 Live from San Francisco, it's theCUBE, covering Informatica World 2017, brought to you by Informatica. Welcome back everyone, we're here live in San Francisco for special presentation exclusive coverage from theCUBE here at Informatica World 2017, our third year of covering the transformation of Informatica and they needed a bigger boat. Things are getting bigger, more data, tsunami's coming, I'm John Furrier with theCUBE, with my co-host Peter Burris, general manager of Wikibon Research at wikibon.com, check out all their great research from cloud, infrastructure and big data, a lot of great stuff, certainly around IoT. Our next guest is CUBE alumni Rowan Schwartz, fourth time on theCUBE, we've gotten up there, Amit Wally is seven, he's your boss, so. Yeah, I'll let him win for the time being at least. Yes, but I'm looking forward to seeing you in reinventing New York later this year. Great, we love chatting with you, thanks for coming on. We really want to get down to it and dirty real quick. Cloud obviously is the hottest thing. You guys kind of made a good strategic bet a few years ago, kind of being multi-cloud, that's the buzz word now, that seems to be the positioning for most folks as they start going hybrid. It's a gateway to multi-cloud, still a lot of work to be done, certainly in certain areas, latency and other things that are going to be worked on, but as an evolution, it's certainly the vector. And I want to get your thoughts, because now data is the most valuable commodity and precious resource for CUBE, it's the heartbeat. Yes, yes, so I think first of all, the world has moved from a world of cloud to a world of clouds and the S is actually very, very important because if you look into the Informatica bet, into the cloud and more than 10 years ago to know that the cloud and the Salesforce is going to lead this revolution is brilliant, but we have made a few early bets that are also very, very significant. I, for example, was a speaker in the first re-invent from AWS. This is as far as we went to actually adopt their trend of building a full platform as a service in the cloud. And we've been betting very early on Microsoft Azure and now on Google and many of the other vendors there that are kind of leading the way into the new generation of analytics, into the things that are possible to do with data. So I think it's actually, as an early bet, it was very, very smart followed by a few other early recognition of the trends and the possibilities, all of them allowing you to bring data into the center. And to add just one last anecdote on that, I think in the world of clouds, when your application are residing in different clouds and so on, data is almost the only center of gravity that you have. And we're really, I'm really happy that we are in this place to support the customers keeping this asset and bringing it into its full value. Well, that's great, great comment here. I want to get to the cloud Google announcement. You guys are mentioned in there. Spanner is now globally available. It was a hot thing at Google next, the cloud conference actually here in San Francisco, but I want you to take a minute, Rowan, for the audience to just simplify Informatica's strategy vis-a-vis the cloud. How do you guys interact with the cloud? Just simply lay out the relationship that Informatica and your technology and offering is vis-a-vis the cloud because a customer may have, I got Amazon for this, I'm kicking the tires on Google, I use Azure for this. So you start to see some swim lanes with respect to early deployments. But how do you guys interface with the different clouds? I think in general we should divide the term cloud at least into two or three groups. I'll use three for this analysis. I think we should look into cloud application or SaaS as they're called. These are vendors that are depending on data coming to them from the on-premise from other clouds to really give the users the ability to work within the application. And then the second group is really the platform as a service. These are vendors that are supporting your ability to move your processes, your execution, your data storage and really your full operation, your full IT operation into the cloud. And then I think the third group is those vendors that deliver only the infrastructure as a service. If you look into these all three groups and I include the analytics vendor in the first group in the application or SaaS group, when you look into all of these groups, they all depends on data. Data is the lifeline of the application. It is also the lifeline of the platform. It's a key thing that every platform needs. Informatica want to play a key role in actually empowering the data to be part of all of these clouds in an efficient and effective way. To do that from a product strategy, what we're doing is we're delivering a broad best of breed set of integration and data management and products that are all supporting this move to the cloud, the move of data across clouds, data quality, master data management, and building this center of gravity of data. All of these products are built as part of a single platform. And that single platform have four layers of capabilities. The first and the most fundamental one is connectivity. You have to be able to connect to all of these clouds as well as the on-premise applications. The second layer is basically the layer of execution. You have to be able to process things in the right way, leveraging the open source technologies or chosen technologies. And basically what we're announcing in the third layer, sorry, is the management and monitoring that you have to do, especially when you work in a distributed environment, it's a different level of a problem. The fourth one, which we're focusing in a big way in this event is really the layer of unified enterprise metadata. And as we just announced, the artificial intelligence and intelligence that this can bring, we now call it clear. With two terms in mind, one is clairvoyant, the ability to predict what needs to be done by the integration and data management. And the second one, clear is very nicely have AI in the middle. And we really believe that AI and machine learning, based on metadata, can bring a lot of intelligence into the work of data. And in this event, we're sharing a lot of the stuff that we've been doing in the last three years to empower that. And there is a lot coming in this area. So very quickly, you said that it can improve the work of data. Yes. One of the things that would be, perhaps have a little bit more clarity on overall, is you're suggesting that there is a next generation or is there a new way of thinking about data management? What is the new data management? Clearly it's not just building a database and administering it. What is the next generation of data management? So I think that there are actually four big changes that are happening that are all impacting the data management. I think change number one is the fact that application and the data sources have been shifting from an on premise inside your data center to a very distributed environment. The second change is that there is a need for additional patterns of integration and data management. It's not just about batch, it's not just about real time, streaming, IoT, they're bringing a new set of requirements to the field. The third one is that basically the integration can reside or can run in your control, in a self-service morning, embedded mode or in the cloud itself, right? So beyond the endpoint that can run in different places or the application that can run in this place, the integration can do that. But the biggest change of all is the addition of users. There are more users that think they have the right to get data that depend on data for their daily work. They don't just execute, they execute based on data. And these changes are shifting or shaping the data management world. And if I may, I can double click on each one of these changes, but I want to double click specifically on the change in the users. The minute that you have very demanding new users that needs data, and they're not data experts, they're not practitioners, you actually have to work really hard in making it really, really simple for them to get their access to the data, to get not just the access to data, but to get the access to the right data and actually to get also very basic things happening to the data without them investing heavy time in doing that. So one of the products that we kind of showed on main stage is our enterprise information catalog. If you, we all get used to the Google experience, we can search the Spanner release that you mentioned earlier in my name and you'll find us both together. We are doing that for any data in the enterprise so a naive user can go into a search interface and just type what he's looking for. He's typing, for example, the word customer. He's not just getting all the, as a return, all the database that have customer inside the field definition or something like that, he's getting all the data set that fits that domain. How do we figure out the domain? That's where machine learning and AI is making a big difference. You can actually scan massive amounts of data, you can calculate back, you can go into vocabularies and things like that and figure out the domain so that when I'm searching for a customer, I'm getting everything that is related to a customer domain. No more naive user, less familiar with the data, is able to get the data that he wants. The second example of AI that I have to share is that even if you chose this data, the minute that you picked it up, we're giving you an Amazon experience telling you there are actually four other options that you might want to consider. This is a more robust option, this is a more curated option, this is two options that are very popular and we really try to help you make the intelligence pick up of the right data. But through the metadata, you know that there is some semantic consistency across the different options. That is correct, and the metadata that we collect is showing the consistency from the technical perspective, but we're also collecting metadata about the users that are using the data, we're collecting metadata about the operation, how easy, how effective it is to access the data, and we put these four segments of metadata all together to really give the naive user the best experience. The experts almost know where to get the data, but if you want to expand the number of users, you really have to automate in doing all of that. So let me build on this. So if we think about moderator management, let me see if I can summarize, we're thinking about a couple of things. First off, in a digital business that is dependent predicated on the availability of high quality data assets, that's what makes, that's the difference between a digital business and a non-digital business. We have to be able to inventory our data assets through metadata, we have to be able to very, very quickly understand how they map to different forms and formats, and we have to be able to understand paths and movement of data through the enterprise. Now talk a little bit about the data movement side, because in a digital business, there's a lot of things we can predict, and we'll be wrong about most of them, but one thing we can predict is more data and more distributed, which says something, says a lot about the increasing importance of intelligent data movement, not just middleware as it used to be, where you're writing the connections, but intelligent data movement. Can you talk a bit about that? Absolutely, and I think it's a very, very, it's a very, very deep observation that you're raising, that I don't think most of the audience and most of the customers have already gone through. I think to many customers, the move to the cloud, for example, seems like everything is going to be shifting from one place to the other. You're actually spot on, the true long-term direction is in the multi-cloud and in the distribution of data across multiple places. The decision that you as an organization have to pay attention, am I going to work in multiple silos, or am I actually going to work in a distributed, but in integrated and intelligent way environment? We are definitely pushing very, very hard to enable the second one, intelligent, integrated environment. There are parts in the discovery that are very, very important to do that, but just like you mentioned, there is other parts in the data movement that are just as important. And to do that effectively, it's not enough to just be able, as you were mentioning, to just move the data in a batch mode or so on, you have to really stream the data in certain places so that it's in real time available in two places. In some other places, when you move the data, you're actually running into the limits of the amount of data that you can move through the pipe. So you have to- And with that latency. Exactly, so you have to compress it, move it in the right batch so that you're reaching this level of accuracy. And most important is you have to do it intelligently. If you just move all the data to seven different places so that you have it seven times, this is not a good strategy. So you want to subset it, you want to sort it. You want to get just the important data to the right place at the right time for one scenario. For another scenario, you want to replicate the full data. That's why I mentioned it inside the Intelligent Data Platform. It's really important to support a variety of integration patterns. And that's what we are doing, and we'll do it better and better. So the Google announcement that was announced today, the public availability of Spanner globally, you guys are mentioned, congratulations. It says here, just want to get your thoughts on this because in preparation for general availability, we're getting closer with our partners, you're mentioned one of them. And it says now that these partners are in early stages of Cloud Spanner, lift and shift, they're passing on their insights. So first, before I get to the lift and shift, which I think just means rip and replace, but in a different way. But that's neither here nor there for now. But what is some of the things you did with Google early on prior to preparation for that as an integration partner with Google? Because Spanner is a wonderful product. Horizontally scalable, which is the ethos of DevOps. This is a core tenant. So most people go, oh, vertically integrate, go to this cloud. You're talking about a new dynamic that is a DevOps ethos, horizontally scalable with data. That's what Spanner does. What are some of the insights you can share with us on the pre-general availability of Spanner? I think the Google engineering team have done a wonderful job building from the ground up. What you're saying is the dream of every DevOps operation of databases. And I think indeed, and we're seeing it in this industry now, the level of innovation that exists right now is parallel to none. Like the database industry, I've been innovating forever, but what we're seeing now is actually- Fast change. Yes. Massive shifts. And just like you're saying, this was the dream, and here is the dream actually coming true. The waves are coming in. Just get on your surfboard. Exactly. By those waves. Exactly. We in Informatica believe, even though I'm a product leader, one of the groups in my team is actually responsible for the strategic relationship with ISVs. And the reason we do that is because we believe that the work that we're doing with Salesforce, with AWS, with Microsoft Azure, with Google, and with a few other vendors needs to be long-term strategic view. So we needed to know about Spanner way ahead of the release, way ahead of the beta. So at the time that they are releasing, we are actually ready to support the customer doing that. What does it mean to be data-ready in terms of integration? You're an integration partner as part of the general availability. What's going on with Spanner? Give us some insight. So what it basically means is that we actually not only have the connectivity to the new database, but we actually have the right set of optimization that are actually very different and unique when it comes to a distributed environment like that. So we're investing not just in getting the connectivity that allow our customer to move the data, but actually in optimizing it so that we can support what you were alluding earlier, which is can you do it in real time? Can you do it faster? Can you do it with larger batch, et cetera? So that actually means that Informatica is optimizing the data movement into this environment, optimizing the enterprise level of delivery of integration into this environment. Rowan, you're the senior vice president in charge of the whole cloud thing. Congratulations, good strategy. Got Amazon, web services, and looking at their stock price. Since really 2010, it's been a pretty much hockey stick. That's kind of the demarcation point. 2008 financial crisis, housing crisis a lot, but 2010 it really kind of changed. I want to get your thoughts on the difference between Informatica now than last year. Obviously 2010 is really kind of when the wave started, but in the past 12 months, a lot's happened with Informatica. What should people know about what's going on now this year at this show right now that's different than a year ago? I think these are really, really exciting times, and if you ask me what have changed in 12 months, the list is very, very long. I think I'm gonna show there a slide, and I think we had to tune down the amount of releases. That's exactly. But I do want to mention a few things that are very, very significant that are different. I think intelligence is now available not just in a few of our product, but actually as a platform capabilities. Our metadata layer have reached the level of maturity, that it's a mandatory thing for every customer of ours in every project. And beyond that, it seems like the growth in the adoption in both our cloud product and our big data technology is skyrocketing. My best example is in our sales kickoff in January, I was really, really proud to present a slide that shows that every month we move about half a billion records to the cloud. I was really proud of that. And as I come to this event, I'm presenting the number one trillion, right? It's less than six months, and the amount of data that goes through the platform has doubled. If I looked into our big data revenues, they're tripling year over year. So the adoption is uptake is huge. Yes, yes. The adoption is huge. It actually grows into new use cases, new examples, and in this event, you actually see tens of these customers, there's about 80 customers here, actually present new use cases. And these new use cases are fabulous. Like people are doing real time and streaming and they're doing TV integrated to the web and IOT examples and cloud adoption. It really is a very exciting year. The data's not the new oil or the new gold. It's the plantation. It's the soil, it's the rich soil that lets things bloom. A lot of good things are growing out of data. Yes, I agree. It's, I think there are so many analogies to data. It's really hard to pick the right one. The ways are coming is a data ocean, not a data lake. I said that years ago, I'm coming true on that prediction. Look, at the end of the day, it's just an asset and businesses have to use it differently. And that's what we're talking about here. Yeah, and your research, by the way, just to plug Wikibon is really phenomenal. You pegged this and again it's one of those points where Wikibon makes a bet it will come true. Data is an asset and needs to be looked at that way and valued as an asset, not as an accounting mechanism. It's just, it'll be a strategic asset. And as you said, it's horizontal. It's going to be fertilized throughout the organization. And I think that to me is just the beginning. So I think you guys are on a good strategy. Congratulations. Thank you. And if I may plug a last question here on the topic is, if you're managing assets, I'm assuming the CFO know exactly where every asset is. It's in the balance sheet. It's in, he knows the list of bank accounts and so on. Our customers needs tomorrow to really collect their metadata and actually build this enterprise information catalog so they will know where the data assets are. This is a mandatory thing for any organization. And it's coming down the pike pretty fast. Yes. So Peter, your research is right on target. Go to wikibon.com to check out the latest research on valuing the data. Any plugs for the research? No, it's brilliant. Of course you feel right. Yes. Rowan, great to see you. Thanks for coming back on. Hey, congratulations. And you know, you got a spring in your step and you got a lot of cloud action going on. Hybrid cloud, congratulations. Thank you very, very much. Pleasure to be here. Okay, we are here live in San Francisco for exclusive CUBE coverage of Informatica World 2017. I'm John Furrier, Peter Burrs. Stay with us for more live coverage after this short break.