>>Okay. Okay. We're back at Caesar's Forum. The Snowflake summit 2022. The cubes. Continuous coverage this day to wall to wall coverage. We're so excited to have the analyst panel here, some of my colleagues that we've done a number. You've probably seen some power panels that we've done. David McGregor is here. He's the senior vice president and research director at Ventana Research. To his left is Tony Blair, principal at DB Inside and my in the co host seat. Sanjeev Mohan Sanremo. Guys, thanks so much for coming on. I'm glad we can. Thank you. You're very welcome. I wasn't able to attend the analyst action because I've been doing this all all day, every day. But let me start with you, Dave. What have you seen? That's kind of interested you. Pluses, minuses. Concerns. >>Well, how about if I focus on what I think valuable to the customers of snowflakes and our research shows that the majority of organisations, the majority of people, do not have access to analytics. And so a couple of things they've announced I think address those are helped to address those issues very directly. So Snow Park and support for Python and other languages is a way for organisations to embed analytics into different business processes. And so I think that will 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 most people in the organisation or not, analysts, they're doing some line of business function. Their HR managers, their marketing people, their salespeople, their finance people right there, not sitting there mucking around in the data. They're doing a job and they need analytics in that job. So, >>Tony, I thank you. I've heard a lot of data mesh talk this week. It's kind of funny. Can't >>seem to get away from it. You >>can't see. It seems to be gathering momentum, but But what have you seen? That's been interesting. >>What I have noticed. Unfortunately, you know, because the rooms are too small, you just can't get into the data mesh sessions, so there's a lot of interest in it. Um, it's still very I don't think there's very much understanding of it, but I think the idea that you can put all the data in one place which, you know, to me, stuff like it seems to be kind of sort of in a way, it sounds like almost like the Enterprise Data warehouse, you know, Clouded Cloud Native Edition, you know, bring it all in one place again. Um, I think it's providing, sort of, You know, it's I think, for these folks that think this might be kind of like a a linchpin for that. I think there are several other things that actually that really have made a bigger impression on me. Actually, at this event, one is is basically is, um we watch their move with Eunice store. Um, and it's kind of interesting coming, you know, coming from mongo db last week. And I see it's like these two companies seem to be going converging towards the same place at different speeds. I think it's not like it's going to get there faster than Mongo for a number of different reasons, but I see like a number of common threads here. I mean, one is that Mongo was was was a company. It's always been towards developers. They need you know, start cultivating data, people, >>these guys going the other way. >>Exactly. Bingo. And the thing is that but they I think where they're converging is the idea of operational analytics and trying to serve all constituencies. The other thing, which which also in terms of serving, you know, multiple constituencies is how snowflake is laid out Snow Park and what I'm finding like. There's an interesting I economy. On one hand, you have this very ingrained integration of Anaconda, which I think is pretty ingenious. On the other hand, you speak, let's say, like, let's say the data robot folks and say, You know something our folks wanna work data signs us. We want to work in our environment and use snowflake in the background. So I see those kind of some interesting sort of cross cutting trends. >>So, Sandy, I mean, Frank Sullivan, we'll talk about there's definitely benefits into going into the walled garden. Yeah, I don't think we dispute that, but we see them making moves and adding more and more open source capabilities like Apache iceberg. Is that a Is that a move to sort of counteract the narrative that the data breaks is put out there. Is that customer driven? What's your take on that? >>Uh, 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 hugely beneficial to the customers to the users, because now, if you have large amounts of data in parquet files, you can leave it on s three. But then you using the the Apache iceberg table format. In a snowflake, you get all the benefits of snowflakes. Optimizer. So, for example, you get the, you know, the micro partitioning. You get the meta data. So, uh, in a single query, you can join. You can do select from a snowflake table union and select from iceberg table, and you can do store procedures, user defined functions. So I think they what they've done is extremely interesting. Uh, 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, >>right? There's hence the delta. And maybe that maybe that closes over time. I want to ask you as you look around this I mean the ecosystems pretty vibrant. I mean, it reminds me of, like reinvent in 2013, you know? But then I'm struck by the complexity of the last big data era and a dupe and all the different tools. And is this different, or is it the sort of same wine new new bottle? You guys have any thoughts on that? >>I think it's different and I'll tell you why. I think it's different because it's based around sequel. So if back to Tony's point, these vendors are coming at this from different angles, right? You've got data warehouse vendors and you've got data lake vendors and they're all going to meet in the middle. So in your case, you're taught operational analytical. But the same thing is true with Data Lake and Data Warehouse and Snowflake no longer wants to be known as the Data Warehouse. There a data cloud and our research again. I like to base everything off of that. >>I love what our >>research shows that organisation Two thirds of organisations have sequel skills and one third have big data skills, so >>you >>know they're going to meet in the middle. But it sure is a lot easier to bring along those people who know sequel already to that midpoint than it is to bring big data people to remember. >>Mrr Odula, one of the founders of Cloudera, said to me one time, John Kerry and the Cube, that, uh, sequel is the killer app for a Yeah, >>the difference at this, you know, with with snowflake, is that you don't have to worry about taming the zoo. Animals really have thought out the ease of use, you know? I mean, they thought about I mean, from the get go, they thought of too thin to polls. One is ease of use, and the other is scale. And they've had. And that's basically, you know, I think very much differentiates it. I mean, who do have the scale, but it didn't have the ease of use. But don't I >>still need? Like, if I have, you know, governance from this vendor or, you know, data prep from, you know, don't I still have to have expertise? That's sort of distributed in those those worlds, right? I mean, go ahead. Yeah. >>So the way I see it is snowflake is adding more and more capabilities right into the database. So, for example, they've they've gone ahead and added security and privacy so you can now create policies and do even set level masking, dynamic masking. But most organisations have more than snowflake. So what we are starting to see all around here is that there's a whole series of data catalogue companies, a bunch of companies that are doing dynamic data masking security and governance data observe ability, which is not a space snowflake has gone into. So there's a whole ecosystem of companies that 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 so that way, you know, snowflakes done a great job of enabling that ecosystem about >>the stream lit acquisition. Did you see anything here that indicated there making strong progress there? Are you excited about that? You're sceptical. Go ahead. >>And 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, 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, um, to San James Point. I think part of it, this kind of plays into it is what makes this different from the ado Pere is the fact that this all these capabilities, you know, a lot of vendors are taking it very seriously to make put this native obviously snowflake acquired stream. Let's so we can expect that's extremely capabilities are going to be native. >>And the other thing, too, about the Hadoop ecosystem is Claudia had to help fund all those different projects and got really, really spread thin. I want to ask you guys about this super cloud we use. Super Cloud is this sort of metaphor for the next wave of cloud. You've got infrastructure aws, azure, Google. It's not multi cloud, but you've got that infrastructure you're building a layer on top of it that hides the underlying complexities of the primitives and the a p I s. And you're adding new value in this case, the data cloud or super data cloud. And now we're seeing now is that snowflake putting forth the notion that they're adding a super path layer. You can now build applications that you can monetise, which to me is kind of exciting. It makes makes this platform even less discretionary. We had a lot of talk on Wall Street about discretionary spending, and that's not discretionary. If you're monetising it, um, what do you guys think about that? Is this something that's that's real? Is it just a figment of my imagination, or do you see a different way of coming any thoughts on that? >>So, in effect, they're trying to become a data operating system, right? And I think that's wonderful. It's ambitious. I think they'll experience some success with that. As I said, applications are important. That's a great way to deliver information. You can monetise them, so you know there's there's a good economic model around it. I think they will still struggle, however, with bringing everything together onto one platform. That's always the challenge. Can you become the platform that's hard, hard to predict? You know, I think this is This is pretty exciting, right? A lot of energy, a lot of large ecosystem. There is a network effect already. Can they succeed in being the only place where data exists? You know, I think that's going to be a challenge. >>I mean, the fact is, I mean, this is a classic best of breed versus the umbrella play. The thing is, this is nothing new. I mean, this is like the you know, the old days with enterprise applications were basically oracle and ASAP vacuumed up all these. You know, all these applications in their in their ecosystem, whereas with snowflake is. And if you look at the cloud, folks, the hyper scale is still building out their own portfolios as well. Some are, You know, some hyper skills are more partner friendly than others. What? What Snowflake is saying is that we're going to give all of you folks who basically are competing against the hyper skills in various areas like data catalogue and pipelines and all that sort of wonderful stuff will make you basically, you know, all equal citizens. You know the burden is on you to basically we will leave. We will lay out the A P. I s Well, we'll allow you to basically, you know, integrate natively to us so you can provide as good experience. But the but the onus is on your back. >>Should the ecosystem be concerned, as they were back to reinvent 2014 that Amazon was going to nibble away at them or or is it different? >>I find what they're doing is different. Uh, for example, data sharing. They were the first ones out the door were data sharing at a large scale. And then everybody has jumped in and said, Oh, we also do data sharing. All the hyper scholars came in. But now what snowflake has done is they've taken it to the next level. Now they're saying it's not just data sharing. It's up sharing and not only up sharing. You can stream the thing you can build, test deploy, and then monetise it. Make it discoverable through, you know, through your marketplace >>you can monetise it. >>Yes. Yeah, so So I I think what they're doing is they are taking it a step further than what hyper scale as they are doing. And because it's like what they said is becoming like the data operating system You log in and you have all of these different functionalities you can do in machine learning. Now you can do data quality. You can do data preparation and you can do Monetisation. Who do you >>think is snowflakes? Biggest competitor? What do you guys think? It's a hard question, isn't it? Because you're like because we all get the we separate computer from storage. We have a cloud data and you go, Okay, that's nice, >>but there's, like, a crack. I think >>there's uniqueness. I >>mean, put it this way. In the old days, it would have been you know, how you know the prime household names. I think today is the hyper scholars and the idea what I mean again, this comes down to the best of breed versus by, you know, get it all from one source. So where is your comfort level? Um, so I think they're kind. They're their co op a Titian the hyper scale. >>Okay, so it's not data bricks, because why they're smaller. >>Well, there is some okay now within the best of breed area. Yes, there is competition. The obvious is data bricks coming in from the data engineering angle. You know, basically the snowflake coming from, you know, from the from the data analyst angle. I think what? Another potential competitor. And I think Snowflake, basically, you know, admitted as such potentially is mongo >>DB. Yeah, >>Exactly. So I mean, yes, there are two different levels of sort >>of a on a longer term collision course. >>Exactly. Exactly. >>Sort of service now and in salesforce >>thing that was that we actually get when I say that a lot of people just laughed. I was like, No, you're kidding. There's no way. I said Excuse me, >>But then you see Mongo last week. We're adding some analytics capabilities and always been developers, as you say, and >>they trashed sequel. But yet they finally have started to write their first real sequel. >>We have M c M Q. Well, now we have a sequel. So what >>were those numbers, >>Dave? Two thirds. One third. >>So the hyper scale is but the hyper scale urz are you going to trust your hyper scale is to do your cross cloud. I mean, maybe Google may be I mean, Microsoft, perhaps aws not there yet. Right? I mean, how important is cross cloud, multi cloud Super cloud Whatever you want to call it What is your data? >>Shows? Cloud is important if I remember correctly. Our research shows that three quarters of organisations are operating in the cloud and 52% are operating across more than one cloud. So, uh, two thirds of the organisations are in the cloud are doing multi cloud, so that's pretty significant. And now they may be operating across clouds for different reasons. Maybe one application runs in one cloud provider. Another application runs another cloud provider. But I do think organisations want that leverage over the hyper scholars right they want they want to be able to tell the hyper scale. I'm gonna move my workloads over here if you don't give us a better rate. Uh, >>I mean, I I think you know, from a database standpoint, I think you're right. I mean, they are competing against some really well funded and you look at big Query barely, you know, solid platform Red shift, for all its faults, has really done an amazing job of moving forward. But to David's point, you know those to me in any way. Those hyper skills aren't going to solve that cross cloud cloud problem, right? >>Right. No, I'm certainly >>not as quickly. No. >>Or with as much zeal, >>right? Yeah, right across cloud. But we're gonna operate better on our >>Exactly. Yes. >>Yes. Even when we talk about multi cloud, the many, many definitions, like, you know, you can mean anything. So the way snowflake does multi cloud and the way mongo db two are very different. So a snowflake says we run on all the hyper scalar, but you have to replicate your data. What Mongo DB is claiming is that one cluster can have notes in multiple different clouds. That is right, you know, quite something. >>Yeah, right. I mean, again, you hit that. We got to go. But, uh, last question, um, snowflake undervalued, overvalued or just about right >>in the stock market or in customers. Yeah. Yeah, well, but, you know, I'm not sure that's the right question. >>That's the question I'm asking. You know, >>I'll say the question is undervalued or overvalued for customers, right? That's really what matters. Um, there's a different audience. Who cares about the investor side? Some of those are watching, but But I believe I believe that the from the customer's perspective, it's probably valued about right, because >>the reason I I ask it, is because it has so hyped. You had $100 billion value. It's the past service now is value, which is crazy for this student Now. It's obviously come back quite a bit below its IPO price. So But you guys are at the financial analyst meeting. Scarpelli laid out 2029 projections signed up for $10 billion.25 percent free time for 20% operating profit. I mean, they better be worth more than they are today. If they do >>that. If I If I see the momentum here this week, I think they are undervalued. But before this week, I probably would have thought there at the right evaluation, >>I would say they're probably more at the right valuation employed because the IPO valuation is just such a false valuation. So hyped >>guys, I could go on for another 45 minutes. Thanks so much. David. Tony Sanjeev. Always great to have you on. We'll have you back for sure. Having us. All right. Thank you. Keep it right there. Were wrapping up Day two and the Cube. Snowflake. Summit 2022. Right back. Mm. Mhm.

. >>Okay, welcome back. This is live in Las Vegas. This is the end of day one. This is our wrap up segment of the cube at Splunk conference dot conference 2013. I'm John furrier with Dave Alante, my cohost and Jeff Kelly making an appearance in this segment has been scouring for stories, talking to all the folks, talking to the CEO, talking to all the people on the team, customers scouring the web. Guys, welcome to the wrap up. Thank you John. John guys, I gotta I gotta say I'm really impressed with what Splunk's done here. Um, and with post IPO you kind of see what people are made of when they have to do transitional things day. We know we do and I've seen companies pivot, turn on a dime. You guys certainly have helped companies, you know, get into that, into the, into the thermal growth and um, but here a companies succeeding, um, they hit a rocket ship growth. >>They go public. A lot of challenges could be distraction, but certainly, uh, my impression is no distraction here. Splunk certainly is hitting cruising altitude only getting better and stronger. Certainly the customer acquisition numbers as strong and their partner ecosystem is great. Their keynote and fan based or customers are loyal. All in all, Dave, I've got to say, you know Splunk's looking really good. Yeah, John. I mean I think you see a lot of different models. This is too broad models. I guess in the, in the it business one is the safe bet. It's, it's IBM, it's, it's HP, it's, it's EMC, it's Oracle, it's Cisco. I mean you're going to do business with those companies because you know they're going to deliver a product and they're going to stand behind it and they're going to service you and then you got the 10 X value proposition companies, that's companies like Tableau service now Workday, Splunk, these are the companies that are really transforming their irreverence. >>Steve Cohen said disruptive, they're disruptive so they got a little mojo going and I'm gone. But at the same time, customers are willing to take a chance because the value proposition is so compelling and so transformative to their business and they can't get that from their traditional it suppliers despite what the traditional it suppliers are telling them. So I love that kind of mojo at a, at a, at an event like this. Jeff Kelly, I want to go to you for a second. Let's talk about what you're finding us. Show us who you are on the, on the, uh, we had a crowd chat today w you know, preparing them for Hadoop world and big data in New York city. A quick programming note. Um, we, the Q will be in New York city for strata conference. Had duper world covering that in con in concert to the big data New York city event going on as well that week. >>Um, but you're out, you did a chat this morning about big data with Hadoop ecosystem. A lot of had doopy we had cloud era MRR Dhalla on, they have a relationship also with Hortonworks. Um, what did you find out there? What stories did you dig in? What observations did you find? Well, very much like a, the last show we were at a Tableau's customer conference. It's a really excited, uh, customer base here. These, these customers, uh, you know, are, are clapping and cheering during the keynote. It's something you don't necessarily see more than excited. They're giddy, right? I mean, right. They're there, they're getting yapping, they're hooting or hollering, right. And, and there's really a sense of community around the, around the customer base. They love to trade stories. They love to trade best practices. The hackathon, last night I was at, uh, you know, just rooms filled off the, off the corridors here at the, uh, the cosmopolitan. >>They were there till 11 o'clock at night. They were in there, you know, they had, uh, some, some, some, some TV going at, I saw a rerun of Alf playing on the big screen for some reason. I guess that's a popular with the group here. But anyways, these guys were up there all night. You know, they're coding the drinking beers, they're having a good time. Uh, they really enjoy this. You didn't, it's not something you see at eight. At one of the, a larger events, some of the mega vendors we see. Um, you know, the other thing, you know, Mike coming into this Splunk I think was really early on, uh, recognizing the, the value that providing applications that allow you to really manipulate and understand data. Really they saw the value of that very early. Obviously that's, they base their whole premise of their organization on that. >>Oh, they have re, you know, kind of written this wave, uh, of big data, all things big data. And they're one of the few companies out there that are actually selling and providing applications that allow people and make sense of, um, in this case, machine generated data, but they're expanding to other data types. Um, the key for them I think going forward is to continue innovating. You know, they've kinda got that lead, uh, I think because they were the, one of the first out of the gate to recognize the value in this. They gotta keep innovating. And I think you saw with the announcements today, clearly they are, uh, the cloud, uh, option that they unveiled today was very popular. Um, and it's going to help them, especially against some of the more nimble startups. It's funny, it's, Splunk is now kind of a kind of a big established company in a sense in this large, in this big data world, there are companies like om Bogley and Sumo logic who are coming at Splunk doing similar things, but doing it from a cloud perspective, well sponsored down. >>Got an answer for that. Why would I want to ask you guys about that? Because you know, John, Jeremy Burton, we, you know, made, we were there when cloud met big data and so people have been putting those two together. But you take a company like Splunk and a couple of like Tableau, not big cloud plays. What about that cloud meets big data? Is that, is that a misconception on the industry's part or not? Or is it a fundamental requirement that cloud meets big data? I think it's a fundamental requirement as you know, we were, you know, close to EMC when they put that together and we had the first cloud mobile social editorial. You guys had the first real research around those three pillars. Um, and big data just became a, came out of social and cloud and since the cloud era, you know, pun intended with Cloudera, the company, um, but you know, Dave, we saw this from day one. >>This is a fundamental economic wealth creating inflection point, meaning new companies, new brands going to emerge that are going to change the game and this is where all the chips are on the table and you're seeing the incumbent vendors like EMC changed their game and go cloud meets big data and go in there. And EMC, I give Ian, Jeremy Burton a lot of credit. He saw the work we were doing. He saw the marketplace, he came fresh into EMC and said cloud and big data. Those are the two pillars. He bet the ranch on that and the beds coming home. Jeremy is making more money than any, even not a CMO anymore. He's the executive vice president doing great just on the stock options. He made a good bet that's playing out who's also a great executive with some product shops. Absolutely. Table stakes in my opinion. >>Um, that the application market is going to be enabled by that. So, Jeff, Kelly, so I've got to ask you, there are forces that you mentioned you've got open source. Uh, you've got some new players that are or have seen the opportunity that Splunk has created, the, they're going to have to Splunk. So, so what's your prediction here? I mean, you've got, you've got a public company now, they've got more resources. They're clearly a leader in the, in the business, but you got other companies coming after him. Not only start us, you know, we were at, um, we were at HP, uh, the, the Vertica user group, they were talking about, you know, their Splunk killer. Uh, you hear it all the time. Oh, we can do that. We can do that. What does that all mean for Splunk? Well, the good news for Splunk is they're, they're, they're ahead of everybody in this game because they've been doing this for longer. >>Uh, you know, they, they, they have a, a more generally accepted among the customers, uh, you know, a better application for VMware, for instance. So they're actually ahead of a lot of these other vendors, VMware itself trying to claim Oh yeah, it'd be where it says, well now we've got a tool for monitoring that's just as good as Splunk. Well, you know, if you talk to some of the people using the Splunk app for VM ware, they'll disagree with that. So bottom line is, you know, this is a little bit simplified, but people really like the Splunk user interface in the application. It's very easy to use and that's something that you can't necessarily replicate. So, you know, it'll take, it'll take some time for some of these players to catch up. But you know, back to the point John was making this whole idea of cloud and big data and you're asking, you know, is that really, is that really the, the, the two mega trends here? >>And I think absolutely when we start talking about, uh, industrial internet, internet of things, whatever term you wanna use, we're, we're years away from that really being a, a reality I think in terms of it's an interconnected world, but clearly the two key enabling technologies are going to be big data, making sense of all those connected devices and cloud being able to connect them in a way that that makes sense. Um, where you can't do that in an on premise situation if you've got isolated data centers. Now the other thing, this company who started in 2005, it's yet another Silicon Valley success story. John, I mean it's just Silicon Valley is just running the table. What's your take on the Valley action going on here? I think Silicon Valley is going to continue to do well and, and um, and rule the road here and on IPOs and success. >>Silicon Valley is the ecosystem that drives a lot of wellness to wall street of startups. However, there are, there are a lot of successes outside of Silicon Valley. This is just another string of, of successes. Um, but Dave, this is an absolute poster child in my opinion, of a venture that could have gone the wrong way. I mean, Splunk was not a shining star when it got funded. It took two visionary venture capitalists, Nick and David Hornick, Nick from, uh, he'd know the ignition and uh, David Hornik from August capital made the bet. They bet on technical founders, they bet on the right product guys. It was in small tools and it was at the time it was, wasn't the trendy thing. This is pre big data. This is log files. They saw a problem, they saw a good team. Now this thing could've gone off the rails, right? >>If you look at today's market, this is what I worry about all this startup environment is that all the different funding dynamics, all of this crowd sourcing this, that you've got to have good investors. This is a great example of great investors back in their guys back on their team because this thing could have been off the rails in the fourth year. Okay. Product strategy, debate, board room dynamics, people not paying attention, uh, asleep at the switch as we say. And this is, this is an example of a company done right. They hit the growth curve, big data swooped in, they had a great product, happy customers and incrementally move the ball down the field. And finally, you know, scored the big long ball with the touchdown with big data. And I think, you know, it's classic. These are football analogies, you know, first down, first down, first down, and then big data comes down. >>They throw the ball in the end zone, touchdown home run. There it is. That's the IPO. That's the success story. There's a fine line between. Good and great here. Isn't there though? I mean, like you say, I mean who even Steven Cohen was saying, uh, uh, uh, not, not Steve Sorkin, sorry. Steven. I was saying that he didn't, could've never predicted, you know, where they'd be today, the IPO, et cetera. So there is a fine line. You could go, well, this is the thing, this is my point. If you look at Splunk, right? Dave, they could have, no one was buying their stuff initially. Right, and so except for some tech geeks, no one was kind of get it, but the recession hit and people weren't spending in 2008 that was a big surge and you saw the spending and Splunk became a great solution because for very little cash you can come in and create business value. >>That was a really, really important moment in the company's history, David, and what's also happened is they believed in their own product. You heard from the people here culture, they're Everett, they're disruptive, they use their own product and they focused on the customer. Those two things, good timing still is, you know, comes to people who are prepared. I mean it's not an, I mean, it's not enough to just have a big market. It's not enough to just have a lot of capital behind you. You need other ingredients obviously to succeed. I'm afraid the younger generation doesn't understand the startup world is you can't just magically put pixie desk and get the home run. You got some times really be in a good position as they say in basketball and be ready for the rebound off the rim. In this case it log file tool with good technology moves into the big data world and hello, they're got an enterprise customers. >>Part of, I think part of it is, look, you've got to admit, part of it is luck and timing. You've got to have that on your side. But they've also got a really good product and they're smart enough when that, when those opportunities present themselves to take them. I think they are. Again, timing is fantastic for them right now. We've been talking about the, uh, the year of the big data application and we're really still waiting for that. They are in a really good position right now to really take advantage of all the interest in, you know, SQL on Hadoop, interactive analytics on Hootsuite. Well guess what, they've got a product and hunk a cute name, but a good product that allows you to get right in there as a business user and start analyzing, searching data using a circular base. I gotta tell you it's a very good looking product and people are looking for this. >>People are like, well, how am I going to get all that value product? I'm going to get all that value out of Hadoop sense bugs in answer hunk. You got the naming convention, interesting names, but nevertheless they've got a, they've got a play right now in an area that's got a lot of interest and they've got, they've got the track record in the log data to actually show they've got, they know how to, they know what they're doing. I don't remember Mike Olson to cloud Hadoop worlds ago, announced the the application tsunami. That kind of never came the way they said. We said the analytics was a killer app. In the meantime, as the market kind of catches up, we still haven't seen that application framework, but yet still analytics is the killer app, right? It's definitely the killer app. I think. Well, the analytics for the masses is the, is the killer app and that's the Holy grail that everybody's going after. >>And I'm not, I'm not declaring Splunk is there. I don't think Splunk is there. I don't think anybody's there yet. You talk to a Tableau customers, you talk to Splunk customers, they're not there yet, but they're closer than the BI crowd ever was. They're certainly closer than the traditional BI players. And they, and then that's because they don't have that legacy architecture to deal with. But there's also a cultural issue. It's not just the technology of the products, it's getting business users to understand how to look at data and look at it as, as an asset and something that you can actually drive. Timing's right for that. Absolutely. So I want to wrap up and ask you guys some follow up questions at the close, the segment out, first impressions of day one and what are you looking for for day two? Jeff, we'll start with you. >>I am first impressions. You know, like I said, very excited, uh, base of customers here and you know, 18,000, 1800, excuse me. Plus customers, 18,000. That'll be a few years. But, uh, nevertheless a good showing here. Uh, I think tomorrow, you know, on the cube, we're going to look for certainly some more customer stories. Um, you know, it's always interesting to hear from customers because they are on the front lines. They're using the product every day. So I expect to see a lot more of that. Um, and really tomorrow I think is going to be a lot about, a lot about uh, these customers networking with one another and I'm hoping to get out there. Let's add on the question to, uh, to you then, then to Dave. Same thing. What's the challenges for Splunk as well? I think the challenge for me is from, from my perspective is to continue and make the, make the cloud play real, continuing to invest in that, uh, and that product and that approach. >>Um, as we met, as I mentioned a minute ago, I think cloud and big data are critical to really leveraging industrial internet, the internet of things. And if Splunk wants to be a key player there, they've got to really fill out that portfolio of cloud based capabilities. I know you said David, go first. Sorry for me. For me, John, we heard from the executives today, very strong story. We heard very solid product lineup. It's very clear in talking to customers that there's, there's passion here, there's real traction. Um, it's substantive. To me. The big thing is ecosystem. I feel as though the ecosystem here at Splunk is, is, is good, but I feel like it's not been as deliberate as it can be. I think Splunk has a ways to go there. I think that is one of the leverage points that this company really has to focus on. >>Because like today we talked about earlier, 45% of Splunk sales goes through the channel. I think it's gotta be way, way, way higher than that. Now they're making great progress, but I think that they've got to have a goal of getting to 70% and that comes through the ecosystem. It's gonna take some time. It's going to take some investment. That's really where, to me, the big upside is for this company and my impression is I'm very impressed with Splunk. I'm very impressed with the ecosystem. I'm impressed by the rabid fan base of their customers who are proud of the private name getting exemplifies my point about startups having a great product focus products will win. Again, you know, the four P's of marketing, they teach you in marketing one Oh one one of those products. Um, but the challenge is, Dave, I would, I would agree with you. >>The ecosystem is a challenge. Good news is they have a great turnout here. Um, you're not, there's no lightweights out there, all heavyweights in terms of what they're doing with tech and their value proposition. So, you know, gray star for the ecosystem. So I think it's looking good off the tee to use the golf analogy, um, landing in the fairway. So, so that's one. My big, my big thing on the challenges for Splunk and that I'm watching is the cloud. I think moving to the cloud is not as easy as it appears, although that's the value proposition. So to move the DNA of the company with the pressure to drive revenue, luckily the market's kind of moving to them right now. So it might be a, a rising tide floats all boats. Moving to the cloud is very, very difficult. And I think that's gonna be a key challenge. >>We're going to keep watching them look at what SAP has challenged the cloud. They've had multiple restarts and misfires. Now they've seen them get their groove back with HANA. I think this could be a big challenge for Splunk and we're going to, I'm going to watch their cloud and that's going to be my focus then tomorrow. I would agree with that. I would just say on the ecosystem point, um, I, I think they would actually, I think they do have more work to do Dave, but I think they're in a really good position because some of the Hudu players, for instance, knees, Splunk, I think more than Splunk means to them right now. Okay. We're going to close down what the government is closing down right now. So, you know, that's, uh, that's, uh, we'll be back tomorrow because we work for free open source content, um, programming node. >>Next weekday we're gonna talk about big data and internet of things. I'll be interviewing the CEO of GE. Um, I'm really proud of you, John, for, uh, being selected out of the zillion people that they could choose. They chose you to, to host this panel. Yeah, that's fantastic. It might be my last, but we'll see. Moving some Q mojo to the GE event, industrial internet next week in Chicago. Minds and machines, another player to watch. Guys. Great day and great wrap up here. And that's day one. Wrap in the books tomorrow here when we go to the party tonight, find out what's going on here at, at, uh, inside the cube, inside a Splunk conference. Dot conference. 2013. I'm John furrier with Dave Alante and Jeff Kelly Wiki bond with back tomorrow. Goodnight. And, and join us tomorrow.