>>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.

>>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.

>>from >>around the >>globe. It's the Cube with digital coverage of pager duty. Summit 2020. Brought to you by pager duty. Hey, welcome back to Brady. Jeffrey here with the Cube in Palo Alto studios today. And we're talking about an upcoming event. It's one of our favorites. This will be the fourth year that we've been doing it. And it's pager duty summit. And we're excited to have from the pager duty team. She's Caroline Gus, the VP of corporate marketing from pager duty. Caroline, Great to see you. >>Hi, Jeff. Great to see you again. >>Absolutely. So, you know, I was thinking before we turn on the cameras we've been doing pager duty for I think this will be like, say, our fourth year that first year was in the cool, um, cruise ship terminal pier. I gotta written appear 27 which was which was nice. And then the last two years, you've been in the, you know, historic Westin ST Francis in downtown San Francisco, which is a cool old venue, but oh, my goodness. You guys were busting at the seams last year. So this year, year to go virtual. There's a whole bunch of new things that that you could do in virtual that you couldn't do in physical space. At least when you're busting out of the seems so First off, Welcome and >>talk a little >>bit about planning for virtual versus planning for a physical event from, you know, head of marketing perspective. >>Absolutely. I mean, the first thing that's changed for us is the number of people that can come. It's five x the number of people that were able to join us, the Western last year. So we have, uh, we we expect to have 10,000 people registered on attending age duty summit. The second thing is thea share number of sessions that we can put on. Last year, I think we had around 25 sessions. This year we have between 40 and 50 on again. That's because we're not constrained by space and physical meeting rooms, so it's being a really exciting process for us. We've built a fantastic agenda on. It's very much personalized, you know, developers come to our event. They love our event for the opportunity to learn mixed with their peers, get best practices and hands on experience. So we have many more of those types of sessions when we have done previously, and that things like labs and Bird of Feather Sessions and Emma's. But we've also built a whole new track of content this year for executives. Page Julie has, um, many of the Fortune 500 on 4100 customers. We work very closely with CEO CTO, so we have built sessions that are really designed specifically for that audience on I think for us it's really opened up. The potential of this event made it so much broader and more appealing than we were able to do when we were, As you say, you know, somewhat confined by the location in downtown San Francisco. >>I think it's such an interesting point. Um, because before you were constrained, right, If you have X number of rooms over a couple of days, you know you've got to make hard decisions on breakouts and what could go in and what can't go in. And, you know, will there be enough demand for these for this session versus another session? Or from the perspective of an attendee, you know, do they have to make hard tradeoffs? I could only attend one session at one oclock on Tuesday and I got to make hard decisions. But this is, you said really opens up the opportunities. I think you said you doubled. You doubled your sessions on and you got five X a number of registrations. So I think, you know, way too many people think about what doesn't happen in digital vs talking about the things that you can do that are impossible in physical. >>Yeah, I think at the very beginning. Well, first of all, we held our Amir summit events in London in July. So that was great because we got Thio go through this experience once already. And what we learned was the rial removal of hurdles in this process. So, to your point about missing the session because you're attending another session, we were calling this sort of the Pelton version of events where you have live sessions. It's great to be there, live participate in the live Q and A, but equally you have an entire on demand library. So if you weren't able to go because there was something else at the same time, this is available on demand for you. So we are actually repeating live sessions on two consecutive day. So on the Monday we're on everything on the Tuesday I ask because show up again for life Q and A at the end of their sessions. But after that it's available forever on an on demand library. So for us, it was really removing hurdles in terms of the amount of content, the scheduling of the content on also the number of people that content in attend, no geographical boundaries anymore. It used to be that a customer of ours would think, Well, I'll send one or two people to the page duty summit. They could learn all the great innovation from page duty, and they'll bring it back to the team that's completely changed. You know, we have tens of 20 signing up on. All of them are able to get that experience firsthand. >>That's really interesting. I didn't didn't even think about, you know, kind of whole teams being able to attend down instead of just certain individuals because of budget constraints, or you can't send your whole team, you know, a way for a conference in a particular area. But the piece to that you're supporting that were over and over is that the net new registrants goes up so dramatically in terms of the names and and and who those individuals are because a lot of people just couldn't attend for for various reasons, whether it's cost, whether it's, uh, geography, whether it's they just can't take time off from from from leaving their primary job. So it's a really interesting opportunity to open up, um, the participation to such a much bigger like you said five x five X, and increase in the registration. That's pretty good number. >>That's right. Yeah. I mean, that crossed boundaries gone away. This event is free on DWhite. That's actually meant is, as I say, you know, larger teams from the same company are attending. Uh, In addition, we have a number of attendees who are not actually paid to duty customers right now to previously. This was very much a community event for, you know, our page duty users on now we actually have a large number of I asked, interested future customers that will be coming to the event. So that's really important for us. And also, I think, for our sponsor partners as well, because it's bordering out the audience for both of us. So let's >>talk about sponsors for a minute, because, um, one of the big things in virtual events that people are talking about quite often is. Okay, I can do the keynotes, and I could do the sessions. And now I have all these breakout sessions for, um, you know, training and certification and customer stories, etcetera. But when it comes to sponsors, right sponsors used, you know, go to events to set up a booth and hand out swag and wander badge. Right? And it really was feeding kind of a top level down funnel. That was really important. Well, now those have gone away. Physical events. So from the sponsor perspective, you know, what can they expect? What? What do you know the sponsor experience at pager duty Summit. Since I don't have a little tiny booth at the Westin ST Francis given out swag this year. >>Yeah. So one important thing is the agenda and how we're involving our sponsors in our agenda this time, something that we learned is we used to have very long keynotes. You know, the keynote could be an hour long on involved multiple components and people would stay in that room for a now er on did really stay and watch sessions all day. So we learned in the virtual format that we need to be shorter and more precise in our sessions on that opened up the opportunity to bring in more of our partners, our sponsorship partners. So zendesk Salesforce, Microsoft some examples. So they actually get to have their piece of both of our keynote sessions and of our technical product sessions. I'm really explain both the partnership with pager duty, but also they're called technology and the value that they provide customers. So I think that the presence of sponsors in content is much higher than it was before on we are still repeating the Expo format, so we actually do have on Expo Hall that any time there's breaking between sessions, you could go over to the Expo ball, and it actually runs throughout as well, and you can go in and you can talk to the teams. You can see product demos, so it's very much a virtual version of the Expo Hall where you went and you want around and you picked up a bit of swag, >>so you mentioned keynotes and and Jennifer and and the team has always had a fantastic keynotes. I mean, I just saw Jennifer being interviewed with Frank's Luqman and and Eric Juan from Zoom By by Curry, which was pretty amazing. I felt kind of jealous that I didn't get to do that. But, um, talk tell us a little bit about some of the speakers I know there'll be some some, you know, kind of big rally moment speakers as well as some that are more down to technical track or another track. Give us some highlights on on some of the people. I will be sharing the stage with Jennifer. >>Absolutely, I said. I think what's really unique about Page duty Summit is that we designed types of content for different types of attendees. So if you're a developer, your practitioner, we have something like this from Jones of Honeycombs, who's talking about who builds the tools that we all rely on today, and how do they collaborate to build them together in this virtual world? Or we have J. Paul Reed from Netflix talking about how to handle the stress of being involved in incidents, So that's really sessions for our core audience of developers who are part of our community and pager duty really helps them day to day with with that job. And then we have the more aspirational senior level speakers who could really learn from a ZA leader. So Bret Taylor, president and CEO of Salesforce, will be joining us on the main stage. You'll be talking about innovation and trust in today's world on. Then we have Derrick Johnson. He is president of N A A. C P, and he'll be talking about community engagement and particularly voter engagement, which is such an important topic for us right now. Aan den. We have leaders from within our customers who are really talking about the way they use pager duty thio drive change in their organization. So an example would be porches, bro. He runs digital for Fox on, and he's gonna be talking about digital acceleration. How large organization like Fox can really accelerate for this digital first world that we find ourselves living in right now, >>right? Well, you guys have such a developer focus because pager duty, the product of solution, has to integrate with so many other, um, infrastructure, you know, monitoring and, uh, and all of all those different systems because you guys were basically at the front line, you know, sending them the signals that go into those systems. So you have such a broad, you know, kind of ecosystem of technology partners. I don't know if people are familiar with all the integrations that you guys have built over the years, which is such a key piece of your go to market. >>That's right. I mean, we we like to say we're at the center of the digital ecosystem. We have 203 170 integrations on. That's important because we want anyone to be able to use page duty no matter what is in their technology stack technology stacks today are more complex than they've ever been before, particularly with businesses having to shift to this digital first model since we all began shelter in place, you know, we all are living through digital on working and learning through digital on DSO. The technology stacks that power that are more complicated than ever before. So by having 370 integrations, we really know that we conserve pretty much any set of services that your business. It's using. >>Yeah, we've all seen all the means right about who's who's pushing your digital transformation. You know, the CEO, the CEO or or covert. And we all know the answer to toe what's accelerated that whole process. So okay, but so before I let you go, I don't even think we've mentioned the date. So it's coming up Monday, September, September 21st through Thursday, September 24th not at the West End Online and again. What air? What are you hoping? You're kind of the key takeaways for the attendees after they come to the summit? >>Yeah, a couple of things. I mean, first of all, I think will be a sense of belonging. Three attendees, the uses, a pager duty. They are really the teams that are at the forefront of keeping our digital services working on. But what that means is responding to incidents we've actually seen. Ah, 38% increase in the volume of incidents on our platform since covert and shelter in place began. Wait 30 >>38% increase in incidents since mid March. >>That's correct. Since the beginning of on bear in mind incidents. Prior to that in the six months prior, they were pretty flat. There wasn't instant growth. But what we've also seen is a 20% improvement in the time that it takes to resolve an incident from five minutes down to four minutes. So what that really means is that the pager duty community is working really hard. They're improving their practices. Hopefully our platform, our platform is a key part of how, but these are some people under pressure, so I hope that people can come and they can experience a sense of belonging. They can learn from each other about experiences. How do you manage the stress of that situation on what are some of the great innovations that make your job easier in the year ahead? The second thing that we don't for that community is that we are offering certification for P. D. You page due to university for free this year. It's of course, with a value of $7500. Last year, you would attend page duty summit on you would sit through your sessions and you would learn and you would get certified. So this year it's offered for free. You take the course during summit. But you can also carry on if you miss anything for 30 days after. So we're really feeling that, you know, we're giving back there, offering a great program for certification and improved skills completely free to help our community in this in this time of pressure, >>right? Right. Well, it is a very passionate community, and, you know, we go to so many events and you can you can really tell it's palatable, you know, kind of what the where the tight communities are and where people are excited to see each other and where they help each other, not necessarily only at the event, but you know, throughout the year. And I think you know a huge shout out to Jennifer on the culture that she's built there because it is very warm. It's very inclusive, is very positive. And and that energy, you know, kind of goes throughout the whole company and ice the teaser. You know this in something that's built around a device that most of the kids today don't even know what a pager is, and just the whole concept of carrying a pager and being on call right and being responsible. It's a very different way to kind of look at the world when you're the one that has that thing on your hip and it's buzzing and someone's expecting, Ah, return call and you gotta fix something So you know, a huge shout out to keep a positive and you're smiling nice and big culture in a job where you're basically fixing broken things most of the time. >>Yeah, absolutely. I mean, there's, I think, a joke that we make you know these things only break on Friday night or your wedding anniversary or Thanksgiving. But one of the announcements we're most excited about this year is the level of automation on artificial intelligence that we're building into our platform that is really going to reduce the number of interruptions that developers get when they are uncle. >>Yeah, I look forward to more conversations because we're gonna be doing a bunch of Cube interviews like Normal and, uh, you know, applied artificial intelligence, I think, is where all the excitement is. It's not a generic thing. It's where you applied in a specific application to get great business outcomes. So I look forward to that conversation and hopefully we'll be able to talk again and good luck to you and the team in the last few weeks of preparation. >>Thanks so much, Jeff. I've enjoyed talking to you. Thanks for having me. >>Alright. You too. And we'll see you later. Alright. She is Caroline. I'm Jeff. You're watching the Cube. Thanks for watching. We'll see you next time.

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hi everybody welcome to this special cube in size powered by ET our enterprise Technology Research our partner who's got this database to solve the spending data and what we're gonna do is a braking analysis on the analytic database market we're seeing that cloud and cloud players are disrupting that marketplace and that marketplace really traditionally has been known as the enterprise data warehouse market so Alex if you wouldn't mind bringing up the first slide I want to talk about some of the trends in the traditional EDW market I almost don't like to use that term anymore because it's sort of a pejorative but let's look at it's a very large market it's about twenty billion dollars today growing it you know high single digits low double digits it's expected to be in the 30 to 35 billion dollar size by mid next decade now historically this is dominated by teradata who started this market really back in the 1980s with the first appliance the first converged appliance or coal with Exadata you know IBM I'll talk about IBM a little bit they bought a company called mateesah back in the day and they've basically this month just basically killed the t's and killed the brand Microsoft has entered the fray and so it's it's been a fairly large market but I say it's failed to really live up to the promises that we heard about in the late 90s early parts of the 2000 namely that you were going to be able to get a 360 degree view of your data and you're gonna have this flexible easy access to the data you know the reality is data warehouses were really expensive they were slow you had to go through a few experts to to get data it took a long time I'll tell you I've done a lot of research on this space and when you talked to the the data warehouse practitioners they would tell you we always had to chase the chips anytime Intel would come out with a new chip we forced it in there because we just didn't have the performance to really run the analytics as we need to it's took so long one practitioner described it as a snake swallowing a basketball so you've got all those data which is the sort of metaphor for the basketball just really practitioners had a hard time standing up infrastructure and what happened as a spate of new players came into the marketplace these these MPP players trying to disrupt the market you had Vertica who was eventually purchased by HP and then they sold them to Micro Focus greenplum was buy bought by EMC and really you know company is de-emphasized greenplum Netezza 1.7 billion dollar acquisition by IBM IBM just this month month killed the brand they're kind of you know refactoring everything par Excel was interesting was it was a company based on an open-source platform that Amazon AWS did a one-time license with and created a redshift it ever actually put a lot of innovation redshift this is really doing well well show you some data on that we've also at the time saw a major shift toward unstructured data and read much much greater emphasis on analytics it coincided with Hadoop which also disrupted the market economics I often joked it the ROI of a dupe was reduction on investment and so you saw all these data lakes being built and of course they turned into the data swamps and you had dozens of companies come into the database space which used to be rather boring but Mike Amazon with dynamodb s AP with HANA data stacks Redis Mongo you know snowflake is another one that I'm going to talk about in detail today so you're starting to see the blurring of lines between relational and non relational and what was was what once thought of is no sequel became not only sequel sequel became the killer app for Hadoop and so at any rate you saw this new class of data stores emerging and snowflake was one of the more interesting and and I want to share some of that data with you some of the spending intentions so over the last several weeks and months we've shared spending intentions from ETR enterprise technology research they're a company that that the manages of the spending data and has a panel of about 4,500 end-users they go out and do spending in tension surveys periodically so Alex if you bring up this survey data I want to show you this so this is spending intentions and and what it shows is that the public cloud vendors in snowflake who really is a database as a service offering so cloud like are really leading the pack here so the sector that I'm showing is the enterprise data warehouse and I've added in the the analytics business intelligence and Big Data section so what this chart shows is the vendor on the left-hand side and then this bar chart has colors the the red is we're leaving the platform the gray is our spending will be flat so this is from the July survey expect to expectations for the second half of 2019 so gray is flat the the dark green is increase and the lime green is we are a new customer coming on to the platform so if you take the the greens and subtract out the red and there's two Reds the dark red is leaving the lighter red is spending less so if you subtract the Reds from the greens you get what's called a net score so the higher the net score the better so you can see here the net score of snowflake is 81% so that very very high you can also see AWS in Microsoft a very high and Google so the cloud vendors of which I would consider a snowflake at cloud vendor like at the cloud model all kicking butt now look at Oracle look at the the incumbents Oracle IBM and Tara data Oracle and IBM are in the single digits for a net score and the Terra data is in a negative 10% so that's obviously not a good sign for those guys so you're seeing share gains from the cloud company snowflake AWS Microsoft and Google at the expense of certainly of teradata but likely IBM and Oracle Oracle's little for animal they got Exadata and they're putting a lot of investments in there maybe talk about that a little bit more now you see on the right hand side this black says shared accounts so the N in this survey this July survey that ETR did is a thousand sixty eight so of a thousand sixty eight customers each er is asking them okay what's your spending going to be on enterprise data warehouse and analytics big data platforms and you can see the number of accounts out of that thousand sixty eight that are being cited so snowflake only had 52 and I'll show you some other data from from past surveys AWS 319 Microsoft the big you know whale here trillion dollar valuation 851 going down the line you see Oracle a number you know very large number and in Tara data and IBM pretty large as well certainly enough to get statistically valid results so takeaway here is snowflake you know very very strong and the other cloud vendors the hyper scale is AWS Microsoft and Google and their data stores doing very well in the marketplace and challenging the incumbents now the next slide that I want to show you is a time series for selected suppliers that can only show five on this chart but it's the spending intentions again in that EDW and analytics bi big data segment and it shows the spending intentions from January 17 survey all the way through July 19 so you can see the the period the periods that ETR takes this the snapshots and again the latest July survey is over a thousand n the other ones are very very large too so you can see here at the very top snowflake is that yellow line and they just showed up in the January 19 a survey and so you're seeing now actually you go back one yeah January 19 survey and then you see them in July you see the net score is the July next net score that I'm showing that's 35 that's the number of accounts out of the corpus of data that snowflake had in the survey back in January and now it's up to 52 you can see they lead the packet just in terms of the spending intention in terms of mentions AWS and Microsoft also up there very strong you see big gap down to Oracle and Terra data I didn't show I BM didn't show Google Google actually would be quite high to just around where Microsoft is but you can see the pressure that the cloud is placing on the incumbents so what are the incumbents going to do about it well certainly you're gonna see you know in the case of Oracle spending a lot of money trying to maybe rethink the the architecture refactor the architecture Oracle open worlds coming up shortly I'm sure you're gonna see a lot of new announcements around Exadata they're putting a lot of wood behind the the exadata arrow so you know we'll keep in touch with that and stay tuned but you can see again the big takeaways here is that cloud guys are really disrupting the traditional edw marketplace alright let's talk a little bit about snowflakes so I'm gonna highlight those guys and maybe give a little bit of inside baseball here but what you need to know about snowflakes so I've put some some points here just some quick points on the slide Alex if you want to bring that up very fast-growing cloud and SAS based data warehousing player growing that couple hundred percent annually their annual recurring revenue very high these guys are getting ready to do an IPO talk about that a little bit they were founded in 2012 and it kind of came out of stealth and hiding in 2014 after bringing Bob Moog Leon from Microsoft as the CEO it was really the background on these guys is they're three engineers from Oracle will probably bored out of their mind like you know what we got this great idea why should we give it to Oracle let's go pop out and start a company and that NIN's and as such they started a snowflake they really are disrupting the incumbents they've raised over 900 million dollars in venture and they've got almost a four billion dollar valuation last May they brought on Frank salute Minh and this is really a pivot point I think for the company and they're getting ready to do an IPO so and so let's talk a little bit about that in a moment but before we do that I want to bring up just this really simple picture of Alex if you if you'd bring this this slide up this block diagram it's like a kindergarten so that you know people like you know I can even understand it but basically the innovation around the snowflake architecture was that they they separated their claim is that they separated the storage from the compute and they've got this other layer called cloud services so let me talk about that for a minute snowflake fundamentally rethought the architecture of the data warehouse to really try to take advantage of the cloud so traditionally enterprise data warehouses are static you've got infrastructure that kind of dictates what you can do with the data warehouse and you got to predict you know your peak needs and you bring in a bunch of storage and compute and you say okay here's the infrastructure and this is what I got it's static if your workload grows or some new compliance regulation comes out or some new data set has to be analyzed well this is what you got you you got your infrastructure and yeah you can add to it in chunks of compute and storage together or you can forklift out and put in new infrastructure or you can chase more chips as I said it's that snake swallowing a basketball was not pretty so very static situation and you have to over provision whereas the cloud is all about you know pay buy the drink and it's about elasticity and on demand resources you got cheap storage and cheap compute and you can just pay for it as you use it so the innovation from snowflake was to separate the compute from storage so that you could independently scale those and decoupling those in a way that allowed you to sort of tune the knobs oh I need more compute dial it up I need more storage dial it up or dial it down and pay for only what you need now another nuance here is traditionally the computing and data warehousing happens on one cluster so you got contention for the resources of that cluster what snowflake does is you can spin up a warehouse on the fly you can size it up you can size it down based on the needs of the workload so that workload is what dictates the infrastructure also in snowflakes architecture you can access the same data from many many different houses so you got again that three layers that I'm showing you the storage the compute and the cloud services so let me go through some examples so you can really better understand this so you've got storage data you got customer data you got you know order data you got log files you might have parts data you know what's an inventory kind of thing and you want to build warehouses based on that data you might have marketing a warehouse you might have a sales warehouse you might have a finance warehouse maybe there's a supply chain warehouse so again by separating the compute from that sort of virtualized compute from the from the storage layer you can access any data leave the data where it is and I'll talk about this in more and bring the compute to the data so this is what in part the cloud layer does they've got security and governance they got data warehouse management in that cloud layer and and resource optimization but the key in in my opinion is this metadata management I think that's part of snowflakes secret sauce is the ability to leave data where it is and have the smarts and the algorithms to really efficiently bring the compute to the data so that you're not moving data around if you think about how traditional data warehouses work you put all the data into a central location so you can you know operate on it well that data movement takes a long long time it's very very complicated so that's part of the secret sauce is knowing what data lives where and efficiently bringing that compute to the data this dramatically improves performance it's a game changer and it's much much less expensive now when I come back to Frank's Luqman this is somebody that I've is a career that I've followed I've known had him on the cube of a number of times I first met Frank Sloot when he was at data domain he took that company took it public and then sold it originally NetApp made a bid for the company EMC Joe Tucci in the defensive play said no we're not gonna let Ned afgan it there was a little auction he ended up selling the company for I think two and a half billion dollars sloop and came in he helped clean up the the data protection business of EMC and then left did a stint as a VC and then took over service now when snoop and took over ServiceNow and a lot of people know this the ServiceNow is the the shiny toy on Wall Street today service that was a mess when saluteth took it over it's about 100 120 million dollar company he and his team took it to 1.2 billion dramatically increased the the valuation and one of the ways they did that was by thinking about the Tam and expanding that Tim that's part of a CEOs job as Tam expansion Steuben is also a great operational guy and he brought in an amazing team to do that I'll talk a little bit about that team effect uh well he just brought in Mike Scarpelli he was the CFO was the CFO of ServiceNow brought him in to run finance for snowflake so you've seen that playbook emerge you know be interesting Beth white was the CMO at data domain she was the CMO at ServiceNow helped take that company she's an amazing resource she kind of you know and in retirement she's young but she's kind of in retirement doing some advisory roles wonder if slooping will bring her back I wonder if Dan Magee who was ServiceNow is operational you know guru wonder if he'll come out of retirement how about Dave Schneider who runs the sales team at at ServiceNow well he you know be be lord over we'll see the kinds of things that Sluman looks for just in my view of observing his playbook over the years he looks for great product he looks for a big market he looks for disruption and he looks for off-the-chart ROI so his sales teams can go in and really make a strong business case to disrupt the existing legacy players so I one of the things I said that snoopin looks for is a large market so let's look at this market and this is the thing that people missed around ServiceNow and to credit Pat myself and David for in the back you know we saw the Tam potential of ServiceNow is to be many many tens of billions you know Gartner when they when ServiceNow first came out said hey helpdesk it's a small market couple billion dollars we saw the potential to transform not only IT operations but go beyond helpdesk change management at cetera IT Service Management into lines of business and we wrote a piece on wiki Vaughn back then it's showing the potential Tam and we think something similar could happen here so the market today let's call 20 billion growing to 30 Billy big first of all but a lot of players in here what if so one of the things that we see snowflake potentially being able to do with its architecture and its vision is able to bring enterprise search you know to the marketplace 80% of the data that's out there today sits behind firewalls it's not searchable by Google what if you could unlock that data and access it in query at anytime anywhere put the power in the hands of the line of business users to do that maybe think Google search for enterprises but with provenance and security and governance and compliance and the ability to run analytics for a line of business users it's think of it as citizens data analytics we think that tam could be 70 plus billion dollars so just think about that in terms of how this company might this company snowflake might go to market you by the time they do their IPO you know it could be they could be you know three four five hundred billion dollar company so we'll see we'll keep an eye on that now because the markets so big this is not like the ITSM the the market that ServiceNow was going after they crushed BMC HP was there but really not paying attention to it IBM had a product it had all these products that were old legacy products they weren't designed for the cloud and so you know ServiceNow was able to really crush that market and caught everybody by surprise and just really blew it out there's a similar dynamic here in that these guys are disrupting the legacy players with a cloud like model but at the same time so the Amazon with redshift so is Microsoft with its analytics platform you know teradata is trying to figure it out they you know they've got an inertia of a large install base but it's a big on-prem install base I think they struggle a little bit but their their advantages they've got customers locked in or go with exudate is very interesting Oracle has burned the boats and in gone to cloud first in Oracle mark my words is is reacting everything for the cloud now you can say Oh Oracle they're old school they're old guard that's fine but one of the things about Oracle and Larry Ellison they spend money on R&D they're very very heavy investor in Rd and and I think that you know you can see the exadata as it's actually been a very successful product they will react attacked exadata believe you me to to bring compute to the data they understand you can't just move all this the InfiniBand is not gonna solve their problem in terms of moving data around their architecture so you know watch Oracle you've got other competitors like Google who shows up well in the ETR survey so they got bigquery and BigTable and you got a you know a lot of other players here you know guys like data stacks are in there and you've got you've got Amazon with dynamo DB you've got couch base you've got all kinds of database players that are sort of blurring the lines as I said between sequel no sequel but the real takeaway here from the ETR data is you've got cloud again is winning it's driving the discussion and the spending discussion with an IT watch this company snowflake they're gonna do an IPO I guarantee it hopefully they will see if they'll get in before the booth before the market turns down but we've seen this play by Frank Sluman before and his team and and and the spending data shows that this company is hot you see them all over Silicon Valley you're seeing them show up in the in the spending data so we'll keep an eye on this it's an exciting market database market used to be kind of boring now it's red-hot so there you have it folks thanks for listening is a Dave Volante cube insights we'll see you next time

from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hey welcome back everybody Jeffrey here with the cube we're in our Palo Alto Studios here today for a cute conversation it's a little bit of a dog days of summer conference seasons a little bit slow so we're excited we can kind of take a step back and we're gonna look back actually in time we're excited to have a very special guest rich Kolbert he is the field CTO at Dell EMC but really what we're talking about today is this data domain is 10-year anniversary of the date domain acquisition so rich first off welcome to the to the cube thanks Jeff excited to be here thanks for the invitation appreciate it I can't believe we're talking before we turned the cameras on that you join in 2006 and yet it's been 10 years I'm like wait 2006 was more than 10 can that be we're just getting old I don't know things are changing too fast no it's like a trip down memory lane and it just seems so long ago and yes in a way it also seems like yesterday I think things have gone so quickly so we're also joined in this segment by our top data analyst also the founder of wiki bond and co-ceo of Silicon angle media and founder of that as well so Dave Villante is joining us all the way from Boston Dave good to see ya hey Jeff hi rich to talk to you guys hey Dave so let's take a quick trip back 10 years ago actually maybe 11 years ago things were starting to heat up there was a lot of different vendors out there a lot of different players and things started to consolidate so I wonder if you can give us a little bit of your perspective what what's going on rich and then we'll get Dave's perspective yeah it was an interesting time right before the data domain acquisition we actually went through some economic times in 2008 and the markets are changing and and and some companies are becoming more successful some companies were struggling through that time customers were also looking for ways to to you know save money and do some interesting things there so it was a mixed feeling set of you know through that times data domain had IPO in 2007 and we were kind of going through this this explosive period of growth but you know across the board we just saw so many things change all at once and we really were surprised I think when initially was NetApp that an that they had intentions to bias and I think that was due to some of the economic factors of play and then of course EMC stepped in and and started a bidding contest with NetApp for for the company right so I Dave wonder if you could share your perspective you're sitting as an analyst you got Jo TG The Godfather of storage back in Boston what were you seeing in terms of the kind of the market dynamics and was it a surprise wouldn't that app decided to make a move well if you know first first of all I had left the storage industry for quite some time and when I started wiki bond we looked at storage and nothing had changed except one thing which was David deduplication that was new until a new tape was finally I always hated the tape the tape was finally being attacked so it was it was amazing time and EMC at the time we had some obviously great management yet Frank Sluman running data domain yo Joe Tucci who always balanced out acquisitions with organic you know in how to R&D and when Tom Georgians and NetApp said they were gonna go by David domain emt's walk right in and said no way so it was somewhat of a defensive move but at the same time when you talk to the M&A guys they said no no it's not just defense we can actually make this a growth play and that's exactly what happened Dayna domain I think at the time rich was probably a couple of hundred million dollar company and then they they popped that at the EMC and scaled that to you know well over a billion dollars and it'll maintain the the franchise and then grew it quite dramatically beyond where all the expectations were for the market the market team at the time was probably around a billion and I think ID seen rich as a over three billion today yeah one of the things that's so don't quote me on all the numbers because I'm not like you know watching the market caps and stocks but I think we'd gotten up to about a 500 million dollar run rate in terms of sales and prior to the crash I think our market cap was actually significantly higher so so our price came down you know which is one of the things I think that attracted NetApp to the game so the interesting dynamic inside the company was that the NetApp offer was was kind of the first one so they were working with the data domain leadership and they were speaking with us EMC was more of a kind of unsolicited offer so there was less communication and I remember there was a morning I was at San Francisco Airport going out to meet a customer and Joe to Chi put out a full-page ad in a local newspaper and we were reading that and that was his way of communicating to the to the people a data domain saying he wants to welcome us into the family it was quite a moment well it sure was and of course you guys were fierce competitors data domain was fierce competitors with with EMC you know fighting for for the install base and then all of a sudden you know the cultures it's somehow work EMC was was very good at acquisitions and he made it work and they not active it was an outside observer but you were there you know Frank Sluman came in did it's kind of running the the data protection organization but a lot has changed since then hasn't it I mean back then you stored you know a little bit of data I think accounting of terabytes today we live in a petabyte scale world I could talk about what's changed well you know the scales and performance certainly has changed I think the data domain platform today is about a thousand times larger than it was when it first came to market and in fact when we were being bid on by NetApp and EMC we had a flagship product is the DD 690 you know behind the scenes we had a system that was coming out that was double that size and EMC nor Netta knew about that so once the deal closed they got to find out that our size had just doubled in our performance and doubled at the same time but you're right you kind of talked about the dynamics inside of EMC EMC had a very large data protection you know division they had avemar networker santaros v TLS they also had an OEM arrangement for a competing product with the data domain platform so it was really like you know I compared to going to Hogwarts right where you have all of these different houses and we came in with with data domain and and I think the thing that really the glue that really helped it come to get was Joe Tucci you know tapping Frank's Luqman on the shoulder as the leader to bring this together and taking what was the borough division and and reforming it as the BRS division and I think we came together very quickly as a team even though people came from all of these different backgrounds you know standing for these different products rich let me follow up on that because there's a lot of M&A activity going on right now and and not very many big M&A deals are ultimately successful it turns out so what you said a little bit about you know Joe and Frank you know coming together but what are some of the other attributes that you would say that made it work it actually did what everybody hopes on an acquisition which is take great technology put it into a big sales machine and watch it grow and grow I think part of it you know quite frankly just comes down to the product and being differentiated because there are a lot of products out there and and if you take a step back they have good things that they're doing but it's very hard to find a product that says hey you're doing something that even if you put the blueprints out there it's very hard for other people to follow in those footsteps and create a similar value proposition and I think I think in this case it was a differentiated product and it had a lot of energy of its own and and I think from an EMC perspective they just stood back and said let's take this momentum and and play it out and see how how far it can take itself unfortunately I think a lot of times they don't do that right a lot of times acquiring companies don't just take this great thing and kind of get out of the way and add the juice where they can but you try to to try to change it so that's a really nice statement on Joe to G and what he was able to accomplish yeah no he was fantastic for us and and his support was tremendous but also his you know delegation and and kind of seeing how this but you know kind of having a vision of how this business unit should be formed right I think what was was very prison and then now you're part of Dell so obviously Michael Dell big personality as well the Dell technology stories he's doing a great job of pulling all these pieces together and you know kind of reinvigorating the brand coming back out of the little little side bar you know make it private for a while and come back so I wonder if you can talk about that integration how's that going as you've gone now a couple of times well I think it's been very exciting for us because the one piece that EMC had always been lacking had been the the compute part of the picture and now we have really the ability to go in and talk about the entire stack with our customers and that's that's a lot more powerful than saying here is an element of it and then if you want to go and add compute to that perhaps you know put in your virtual or physical servers then you're gonna we're going to need to partner with somebody and you know it's it's just a much cleaner story from end to end right right so the big big change obviously that wasn't around ten years ago that is around today is public cloud right huge impact not only directly in in taking workloads to the public cloud but also I think much more importantly changing the way people think about provisioning thinking about the way people think about elastic capacity so as as the market has evolved the rise of AWS and any other public clouds how has that changed what you guys are doing how are you reacting to that house at a new opportunity you know to kind of grow the maturity of the core product yeah well the thing is we have taken a lot of approach you know that's been learning and evolving as well right so so you know developers and applications really figured out AWS and the public cloud early I think data protection has has followed along with a couple years of lag in terms of doing that so you know our perspective is we learned as well right so so 2015 2016 I think there was some resistance and I think ultimately when we started to follow those workloads into the cloud there was a little bit of a lift and shift what we've learned is that the architecture really matters when you get to the cloud so the efficient use of resources the ability to do things in a cloud like way to use for example object storage instead of block storage when when the case presents itself so we took our products and virtualize them and followed them into the cloud but we realized that just taking the on-premise version of the product and putting it in the cloud itself isn't enough right because at the end of the day the customer is paying for all the underlying resources and so if your architecture is an efficient from a cost perspective as well as a performance perspective it's not going to be a viable solution and so 2017-2018 we've really seen a big acceleration in our adoption in the cloud because we have adapted our architecture to be more cloud friendly and more cost-effective for our customers to deploy but it was a learning experience for sure you know and and I think we're continuing to learn and continue to develop in that space and there's a lot of opportunity ahead of us the other big change I think that's come that we see over and over and over is really data as an asset only as an asset but as a huge valuable asset that drives your business drives real lytx but then becomes actually something that drives your company value and I think we see that and the Facebook's of the world and the googles of the world of why they have these crazy high valuations relative to here to their revenue and their profits because they're getting value for the data alright great news for you right it used to be a sample the day of the day was a pain it was expensive to store I didn't want to keep it all now everyone wants all the data they want to analyze it in real time and they want to put it in a place where they can actually put multiple applications across that same data set to do all kinds of new analytics so again super opportunity for you guys people aren't storing any less data no absolutely yeah no the data amount being stored is definitely growing one of the things that we're seeing that that's this kind of pervasive is this idea of of really using the right data the right place the right time so accessibility to whether it is a data Lake or it is your protection copies or you know an instant access of your protection copies there's a lot of different thing customers are doing with data but it's no longer a one-size-fits-all proposition like it was back in the tape automation days where I'm just throwing all of this stuff into a box and and never accessing it again right so the dynamics are changing and continue to evolve I expect that if we have this conversation two or three years down the road we're going to see some amazing things happen in the next couple of years that and some of it we were not predicting now we're gonna find out as customer demand and as innovation guides us along right because then the other big piece is the media right we've talked about tapes and the original data domain was was in response to some issues with tape and we get spinning rust as everybody likes to call it and now of course flash so yeah again see change in terms of capability the cost is coming down it's no longer the super high-end thing just for super high value applications so very transfer transformative opportunity on the on the media side as well on the flashlight as well you hit on a couple of really key things data domain was very successful because it became viable and practical to displace tape automation and nobody was a fan of their tape automation environments and now I think we're gonna see that's that same shift you know spinning disk is right now being relegated to archival and backup purposes but we're gonna hit an inflection point very soon I think we're where every instance of spinning disk probably can be questioned and so we are actually doing the you know kind of getting ahead of that curve and coming out with all flash products as a choice for a customer so we'll still have spinning disk for some backup use cases but we'll also have you know be able to offer customers a choice of the data domain technology on an all flash set of platforms and that will give customers a chance to get out of the yeah that spinning disk business as well right good I wonder if I get what if I get chime in here I you guys were talking about the the technologies and the cloud and the architecture it's interesting it David the main really started out don't hate me for saying this but as a feature product and the key feature was data deduplication data domain had the best you had a lot of guys doing post process you had you know some guys trying to do server-side avemar itself for example but they domain really killed it with regard to data David II do and if this feature product became a platform and had an architecture people became as you know unicorn times 2 plus plus and so I wanted to ask you rich about that architecture and aware it can go you're talking about different media now beyond spinning disk you know it used to be just a kind of a dumb target you've now got integrated appliances you've got software that's integrated there so it's you know you talked about the scale and the capacity where do you see this architecture going I wonder if you could comment on yeah well I think a lot of that belongs in in the realm of the data management software that speaks to it and and by having a distributed ecosystem and having things like you know distributed segment processing so we can take data domains technology and extend it out into those data management activities because a lot of the what's happening in the market is as new workloads are coming into the market they're having their own methods and native tools built-in for data protection and to be able to leverage those and have a highly consolidated affect on the backend is still extremely valuable to our customers and you're right it was a differentiated product from a deduplication standpoint but really the feature was that I can keep my 30 60 or 90 days worth of copies that are separate from my primary copies so I putting them somewhere safe I can even put them under different governance from my primary storage or my primary application owners right and it's practical and feasible and and prior to that the only real way to do that was with tape automation deduplication has become more of a broader word itself and it goes beyond what data domain does so there's deduplication and primary storage but if you look at primary storage deduplication it's good but it's designed to help you reduce the use of primary storage by 2 or 3 times it doesn't touch on the 30 60 90 days of retention that data domain does so there the similar technologies and a common use of the word but but they're two different use cases that the the remains separate I think yeah and you know as a former practitioner the other you are I think a former customer the genius part of the genius of data domain was its ability to just plug in to existing processes yes you didn't have to change things up and so it was an easy in but but it's impressive that you've been able to keep that that architecture going I wanted to ask you about market share you aided them in has always had a sixty plus percent market share I think it's at sixty now but it's it's like the Cisco of purpose-built backhaul appliances you're able to sort of dominate that little segment of the market which keeps getting bigger what but now you've got a lot of new entrants you know on VC money pouring in a lot of noise in the marketplace I feel like you guys maybe a couple years ago took your eye off the wall and now you've got this renewed sense of a vigor you know maybe it was parked partly the acquisition but you know we've talked to Beth Phelan about this a number of times you've really refreshed the portfolio so so wonder if you can talk about that and my question is what gives you confidence that you can continue to maintain your dominance yeah that's a great question and things have really changed I think starting around 2014 we were having some internal conversations about things like simplification the consumerization of IT and and all of those those dollars that you're talking about are really being poured into companies that are trying to take a different approach they're going into the white space that we had kind of left open which was simplicity right if you if you look back 10 or 15 years and you look at the the data management and enterprise backup software space enterprise backup software has been complicated and as you add more use cases it has become even more complicated and the customer base is no longer tolerant of that that's something that that maybe 10 or 15 years ago that was kind of a badge of honor to be working with complex and people just don't have the time for that there's a lot of IT generalists and folks that are out there that don't want to go to training class you know you know five days or ten days out of the year to learn how to use a product so that was a really good thing that we're seeing in the marketplace in terms of making products simpler easier to use and more approachable with things like discoverable functionality we certainly have the you know put a lot of effort into going in that direction because we think that's the right direction but what gives me confidence is the underlying storage value proposition about efficiency and performance and scale is something that we've still think that we have a strong upper hand on and when it comes down to that you know we take cloud as an example our data reduction in the cloud we think allows a much lower cost to serve and you know the customer is going to pay for that cloud storage or that cloud compute regardless of which vendor they're trusting in terms of their their solutions so simple only goes so far we think we can get there with simple but we don't necessarily see our competition having the efficiencies scalability and and so forth that we've already had so that that's good that gives me a lot of confidence so when you talk to customers what's the big problem the big hairy problem that they're trying to solve in your space and how are you guys helping so I one of the two big problems I see is is really a lot of IT teams are confronted with they've got a digital transformation going on they've got a cloud strategy going on an IT isn't necessarily being invited to the table early enough or often enough to go ahead and help with that process so what you have is you a cloud team building applications bringing things online and then the data protection the backups the snapshots whatever they're doing to make sure that that data is safe is is a bit of an afterthought and it you know I think of DevOps and I think about the ops part and I've never really come across an application team that wanted to own the business responsibility for the risk of you know backups recovery replication and all of that and I think IT has a lot of established practices that would be good to inform how those things should be built so the number one thing that I'm talking to with my customers when we're talking about this whole you know tectonic shift and in the way things are being done is that IT and the digital transformation or the cloud team do need to speak early and often and proactively about how they approach data protection because they continue to need to have a strategy that evolves and make sure they keep themselves protected as they start moving these critical workloads into the cloud it's an age-old problem with backup and data protection people think of it as a back as a bolt-on is an afterthought and your point is right on it's got to be a fundamental part of any transformation it's just like security you can't bolt it on earth just doesn't scale yeah and it's very much like you know back in the day when open systems was just coming of age there was a lot of operational discipline that the mainframe teams had and the mid-range teams had but the open systems was the Wild West and eventually open systems learned and and and a lot of that you know was knowledge sharing about best practices and you know Mis became IT now IT is becoming you know DevOps and digital transformation we're seeing a lot of that same dynamic happening again and and you know my main point is just you know start those conversations and if you're on the IT side start those conversations proactively you might not be getting invited to the digital transformation party invite yourself rich has been quite a 10 years and and as I was just watching an Andy Jazzy interview if you think the last 10 years have been crazy you ain't seen nothing yet so you guys are in a great position to stay agile and I'm gonna steal your line that it's no longer an honor to work on complicated systems that's great yeah it's been great being here thanks for having me and looking forward to maybe coming back in ten years and seeing what changed so hopefully we won't wait 10 years so rich thanks for stopping by Dave thanks for checking in from Boston and it's great to see you as well thanks you guys thanks Dave thanks Jeff [Music]

live from Las Vegas Nevada it's the cute covering knowledge 15 brought to you by service now okay hello everyone we are live for day two of coverage this is the cube our flagship program we go out to the events and extract the signal noise we go over here live in service now's knowledge 15 hashtag no 15 you want to join the conversation we have a back channel live chat on crowd chat new application which I'm excited Dave to show the guys from Sarah's neck as they love good software so but a crowd shot net / no 15 and see the conversation ask questions join our virtual social experience and we'll be happy to address that with your day to coverage live in Las Vegas out of three full days yesterday was a great day we had Frank sloop enough CEO opening up the day really laying down and and in clarifying the future of service now certainly they took a bath on the the stock last week on their earnings still in throwing off a lot of lot of cash great platform business great buying opportunity as Dave and I were speculating and ended the day with John Cleese famous actor writer comedian who we had some fun we try to bring a little bit of Jon Stewart a little bit of Jimmy Fallon I'm jump Road Dave vellante Dave what you think about yes that your laptop working parts of my lap water here I've lost my return key in my M so what you think John Cleese k the holy grail of our of our of our program yesterday he was great I mean we had a nice little bit going on there all ad lib just for the record folks he was not pissed he was totally happy at a great time but was all ad-lib he challenged us on the cube and it was great seeing after we were nervous and he's a pro we couldn't even hold a candle to his performance David it was great seeing him afterwards he came up to us yellow hey mr. classy came up and high-five and a smiling laughing it was great smart guy what you think of the inter very opinionated I thought the interview was great I mean it was weird but it was great I top guest top test of six years he's on a great show we had about you know 50 people behind that's all watching so it was really a lot of fun again but let's get back to the event here day two well you know another top guest coming up today is Fred ludie I think you're really going to enjoy interviewing and you heard him on the keynote John he was talking about the new development platform the new UI the new mobile app all that he was geeking out on all the technologies a lot of things that you're very familiar with borrowing from you know real-time geolocation leveraging the camera in the mobile app a lot of technologies borrow from Facebook and Twitter and a whole that whole real-time crowd a lot of stuff that that that crowd chat uses I know you talk about it all the time angularjs and all these kind of things that people don't understand our new crowd chat application go to crouch at that poke around look at the live one but what you'll notice on that app is one hundred percent as synchronous we use cutting-edge technologies like bootstrap we use angularjs and our new crowd pages coming out we have knowed Java on the backend for analytics really a cross-section of all the different language but node bootstrap angular these are the technologies that truly make it a singer's Facebook by the way is not a synchronous you've got to load the page having a synchronous communications loose from WebSockets days of web browser to fully available data real-time so near real-time is the holy grail today and basically instant is going to be defensive state-of-the-art today in software development that's what service now is showing on the stage and again a lot of it resonated because I hear you talking about all the time and I see it I see the green dot I see the presence I see the real-time nature and that's really what today's modern apps are all about and we'll talk about that today in detail what's under the hood for service now and again I can reiterate what a great software platform service now has I am super impressed the people here a passion about what they do Dave and I say you know we're going to get with Fred and here the founder story the prot chief product officer and all his folks because what they're building is the future generation Frank's Ludeman is a world-class CEO we heard the story of how he was hired you know Fred Letty said his keynote I wake up every day and I want to write code I don't want to be the CEO they hired Frank's luqman built a great business but not only do they have great business fundamentals and how they're executing their business plan Dave they have a great product leadership team the founder stays around every successful company that I talked to and i can highlight you look at them you name them all the ones that are the really sustainable companies Dave the founder stays around this is a lesson that the top VCS and Silicon Valley and around the world are now paying attention to is do not boot the founders out of the company marc andreessen with injuries Horowitz absolutely adamant founder friendly means growth and sustainability the old days of kick the founder out don't work ServiceNow is a great case study of a company that has grown from a seed idea go to market one booth at a show get some customers get some funding have a grade VC build a great product and continually to go to the next level and I think that's the story for us today what's the next level for service now what is that and you're going to see two major themes cloud born in the cloud capabilities asynchronous real-time presidents to enterprise grade enterprise-grade means you can't you can be born in the cloud and enterprise grade that's the Holy Grail Dave that is the key question people ask can you be enterprise-grade can you be agile can you have integrated stacks can you do stuff in real time and do it at a speed and at a scale that's the premise of the cloud and service now is delivering that so even my take on that so I mean you're talking about a cool tech behind it and there's a whole nother story here and Fred muddy and Dave right took us down memory lane today you know sort of the history of the company and going back to the original first knowledge and San Diego showed some pictures that was all fine and well and good but the fact is the piece that I want to add to what you just said is the customer angle I treated out yesterday Frank's lubin has made a career and identifying pain points and resolving those pain points essentially selling aspirin is what I call it and so that's what service now is doing there resolving the pain points within organizations it was interesting to note Dave right and Fred Lunney talked about how in 2008 when the economy was collapsing and Sequoia Capital you remember John put out that famous memo you better you hunker down conserve cash and Fred ludie showed the audience his counterpoint and basically it makes sense to me because what happened in 2008-2009 is people said let's let's start moving to the cloud more aggressively let's ship shift capex to op X and let's try to save money and service now is one of those technologies that really you know is all about saving money we kind of lived through that John right we were the open source version of information and so we have tons of demand around that time for our content service now in a whole different world saw uptick in demand and so they are really out solving customer problems dealing with process problems we're now seeing sort of the next wave the next evolution of that around email and how email is used as a workflow management system and is ineffective at that the hole forms business going to mobile and you saw today in the mobile apps it wasn't forms oriented it wasn't forms front and center forms is still there but it wasn't all about the forms it was all about the mobile experience so they're transitioning from this sort of forms based automation to one that's more mobile optimized that's something to talk to Fred yeah I think I think which day was your pointing out is is that the highlight of during a crisis at Fred Letty pointed out in OA at a critical inflection point of the company Sequoia Capital issued out a memo to all their portfolio come a little bit inside baseball but important to note that they said bunker down hunker down filled a bunker hoard your cash service now and this is where I love this company right they wrote a counter memo to their customers and the venture has a no no this is the winds are shifting we see an opportunity because their customers were going under or having financial problems they shifted their product value proposition to saving cash consolidation and creating an opportunity out of the crisis and I think this is the opportunity with cloud as you pointed out you seeing a transformation in workflows you're seeing a transformation in business process that is changing the game in terms of you know time to value cost structures and then the economics that's the promise of the cloud so again the companies that can take advantage of the times of the shifts and the inflection point because what's happening is the shift is happening and as an inflection point so yeah I think everybody talks about and it's so overused now seventy percent of the money that I t spends is on on keeping the lights on and and only thirty percent is on innovation I like to look it a little differently I like to break it down when i had my cio consultancy with floyer we used to consult and try to get the others to think about putting their portfolio into three categories their application portfolio in the project portfolio running the business growing the business in transforming the business and i think if you think about those things i think servicenow is very transformative and our helping companies run the business differently and grow the business as well so they're sort of fit into all three but they start with transformation and then change the way that people are running the business I think that's a much more effective way to look at that hole 7030 mix and I think service now is changing the way companies work what do you think about service now see earnings are we're out last week EMC report a little bit down VMware blew it away covering for emc you're seeing the big enterprise players service now take a big knife cut on Friday but that's Frank's lubin pointed out there in the long game and they have a platform play and they're throwing up a lot of cash so their cash flow is amazing Wall Street Journal has some articles about this kind of shift that we in a bubble is service now built for the long haul I want your opinion on this Frank subin weighed in on his and I think the software's phenomenal but let's talk about that yeah let's really his wall street not understanding about service so let's recap what happened on Friday service now announced earnings the stock had hit about a 12 billion dollar valuation which is you know sort of the highest valuation roughly that it had hit and people were getting used to service now continuingly continuously beating expectations well they met expectations actually beat by a little they had but they guided lower because of currency headwinds everybody's facing headwinds you saw EMC missed by about fifteen percent and it's you know this week and so all the companies and earnings releases are saying all right we're being more cautious because of currency fluctuations right the dollars getting stronger as a result you're translating international currency back into fewer dollars means less earnings so on an apples-to-apples basis servers now continued to blow it away they grew fifty percent plus but they guided lower they're a little bit more conservative so with the street did is they took about a billion dollars out of the valuation now since then it's come back a little bit it's not not come back to ten points to the loss but i see this john is a very very positive opportunity you said that you call it a buying opportunity i think it probably is you know who knows the markets choppy and maybe maybe you companies like service now that are high flyers you might see them you know up and down evan flow but here's the point and I think you've made this as well they are built for the long term and here's why they they started out in what everybody thought was a very small they've got a 40 to 50 billion dollar total available market that they're going after they're just scratching the surface right now they've got leading-edge technology they're killing the competition and they're growing into new places where typically these types of companies don't go the traditional IT service management folks where are they going they're automating service management not only with an IT but also within HR within finance within legal anything that's service oriented and their billet going after email if it's maybe it's be even bigger than a 40 or 50 billion dollar market so they got a big market they got great tech they got great management so I think there's a lot of room for this company to grow can they go to the collaboration space that's gonna be the question means all about email how much collaborative even ibn about competing with with this with companies like work they went all out HRM well well a CRM a Salesforce i think is a potential big competitor down the road i think they're on a collision course with force calm and Heroku and you know all those app development you know activities that those guys are doing but that's it's early there but I see that yeah damn your point about sales force this is why I think its dangers for sales forces why I think you know maybe we're kind of opening up the kimono here on service now because we're reading the tea leaves but what em what Amazon is done for the cloud and what we're doing with crouched at servicenow is doing for iit meaning they're building integrated technologies for a variety of different use cases that quite frankly it's it's enabling so sales forces cobbling together a bunch of stuff they got chatter I got this and when you put monolithic systems together and try to match them together into quote a you know fake stack that's really not going to work so I think the challenge for the incumbent companies like Salesforce and others is if you cobble together technologies and don't integrate them in there for this new real-time clouded native born in the cloud mentality and have the enterprise grade you will lose some territory so service now is doing both of those and they could take territory very quickly so they're humble saying no no we're not competing I know we got to go but last thing I'll say this frank says ITR our homies that's the Franks lupins you know so it talks about IT and the reason why I see that as a big advantages i T is the one part of the organization that has purview over the entire organization so a single cmdb with nit is very and whoever controls the data will be very interesting so real time having the data having the platform will give you a lot better horizontal platform I love what service now is doing again we're going to go this is our pep in by the way and this is not their messaging but we will probe all the guests Dave we're going to kick off date you this is our intro for day two wall-to-wall coverage when we hear all day here at in Las Vegas with service now nawlins 15 this is the cube I'm John for Dave vellante thanks for watching stay tuned and all day today thats is the cube we'll be right back after this short break

okay we're back here live at the IBM iod information on demand conference hashtag IBM iod this is the cube so looking the anglo Mookie bonds flagship program we go out for the events extracting from the noise i'm john furrier might join my co-host Davey lonte and we'd love to have analysts in here and in this case former analyst James Cole Beatles welcome to back to the cube thank you very much John thank you Dave pleasure see you again finger of being at IOD you're a thought leader you are an influencer you work at IBM so you you're out there the front lines doing some great work so thank you very much tell us explains the folks out there not about the show because we've had some people coming in last year you were private in but what does this fit what is this vector in context to what's relevant the market obviously big data and analytics is the hottest thing on the planet right now and you got social business now emerging categorically here but it has a couple different flavors to it right within IBM's context yeah but the messaging is simple right you got analytics that drives value outcomes social business is the preferred way of people going to operate their businesses engagement and all that is great stuff new channels marketing eccentric cetera explain to them how I OD is fitting into these megatrends into mega trends I think the hottest trends why our customers caring about what's going on here is a lot of a lot of activity around customers what is what does IOD fit into that a bigger picture yeah well you know the world has changed the world culture has changed radically and really in the last decade or so none is everywhere in the world everything is now online and digital increasingly it's streaming in terms of culture look what's happening to Hollywood is being deconstructed by the netflixs of the world you know movies and TV and music and everything is delivered online now all engagement more more engagements with your employer with your you know with merchants with your family everywhere is online things like streaming media so if you look at how the world culture has changed I yesterday I spoke here on a topic that's near and dear to my heart called big media it's the support of the ascendance of streaming media and not just the area as I laid out but in education like MOOCs distance learning we use it internally at IBM for our think fridays and Ginni Rometty and the executive team you know every Friday its cloud or its big data or whatever you know we need all need to get up to speed on the world culture has changed now analytics is fundamental to that whole proposition in terms of world culture analytics driving gagement analytics in terms of you know in a business context analytics a 360-degree view and you have data warehouses and the master data and you have predictive models to drive segmentation and target marketing and all that good stuff you know that's been in business for a long time that those set of practices they have become prevalent in most industries now not just in say retailing you know the Amazons of the world they're pervasive across all industries big data is fundamental to that you know engagement model its social social in the sense that social is one of many channels through which business is engaged with through which many people engage the social is assumed assuming a degree of importance in the fabric of modern life that goes beyond simple you know engagement with you know brands and whatnot social is how people create is how they declare who they are it's their identity and so social in your personal life we all know about Facebook and Twitter and everything else and YouTube but social has revolutionized enterprise cultures everywhere you know we use social internally of course we use our own Lotus connections most large and even many mid-sized firms now use social for interactions among employees or throughout their Val you chain so social business is about all of that it's the b2c it's the b2b it's the e2e and employ to employ all these different models of engagement they all demand a number of things obviously the social platform they demand the data of various sorts structured unstructured in shared repositories or cubes or Mars or whatnot they it demands the the big data platforms not only at respite in motion the streaming media to make it all happen in real time so at IOD if you see what the themes are this year and really it's been a building for several years cloud everything social is running in the cloud now more and more not just public Claus but Federation's of public and private clouds it's it's all about cognitive computing which is a relatively new term in the Sun sets achieved a certain amount of vogue in the last year or so which is really fundamentally as an evolutionary trend it's basically a I for the 21st century but leveraging unstructured data and and machine learning and so forth and predictive analytics and you know well the whole world learn what metadata was with the whole NSA yeah comments no it's like me and then just to wrap it up in memory real-time blu acceleration you know you need real-time you need streaming you need collaboration and social you know peer-to-peer user-generated content all of that to make this new world culture really take off and IBM provides all that we recognize that that's where the world's going we've been orienting reorienting all of our solutions around these models cloud social increasingly going forward and you know we provide solutions that enable our customers in all industries to go there and big data is fundamental to all of that as we say we're computer science meets social science that's always been Silicon angles kind of masthead view but to unpack what you just said from the market relevance you mentioned Netflix we saw Amazon coming out their own movie they're going to go direct with their own programming so so but that speaks to the direct business model of the web was originally pioneered as hey direct business model cut the middleman out but now that dimension has been explored so that kind of what you're saying there so that's cool the end user pieces interesting image is social so what's your take on the end user orientation what's the expectation because you got social you got a trash you got in motion you got learning machines providing great recommendations got the Watson kind of yeah reasoning for people so personalization recommendation engines the sea change attention time currency big days of all those buzzwords all right what is the expectation for users in the future right now we're moving into this new world where I can self serve myself monologue based the information from the web now it's all coming at everyone real time the alarms are going off as Jeff Jonas says what is that prefer user experience the direct business model people get that I think the business to see that but now the end users are now at the center of the value proposition how do what's the role of the user now they're participating in the media there are also consumers of the media yeah and they now have different devices so what's the sources of data so fundamentally yeah the role of the consumers expectations now is always everything is always on everything is always online everything is all digital everything is all real time and streaming everything is all self-service everything is all available in the palm of my hand and then the back-end infrastructure the cross-channel infrastructure users don't care about individual socials they really don't they don't really fundamentally care about Facebook or Twitter or whatever you have they just care that what their experience is seamless as they move from one channel to another they're not perceived as channels anymore they're simply perceived as places or communities that overlap too in a dizzying array of socials thus social is where we all live and thus social increasingly is mobile increasingly mobile is you know the user expects that the handoff from my smartphone to my tablet to my laptop to my digital TV sentence and so forth that it all happens through the magic of infrastructure that it's being taken care of and they don't have to worry about that handoff it all it's all part of one seamless experience yeah they always just say the search business it's the it's the it's the intersection of contextual and behavioral yeah and now you take that online behaviors community contextual is context to what people are interested at any given time yeah it's so many longtail distributions at any given time so do you see the the new media companies that the new brands that might emerge mean there's all the talk about Marissa Mayer kind of turning over yahoo and yeah she some say putting lipstick on a pig but but but is that they're just an old older branch trying to be cool but is that what users want just like media but just user experience me like we're small media but we got big ideas but the thing is the outcomes right small frying big blues go figure are the outcomes still the same company still want to drive sales for their business sell a product provide great value you just want to find great content and find people I mean the same concept of the old web search find out and run sumit give any vision on how that environment will evolve for a user like is it going to be pushed at me do you see it a new portal developing is mmm Facebook's kind of a walled garden humble don't care about that what's your take on that the future vision of a user experience online user experience online future vision in many ways I think let's talk about Internet of Things because that keeps coming more and more into the discussion it's it's not so much that the user wants a seamless experience across channel cross device all that but a big part of that experience is the user knows that increasingly they'll have some confidence that whatever environments physical environments there in our being obviously there's privacy implications that surveillance here are being monitored and tracked and optimized to meet their requirements to some degree in other words environmental monitoring internet of things in your smart home you want to configure so you smart home so that every room that you walk into is as you as you're moving there even before you get there has already been optimized to your needs that ideally there should prediction Oh Jim's walking into the bathroom so turn the light on and also start to heat up the water because it's ten o'clock at night Jim's usually takes his bath around this time you sort of want that experience to be handled by the internet of things like nest these new tools like nest oh yeah yeah so essentially then it's my user experience is not just me interacting with devices but me simply moving through environments that are continuously optimized to my knees and needs of my family you know the whole notion of autonomous vehicles your vehicle if it's your personal vehicle then you want to always autumn optimize the experience in terms of like you know the heat setting and and the entertainment justement saan the you know the media center and they're always to be tailored to your specific needs at any point in time but also let's say you take a zipcar you rent a zipcar and you've got an ID with that company or any of the other companies that provide those on-demand rental car services ideally in this scenario that whatever vehicle you you rent through them for a few hours or so when you enter it it becomes your vehicle is completely customized to your needs because you're a loyal customer of that firm and they've got your profile information this is just a hypothetical I'm not speaking to anything that I actually know about what they're doing but fundamentally you know ideally any on-demand vehicle or conveyance or other item that you you lease in this new economy is personalized to your needs while you're using it and then as it were depersonalized when you check it back in so the next person can have it personalized to their use as long as they need it that's the vision of a big part of the vision of customer experience management personalization not just of your personal devices but personalization of almost any device or environment in which you are operating so that's one kanodia wants this question no I would ask one more question on that on the user experience came on Twitter from a big data alex says while you're on the subject which a my Alex I don't great great friend of the cube but thanks for the tweet today we don't have our crowd shado-pan we can get the chat going there but why not talk about AR and I've been in reality I mean honestly Internet of Things is now not the palm of your hand it could be on your wrist or on your clothing the wearables on the glasses and just gave out three invites to google glass so this is again another edition augmented reality is software paradigm as well what is that what is it what does that fit into that what's your take on augmented reality augmented reality ok so augmented reality is that which I don't use myself I've just simply seen it demonstrated and plenty of places so augmented reality is all about layers of additional information overlaid on whatever visual video view or image view that you happen to be carrying with you or have available to you while you're walking around in your normal life so right now conceivably if this is an AR a setting that I would environment or enabled device I would be able to see for example that ok who's in this room in the sense that who is declared that they are in this area of Mandalay Bay right now and why specifically are they doing to the extent that they allow that information to be seen and o of these people here which of these people if any might be the person I'm going to be speaking with it for 30 so that if they happen to be in this environment i can see that i can see that they're to some degree they may have indicated status waiting for james could be a list to get done with the Wikibon people oh that's kind of cool so I'd see that overlay and I walk to other parts of the Convention Center I might also see overlays as I walk around like oh there's a course down as several rooms down that I actually put in my schedule it's going to start in about five minutes I'll just duck you into there because it reminds me through the overlay that's the whole notion of personalization of the environment in which you're walking around in real time dynamically and contextual in alignment with your needs or with your requirements are in alignment also with these whatever data those environment managers wish to share to anybody who's subscribing in that contact so that's a context-aware that theme have been talking about here on textual essentially it's a public space that's personalized to your needs in the sense that you have a personalized view in a dynamically update okay that sounds like crowd chat Oh are we running a trip crouched at right now crouch at San overlay so just as lovely overlay so look to the minute social network yeah tailored to the needs of the group yep that adds value on top of that data yeah so James I gotta get your take on something so we had Merv on yesterday great Adrian with my great Buy analyst day and he was on last week at Big Data NYC you know we did our own little vent there Don coincident with hadoop world so Murph said well we're just entering the trough of disillusionment for big data yeah you love those Gartner you know I love medications tools I mean they are genius and I get him but he said that's a good thing because it goes left to right so we're making progress here ok right but I'm getting nervous the internet of things I love the concept we don't we don't work on industrial internet and you know a smarter planet it's in there so I love it but I'm getting nervous here's why I look back at a lot of the promises that were made in the BI days 360-degree other business predictive analytics a lot of things that are now talking about in the hood sort of Hadoop big data movement that we're actually fulfilling with this new wave that the old wave really wasn't able to fill because the cousin sort of distracted doing sarbanes-oxley and reporting in and balanced scorecards so so I'm nervous he's old school now it when he when he referenced is something that was hot in the mid part of the two thousand decade okay go ahead okay we had a guy on today talking about balance core would you know we're just talking about crowd chat that's the hottest day in 2013 like five years or hurt anybody mentions sarbanes-oxley so what kind of saved that whole business Roy thank you and Ron but so heavy right so what I'm nervous about as we as I've seen a number of waves over the years where the the vendor community promises a vision great vision great marketing and then all of a sudden something hotter comes along like Internet of Things and says don't know this is really it so my question to you is will help us it'll help me in my mind you know close that dissonance gap is are these two initiatives the sort of big data analytics for everybody putting analytics in the hands of business users yeah or is that sort of complementary to the internet of thing his internet of things just the new big trillion dollar market that everybody's going to go after and forget about all those promises about analytics everywhere help me sure Jay through that my job is to clarify confusion hey um you know if you look at the convergence of various call them paradigms there's a lot of big data analytics is one of them right now clearly there's cloud clearly their social there's big data analytics in mobile and there's something called Internet of Things so some some talk about smack smac social mobile analytic a que a big data cloud if you add IOT of there it's smack yet I don't think it works or smash yet but fundamentally if you think about Internet of Things it's it's all about machines or automated devices of various sorts probes and you know your smartphone and whatever I know servers or even you know the autonomous vehicles those are things that do things and you know they might be sources of data they would are they might be consumers of data they might conceivably even be intermediaries or brokers or routers or data what I'm getting at is that if you look at big data analytics I always think of it as a pipeline all data it's like data sources and data consumers and then there's all these databases and other functions that operate between them to move data and analytics and insight from one end to the other of the pipe in a conceptual way think of the internet of things as well a new category of sources of data these devices whether they be probes or monitors or your smart phones and new consumers and they all those same things are probably going to be many of them consumers of data and there's message passing among them and then the data that they passed might be passed in real time through streaming like InfoSphere streams it might be cached or stored and various intermediate databases and various analytics performed on them so think of you know I like to think of the internet of persons places and things persons that's human endpoints consumers and and sources of data that's all of us that's social places that's geospatial you know you think about it the Internet of geospatial you know geo spatial coordinates of of data and analytics and then there's things there's you know automated endpoints or you know hardware even Nana from macro to nano devices so it's just a new range of sources and and consumers of data and new types of analytics that are performed in new functions that can be performed and outcomes enable when you as it were stack in and out of things with social with claw with mobile new possibilities in terms of optimization in real time it throughout the you know the smarter planet if you think about the smarter planet vision it's all about interconnected instrumented and intelligent instrumented you know instrumentation that traditionally it suggests hardware instrumentation that's what probes our sensors and actuators that's the Internet of Things it's a fundamental infrastructure within smarter planet I'd love that thank you for clarifying i could write a blog post out of that and i think i'm very well made so um now i want to follow up and bring it back to the users I know snack and I thought you were going to say a story no smack MapReduce analytics and query or sell smack on the cube so so I want bring it back to the users so we had a great conversation yesterday actually last week I'll be met it was on off you know ah be met and he said look why are there any any you know where all the big data apps he said you need three things to for big data apps you need domain expertise you need algorithms which are free and you need data scientists like oh we'll never get there all right oh so rules really free while there are that was this argument yeah it means a source if people charge him for algorithms big trouble was this point I think okay sure so and then we had a discussion yesterday about how in the early days of the automobile industry you know the forecast was this is problematic the gap to adoption is just aren't enough chauffeurs know the premise that we were putting forth in the discussion yesterday I don't know who that was with was that with Judith it was good was that look we've got to figure out a way to get analytics in the hands of the business user we can't have to go through a data scientist or some business analyst no that's not going to work and we'll never get adoption so what what's going to bridge that gap is it is it the things you talked about before all these you know cool solutions that you guys are developing the project neo that you announce today visualization yeah there's another piece of that what puts it in the hands of guys like me that I can actually use the data in new and productive ways yeah well self-service business intelligence and visualization tools that are embedded in the very experience of using apps for example on your smartphone democratization of data science down to all of us you need the right tools you need you need the tools that the new generation of people like my children's generation just adopt and they work in there just a tune from from the cradle to working with data and visualizations and creating visual you know analytics of various sorts though they may not perceive it as being analytics they miss may perceive it as working with shapes and patterns and stuff yeah you would stop yeah so playing around you know in a sandbox i love that terminology data scientists working you know sandboxes which is data that's martes that they build to do regression analysis and segmentation and decision trees and all you know all that good stuff you know the fact is your sandbox can conceivably be completely on your handheld device with all the visualizations built-in you're simply doing searches and queries you know you're asking natural language questions you're looking at the responses you're changing your queries you're changing your visualizations and so forth to see if anything pops out at you as being significant playing around it you know it's as simple a matter that that these kinds of tools such as IBM you know cognos and so forth enable everybody to become as it worried a data scientist without having to you know become a maquette their profession it's just a part of the fabric of living in modern society where data surrounds us people are going to start playing with data and they're going to start teaching themselves all these capabilities in the same way that when they invented automobiles and you know wasn't Henry 42 invented them it was in like the late 1800s by engineers in Europe and America you know it's like we didn't all become auto mechanics you know there are trained auto mechanics but I think most human beings in the modern world know that there's a thing called an automobile that has an engine that needs gasoline and oil and occasionally needs to be brought to a professional mechanic for a repair and so forth we have many of us have a rough idea of something called a carburetor blah blah blah you know in the same way that when computers came up after world war two and then gradually invaded our lives through PCs and everything we all didn't become computer scientist but most of us have an idea of what a hard disk is most of it no most of us know something about something called software and things are called operating systems in the same way now in this new world most of us will become big data analytics geeks practical into the extent that will learn enough of the basic terms of art and the relationships among the various components to live our lives and when the stuff breaks down we call the likes of IBM to come and fix it or better yet they just buy our products and they just work magically all the time without fail conversing and comfortable with the concepts to the point which you can leverage them and what about visualization where does that fit visualization visualization is where the rubber meets the road of analytics is it's where human beings how human beings extract meaning insight fundamentally maybe that's like yeah you extracted inside a lots of different ways you do searches and so forth but to play around it to actually see you know a heat map or a geospatial map or or or you know a pie chart or whatever you see things with your eyes that you may not have realized we're there and if you can play around and play with different visualizations against the same data set things will pop out that you know the statistical model just seek the raw output of a data mining our predictive model or statistical analysis those patterns may not suggest themselves and rows of numbers that would pop out to an average human being or to a data scientist they need the visualizations to see things that you know because in other words when you think about analytics it's all about the algorithms that are drilling through the data to find those patterns but it's also about the visualizations the algorithms and you need the visualizations and of course you need the data to really enable human beings of all levels of expertise to find meaning and fundamentally visualizations are a lingua franca between non-expert human beings and expert eamon beings between data scientists visualizations are a lingua franca Hey look what I saw what do you think you know that's the whole promise of tools like concert for example we demonstrated this this morning it's a collaborative environment as sharing of visualizations and data sets and so forth among business analysts and the normal knowledge worker you know it with it you know like what do you see here's what I see what do you think I don't see that here's another visualization what do you see there oh yeah I think I see what you mean and here's my annotation about what I have broader context I've you know here's what I oh this is great that's the whole notion of humans deriving insight we derive it in socials we derive it in teams of that some Dave might be adept at seeing things that Jim is just absolutely blind to or you know Nancy might see things that both of us are applying to but we're all looking at the same pictures and we're all working with the same data part art yeah it's all so let's talk about some plumbing conversations you know one of the things that we noticed we were at the splunk conference this year's blown came out of nowhere taking log files making them manageable saving time for people so the thing that comes out of the splunk conversation is that it's just so easy to use that their customer testimonials are overwhelmingly positive around the area hey I just dumped my data into this the splunk box and it grid good stuffs happening I can search it it can give me insight save me time so that's the kind of ease of use so so how does IBM getting to that scenario because you guys have some good products we've got on the platform side but you also have some older products legacy Lotus other environments collaborative software that's all coming together in converging so how do we get to that environment where it's just that he just dumped your data in and let it do its magic well Odin go that's the very proposition that we provide with our puresystems puredata systems portfolio tree data system and big insights right for Hadoop so forth big in size you know we have an appliance now yeah we have pdh so that's the whole create load and go scenario that because Bob pidgeotto unless wretched and others demonstrated on the main stage yesterday and today so we did we do that and we are simple and straight being easy to use and so forth that's our value prop that's the whole value prop of an appliance you know simple you don't need a ton of expertise we pre build all the expert in a expertise patterns that you can use to derive quick value from this deployment we provide industry solution accelerates from machine data analytics on top of big insights to do the kinds of things you're talking about with splunk offerings so fundamentally you know that's scenario we all we and we're you know we have many fine competitors we offer that capability now in terms of the broader context you're describing we're a well-established provider of solutions we go back more than a hundred years we have many different product portfolios we have lots and lots of customers who would invested in IBM for a long time they might have our older products our newer products in various combinations we support the older generations we strive to migrate our customers to the newer releases when they're ready we don't force them to migrate so we make very we're very careful in our row maps to provide them with a migration path and to make it worth their while to upgrade when the time comes to the newer feature ok so I got it don't change gears to the to the shiny new toy conversation which is you know you know we love that in Silicon Valley what's a shiny new toy there's always an emerging markets when you have see changes like this where there's a whole the new whole new wave comes in creates new wealth old gets destructed new tags over whatever the conversation goes but I got to ask you okay well Elsa to the IBM landscape that you that you're over overlooking with big data and under the under the hood with cloud etc there's always that one thing that kind of breaks out as the leader the leading toy a shiny object that that people gravitate to as as I'm honest I won't say lost later because you got you know it's not not about giving away free it's it's the product that goes well we this is the lead horse you know and in this game right yeah so what is that what is the IBM thing right now that you're doubling down on is it blu acceleration is it incites is it point2 with a few highlights right now that's really cutting through the new the new the new soil of yeah we're developing our own rip off version of google glass thank you know I'm saying it's always I mean I'm gonna say shiny too but there's always that sexy product well I want that I want L customers name I want that product which leads more you know how she lifts for other products is there one is there a few you can talk about that you've noticed anecdotally is going to be specific data but just observational a shiny toy for the consumer market or for the business business business mark okay yeah yeah is it Watson is Watson the draw is it what's the headline looking for the lead lead dog here what's the attack there's always one an emerging market well you can put your the spot here well you could say that the funny thing is the whole notion of a shiny new toy implies something tangible when the world is gone more and more intangible in the cloud so we are moving our entire portfolio beginning links the big data analytics solutions into the cloud cloud first development going forward our other core principles for the pure data systems portfolio and the light for the shiny the shiny new thing the new cons could be shiny new concept or new paradigm yeah but the shiny new thing is the cloud the cloud is something pervasive and the cloud is something that it really multi form factors that's not very sexy but customers want flexibility you know they want to acquire the same functionality either as a licensed software package and running on commodity hardware we offer that for our big data analytics offerings or as an appliance and one sort or another that specialized particular occurrence or as a SAS cloud offering or as a capability that they can deploy in a virtualization layer on top of IBM or non-ibm hardware or they want the abilities you can mix and match those various deployment form factors so in many ways the whole notion of multi form factor flexibility is the shiny new thing it's the hybrid model for deployment of these capabilities on Prem in the cloud combination thereof that's not terribly sexy because it's totally it's totally abstract but it's totally real I mean demand wise people can see them that drives my business because when you go to the cloud I mean that's where you can really begin to scale seriously beyond the petabytes the whole notion of big media it will exist entirely in the cloud big media I like to think is the next sexy thing because streaming is coming into every aspect of human existence where stream computing a lot of people who focus on Big Data think of volume as being like big headline oh god we'd go to petabytes and exabytes and all that yeah it's important some really fixate on variety all these disparate sources of data and now we have all the sensor data and that's very important we have all the social media and everything all those new sources that's extremely important but look at the velocity everybody is expecting real-time instantaneous continuous streaming you know everything we do all of our entertainment all of our education surveillance you know everything is completely streaming I think ubiquitous streaming to every device and everybody themselves continue to continuing to stream their very lives everywhere all the time is the sexy new thing Dave and I talk about running data we coined that term running data what four years ago so I got to get you got to get kind of a thought leader they're watching us and we're watching streaming data right now from these said these are your guys are streaming this is big media give us some wanna get your thought leader perspective here some thought leader mojo around um the hashtag data economy you know you need now you're moving into a conversation with c-level folks and they said James tell me what the hell is this data economy thing right so what is the data economy in your words kind of like I mean I'll say it's a mindset I'll everything else what's your take on that we've been discussing that internally and externally at IBM we're trying to get our heads around what that means here's my take as one IBM are one thought Leigh right by the way the trick of being a thought leader is just to let your own thoughts lead you where they will turn around where all my followers yeah hopefully they want to lead you to far astray where you're out in the wilderness too long that's an important type of people are talking about because people are trying to put the definition around at economy can you actually have a business construct around yeah data here is my taken on the layers of the meaning of data economy it's monetizing your data the whole notion of monetization of your data data becomes a product that you generate internally or that you source from externally but you repackage it up and then resell with value add the whole notion of data monetization and you know implies a marketplace for data based products you know when I say data I'm using it in the broader context of it could be streaming media as the kind of one is a very valuable category of you know data like you know whatever kollywood provides so there's a whole notion of monetizing your data or providing a marketplace for others to monetize their data and you take a transaction fee from that or it also means in more of a traditional big data or data warehousing bi sense it means that you drive superior outcomes for your your own business from your own data you know through the usual method of better decision if better decisions on trustworthy data and the like so if you look at data monetization in terms of those layers including the marketplace including you know data-driven okay in many ways the whole notion of a data economy hinges on everybody's realization now that the chief resource for betterment of humanity one of the chief resources going forward for us to get smarter as a species on this planet is to continue to harness the data that we ourselves generate you know people stop what data is being the new oil what oil was there before we ever evolved but data wasn't there before we we landed on earth or before we evolved we generate that so it's our own exhaust your own exhaust that's actually a renewable resource data exhaust from data from exhausted gold that's what we say data is the data exhaust it's good if you can harness it and put it together as Jeff Jones says the puzzle piece is the picture the big picture at the smarter picture the smarter planet so on the final question I want to wrap up here to our next guest but what's going on with you these days talk about what's up with you you know you're very active on Facebook will you give a good following I'll be coming up what's happening you know I'll make sure I said big birthday for you on your Facebook page what's going on in your life I'll see you're working at IBM one of the things are interesting what's on your mind these days when you're at leisure are you hanging out you think what are you thinking about the most what are you doing with your you know things with your family's cherith let's see what's going on well I hang out at home with my wife and drink beer and listen to music and tweet about it everybody knows that stuff kind of beer do you drink whatever is on sale I'm not going to say where we buy it but it's a very nice place that whose initials are TJ but fundamentally you know my my mind is an open book because I evangelize I put my thoughts and my work thoughts and love my personal thoughts out there on socials I lived completely ons but I completely unsocial I self-edit but fundamentally the thought leadership I produce that the blogs and whatnot I produce all the time I put them out there for general discussion and I get a lot of good sort of feedback the world and including from inside of IBM I just try to stretch people's minds what's going on with me I'm just enjoying what I'm doing for a living now people save Jim you're with IBM why aren't you an analyst I'm still doing very analyst style work in in a vendor context I'm a thought leader I was a thought leader as I try to be being a thought leader is like being a humorist it's like it's a statement of your ambition not your outcome or your results yeah you can write jokes too you're blue in the face but if nobody laughs then you're not a successful comedian likewise i can write thought leadership pieces till I'm blue in the face but if nobody responds that I'm not leaving anybody anywhere i'm just going around in circles so my my ambition and every single day is to say at least one thing that might stretch somebody's box a little bit wider yeah yeah I think I think IBM smart they've been in social for a while the content markings about you know marketing to individuals yeah with credibility so I love analysts I love all my buds like like Merv and everybody else and I'm you know sort of a similar cat but you know there's a role for X analysts inside of solution providers and we have any number John Hegarty we have we have Brian Hill another X forest to write you know it's it's a you know it's a big industry but it's a small industry we have smart people on both sides of the equation solution provider and influencer my line um under people 99 seats and you know I I suck up to my superiors at IBM i suck up to any analyst who says nice things about me and hosts be on their show and i was going out of my life i'm just a big suck up well we like we like to have been looking forward to doing some crowd chats with you our new crouch an application with you guys lock you into that immediately it's a thought leader haven that the Crouch as as it turns out Dave what's your take on the analyst role at IBM just do a little analysis of the analyst at IBM which you're taken well I think it's under situation I think that the role that they that IBM's put James in is precisely the way in which corporations vendors should use former analysts they should give you a wide latitude a platform and and not try to filter you you know and you're good like that and so guess what I do the usual marketing stuff to the traditional but I do the new generation of thought leadership marketing and there's a role for both of those to me marketing have said this is if I said it was I said a hundred times marketing should be a source of value to people and it's so easy to make marketing a source of value by writing great content or producing great content so yeah that's my take on a jonathan your your marketing is a great explainer you explain the value to the market and thereby hopefully for your company generate demand hopefully in the direction of your cut your customers buying your things but that's what analysts the influencers should be explainers it's you know probably Dave I mean has influenced as influences that we are with with a qu here's my take on it when you have social media of direct full transparency there's no you can't head fake anyone anymore that all those days are gone so analyst bloggers people who are head faking a journalist's head faking the house the audiences will find out everything so to me it's like it's the metaphor of when someone knocks on your door your house and you open it up and they want to sell you something you shut the door in their face when you come in there and they say hey I want to hang out I got you know I got some free beer and a big-screen TV you want to watch some football maybe you invite him in the living room so the idea of communities and direct marketing's about when if you let them into your living room yeah you're not selling right you are creating value see what i do i drop smart i try to drop smart ideas into every conversational contacts throughout socials and also at events like i od so you know a big part of what I do is I thought leadership marketer is not just right you know you're clever blogs and all that but I simply participate in all the relevant conversations where I want I want ideas to be introduced and oh by they want way I definitely want people to be aware that I am an IBM employee and my company's provides really good products and services and support you know that's really a chief role of an evangelist in a high-tech slider that's one of the reasons why we started crouched at because the hashtag get so difficult to go deep into so creates crowd chatter let's go deeper and have a conversation and add some value to it you know it's you thinking about earned media as parents been kicked around but in communities the endorsement of trust earning a position whether you work at IBM people don't care a he works at IBM or whatever if you're creating value and you maybe have some free beer you get an entry but you win on your own merits you know I'm saying at the end of the day the content is the own merits and I think that's the open source paradigm that is hitting the content business which is community marketing if your pain-in-the-ass think you're going to get bounced out right out of the community or if you're selling something you're on so you guys do a great job really am i awesome you thank you James I really love what you add to the iod experience here with this corner and all the interviews is great great material well thanks for having us here really appreciate it I learned a lot it's been great you guys are great to work with very professional the products got great great-looking luqman portfolio hidden all hitting all the buttons there so hitting all the Gulf box so this is the cube we'll be right back with our last interview coming up shortly with Jeff Jonas he's got some surprises for us so we'll we'll see what he brings brings to his a game apparently he told me last night is bring his a-game to the cube so I'm a huge Jeff Jonas fan he's a rock star we love them on the cube iza teka athlete like yourself we write back with our next guest after this short break