemeral environments. >> Right. >> We've also kind of built this in such a way that it's Spark today but it could be like, Native or some other engine like Flank or other things that come up. We really don't care like what back end engine actually is as long as it can run certain types of data oriented jobs. It's actually like lots of things in one. We combine out data acquisition and distribution capability with this like, massive elastic scale out capability. >> Yeah, it's unbelievable how you can spin that up and then of course, most people forget you need to spin it down after the event. >> James: Yeah, that's right. >> We talked to a great vendor who talked about, you know, my customer spends no money with me on the weekend, zero. >> James: Right. >> And I'm thrilled because they're not using me. When they do use me, then they're buying stuff. I think what's really interesting is how that changes. Also, your relationship with your customer. If you have a recurring revenue model, you have to continue to deliver a value. You have to stay close to your customer. You have to stay engaged because it's not a one time pop and then you send them the 15% or 20% maintenance bill. It's really this ongoing relationship and they're actually gaining value from your products each and every time you use that. It's a very different way. >> Yeah, that's right. I think it creates better relationships because you feel like, what we do is unproportionate to what they do and vise versa, so it has this fundamental fairness about it, if you will. >> Right, it's a good relationship but I want to go down another path before you turn the cameras on. Talk a little bit about the race always between the need for compute and the compute. It used to be personified best with Microsoft and Intel until we come out with a new chip and then Microsoft OS would eat up all the extra capacity and then they'd come up with a new chip and it was an ongoing thing. You made an interesting comment that, especially in the cloud world where the scale of these things is much, much bigger, that ran a world now where the compute and the storage have kind of, outpaced the applications, if you will, and there's an opportunity for the application to catch up. Oh by the way, we have this cool new thing called machine learning and augmented intelligence. I wonder if you could, is that what's going to fill or kind of rebalance the consumption pattern? >> Yeah, it seems that way and I always think about kind of like, compute and software spiraling around each other like a helix. >> Like at one point, one is leading the other and they sort of just, one eventually surpasses the other and then you need innovation on the other side. I think for a while, like if you turn the clock way back to like, when the Pentium was introduced and everyone was like, how are we ever going to use all of the compute power. >> Windows 95, whoo! >> You know, power of like the Pentium. Do I really need to run my spreadsheets 100% faster? There's no business value whatsoever in transacting faster, or like general user interface or like graphical user interfaces or rendering web pages. Then you start seeing this new glut, often led by like researchers first. Like, software applications coming up that use all of this power because in academia you can start saying, what if I did have infinite compute? What would I do differently? You see things, you know like VR and advanced gaming, come up on the consumer side. Then I think the real answer on the business side is AI and ML. The general trend I start thinking of is something I used to talk about, back in the old days, which is conversion of like, having machines work for us instead of us working for machines. The only way we're ever going to get there is by having higher and higher intelligence on the application side so that it kind of intuits more based on what it's seen before and what it knows about you, etc., in terms of the task that needs to get done. Then there's this whole new breed of person that you need in order to wield all that power because like Hadoop, it's not just natural. You don't just have people floating around like, hey, you know, I'm going to be an Uzi expert or a yarn expert. You don't run into people everyday that's like, oh, yeah, I know neural nets well. I'm a gradient descent expert or whatever you're model is. It's really going to drive like, lots of changes I think. >> Right, well hopefully it does and especially like we were talking about earlier, you know, within core curriculums at schools and stuff. We were with Grace Hopper and Brenda Wilkerson, the new head of the Anita Borg organization, was at this Chicago public school district and they're actually starting to make CS a requirement, along with biology and and physics and chemistry and some of these other things. >> Right. >> So we do have a huge, a huge dearth of that but I want to just close out on one last concept before I let you go and you guys are way on top of this. Greg talked about what you just talked about, which is making the computers work for us versus the other way around. That's where the democratization of the power that we heard a lot about the democratization of big data and the tools and now you guys you guys are talking about the democratization of the integration, especially when you have a bunch of cloud based applications that everybody has access to and maybe, needs to stitch together a different way. But when you look at this whole concept of democratization of that power, how do you see that kind of playing out over the next several years? >> Yeah, that's a very big- >> Sorry I didn't bring you a couple of beer before I brought that up. >> Oh no, I got you covered. So it's a very big, interesting question because I think that you know, first of all, it's one of these, god knows, we can't predict with a lot of accuracy how exactly that's going to look because we're sort of juxtaposing two things. One is, part of the initial move to the cloud was the failure to properly democratize data inside the enterprise, for whatever reason, and we didn't do it. Now we have the computer resources and the central, kind of web based access to everything. Great. Now we have Cambridge Analytica and like, Facebook and people really thinking about data privacy and the fact that we want ubiquitous safe access. I think we know how to make things ubiquitous. The question is, do we know how to make it safe and fair so that the right people are using the right data and the right way? It's a little bit like, you know, there's all these cautionary tales out there like, beware of AI and robotics and everything and nobody really thinks about the danger of the data that's there. It's a much more immediate problem and yet it's sort of like the silent killer until some scandal comes up. We start thinking about these different ways we can tackle it. Obviously there's great solutions for tokenization and encryption and everything at the data level but even if you have the access to it, the question is, how do you control that wildfire that could happen as soon as the horse leaves the barn. Maybe not in it's current form, but when you look at things like Blockchain, there's been a lot of predictions about how Blockchain can be used around like, data. I think that this privacy and this curation and tracking of who has the data, who has access to it and can we control it, I think you are looking at even more like, centralized and guarded access to this private data. >> Great, interesting times. >> Yeah, yeah Jeff, for sure. >> Alright James, well thanks for taking a couple of minutes with us. I really enjoyed the conversation. >> Yeah, it's always great. Thanks for having me Jeff. >> It's James on Jeff and you're watching theCUBE We're at the Snaplogic headquarters in San Mateo, California and thanks for watching. (electronic music)

>> Announcer: From San Mateo, California, it's theCUBE! Covering SnapLogic, Innovation Day, 2018. Brought to you by SnapLogic. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are in San Mateo, at what they call the crossroads, it's 92 and 101. If you're coming by and probably sitting in a traffic, look up and you'll see SnapLogic. It's their new offices. We're really excited to be here for Innovation Day. We're excited to have this CTO, James Markarian. James, great to see you and I guess, we we last talked was a couple years ago in New York City. >> Yeah that's right, and why was I there? It was like a big data show. >> That's right. >> And we we are two years later talking about big data. >> Big data, big data is fading a little bit, because now big data is really an engine, that's powering this new thing that's so exciting, which is all about analytics, and machine learning, and we're going to eventually stop saying artificial intelligence and say augmented intelligence, 'cause there's really nothing artificial about it. >> Yeah and we might stop saying big data and just talk about data because it's becoming so ubiquitous. >> Jeff: Right. >> I know that big data, it's not necessarily going away but it's sort of how we're thinking about handling it is, like kind of evolved over time, especially in the last couple of years. >> Right. >> That's what we're kind of seeing from our customers. >> 'Cause there's kind of an ingredient now, right? It's no longer this new shiny object now. It's just part of the infrastructure that helps you get everything else done. >> Yeah, and I think when you think about it, from like, an enterprise point of view, that that shift is going from experimentation to operationalizing. I think that the things you look for in experimentation, there's like, one set of things here looking for proving out the overall value, regardless maybe of cost and uptime and other things and as you operationalize you start thinking about other considerations that obviously Enterprise IT has to think about. >> Right, so if you think back to like, Hadoop Summit and Hadoop World who were first cracking their teeth, like in 2010 or around that time frame, one of the big discussions that always comes up and that was before kind of the rise of public cloud, you know which has really taken off over the last several years, there's this kind of ongoing debate between, do you move the data to the compute or do you move the compute to the data? There was always like, this monster data gravity issue which was almost insurmountable and many would say, oh, you're never going to get all your data into the cloud. It's just way too hard and way too expensive. But, now Amazon has Snowball and Snowball isn't big enough. They actually had a diesel truck that'll come and help you come move your data. Amazon rolled that thing across the stage a couple of years ago. The data gravity thing seems to be less and if you think of a world with infinite compute, infinite stored, infinite networking asyndetically approaching zero, not necessarily good news for some vendors out there but that's a world that we're eventually getting to that changes the way that you organize all this stuff. >> Yeah, I think so and so much has changed. I was fortunate to be one of the early speakers, like I used to do Worlds and everything, and I was adamantly proclaiming you know, the destiny of Hadoop as bright and shiny and there's this question about what really happened. I think that there's a kind of a few different variables that kind of shifted at the same time. One, is of course, this like glut of computing in the cloud happened and there are so many variables moving at once. It's like, How much time do you have Jeff? >> Ask them to get a couple more drinks for us. >> Seeing our lovely new headquarters here and one of the things is that there is no big data center. We have a little closet with some of the servers we keep around but mostly, everything we do is on Amazon. You're even looking at things like, commercial real estate is changing because I don't need all the cooling and the power and the space for my data center that I once had. >> Jeff: Right, right. >> I become a lot more space efficient than I used to be and so the cloud is really kind of changing everything. On the data side, you mention this like, interesting philosophical shift, going from I couldn't possibly do it in the cloud to why in the world would we not do things in the cloud. Maybe the one stall word in there being some fears about security. Obviously there's been a lot of breaches. I think that there's still a lot of introspection everyone needs to do about, are my on premise systems actually more secure than some of these cloud providers? It's really not clear that we know the answer to that. In fact, we suspect that some of the cloud providers are actually more secure because they are professionals about it and they have the best practice. >> And a whole lot of money. >> The other thing that happened that you didn't mention, that's approaching infinity and we're not quite there yet, is interconnect speeds. So it used to be the case that I have a bunch of mainframes and I have a tier rating system and I have a high speed interconnect that puts the two together. Now with fiber networks and just in general, you can run super high speed, like WAN. Especially if you don't care quite as much about latency. So if 500 millisecond latency is still okay with you. >> Great. >> You can do a heck of a lot and move a lot to the cloud. In fact, it's so good, that we went from worrying, could I do this in the cloud at all to well, why wouldn't I do somethings in Amazon and some things in Microsoft and some things in Google? Even if it meant replicating my data across all these environments. The backdrop for some of that is, we had a lot of customers and I was thinking that people would approach it this way, they would install on premise Hadoop, whether it's like Apache or Cloud Air or the other vendors and I would hire a bunch of folks that are the administrators and retire terra data and I'm going to put all my ETL jobs on there, etc. It turned out to be a great theory and the practice is real for some folks but it turned out to be moving a lot of things to kind of shifting sands because Hadoop was evolving at the time. A lot of customers were putting a lot of pressure on it, operational pressure. Again, moving from experimentation phase over to like, operational phase. >> Jeff: Right, right. >> When you don't have the uptime guarantee and I can't just hire somebody off the street to administer this, it has to be a very sharp, knowledgeable person that's very expensive, people start saying, what am I really getting from this and can I just dump it all in S3 and apply a bunch of technology there and let Amazon worry about keeping this thing up and running? People start to say, I used to reject that idea and now it's sounding like a very smart idea. >> It's so funny we talk about people processing tech all the time, right? But they call them tech shows, they don't call them people in process shows. >> Right. >> At least not the ones we go to but time and time again I remember talking to some people about the Hadoop situation and there's just like, no Hadoop people. Sometimes technology all day long. There just aren't enough people with the skills to actually implement it. It's probably changed now but I remember that was such a big problem. It's funny you talk about security and cloud security. You know, at AWS, on Tuesday night of Reinvent, they have a special, kind of a technical keynote speak and like, James Hamilton would go. In the amount of resources, and I just remember one talk he gave just on their cabling across the ocean, and the amount of resources that he can bring to bear, relative to any individual company, is so different; much less a mid-tier company or a small company. I mean, you can bring so much more resources, expertise and knowledge. >> Yeah, the economy is a scale, their just there. >> They're just crazy. >> That's right and that why you know, you sort of assume that the cloud sort of, eventually eats everything. >> Right, right. >> So there's no reason to believe this won't be one of those cases. >> So you guys are getting Extreme. So what is Snaplogic Extreme? >> Well, Snaplogic Extreme is kind of like a response to this trend of data moving from on premise to the cloud and there are some interesting dynamics of that movement. First of all, you need to get data into the cloud, first of all and we've been doing that for years. Connect to everything, dump it in S3, ADLS, etc. No problem. The thing we're seeing with cloud computing is like, there's another interesting shift. Not only is it kind of like mess for less, and let Amazon manage all this, and I probably refer to Amazon more than other vendors would appreciate. >> Right, right. They're the leaders so let's call a spade a spade. >> Yeah. >> Certainly Google and Microsoft are out there as well so those are the top three and we've acknowledged that. >> One of the interesting things about it is that you couldn't really adequately achieve on premises is the burstiness of your compute. I run at a steady state where I need, you know, 10 servers or a 100 servers, but every once in a while, I need like, 1,000 or 10,000 servers to apply to something. So what's the on premise model? Rack and stack, 10,000 machines, and it's like waiting for the great pumpkin, waiting for that workload to come that I've been waiting months and months for and maybe it never comes but I've been paying for it. I paid for a software license for the thing that I need to run there. I'm paying for the cabling and the racking and everything and the person administering. Make sure the disks are all operating in the case where it gets used. Now, all of a sudden, we are taking Amazon and they're saying, hey, pay us for what you're using. You can use reserved pricing and pay a lower rate for the things you might actually care about on a consistent basis but then I'm going to allow you to spike, and I'll just run the meter. So this has caused software vendors like us, to look at the way we charge and the way that we deploy our resources and say, hey, that's a very good model. We want to follow that and so we introduced Snaplogic Extreme, which has a few different components. Basically, it enables us to operate in these elastic environments, shift our thinking in pricing so that we don't think about like, node based or god forbid, core based pricing and say like, hey, basically pay us for what you do with your data and don't worry about how many servers it's running on. Let Snaplogic worry about spinning up and spinning down these machines because a lot of these workloads are data integration or application workloads that we know lots about. >> Right. >> So first of all, we manage these ephemeral, what we call ephemeral or elastic clusters. Second of all, the way that we distribute our workload is by generating Spark code currently. We use the same graphic environment that you use for everything but instead of running on our engines, we kind of spit out Spark code on the end that takes advantage of the massive scale out potential for these ephemeral environments. >> Right. >> We've also kind of built this in such a way that it's Spark today but it could be like, Native or some other engine like Flank or other things that come up. We really don't care like what back end engine actually is as long as it can run certain types of data oriented jobs. It's actually like lots of things in one. We combine out data acquisition and distribution capability with this like, massive elastic scale out capability. >> Yeah, it's unbelievable how you can spin that up and then of course, most people forget you need to spin it down after the event. >> James: Yeah, that's right. >> We talked to a great vendor who talked about, you know, my customer spends no money with me on the weekend, zero. >> James: Right. >> And I'm thrilled because they're not using me. When they do use me, then they're buying stuff. I think what's really interesting is how that changes. Also, your relationship with your customer. If you have a recurring revenue model, you have to continue to deliver a value. You have to stay close to your customer. You have to stay engaged because it's not a one time pop and then you send them the 15% or 20% maintenance bill. It's really this ongoing relationship and they're actually gaining value from your products each and every time you use that. It's a very different way. >> Yeah, that's right. I think it creates better relationships because you feel like, what we do is unproportionate to what they do and vise versa, so it has this fundamental fairness about it, if you will. >> Right, it's a good relationship but I want to go down another path before you turn the cameras on. Talk a little bit about the race always between the need for compute and the compute. It used to be personified best with Microsoft and Intel until we come out with a new chip and then Microsoft OS would eat up all the extra capacity and then they'd come up with a new chip and it was an ongoing thing. You made an interesting comment that, especially in the cloud world where the scale of these things is much, much bigger, that ran a world now where the compute and the storage have kind of, outpaced the applications, if you will, and there's an opportunity for the application to catch up. Oh by the way, we have this cool new thing called machine learning and augmented intelligence. I wonder if you could, is that what's going to fill or kind of rebalance the consumption pattern? >> Yeah, it seems that way and I always think about kind of like, compute and software spiraling around each other like a helix. >> Like at one point, one is leading the other and they sort of just, one eventually surpasses the other and then you need innovation on the other side. I think for a while, like if you turn the clock way back to like, when the Pentium was introduced and everyone was like, how are we ever going to use all of the compute power. >> Windows 95, whoo! >> You know, power of like the Pentium. Do I really need to run my spreadsheets 100% faster? There's no business value whatsoever in transacting faster, or like general user interface or like graphical user interfaces or rendering web pages. Then you start seeing this new glut, often led by like researchers first. Like, software applications coming up that use all of this power because in academia you can start saying, what if I did have infinite compute? What would I do differently? You see things, you know like VR and advanced gaming, come up on the consumer side. Then I think the real answer on the business side is AI and ML. The general trend I start thinking of is something I used to talk about, back in the old days, which is conversion of like, having machines work for us instead of us working for machines. The only way we're ever going to get there is by having higher and higher intelligence on the application side so that it kind of intuits more based on what it's seen before and what it knows about you, etc., in terms of the task that needs to get done. Then there's this whole new breed of person that you need in order to wield all that power because like Hadoop, it's not just natural. You don't just have people floating around like, hey, you know, I'm going to be an Uzi expert or a yarn expert. You don't run into people everyday that's like, oh, yeah, I know neural nets well. I'm a gradient descent expert or whatever you're model is. It's really going to drive like, lots of changes I think. >> Right, well hopefully it does and especially like we were talking about earlier, you know, within core curriculums at schools and stuff. We were with Grace Hopper and Brenda Wilkerson, the new head of the Anita Borg organization, was at this Chicago public school district and they're actually starting to make CS a requirement, along with biology and and physics and chemistry and some of these other things. >> Right. >> So we do have a huge, a huge dearth of that but I want to just close out on one last concept before I let you go and you guys are way on top of this. Greg talked about what you just talked about, which is making the computers work for us versus the other way around. That's where the democratization of the power that we heard a lot about the democratization of big data and the tools and now you guys you guys are talking about the democratization of the integration, especially when you have a bunch of cloud based applications that everybody has access to and maybe, needs to stitch together a different way. But when you look at this whole concept of democratization of that power, how do you see that kind of playing out over the next several years? >> Yeah, that's a very big- >> Sorry I didn't bring you a couple of beer before I brought that up. >> Oh no, I got you covered. So it's a very big, interesting question because I think that you know, first of all, it's one of these, god knows, we can't predict with a lot of accuracy how exactly that's going to look because we're sort of juxtaposing two things. One is, part of the initial move to the cloud was the failure to properly democratize data inside the enterprise, for whatever reason, and we didn't do it. Now we have the computer resources and the central, kind of web based access to everything. Great. Now we have Cambridge Analytica and like, Facebook and people really thinking about data privacy and the fact that we want ubiquitous safe access. I think we know how to make things ubiquitous. The question is, do we know how to make it safe and fair so that the right people are using the right data and the right way? It's a little bit like, you know, there's all these cautionary tales out there like, beware of AI and robotics and everything and nobody really thinks about the danger of the data that's there. It's a much more immediate problem and yet it's sort of like the silent killer until some scandal comes up. We start thinking about these different ways we can tackle it. Obviously there's great solutions for tokenization and encryption and everything at the data level but even if you have the access to it, the question is, how do you control that wildfire that could happen as soon as the horse leaves the barn. Maybe not in it's current form, but when you look at things like Blockchain, there's been a lot of predictions about how Blockchain can be used around like, data. I think that this privacy and this curation and tracking of who has the data, who has access to it and can we control it, I think you are looking at even more like, centralized and guarded access to this private data. >> Great, interesting times. >> Yeah, yeah Jeff, for sure. >> Alright James, well thanks for taking a couple of minutes with us. I really enjoyed the conversation. >> Yeah, it's always great. Thanks for having me Jeff. >> It's James on Jeff and you're watching theCUBE We're at the Snaplogic headquarters in San Mateo, California and thanks for watching. (electronic music)

>> Announcer: From the Computer Museum in Mountain View, California, it's theCube, covering ACG Silicon Valley GROW! Awards, brought to you by ACG Silicon Valley. >> Hey, welcome back everybody. Jeff Frick here with theCube. We're at the ACG SV 14th Annual GROW! Awards. It's their big annual event, about 300 people here at the Computer History Museum in Mountain View. We're excited to have one of the board members join us. She's Anita Ganti, SVP and Global Head of Product Engineering Services, for Wipro, and a board member, welcome. >> Thank you, thank you for having me here. >> So how long have you been involved in this organization? >> Not very long. It's just a little over a year. >> All right, and what attracted you to it? >> I actually got introduced by a friend. She connected me to the board of ACG, and I could see what the organization was doing in terms of bringing more growth, more energy here in the Silicon Valley, not that we don't have enough already, but I'm very passionate about it, and so I was really glad to be introduced and brought into the fold, so to speak. >> All right, good. So I'm going to set you up, I did a little research before we have you on, famous Jeffrey Hammerbacher quote, you probably know what I'm going to say, "The best minds of my generation are thinking about "how to make people click on ads, and it sucks." You're all about using tech for good, that's what you're passionate about. Not just using it to get people to click ads, but really doing some meaningful work around meaningful things. What are some of your favorite projects you're working on? >> I'll just clarify, right? It's that clicking on ads is a bad thing. I mean, people do need to buy, we need to get commerce going and all that. But with all the technology that we have access to, it seems such a shame that we are not paying attention to real world problems, larger world problems. I think global warming is something that's real. I'm in the camp that believes that it's very real. And there's a lot of harm that some aspects of technology have cost our planet. It's important to really look at not just the First World problems those of us here in the Silicon Valley see every day, but really open our eyes to what's happening in other parts of the globe. The need for water, clean water, water filtration, clean air, combating some of the changes that have been created as a consequence of global warming, having access to information, education. So these are some things that are really personally dear to me. >> Right, right. So we've done some stuff with the Western Digital. I know SAP is part of this work with the United Nations for some of their really big, global goals that they're addressing. A lot of them you talked about. Simple things: water, access to information, better food production. There's so much inefficiency in Ag that we see that people are applying technology to. So there is a real opportunity and we are seeing, I think, some movements into that area. >> Absolutely. And it doesn't always have to be done by the corporate arm that's focused on social issues. We can do that as engineers who are working just in our day-to-day lives. We could be looking for ways in which we apply things like IOT, Internet of Things, to providing services as a service to enable smart cities. Really look for avenues in which we look at technologies that are available to us every day and then just like people invest in social causes without really looking at it as philanthropy, look for for-profit avenues, avenues to enable technology but then keeping the impact to our planet in mind. >> You guys deal with a ton of customers, right? You're out on the leading edge, you're helping people implement technology. So are you seeing people add that in, as kind of a, you think of a public works project or a building project, there's always some carve out for art or other things to keep cities beautiful. Is there similar type of thing you're seeing for social good in some of these projects where there's some carve out, some allocation, to make sure that that base is being covered? >> No, what I want to say is you don't have to think of it as a carve out. You can make that as a part of your mission in what you do. So here in the Silicon Valley we are creating so much technology and all that technology has multiple applications. It's like both sides of the coin. And if we are making technology available for artificial intelligence machine learning, we're creating technology to do things like block chain authentication, distributed ledger, it's just about opening our minds a little bit and then taking those products, taking that technology to other markets. There are in many ways the technology-haves and the technology-have-nots. >> Absolutely. >> A lot of it is not just about making the product but then taking the product you made and then implementing it in various use cases that really make a change come about in the world. So that's something that I'm very passionate about. >> All right, Anita, well thank you for taking a few minutes to stop by and give us the update. And really excited for doing tech for good because we hear so much about the bad these days. So thanks for your time. >> Thank you. My pleasure. >> She's Anita Ganti. I'm Jeff Frick. You're watching theCube from the ACG SV Awards, Mountain View California. Thanks for watching.

(upbeat music) >> Narrator: Live from the Wynn Hotel in Las Vegas, it's theCUBE, covering Magento Imagine 2018. Brought to you by Magento. >> Welcome back to theCUBE's continuing coverage of Magento Imagine 2018 from Las Vegas. I'm Lisa Martin, joined by Anita Andrews, the director of analytical services at Magento. Anita, welcome to theCUBE. >> Hi, Lisa. How are you? (laughs) >> Very good, excited to be here. This is a really interesting topic, commerce. We talk a lot on theCUBE about digital transformation in so many different contexts. But really, it seems that commerce is becoming the center of gravity for digital transformation. Data is everywhere. There's so much opportunity for B to B organizations, B to C organizations, to leverage that data to drive new revenue streams, et cetera. Talk to us about what Magento is doing with respect to BI and how you're enabling your customers to use it to better their businesses. >> Yeah, so, I'm so glad that you sort of asked this question because we're doing a lot of conversations at this Imagine as opposed to previous ones around BI, around analytics, the role of data. And it's because I think we have a conversation and a story to tell around this. It's actually been long in the making. So, what we've learned after working with thousands of clients, from the basics of KPIs and reporting all the way up to machine learning, is that the approach to how do you launch this aspect of the business, really, that powers the entire business, is so important. Because otherwise, you end up with a crazy Christmas tree of solutions and no one really is moving the KPIs of the business forward using data. So, what we are doing is, we've created an infrastructure that allows all kinds of data. Whatever data that you have. It could be in a spreadsheet or it could be an automated feed. To come together into the platform to cleanse it, because everybody has dirty data, cleanse it, sort of model it for your use, and then be able to leverage it for, of course, KPIs reporting, but also run advanced data science on it, and then use that to power the commerce. And not just cross-sales and up-sales on the website, that's a story everybody wants to do and many aren't even doing yet, but also for things like email marketing, for online advertising, for vendor management, for inventory management. I mean, there's so many use cases. So, it's really about bringing the data together into a single place and then using that all throughout the organization. >> So, this is the eighth Magento Imagine. >> Anita: It's my first! (laughs) >> Mine too, ours too, at theCUBE! But you were saying that this is, the topic of business intelligence, is relatively new. Tell us, the role of data, you mentioned a number of use cases and multiple lines of business in an organization that can benefit from this. Why is this something that you think now is becoming so critical when 'big data' as a term has been around for quite some time? >> For a long time, and data has been around for a long term, right, everybody has spreadsheets from years back. I don't think it's that the role of data is becoming more important, per se, but I think that a lot of businesses have tried a lot of things and had sort of spotty successes, so online marketing is a lot better now with data. Right, I mean, absolutely. But this notion that there's these silos across the organization and the whole, I'm sure you guys have talked about this either today or yesterday, the whole customer-centric view that is becoming so vital to the business >> It's essential. online, offline, multi-channel. Well, the only way you do that is if you don't have silos. Right, and so this question of how do we bring all of this together and create the customer-centric view, and, by the way, you know, apply AI to many aspects of the customer experience, it can only happen if we sort of elevate the usage, the consolidation, all of that, and so I think that's a bigger problem. It's easy to kind of have a team work with data on its own. It's much more, it requires a lot more thought to kind of bring it all together and also get going, right? This isn't a a four-year plan to get there. You need to get going soon. >> Exactly, or you risk falling behind and not being able to catch up. So, let's talk about this modern stack. >> Anita: Yeah. >> This modern technology stack to capitalize on the e-commerce opportunities. Give us an example of a B to B organization, what they have existing when Magento comes and how they're able to use your technology across that spectrum of BI. >> Sure, so, most B to B organizations have data. Let's list some common sources of that data, right. So, first of all, they're going to have, most likely, Salesforce or some other sort of CRM database. They're going to have some sort of vendor database, right, either using a third-party tool or something they've home-grown. So often, something they've home-grown. They certainly have online marketing data, they've got transactional data, all of these different things that need to come together. So, in that way, they can leverage the MBI product, Magento Business Intelligence, to bring those data sources in together. Also, they can bring in their spreadsheets or whatever. But you use MBI to bring it together and then there's a level within that stack, the transformation layer, that allows you to sort of edit that data, right. I mean, back to the point of dirty data, edit it so that it's clean. So, you know that, well, in March we were wrongly charging shipping or something like that. Whatever the issues were, cleansing. And then start to report on that within MBI and create whatever sort of analytics you need to. But then you can also incorporate machine learning algorithms to start doing things like predictive analytics. So, start doing this vendor management, et cetera and then use that to, actually, MBI comes with some pre-built B to B dashboards, which is a thing that we just launched in the past year, which is also proving very useful. I mean, businesses have never seen this sort of total view of their customers, their data. And then you take, sort of, some of the learning and some of the information that's in the MBI and then use that to configure personalization Magento 2 commerce or, again, some of these other channels which might be email marketing, which might be, you know, call center scripting. I mean, whatever it is, that's kind of how it comes together. The MBI stack powering Magento 2, whether it's cloud or enterprise, and then other third-party tools that make sense to the customer as well. >> So, the customer has an existing POS system or an ERP system or a web store. Is it a simple integration process? How do they go about integrating that with, especially with, an accent group is coming on later today that has a hundred thousand skews and three thousand products. >> Yeah, so, the aim and the aspiration of MBI is to be able to take any data source, right. So, there's a bunch of data sources for which we have automated integrations. Literally, you put in your credentials and it starts flowing right away. Another option is that you have an API that you can use to import data in, so, if you've got the resources to leverage that, that's an option. Sometimes, if we don't have an automated integration, a lot of third-party data sources now will allow you to put them in a MySQL database or something like that. You can just just connect that directly to MBI, as well. And finally, we're very much looking at, from a product standpoint, how do we leverage the incredible community we have around Magento to develop more integrations, right. Because we cannot keep pace with the thousands and thousands of data sources that are launching every day. So, this community can and they are so close to what customers need to be able to bring in from a data perspective, so, we're also exploring that possibility as well, which would completely change the game. >> Yeah, you've got a very active developer community of, what, three hundred thousand developers? >> Yeah, it's something phenomenal like that. >> Lisa: That is phenomenal. >> Yes. >> When we look at the spectrum of analytics and we get towards the, whichever end it is, the right side, the left side, looking at advanced analytics. >> Anita: Yes. >> Artificial intelligence, for example, can you give us an example of a Magento customer that's being able to utilize artificial intelligence to drive new revenue streams or reduce attrition. Anything that comes to mind that's a really strong hallmark of your capabilities? >> Yeah, so, one of the ones that I love the most is around inventory management. And that applies to B to B and B to C, right. So, one of the things that we're starting to see a lot of traction and results around is advanced analytics and machine learning that's predicting how much inventory you have. So, inventory is money. You don't have enough, you're going to lose your customers. If you have too much, that's dollars sitting on the shelf, right, or accounts payable to your vendors, I mean, whatever it is. So, it is so, traditionally, it's been very hard to predict what you're going to need and when you're going to need it. So, there is now capability within MBI that you can feed into your vendor management or other sorts of merchandising management systems wherein you can sort of say, if you have a two week lead time to be able to get new inventory, then it can predict which of your skews, which of your products, are going to be running out before that two weeks end. And what we've seen with customers that are leveraging that is incredible increase in customer satisfaction rates because that sort of mismatch of, I thought I was going to get this but no, I'm not getting this, is going down. But they're also able to not even have to say it's out of stock on the site, which is a such a disappointing factor. So, improvement in conversion rates and customer satisfaction rates and on the flip side, there's another aspect of that functionality that says, well, do you have more inventory than, let's say, you know, two months' worth? And that two months piece is configurable per business, because if you're an outdoor goods store, two months in March for winter stuff is too late, right? You need to get rid of that now. But at the start of winter, four months might be great. So, all of that is totally configurable to be customized to that business, who knows the particulars of their business so well. And so, what we're seeing there is the, sort of, cost of goods that are being sent into after-market channels or sale or discount channels, is going down dramatically. And that's just a great case that I love because it's applicable, like I said, to B to B and B to C. >> So, on a B to B front, we have a lot of businesses behind us here. >> Anita: Yeah. >> As consumers, we expect to be able to get whatever we want whenever we want. Amazon just announced a hundred million Amazon Prime subscribers >> That's a lot of people. And people will not buy something if it's not available on Amazon Prime. We just think, what? We have to wait a week? >> Must not be a thing. (laughs) >> Exactly, exactly. But also something that the gentleman that was on main stage this morning from Amazon said, that about half of what's purchased on Amazon isn't sold by Amazon. >> Anita: Yeah. >> So, in the consumer space, we have this bar set very, very high. As business buyers, business buyers are consumers in their daily lives, as well. >> Anita: Yeah. I wonder, what are some of the trends that you're seeing on the B to B side that are maybe spilling over or being influenced by the consumer side and how is Magento helping businesses to be able to create these seamless experiences for businesses to transact in a high-velocity, low-touch model? >> Yeah, that's a really good question. You and I were talking before we got started here about how the buyers in a B to B environment, they're not a corporation. They're individuals. They're humans that actually are bringing their B to C personal experiences and expectations into their workplace. I mean, they don't turn into another person, right. They're maybe harder for procurement, you know, channels and all of that, but they're bringing the same expectations into it. So, frankly, you know, while Magento has sort of a B to B focused technology commerce platform, as well, that we've launched and is growing, as does MBI, you know, that will be a growing aspect, a particularization of the Magento platform. On the flip side, what we're also doing is saying they're not different and we're setting high standards for our B to B customers to say, it may be more challenging for you to act like a B to C customer, but that doesn't mean you get to, it may be hard for you to act like a B to C business, but that doesn't mean you get to not act like one, right, because the expectations are there. So, things like, whether it's as simple as what is order management, right, what is order tracking, what are ship and delivery timelines look like? Do I have various payment mechanisms, right? Consumers expect that, right, and those are often geographically dictated. Well, in the business environment, there may be other sort of procurement things to be thoughtful of. So, the conversation we're having, whether it's from a services standpoint or from a technology and product standpoint is have the same standards. And that is, frankly, in the conversations that I have day to day, I get a lot of but buts. You know, but, that's hard for us. Yeah, but so? Right, so let's figure this out. And, of course, you have to prioritize and all of that, you're not going to sort of turn from one end to the other overnight, but really, the message that we are seeing successful B to B customers hear and act upon is meet those consumer expectations and you'll knock it out of the park. >> Lisa: And who doesn't want to do that? >> Right. >> So, let's kind of turn the tides here. Let's look at Magento and how you're using your own technologies. How are you using analytics across that spectrum to really change the entire model? For example, you know, we talked about before we went on, as well, marketing. I'm a marketer. Marketing is a science now because marketers and every line of business has the ability to leverage data to drive many new opportunities. Talk to us about, internally, how you guys are using this spectrum of analytics >> Yeah. to continue to expand in B to B and B to C. >> Yeah, so, I'm going to give you a couple of different use cases, but this will be interesting because we're sort of opening up the kimono here about what goes on, you know, in our offices. So, yesterday, I actually heard our head of development, Ramadass, talk about a use case for using Magento BI within his organization. All of his different many development teams were tracking their tickets and numbers and all of that in various different ways and he sort of came in and said, well, this isn't going to work. I can't measure my organization. And he decided to deploy Magento BI across the whole thing. That wasn't easy, he said it wasn't smooth, but he started with one group who sort of took to it, and then once the benefit started to be seen, started to deploy across all the organization and he said, you know, he had the foresight and patience to stick with it and now he's got, you know, consistent view of what's going on there in the organization. Another angle that we use it from is, for example, with Mangento BI, there's certainly, it's different than implementing Magento Commerce, where, well, maybe it's not that different, but one aspect that I think is different is you do a lot of work to launch Magento Commerce and then, yes, you can expand your use a bit. MBI is pretty quick to get going, but how much you're using it throughout your organization or even within the product takes time. So, we've leveraged our predictive analytics to understand, to track those customer behaviors, and understand, well, when might be a good time to talk to them about, you know, machine learning? When might be a good time to talk to them about, you know, inventory management, whatever those topics are. But we're looking at those customer attributes, how far along are they in MBI, to run our online marketing campaigns, but even our personal marketing campaigns. We're not so big that we can't call up in our own customer success experiences and say, we think you're in a good place where you might want to think about doing this, as well. And then a third place is around customer support, so, a couple years ago, we used the product to figure out how much time were we spending on our customers, right? And there's a notion of a rate per hour. Are we allocating our time properly? It's very easy for the squeaky wheel to get the most attention. Is that the right thing for the business? So, these are the ways that we've used it internally. We're B to B, right? (laughs) >> Right! Would it be fair to say that you're democratizing data within Magento? >> Yes, everybody, I can at least speak to it on the MBI side and I know this is true in development, et cetera, everybody has access to the data. And that's kind of where, watching, you know, an individual contributor take that and run with it and sometimes it's a little bit too eager for me, and then I have to kind of dial it back, and we can't make all those changes today, but it is so impressive to see what they think about asking, what questions they think about asking of the business and that they feel like will solve an actual problem. >> So, kind of allowing innovation. Well, Anita, thank you so much for taking some time >> Yeah, thank you. to stop by theCUBE. We wish you the best of luck in your general session presentation this afternoon and we look forward to hearing from some of your customers and some of your leaders on the program later today. >> Great, thank you, Lisa. >> We want to thank you for watching theCUBE. We are live in Las Vegas at Magento Imagine 2018. Stick around, I'm Lisa Martin. We'll be back with our next guest after a short break. (upbeat music)

>> Narrator: Live from the Wynn Hotel in Las Vegas, it's the CUBE, covering Magento Imagine 2018, brought to you by Magento. (upbeat music) >> Hey, welcome to the CUBE, we are live in Las Vegas at the Wynn for Magento Imagine 2018. I'm Lisa Martin with my co-host John Furrier, and John, we have a really exciting day planned, talking all things digital commerce innovation. What are you most excited about? >> Well Magento's one of those companies that people know about, but it's the rocket ship in eCommerce, mainly because they've cracked the code on a few things, Lisa, that I'm really impressed with. One is, they've modernized eCommerce. ECommerce has been around 25 plus years on the web, with internet, but you think of it like the old Amazon, eBay, database world, but now we're living in a cloud world, cloud native's big, and there's still money to be made in retail as everything goes online. The digital transformation is impacting retail more than ever, smart phones is over 10 years old, so the question I've always asked is, where's the modern stack? So these guys have cracked the code on that. Two, and they're powering a lot of impressive sites, and the growth is phenomenal, but they have an ecosystem partner network that you can see behind us, if you can look at the camera you'll see hundreds of partners. So I mean, eCommerce obviously isn't going away, look at the growth of digital, digital natives are coming online, people want to do things digitally, but also it's changing the offline consumer experience. So there's a gap, traditionally, between online, offline, that's coming together. This is only going to get more acute as cloud, mobile, decentralized, block chain, there's still eCommerce in our future, and it's just never going away, and these guys have a really interesting approach, so we're excited to find out more here on what they're doing, their success, and how eCommerce is going to evolve. To me, that's the number one story is, can people leverage turnkey, scalable digital technologies to do business? >> So Magento has built their reputation on helping retailers to target online shoppers. You talked about online and offline, but they're now moving into the B2B space. As consumers, we expect, Amazon set the bar obviously very high, we expect to be able to get whatever we want as consumers, we're channel agnostic, we don't care, we just want to be able to find whatever we want when we want it, have it shipped to us, have it shipped to the store, and that is spilling over into the B2B space. And Magento's data suggests that 93% of B2B buyers want to be able to buy online, which not only changes the sales model, it changes the marketing model as well. >> I mean, they're taking the charge, that's the slogan here, and the thing that's interesting is that it used to be nice little buckets, B2C, business to consumer, B2B, business to business, but really it's a consumer to consumer role, and one of the things that you see right now social media is consumers are directly involved in either the content development process, or the engagement process. And if you look at no further than the side effects of what we see with Facebook, the downside of this whole data conversation is that the users want to be in control, and they are in control. So you're seeing almost a blurring of the lines between B2B, B2B, and C2C, where people need to tailor the eCommerce experience and have the data insights, either realtime, and or intelligent wise to know that the consumer is participating offline, they're online, but also peer to peer. The consumer to consumer relationship is to me going to be the cutting edge forward innovation area that a lot of these companies are going to innovate on because a lot of referrals are going on organically now as it's not so much audience anymore, because the audience is online digitally, it's about the network connection. So as people have a network connection with their friends, and you're seeing Facebook proving this, and LinkedIn, and others, is that you're going to start to see that data be very important. So I see a future where eCommerce stacks have to support consumer to consumer in any context, business to business, B2C, business to consumer, consumer to consumer, this is the holy grail, and whoever can scale that, again at large scale, while creating a money making opportunity, value creation opportunity for ecosystems is the winning formula. >> One of the themes that popped up during the keynote this morning with a number of folks that were on stage, including their CEO, and the Pittsburgh Steelers, was personalization. That's something that we expect as consumers, and as well as business buyers, we want to be able to have something where we know they know us, but we don't want to be marketed to. So Magento has done an interesting job and we're going to have a number of guests on the show today talking about how they're enabling this more personalized customized, you mentioned the word tailored, experience as a consumer to be able to get what I want when I want it, but also, through a now omnichannel. We're going to hear a lot about omnichannel today and how that's enabling new revenue streams, reduction in attrition, they talked about one of their newest features, Magento did, with the instant purchase. We want to be able to click once, buy it, and have it, something that means something to us, be able to buy it again, and again, and again. >> I mean this is the challenge right, in eCommerce, is table stakes are some of these features like instant click buying, having the kind of personalization, but the real angle to me is bringing in the personalization so that the consumer's involved. So what you see with the Steelers for instance, they do realtime shooting of the game and incorporate the fan experience into the eCommerce experience really seamlessly and in realtime, and so what you have is a change of a methodology. And so, eCommerce used to be a very one directional monologue, you'd put content out there, people browse and consume. Now you have a realtime interactivity piece, which changes the content production perspective, and the Steelers pointed that out. In the tech world, we used to call this agile programming, when you write software development. So you start to see the concept of agile come into eCommerce where, whether it's an entrepreneur, Melissa, baking goods, or a business, they want to focus on the business at hand, not provisioning technology. So you've got to have a partner like a Magento or someone who can build all that tech turnkey so that people can focus on the business at hand and that's agile. So if they decide to incorporate something really fast, you can't have this waterfall process, and that's the problem with the content market, and that is a legacy baggage of eCommerce, where hey, we built it, we ship it, but we got to go back and decide what to change, and we got to push it through the code base. You're provisioning technology, that is an old way of doing things, that's not ideal for the modern era. You need to be very agile, very scrum like, to use that term, and content people need that to be successful because the difference between realtime and having that right experience is a matter of seconds and or context specifics. So agile content, can't be waterfall. >> Exactly, agile content that's data driven. You mentioned data earlier, we're going to actually be talking with Anita Andrews, who's going to be talking about what Magento can facilitate and deliver their users with respect to BI, the Steelers talked about that, they actually see when the Steelers aren't doing well, they see a reduction in merchandise, merch that's actually purchased on site. So they have the data to be able to make the decisions to deliver this personalized content in a way that they can see, how can we adjust our sales structure to be able to capitalize on revenue opportunities. >> I mean responding to data is really critical, so the Steelers example is great. When they lose, there's no sales, 'cause everyone's kind of bummed out. When they win, they sell everything out. So you know, in sports world, which is that big part of Magento's base, managing the assets of running the franchise, for instance, becomes a real big thing. Whether it's food, or apparel, or any kind of fan experience, they can adjust either dynamic pricing, these are the things that the content owners want. They want to be able to say, hey, we can understand sentiment from the data, and then adjust the marketing mix and content mix based on what's going on in realtime. That's a game changer, and if you can do that on a form factor for web, mobility, and future formats, whether it's cryptocurrency, that is going to be to me the tell sign of who's innovating. >> And speaking of innovation, this is the eighth event that Magento, the eighth Imagine event, our first time here, but you mentioned their partner ecosystem, there's 1150 solutions and technology partners you can see quite a few of them behind us here, a lot of people are needing this type of technology to be able to better merge the online and offline worlds, across consumers, across businesses. We have some great guests here who are going to talk to us about how they're doing that, enabling multi-retail, enabling multi-channel, and really enabling this true globalization of commerce to allow businesses to go, we actually have a guy from Coca Cola who's going to be on today, talking about the project that they are, where they're personalizing the Coke bottles, it's such an interesting topic of discussion because it's very personal and very relatable, and I think. >> Marketing's always, market to the persona of one, but now you have a brand relationship that's online and offline, and this is changing how companies are building their assets. So an offline retail outlet, whether it's a mall or a superstore, or whatever, that can be configured in a way that's complementary to the online, and then having the merging of the data, and then having that relationship with the consumer. To me, omnichannel is a huge retail challenge, it's super important, because at the end of the day, do you want to have that insight into the customer, but also have the great experience, that's key. >> Exactly, so we're going to be talking with the Accent Group, who's an award nominee for their awards here, and they're going to be talking about how they are merging multiple brands, hundreds of thousands of SKUs to be able to facilitate, and also give them the insight that retailers need on inventory, giving them fulfillment options, there's so much positive business outcomes that can be generated from this. We talked about reducing attrition, getting us faster check outs, we want to have something that's very simple, very seamless, and as you pointed out, really interesting to understand, what is the modern technology stack that can facilitate that? >> Yeah, great user experience, retail intelligence is something I think that's going to be something that's fascinating, and again, it's all about scale and the technology stack, and taking that complexity away from the customer, because at the end of the day, the digital storefront is what people are going to be interfacing with on a primary basis, that's also very complementary to the offline. So I'm super excited, I'm totally pumped to get into it. >> Me too, well looking forward to hosting with you all day John, and again, we are live in Las Vegas at the Wynn at Magento Imagine 2018. I'm Lisa Martin with John Furrier, we're going to be here all day, stick around. We're going to be right back with our next guest. (upbeat music)

(intense music) >> Hi and welcome to theCUBE, I'm Lisa Martin coming to you from our Palo Alto studio. Very excited to be joined by a CUBE alumni, the CEO and president of Anita Borg, Brenda Darden Wilkerson. Welcome back to theCUBE, Brenda. >> Thanks so much for having me. >> It's great to have you here. You have been at Anita Borg for about six months. You've got a great background in the tech industry and in education. Give us some perspective of what's happening, what's new with Anita Borg? >> Well, we are very excited to be in this space at this point in history. It's very exciting. Women are alive to the possibilities of what they can contribute in tech. We can thank so many important women who are contributing to the conversation, and it is our job to make sure that they have a voice. And so we are working really hard to make sure that the perceptions that would create barriers for women contributing to tech, having a career path, taking those really important positions of power in tech, that we obliterate them and that the flood gates are open for all who want to participate. >> I love that on the website I saw the what we do, one of the things that shattering perceptions. And I thought that word shattering, that description, was really, really important. >> It is very important because you would think in 2018 that these issues that our founder, Anita Borg, talked about years and years ago, I mean she was a visionary, when she said 50/50 by 2020. And actually we are coming back from the cliff that we fell off of in terms of being our percentages in tech. We're at about 22% now, and a lot of that has to do with those perceptions. What are the images that young women see? Or people in power in tech. What are those images that continue to contribute to those barriers, and that's first and foremost the thing that we're working to change. >> When you were on theCUBE at Grace Hopper 2017, just six months or so ago, one of the things that you said that I really love was people can be what they can see. So having awareness and showing females in technology and leadership positions, showing people this power of representation is critical. >> Very much, very much so. And really all we're talking about is telling the truth. You know? It's not as though the women haven't always been there. It's not as though they aren't making huge contributions, it's just making sure that when they do the work they get the credit for it and that people get to see it. I've seen it be very important in my previous work in driving computer science. All of the stakeholders needed to understand that underrepresented people of all kinds could do tech, and they were very much impacted by the images that they saw. And so it's our job to make sure that all of those stories get told. >> So you spent 15 years in education, and you had many years before that in tech. You made a massive impact with the Computer Science For All initiative that you founded back in 2013 in Chicago. Tell us a little bit about that because it's really exploded and I'm sure really kind of exceeded your expectations. Tell us about that initiative and where it is currently today. >> I'm very excited about the initiative. I mean, really it was born out of some of my own experiences. I was a person who, in my background, I wasn't exposed to computer science until I found it accidentally in college. I mean, obviously that accident changed my whole trajectory, right? So when I found out that that was still happening to women and underrepresented students when I got into education, that was sort of the genesis of wanting to do something about it. That was when we launched Computer Science For All. And yes, now it is a national initiative. In Chicago we have a graduation requirement. Students all have to graduate with at least one year of computer science, and we're seeing that transformation. I've got students who we started with in the beginning who are graduating this year from universities with computer science, data science, information science degrees, and they are doing amazing things. They're starting companies, they're developing products, all because they had that exposure. And so it's exciting now to be on the other side, really kind of coming home full circle, back to advocate for women in tech, as I started out. To make sure that those hundreds of thousands, millions of students have access to the opportunities that we need them to have access to. >> Right, that access is such a critical thing. And you kind of think in some respects, as we were talking about earlier, you've made a massive impact in Chicago, New York City, the Obama administration got behind this. Well, you started out with a goal of reaching four hundred thousand kids in Chicago, there's now over 1.5 million. But it starts with that awareness, that this shouldn't be an elective. But kids need access to understand I can be what I can see. If I can't see it, I don't know that it's an opportunity. >> And if I don't know, if I can't touch it and know that I have access to being the creator of technology, changing the world as we know technology alone can do, then we're going to miss out on the contributions that only they can make, and so that's what makes this so exciting. When we started out, I'm thinking of the kindergartners that started that first year. They're in fourth grade now, right? What is the world going to look like when they graduate from high school? It's just going to be amazing, I can't wait. >> Yeah, we were just covering Women In Data Science a couple of weeks ago, I was mentioning to you before, and I love that event because you walk into where the main event at Stanford is held, and you just instantly feel positivity, excitement of this movement. And there's so much opportunity within data science alone, and one of the things I wanted to talk with you about is we heard a lot of people that were guests that day talk about the creative element. And we often think of the hard skills that computer scientists and data science need to have, but you found CS accidentally as you said, and one of the things that I've heard you say is the opportunity to be creative. Tell us a little bit more about what, how people, young girls can get creative and expressive creativity through computer science. >> Well, that's very important. We found that we could attract more girls into computer science when we told them that they could use these skills and this knowledge to solve problems that they cared about. You know, initially because it was such a, thought to be such a male-oriented subject, it was all about computer games and the kill games, and the girls were like, I'm not interested in that, but I want to do things that are impactful to the world, to change my society, to change my community, and you can do that with technology, and you can create something out of your own ideas from scratch, from concept, and I can see the lights go on for them, wait, I can create an app that helps my friends through a particularly difficult time with bullies. Yes, you can do that. And so, that is the exciting explosion that's about to happen. People who are really using these skills to solve problems for the human good, that's what we're going to see an increase of, because that's what many times the women bring. So Grace Hopper 2018 is coming up, what in September? >> It's September 26th through 28th this year, and it's in Houston, we're returning to Houston. We're actually even going to use the Toyota Center for our keynotes. >> And you're expecting 20 thousand people this year? >> That's right, we had 18 thousand last year, we're inviting 20 thousand this year. We're going to have over 17 tracks. Last year we had 405 concurrent sessions. The whole point is to give women an idea of how they can transform their lives, coming into technology at whatever stage they found themselves in, whether they are just seekers and are interested in learning about technology, or if they are middle career and going to that next stage or the executive level, we have something for all of them. >> So, and you give out awards, the Abie awards, at Grace Hopper. Give us a little bit of an idea of the types of categories in which women are awarded. >> So we award the top innovator, we award top educator, so wherever women find themselves, we want to bring attention to the fact that we need participation not in just what we think as the high-tech sector, but all along the pathway. People who are bringing attention to issues using technology in their community. We award all of those, people who participate in creating more of a well-rounded experience for all of us to understand what technology can do for our lives. >> And it's really everywhere, right? And that's one of the thing that I think is personally really intriguing about technology is every company now has to be a tech company. >> That's right, every company is a tech company, right? And so that's another thing that we want to make sure that people are not just thinking, oh if I'm going to get in tech I can just work for these five or 10 high-tech companies. Tech is everywhere, it's across the country, it's around the world, it's right where women are living and having their existence. And we need their contribution in those places. >> Yeah, another thing about WIDS and women, we were talking about data science that I found interesting, was some of these female leaders talking about the hard skills, the data analysis, the interpretation, but also needing to have more diversity in the analysis to remove, we all kind of come with biases, but to start having more female perspectives to really kind of open up the analyses and remove some of the biases, which was kind of something, to be honest, I've been in tech for a long time, I hadn't really thought about before. >> Yeah, and it's really shocking just how impactful some of those biases are in the data on people's everyday lives. We've heard things everywhere from as serious as different sentencing levels for people based upon the algorithms that are there, to how much things can cost more for important things like insurance, based upon the data that's there. I think the New York Times did a piece a couple weeks ago about face recognition software and those images that are in those databases. And so it's so important that we have diverse faces at the table, as a black woman, my face is likely to be misunderstood 37% of the time. Right? So to be able to have the diverse background there that will check for those images to make sure that they are more representative of the whole population is just going to make all of our lives better. >> So at Grace Hopper your audience is made up of girls maybe interested in STEM, women that you said are in many stages of their careers, on the corporate side, one of the things I read recently is that article that you wrote in Mashable called Voices of Women in Tech collaboration with Anita Borg where you talked about corporate activism, and there's some pretty significant benefits that companies can achieve by speaking out. Tell us a little bit more about that. >> Well, you know, we have a much more engaged and active population, especially the millennials, and they care what their companies care about and how they contribute or don't contribute to the causes that they care about. And so one of the most expensive things that a company will ever experience is their ability to retain great talent. And what we've seen is that millennials will decide to stay or leave based upon some of the things that companies contribute to or don't contribute to, so being able to pay attention and to get into the game of other things that are outside just the product that they produce, actually contributed to company's bottom line. >> That's pretty interesting. >> It's very interesting and very important, and knowing that is something that they can immediately put in place that impacts the success of their company. >> Absolutely, and some of the things, too, that I've heard on various CUBE shows that we've done is the millennials perspective on the gender gap. And often they'll go, I don't know why you guys are still talking about this. And we think, we don't either, but we are, and it's refreshing to hear that this next generation thinks that that is just something that is just kind of ridiculous that we're still talking about, and also how important seeing a leader, a CEO being involved in something important, is to retention, so I think that's a great message that Anita Borg can help get out there and show businesses this huge impact and benefit to you and fostering your own talent. >> Yeah, you know, and it's encouraging, as you say, the millennials are jumping in, and many more people are jumping in and giving this perspective to companies, which is actually assisting them, right? So now they don't have to feel like, okay, this is just my idea, I'm going to take a risk and jump out. They've got people who are loyal to their organization saying, I believe in this and I believe in you, let's do this together, and so definitely our job is to make sure that companies have access to all the information they need to make these, what shouldn't be hard decisions, but we're there to help them. So the 50/50 idea, you have said that, and you mentioned that earlier, that you want to see 50/50 representation of females in the next 10 years. Tell us a little bit more about kind of what's coming out the rest of 2018 from Anita Borg, and how you guys are working to help make that, help get those numbers up from where they are currently. >> So it's all about awareness, and there's a lot of awareness out there, but what we want to do is increase it. You mentioned the idea of people can't be what they can't see. Images are so powerful, and so we want to work with media outlets, we want to work with entertainment companies with writers, with producers, and say help us create the images that can turn around and tell the truth, really. I mean we're not creating a fiction. Let's just tell the truth and allow people to understand that yes, this is how this works, and let's couple that with the data that shows that the bottom lines of companies that have more diverse workforces, that have more diverse boards, are muchly improved over those that are nondiverse. And so, we are creating that awareness, we are helping our companies find out what we call, not only best practices, but many times it's better practices. We're still working towards that best practice of here's how you can make incremental steps forward. Excuse me, you mentioned 10 years, I'm a little more urgent than that. I feel like the things that we get done are the things that we're most urgent about. One of the issues about why we're still dealing with these things, it's just been sort of like let's work on it in the sweet by and by. I want to say, let's work on it in the next two years, in the next three years. Let's make some goals, let's put some metrics behind them, and those were some of the things that we help companies do. >> I love that urgency. I think it's essential, but the awareness and kind of this idea that you have of, let's just tell the truth. There's really nothing more powerful than that. But also, the imagery and the representation is critical for that. If you look back at all of your success and think back to younger Brenda, what advice would you give somebody that looks at you and goes, wow. Where do I start? What's that recommendation for shattering someone's own maybe perception of themselves in getting into technology? >> Right, I mean we have to start with the conversation that we have with ourselves, but you know, we're in this world now where there's so many great images. Find those images. You know, you can find successful women. There are so many of them. Talk to them, reach out to those of us, because we want you to succeed. We want you to participate and come on board. And so, we have a world with social media that allows people to have access to each other that we didn't have before. The most important thing is don't take no for an answer. Not only because it's just not true, but because we need you, and it is an amazing time right now where you have all these women who are standing up saying that they want change, and we're here to support them, and we're here to support you. >> Speaking of this kind of movement going on globally about we want change, with the Me Too movement, a bit of a different genesis, however, the awareness is starting to be there. You talked about needing the entertainment industry to get on board and really start ensuring that we're sharing the truth here. What opportunities do you see to deliver through Anita Borg that maybe you can leverage that's coming from the Me Too movement and all of Hollywood that's really starting to stand up and be very vocal about this? >> Well, you know, it's interesting because people ask me that question a lot, and from my own perspective, there's this awakening because those same sorts of things are happening in tech as well, we know. We've seen the stories. It's not as though we're looking aghast at what's happening to women across the way. So these things have been happening, and what is happening is people are starting to look internally to say, how can I strengthen myself and stand up like these women did? And so at AnitaB.org we are creating those opportunities for women to network, for them to get mentored. We have communities around the world where women can get together and understand what the pathway was of other women. It would have been really helpful for me to have sort of some of those breadcrumbs out in front of me, some of those examples and other people to talk to, but we provide that as part of what we do in our organization. We provide training opportunities, other experiences where people can see all across the tech ecosystem where they can come in. It's not just one way in, it's not just one pathway, and so that's going to be a really important thing to make sure that women know they have choices. >> And I think it's so important in general, but you mentioned some of the attendees at Grace Hopper are maybe women who are in transition who are maybe, had a career in something different for a while, and are now getting into tech. I'd love to maybe understand that a little bit more, maybe some of the demographics there, but how do you see, what are some of the inspirational stories maybe that you can see where a woman who was maybe mid-career or somewhere around there, just went, you know what, I am interested in this, maybe didn't have the confidence when she was younger. Any stories there that kind of jump out at you that are great examples of it's never too late? >> Absolutely, in fact that was some of my first inspiration in getting involved with taking my background in tech and sort of lighting the path for people to get in who had traditionally been shut out. My first educational experience was at a community college level. And many of those people were people who, like myself, had not been given that introductory experience of computer science in K-12 space. Maybe they went to work and did some other things, maybe they got talked out of it. You know, it's not for you. And they came back later saying, you know, maybe I could learn, maybe I could try, and so really opening up that pathway to them. I've seen people who have gone from either having no education or maybe having even a PhD in linguistics figuring out once again that creativity. How can I take that and apply that technologically to creating solutions that only I would care about or know about? And so we've seen people come from all different walks of life, different career paths, and start small. Some of them are self trained, some of them are bootcamp trained, some of them go back and get an additional education. What we do at AnitaB.org is, not only help them understand those multiple pathways, but we work with partner companies to say, you know, there are other ways for people to come in. We've got these, what, 500, 600 thousand empty positions. Why don't you take a look at some of the people who are in your industry already? If you're a bank and you've got a woman who's been working for you for 20 years, she knows your business inside out, she is loyal, she can learn the tech. So we're seeing those types of transitions take place as well. >> Fantastic, well Grace Hopper in Houston in September. Is there also Grace Hopper, there are forums in other countries? >> Yes, so we also have Grace Hopper India that takes place in November, right after the one we do here in the United States. We've also started to have one day Grace Hopper events, we call them Hopper by Once, and we are planning those out around the world. And so we're increasing, we're trying to increase people's opportunity to come and experience all of the wonderful things that are available at Grace Hopper. We hear so many wonderful things about how it's transformative in their lives to see that many women in one place, to have access to training and mentoring and networking opportunities, and we're just excited for what's to come. >> Well we're excited to see what happens in the next few months, and Brenda thanks so much for stopping by, sharing what's new with AnitaB.org, your vision for that, and the transformation that you're already helping to facilitate. >> Thank you for having me. >> Absolutely our pleasure. We want to thank you for watching theCUBE, I'm Lisa Martin, from our Palo Alto studios, thanks for watching. We'll see you next time. (intense music)

>> Welcome back everybody, Jeff Frick here with theCUBE. It's International Women's Day 2018. There's a ton of events happening all over the world. Check the social media stream, you'll be amazed. But we're excited to be here, downtown San Francisco, at the Accenture event. It's called Getting to Equal, 400 people, it's a packed house here at the Hotel Nikko, and we're really excited to have the authors of some really important research here as our next guests. This is Julie Sweet, the CEO of North America for Accenture. Good to see you, Julie. >> Great, thanks for having me today. >> And Ellyn Shook, the Chief Leadership and HR Officer at Accenture. Great to see you. >> Thank you, Jeff. >> All right. So Ellen, I want to start with you just cause I noticed your title, and I wrote it down, I've never seen, we do hundreds of events, thousands of interviews, I've never seen Chief Leadership and HR. Where did that title come from, and why is "Leadership" ahead of "HR"? That's a pretty significant statement. >> It is, it is, and Accenture's a talent-led business, and part of being a talent-led business is growing our people to grow our business, so leadership and leadership development is essential to our business. It's a core competency of ours, and that's why my title is Chief Leadership & Human Resources Officer. >> And Leadership before HR, meaning you really need people to get out in front. >> Yes. >> It's not about compliance, >> Yes, leaders at all levels. >> and this and that, leaders of all levels. >> Correct, correct. >> Okay, so let's talk about the research. >> Sure. >> It says, "When she rises, we all rise." I think it's pretty common, and everybody knows hopefully by this point, that diversity of opinion, diversity of teams, leads to better business outcomes. So what specifically is this piece of research, and give us a little background. >> Sure, the research, I think, is groundbreaking because never have I seen a piece of research that looks at the cultural aspects of an organization and really helps to articulate very transparently, what are the biggest accelerators in a culture for equality? And that's what the research is about. >> And you've identified, and is this an ongoing research, is this the first time it's been published, is it kind of an annual thing? >> Every year we publish a piece of research about gender equality, and this year we put a different lens on it to really look at equality for all. >> So you've identified 40 kind of key areas, but of those 40, really 14 are the big hitters. Is that accurate? >> That's correct. >> So what are some of those 14? >> Well, I would put them, we've put them in three categories. The first is bold leadership, so think about companies like Accenture who set targets and have CEOs who are very clear about their priorities. The second is comprehensive action, so think about policies and practices that are really effective. And then finally third, which I think is often under focused on, which is an empowering environment. What does it feel like to be at work every day? Do they ask you to dress a certain way? Is there flexible time for all? And it's the combination of these 14 factors that really makes a difference about creating a culture of equality where men and women advance. And what was really impressive is we saw that, in companies with these factors, women were five times more likely to advance to director or senior manager, and men were two times more likely. And so it really is about, when she rises, all rise, and that is probably one of the most exciting things about the research. >> It's really interesting, we just had Lisa on from The Modist, and you know, I would never have thought of clothing and dress as such a significant factor, but you've got that identified in that third bucket that you mentioned. And in fact, it's the number one attribute. So what are some of the other surprises that kind of came out of the research? >> Well, I think one of the surprises was that companies that, as part of comprehensive action, that implemented maternity leave only, it actually had a negative effect on women's advancement. But where companies implemented parental leave, so it was for men and women, it eliminated that negative bias. And it really goes to the importance that these policies, and actions, and the focus need to be about women and men. And when you start putting women too much in a category, like flex time is a mommy track, as opposed to flex time being something that men and women commonly do, it really changes how it feels to, does it feel inclusive every day at work? >> Right. >> Yeah, so companies really need to, I think what the research showed very strongly is that companies need to look at programs, policies, practices, and an environment that levels the playing field rather than isolating any particular gender or other form of diversity. >> But it's interesting, kind of law of unintended consequences, I think that panel that you were on earlier, one of the gentlemen said, since the not me, there's been reports of, >> Me too. >> for me too, excuse me, a lot of hashtags today. That there's been people doing, men scared of mentoring maybe that they weren't before. I don't know how true that is, but no it is kind of interesting to think, are there some kind of counter balances, as you said, if there's just maternity and not parental leave that need to be thought about? That probably people aren't thinking it through that far. >> Well and I think, one of the things as we saw in the research is that it's not about also one action, and so the way that companies really create a culture of equality is it's a combination of these factors. And you said something when we first started that I think is really important, and that was, you said, well it's really commonly known that diversity is important. And I think that people do need to understand that, we are optimistic about where we are today because, as a company, we're constantly in the c-suite. We serve in the U.S., 3/4 of the fortune 500, and as much as we're talking as a leader in digital disruption and artificial intelligence, the conversation quickly turns to people, to talent, to diversity, and so there's a real business lens that's on this, and that's the context in which we're operating. >> Right, and we can go to Grace Hooper, we do a ton of women's events as well as large conventions. And most people, I think, hopefully have figured it out, that it's not just about doing the right thing, it's about actually having better business outcomes. You get better outcomes with diversity of opinions, diversity of teams, you think about things that you just wouldn't think about. You don't have that same experience, everybody has a bias from where they come from, so you want to get some other people and have different points of view, different lenses to look at things. So it is really important. But why do you think things feel like they're changing now? What's important about, March 8th, 2018, versus say a year ago when you started doing some of this research? Is it the tipping point that it feels like, or? >> I think there's a couple of factors that are coming together right now. First of all, we're living in the digital age, and the digital age is all about innovation and innovation fast. And as you just said, you cannot innovate without diversity. Diversity is a form of, you're able to tap into creativity, and it's a source of competitive advantages for organizations in this age. But also what's happening in culture around the world, the me too movement as well as other things that are occurring for women around the world, and it's a moment in time where a movement can really start to happen. And I think, companies who look at culture as an accelerator of change are going to be the winners. >> Right, so what impacted bold leadership? We had from the Golden State Warriors on earlier and I think there's, what's great about sports teams is we all get to see them do their business. And we get to see the scoresheet at the end of the day, we don't necessarily get to see that in other companies. But really a fantastic example of new leadership coming in, made bold sweeping changes, probably a little bit of luck, which most success stories have, but you know significant top-down culture change. So how do you see cultures changing with bold leadership and old-line companies? Can the old guard flip? Do they need to bring in new blood? How are people executing bold leadership? >> Well first of all, I do think that it's not about old-line, it's not about young, it's really about leadership. And so it is very dependent on who is the CEO and what kind of a board we have, and so, we don't, both of us don't subscribe to the idea that you have to be born digital to be have a great culture >> To be digital. >> Yeah to be digital. And I would say that, one of the key things we saw in the study was around transparency of goals. And we talk a lot at Accenture about transparency creates trust. And so when you think about, how do you change a culture? Bold leadership is in part to find in the research by the willingness to set public goals, and to be transparent and that creates the trust. The trust of your employees, and the trust of the people you want to attract. And what I often will say that is, when we put out our statistics in the U.S, we're the first professional services firm, it wasn't that we had phenomenal statistics, but the fact that we were willing to put them out created trust that we were trying to change. And it helped people want to be a part of that change. >> Right. I mean you know that, you guys are in this business, if you can't measure it, you can't improve it. It's interesting, the Anita Borg organization puts out a self-assessment, we do their show, and Grace Hopper, to have companies. Again, not necessarily that they're going to score high but at least they recognize the problem, they're trying to measure it, they're trying to set a base line and make moves. We've heard that from Brian at Intel, Intel's making moves. And you guys have made a very definitive statement, write a line in the sand, at 2025, you're going to hit 50%. I believe that's the goal. >> Correct. And not only do we say that we're going to do it but we're doing something about it. And a lot of companies will say they want to achieve gender equality, but it's actually the actions that you take every single day. And then, of course, reporting on your progress, whether it's what you wanted to see or not, just the full transparency around the scorecard is important. >> Yeah, it's so critically important cause again, if you can't measure it, you can't change it. So great event here, as you look forward into 2018, I still can't believe we're a quarter of the way in to the year, it shocks me. (laughs) What are some of the priorities for 2018, if we sit down here again a year from now, where will you have moved on that measure, what are some of the things that are your top priorities around this initiative this year? >> Well I know for me, we certainly are trying to make sure that we continue to make progress, but I also think there's a growing conversation about the intersectionality of diversity, and so, it's women in color, it's race and the workforce, and so. We're a global company, but certainly in the U.S, which is part of the business I lead, we are not only focusing on gender, but the intersectionality of diversity and on race. >> Yeah and I think just broadening the conversation from gender diversity to true equality for all is really the big push for us here at Accenture now. And I think it's essential that no part of our organization or no individual gets left behind. And that's what we're really focused on. >> Well that's great, and so I want to thank you for having us, and wish you well in 2018, and really a fantastic event and super, super initiative. >> Come back in 2019 and we'll show you our progress. >> Alright. >> Exactly. >> She's Julie, she's Ellyn, and I'm Jeff, you're watching theCUBE from International Women's Day at the Accenture event in downtown San Francisco. Thanks for watching.