 From San Jose in the heart of Silicon Valley, it's theCUBE covering Big Data SV 2016. Now your host, John Furrier and George Gilbert. Okay, welcome back everyone. We are here live in Silicon Valley for theCUBE. This is Silicon Angles flagship program where we go out to the events and extract the signal from the noise. I'm John Furrier, my co-host. George Gilbert, analyst at BigData at wikibon.com. Our next guest is Christina Norrin, who's the CPO at Interana. Just announced, just joined the company two weeks ago. Welcome to theCUBE. Glad to be here. Love your background, been at Splunk in the early days. Saw that growth prior to the IPO and was it through the IPO? Yeah, so I joined when we were still in stealth mode and no one knew who we were and we hadn't decided we were gonna be open source or closed source and stayed there through the IPO. So that's a great wave that you wrote. One, you guys invented and pioneered a ton of the stuff that we see today, land and expand, SaaS, BigData, value creation, kind of creating the gold out of the trash and they say in data, log data if you will. But now you're at Interana, talk about the new company, the new role, Chief Product Officer, which is fantastic. We love product folks in theCUBE, share a little bit about this new company you're with. Yeah, so Interana is fabulous. I learned about it through my network and the more I got to know it, the more I realized that it was picking up everything that was still left to do around event data that really has excited me about it because Splunk was my first go at event data. You know, I first was group manager for data ceremony monitoring at MSN in the late 90s dealing with this class of data. And when I learned about Interana, Interana really was returning me to that original passion of giving the decision makers and the product managers and the growth people and the marketing people, the people who are deciding what services to roll out, how to design them, how to market them, giving them direct access to the value that's in this event data. And I feel like a lot of the last few years in this sort of big data space that's gotten created has been returning everything to the high priest of data. And so this was getting back to that sort of user focus that really inspires me and as Chief Product Officer, what I get to do is make that as immediately obvious as possible to all of the users that we're really building this for. And so that's exciting. You know, one of the things you're, the tagline for the company is the behavioral analytics solutions for event data at scale, the keyword behavioral data. You mentioned some of the things at MSN and you know, I have a search background and you look at that back in the day, behavioral and contextual where the gods of how things got done on search. And then now you got Web 2.0 and you got Splunk. So this behavior of data is interesting. So the pattern recognition, machine learning, a lot of tech involved imagining. Now you have this event data, the log data, whatever you want it, wherever it is in multiple systems are really the nuggets to stitch together insights. Share what that means today because search was pretty much in a siloed system, platform specific, but now out in the wild, all this data's out there. Well, I mean, I think that there have been different challenges at different times with this class of data and there's been a very slow building realization about all the value that's in this data and it's spread very slowly through different organizations. And so the workloads to answer questions that marketers might have or that growth people might have or product managers might have are inherently different workloads because they're more concerned, like as a product manager, I'm concerned with a user's journey through my product. I don't care if it's a commercial product for enterprises, enterprise product like Sponk or Inarana or if it's a consumer product, I care about the user's journey, which is a very different analytic workload on the same data than what an IT person doing troubleshooting or a security person looking at security threats wants to do. And so this is the first system that's been able to look at the kinds of scale of data that our customers at Inarana, like a Tender, like a Sotos, these companies have, you know, Microsoft Bing. You know, these companies have a scale of data where the business people have been forced to accept summaries that aren't very insightful and don't let them really watch that user journey. So that's what's different. Take us through what entices you to join this company. Obviously, your background fits perfectly at a unique perspective, which is amazing. And we love that. Was it the product roadmap? Did they have a product roadmap? Did you just, what did you glob onto? What was the big aha moment for you when you looked at what Inarana was doing? It was a combination of the vision, the people and their ability to execute on that vision and the technology that they've built. And then the customer validation is important, but I've been in this space a long time. So, you know, it's like, that was interesting. But the real thing was that the vision was one I could really get behind. And the people, I mean, this has been just an amazing team to get to know and see how able everybody in the company is to really, you know, to really do their part in making this, you know, making this something that users can actually discover and use. But from a technology perspective, as I started to learn building block by building block, I realized that some things they were doing, were things that I'd seen done before at different times, but I knew to be the right thing if this is a set of things you wanna do with the data. And some things were totally brand new. And it was like, oh, well this would allow us to do the things that I haven't been able to do in the past. And it's a very, and then the timing. And I think that the, you know, some of these use cases, you know, I and people around me, we've had Inar sites for a long time, but it's pretty obvious, this is where the customer validation comes in, is, you know, at these large customers that Inarana has, there are places where hundreds of people are routinely logging into Inarana. And that's a readiness of the people who have value to get in this data that hasn't been seen before. Let me ask, I wanna key in on two things you were mentioning. One that we seem to have gone back to the high priests of data. And, you know, one of the qualities good or bad with Hadoop gives you, you know, great flexibility, mix and match capabilities. But, you know, almost as if they're acknowledging the issue, you know, they have a zookeeper to keep track of all the zoo of, you know, components. How do you simplify that for your usage scenarios? And then what are some of those new workloads that you can handle that were not possible before? Is that because you've simplified the backend or you've modeled something new on the front end? Well, I think there's a few different things. So first off, it's a full stack solution. And I think other than cloud-based offerings, I think Splunk is the only widely successful full stack solution to date, but for a different set of users and workloads. But what simplifies this for our end customers and it's part of why Splunk was successful, it's part of why Inarana's becoming successful is that really, if you're focused on the end user, they don't care about, you know, picking this backend versus this backend or choosing what they want to store a columnar, what they want to store in a, you know, search index, et cetera, et cetera, they just want it to work. So we take that, you know, it should just work for our customer's perspective and we really abstract a lot of that. But behind the scenes, inside Inarana, you have a set of engineers who are building and optimizing the technologies that are necessary to deliver the performance and the use cases that our customers want. So, you know, there are some very unique things about the backend of Inarana's technology that have not been done before in commercial technologies. And you're gonna get into, like, what the use case is for. Yeah, I wanna understand how you have that turned into. So just to be very specific, it's the patterns at scale. So it's very different for you to ask a system a question and say I want a count of people who visited my promotions page, you know, by hour for the last week. Not interesting. You know, I want a count of people, you know, broken down by geography or gender or age or whatever. But I have this hypothesis as a product manager or marketer that people who do X and then Y and then Z, where I've just thought of X and Y and Z on the fly, I have a hypothesis, those are the people that I retain longer and I wanna test that hypothesis and then I wanna show that to my management and I wanna invest in pushing more towards X. That's a really flexible analysis on a pattern of behavior that has to be dynamically aggregated from raw events on the fly. And I have never seen a system that can do that at scale across all actors, across all events like in Ironic Han. And when you really get to know why in Ironic customers are choosing us, it's because they're the companies where the marketers, the growth hackers, the product managers are the most data-driven and forward-looking and they're realizing they need that capability and counting is not enough. You mentioned validation, you mentioned Tinder, their customer and those on the site. Other huge, huge traffic orient sites. This is the new digital consumer. Peter Burris was just on our analyst segment talking about this and it's something that we've been hardcore on. I wanna get your thoughts on because what you're basically saying is the old way of doing data capture to get analytics is boring. You said, oh, I don't know, this is a nice comment. But what he was saying is that the digital journey or the progression of the user is taking now new non-linear vectors. And that is something that used to do on the fly, very difficult for folks that don't know what that means, it's really hard. Now at scale, what is the key technology that you guys have? Because that is where everyone's going. That digital journey is not just get a lead and pass some analog process. It's fully digital end to end. It is our proprietary data store and the query model and the execution engine on top of that. And then you mentioned user interface. I think the important part is we're putting it in a user interface that is accessible to these people. But the backend is a totally different way of persisting and executing queries against these raw events than has been seen before. So how do I deploy you guys? So I'm a customer saying, I'm totally love you guys. This is exactly what I want, this digital progression, whatever you wanna call it, the end to end journey online, not analog at all. What do I do? Do I just as a sass? Do I buy software? What's the? At the moment, we license it and you can deploy it in the cloud or you can deploy it on-premises. So I think there'll be a lot of different deployment models. I mean, really one of the things I'm looking at is what is the easiest and fastest way to get this capability into the hands of these business users and what has the fewest barriers to adoption. So I think there are a lot of different ways that we can offer this in the future. But for our customers right now, we offer a full stack solution that they can license. Mainly because they're sophisticated enough they can just take the software. No, we help them with it. And so we really do try to abstract that and we have a generation of abstracting that. So we are focused on the users in the organization who want to get the value out of the data, not focused on adding more burden to IT organizations, data organizations for integration. That's something that you're going to put on your agenda to figure out more consumption models. We've already made it very, very easy for the large scale customers we have and we can make it even easier. Would it be fair to say, when you look at a framework for customers like maximizing retention, deep in engagement, are you essentially preparing a set of queries or ways to interact with the data so that the customer gets up and running with a solution really fast? Because you've got the full stack and because you know where to get the data, it's sort of out of the box and just works, like you said. There's a lot of building blocks in the system and we train our users as to how to use and extend those building blocks to look at things, the sort of classic kinds of retention and churn and all those kinds of things. But our system makes it very easy for the end users to define new building blocks that are very specific to their organization. So again, if I have that XYZ pattern that I'm interested in, we provide them an interface where they can define that and start to look at that. And specifically, what skill level do they need to take those building blocks and create a new pattern? I think it's really, I tend to push back on people talking about technical or non-technical. It's just pet peeve of mine. I just, I think it's missing the point. The people who get the most value out of our system know their businesses and their business processes and have a mentality where they can say, okay, this is probably the digital trail that's being left behind. But they are not data scientists. They are not developers. They are not coders. They are not SQL geeks. They're people who can think in a structured way about their business, which today, product managers, marketers, growth hackers, those people can think that way. Well, the people on the front lines right now are, it's flipped upside down. Basically what you're saying is you're flipping it on its head saying people close to all the action, whether they're, it could be some developers on the app side, but mainly the people who know the usage consumption and making these decisions on the fly where they think there might be value. Is that what you're saying? Standing stuff up. Yeah, and I think it's, they can do fresh analytics on questions that wouldn't have heard us and wouldn't have acquired their developers. And if they told their developers to go build them a report, it would have generated a thousand more questions and they would have stopped there. So it would have stopped dead in the tracks. We'd be like, no ops kicks in at that point. So I gotta ask you a question about your background Splunk because we're in an era now where the rubber's hitting the road. Business value is the conversation. Certainly we've seen the market soften up on some of the B rounds and C rounds only are getting funded. If there's huge traction validation, meaning by customers, you mentioned that, you guys have that. So what is the view from your perspective of Splunk, because you've seen this before. You've seen this wave where, okay, you have this technology enablement. You have business value being validated. But yet now we're in a different era of the business. It's now, big data is now in its seventh year, if you will, or certainly for theCUBE. What's the dynamics in the marketplace today? What's your thoughts on that? Because a lot of people are trying to scratch their heads and make bets. What do you see in the market today? Well, I think there's a lot of spending on people and services around sort of this sort of big data trend. And because it's in this sort of high price of data, there's actually, I think, been a, there's been a slowing of value to the end users. I mean, I know at Splunk, we were constantly being asked for this sort of end business user value. And we delivered a lot of it, but it was a little bit more sort of the Splunk priests would deliver the reports, which was still better. But, exactly. But I think in terms of where this market is going, I think that the lines of business that are going to benefit from this analytic capability need to be able to make business cases and then realize the business value independently of developers or data scientists or IT and rely on vendors to deliver that. And I think that's gonna be a much bigger market and one where there's more value really being realized. When you talk about that, I don't know how far you've gotten in your most mature customers, but what would that look like where you've got a data-driven business customer, where the focus isn't on, hey, how do we run the back end and how do we feed the data? But the focus is on all these users who now can make data-driven decisions. Do you have a customer that's that mature or do you see even in departments? I mean, the numbers I've been saying internally as I think, and I hope it's okay that I say this, but I think we've seen a doubling of the total number of weekly users across our customer base since the beginning of this year. I mean, that's phenomenal. That's metric I was very concerned with at Splunk and we saw high numbers of users per installation. It was wonderful when we started to see dozens or hundreds of users. And to be seeing that growth in something like in Arana at this stage and seeing that it is these business users who have the direct questions and not priests of data, that's really phenomenal. That means that the success in the product market fit is right there. Yeah, yeah. And yet there's so much more opportunity to do even more and there's so much more opportunity to do real community-driven education and shared best practices to get that to happen even more. I know you're new to the company. So what is some of the things you look forward to doing? I mean, honestly, you've got a great base, foundation, growth. What are some of the things that, what twinkle in the eye do you have for things that you, you're geeking out, oh, wow, I really wanna make that easier or what product things are you following and love with that you see maybe coming down the road? Well, I mean, I do see this difference of looking at sequences of behaviors as something that you can do in the product today and it's a whole lot easier than it's ever been and it actually executes its scale. But now we have a lot of examples of users doing that and we can sort of step back and say, okay, what's really special about this? I think we can make that even more discoverable and composable for our end users. So I think there's a next generation we can do of just really pushing and it's like, you know, when you ask me about why I joined, it's like, it's not about product romance, it's about product vision and technology vision and it's like, there's the next stage of growth into that really huge and wonderful vision. So I think there's that piece and then I think there is a lot of the community because I'm very much a whole product person. So, you know, the community of users and the tools we put in place to help that community find one another is as much a part of the product for something like this that is user centered and is around enabling a whole, you know, a whole movement of people. And so I see a lot of opportunity on that community front that we, you know, haven't even touched the surface of our users there. Christina, great insight and congratulations on the new role. I want to ask you the final question for the folks that are watching. A lot of developers, but also a lot of business people, but also we have a lot of product folks out there and being a product leader at this time in the history of the tech business is interesting. It's not waterfall, it's more agile, make things easier, minimalistic. These are the things we always see stuff on Quora and you meet him about, you know, don't be a product manager and you gotta be more developer. What does it take to be a great product manager right now because, you know, that's attracting a lot of talent in the new, I would call the new product management role where it is much more real time. It's much more about some, you know, abstracting the way, the complexities, it's about making things out more elegant, obviously design and you put all that on the table. At the end of the day, you gotta ship a product. You have valuable customers. What's your view on being a product manager today? Well, I mean, I think it's the most exciting time in our industry to be in product. I mean, it's just, it's enormously fun. And you know, I think for a certain mentality, I mean, obviously, you're gravitating towards data. I'm a data-driven person and I like the machine. So I think being ahead of product these days is about building a machine for constant communication between a marketplace and users and customers and an agile engineering organization and sort of, you know, the care and feeding of that machine once you've built it and sort of creating this culture of listening to users and customers. So it's a, you know, it's a broad answer. I'll always be learning, that's a big thing, right? But yeah, but I think that there's a lot of very limited ways of understanding, agile, very limited ways of understanding this data culture that, you know, are just the wrong, the wrong, you know, above all, you still need a point of view and you need opinions, you need to understand that your customers are not gonna tell you what to build because they often don't think what they really need can be built or don't really, you know, don't really have any idea that's really gonna solve their problems, but they're gonna tell you, you know, they're gonna tell you valuable things, but it's about building a machine for learning and from learning deeply from what is really going on in the market. So I was just gonna add one last comment. Having been a product manager way back in the early days of Lotus Notes, but also been inspired by Steve Jobs, you don't build what customers say they want, you build what they really want. That old joke of, you know, Henry Ford would have just built faster carriages, but people wouldn't have asked for automobiles. Yeah, I mean, I used to teach on this topic, you know, sort of middle years of Splunk, I did a lot of speaking on how to do product management in Agile World and the example that I borrowed from my dear friend Rich Marinoff is he uses teleporters as his classic product management example. That's great. And so the customer says, I need a rocket ship and, you know, the sales goes, they need a rocket ship or they won't buy. And it's like, okay, I'll you back it up. Jet travel is not fast enough, but we've got this teleporter technology in R&D. How about that? You know? And I think that's the mentality that I try to bring. Teleporting is the future. We'll be teleporting to Dublin for Hadoop Summit. Christina Norrin, great to have you on theCUBE. Great conference, great insights. It's the data-driven world, new patterns at scale. This is the insight, making it easier and getting the value. This is theCUBE, of course. We're data-driven. We write back with more great data and insights here in Silicon Valley after this short break.