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Graeme Thompson, Informatica - Informatica World 2017 - #INFA17 - #theCUBE


 

>> 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)

Published Date : May 17 2017

SUMMARY :

brought to you by Informatica. Francisco for the Cube's exclusive coverage and is that still the case? And the scale that some of these companies Chairman of the Board of Informatica, And the access to talent is strategic. One of the premises of business is to try the constraint on the asset to be for who paid for it, and the Wikibon team talk about this all the time So I've got to ask you... Because that's the real proof in the pudding, if you will. and how safer it'll be if the cars and the data is being generated to apply it. The data's available and the cost Because that seems to be, whether you go multi-cloud And then you had to think about, cloud and the SAS cloud, but to execute an end-to-end and it's not on, you don't have it. And then you use Microservices to plug into that That's the human error point. But also the maintenance of that is just virtually I mean the coding thing's a big deal. and you have to rewrite or retest the whole thing. That's kind of what I think you're getting at, right? the business teams the ability to do integration and I'm like, yeah you know your I need the data to make my little macro run. so that the business is better able to use the data So that's the first thing you have to do is remind them innovation and all of the other So it's almost a feet on the street. And that's one of the catalysts for going to the cloud and not make the same mistake that we made I don't advocate that you just go buy and looking at the metadata associated so far just on the show vibe You know, the customers are the ones driving this And as we say the KPI, the metric of the And I think that's a great point.

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