welcome back to thecube's live coverage coming to you from the big apple in new york city we're talking all things aws summit but right now i've got two powerhouses you know them you love them john furrier dave vellante going to be talking about super cloud guys we've been talking a lot about this there's a big event coming up on the cube august 9th and i gotta start dave with you because we talk about it pretty much in every interview where it's relevant why super cloud yeah so john furrier years ago started a tradition lisa prior to aws which was to lay down the expectation for our audiences what they should be looking for at aws reinvent okay john when did that start 2012 2013. actually 2013 was our first but 2015 was the first time when we get access to andy jassy who wasn't doing any briefings and we realized that the whole industry started looking at amazon web services as a structural forcing function of massive change uh some say inflection point we were saying complete redefinition so you wrote the trillion dollar baby yeah right which actually turns into probably multi-trillion dollars we got it right on that one surprisingly it was pretty obvious so every year since then john has published the seminal article prior to reinvent so this year we were talking we're coming out of the isolation economy and john hedwig also also adam silevski was the new ceo so we had a one-on-one with adam that's right and then that's where the convergence between andy jassy and adam celebski kicked in which is essentially those guys work together even though they he went off and boomerang back in as they say in aws but what's interesting was is that adam zluski's point of view piggyback jassy but he had a different twist yeah some so you know low you know people who didn't have really a lot of thought into it said oh he's copying microsoft moving up the stack we're like no no no no no something structural is happening again and so john wrote the piece and he started sharing it we're collaborating he said hey dave take a take a look add your perspectives and then jerry chen had just written castles in the cloud and he talked about sub-markets and we were sort of noodling and one of the other things was in 2018 2019 around that time at aws re invent there was this friction between like snowflake and aws because redshift separated compute from storage which was snowflake's whole thing now fast forward to 2021 after we're leaving you know the covert economy by the way everyone was complaining they are asking jassy are you competing with your ecosystem the classic right trope and then in in remember jason used to use cloudera as the example i would like to maybe pick a better example snowflake became that example and what the transition was it went from hey we're kind of competitive for sure there's a lot of examples but it went from we're competitive they're stealing our stuff to you know what we're making so much money building on top of aws specifically but also the clouds and cross clouds so we said there's something new happening in the ecosystem and then just it popped up this term super cloud came up to connote a layer that floats above the hyperscale capex not is it's not pass it's not sas it's the combination of the of those things on top of a new digital infrastructure and we chose the term super cloud we liked it better than multi-cloud because multiplayer at least one other point too i think four or five years earlier dave and i across not just aws reinvent all of our other events we were speculating that there might be a tier two cloud service provider models and we've talked with intel about this and others just kind of like evaluating it staring at it and we met by tier two like maybe competing against amazon but what happened was it wasn't a tier two cloud it was a super cloud built on the capex of aws which means initially was a company didn't have to build aws to be like aws and everybody wanted to be like aws so we saw the emergence of the smart companies saying hey let's refactor our business model in the category or industry scope and to dominate with cloud scale and they did it that then continued that was the premise of chen's post which was kind of rift on the cube initially which is you can have a moat in a castle in the cloud and have a competitive advantage and a sustainable differentiation model and that's exactly what's happening and then you introduce the edge and hybrid you now have a cloud operating model that that super cloud extends as a substrate across all environments so it's not multi-cloud which sounds broken and like put it distance jointed joint barriers hybrid cloud which is the hybrid operating model at scale and you don't have to be amazon to take advantage of all the value creation since they took care of the capex now they win too on the other side because because they're selling ec2 and storage and ml and ai and this is new and this is information that people don't might not know about internally at aws there was a debate dave okay i heard this from sources do we go all in and compete and just own the whole category or open the ecosystem and coexist with [ __ ] why do we have these other companies or snowflake and guess what the decision was let's make it open ecosystem and let's have our own offerings as well and let the winner take off smart because they can't hire enough people and we just had aws and snowflake on the cube a few weeks ago talking about the partnership the co-op petition the value in it but what's been driving it is the voice of the customer but i want to ask you paint the picture for the audience of the critical key components of super cloud what are those yeah so i think first and foremost super cloud as john was saying it's not multi-cloud chuck whitten had a great phrase at dell tech world he said multi-cloud by default right versus multi-cloud by design and multi-cloud has been by default it's been this sort of i run in aws and i run my stack in azure or i run my stack in gcp and it works or i wrap my stack in a container and host it in the cloud that's what multi-cloud has been so the first sort of concept is it's a layer that that abstracts the underlying complexity of all the clouds all the primitives uh it takes advantage of maybe graviton or microsoft tooling hides all that and builds new value on top of that the other piece of of super cloud is it's ecosystem driven really interesting story you just told because literally amazon can't hire everybody right so they have to rely on the ecosystem for feature acceleration so it's it also includes a path layer a super pass layer we call it because you need to develop applications that are specific to the problem that the super cloud is solving so it's not a generic path like openshift it's specific to whether it's snowflake or [ __ ] or aviatrix so that developers can actually build on top of and not have to worry about that underlying and also there's some people that are criticizing um what we're doing in a good way because we want to have an open concept sure but here's the thing that a lot of people don't understand they're criticizing or trying to kind of shoot holes in our new structural change that we're identifying to comparing it to old that's like saying mainframe and mini computers it's like saying well the mainframe does it this way therefore there's no way that's going to be legitimate so the old thinking dave is from people that have no real foresight in the new model right and so they don't really get it right so what i'm saying is that we look at structural change structural change is structural change it either happens or it doesn't so what we're observing is the fact that a snowflake didn't design their solution to be multi-cloud they did it all on aws and then said hey why would we why are we going to stop there let's go to azure because microsoft's got a boatload of customers because they have a vertically stacking integration for their install base so if i'm snowflake why wouldn't i be on azure and the same for gcp and the same for other things so this idea that you can get the value of an amp what amazon did leverage and all that value without paying for it up front is a huge dynamic and that's not just saying oh that's cloud that's saying i have a cloud-like scale cloud-like value proposition which which will look like an ecosystem so to me the acid test is if i build on top of say [ __ ] or say snowflake or super cloud by default i'm either a category leader i own the data at scale or i'm sharing data at scale and i have an ecosystem people are building on top of me so that's a platform so that's really difficult so what's happening is these ecosystem partners are taking advantage as john said of all the hyperscale capex and they're building out their version of a distributed global system and then the other attribute of super cloud is it's got metadata management capability in other words it knows if i'm optimizing for latency where in the super cloud to get the data or how to protect privacy or sovereignty or how many copies to make to have the proper data protection or where the air gap should be for ransomware so these are examples of very specific purpose-built super clouds that are filling gaps that the hyperscalers aren't going after what's a good example of a specific super cloud that you think really articulates what you guys are talking about i think there are a lot of them i think snowflake is a really good example i think vmware is building a multi-cloud management system i think aviatrix and virtual you know private cloud networking and for high performance networking i think to a certain extent what oracle is doing with azure is is is definitely looks like a super cloud i think what capital one is doing by building on to taking their own tools and and and moving that to snowflake now that they're not cross-cloud yet but i predict that they will be of i think uh what veeam is doing in data protection uh dell what they showed at dell tech world with project alpine these are all early examples of super well here's an indicator here's how you look at the example so to me if you're just lifting and shifting that was the first gen cloud that's not changing the business model so i think the number one thing to look at is is the company whether they're in a vertical like insurance or fintech or financial are they refactoring their spend not as an i.t cost but as a refactoring of their business model yes like what snowflake did dave or they say okay i'm gonna change how i operate not change my business model per se or not my business identity if i'm gonna provide financial services i don't have to spend capex it's operating expenses i get the capex leverage i redefine i get the data at scale and now i become a service provider to everybody else because scale will determine the power law of who wins in the verticals and in the industry so we believe that snowflake is a data warehouse in the cloud they call it a data cloud now i don't think snowflake would like that dave i call them a data warehouse no a super data cloud but but so the other key here is you know the old saying that andreessen came up with i guess with every company's a software company well what does that mean it means every company software company every company is going digital well how are they going to do that they're going to do that by taking their business their data their tooling their proprietary you know moat and moving that to the cloud so they can compete at scale every company should be if they're not thinking about doing a super cloud well walmart i think i think andreessen's wrong i think i would revise and say that andreessen and the brain trust at andreas and horowitz is that that's no longer irrelevant every company isn't a software company the software industry is called open source everybody is an open source company and every company will be at super cloud that survives yeah to me to me if you're not looking at super cloud as a strategy to get value and refactor your business model take advantage of what you're paying it for but you're paying now in a new way you're building out value so that's you're either going to be a super cloud or get services from a super cloud so if you're not it's like the old joke dave if you're at the table and you don't know who the sucker is it's probably you right so if you're looking at the marketplace you're saying if i'm not a super cloud i'm probably gonna have to work with one because they're gonna have the data they're gonna have the insights they're gonna have the scale they're going to have the castle in the cloud and they will be called a super cloud so in customer conversations helping customers identify workloads to move to the cloud what are the ideal workloads and services to run in super cloud so i honestly think virtually any workload could be a candidate and i think that it's really the business that they're in that's going to define the workload i'll say what i mean so there's certain businesses where low latency high performance transactions are going to matter that's you know kind of the oracle's business there's certain businesses like snowflake where data sharing is the objective how do i share data in a governed way in a secure way in any location across the world that i can monetize so that's their objective you take a data protection company like veeam their objective is to protect data so they have very specific objectives that ultimately dictate what the workload looks like couchbase is another one they they in my opinion are doing some of the most interesting things at the edge because this is where when you when you really push companies in the cloud including the hyperscalers when they get out to the far edge it starts to get a little squishy couchbase actually is developing capabilities to do that and that's to me that's the big wild card john i think you described it accurately the cloud is expanding you've got public clouds no longer just remote services you're including on-prem and now expanding out to the near edge and the deep what do you call it deep edge or far edge lower sousa called the tiny edge right deep edge well i mean look at look at amazon's outpost announcement to me hp e is opportunity dell has opportunities the hardware box guys companies they have an opportunity to be that gear to be an outpost to be their own output they get better stacks they have better gear they just got to run cloud on it yeah right that's an edge node right so so that's that would be part of the super cloud so this is where i think people that are looking at the old models like operating systems or systems mindsets from the 80s they look they're not understanding the new architecture what i would say to them is yeah i hear what you're saying but the structural change is the nodes on the network distributed computing if you will is going to run hybrid cloud all the way across the fact that it's multiple clouds is just coincidence on who's got the best capex value that people build on for their super cloud capability so why wouldn't i be on azure if microsoft's going to give me all their customers that are running office 365 and teams great if i want to be on amazon's kind of sweet which is their ecosystem why wouldn't i want to tap into that so again you can patch it all together in the super cloud so i think the future will be distributed computing cloud architecture end to end and and we felt that was different from multi-cloud you know if you want to call it multi-cloud 2.0 that's fine but you know frankly you know sometimes we get criticized for not defining it tightly enough but we continue to evolve that definition i've never really seen a great definition from multi-cloud i think multi-cloud by default was the definition i run in multiple clouds you know it works in azure it's not a strategy it's a broken name it's a symptom right it's a symptom of multi-vendor is really what multi-cloud has been and so we felt like it was a new term of examples look what we're talking about snowflake data bricks databricks another good one these are these are examples goldman sachs and we felt like the term immediately connotes something bigger something that sits above the clouds and is part of a digital platform you know the people poo poo the metaverse because it's really you know not well defined but every 15 or 20 years this industry goes through dave let me ask you a question so uh lisa you too if i'm in the insurance vertical uh and i'm a i'm an insurance company i have competitors my customers can go there and and do business with that company and you know and they all know that they go to the same conferences but in that sector now you have new dynamics your i.t spend isn't going to keep the lights on and make your apps work your back-end systems and your mobile app to get your whatever now it's like i have cloud scale so what if i refactored my business model become a super cloud and become the major primary service provider to all the competitors and the people that are the the the channel partners of the of the ecosystem that means that company could change the category totally okay and become the dominant category leader literally in two three years if i'm geico okay i i got business in the cloud because i got the app and i'm doing transactions on geico but with all the data that they're collecting there's adjacent businesses that they can get into maybe they're in the safety business maybe they can sell data to governments maybe they can inform logistics and highway you know patterns roll up all the people that don't have the same scale they have and service them with that data and they get subscription revenue and they can build on top of the geico super insurance cloud right yes it's it's unlimited opportunity that's why it's but the multi-trillion dollar baby so talk to us you've done an amazing job of talking which i know you would of why super cloud what it is the critical components the key workloads great examples talk to us in our last few minutes about the event the cube on super cloud august 9th what's the audience going to who are they going to hear from what are they going to learn yeah so august 9th live out of our palo alto studio we're going to have a program that's going to run from 9 a.m to 1 p.m and we're going to have a number of industry luminaries in there uh kit colbert from from vmware is going to talk about you know their strategy uh benoit de javille uh from snowflake is going to is going to be there of g written house of sky-high security um i i i don't want to give it away but i think steve mullaney is going to come on adrian uh cockroft is coming on the panel keith townsend sanjeev mohan will be on so we'll be running that live and also we'll be bringing in pre-recorded interviews that we'll have prior to the show that will run post the live event it's really a pilot virtual event we want to do a physical event we're thinking but the pilot is to bring our trusted friends together they're credible that have industry experience to try to understand the scope of what we're talking about and open it up and help flesh out the definition make it an open model where we can it's not just our opinion we're observing identifying the structural changes but bringing in smart people our smart friends and companies are saying yeah we get behind this because it has it has legs for a reason so we're gonna zoom out and let people participate and let the conversation and the community drive the content and that is super important to the cube as you know dave but i think that's what's going on lisa is that it's a pilot if it has legs we'll do a physical event certainly we're getting phones to bring it off the hook for sponsors so we don't want to go and go all in on sponsorships right now because it's not about money making it's about getting that super cloud clarity around to help companies yeah we want to evolve the concept and and bring in outside perspectives well the community is one of the best places to do that absolutely organic it's an organic community where i mean people want to find out what's going on with the best practices of how to transform a business and right now digital transformation is not just getting digitized it's taking advantage of the technology to leapfrog the competition so all the successful people we talked to at least have the same common theme i'm changing my game but not changing my game to the customer i'm just going to do it differently better faster cheaper more efficient and have higher margins and beat the competition that's the company doesn't want to beat the competition go to thecube.net if you're not all they're all ready to register for the cube on supercloud august 9th 9am pacific you won't want to miss it for john furrier and dave vellante i'm lisa martin we're all coming at you from new york city at aws summit 22. i'll be right back with our next guest [Music] you

>> From theCUBE studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Snowflake Summit 2022 underscored that the ecosystem excitement which was once forming around Hadoop is being reborn, escalated and coalescing around Snowflake's data cloud. What was once seen as a simpler cloud data warehouse and good marketing with the data cloud is evolving rapidly with new workloads of vertical industry focus, data applications, monetization, and more. The question is, will the promise of data be fulfilled this time around, or is it same wine, new bottle? Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this "Breaking Analysis," we'll talk about the event, the announcements that Snowflake made that are of greatest interest, the major themes of the show, what was hype and what was real, the competition, and some concerns that remain in many parts of the ecosystem and pockets of customers. First let's look at the overall event. It was held at Caesars Forum. Not my favorite venue, but I'll tell you it was packed. Fire Marshall Full, as we sometimes say. Nearly 10,000 people attended the event. Here's Snowflake's CMO Denise Persson on theCUBE describing how this event has evolved. >> Yeah, two, three years ago, we were about 1800 people at a Hilton in San Francisco. We had about 40 partners attending. This week we're close to 10,000 attendees here. Almost 10,000 people online as well, and over over 200 partners here on the show floor. >> Now, those numbers from 2019 remind me of the early days of Hadoop World, which was put on by Cloudera but then Cloudera handed off the event to O'Reilly as this article that we've inserted, if you bring back that slide would say. The headline it almost got it right. Hadoop World was a failure, but it didn't have to be. Snowflake has filled the void created by O'Reilly when it first killed Hadoop World, and killed the name and then killed Strata. Now, ironically, the momentum and excitement from Hadoop's early days, it probably could have stayed with Cloudera but the beginning of the end was when they gave the conference over to O'Reilly. We can't imagine Frank Slootman handing the keys to the kingdom to a third party. Serious business was done at this event. I'm talking substantive deals. Salespeople from a host sponsor and the ecosystems that support these events, they love physical. They really don't like virtual because physical belly to belly means relationship building, pipeline, and deals. And that was blatantly obvious at this show. And in fairness, all theCUBE events that we've done year but this one was more vibrant because of its attendance and the action in the ecosystem. Ecosystem is a hallmark of a cloud company, and that's what Snowflake is. We asked Frank Slootman on theCUBE, was this ecosystem evolution by design or did Snowflake just kind of stumble into it? Here's what he said. >> Well, when you are a data clouding, you have data, people want to do things with that data. They don't want just run data operations, populate dashboards, run reports. Pretty soon they want to build applications and after they build applications, they want build businesses on it. So it goes on and on and on. So it drives your development to enable more and more functionality on that data cloud. Didn't start out that way, you know, we were very, very much focused on data operations. Then it becomes application development and then it becomes, hey, we're developing whole businesses on this platform. So similar to what happened to Facebook in many ways. >> So it sounds like it was maybe a little bit of both. The Facebook analogy is interesting because Facebook is a walled garden, as is Snowflake, but when you come into that garden, you have assurances that things are going to work in a very specific way because a set of standards and protocols is being enforced by a steward, i.e. Snowflake. This means things run better inside of Snowflake than if you try to do all the integration yourself. Now, maybe over time, an open source version of that will come out but if you wait for that, you're going to be left behind. That said, Snowflake has made moves to make its platform more accommodating to open source tooling in many of its announcements this week. Now, I'm not going to do a deep dive on the announcements. Matt Sulkins from Monte Carlo wrote a decent summary of the keynotes and a number of analysts like Sanjeev Mohan, Tony Bear and others are posting some deeper analysis on these innovations, and so we'll point to those. I'll say a few things though. Unistore extends the type of data that can live in the Snowflake data cloud. It's enabled by a new feature called hybrid tables, a new table type in Snowflake. One of the big knocks against Snowflake was it couldn't handle and transaction data. Several database companies are creating this notion of a hybrid where both analytic and transactional workloads can live in the same data store. Oracle's doing this for example, with MySQL HeatWave and there are many others. We saw Mongo earlier this month add an analytics capability to its transaction system. Mongo also added sequel, which was kind of interesting. Here's what Constellation Research analyst Doug Henschen said about Snowflake's moves into transaction data. Play the clip. >> Well with Unistore, they're reaching out and trying to bring transactional data in. Hey, don't limit this to analytical information and there's other ways to do that like CDC and streaming but they're very closely tying that again to that marketplace, with the idea of bring your data over here and you can monetize it. Don't just leave it in that transactional database. So another reach to a broader play across a big community that they're building. >> And you're also seeing Snowflake expand its workload types in its unique way and through Snowpark and its stream lit acquisition, enabling Python so that native apps can be built in the data cloud and benefit from all that structure and the features that Snowflake is built in. Hence that Facebook analogy, or maybe the App Store, the Apple App Store as I propose as well. Python support also widens the aperture for machine intelligence workloads. We asked Snowflake senior VP of product, Christian Kleinerman which announcements he thought were the most impactful. And despite the who's your favorite child nature of the question, he did answer. Here's what he said. >> I think the native applications is the one that looks like, eh, I don't know about it on the surface but he has the biggest potential to change everything. That's create an entire ecosystem of solutions for within a company or across companies that I don't know that we know what's possible. >> Snowflake also announced support for Apache Iceberg, which is a new open table format standard that's emerging. So you're seeing Snowflake respond to these concerns about its lack of openness, and they're building optionality into their cloud. They also showed some cost op optimization tools both from Snowflake itself and from the ecosystem, notably Capital One which launched a software business on top of Snowflake focused on optimizing cost and eventually the rollout data management capabilities, and all kinds of features that Snowflake announced that the show around governance, cross cloud, what we call super cloud, a new security workload, and they reemphasize their ability to read non-native on-prem data into Snowflake through partnerships with Dell and Pure and a lot more. Let's hear from some of the analysts that came on theCUBE this week at Snowflake Summit to see what they said about the announcements and their takeaways from the event. This is Dave Menninger, Sanjeev Mohan, and Tony Bear, roll the clip. >> Our research shows that the majority of organizations, the majority of people do not have access to analytics. And so a couple of the things they've announced I think address those or help to address those issues very directly. So Snowpark and support for Python and other languages is a way for organizations to embed analytics into different business processes. And so I think that'll be really beneficial to try and get analytics into more people's hands. And I also think that the native applications as part of the marketplace is another way to get applications into people's hands rather than just analytical tools. Because most people in the organization are not analysts. They're doing some line of business function. They're HR managers, they're marketing people, they're sales people, they're finance people, right? They're not sitting there mucking around in the data, they're doing a job and they need analytics in that job. >> Primarily, I think it is to contract this whole notion that once you move data into Snowflake, it's a proprietary format. So I think that's how it started but it's usually beneficial to the customers, to the users because now if you have large amount of data in paket files you can leave it on S3, but then you using the Apache Iceberg table format in Snowflake, you get all the benefits of Snowflake's optimizer. So for example, you get the micro partitioning, you get the metadata. And in a single query, you can join, you can do select from a Snowflake table union and select from an iceberg table and you can do store procedure, user defined function. So I think what they've done is extremely interesting. Iceberg by itself still does not have multi-table transactional capabilities. So if I'm running a workload, I might be touching 10 different tables. So if I use Apache Iceberg in a raw format, they don't have it, but Snowflake does. So the way I see it is Snowflake is adding more and more capabilities right into the database. So for example, they've gone ahead and added security and privacy. So you can now create policies and do even cell level masking, dynamic masking, but most organizations have more than Snowflake. So what we are starting to see all around here is that there's a whole series of data catalog companies, a bunch of companies that are doing dynamic data masking, security and governance, data observability which is not a space Snowflake has gone into. So there's a whole ecosystem of companies that is mushrooming. Although, you know, so they're using the native capabilities of Snowflake but they are at a level higher. So if you have a data lake and a cloud data warehouse and you have other like relational databases, you can run these cross platform capabilities in that layer. So that way, you know, Snowflake's done a great job of enabling that ecosystem. >> I think it's like the last mile, essentially. In other words, it's like, okay, you have folks that are basically that are very comfortable with Tableau but you do have developers who don't want to have to shell out to a separate tool. And so this is where Snowflake is essentially working to address that constituency. To Sanjeev's point, and I think part of it, this kind of plays into it is what makes this different from the Hadoop era is the fact that all these capabilities, you know, a lot of vendors are taking it very seriously to put this native. Now, obviously Snowflake acquired Streamlit. So we can expect that the Streamlit capabilities are going to be native. >> I want to share a little bit about the higher level thinking at Snowflake, here's a chart from Frank Slootman's keynote. It's his version of the modern data stack, if you will. Now, Snowflake of course, was built on the public cloud. If there were no AWS, there would be no Snowflake. Now, they're all about bringing data and live data and expanding the types of data, including structured, we just heard about that, unstructured, geospatial, and the list is going to continue on and on. Eventually I think it's going to bleed into the edge if we can figure out what to do with that edge data. Executing on new workloads is a big deal. They started with data sharing and they recently added security and they've essentially created a PaaS layer. We call it a SuperPaaS layer, if you will, to attract application developers. Snowflake has a developer-focused event coming up in November and they've extended the marketplace with 1300 native apps listings. And at the top, that's the holy grail, monetization. We always talk about building data products and we saw a lot of that at this event, very, very impressive and unique. Now here's the thing. There's a lot of talk in the press, in the Wall Street and the broader community about consumption-based pricing and concerns over Snowflake's visibility and its forecast and how analytics may be discretionary. But if you're a company building apps in Snowflake and monetizing like Capital One intends to do, and you're now selling in the marketplace, that is not discretionary, unless of course your costs are greater than your revenue for that service, in which case is going to fail anyway. But the point is we're entering a new error where data apps and data products are beginning to be built and Snowflake is attempting to make the data cloud the defacto place as to where you're going to build them. In our view they're well ahead in that journey. Okay, let's talk about some of the bigger themes that we heard at the event. Bringing apps to the data instead of moving the data to the apps, this was a constant refrain and one that certainly makes sense from a physics point of view. But having a single source of data that is discoverable, sharable and governed with increasingly robust ecosystem options, it doesn't have to be moved. Sometimes it may have to be moved if you're going across regions, but that's unique and a differentiator for Snowflake in our view. I mean, I'm yet to see a data ecosystem that is as rich and growing as fast as the Snowflake ecosystem. Monetization, we talked about that, industry clouds, financial services, healthcare, retail, and media, all front and center at the event. My understanding is that Frank Slootman was a major force behind this shift, this development and go to market focus on verticals. It's really an attempt, and he talked about this in his keynote to align with the customer mission ultimately align with their objectives which not surprisingly, are increasingly monetizing with data as a differentiating ingredient. We heard a ton about data mesh, there were numerous presentations about the topic. And I'll say this, if you map the seven pillars Snowflake talks about, Benoit Dageville talked about this in his keynote, but if you map those into Zhamak Dehghani's data mesh framework and the four principles, they align better than most of the data mesh washing that I've seen. The seven pillars, all data, all workloads, global architecture, self-managed, programmable, marketplace and governance. Those are the seven pillars that he talked about in his keynote. All data, well, maybe with hybrid tables that becomes more of a reality. Global architecture means the data is globally distributed. It's not necessarily physically in one place. Self-managed is key. Self-service infrastructure is one of Zhamak's four principles. And then inherent governance. Zhamak talks about computational, what I'll call automated governance, built in. And with all the talk about monetization, that aligns with the second principle which is data as product. So while it's not a pure hit and to its credit, by the way, Snowflake doesn't use data mesh in its messaging anymore. But by the way, its customers do, several customers talked about it. Geico, JPMC, and a number of other customers and partners are using the term and using it pretty closely to the concepts put forth by Zhamak Dehghani. But back to the point, they essentially, Snowflake that is, is building a proprietary system that substantially addresses some, if not many of the goals of data mesh. Okay, back to the list, supercloud, that's our term. We saw lots of examples of clouds on top of clouds that are architected to spin multiple clouds, not just run on individual clouds as separate services. And this includes Snowflake's data cloud itself but a number of ecosystem partners that are headed in a very similar direction. Snowflake still talks about data sharing but now it uses the term collaboration in its high level messaging, which is I think smart. Data sharing is kind of a geeky term. And also this is an attempt by Snowflake to differentiate from everyone else that's saying, hey, we do data sharing too. And finally Snowflake doesn't say data marketplace anymore. It's now marketplace, accounting for its application market. Okay, let's take a quick look at the competitive landscape via this ETR X-Y graph. Vertical access remembers net score or spending momentum and the x-axis is penetration, pervasiveness in the data center. That's what ETR calls overlap. Snowflake continues to lead on the vertical axis. They guide it conservatively last quarter, remember, so I wouldn't be surprised if that lofty height, even though it's well down from its earlier levels but I wouldn't be surprised if it ticks down again a bit in the July survey, which will be in the field shortly. Databricks is a key competitor obviously at a strong spending momentum, as you can see. We didn't draw it here but we usually draw that 40% line or red line at 40%, anything above that is considered elevated. So you can see Databricks is quite elevated. But it doesn't have the market presence of Snowflake. It didn't get to IPO during the bubble and it doesn't have nearly as deep and capable go-to market machinery. Now, they're getting better and they're getting some attention in the market, nonetheless. But as a private company, you just naturally, more people are aware of Snowflake. Some analysts, Tony Bear in particular, believe Mongo and Snowflake are on a bit of a collision course long term. I actually can see his point. You know, I mean, they're both platforms, they're both about data. It's long ways off, but you can see them sort of in a similar path. They talk about kind of similar aspirations and visions even though they're quite in different markets today but they're definitely participating in similar tam. The cloud players are probably the biggest or definitely the biggest partners and probably the biggest competitors to Snowflake. And then there's always Oracle. Doesn't have the spending velocity of the others but it's got strong market presence. It owns a cloud and it knows a thing about data and it definitely is a go-to market machine. Okay, we're going to end on some of the things that we heard in the ecosystem. 'Cause look, we've heard before how particular technology, enterprise data warehouse, data hubs, MDM, data lakes, Hadoop, et cetera. We're going to solve all of our data problems and of course they didn't. And in fact, sometimes they create more problems that allow vendors to push more incremental technology to solve the problems that they created. Like tools and platforms to clean up the no schema on right nature of data lakes or data swamps. But here are some of the things that I heard firsthand from some customers and partners. First thing is, they said to me that they're having a hard time keeping up sometimes with the pace of Snowflake. It reminds me of AWS in 2014, 2015 timeframe. You remember that fire hose of announcements which causes increased complexity for customers and partners. I talked to several customers that said, well, yeah this is all well and good but I still need skilled people to understand all these tools that I'm integrated in the ecosystem, the catalogs, the machine learning observability. A number of customers said, I just can't use one governance tool, I need multiple governance tools and a lot of other technologies as well, and they're concerned that that's going to drive up their cost and their complexity. I heard other concerns from the ecosystem that it used to be sort of clear as to where they could add value you know, when Snowflake was just a better data warehouse. But to point number one, they're either concerned that they'll be left behind or they're concerned that they'll be subsumed. Look, I mean, just like we tell AWS customers and partners, you got to move fast, you got to keep innovating. If you don't, you're going to be left. Either if your customer you're going to be left behind your competitor, or if you're a partner, somebody else is going to get there or AWS is going to solve the problem for you. Okay, and there were a number of skeptical practitioners, really thoughtful and experienced data pros that suggested that they've seen this movie before. That's hence the same wine, new bottle. Well, this time around I certainly hope not given all the energy and investment that is going into this ecosystem. And the fact is Snowflake is unquestionably making it easier to put data to work. They built on AWS so you didn't have to worry about provisioning, compute and storage and networking and scaling. Snowflake is optimizing its platform to take advantage of things like Graviton so you don't have to, and they're doing some of their own optimization tools. The ecosystem is building optimization tools so that's all good. And firm belief is the less expensive it is, the more data will get brought into the data cloud. And they're building a data platform on which their ecosystem can build and run data applications, aka data products without having to worry about all the hard work that needs to get done to make data discoverable, shareable, and governed. And unlike the last 10 years, you don't have to be a keeper and integrate all the animals in the Hadoop zoo. Okay, that's it for today, thanks for watching. Thanks to my colleague, Stephanie Chan who helps research "Breaking Analysis" topics. Sometimes Alex Myerson is on production and manages the podcasts. Kristin Martin and Cheryl Knight help get the word out on social and in our newsletters, and Rob Hof is our editor in chief over at Silicon, and Hailey does some wonderful editing, thanks to all. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis Podcasts. I publish each week on wikibon.com and siliconangle.com and you can email me at David.Vellante@siliconangle.com or DM me @DVellante. If you got something interesting, I'll respond. If you don't, I'm sorry I won't. Or comment on my LinkedIn post. Please check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time. (upbeat music)

>>Hey everyone. Welcome back to the Cube's live coverage of snowflake summit 22. We are live at Caesar's forum in Vegas, Lisa Martin, with Dave ante, excited to welcome a VIP fresh from the keynote stage, the SAP, a product at snowflake Christian C Claman Christian. Thank you so much for joining us on the queue today. >>Thank you for having me very exciting. >>And thanks for bringing your energy, loved your keynote. I thought, wow. He is really excited about all of the announcements jam packed. We, and we didn't even get to see the entire keynote talk to us about, and, and for the audience, some of the things going on the product revenue in Q1 fiscal 23, 390 4 million, 85% growth, lot of momentum at snowflake. No doubt. >>So I think that the, the punch line is our innovation is if anything, gaining speed. Uh, we were over the moon excited to share many of these projects with customers and partners, cuz some of these efforts have been going on for multiple years. So, um, lots of interesting announcements across the board from making the existing workloads faster, but also we announced some new workloads getting into cyber security, getting into more transactional workloads with uni store. Um, so we're very excited. >>Well first time being back, this is the fourth summit, but the first time being back since 2019 a tremendous amount has changed for snowflake in that time, the IPO, the massive growth in customers, the massive growth in growth in customers with over 1 million in ARR, you talked about one of the things that clearly did not slow down during the last two years is innovation at snowflake. >>Yeah, that, that, that for, for sure, like, um, even though we, we had a, um, highly in the office culture, we did not miss a beat the moment that we said, Hey, let's all start doing zoom based calls. We, we did. So, uh, I dunno if you saw the, the first five minute minutes of my section in the keynote. Yeah. We, we originally talked about summarizing it and no we're gonna spend 40 minutes here. So we did a one minute clip and whatever gets flashed there. So no, the, the pace of innovation, I think it's second to none and maybe I'll highlight the something that we're very proud of. Snowflake is a single product, a single engine. So if we're making a query performance enhancement, it will help the cyber security workload and the low high concurrency, low latency workload. And eventually we're starting to see some of those enhancements all the way to uni store. So, so we get a lot of leverage out of our investments. What's >>Your favorite announcement? >>That's like picking children. Of course. Um, I think the native applications is the one that looks like, eh, I don't know about it on the surface, but it has the biggest potential to change everything like create an entire ecosystem of solutions for within a company or across companies that I don't know that we know what's possible. >>Well, I I've been saying for a while now that you have this application development stack over here, the database is kind of here and then you have the analytics and data pipeline stack. Those are those separate worlds. We, we talk about bringing data and AI and machine intelligence into applications. The only way that that is actually gonna move forward is if you bring those worlds together is a good example of that happening, um, within a proprietary framework, uh, it's probably gonna happen open source organically and you can sort of roll your own. Is that by design or is it just sort of happening? Well, >>The, the, they bring it all into a single platform obviously by design, cuz there is so much friction today on making all the pieces work together, which database do I use for transactions and how do I move data to my analytics system? And how do I keep system, uh, reference data in sync between the two? So, so it's complicated and our mission was remove all of this friction from, from, from the equation. Uh, the open source versus not the way we think about it is opensourcing open formats or even open APIs it's does it help us deliver the solution that we want for our customer? Does it help us solve their problems? In certain instances, it has done in the past and we've opened source frameworks in, in others. We mentioned at the keynote today, the, the integration of iceberg tables, that's an strong embrace of open technologies, but that does not mean that we want to continue to innovate in our formats. A lot of what you see in the open formats is because snowflake proprietary, uh, innovation. So, uh, we have a very clear philosophy around this. Well >>Like any cloud player, you have to bring open source tools in and make them available for your application developers. But take us through an example of, of uni store and specifically how you're embracing transaction data. What's a customer gonna actually do take us paint a picture >>For us. I I'm gonna give you a very simple use case, but I love it because it, it shows the power of the scenario today. When people are ingesting data into snowflake, you wanna do some book capping associating with those loads. So imagine I have, I dunno, a million files. How many of those files have I loaded? Imagine that one of those loads fail, how do you keep in sync? Whether the data made or not with your bookkeeping today, if you had to do it with a separate transactional database for the bookkeeping and the loading in, in snowflake, it is a lot of complexity for you to know what's where with uni store, you can just say, I'm gonna do the bookkeeping with these new table. It's called hybrid tables. The lows are transactional and all of this is a single transaction. So for, for anyone that has dealt with inconsistencies in database world, this is like a godsend. >>Okay. So my interpretation of that's all about what happens when something goes wrong >><laugh> which is a lot of the, everything about transactions. Yeah. It's what happens when goes wrong and goes wrong. Doesn't mean failures like goes wrong is when you're debiting money from your bank account, not having enough balance that counts as go wrong and the transactions should be aborted. So yes, transactions are all about conflict management and we're simplifying that in a broader set of use cases >>And, and in recovery. So you're, you're in fast recovery. So you're, you're the, the business impact of what you're doing is to sort of simplify that process. Is that the easy way to >>Boil down? Pretty much everything we do is about simplification. Like we, we we've seen organizations are large focusing on wrestling infrastructure as opposed to what are the business problems for a Frank who reference something that, that, that I believe very much in like, which is mission alignment. We are working on helping our customers achieve what they're set out to achieve, not giving them more technology for them to their goal to become, to wrestle the infrastructure. So it's all about ease of use all about simplification removal, friction, >>Just so if I may, so mission alignment, you know, you always hear about technology companies that, you know, provide infrastructure or a service, and then the customer takes that and, and, you know, monetizes it pretty much on their own. What the big change that I'm discerning from these announcements is you're talking about directly monetizing and participating in that monetization as a technology partner, but also the marketplace as well. >>Correct. And I would say in some ways this is not new. This has been happening for the last couple of years with data. Like if you just saw our industry data cloud launches, the financial services cloud, it comes with data providers that help you achieve specific outcomes on a specific industry. Mm-hmm <affirmative> what we're doing now is saying, it's not just data. Maybe it's some business logic, maybe it's some machine learning, maybe it's some user interface. So I think we're just turning the knob on collaboration and it's a continuation of what we've been doing. >>Talk a little bit more about mission alignment. When I heard Frank, Sweetman talk about that this morning. I always love that when I hear cultural alignment with organizations, but as you just said, it's really about enabling our customers to deliver outcomes to their customers as the SVP product. Can you, uh, talk a little bit about how the customers are influencing the product roadmap, the innovations and the speed with which things are coming out at snowflake? >>Yeah, so great question. We have several organizations at snowflake that are organized by vertical by industry. So the, the major sales organization is part of ed that the marketplace business development team is organized like that. We have a separate team that provides top leadership by industry vertical, um, globally. And then even within our solution engineering, there is verticals. So we have a longitudinal view of all the different functions and what do we need to do to achieve a set of use cases in a vertical? And all of those functions are in con constant communication with us on this is where the product is, um, seeing an opportunity or could do better for that vertical. So yeah, I can tell you, and obviously we love when, when there's alignment between those, but that's not always the case. You heard us talk about clean rooms now for some time, clean rooms are applicable to almost any industry, but it's red hot for media and advertising, third party, cookie deprecation, and all of that. So we, we get to, to see that lens, that our innovation is informed by industries. >>So we, we're seeing, obviously the evolution of snowflake we talked about in the keynotes today, you guys talked about 2019 and, you know, pre 2019, even it was to me anyway, your first phase was, Hey, we got a simpler EDW. You know, we're gonna pick that off and put it in the cloud and make it elastic and separate compute from storage, all that kind of cool stuff. And then during the pandemic, it was really IPO, but also the data cloud concept, you sort of laid that vision out. And now you're talking about application development, monetization, what I call the super cloud that layer. Right. Okay. So I, are >>You determin it best? >>Yes. You talk about this, uh, these announcements, how they fit into that larger vision where you're >>Going. Great question. The, the, the notion of the data cloud has not changed one bit. The data cloud thesis is that we want to provide amazing technology for our customers, but also facilitate collaboration and content exchange VR platform. And all that we did today is expand what that content can be. It's not just data or little helper function, it's entire applications, entire experiences. That is the, the summing up the, the, the impact of our announcements today. That, that that's the end of it. So it's still about the data cloud. >>So what is impressive to me is that you guys wouldn't couldn't have a company without the hyperscalers, right? It would be a lot different, right? So you built on top of that and, and now you have your customers building their own super clouds. I call it, I get a lot of grief for that term it's but the, the, the big area of criticism I get is, ah, that's just SAS. And I'm like, no, it's not, no, uh, I, I is everybody public who's announcing stuff. I, I better be careful, but you have customers that are actually building services, taking their data, their tooling, their proprietary information, and putting it on the snowflake data cloud and building their own clouds. Yeah. That's different. Then that's not multi-cloud, which is I can run on a different cloud and it's not, is it sass? If it feels like it's something new from a, from your perspective, is, is it different? >>I, I, I love that you called out that running on all clouds is not what we do right. This days, everyone is multi-cloud, you, you run on a VM or a container, and I multi-cloud check, no, we have a single platform that does multi-region multi-cloud but also cross region cross cloud globally, that that is the essence of what we're doing. So it, it is enabling new capabilities. >>I've I've also said, you know, in many respects, the super cloud hides, the underlying complexity, you think about things like exploiting graviton and a developer. Doesn't need to worry about that. You're gonna worry about that. Uh, but at the same time, they, the, as you get into the develop, the world of application development, some of your developers may want access to some of those cloud primitives. Are you providing both? What's the strategy there? >>Generally not in some areas, we, we, we, I would say bleed through some details that are material, but think of the reality of someone that wants to build a solution, it's really difficult to build an awesome solution in one cloud, Hey, you need to do this. What's the latest instance, and is gravity tank gonna help you or not all of that. Now do it for another one and then do it for another one. And I can tell you it's really difficult because we go through that exercise. Snowflake pouring to a new cloud is somewhere between one and two years of effort and not, not a small number of people because you're looking at security models and storage models. So that's the value that we give to anyone know, wants to build a solution and target customers in all three clouds. I >>Mean, people are still gonna do it themselves, but they're gonna spend a lot more and they're gonna lose their focus on what their real business is. And there'll still be that. I think that D DIY market is enormous for you guys, huge >>Opportunity. And there's also the question on what is the cost of that analysis and that effort. And can we amortize it on behalf of all of our customers? Like we talk about graviton, we have not talked about the many things that we evaluated that were not better price performance for our customers. That evaluation happened. That value was delivered by not moving there. >>And when you do it yourself, the curve looks like, okay, Hey, we can do it ourselves. We can make it pretty Inex. And then, and then the costs are gonna decline, but what really happens, like developing a mobile app, you gotta maintain it. And then if you don't have the scale and you don't have the engineering resources, you're just, the, the costs are gonna continue to go through the roof. I, >>I, I love that you compare it to mobile apps. Like, yeah. I still don't understand why every company that wants to build an app has to build two <laugh>. They got it. Yeah. There is no super cloud for the phone. >>Right. >>That's sort of our, our, our broad vision. Not yet. Not, not the phone, but the super cloud. Yeah, >>Yeah, absolutely. >>You >>Get it. This is, and you look out the ecosystem here. I mean, what a difference that you've been pointing this out, Lisa from, from, from 2019, a lot of buzz, it's all about innovation. You see this at, at thing at the reinvent is like the super bowl obviously. And you see that and it used to be, oh, how is, how is AWS gonna compete with snowflake and separate compute with stores? That's I, I feel like in a large way, that's all gone. It's like, okay, how do we like rise the whole, the whole industry? And that's really where the innovation is. >>We have an amazing partnership with AWS and they benefit from what we do. Yes. There's some competitive elements, but we're changing so many things creating so much opportunity that we're more aligned than not. Yeah. >>Last question for you is continuing on the part AWS partnership front, how does a partner like AWS and other partners, how do they fit into the data cloud narrative that you're talking about to customers? >>I would say that other than the one or two teams that are directly competitive, the rest of their teams are part of in data cloud. Like, uh, our relationship with SageMaker as an example is amazing. And a lot of what we wanna deliver to our customers is choice around machine learning, frameworks and tools. And they're part of the data cloud. We're working with them on how do you push down computation to avoid getting data out, to reinforce governance? So I, I would say that and, and go look at it that they have a hundred and something teams. So if two teams out of hundreds, uh, are, are the competitive element, we are largely aligned. And they're part of data cloud. >>Yeah. I mean, you, your customers consume a lot of compute and storage for, >>For a lot. Yes. >>AWS and, and also, you know, increasingly Azure and, and Google. I mean, it's, um, pretty amazing times, uh, Christian, I want to ask you about, um, couple of terms. Uh, one term that came up a couple of times today in Frank's keynote, he said, I'm not gonna call it a data mesh out kind of out of respect for the purists, which is cool, I thought, but then you had a customer stand up Geico and said, we're building a data. Mesh JPMC is, is speaking at this event, building a data mesh. And I look at things through that prism and say, okay, data mesh is about, you know, decentralization. Some, I I'd be curious as to whether or not you tick that box, but it's about building data products. It's about, uh, uh, self-service infrastructure. And it's about automated computational governance. You are actually tipping a lot of the ticking, a lot of those boxes and, and Mike, I guess the big one is, are, are you building a bigger walled garden? But I, I think you would say, no, it's a, it's a giant distributed network, but, but what, what, what do you say to that? We, >>The latter, the latter, yeah, giant distributed, open cloud and open in the sense that we want anyone to plug in and, and someone can say, well, but I cannot read your file formats. Sure. You can with what we announced today, but it's not about that. Our APIs are open. We have rest APIs. We have JDC ODC, probably most popular interfaces ever. Um, and we want everyone to be part of it. If anything, there's lots of areas that we would not want to go into ourselves cause we want partners and customers to go in there. So, no, we we're looking at a very broad ecosystem. We win based on the value created on top of the platform. Yeah. >>And I makes total sense to me. I mean, I think the imaculate conception of data mesh might be a purely open source version of snowflake. I just don't see that happening anytime soon. And so I, I think you're gonna, you are, I wrote about this creating a defacto standard and >>Exactly, and, and I don't like to get into the terminology that, oh, is the data measure? Not, no go look at the concepts like people used to say, but snowflake is not a data lake. Okay. What is the data lake? It's just a pattern. And if you follow the pattern and you can do it, that's fine. Then there's the, uh, emotional quasi-religious overlay open versus not, I think that's a choice. Not necessarily the concept, >>It's a moving target. I mean, I Unix used to be open. You know, that was the, I agree. Now, the reason why I do think the data mesh conversation is important is because Shaak Dani, when she defined data mesh, she pointed out in my view. Anyway, the problems of getting value outta data is that you go through these hyper specialized teams and they're they're blockers in the organization. And I think you in many respects are attacking that. And it's an organizational issue. >>The, the insights in the pattern are a hundred percent value and aligned with what we do, which is they, you want some amount of centralization, some amount of decentralization living in harmony. Uh, yeah. I have no problem with, with terminology. >>And the governance piece is, is, is massive. Especially it's the, the picture's becoming much more clear. Um, whatever's in the data cloud is a first class citizen, right? And you give all these wonderful benefits. I mean, the interesting thing, what you're doing with Dell and, and pure, I, I asked you that on the analyst call, it's a start. You know, I, I, I mean, >>And I said it briefly in, in, in the keynote this morning, we're publishing a set of standard conformance tests. So any storage system can plug into data cloud. >>Yeah. >>And by the way, it's based on S three APIs, another defect of standard. Like it's not a standard, but everyone is emulating that. And we're plugging >>Into that. Yeah. Nobody's complaining against, against S3 API >>About it is a, oh, it's not a Apache project. We shouldn't, who cares. Everyone has standard horizon net. That's it? >>Well, we've seen the mistakes of the past with this. I mean, look at, look at Hadoop, right? There was this huge battle between, you know, Cloudera and Horton works and map, oh, map bar is proprietary. Oh, Horton works is purely open. Cloudera is open. They're, they're all gone now. I mean, not gone, but they're just, they didn't have it. Right. You know, they, they got unfocused. I go back to Frank's book. They were trying to do too much to, to too many of those, the, the, the zoo animals and you can't fund it all >>To be effective for us. It's very important. I can give you, I don't know, 20 announcements or 50 announcements from the conference, but they're all going a singular goal. And it's, this do not trade off governance of data with the ability to get value out of data. That's everything we do. >>And that's critical for every company in every industry these days that has to be a data company to be, to survive, to be competitive, to be able to extract value from data. If data's currency, how do I leverage a tool like snowflake to be able to extract insights from it that I can act on and create value for my organization, Geico was on stage this morning. Everyone knows Geico and their beloved, um, gecko. Yeah. Is there another customer that you had that you think really articulates the value of the data cloud and to Dave's point how snowflake is becoming that defacto standard data platform? >>Well, we had Goldman Goldman Sachs on stage as well today. And he, he, he, he mentioned it that people think of Goldman as investment banking and all of that, but no, at the heart of what they do, there's a lot of data. And how do they make better decisions? So I think we could run through 20 different examples cuz your premise is the most important. Everything is a data problem. If it is not a data problem, you're not collecting the right data and getting the sense that you could be getting. >>These guys are public, right. >>Adobe. >>Yeah. Right. Adobe's doing it. Yeah. I dunno if the other one is, I don't wanna say, I'll have to ask you off camera, but the other financial firm building a super cloud, right. <laugh> yeah. I call it super cloud. So let be taking advantage of uni store. Yeah. To bring different data types in and monetize it. That's to me, that's the future of data. That's that's been the holy grail, right. >>We, we tried to emphasize that this is, is not a, Hey six, six months ago. We decided to do this. No, this is years in the making mm-hmm <affirmative>, which is why we were so excited to finally share it. Cuz you don't wanna say three years from now, we're gonna have something. No, it was the, now we have it. We have it in preview and it's working at it is as close to the holy grail as it gets. >>Yeah. I mean, look, pressure's on Kristin. Let's face it. Enterprise data warehouse failed to live up to the promises. Uh, certainly the data lakes fail to deliver master data management, all that's a Hadoop, all that stuff. There was a lot of hype around that. And a lot of us got really excited. Me included and then customers spent and they were underwhelmed. Yeah. So you know, you, you, you gotta deliver, you say it, you gotta do it. >>And correct. And then the, the other thing is I would say all of those waves of technology, there was no real better choice. >>Right. They added value. I wouldn't >>Debate that. You have to give it a shot. Like when you've bought 20 different appliances and you have all these silos and someone sells you, Hey, Hadoop will unify it. It sounds good. Just didn't do it. >>Yeah. And no debate that it brought some value for those that were agree. Sophisticated enough to deploy it. And I agree. Yeah. But, but this is a whole different ball game. >>Oh, everything we want to do is democratize and simplify mm-hmm <affirmative> yeah. We could go build something that I don't know. 10 companies in the world could use. That's not the sweet spot. Like how do we advance like the, the state of value generation in the world? That's the scale that we're talking about is go make it easy, accessible for everyone. >>Governed >>Governance and imperative this these days it's law. Yes. So >>Yeah, you have to, but it's not, it's, that's a, that's a ch really difficult challenge to create what I'll call automated or computational governance in a federated manner. That's not trivial. >>And that's our thesis. Everything we're doing is snow park, big announcement today. Python. I I've had people tell me well, but Python should be easy to host the Python run time. Like you can do it. Like I think in a week it took us years. Why? Oh, secure. Oh, details a lot. And <inaudible> mentioned it like securing. That is no easy, uh, feed >>Christian. Thank you so much for joining Dave and me bringing your energy from the keynote stage to the cube, set, breaking down some of the major announcements that have come out today. There's no doubt that the flywheel of innovation at snowflake is alive well and moving quickly, >>Innovation is, uh, at an all time hat snowflake. Thank you for having me. All >>Right. Our pleasure Christian from our guest, Dave ante, Lisa Martin here live in Las Vegas at Caesar's forum covering snowflake summit 22. We right back with our next guest.

>>Good morning live from Las Vegas, Lisa Martin and Dave Lanta here covering snowflake summit 22. Dave, it's great to be here in person. The keynote we just came from was standing room only. In fact, there was overflow. People are excited to be back and to hear from the company in person the first time, since the IPO, >>Lots of stuff, lots of deep technical dives, uh, you know, they took the high end of the pyramid and then dove down deep in the keynotes. It >>Was good. They did. And we've got Doug Hench with us to break this down in the next eight to 10 minutes, VP and principle analyst at constellation research. Doug, welcome to the cube. >>Great to be here. >>All right, so guys, I was telling Dave, as we were walking back from the keynote, this was probably the most technical keynote I've seen in a very long time. Obviously in person let's break down some of the key announcements. What were some of the things Dave that stood out to you and what they announced just in the last hour and a half alone? >>Well, I, you know, we had a leave before they did it, but the unit store piece was really interesting to me cuz you know, the big criticism is, oh, say snowflake, that doesn't do transaction data. It's just a data warehouse. And now they're sort of reaching out. We're seeing the evolution of the ecosystem. Uh, sluman said it was by design. It was one of the questions I had for them. Is this just kind of happen or is it by design? So that's one of many things that, that we can unpack. I mean the security workload, uh, the, the Apache tables, we were just talking about thatt, which not a lot of hands went up when they said, who uses Apache tables, but, but a lot of the things they're doing seem to me anyway, to be trying to counteract the narrative, that snow, I mean that data bricks is put out there about you guys. Aren't open, you're a walled garden and now they're saying, Hey, we're we're as open as anybody, but what are your thoughts, Doug? >>Well, that's the, the iceberg announcement, uh, also, uh, the announcement of, of uni store being able to reach out to, to any source. Uh, you know, I think the big theme here was this, this contrast you constantly see with snowflake between their effort to democratize and simplify and disrupt the market by bringing in a great big tent. And you saw that great big tent here today, 7,000 people, 2,007,000 plus I'm told 2000 just three years ago. So this company is growing hugely quickly, >>Unprecedented everybody. >>Yeah. Uh, fastest company to a billion in revenue is Frank Salman said in his keynote today. Um, you know, and I think that there's, there's that great big tent. And then there's the innovations they're delivering. And a lot of their announcements are way ahead of the J general availability. A lot of the things they talked about today, Python support and some, some other aspects they're just getting into public preview. And many of the things that they're announcing today are in private preview. So it could be six, 12 months be before they're generally available. So they're here educating a lot of these customers. What is iceberg? You know, they're letting them know about, Hey, we're not just the data warehouse. We're not just letting you migrate your old workloads into the cloud. We're helping you innovate with things like the data marketplace. I see the data marketplace is really crucial to a lot of the announcements they're making today. Particularly the native apps, >>You know, what was interesting sluman in his keynote said we don't use the term data mesh, cuz that means has meaning to the people, lady from Geico stood up and said, we're building a data mesh. And when you think about, you know, the, those Gemma Dani's definition of data mesh, Snowflake's actually ticking a lot of boxes. I mean, it's it's is it a decentralized architecture? You could argue that it's sort of their own wall garden, but things like data as product we heard about building data products, uh, uh, self-serve infrastructure, uh, computational governance, automated governance. So those are all principles of Gemma's data mesh. So I there's close as anybody that, that I've seen with the exception of it's all in the data cloud. >>Why do you think he was very particular in saying we're not gonna call it a data mesh? I, >>I think he's respecting the principles that have been put forth by the data mesh community generally and specifically Jamma Dani. Uh, and they don't want to, you know, they don't want to data mesh wash. I mean, I, I, I think that's a good call. >>Yeah, that's it's a little bit out there and, and it, they didn't talk about data mesh so much as Geico, uh, the keynote or mentioned their building one. So again, they have this mix of the great big tent of customers and then very forward looking very sophisticated customers. And that's who they're speaking to with some of these announcements, like the native apps and the uni store to bring transactional data, bring more data in and innovate, create new apps. And the key to the apps is that they're made available through the marketplace. Things like data sharing. That's pretty simple. A lot of, uh, of their competitors are talking about, Hey, we can data share, but they don't have the things that make it easy, like the way to distribute the data, the way to monetize the data. So now they're looking forward monetizing apps, they changed the name from the data marketplace to the, to the snowflake marketplace. So it'll be apps. It will be data. It'll be all sorts of innovative products. >>We talk about Geico, uh, JPMC is speaking at this conference, uh, and the lead technical person of their data mesh initiative. So it's like, they're some of their customers that they're putting forth. So it's kind of interesting. And then Doug, something else that you and I have talked about on the, some of the panels that we've done is you've got an application development stack, you got the database over there and then you have the data analytics stack and we've, I've said, well, those things come together. Then people have said, yeah, they have to. And this is what snowflake seems to be driving towards. >>Well with uni store, they're reaching out and trying to bring transactional data in, right? Hey, don't limit this to analytical information. And there's other ways to do that, like CDC and streaming, but they're very closely tying that again to that marketplace, with the idea of bring your data over here and you can monetize it. Don't just leave it in that transactional database. So a, another reach to a broader play across a big community that they're >>Building different than what we saw last week at Mongo, different than what you know, Oracle does with, with heat wave. A lot of ways to skin a cat. >>That was gonna be my next question to both of you is talk to me about all the announcements that we saw. And, and like we said, we didn't actually get to see the entire keynote had come back here. Where are they from a differentiation perspective in terms of the competitive market? You mentioned Doug, a lot of the announcements in either private preview or soon to be public preview early. Talk to me about your thoughts where they are from a competitive standpoint. >>Again, it's that dichotomy between their very forward looking announcements. They're just coming on with things like Python support. That's just becoming generally available. They're just introducing, uh, uh, machine learning algorithms, like time series built into the database. So in some ways they're catching up while painting this vision of future capabilities and talking about things that are in development or in private preview that won't be here for a year or two, but they're so they're out there, uh, talking about a BLE bleeding edge story yet the reality is the product sometimes are lagging behind. Yeah, >>It's interesting. I mean, they' a lot of companies choose not to announce anything until it's ready to ship. Yeah. Typically that's a technique used by the big whales to try to freeze the market, but I think it's different here. And the strategy is to educate customers on what's possible because snowflake really does have, you know, they're trying to differentiate from, Hey, we're not just a data warehouse. We have a highly differentiatable strategy from whether it's Oracle or certainly, you know, Mongo is more transactional, but, but you know, whether it's couch base or Redis or all the other databases out there, they're saying we're not a database, we're a data cloud. <laugh> right. Right. Okay. What is that? Well, look at all the things that you can do with the data cloud, but to me, the most interesting is you can actually build data products and you can monetize that. And their, the emphasis on ecosystem, you, they look at Salman's previous company would ServiceNow took a long time for them to build an ecosystem. It was a lot of SI in smaller SI and they finally kind of took off, but this is exceeding my expectations and ecosystem is critical because they can't do it all. You know, they're gonna O otherwise they're gonna spread themselves to >>That. That's what I think some competitors just don't get about snowflake. They don't get that. It's all about the community, about their network that they're building and the relationships between these customers. And that they're facilitating that with distribution, with monetization, things that are hard. So you can't just add sharing, or you can share data from one of their, uh, legacy competitors, uh, in, in somebody else's marketplace that doesn't facilitate the transaction that doesn't, you know, build on the community. Well, >>And you know, one of the criticisms too, of the criticism on snowflake goes, they don't, you know, they can't do complex joins. They don't do workload management. And I think their answer to that is, well, we're gonna look to the ecosystem to do that. Or you, you saw some kind of, um, cost governance today in the, in the keynote, we're gonna help you optimize your spend, um, a little different than workload management, but related >>Part of their governance was having a, a, a node, uh, for every workload. So workload isolation in that way, but that led to the cost problems, you know, like too many nodes with not enough optimization. So here too, you saw a lot of, uh, announcements around cost controls, budgets, new features, uh, user groups that you could bring, uh, caps and guardrails around those costs. >>In the last couple minutes, guys talk about their momentum. Franks Lutman showed a slide today that showed over 5,900 customers. I was looking at some stats, uh, in the last couple of days that showed that there is an over 1200% increase in the number of customers with a million plus ARR. Talk about their momentum, what you expect to see here. A lot of people here, people are ready to hear what they're doing in person. >>Well, I think this, the stats say it all, uh, fastest company to a, to a billion in revenue. Uh, you see the land and expand experience that many companies have and in the cost control, uh, announcements they were making, they showed the typical curve like, and he talked about it being a roller coaster, and we wanna help you level that out. Uh, so that's, uh, a matter of maturation. Uh, that's one of the downsides of this rapid growth. You know, you have customers adding new users, adding new clusters, multi clusters, and the costs get outta control. They want to help customers even that out, uh, with reporting with these budget and cost control measures. So, uh, one of the growing pains that comes with, uh, adding so many customers so quickly, and those customers adding so many users and new, uh, workloads quickly, >>I know we gotta break, but last point I'll make about the key. Uh, keynote is SL alluded to the fact that they're not taking the foot off the gas. They don't see any reason to, despite the narrative in the press, they have inherent profitability. If they want to be more profitable, they could be, but they're going for growth >>Going for growth. There is so much to unpack in the next three days. You won't wanna miss it. The Cube's wall to oil coverage, Lisa Martin for Dave Valenti, Doug hen joined us in our keynote analysis. Thanks so much for walking, watching stick around. Our first guest is up in just a few minutes.

>> Live from Las Vegas, it's theCUBE covering VMworld 2018 brought to you by VMware and it's ecosystem partners. >> Hello, everyone, welcome back to the live CUBE coverage. This is day three of VMworld 2018. We're live in Las Vegas this is theCUBE's special coverage. Our ninth year covering VMworld. Kicking off day three, we've got two sets. Our next guest, Brian Reagan, who's the CMO of Actifio, theCUBE alumni. Great to see you. Great company doing some great things on the marketing side. You guys taking a different approach than others. Let the product do the talking. Let the solution speak for itself. Welcome to theCUBE. >> Thank you, John. It's great to be back and, Dave, it's always a pleasure. It's great to be at VMworld. >> You guys, I don't want to say, a different approach, but you're here at VMworld. There's a lot of pomp and circumstance. There's a lot of big booths, a lot of glam, a lot of attention getting. You got to do that but you don't want to overspend on that. You really want to just be in the community. What's your strategy? How are you as a CMO going into a world that wants more content? They want more data. They want to get solutions built. They love the glam, but the meat and potatoes is what they want. >> Monday night we had an event at TopGolf and I was talking to a couple customers and they basically were all saying the same thing to me which was, I come to VMworld to basically collect squeezy balls for my kids. They're going back to school. I'm going to collect a lot of toys. I'm going to do the solution expo. Great, great opportunity to really breakthrough from a swag standpoint, but no one's coming here to necessarily research the company that they want to disrupt or transform their business around. What we believe for VMware and, quite frankly, just in general is this is a great place to engage with customers. They're all here. This is the IT, this is COMDEX 2018. We need to be here, but we don't necessarily need to be in a solutions exchange where it's just an arms race about swag. >> What's your relationship with VMware? How do you guys fit in the ecosystem? What's the value proposition? What is the Actifio relationship to the community? How do you guys walk that line and how do you deliver those solutions? >> Pretty much throw a rock and you'll hit a vendor out here who has a great VMware solution, right? We are no exception. Everyone does VMware. Quite frankly, it's actually really easy nowadays. There's zero differentiation. I hate to say it, but everyone does VMware the same way. There is really no disruption in this marketplace because everyone does VADP. Everyone does Snapshot. Quite frankly, what we major on and what we focus on is actually the workloads that are franchise critical to businesses, which really are databases. Yeah, they might run out of VM, but often times they run on physical machines. Let's focus on databases. If they happen to be VMware, great. You know what, we like everybody else has a great VMware solution, but it's easy. Let's focus on the hard stuff which is databases which run the business and dX is all around databases and applications that run the business. That's where we major on. That's where our value comes in. That's where our customers see the most value from Actifio. >> My take away is, five/ten years ago it was all about integration and that was a differentiation, who could get the SDK faster, >> Exactly right, yeah. >> And you say, we were, we own them and that app would be right there. Okay, fine. That's done, okay. Fast forward to 2018, what's your perspective on VMware, what they're doing, the market momentum. You mentioned databases. You see them with Amazon bringing database now on prem. A lot has changed. What's your perspective? >> I think VMware is really... You talk to any CIO, any IT leadership, VMware is a critical part of the conversation so I don't mean to, in any way, diminish the value that VMware brings to the enterprise. And actually they are enabling cloud in every enterprise today whether it's private, whether it's hybrid, whether it's I'm going to do public, but I'm going to do public in VMware in the Amazon Cloud. VMware is table stakes in terms of running mission critical applications. What we believe is the next level of integration is what's the app running in VMware, right? What is it Oracle? I'm running Oracle rack inside of VMware. I'm running SAP inside of VMware. That's the next level of integration that becomes the differentiation and, quite frankly, the value creation in a lot of these enterprises. >> How do you guys differentiate, John was talking about all the glam and all the noise, a lot of noise, tons of noise around data protection. You guys pioneered the whole copy data management space. Where are you seeing growth? Where's the momentum, maybe you can give some examples. >> 2/3 of our business is now actually leading with DevOps and cloud. The real lever there is time. People want more time back in their day and they want more time back because whether it's-- there was a great article that SearchITOperations published about Aetna where they have tens of multi-terabyte databases and, quite frankly, it breaks every piece of infrastructure that they had, but they want to be able to serve those multi-terabyte databases out to their developers within minutes, as opposed to weeks or months or however long it takes traditional operations. Let's serve that need. Let's solve the time problem and all of a sudden digital transformation becomes a reality. dX and continuous integration, continuous development is really easy when you're talking about megabyte-sized JSON files. When you talk about 100 terabyte databases, it becomes really hard. With Actifio, we solve that problem. Now, we're enabling dX at scale in these large enterprises. It's really a time problem. >> Aetna's a customer obviously. We heard a similar story from Live Nation, which is another customer, but go ahead, John, sorry. >> What's the drivers in this because this is a unique thing? Because databases, as we said on theCUBE here on our analysis, the battleground in cloud, on premise in cloud database is the crucial thing. Look at Amazon, they're going after Oracle. RDS, their relational database service, on VMware on premise. Amazon's never done that before so clearly the database is a hard nut to crack, one. Two, it's super important. It's the pacing item on all migrations, all activity. What's driving your business because you're targeting that, trying to improve ease of use, but what's the market force? Migration, developer scale? What are some of the things that are driving your business? >> Yes and yes, right? It's help me collapse my cycle time. Typically, the time to actually get a copy of data for a developer is measured in weeks or months. >> In the old way. >> In the old way. CICD is talking about a daily check-in. And daily check-in, weeks and months, it just doesn't jive. If I can actually collapse that down into, yes, no matter how big that database is, I can give it to you in a 15 minute, 30 minute SLA. >> The mismatch between data pipelining to developer need is a gap, huge problem that you solve. What about some of the consequences if that's not solved? >> What do people do to compromise the time problem? They subset. They give their developers, it's a 100 terabyte production database, they give them a terabyte or 1/2 a terabyte of actual subsetted data so they run their queries in development and they work great. Then they roll them into production, all of a sudden they break because 100 terabytes is a different animal. >> And that could be a terrible experience for the application where data has to drive all the value. So speed of data insertion into the application is the critical cloud negative and/or developer need. >> It drives quality. It drives customer satisfaction. It drives, quite frankly, in regulated industries, it drives compliance. >> I feel like the Geico commercial. Everybody knows that this is a problem. Why aren't people doing this? Is it just too hard? I mean, this is a card. What specifically do you guys have for IP? What makes it happen? What do you guys do? >> 57 patents later, we have cracked the code on how to do really application native virtualization of data and the ability to serve it up through workflows, through automation in some of the largest enterprises in the world. We are enterprise tested, battle tested. Quite frankly, the applications and data that serves the largest enterprises, that's where we shine. >> What are some of the value points you can point to anecdotally or publicly around the value your customers have gotten from having thae ability to have data addressable and almost in real-time for developers because there's got to be some new experiences or new capabilities that they're realizing. Can you share just some of things that come out of this? >> An IT leader in a major bank that you've heard of said to us after we went through the initial phase of deployment, you've just given me an extra quarter of development in every year. >> Extra quarter of time. >> Extra quarter of time. We've collapsed down and we now have five quarters of development cycles as opposed to four. That, quite frankly, if you put a dollar value on it is measured in the hundreds of millions of dollars. >> Developer productivity, any new cool things that have happened, top line revenue growth, any impact to applications? >> Absolutely, yeah. I mean, you think about what is the battle front now, whether it's online banking, whether it's retail, whether it's healthcare even. What is the battle front? It is your app, your phone, your mobile device. It is the ability to self-serve content, information and transactions. All of that is happening because people are transforming the way they're doing business around applications today. >> Customers are going to eat this up. You solve the holy grail problem. It's so obvious to us, but getting data in real-time, having speed and scale and relevance is super critical. How do you guys compare with the competition? Are you guys ahead? How do you guys compare versus other solutions? Are there anything like you guys? What's out in the marketplace? Share your perspective on the landscape on how you guys compare. >> You're asking a marketing guy how we compare to the competition. >> Of course you're going to say you blow them away? >> Of course, I have this very convenient chart that shows us being the leader compared to everybody. The reality is 3,000 customers, 37 countries, nine years in the marketplace. We have been there and done that at scale in the enterprise. Five of the top global 20 financial institutions. Four of the 10 energy companies in the world. Four of the 10 top retail organizations in the world. We have done it for the largest companies in the world and we continue to deliver value at scale in the enterprise. >> You said before hundreds of millions of value. That sounds like a lot and people might go, oh, but how do you do that? Your cloud and your devops which is all about agility and speed, if you take a net present value, a discounted cash flow, a break even or whatever curve you draw, and I think I heard three months, right? You compress that by a quarter and then look at the numbers, that's the value. >> Huge. >> So if it's $200 million in revenue, do the math. If it's $10 in revenue, okay, it's not going to be as much, but the companies that you're talking about, the industries, talking about big, big projects and a lot of revenue associated with them. You talked about cloud and devops, how is your business model cloud and devops? Can you talk about that in terms of the way we do business, customer to Actifio? >> Increasingly, cloud has been for us a place where all of these use cases are executed. As a result, the business model has been BYO. I'm going to buy a license from Actifio. I'm going to bring it to Amazon, Azure, Google, what have you. More and more we're seeing a mixture of marketplace transactions plus the traditional cloud marketplace. You mentioned Live Nation. They are in many ways way ahead of the curve in terms of just going wholesale. I'm out of the data center business. I'm all in on cloud and I'm just going to buy everything through the marketplace. Increasingly, we're seeing marketplace transactions becoming a relevant part of our business. The fact that we've integrated with the top six public cloud providers and increasingly we're going to expand out to Huawei and Alicloud and more, it's not just a destination to connect a use case. It is becoming a platform to conduct transactions as well. >> And a really important channel. >> Yeah, absolutely. >> Brian, great to hear from you. Congratulations on your success. Love the business model. We've been saying on theCUBE, so many years, data's at the center and the time to get the data from any database or a database into the application speed is critical. That makes great value so thanks for doing that. Appreciate it. >> Thank you guys. Always a pleasure to be here. >> Check out Actifio. Of course, we're bringing the data to you in real-time here on theCUBE at VMworld. We're live in Las Vegas. I'm John Furrier with Dave Vellante. Stay with us for more after this short break. (electronic music)

(upbeat music) >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're in our Palo Alto studio this morning for a CUBE Conversation talking about content marketing, attention economy, a lot of really interesting topics that should be top of mind for marketers, that we're in very interesting times on the B2C side and even more, I think, on the B2B side. So we're excited to have Randy Wootton, he's the CEO of Percolate. Randy, great to see you. >> Thanks very much for having me. A real pleasure to be here. >> Absolutely, so for those who aren't familiar, give us kind of the quick and dirty on Percolate. >> Percolate has been around for about seven years. It started as a social media marketing platform. So helping people, helping brands, build their brands on the social landscape, and integrating campaigns to deploy across the different social channels. Over the last couple of years, it's been moving more into the space called content marketing, which is really an interesting new area that marketers are coming to terms with. How do you put together content and orchestrate it across all the different channels. >> And it's interesting, a lot of vocabulary on the website around experiences and content not a lot about products. So how should marketers think and how does experience and content ultimately map back to the products and services you're trying to sell. >> Well, I do think that's a great point. And the distinction between modern brands, who are trying to create relationships with their consumers, rather than pushing products, especially if you're B2B, or technology pushing speeds and feeds. Instead, you are trying to figure out what is going to enable you to create a brand that consumers pull through versus getting pushed at. And so I think the idea around content marketing is that in some ways advertising isn't working anymore. People aren't paying attention to display ads, they're not clicking, they aren't processing the information. But, they are still buying. So the idea for marketers is, how do you get the appropriate content at the right time, to the right person, in their purchase journey. >> Right, and there's so many different examples of people doing new things. There's more conversations kind of, of the persona of the company, of the purpose, purpose driven things, really trying to appeal to their younger employees as well as a younger customer. You have just crazy off the wall things, which never fail to entertain. Like Geico, who seems to break every rule of advertising by having a different theme every time you see a Geico ad. So people are trying humor, they're trying theater, they're trying a lot of things to get through because the tough thing today is getting people's attention. >> I think so, and they talk a lot about the attention economy. That we live in a world of exponential fragmentation. All the information that we are processing across all these different devices. And a brand trying to break through, there's a couple of challenges, one is you have to create a really authentic voice, one that resonates with who you are and how you show up. And then, I think the second point is you recognize that you are co-building the brand with the consumers. It's no longer you build the Super Bowl ad and transmit it on T.V., and people experience your brand. You have this whole unfolding experience in real time. You've seen some of the airlines, for example, that have struggled with the social media downside of brand building. And so how do control, not control, but engage with consumers in a way that feels very authentic and it continues to build a relationship with your consumers. >> Yeah, it's interesting, a lot of things have changed. The other thing that has changed now is that you can have a direct relationship with that consumer whether you want it or not, via social media touches, maybe you were before, that was hidden through your distribution, or you didn't have that, that direct connect. So, you know, being able to respond to this kind of micro-segmentation, it's one thing to talk about micro-segmentation on the marketing side, it's a whole different thing with that one individual, with the relatively loud voice, is screaming "Hey, I need help." >> That's right, and I think there are a couple of things on that point. One is, I've been in technology for 20 years. I've been at Microsoft, I was at Salesforce, I was at AdReady, Avenue A, and Quantive. And now, Rocket Fuel before I came to Percolate. And I've always been wrestling with two dimensions of the digital marketing challenge. One is around consumer identity, and really understanding who the consumer is, and where they've been and what they've done. The second piece is around the context. That is, where they are in the moment, and which device they're on. And so, those are two dimensions of the triangle. The third is the content, or in advertising it's the creative. And that's always been the constraint. You never have enough creative to be able to really deliver on the promise of personalization, of getting the right message to the right person at the right time. And that now is the blockade. That now is the bottleneck, and that now is what brands are really trying to come to terms with. Is how do we create enough content so that you can create a compelling experience for each person, and then if there's someone who is engaging in a very loud voice, how do you know, and how do you engage to sort of address that, but not loose connections with all your other consumers. >> Right, it's interesting, you bring up something, in some of the research, in micro-moments. And in the old days, I controlled all of the information, you had to come for me for the information, and it was a very different world. And now, as you said, the information is out there, there's too much information. Who's my trusted conduit for the information. So by the time they actually get to me, or I'm going to try to leverage these micro-moments, it's not about, necessarily direct information exchange. What are some of these kind of micro-moments, and how are they game changers? >> Well, I think the fact that we can make decisions in near real time. And when I was at Rocket Fuel, we were making decisions in less than 20 milliseconds, processing something like 200 billion bid transactions a day, and so I just think people are not yet aware of the amount, the volume and the velocity of data that is being processed each and every day. And, to make decisions about specific moments. So the two moments I give as examples are: One, I'm sitting at home watching the Oakland Raiders with my two boys, I'm back on the couch and we're watching the game, and Disney makes an advertisement. I'm probably open to a Disney advertisement with my boys next to me, who are probably getting an advertisement at the same time by Disney. I'm a very different person in that moment, or that micro-moment than when I'm commuting in from Oakland to San Francisco on BART, reading the New York Times. I'm not open to a Disney ad at that moment, because I'm concentrating on work, I'm concentrating on the commute. And I think the thing that brands are coming to terms with is, how much am I willing to pay to engage with me sitting on the couch versus me sitting on BART. And that is where the real value comes from, is understanding which moments are the valuable ones. >> So there's so much we can learn from Ad Tech. And I don't think Ad Tech gets enough kind of credit for operating these really large, really hyper speed, really sophisticated marketplaces that are serving up I don't even know how many billions of transactions per unit time. A lot of activity going on. So, you've been in that world for a while. As you've seen them shift from kind of people driving, and buyers driving to more automation, what are some of the lessons learned, and what should learn more from a B2B side from this automated marketplace. >> Well, a couple of things, one is the machines are not our enemies, they are there to enable or enhance our capabilities. Though I do think it's going to require people to re-think work, specifically at agencies, in terms of, you don't need people to do media mixed modeling on the front end in Excel files, instead, you need capacity on the back end after the data has come out, and to really understand the insights. So there is some re-training or re-skilling that's needed. But, the machines make us smarter. It's not artificial intelligence, it's augmented intelligence. I think for B2B in particular what you're finding is, all the research shows that B2B purchasers spend something like 70 or 80% of their time in making the purchase decision before they even engage with the sales rep. And as a B2B company ourselves, we know how expensive our field reps are. And so to make sure that they are engaging with people at the right time, understanding the information that they would have had, before our sales cycle starts, super important. And I think that goes back to the content orchestration, or content marketing revolution that we are seeing now. And, you know, I that there is, when you think about it, most marketers today, use PowerPoint and Excel to have their marketing calendar and run their campaigns. And we're the only function left where you don't have an automated system, like a sales force for marketers, or a service now for marketers. Where a chief of marketing or a SVP of marketing, has, on their phone the tool of record, they system of record that they want to be able to oversee the campaigns. >> Right, although on the other hand, you're using super sophisticated A/B testing across multiple, multiple data sets, rather than doing that purchase price, right. You can test for colors, and fonts, and locations. And it's so different than trying to figure out the answer, make the investment, blast the answer, than this kind of DevOps way, test, test, test, test, test, adjust, test, test, test, test, adjust. >> You're absolutely right, and that's what, at Rocket Fuel, and any real AI powered system, they're using artificial intelligence as the higher order, underneath that you have different categories, like neural networks, deep learning and machine learning. We were using a logistic regression analysis. And we were running algorithms 27 models a day, every single day, that would test multiple features. So it wasn't just A/B testing, it was multi variant analysis happening in real time. Again, the volume and velocity of data is beyond human comprehension, and you need the machine learning to help you make sense of all that data. Otherwise, you just get overwhelmed, and you drown in the data. >> Right, so I want to talk a little bit about PNG. >> I know they're close and dear to your heart. In the old days, but more recently, I just want to bring up, they obviously wield a ton of power in the advertising spin campaign. And they recently tried to bring a little bit more discipline and said, hey we want tighter controls, tighter reporting, more independent third party reporting. There's this interesting thing going now where before, you know, you went for a big in, 'causethen you timed it by some conversion rating you had customers at the end. But now people it seems like, are so focused on the in kind of forgetting necessarily about the conversion because you can drive promoted campaigns in the social media, that now there's the specter of hmm, are we really getting, where we're getting. So again, the PNG, and the consumer side, are really leading kind of this next revolution of audit control and really closer monitoring to what's happening in these automated ad marketplaces. >> Well, I think what you're finding is, there's digital transformation happening across all functions, all industries. And, I think that in the media space in particular, you're also having an agency business model transformation. And what they used to provide for brands has to change as you move forward. PNG has really been driving that. PNG because of how much money they spend on media, has the biggest stick in the fight, and they've brought a lot of accountability. Mark Pritchard, in particular, has laid down these gauntlets the last couple of years, in terms of saying, I want more accountability, more visibility. Part of the challenge with the digital ecosystem is the propensity for fraud and lack of transparency, 'cause things are moving so quickly. So, the fact, that on one side the machines are working really well for ya, on the other side it's hard to audit it. But PNG is really bringing that level of discipline there. I think the thing that PNG is also doing really well, is they're really starting to re-think about how CPG brands can create relationships with their consumers and customers, much like we were talking about before. Primarily, before, CPG brands would work through distributors and retailers, and not really have a relationship with the end consumer. But now as they've started to build up their first party profiles, through clubs and loyalty programs, they're starting to better understand, the soccer mom. But it's not just the soccer mom, it's the soccer mom in Oakland at 4 o'clock in the afternoon, as she goes to Starbucks, when she's picked up her kids from school. All of those are features that better help PNG understand who that person is, in that context, and what's the appropriate engagement to create a compelling experience. That's really hard to do at the individual level. And when you think about the myriad of brands, that PNG has, they have to coordinate their stories and conversations across all of those brands, to drive market share. >> Yeah, it's a really interesting transformation, as we were talking earlier, I used to joke always, that we should have the underground railroad, from Cincinnati to Silicone Valley to get good product managers, right. 'Cause back in the day you still were doing PRD's and MRD's and those companies have been data driven for a long time and work with massive shares and small shifts in market percentages. But, as you said, they now, they're having to transform still data driven, but it's a completely different set of data, and much more direct set of data from the people that actually consume our products. >> And it's been a long journey, I remember when I was at Microsoft, gosh this would have been back in 2004 or 2005, we were working with PNG and they brought their brands to Microsoft. And we did digital immersions for them, to help them understand how they could engage consumers across the entire Microsoft network, and that would include X-Box, Hotmail at the time, MSN, and the brands were just coming to terms with what their digital strategy was and how they would work with Portal versus how they would work with other digital touchpoints. And I think that has just continued to evolve, with the rise of Facebook, with the rise of Twitter, and how do brands maintain relationships in that context, is something that every brand manager of today is having to do. My father, I think we were chatting a little earlier, started his career in 1968 as a brand manager for PNG. And, I remember him telling the stories about how the disciplined approach to brand building, and the structure and the framework hasn't changed, the execution has, over the last 50 years. >> So, just to bring it full circle before we close out, there's always a segment of marketing that's driven to just get me leads, right, give me leads, I need barcode scans at the conference et cetera. And then there's always been kind of the category of kind of thought leadership. Which isn't necessarily tied directly back to some campaign, but we want to be upfront, and show that we're a leading brand. Content marketing is kind of in-between, so, how much content marketing lead towards kind of thought leadership, how much lead kind of towards, actually lead conversions that I can track, and how much of it is something completely different. >> That's a great question, I think this is where people are trying to come to terms, what is content, long form, short form video. I think of content as being applied across all three dimensions of marketing. One is thought leadership, number two is demand gen, and number three is actualization or enablement in a B2B for your sales folks. And how do you have the right set of content along each of those dimensions. And I don't think they're necessarily, I fundamentally think the marketing funnel is broken. It's not you jump in at the top, and you go all the way to the bottom and you buy. You have this sort of webbed touch of experiences. So the idea is, going back to our earlier conversation, is, who is that consumer, what do you know about him, what is the context, and what's the appropriate form of content for them, where they are in their own buyer journey. So, a UGC video on YouTube may be okay for one consumer in a specific moment, but a short form video may be better for someone else, and a white paper may be better. And I think that people don't necessarily go down the funnel and purchase because they click on a search ad, they instead may be looking at a white paper at the end of the purchase, and so the big challenge, is the attribution of value, and that's one of the things that we're looking at Percolate. Is almost around thinking about it as content insight. Which content is working for whom. 'Cause right now you don't know, and I think the really interesting thing is you have a lot of people producing a lot of content. And, they don't know if it's working. And I think when we talk to marketers, that we hear their teams are producing content, and they want to know, they don't want to create content that doesn't work. They just want a better understanding of what's working, and that's the last challenge in the digital marketing transformation to solve. >> And how do you measure it? >> How do you measure, how do you define it? And categorize it, so that's one of the challenges, we were chatting a little bit before, about what you guys are doing at CUBE, and your clipper technology and how you're able to dis-aggregate videos, to these component pieces, or what in an AI world, you'd call features, that then can be loaded as unstructured data, and you can apply AI against it and really come up with interesting insights. So I think there's, as much as I say, the transformation of the internet has been huge, AI is going to transform our world more than we even can conceive of today. And I think content eventually will be impacted materially by AI. >> I still can't help but think of the original marketing quote, I've wasted half of my marketing budget, I'm just not sure which half. But, really it's not so much the waste as we have to continue to find better ways to measure the impact of all these kind of disparate non-traditional funnel things. >> I think you're right, I think it was Wanamaker who said that. I think your point is spot on, it's something we've always wrestled with, and as you move more into the branding media, they struggle more with the accountability. That's one of the reasons why direct response in the internet has been such a great mechanism, is because it's data based, you can show results. The challenge there is the attribution. But I think as we get into video, and you can get to digital video assets, and you can break it down into its component pieces, and all the different dimensions, all of that's fair game for better understanding what's working. >> Randy, really enjoyed the conversation, and thanks for taking a minute out of your busy day. >> My pleasure, always enjoy it. >> Alright, he's Randy, I'm Jeff, you're watching theCUBE from Palo Alto Studios, thanks for watching. (digital music)