(upbeat music) >> Announcer: theCUBE presents UiPath Forward5. Brought to you by UiPath. >> Hi everybody, we're back in Las Vegas. We're live with Cube's coverage of Forward 5 2022. Dave Vellante with Dave Nicholson Ted Kumer this year is the Executive Vice President, product and engineering at UiPath. Brought on to do a lot of the integration and bring on new capabilities for the platform and we've seen that over the last several years. And he's joined by Dr. Edward Challis, who's the co-founder of the recent acquisition that UiPath made, company called Re:infer. We're going to learn about those guys. Gents, welcome to theCUBE. Ted, good to see you again. Ed, welcome. >> Good to be here. >> First time. >> Thank you. >> Yeah, great to be here with you. >> Yeah, so we have seen, as I said, this platform expanding. I think you used the term business automation platform. It's kind of a new term you guys introduced at the conference. Where'd that come from? What is that? What are the characteristics that are salient to the platform? >> Well, I see the, the evolution of our platform in three chapters. You understand the first chapter, we call that the RPA chapter. And that's where we saw the power of UI automation applied to the old problems of how do I integrate apps? How do I automate processes? That was chapter one. You know, chapter two gets us to Forward3 in 2019, and the definition of this end-to-end automation platform you know, with the capabilities from discover to measure, and building out that core platform. And as the platform's progressed, what we've seen happen with our customers is the use of it goes from being very heavy in automating the repetitive and routine to being more balanced, to now where they're implementing new brought business process, new capability for their organization. So that's where the name, Business Automation Platform, came from. Reflecting now that it's got this central role, as a strategic tool, sitting between their application landscape, their processes, their people, helping that move forward at the rate that it needs to. >> And process mining and task mining, that was sort of the enabler of chapter two, is that right? >> Well, I'd say chapter two was, you know, first the robots got bigger in terms of what they could cover and do. API integration, long running workflows, AI and ML skills integrated document processing, citizen development in addition to professional development, engaging end users with things like user interfaces built with UiPath apps. And then the discovery. >> So, more robustness of the? Yeah, okay. >> Yeah. Just an expansion of the whole surface area which opened up a lot of things for our customers to do. That went much broader than where core RPA started. And so, and the other thing about this progression to the business automation platform is, you know, we see customers now talking more about outcomes. Early on they talk a lot about hours saved and that's great, but then what about the business outcomes it's enabling? The transformations in their business. And the other thing we're doing in the platform is thinking about, well, where can we land with solutions capabilities that more directly land on business, measurable business outcomes? And so we had started, for example, offering an email automation solution, big business problem for a lot of our customers last year. And we'd started encountering this company Re:infer as we were working with customers. And then, and we encountered Re:infer being used with our platform together. And we saw we can accelerate this. And what that is giving us now is a solution now that aligns with a very defined business outcome. And this way, you know, we can help you process communications and do it efficiently and provide better service for your customers. And that's beginning of another important progression for us in our platform. >> So that's a nice segue, Ed. Tell about Re:infer. Why did you start the company? >> Right, yeah, so my whole career has been in machine learning and AI and I finished my PhD around 2013, it was a very exciting time in AI. And me and my co-founders come from UCL, this university in London, and Deep Mind, this company which Google acquired a few years later, came from our same university. So very exciting time amongst the people that really knew about machine learning and AI. And everyone was thinking, you know, how do we, these are just really big breakthroughs. And you could just see there was going to be a whole bunch of subsequent breakthroughs and we thought NLP would be the next breakthrough. So we were really focused on machine reading problems. And, but we also knew as people that had like built machine learning production systems. 'Cause I'd also worked in industry that built that journey from having a hypothesis that machine learning can solve a problem to getting machine learning into production. That journey is of painful, painful journey and that, you know, you can see that you've got these advances, but getting into broad is just way too hard. >> So where do you fit in the platform? >> Yeah, so I think when you look in the enterprise just so many processes start with a message start with a no, start with a case ticket or, you know, some other kind of request from a colleague or a customer. And so it's super exciting to be able to, you know, take automation one step higher in that process chain. So, you could automatically read that request, interpret it, get all the structured data you need to drive that process forward. So it's about bringing automation into these human channels. >> So I want to give the audience a sense here. So we do a lot of events at the Venetian Conference Center, and it's usually very booth heavy, you know, brands and big giant booths. And here the booths are all very small. They're like kiosks, and they're all pretty much the same size. So it's not like one vendor trying to compete with the other. And there are all these elements, you know I feel like there's clouds and there's, you know, of course orange is the color here. And one of the spots is, it has this really kind of cool sitting area around customer stories. And I was in there last night reading about Deutsche Bank. Deutsche Bank was also up on stage. Deutsche Bank, you guys were talking about a Re:infer. So share with our audience what Deutsche Bank are doing with UiPath and Re:infer. >> Yeah, so I mean, you know, before we automate something, we often like to do what we call communications mining. Which is really understanding what all of these messages are about that might be hitting a part of the business. And at Deutsche Bank and in many, you know, like many large financial services businesses, huge volumes of messages coming in from the clients. We analyze those, interpret the high volume query types and then it's about automating against those to free up capacity. Which ultimately means you can provide faster, higher quality service because you've got more time to do it. And you're not dealing with all of those mundane tasks. So it's that whole journey of mining to automation of the coms that come into the corporate bank. >> So how do I invoke the service? So is it mother module or what's the customer onboarding experience like? >> So, I think the first thing that we do is we generate some understanding of actually the communications data they want to observe, right? And we call it mining, but you know, what we're trying to understand is like what are these communications about? What's the intent? What are they trying to accomplish? Tone can be interesting, like what's the sentiment of this customer? And once you understand that, you essentially then understand categories of conversations you're having and then you apply automations to that. And so then essentially those individual automations can be pointed to sets of emails for them to automate the processing of. And so what we've seen is customers go from things they're handling a hundred percent manual to now 95% of them are handled basically with completely automated processing. The other thing I think is super interesting here and why communications mining and automation are so powerful together is communications about your business can be very, very dynamic. So like, new conversations can emerge, something happens right in your business, you have an outage, whatever, and the automation platform, being a very rapid development platform, can help you adapt quickly to that in an automated way. Which is another reason why this is such a powerful thing to put the two things together. >> So, you can build that event into the automation very quickly you're saying? >> Speaker 1: Yeah. >> Speaker 2: That's totally right. >> Cool. >> So Ed, on the subject of natural language processing and machine learning versus machine teaching. If I text my wife and ask her would you like to go to an Italian restaurant tonight? And she replies, fine. Okay, how smart is your machine? And, of course, context usually literally denotes things within the text, and a short response like that's very difficult to do this. But how do you go through this process? Let's say you're implementing this for a given customer. And we were just talking about, you know, the specific customer requirements that they might have. What does that process look like? Do you have an auditor that goes through? And I mean do you get like 20% accuracy, and then you do a pass, and now you're at 80% accuracy, and you do a pass? What does that look? >> Yeah, so I mean, you know when I was talking about the pain of getting a machine learning model into production one of the principle drivers of that is this process of training the machine learning model. And so what we use is a technique called active learning which is effectively where the AI and ML model queries the user to say, teach me about this data point, teach me about this sentence. And that's a dynamic iterative process. And by doing it in that way you make that training process much, much faster. But critically that means that the user has, when you train the model the user defines how you want to encode that interpretation. So when you were training it you would say fine from my wife is not good, right? >> Sure, so it might be fine, do you have a better suggestion? >> Yeah, but that's actually a very serious point because one of the things we do is track the quality of service. Our customers use us to attract the quality of service they deliver to their clients. And in many industries people don't use flowery language, like, thank you so much, or you know, I'm upset with you, you know. What they might say is fine, and you know, the person that manages that client, that is not good, right? Or they might say I'd like to remind you that we've been late the last three times, you know. >> This is urgent. >> Yeah, you know, so it's important that the client, our client, the user of Re:infer, can encode what their notions of good and bad are. >> Sorry, quick follow up on that. Differences between British English and American English. In the U.K., if you're thinking about becoming an elected politician, you stand for office, right? Here in the U.S., you run for office. That's just the beginning of the vagaries and differences. >> Yeah, well, I've now got a lot more American colleagues and I realize my English phrasing often goes amiss. So I'm really aware of the problem. We have customers that have contact centers, some of them are in the U.K., some of them are in America, and they see big differences in the way that the customers get treated based on where the customer is based. So we've actually done analysis in Re:infer to look at how agents and customers interact and how you should route customers to the contact centers to be culturally matched. Because sometimes there can be a little bit of friction just for that cultural mapping. >> Ted, what's the what's the general philosophy when you make an acquisition like this and you bring in new features? Do you just wake up one day and all of a sudden there's this new capability? Is it a separate sort of for pay module? Does it depend? >> I think it depends. You know, in this case we were really led here by customers. We saw a very high value opportunity and the beginnings of a strategy and really being able to mine all forms of communication and drive automated processing of all forms of communication. And in this case we found a fantastic team and a fantastic piece of software that we can move very quickly to get in the hands of our customer's via UiPath. We're in private preview now, we're going to be GA in the cloud right after the first of the year and it's going to continue forward from there. But it's definitely not one size fits all. Every single one of 'em is different and it's important to approach 'em that way. >> Right, right. So some announcements, StudioWeb was one that I think you could. So I think it came out today. Can't remember what was today. I think we talked about it yesterday on the keynotes anyway. Why is that important? What is it all about? >> Well we talked, you know, at a very top level. I think every development platform thinks about two things for developers. They think, how do I make it more expressive so you can do other things, richer scenarios. And how do I make it simpler? 'Cause fast is always better, and lower learning curves is always better, and those sorts of things. So, Re:infer's a great example of look the runtime is becoming more and more expressive and now you can buy in communications state as part of your automation, which is super cool. And then, you know StudioWeb is about kind of that second point and Studios and Studio X are already low code visual, but they're desktop. And part of our strategy here is to elevate all of that experience into the web. Now we didn't elevate all of studio there, it's a subset. It is API integration and web based application automation, Which is a great foundation for a lot of apps. It's a complete reimagining of the studio user interface and most importantly it's our first cross-platform developer strategy. And so that's been another piece of our strategy, is to say to the customers we want to be everywhere you need us to be. We did cross-platform deployment with the automation suite. We got cross-platform robots with linear robots, serverless robots, Mac support and now we got a cross-platform devs story. So we're starting out with a subset of capabilities maybe oriented toward what you would associate with citizen scenarios. But you're going to see more roadmap, bringing more and more of that. But it's pretty exciting for us. We've been working on this thing for a couple years now and like this is a huge milestone for the team to get to this, this point. >> I think my first conversation on theCUBE with a customer was six years ago maybe at one of the earlier Forwards, I think Forward2. And the pattern that I saw was basically people taking existing processes and making them better, you know taking the mundane away. I remember asking customers, yeah, aren't you kind of paving the cow path? Aren't there sort of new things that you can do, new process? And they're like, yeah, that's sort of the next wave. So what are you seeing in terms of automating existing processes versus new processes? I would see Re:infer is going to open up a whole new vector of new processes. How should we think about that? >> Yeah, I think, you know, I mean in some ways RPA has this reputation because there's so much value that's been provided in the automating of the repetitive and routine. But I'd say in my whole time, I've been at the company now for two and a half years, I've seen lots of new novel stuff stood up. I mean just in Covid we saw the platform being used in PPP loan processing. We saw it in new clinical workflows for COVID testing. We see it and we've just seen more and more progression and it's been exciting that the conference, to see customers now talking about things they built with UiPath apps. So app experiences they've been delivering, you know. I talked about one in healthcare yesterday and basically how they've improved their patient intake processing and that sort of thing. And I think this is just the front end. I truly believe that we are seeing the convergence happen and it's happening already of categories we've talked about separately, iPass, BPM, low-code, RPA. It's happening and it's good for customers 'cause they want one thing to cover more stuff and you know, I think it just creates more opportunity for developers to do more things. >> Your background at Microsoft probably well prepared you for a company that you know, was born on-prem and then went all in on the cloud and had, you know, multiple code bases to deal with. UiPath has gone through a similar transformation and we talked to Daniel last night about this and you're now cloud first. So how is that going just in terms of managing multiple code bases? >> Well it's actually not multiple Code bases. >> Oh, it's the same one, Right, deployment models I should say. >> Is the first thing, Yeah, the deployment models. Another thing we did along the way was basically replatform at an infrastructure level. So we now can deploy into a Kubernetes Docker world, what you'd call the cloud native platform. And that allows us to have much more of a shared infrastructure layer as we look to deliver to the automation cloud. The same workload to the automation cloud that we now deliver in the automation suite for deployment on-prem or deploying a public cloud for a customer to manage. Interesting and enough, that's how Re:infer was built, which is it was built also in the cloud native platform. So it's going to be pretty easy. Well, pretty easy, there's some work to do, but it's going to be pretty easy for us to then bring that into the platform 'cause they're already working on that same platform and provide those same services both on premises and in the cloud without having your developers have to think too much about both. >> Okay, I got to ask you, so I could wrap my stack in a container and put it into AWS or Azure or Google and it'll run great. As well, I could tap some of the underlying primitives of those respective clouds, which are different and I could run them just fine. Or/and I could create an abstraction layer that could hide those underlying primitives and then take the best of each and create an automation cloud, my own cloud. Does that resonate? Is that what you're doing architecturally? Is that a roadmap, or? >> Certainly going forward, you know, in the automation cloud. The automation cloud, we announced a great partnership or a continued partnership with Microsoft. And just Azure and our platform. We obviously take advantage of anything we can to make that great and native capabilities. And I think you're going to see in the Automation Suite us doing more and more to be in a deployment model on Azure, be more and more optimized to using those infrastructure services. So if you deploy automation suite on-prem we'll use our embedded distro then when we deploy it say on Azure, we'll use some of their higher level managed services instead of our embedded distro. And that will just give customers a better optimized experience. >> Interesting to see how that'll develop. Last question is, you know what should we expect going forward? Can you show us a little leg on on the future? >> Well, we've talked about a number of directions. This idea of semantic automation is a place where you know, you're going to, I think, continue to see things, shoots, green shoots, come up in our platform. And you know, it's somewhat of an abstract idea but the idea that the platform is just going to become semantically smarter. You know, I had to serve Re:infer as a way, we're semantically smarter now about communications data and forms of communications data. We're getting semantically smarter about documents, screens you know, so developers aren't dealing with, like, this low level stuff. They can focus on business problem and get out of having to deal with all this lower level mechanism. That is one of many areas I'm excited about, but I think that's an area you're going to see a lot from us in the next coming years. >> All right guys, hey, thanks so much for coming to theCUBE. Really appreciate you taking us through this. Awesome >> Yeah Always a pleasure. >> Platform extension. Ed. All right, keep it right there, everybody. Dave Nicholson, I will be back right after this short break from UiPath Forward5, Las Vegas. (upbeat music)

>> From our studios in the heart of Silicon Valley, Palo Alto, California. This is a CUBE Conversation. >> Hi everyone, welcome to this CUBE Conversation here in Palo Alto, I'm John Furrier. Host of theCUBE here in theCUBE studios. I'm joined with Ronen Schwartz. Senior Vice President and General Manager of Data Integration and Cloud Integration at Informatica, CUBE alumni, been on multiple times, here to do a preview round. Informatica World coming up as well as just catch up. Ronen, great to see you. >> Really happy to see you, you guys have a beautiful place here in Palo Alto. >> I know you live right around the corner so I'm expecting to see you come on multiple times and come in and share your commentary, but I want to get your thoughts, it's been a couple of months since we last chatted, interesting turn of events. If you go back just, you know, September of last year, and then you had Amazon Reinvent. They announced Outpost, multi-cloud starts hitting the scene, first it was hybrid. First it was all public cloud. But now the realization from customers is that this is now a fully blown up cloud world. It's cloud operations, it's just public cloud for unlimited cloud natives activity, on premise for existing workloads, and a complete re-architecture of the enterprise. >> Yes, and I think from Reinvent to Google Next just a week before, I agree with you. It's a world of hybrid and a world of multi-cloud. I think a lot of exciting announcements and a lot of changes, I think from my perspective what I see is that the Informatica customers are truly adopting cloud and hybrid and as data is growing, as data is changing the cloud is the place that they actually address this opportunity in the best way. >> So I know we've talked in the past. Your title is Data Integration, Cloud Integration. Obviously integration is the key point. You're starting to see APIs going to a whole other level, with Google they had acquired Apogee, which is an API marketplace, but with microservices and service meshes and Kubernetes momentum you're starting to see the advent of more programmability. This is a big trend, how is that impacting your world? Because at the end of the day you need the data. >> Yes, it actually means that you can do more things with the data in an easier way and also it means that you can actually share it with more users within the enterprise. I think that especially the whole ability to use containers, and Kubernetes is a great example of how you can do it, it's actually giving you unparalleled scale, as well as simplicity from the obstruction perspective. And it allows more and more developers to build more value from the data that they have. So data is actually in the core. Data is the foundation, and really a lot of this new technology allows you to build up from the data more valuable capabilities. I'm really happy that you're mentioning Apogee because one of the things that Google and Informatica notice together is the need for API to actually leverage data in a better way, and we strike a very strategic partnership that has gone into the market in the last few months allowing every user of Informatica Ipaas to basically publish APIs in a native experience from the Informatica Ipass directly to Apogee and vice versa, everything that you build in Informatica Cloud is basically automatically an API inside Apogee, so users get more value from data faster. >> So can you give an example, 'cause I think this is one of the things we saw at Google as a tell sign or the canary in the cole mine whatever trend parameter is that end to end CICD pipe lining, seamless execution in any environment seems to be the trend. What you're kind of getting at is this kind of cross integration, can you give an example of that Informatica Cloud to Apogee example of benefit to the customer or use case and why that's important. >> Yes, definitely, so if I'm a retailer or a manufacturer, I'm actually looking into automate processes. There is nothing better than deleting the Ipaas from Informatica to actually automate process anything from order to cash or inventory validation or even next best recommendation coming from some AI in the backend. Once you have created this process exposing this process as an API is actually allowing multiple other services. Multiple other capabilities to very easily leverage that, right, so this is basically what we're doing, so what an individual in the retailer is doing is they're actually defining this process of order to cash, and then they're publishing it as an API in one click, at that stage anybody anywhere can very very easily consume that API and basically use this process again and again. >> And that means what? Faster execution of application development? >> It means faster execution of application development. It also means consistency and basically scale so now you don't need to redevelop that. It's available as an API, you can reuse it again and again, so you do it in a consistent way, when you need to update you need to change, you need to modernize this process you modernize it once and use it again and again. >> Sorry to drill down on kind of the unique use case here, but this points to the integration challenges out there and the opportunities. Mentioned Google Next, Google Cloud. You've got a relationship with Amazon. This is part of your strategy for ecosystem. This is critical, integration is becoming Amit Walia was saying that you can compose. Have that foundation for the data and you compose your applications, but if you got to have a lot of composition, you need to have integration points, that's going to be either APIs or some sort of glue layer. This is huge, this is like the entire thesis of cloud architecture. >> Right, and the reality that our customers are facing is basically irrelative from multi-cloud, they will use a best of breed cloud for CRM, a best of breed cloud for ERP as well as a best of breed cloud for their data warehouse, their databases as well as their analytics, AI, et cetera. In that world, the only thing that is kind of common across this cloud is the data. And if you're actually able to allow the data to reside in the best place but you keep the metadata managed centrally by software like the one at Informatica is giving you are getting the best of breed of all of these offerings without actually paying a fine for that. >> So you guys are in a lot of magic quadrants out there in terms of categories of leadership and focus on data from day one. As you talk about your ecosystem, can you explain what that means because you're also an ecosystem partner of cloud players but you also have your own ecosystem. Talk about the ecosystem, how is it laid out? What's the update, what are some of the momentum points, can you share just an overview of how that's all happening? >> Yes, definitely, so when we're looking into our partnership with Microsoft Azure, with AWS, with JCP, we're not talking about just Informatica supporting the technologies that they build, we're talking about Informatica supporting the technologies that they're building as well as their ecosystem of partners. We're talking about an end-to-end solution that supports the entire ecosystem. What that actually translates to is Informatica building services that are giving best of breed experience for users within this cloud environment and really giving you the full power of data management integration, data quality. Master data management, data security. Data catalog across all of this cloud. In a way you're right, we can look at it in the same way as like we have an ecosystem and in that ecosystem we're seeing a lot of strategic partners that are very very large, definitely all of these cloud scales are key partners for us and for our customers, but we're also seeing a huge amount of smaller, innovative vendors that are joining this ecosystem, and Informatica World in May 20th is a great place to come and actually see these vendors. We're actually showing for the first time our AI and cloud ecosystem in one place and these vendors are coming and they're showing how are they leveraging Informatica technology to basically bring new value in AI, in machine learning, in analytics to their customers. If you ask me, like, what is Informatica doing to help them, we're basically making the data available in the best way for their offering, and that kind of allowed them to focus on their innovation rather than how do they work in the different places. >> Rowen, you got ahead of me on the Informatica World question, but you just brought it out, you're doing an innovation. Let's talk about Informatica World. Because again, this data, there's a lot of sessions, so you do the normal thing. We've covered multiple years there. Integration's the key point, what are, why should someone come to Informatica World if they're a customer or a prospect? Now, you mentioned the AI zone. What's the core theme that you're going to be seeing there from your group and from the company? >> Informatica World this year is an amazing place for people to come and see the latest that happens within the cloud and hybrid journey, a great place to actually see next generation analytics and all the innovation there, it is a great place to see customer 360 and master data management and how can that change your organization as well as an amazing place to see data security and data privacy and a lot of other innovations around data. But I would actually say that it's great to see everything that Informatica can share with you. It is a better place to see what our customers and our partners are sharing. And especially from a partnership perspective Informatica World 2019, you're actually going to see leaders from Google, you're going to see leaders from Microsoft, you're going to see leaders from AWS, the people that are leading the best data warehouses in the world the best analytics in the world as well as innovators like DataRobot and Databricks that are changing the world and are actually advancing technology very very fast. >> And the AI zone, there's a cloud and AI zone. I've seen them, I know it's here from the prep. What does that mean, what's someone, AI's going to be hot, I think that's a big theme. Getting clarity around, as Amit kind of shared with us on a previous interview. AI's hot because automation kind of left the blocking and tackling. But the value of creation is going to come from using the data, where's the, and it's not integrated, you can't get the data in. If it's not integrated, you can't leverage machine learning, so having access to data makes machine learning get great. The machine learning gets great, AI is great. So tell us what's going on with it. Give a little sneak preview. >> It's actually amazing what we can do leveraging the iron machine learning today, right? I wake up in the morning and I say Alexa, good morning, and I actually get back what's the weather and what's happening. I'm getting into my car, Google is telling me how fast will I get to the office or the first meeting. I left to come here and I knew exactly what's the best route to take. A lot of that is actually leveraging AI and machine learning, I think it's not a secret that the better your data is the better the machine can learn from the data. And if your data is not good, then learning can actually be really really bad. You know, sometimes I can use, like with my kids. If their learning books are bad, there's no way that they can actually get to the right answer. The same as data, data is so critical. What we're seeing is basically data engineers, data operation becoming a super strategic function to make AI and machine learning even possible. Your ability to collect enough data to make sure that the data is ready and clean for AI and machine learning is critical. And then once the AI and machine learning eventually contributed the automation, the decision making, the recommendation, you have to put it back in to the data pipes so that you are actually able to leverage them to do the right thing. >> You know, you, I think you nailed this one. We've talked about this before but I think more important than ever, data cleansing or data cleaning was always an afterthought in the old data warehouse world where well, we're not getting the answers we wanted so you kind of have to fail to figure out that the data sucks so you had to get the data to be better, now it's much more acute in the sense that people realize that you need quality data so there's now new capabilities to make sure there's a process for doing that on the front end, not on the back end. Talk about that dynamic, because this is something that is critical in the architecture, and how you think about data pipe-lining, data management, the things that you guys do, this is an important trend. Take a minute to explain that. >> Yes, I totally agree with you and I think that the rise of the importance of data quality, and it actually is coming also as part of the pattern of data governance and we want to make sure that the processes exist to make sure that the data that we make available for our AI research, for analytics, for our executives and data workers that this data is really the right data is critical. To actually support that, what we are seeing is people defining data governance process. What are the steps that the data needs to go before it is actually available for the next step? And what is nice today is that this is not people that the data needs to go through. These are processes, automation, that can actually drive data quality, it goes from things that are very very basic. Let's remove duplicate data, but also into the fact that you actually identify anomalies in the data and you ask the right questions so that that data doesn't go in. >> Is this the kind of topics that people will hear at Informatica World? >> Definitely, they will hear about how they can actually help the organization get the data right so that machine learning automation, and hyper growth is actually possible. >> You're excited about this market, aren't you? >> Super excited, I mean I think each and every one of us, we're going to see a lot of innovation coming out and I consider myself lucky that data is actually in the center of all of this innovation and that we're actually able to help the customers and our partners be successful with that. >> Yeah, you and I were talking before you came on camera, I wish I was 23 again right now, this is a great time to be in tech, everything's coming together. You got unlimited compute, machine learning's rocking and rolling, everyone's all kinds of diverse areas to play on, it's kind of intoxicating to be in this environment, isn't it? >> I totally agree, and I will add one additional thing to the reasons, agility. Like the fact that it all is available at your fingertip, and you can actually achieve so much with very little patience is really really amazing. >> This compose ability really as the new developer modernization renaissance. It's happening. >> Yes, yes, and as we usually say it all starts from the data. >> Okay, Ronen Schwartz, we're talking Informatica World but getting an update on what's going on because data integration, cloud integration, this is the number one activity people are spending their time on. You get it right, there's huge benefits. Ronen, thanks for coming in and sharing your insights, appreciate it. >> Hey, my pleasure. >> Okay, this is theCUBE, here for CUBE Conversation here in Palo Alto, California at theCUBE headquarters, I'm John Furrier Thanks for watching. (jazz music)

>> Live, from Las Vegas, it's theCUBE, covering Boomi World 2018. Brought to you by Dell Boomi. >> Welcome back to theCUBE, we are live at Boomi World 2018 at the Encore Las Vegas. I am Lisa Martin with my co-host John Furrier, and we're excited to welcome the CMO, the new CMO of Dell Boomi, Mandy Dhaliwal. Mandy, welcome to theCUBE. >> Thank you Lisa, it's great to be here. >> And thanks for having us here. >> Oh my gosh. >> Second annual Boomi World >> Yes >> Doubled in size from last year, moved it from San Francisco to Las Vegas. This morning's keynote was action-packed, standing room only, and some of the stats that really struck out at me: five new customers are being added to Dell Boomi everyday, over 7500 customers to date, your Dell Boomi community is over 64,000 strong, there's a lot of momentum. Talk to us about, you're new, been seven weeks, what are some of the things that excited you about coming to lead marketing for Dell Boomi? >> Oh my gosh, hard to pinpoint one thing. So many wonderful things about this company. Market leading technology, Gartner Magic Quadrant leader five years in a row, right? Just fantastic reputation in the technology landscape. Everybody has very positive things to say about Boomi. The company culture, right? Companies like this don't come around everyday. It's fantastic, everybody is very collaborative, we have a winning culture, we put customers first. We don't just talk to the talk, we walk the walk, and it's fantastic to be a part of it. Outstanding sales team, outstanding leadership team, I could go on. >> Michael Dell said 80%, sales are booming at Boomi. But, as far as a marketer, or CMO, you have a challenge. You have a successful company that was acquired by Dell eight years ago, incubated, and is part of the puzzle pieces of the Micheal Dell strategy. You have all of Dell Technologies' portfolio, but Boomi seems to be one of the key ingredients. You got VMware, everyone knows what's going on there, Pivotal, and now Dell Boomi, born in the cloud. So you got product market fit, check. >> Absolutely, yes. >> Now you got to get the word out, you got to drive value, be part of that flagship trio that's Dell Technologies. >> Right, right. >> That's a big task, how are you going to attack that? What's your plan, what's the vision? >> First and foremost, it's awareness, right? We've got to get the word out. We've got so many wonderful customer stories, that we just need to share with the world. Our own company, amongst Dell Technologies, day one, Dell EMC merger, sales force was integrated, day one. And guess who did that, what technology was behind the scenes? We drink our own champagne. >> That's impressive considering I can't even imagine the sheer number of sales force instances that came together in a single day >> Absolutely, customer service. We're our own best proof point. Dell Technologies is our largest enterprise case study. Customer service, across RSA, Secureworks, and Dell Boomi, one point of contact, one phone call. We get notes and if there's an issue with any one of our customers, we're able to pass through that customer request directly to the company that needs to be dealing with the customer. We don't make the customer hang up and call another number. >> So cloud scale certainly gives you an advantage, we heard that. Product is strong, data now is becoming much more instrumental across horizontal data sets. So it's not just the silo data and do some integration, you got cloud native, you got VMware and the enterprise, you've got Pivotal, Kubernetes, Cloud Foundry, cloud native stuff. How are you guys going to take that data explosion and make it trustable? Is that part of the plan, is that going to be a key part of that? >> Trustable in terms in privacy and data governance? >> Just leveraging the data, being data driven. You mention integrating sales, that's a tough job that has to be done, check. But now how do you get value out of the app and the workloads that run with that data? >> Well it's a complex ecosystem that we're a part of, right? And that's Boomi's job, we radically simplify that whole ecosystem, so the value is starting to show. We're about to unleash next week a Forrester TEI study. So we took a conglomerate with five of our top enterprise customers and built this 300 billion dollar business as a scenario, and started to look at the value that Boomi was able to derive in terms of cost reduction, in terms of savings on infrastructure costs, in terms of innovation potential, as far as speeding up their routes to market, in the ROI, which came back conservative from an innovation potential perspective, because you really can't quantify what you don't know, 300% was the number in terms of the ROI that we're able to deliver as a Boomi-empowered business. >> Which is huge, there were, besides that, a number of other really eye-popping quantitative stats, business outcomes, that that Forrester Total Economic Impact study covered, one of them being, incremental revenue is the biggest benefit that Dell Boomi customers get, 3.4 million of incremental revenue. Here's some other stats that I saw here that I thought were really transformative are, cutting development times by 70%, freeing up IT resources, being able to reallocate them, helping, ultimately, accelerate the pace of innovation, which we know is critical to transforming and continuing to use data, and to John's point, establish that trust, not just with customers and partners, but also internally. >> Absolutely. Every company's a software company, right? We've been hearing that now for years. We practice it, we live it every day, we're empowering these brands to go out and do what they do best and re-imagine their businesses from their customers' perspectives. It's incredibly powerful, it's exciting. >> And you, sorry John, I was going to say you've got, speaking of customers, over 92% of the breakout sessions here have customers and partners, and I know as a marketer how challenging it is to get. And you said about 68 customers here speaking on your behalf. >> Absolutely. >> That's huge. >> Our community is tremendous. We truly partner with our customers, and it shows. You heard Chris Port on stage, recognizing customers for innovation in various categories. We take our customers and partner with them for them to be successful. The company culture extends beyond the employees, and it's been the secret to our success. We're able to help them unlock the value of their businesses. It starts with the data and the applications, but at the end of the day, we're an enterprise transformation company. And you're going to start to see a lot more of that in the coming months, as far as messaging, and the value that we deliver as a platform. >> I want to give you thoughts, Mandy, on a couple things. One is the technology partner program, and the ecosystem, you mentioned that, but also you're starting to see the messaging change around Boomi, Dell Boomi. Integration, certainly we know how hard it is, as a glue layer, to put stuff together, but you guys are talking about connecting businesses. So you're now moving up the value proposition, the more holistic kind of perspective. By design, is there a rationale for it? Can you explain why this is happening, what's the evolution? >> The market is taking us there, right? The customer need is where we're focused. Digital transformation, right now, today, the stats that we have, only 26% of digital transformations succeed. We've got an awful lot of customers saying, "Hey, we got to get this figured out." It's on the C-suite agenda, it's on the boardroom agenda. It has to succeed, it's innovate or die. There's stats out there in terms of how many of the Fortune 500 are going to be around 10 years from now, five years from now, right? Boomi is that company that will solve those problems. Michael said it this morning. >> And speed's important too, they got to get there faster. >> Absolutely, absolutely. >> And that's not what they're used to. (chuckles) >> We have a very simple UI, very plug-and-play, drag-and-drop platform that helps our customers go deliver. Not to mention the power of the analytics and the AI that we've got behind us. We've got the pattern recognition down. >> Talking about the partner program, I'll say (mumbles) some of the announcements. Yesterday was a partner day. What happened yesterday, what's going on today, what's the vibe of the show, ecosystem, partner program, what are the new things? >> You know, bottom line for the partners, we're here to help them extend their businesses. There's tremendous momentum in the market as far as, we're pulling through demand on the integration scenarios. You know, we've got Deloitte and TCS, Accenture, some of our top sponsors here, our sponsorships are sold out, right? Our partners are here in this ecosystem. Dell Technologies, right behind us. It's a tremendous show of force, it's fantastic. And it just shows you the market potential and the need out there. Customers are clamoring for these types of solutions. >> As the CMO, I want to get your take on some of the messaging breakdown. One of them that came out today, left bold messaging is, not only, as you mentioned a minute ago, Dell Boomi is the transformation partner, but also that, "Hey we're re-imagining the 'i' in iPass." iPass is a competitive, well-established market. You guys are using your own, upwards of 30 terabytes of anonymous metadata to make the Boomi unified platform smarter, more responsive. As you look to help that 76% of customers who are failing in their digital transformations, how is the "re-imagined" 'i' in iPass going to be a facilitator of that? >> It's putting the user at the center of the experience. Steve Wood, our Chief Product Officer, is going to be on stage tomorrow, doing a demo of this re-imagined user experience. It's driven by the data that we've got, It's driven by the patterns that we've been able to look at as far as business processes and integrations, and be able to provide a user experience where the customer's at the center, I go with a problem, not a list of technologies that I need to connect. Mandy wants to build EDI for a couple of trading partners, right? I don't need to tell Boomi that, I need to tell them, "I need this outcome, "and I need data to be transferred from here to here," and at the end of the day, I, from my cell phone, want to be able to figure out what's going on as far as my supply chain. I want to know where that boat is, coming for Black Friday. Is my inventory hitting the port when it needs to? I should be able to see that from my phone. That's what we're doing, we're giving the power back to the users, and enabling them to go power their businesses. >> As a new person to Dell, we've known each other, at the last (mumbles) you were at a born in the cloud, Amazon sets the agenda for a lot of the cloud computing market, you guys are cloud native as a startup, really kind of nailed that stats formula with Boomi. Dell is not restrictive in the sense, but it's got a lot of muscle behind you. Boomi seems to be standing on its own and flying out, like VMware, while it's still 100% owned by Dell. Those trends are big, that's a big wave that you're on. How are you thinking about it as you look at your assignment as the CMO, how are you going to ride that wave, are you going to hang 10 early, are you going to build it out slowly? What's going on? >> Oh, we're going. We're going for it. We're going to go ride that wave, it's here. If anything, we've got to work better with our Dell Technologies partners, right? We're getting in deeper from a go-to-market standpoint, with a lot of the enterprise reps already in the ecosystem. We're looking at driving customer value. As Michael said, there's always a need for Boomi. We haven't found a single opportunity yet that Boomi isn't needed. >> So you're on a growth curve? >> We're absolutely on a growth curve. It's just, we can't get there fast enough. We're hiring like crazy, we're, you know, we're just doing it. >> What kind of jobs you guys looking for, what's the hiring, what are your needs? Take a minute to share. >> Technical talent is always priority number one for a company like ours. On the go-to-market side as well, we need sales people, you know I've got marketing recs out already, check our website. There's lots of opportunity from a VD standpoint partner as well, so tremendous opportunity on the go-to-market side as well as on the R&D side. >> Looks like Boomi is going to be one of those flagships for Dell Technologies. >> I certainly hope so, that's my vision. >> I mean, you've got good company. VMware didn't skip a beat, Pivotal's growing like a weed, Dell Boomi's exploding in a big way, you guys are doing great, congratulations. >> Thank you, thank you. >> And another thing, before we wrap up here, that is impressive, all those companies, those Dell companies that John just mentioned, including Dell Boomi as a business unit, all of them have women at the executive level. There are six CMOs, including yourself, female CMOs in that position, and that's something that theCUBE has always long been a supporter of women in technology, and I always admire that. It's great, congratulations on your appointment. It's great seeing a strong female leader in a role. And your energy is contagious, so. It's a good thing that they got you on that growth trajectory, 'cause I can feel it. >> It's happening, it's going to be amazing. And thank you for being a part of this journey with us. >> Thanks so much, Mandy, for having us, we appreciate your time, and have a great time at the rest of the event, we'll see you next year. >> Thank you, thank you. >> For John Furrier, I'm Lisa Martin. You're watching theCUBE live from Boomi World 2018, John and I will be right back with our next guest. (digital music)

>> Live from Washington DC, it's theCUBE covering Inforum DC 2018 brought to you by Inforum. >> Well we are back here at Inforum 2018 in Washington DC John Walls with Dave Vellante. We are in the nation's capital and joined right now by Massimo Capoccia who is SVP of Info OS and Rick Rider, product director at for common at Infor. Gentlemen, thanks for joining us, >> Thank you >> Good to see you both. >> Thank you for having us >> Thank you >> Let's start first off good job by the way >> Welcome to keynote.. thanks stage this morning we had some time to shine out there. Your thoughts about the show in general so far? We've been a couple of days in now, how is it going for you? >> Yeah, very very well the customers have received the Infor OS and the technology innovation and what we do with the AI very very well. You know lots of people in the hub, lots of sessions, so lots of interest on the technology innovation for Infor OS and for Infor as well. >> Sure, Rick for you? >> Yeah, its been great, it's been interesting. What we are finding out is getting a lot of this out in front of customers and partners is bringing up some interesting opportunities for us moving forward. So it is not everyday we get the opportunity to get in front of these many people within our network, so it's been great. >> So we'll be hearing from folks Let's talk about AI, especially for those who maybe don't know, haven't embraced it yet. What are the Hesitation, reservations, I mean what are you hearing from them as far as what's going to trigger them to make a decision? >> Yeah, to be honest I think they have been hesitant in the past just because it hasn't really been clear. We have talked about AI in the technology community, it's been hard to define. Some people might in fact define incorrectly, because we are making assumptions about what technology can and can't do. I think what we are uncovering. I feel we've got a pretty unique approach to what we are doing here with Infor OS and common connected to it. We are working directly with customers to identify use cases on how we can apply AI. Rather than just starting at the top and saying, "hey we should be doing all these great things and let's see how we can make it work for our customers." It's kind of we are flipping the script and starting backwards and saying, "hey what are the issues? What are the opportunities the customers have? How can we build the technology using AI to make it meaningful?" So we have business impact they want. And by doing that, I think it's a lot more understandable, it's a lot more relatable, it's a lot more trust able from our customers. >> We from in theCUBE here, watch and observe the ascendancy of the hype and so called big data. And which is sort of moderated now. But in data is plentiful, insights aren't. and so we feel we have come to the conclusion that the innovation recipe, if you will, for the next decade or so, is data, applying machine intelligence, that data and having a cloud to be able to scale it. Having cloud economics to be able to track innovation. You guys seem to have all three >> Yeah >> Of those pieces But AI without the data is just.. I don't know what it is? >> Right? Excited. >> Data without the ability to extract (laughs)...you know insights... What good is it? >> Right >> Yeah. Yeah. >> Then you got to have cloud to scale it. Your thoughts on from a platform perspective with that means? >> Yeah, Absolutely. So I was seeing the interview that you were doing with Charles, says we build this platform from the beginning. And one of the big element is that we have you know, made it possible to synchronize you know real time all this data that the applications will generates, into a single place called the data lake. So when you have the data and data lake then you can do many many things and not only analytics and reporting, which is the classical use case, but now it allows you to do AI. And the difference is we don't have one domain of the data. So some of the vendors have only CRM data or ACM data or financial data. With Infor we have all different domains of data. So we can go from ACM from financials, to asset management, to IoT readings for IoT devices, to ERP and CRM also. So when you combine when you can cross and combine the relationship with this data, then your AI is much more smart and intelligent. When you have only the AI focused on a domain, is less intelligent. So that's actually the power that we do. And our Coleman will take advantage of that, you know that you know rich data lake. >> Okay and we talked a lot to someone earlier about the stack. and that the bottom layer, is the OS >> Yes >> So everybody is familiar with what the operating system does in computer science. How is your OS similar and different? What's the function that it does if we can double-click on that? >> Yeah, so we.. It's in for operating service and we call it a service. Because it's not actually in the database and operating system level, right? So we believe... We are more in the application technology. We are the layer that takes you know the bare technology and makes it usable for a business, for an enterprise. And we build applications on top of it. So what we believe at Infor, when you have an architecture with this composite of a suite of applications. Or even the new Microsoft architecture that developers built. You still have to deliver a uniform user experience, a uniform business process, uniform security and data management and even AI. So if you look at services like Facebook or Netflix, they have maybe the entire Microsoft architecture thousands of that, but the experience is one.alright? Thus what we want to bring it to the enterprise. Infor OS big.. that unify the experience both from the end user and business process, to the enterprises. And we do it for all the cloud suites. Infor OS is all the cloud suites not just one but all of them the same services. >> So, I love the Netflix example, because if you think about digital... digital transformation, digital business. My experience with Netflix is just with Netflix I don't have a... There's no marketing department, sales department service department. I do have a problem, I go to Netflix on my app(laughs) I interact with... >> Absolutely >> So that's... I considered that what's called a product. So Rick, how does this capability get translated into product? >> Yeah. You know one thing that you brought up a lot earlier is, with all this interconnectivity and how we have to package things. So we've got all these different services that OS offer. So we've got the data lake, we've got the API gateway. We've got the integration platform, and... All those pieces is what bring this together to where, we can actually deliver something to our customers. In my case, it's an AI model or it's RPA, because of all these things are packaged together. So they don't actually see what's happening, because it's already packaged for them. >> Okay, so... what I was saying the Charles, you probably you might have seen it, is when we first discovered Infor was like, "What do you guys do?" It wasn't clear exactly what you guys were doing. But he said, and I believe him, was always our vision to have a platform. Now that... the... it's not opaque anymore, the platform is pretty clear. Now you've added the Birst Analytics, you've added Coleman AI on top of that. So you know Andy Jassy AWS always talks about the flywheel effect. So I suspect that you're entering this flywheel phase. What is that phase? What does it kind of mean for you guys, for customers, in terms of innovation? >> Yeah, is a very good question. Actually I worked for years with... We started with this platform, this journey with Charles and we start really with... okay, what's the first first issue. You know, we want to solve the integration promise. We want to give an integration platform. Then we build that. Then we start to say, okay, we want to unify the experience. We build a unified portal with a single sign on. Then we say, okay, we want to unify the data, we build a data lake. So we continue to build out the platform. We are now at the level we have a platform and its unique platform because you can say it fits in one Magic Quadrant. Because yeah, it does the iPass in the past. So with all these magic quadrants. But it doesn't fit in one, it's in all of them, right? So and in... The analyst looks at that and say, Okay, we have a platform doesn't fit in one, if it's in all of them, right? >> The Magic Quadrant is now becoming outdated, because... >> Exactly. >> Because its as you said... I don't need 15 stove pipes... >> Exactly. >> With the stove pipe thinking. >> Exactly. So.. >> With all due respect to my friends at Gartner (laughs) >> But the Fly wheel is... Yeah, the platform is going to become more and more important, relevant. The customers that... you know are in the cloud, are not in the cloud, they will use the platform to get to the cloud. It's going to be a new enabler for those customers are still on premises, to go to the cloud. We the Infor OS is enabler for hybrid process. So some some application can be in the on premises or in the cloud. With the OS they can take the journey and get to the cloud and their own place. >> So architecturally, you don't care. >> We don't care what the application side, >> Okay. But you've certainly done a lot of work to optimize AWS, you know, we're AWS customer, we know it's, it's not trivial, you have to, you know work it. It's simple, developers love it, but to really take advantage of it, integrate it with your processes will take some work. But architectural, you don't care. But it's not. That's not a that's not an offering statement, is it? I mean, today, can I run that multi cloud, run their software anywhere? >> Well >> Doing that? >> Well, today, we have a mix off, we use open source library, but we do utilize AWS, the data lake is built on S3. On AI, we use Laks, or Sagemaker for the training on the models. So we do a lot of AWS, Because it gives you our computing power and any out of the box solution for certain certain pieces. What we do we build interfaces to our application, so that our customers doesn't need to take care of all the plumbing, it's all interconnected and done. So that's, that's one of the power of Infor OS. It brings that application technology layer, between the business application and you know, the basic, you know, technologies >> And the customer doesn't want to think about the plumbing these days, right? >> Right. >> To most customers, infrastructure is irrelevant, you know, again, apologies to my hardware, friends, but they don't care about hardware, right? I mean, >> Yeah. >> It's interesting, Charles said in the keynote yesterday, when we were an onPrem software company, we didn't manage servers for our customers. Customers didn't care really about the server, and any more than they care about the plumbing today, right? >> Right. Yeah. And if I want to relate that to the AI space, all the training, all the science, all the highly computational things that we have to do, customers don't really want to know what that means or how to use that. So what we're actually doing is in conjunction with some of the AI services we're working with, with AWS is we've built a modeling platform to where they're operating in one location. They've got no concept of where this is hosted, what's going on behind the scenes, and then we connect it, we expose an API, and they can do any sort of RPI that they want to. >> So...I mean you are talking about when you talk about your customers, and they don't care about, you know, what's behind the curtain, they just wanted it to handle, maybe something up front, but yet, you have to understand what they can do. Right? You have to understand their potential. So how do you do that, when you're dealing with different companies, different sizes, different priorities, different challenges, they're different technology stages. How do you all address them individually and help them get to that better place? >> Yeah, I think, you know, it's never a one size fits, all right. So we try to give them what we've called citizen developer tool sets in the past. And I've even started to try to say, citizen data science tool set. So how can we make it more consumable by all types of users? So yes, we can provide templates, we can create these things that might work somewhat out of the box. But each one of these customers their data is, is just slightly different than need to make tweaks. So we really want to be able to, you know, provide all that flexibility. And it gets back to we start with our use cases. And then we build from there. So we get all that feedback, and make sure we're making we're hitting those key points. >> So I want to pick up on something you said about citizens, citizen data scientists. I've used that term before in front of data scientists some of them don't like it, right. That denigrates what they do. And it's true, a data scientist is a math whiz, maybe a stats, was there a data hacker they can code, Okay. And that's not every business person, right? Clearly. However, when you think about things like our RPA, I mean, you really want to enable business users. You don't want to repeat the same problem that we had for years with things like decision support, where you had two people in the company that knew how to build a Cube. And you had to have line up with an ask, please can you build my cube, I have a deadline while everybody else does too. Just there wasn't effective. So things like our RPA and low code, citizen data scientists spread that technology throughout. Now, part of that is having a platform that is I vision a studio, whereas a user, I can actually create some kind of process and code that in software, you know, code it. It is something that's repetitive that I don't have to do every day. I do it every day, I do it the same way. Somebody gave the example might have been Soma, I know somebody else, expense report approval? >> Yeah, yeah. Yeah. >> I've never not approved and expense report. I don't crack them open. Look, I don't know, maybe every now and then somebody does. Somebody does, by the way. (laughs) >> (shouts) So don't get any idea here. >> I always press the approval button, right? Why can't a robot do that and look for anomalies and say, Oh, a $300 scotch? That's... >> Yeah Yeah. Absolutely... So is that a capability that you're working on, that you have today. That what I'm envisioning a studio and then I imagine this got some orchestrator... >> Yeah. So yeah, so if you look at throughout all Infor OS, is completely Model Driven. So either you, you build a new integration, or a workflow, or a, an AI model, or a even, we have a platform as a service Mongols, where you build with low code applications. So you can take it to end to end where you you train models in AI, us suppose as an API. You can build your own app on top of it with low code and then, you know, give it to your business users. Very, very simple and in the cloud. You know, in the browser and you can do every customer can do it. So that's very important for us. We work from the beginning with this model to give you know, the tools to everybody, not only an elite of people that can do and then you know, there is the rest of the people that cannot do it. Every new computer science engineer that comes out gets you know, AI out of the box. When I did computer science, Yeah, I got some AI, you know, but it was not really like today. So every everybody can program AI now. And we want to give this tools to every developer and not just went to an elite. >> Yeah. And the workflow prediction model that you've been talking about. If you want to come join us down there, we've actually got a model that we're working on for that exact use case. >> Oh, cool. >> Yeah. So yeah. Giving the ability for those business users, as you say to... it's almost like lowering the barrier to entry to a lot of this AI technology. It's not devaluing or anything, data science, because we've got those advanced tool sets, to where if you want to do something in our studio, bring it over into the Coleman AI platform. You certainly can, we're not devaluing that. But you know, what, if we want to start and take little bites off and you want to give this in the hands of the business users, we've got a great solution for that. >> So this is all the cool stuff. This is stuff that business users care about? I mean, do they... My question is, do people care about what's under the covers? I mean, are they asking you or what's the database? And how does this work? How does that work? Or they just really want to focus on that functionality that they're getting in the business impact? >> Yeah, with the advent of the cloud, you know, people, just those questions like we sh... you know, operating system database, which technology you use? it just went away, right? So people just want to know, the functionality and the value. You know, maybe there are companies that I have more, you know, an IT architects and they want to know, more, you know, that's what they want to go down into the details, then you go into the architecture of the OS, of the application, we integrate with AWS. So we do that as well. We, you know, we talk to customers about it. But most of them, they just want to know, okay, "how can I use this platform to make my business better," right. So it runs the cloud suit, but I now I can connect to other cloud services, I can connect to the other application, I can build my own app and bring it in. So they want that business value immediately. And that's why we built this Infor OS, so that they can run the cloud suite and add business value. >> You guys at last year's analyst meeting, gave a little glimpse of some of the architecture and it was very useful, actually, analysts love that kind of stuff. I didn't get the invite this year, maybe something the some smarmy questions I ask. (laughs) But I found that actually quite impressive in terms of the tech behind it and the RND that you guys are doing there. But ultimately, it comes down to what products you can build and what business impact that has, right? >> Yeah, absolutely. I think where we're heading with this, we really don't have many limitations for what we're seeing right now. We're built in a way to where we can apply to every single industry, every single cloud suite. We have the unique, you know, possibility to where we can go through all these different industries and create these sort of value. So we've got a very unique future ahead of us. >> So. Yeah, So how much better or can you give us an idea of a road map a little bit about what you think Coleman can go? >> Yeah so, we're starting to play in the image recognition space a little bit. Maybe looking at how we can utilize things like drone technology and do inspection reports, those sort of things. It's maybe and at least my opinion, I think others kind of express the same, it's maybe the least developed area and we want to make sure we have something that works for customers the way that they're going to see value immediately. But also we're starting look at edge AI. So how can.... not necessarily just an IoT, but how can we how can we build something in the cloud? How can we create a model, then deploy that for our onprem customers who aren't quite ready, so that they can get that AI experience as well, and that predictive insight. >> It's dvallante@Siliconangle.com Is that right? Your email for the invitation >> David.valante... >> (laughs) to make sure... so what will exchange information later. >> We'll invite you (laughs) >> I'm sure this is not your territory. (laughs) >> Its on me. >> Thanks for joining us. >> Thank you. >> Its been a pleasure. Thank you for the time we appreciate that. Back with more here from Washington DC right after this. You're watching theCUBE.

(futuristic music) >> Welcome back everybody, Jeff Frick here with theCUBE. We're having a CUBE conversation in our Palo Alto studios, we're waiting for the crazy madness of the second half conference season to begin but before that it's nice to get a little bit of a break in the action and we can have people into our studio in Palo Alto. We're really excited to have our next guest really adding to this journey that we've been kind of watching over a course of many years with Informatica, she's Tracey Newell she's the newly announced President, global field operations from Informatica, Tracey great to meet you. >> Yeah nice to meet you. >> Absolutely. So we've following Informatica for a long time, I think our first visit to Informatica world was 2015 back when it was still a public company, I think it was Info which still has this legacy, that's the hashtag for this show. >> It certainly does. >> Which is kind of funny cause it's not really a stock ticker anymore. So it's been quite a journey and really well timed with kind of the big data revolution. You joined the board a couple years ago. >> I did in 2016. >> But you just decided to leave Mahogany Row and take off the board outfit and jump in and get on the field and get dirty. So why did you decide to get into the nitty gritty? >> Yeah so I joined the board because I really believed in the mission so. Digital transformation is something that's real, it's a boardroom discussion. Every enterprise and government around the world's trying to figure this out and so I wanted to be part of that and I've had a front row seat for a couple of years. >> Right right. >> I'm not one to sit on the sidelines for very long and I thought this is just too much fun and I want to get in the game so I asked to step down and I've recently joined as a president of Global Field ops. >> Great so your background is a little bit of confusion due to history, a lot of sales, you've been running sales for lot different companies, been in the valley for a while. But sales is really under you so you haven't really left your sales hat, that's just part of now a bigger role that you're going to be doing with Informatica. >> Yeah that's right, it's a bigger and broader role, but my favorite thing is running sales organizations. So I've done other things too, I've run operations, and customer success, but I was thrilled to join and also run professional services as well cause that's so important to the delivery and for our customers. >> So you'll write the digital transformation, it's the hop topic, it's what everybody is talking about, and it's true and as Informatica is in the middle of it, data is such a big piece of the digital transformation as everybody, we used to joke, there are no companies except software companies. I think we're taking it to the next step, now there are no software companies, really everybody should be a data company, and Informatica is sitting right in the middle of that world. No that's right, yeah data is the new currency, it's become of the most important assets for enterprises, everyone's trying to transform, they're trying to disrupt, they're trying to take on the leader or they're trying to keep their lead. And they need all their information throughout their organization in order to do that and so you know one of the stories hat I really like, Graham Thompson's our CIO and he talks to lots of CIOs and he'll use this analogy in that you know he'll say does your CFO have good containment strategy around their most important asset, and that's revenue. Does your CFO, does he or she know what the data is and inevitably the CIO will say of course. Well that's great does he know or she know how they're spending the money and who's spending the money? Do they have controls and compliance and security around that and of course the answer is yes yes yes and yes. And it inevitably turns to the CIO to say well if data is your most important asset, if that truly is the currency in your organization, do you know where all of your data is? And the answers always no. And there's lots of reasons for that, it's most enterprises have hundreds if not thousands of databases and shadow IT projects everywhere. But if the answers no then how do take advantage and leverage that information to the companies advantage? How do you control it, how do you have compliance and that's where we come in. >> So what's the Informatica special sauce? What's the secret sauce that you guys can bring to the party that nobody else can? >> Yeah so I think inevitably that it would be the platform so our intelligent data platform is really important to the enterprise. The CIOs that I've been meeting with for the last decade have said you know I can't have ten widgets that are all solving a similar problem cause it's just too expensive. I need the bet with the leader in the space and so what we're doing to provide that for enterprises is really important and yet at the same time, you've got to be the best at what you do, you can't just be comprehensive but you have to have best debris technology. We're spending 17 cents of every dollar in r&d and we're so focused on just this one thing, our mission is to lead in digital transformation for the large enterprise and we've been doing this for 25 years so we've spent billions of dollars at making sure our customers are invested in us and that we protect that investment. >> Right. So what is your charge is as you're starting your new role I think the press release just came out a couple days ago. You know what does O'Neil say to you, you know we want you, here's where we want you to go take down that next mountain, what are some of your short term priorities, what are some of your longer term priorities? >> Yeah so we have a great opportunity in front of us. So stating the obvious I'm here to drive growth and expansion both in market share opportunities, we have over nine thousand customers globally and yet we all know that there's a tremendous opportunity to continue direct market shares. This is a global phenomena and yet our largest customers we have 85 of the Fortune 100, they certainly need a lot of support and we're here to help provide that leadership. And we do a lot of best practice sharing, we do a lot around helping customers on their journeys cause we see these themes given that we do work with the largest companies around the world. >> And I'm sure you're going to be getting on a plane and meeting with a whole bunch of customers over the next, over the next several weeks and months but was there something from your board position that you could see was a consistent pattern that you really see an opportunity for growth, kind of an unexploited opportunity as people are going through this digital transformation cause we talk all the time, it's how do I get started and you know I have small projects to give me early success and kind of those types of conversations but clearly we're kind of beyond the beginning and we should be starting to move down the field a little bit. >> Yeah certainly. So we work with all the global SIs and we won't ever try to take their place you know Insentrum, Delite, Capgemeni, Cottonsmith, they're tremendous at what they do and we partner with them very well. But we've absolutely seen consistent themes as we work with these big enterprises, I mean we've seen Coca Cola work on delivering new packaging for the World Cup where they drove exponential sales and they wanted to use the power of all of their data. The data in the Cloud, the data that they have on premise, the data in all the SAS applications and that's where we come in and really help them, helping them to leverage all of their information and to do that in an intelligent way and so we've seen several patterns emerge how customers can get started and we've created a series of workshops and summits and specialists that we we can sell on a pro forma basis in helping customers figure out where those quick fixes are. There's a couple of key big buckets, we see most large enterprise moving from on premise to Cloud and they're trying to figure out a a migration strategy so we help a lot there. Most customers are trying to figure out how to get closer to their customers so we do a lot of work around customer intimacy. Intimacy could be driving the top line, cross sale, up sale, or even customer retention. B&P Paraboss did a lot of work with us there around getting closer to you know in their wealth practice. And then we do quite a bit around governance as you would expect. That's a hot topic with GDPR again if you can't say you know where all your data is well then how can you be compliant? >> Right how can you delete me? >> How can you delete me if you don't know where your data is. There's a number of practices that we've set up and we'll do some not for fee consulting work to help customers try and figure this out. >> Yeah clearly when we first met Informatica in 2015, you know the Cloud was moving, the public Cloud, but it wasn't near what it is today. And I guess you guys just had a recent announcement, Google Cloud Next is coming up in a couple of weeks and so you guys are now doing some stuff with Google Cloud? We are yeah so we're pretty good listeners I think that's important if you're going to be a business partner to your clients you got to know what they want and one of the things that clients have said to us is we need you to partner with our partners. You know the days of proprietary and sole source, you know we're going to be everything to you without working with anyone you know those days are over. And so the key Cloud partners our customers have asked us to work with include Amazon, Google, Microsoft, Azure, so you're right last week we did make an announcement that we've done deep integration and we're spending our r&d dollars for customers that are investing with Google to make those investments more valuable and we announced API management and integration with Google make that easy for customers so. Informatica world we announced native integration in our Ipass platform for Microsoft so over and over again you'll hear us continue to do more with the the partners that our customers want us to and that's a win win for everybody. >> Its just so funny too because when people talk about a company like say Coca Cola which you brought up they talk about it like it's a company. No it's like not a company, it's many many companies, many many projects, many many challenges you know it's not just one entity that has a relationship with one other entity. >> That's right. >> But the other thing I think is interesting times and Coke's a good example or Ford or pick many old line industrial companies that used to have distribution right and what was the purpose of distribution is to break bulk is to communicate information and to get the product close to the customer. But the manufacturer never knew what happened once they shipped that stuff off into their distribution. Now it's a whole different world, they have a direct connection with their in customer, they're collecting data from their in customer, and so they have a relationship and an opportunity and a challenge with that they never had before. They just sent it off to the distributor and off it went and hopefully it doesn't come back for repair. (laughing) >> No that's right but you're exactly right, and that's the challenge that customers are facing. I don't care if it's a customer in the mid market or it's a customer in large enterprise or if it's a government organization. They need to know all aspects of their customer partner supplier information and how to communicate globally if they're going to drive disruption. And one of the CIOs of a Fortune 500 made a comment that we decided that we were going to disrupt ourselves before someone else disrupted us. And that's, that's my comment on why this is a board level discussion, it's super important, and we can help solve those problems. >> It's funny Dave Potrick one of my favorite executives used to be the number two guy at Charles Schwab and I remember him speaking when they went to fix price trading back in the day, I'm aging myself unfortunately but you know he said the same thing, we have to disrupt ourselves before somebody else disrupts us. And if you're not thinking that way you're going to get disrupted so better it be you than someone that you don't even see and usually it's not your side competitor, it's the one coming from a completely different direction that you weren't even paying attention to. >> That's right. And we see that over and over again and you made the right comment in that it's not always easy, some of these Fortune 500s through consolidation, even the Global 2000. They've done all these acquisitions and so you've got hundreds of BUs that don't have any systems tied together and how do you start to create a common connection in so that you can build your brand and you can try differentiation and that's the key, that's back to the intelligent data platform. >> Right and as you said and there's not single systems and now we got API economy, things are all connected so you don't necessarily even have that much direct control over a lot of these opportunities and you said that first I think it's just like okay where's your data? Can you start with the very simple question and a lot of people aren't really sure and can't even start from there. >> That's right. >> So good opportunities. >> Absolutely, there's no question. >> Alright Tracey, well thank you for stopping by, congratulations on your, on your new position and moving from Mahogany Row down into, down into the trenches. >> Down on the field. >> I'm sure they're going to be happy to have you down there on the field. >> Yeah no thanks Jeff I'm happy to be here and thanks for the time today. >> Thank you and we'll see you in Informatica world if not sooner. >> That's right. >> Alright she's Tracey Newell I'm Jeff Frick, you're watching theCube from Palo Alto, thanks for watching. (futuristic music)

>> Narrator: From San Mateo, California, it's theCUBE, covering SnapLogic Innovation Day 2018. Brought to you by SnapLogic. >> Hey, welcome back here, Jeff Frick here with theCUBE. We're at the crossroads, it's 101 and 92 in San Mateo, California. A lot of popular software companies actually started here, I can always think of the Siebel sign going up and we used to talk about the movement of Silicon Valley from the chips down in the South Bay and Sunnyvale, and intel, really to a lot of software here in the middle of the peninsula. We're excited to be here at SnapLogic's headquarters for Innovation Day, and our next guest is Craig Stewart, he's the VP of product management. Craig, great to see you. >> Thank you very much. Welcome. >> Absolutely So, we're talking about API's, and we go to a lot of tech shows and the API economy is something that's talked about all the time. But really that has evolved for a couple reasons. One, is the proliferation of Cloud services, and the proliferation of applications in the Cloud services. We all know if you go to Google Cloud Next or Amazon re:Invent, the logo slide of absent services available for these things is tremendous. Give us kind of an update, you've been involved in this space for a long time, how its evolving what you guys are are working on here at SnapLogic. >> What we've seen change of late, is that not only is there a requirement for our customers to build API's, but also to then allow those API's to be consumed by their partners and networks out there. As a part of that, they may need to have more management of those API's, then we provide. We're very good at creating API's with inbound and outbound payload, parameters, all of those things, so we can create those data services via our API's, but customers then need to have a requirement now to add some functionality around. What about when I have a thousand users of these, and I need to be able to throttle them and those kinds of things. What we've seen happening is there's been this space of the full lifecycle API management technologies, which have been available for some time, and amongst those we've had Google Apigee kind of being the benchmark of those with the Apigee Edge platform, and in fact what we've done in this latest release is we've provided engineered integration into that Apigee Edge platform so that the API's that we create, we can push those directly into the Apigee Edge platform for them to do the advanced authentication, the monetization, the developer platform around it to develop a portal, all of those kind of things. In addition to that, we've also added the functionality to generate the open API specification, Swagger, as it's known, and to be able to take that Swagger definition to having generated it, we can then actually drop it into the API gateways provided by all of the different Cloud vendors. Whether it's Amazon with their API gateway or the Aggre gateway, all you need to do is then take that generated Swagger definition, and this literally is a right-mouse button, "open" API, and it generates the file for you, from there just drop that into those platforms and now they can be actually managed in those services directly. >> I want to unpack API lifecycle management, cos just for a 101 for people that aren't familiar. We think of API's and we know applications or making calls, and it's, "I'm sending data from this app to that app, "and this is pulling information from that app to this app." That's all pretty straightforward, but what are some of the nuances in lifecycle management of API's that your typical person really hasn't fought through that are A, super important and only increasing in relevance as more and more of these systems are all tied together. >> The use of those API's, some of the things around them that those platforms provide is some advanced authentication. They may be using, wanting to use OWA two-factor authentication, those kind of things. They may want to do some protocol translation. Many customers may know how to consume a SOAP service... generally Legacy, these days-- >> So funny that SOAP is now Legacy (laughs) >> It just cracks me up. I remember, the hottest thing since sliced bread >> Oh yeah! Oh yeah! I still have the Microsoft Internet Explorer four T-shirt-- >> When it was 95 Box too, I'm sure. But that's another conversation for another day. (laughs) >> The management of those API's adding that functionality to do advanced authentication, to do throttling... If you have an API, you don't want all of your back end systems to suddenly be overwhelmed. >> Jeff: Right. Right. >> One of those things that those full lifecycle platforms can do is throttle so that you can say this user may have only 10 requests a minute or something like that, so that stops the back end system being overwhelmed in the event of a spike in usage. That helps with denial of service attacks and those kind of things where you're protecting the core systems. Other things that they can do is the monetization. If you want to atrially expose an API for partners to consume but you want to charge them on that basis, you want to have a way of actually tracking those things to then be able to monetize that and to provide the analytics and the billing on top of it. There's a number of those different aspects that the full lifecycle provides on top of what we provide which is the core API that we're actually creating. >> Right. Is it even feasible to plug an API into a Cloud-based service if your service isn't also Cloud-based cos as you're speaking and talking about spikes, clearly that's one of the huge benefits of Cloud, is that you have the ability to spike whether it's planned or unplanned to massive scale depending on what you're trying to do and to turn that back down. I would imagine (laughs) if your API is going through that platform and you're connecting to another application, and it's Pepsi running a promotion on Superbowl Sunday, hopefully your application is running in a very similar type of infrastructure. >> Absolutely. You do have to plan for that elastic scalability. And that's one of those things with the SnapLogic platform, is it has been built to be able to scale in that way. >> Right. Now there's a lot of conversation too around iPass and integration platforms as a service. How do you see that mapping back to more of a straightforward API integration. >> What we're talking about in terms of API integration here, and the things that we've just recently added, this is the consumption of our API's. The iPass platform that we actually provide consumes API's, all sorts of different API's, whether they're SOAP or REST and different native API's of different applications. That we do out of the box. That is what we are doing, is API integration. >> Right. >> The new functionality that we've introduced is this added capability to then manage those API's from external systems. That's particularly where those external systems go beyond the boundaries of a company's own domain. It's when they need to expose those API's to their partners, to other third parties that are going to want to consume those API's. That's where you need those additional layers of protection. Most customers actually use those API's internally within their organization, and they don't need that extra level of management. >> Right. Right. But I would imagine it's an increasingly important and increasingly common and increasingly prolific that the API integration and the API leverage is less and less inside the building and much much more outside the building. >> It is certainly going a lot more outside the building because customers are recognizing their data is an asset. >> Right. Right. Then having it be a Cloud broker, if you will, just adds a nice integration point that's standardized, has scale, has reliability, versus having all these point-to-point solutions. >> Yeah, absolutely. >> I was going to say, As you look forward, I can't believe we're May 16 of 2018 already (laughs), the years halfway over, but what are you looking forward to next? What's kind of on the roadmap as this API economy continues to evolve, which is then going to increase the demands on those API's integration, those API's in management, as you said the lifecycle of the way all this stuff works together, what's kind of on the roadmap if we talk a year from now, what are we going to be talking about? >> There's a lot of... settling down of what we've delivered that's going to take place, and on top of that, then the capabilities that we can add to add some additional capabilities that the customers want to use, even internally. Because even internally where they're not using a Cloud service, they have requirements to identify who in an organization is utilizing those things. So additional capabilities without having to go beyond the boundaries of the customers own domain. That's going to be some things like authentication, it's going to be some additional... Metrics of what's actually being used in those API's, the metrics on the API's themselves in terms of how are they performing, how frequently are they being called, and in addition to that, what's the response time on those things? So there's additional intelligence that we're going to be providing over and above the creation of the API's that we're looking to do for those customers, particularly inside the organization. >> It's very similar requirements but just different, right, because organizations, take a company like Boeing, or something, is actually not just one company, there's many, many organizations, you have all kinds of now with GDPR coming out, cut of data, privacy and management restrictions, so even if it's inside your four walls, all those measures, all those controls are still very very relevant. >> Very much so. Providing some additional capabilities around that is pretty important for us. >> Alright. Well Craig, you're sitting right on top of the API economy, so I think you'll keep busy for a little while. >> (laughs) That's for sure. >> Thanks for taking a few minutes to stop by. >> Thank you. >> He's Craig Stewart, I'm Jeff Frick, you're watching theCUBE from SnapLogic in San Mateo, California. Thanks for watching. (techno music)

>> Narrator: Live from San Francisco it's The Cube covering Informatica World 2017, brought to you by Informatica. >> Okay, welcome back everyone we're here live in San Francisco for the Cube's exclusive coverage of Informatica World 2017. I'm John Furrier of SiliconAngle Media. My cohost, Peter Burris, head of research at SiliconAngle Media as well as the general manager of Wikibon.com, Wikibon research, check it out. Some great research there on IoT, big data, and certainly cloud computing. Our next guest is Graeme Thompson, Executive Vice President and Chief Information Officer for Informatica, great to see you, welcome back to the Cube. >> Nice to see you, John. >> Conference here, lot of customers, you've got an executive summit, dinner last night, you're kind of like the sounding board, they go to you for the checkpoint, hey, does this story jive, what's going on internally, 'cause you're living through a transformation as well at Informatica. Your customers are going through a transformation as well. We're at this tipping point. What's your take so far of the conference, and is that still the case? Anything you'd like to share on that would be great. >> Yeah, I mean we're proud to have some of the world's best companies using our products to do meaningful and important things. And the scale that some of these companies are doing it at is just staggering. I met with someone last night at dinner and, at Allegis, the talent management organization, and they process and keep up to date 55 million resumes every day. And they extract the metadata from those resumes to match the right candidate to the right job. And you know, that's interesting for them as a company but the societal impact of that is significant. Imagine, I mean we're all starved for talent, and you're matching the right talent with the right opportunity more often than not, using the intelligence of the data, it's pretty interesting. And then of course, I know you had Andrew McIntyre from the Cubs on yesterday, I mean how can you not love that story of how an organization as great and renown as the Cubs is using data to transform it's business operation. It's really amazing. >> We had Bruce Chizen on who's Executive Chairman of the Board of Informatica, was on the board at Oracle, but Peter asked him an interesting question that I'll ask you. What's your definition of strategic data management? >> That's a good one, so the way I define it is, if the basis of your competition is on digital assets compared to physical assets. So we're no longer dealing with plant or machinery or even capital, it's digital assets. If that is the basis of your competition, then the data that you rely on is the very foundation of that. And then it becomes strategic just like money is strategic. And the access to talent is strategic. The ability to leverage the data within your company, about your company, is strategic, and you have to be able to do it on-prem, you have to be able to do it on the cloud, you have to be able to do it in the real world where most of us live, which is in both worlds. And that to me, that's what makes it strategic. >> But let me build on that Graeme, 'cause in many respects the whole concept of digital transformation is, oh let me step back. One of the premises of business is to try to reduce what's known in financial or economic worlds as an asset specificity. So traditionally we've looked at assets and said, this asset's going to be applied to that use, and this asset's going to be applied to that use, and if it's the use isn't needed or it's not being applied, you lose the value of the asset. One of the basic premises of digital business and business generally is how to we reduce asset specificity, and data let's us do that by turning an aircraft engine into a service, we have transformed the role that that asset plays in our customer's business. So you're absolutely right, it's the ratio of physical to digital assets, but all businesses have to find ways to reduce their asset specificity by adding digital on top of it so they can appropriate that asset to a lot of new purposes. Do you agree with that? >> Absolutely, so take, so I know you talked to Sally about the data leak. So take a user case like customer support. Who in a software company knows more about the customer, what product their running, what version of product their running, what they're using it for because of the connectors they have. Nobody in the company knows more about that than the customer support organization. But that asset, the most profitable use of that information, may be in marketing, because then we can help our customers adopt something more quickly, we can help them get value from it more quickly. And it helps us because it helps us focus our R&D effort where the customers are really using the product instead of having to guess. So I think you're spot on, if you can remove the constraint on the asset to be for who paid for it, for one particular purpose and make it available to the entire enterprise and outside the enterprise, then you really start to see the value. >> The thing that you mentioned about digital assets Peter, and the Wikibon team talk about this all the time in their research, digital assets, is the data. Whether it's content or whatever. Certainly we're in the content business, but... >> Peter: Well digital assets are data. >> Are data, exactly, and whether it's content or whatever aspect it is. So I've got to ask you... >> Software, software is a digital asset. >> Data is at the center of it all. So I've got to ask you, there's been a lot of artificial intelligence watching going on in the industry. I call it augmented intelligence because it's really not yet artificial by the strictest, purest definition, but machine learning is very relevant. We talked about IoT when you were last in our studio. How is it impacting your business and customer's business? Because that's the real proof in the pudding, if you will. And customers are trying to sift through the BS that they're hearing from other folks. I'm not saying that you guys are saying BS, but what's the acid test? How do you differentiate between smokescreen and real deal? >> I think it comes down to, like any other technology investment, is what is the business outcome that it generated? So if you're trying to... So humans make mistakes, if you're trying to eliminate human error from a process, a machine can execute that process more repeatably and more accurately than a human. It's not about reducing cost, that's only semi-interesting. It's about enabling outcomes that weren't possible before. So you think about healthcare industry. Everyone talks about self-driving cars and how safer it'll be if the cars aren't dependent on a human, but one thing I read recently is we kill more people in the US by prescribing the wrong drug or the wrong dosage than we do on the roads. So humans work hard, but they make mistakes. If we can have the machine do that job because a human can tell it how to do the job and it can learn over time, then you can eliminate that error. And we're able to do things that we can only imagine. >> Machines rarely get tired, they rarely lose attention, blah blah blah blah blah, and it's all those things, and that's where the augmentation is. And there will be the other forms of artificial intelligence, the algorithms have been around for a long time. The hardware now can support it, and the data is being generated to apply it. >> The data's available and the cost of compute is approaching zero. So we're able to do things that the government could only do before. >> Graeme, I want to get your thoughts on data integration. Certainly we saw yesterday the news with Google Spanner. You guys were one of three companies that was early on, before they announced their general release of Spanner Worldwide, the attributed database, horizontally scaled database. Big deal, but you guys were also on the front end of that as it says in their blog post, and you guys are really strong at data integration. What are some of the challenges that the customers face with integration? What are the key things? Because that seems to be, whether you go multi-cloud or hybrid-cloud today, which is a gateway to multi-cloud, which is happening pretty fast, data integration is pretty important. >> Yes, so as a CIO this is something that is a very hot topic for me, and it's not a new hot topic, it was a hot topic 15 years ago when we went nuts and deployed all these client server applications because they were cheap and easy. And then you had to think about, oh these different disconnected applications don't serve an end-to-end process anymore, now we have to stitch them all together. That was hard, but it was all on-prem and you had access to it all. >> Peter: It was all programed. >> Right, whereas now, like you said you've got Salesforce, you've got Workday, you've got Great People, you've got your on-prem stuff, you've got applications that you're hosting on someone's PAS cloud and the IAS cloud and the SAS cloud, but to execute an end-to-end business process to generate an outcome you have to tie it all together. So instead of thinking about... >> John: And it's not on-prem so you can't touch it, and it's not on, you don't have it. >> Right so you can't hand code that, you could, but I would argue that that would be an unintelligent way to do it, which is where Microservices API has come in. So you can leverage the R&D efforts that the great software vendors like Salesforce create for us. And then you use Microservices to plug into that instead of having an army of people hand-coding interfaces, which is what we used to do 15 years ago. >> That's the human error point. I mean, it could be spaghetti code, all kinds of errors could happen. >> But also the maintenance of that is just virtually impossible given the speed and the fact that human beings are now thinking about new ways of doing things. You just can't keep up with that. >> I mean the coding thing's a big deal. We used to call it, back in the day, spaghetti code cause it's like all this integrated purpose-built coding for one purpose to glue it together. >> Right and then you change one data element and you have to rewrite or retest the whole thing. >> John: A guy leaves or a girl leaves, it's a nightmare, right? With APIs and Microservices you're decoupling that. That's kind of what I think you're getting at, right? >> Exactly, and that's what the whole iPass space is about. You can decouple the user experience from the data and just have, what does a user have to do, and then Microservices and APIs will take care of the work behind the scenes between the applications and that really lets... There's this concept of a citizen integrator. So 15 years ago, it was kind of a modern thought to have business people write reports. I think it won't be long before we'll be able to give the business teams the ability to do integration between applications without depending on me. >> I was talking with a young developer the other day and I'm like, yeah you know your coding is like me doing PowerPoints. They're like, what do you mean, it's so easy. No, it's not that easy. >> Well we've been building macros, good or bad, inside for example things like Excel for a long time and one of the primary drivers, in fact of a lot of the BI stuff, was citizen coders building macros and said I need the data to make my little macro run. Now I don't want to say that that is... That's not what we're talking about, we're talking about something that's considerably more robust where we can be very very creative in thinking about how we might use the data. And then being able to discover it and find it and very quickly and with a low-code orientation being able to make the actual application happen that has consequential impact in the marketplace. So Graeme, you're in a company that's trying to help customers move through some of these transitions. You're in a crucial role because we know where the data is, we know how to integrate it. >> Graeme: You did? >> Well we're discovering where the data is, we have tools that's going to help us, we're learning how to integrate it. But one of the big challenges is to get the business to adopt new orientations to the role that data's going to play. That to me is one of the key roles of the CIO, having worked with a lot of CIOs over the years. For a very very simple example, agile development does not line up with annual budget finance. How are you with Informatica helping to acculturate executive teams to think through new processes, new approaches to doing these things so that the business is better able to use the data so that consequential action happens as these concepts of these great insights that you're generating? >> So the whole change in management effort is a huge and complex thing to overcome. But I have a personal passion about making sure that you always remind people why they're doing it. Too often as product people or technologists, we get into the how and the what and we forget the why. And as soon as it gets difficult people abandon because it starts to get too hard, it starts to get painful, and if they've lost sight of the big why they're not going to role their sleeves up and gut it out and get through the process. So that's the first thing you have to do is remind them that the prize at the end is worth the pain. And it will be painful because no longer are you optimizing just your function. You have to think about what happens upstream from you, what happens downstream from you, and try and optimize things at the enterprise level. And that's not how most people were brought up. It's not how their measured, it's not how their compensated, but that's what's really required if you're going to make that transformation I think end-to-end. >> But it's also, even our language, we talk about innovation in this industry as though it was synonymous with just creating something new. Certainly our research very strongly shows that there's a difference between inventing something which is an engineering act and innovating around something which is a social act. Exactly what you just said. How do we get people to adopt things and change behaviors and fully utilize something and embed it within their practices so that we get derivative innovation and all of the other stuff that we're looking for? >> Yeah there's no easy recipe. People are different so people require a different story in order to have them buy in. Some people are loss-framed people, where you got to explain here's what's going to be bad if you don't do this. Other people are gain-framed people where you can say if we can accomplish this, we'll be able to do these great things. And it would be great if everyone was the same and one story worked for everyone, but it doesn't. So it's almost a feet on the street. Go talk to people and just keep reminding everyone why you're doing this and why it's going to be worth it. >> Peter: A little bit of behavioral economics there. >> John: Graeme I want to ask you one final question. You mention client server and how it was easy on-prem in the old days, get your arms around things, which is the IT practice, you know? That's the way it was done. In the cloud, a little bit more complex. But to take that a little step further, I want to get your thoughts on something. You lived through the world of server sprawl. More servers, more glue, you get your arms around it but then it got bloated, IT got bloated. And that's one of the catalysts for going to the cloud is efficiencies, bottom-line costs. But now, top line revenue now is a mandate. So now we have SAS sprawl. So with APIs, a little bit more security concern, but your thoughts on the now we have a SASification happening or API economy. So you have a lot more APIs, there's Microservices coming on the scene, it's emerging very quickly, still emergent. Embryonic some will say, not so, but I think it's embryonic still. Okay server sprawl, client server, VM sprawl, now you got SAS sprawl. Your thoughts on this dynamic and how a CIO tackles that? >> Yes, so it's the modern equivalent of your legacy technical debt. So it's a modern mess instead of an old mess, but it's the same problem. You know, you have to stitch these applications together and it's made worse by the ease of consuming these SAS applications. So one business function can go off and buy an application that's just for them, and the adjacent business function goes off and buys another application that's just for them. And before you know where you are, you're single sign-on page has three pages because you've got so many applications that you're using to run your business. So I think we have to be more thoughtful and not make the same mistake that we made after 2000 when we went nuts on all these client server applications and make sure that we're thinking about the end-to-end business outcome. >> John: So the unification layer is what, Identity, is it the data? I mean how do you think about that just conceptually? >> Well I think you still need a sensible portfolio of applications. I don't advocate that you just go buy every great application that's out there. If your business doesn't compete based on the capability that that application provides, you've got no business innovating. Just be as good as the next guy. But if you compete based on something, go pick the very best application you can but deploy it thoughtfully. Make sure it's integrated, make sure it serves the end-to-end... >> Well I'm also fascinated by the role that Clair might play here at going and looking at the metadata associated with some of these SAS applications to help us identify patterns and utilization. I think Clair and the thing that was announced here actually could have an impact in thinking about some of these things. >> The Clairvoyant app is a great one, Clair, I mean... She, he, it's vendor neutral, that's a whole different story, only kidding. Final thought Graeme on this show? Just color perspective, what's your thought so far just on the show vibe for the folks who aren't here, what's it like? >> So when you and I met a couple weeks ago we talked about the fact that I'd just joined the company just after last year's show. So I have nothing to compare it to, but the energy level is phenomenal. The feedback from the customer's I've talked to just reinforces that we have really really important customers and we're really important to them. You know, the customers are the ones driving this digital transformation and we're proud to be helping them. And every conversation I've had with customers has really reinforced that and it's great, I can't wait to get back to the office. >> And as we say the KPI, the metric of the transformation of the world is not quadrants or category winners, it's customer wins. >> Graeme: Absolutely. >> And I think that's a great point. Graeme Thompson, Executive Vice President and Chief Information Officer of Informatica sharing his insight. He is an integral part of their transformation as well as his customers. Informatica World coverage with the Cube continues. I'm John Furrier with Peter Burris with Wikimon.com. We'll be back with more, stay with us after this short break. (electronic music)