 Live, from Las Vegas, it's theCUBE. Covering Informatica World 2019. Brought to you by Informatica. Welcome back everyone to theCUBE's live coverage of Informatica World here in Las Vegas. I'm your host, Rebecca Knight, along with my co-host, John Furrier. We have a CUBE alum joining us. Graham Thompson, SVP and CIO of Informatica. Thank you so much for coming, for returning to theCUBE. Pleasure to be here. So one of the themes we talk a lot about on theCUBE is the 10th anniversary of theCUBE. Is the changing role of the CIO? And you are a CIO, so you are well positioned to answer this question. In addition to the changing role, there's also the perception of what it is versus the reality. Can you talk a little bit about how you see the role having evolved both at Informatica and as well as your peers at other companies, as well as what sort of the industry is expecting or maybe those not in the industry thinks you do versus actually what you do? Yeah, that's a long first question, thank you. Keeping all my toes here. Yeah, so a lot of things are, the outcome is the same, but the method is different. So vendor management's always been important, cost management's always been important, but as it moves from being predominantly on-prem to being predominantly in the cloud, the dynamics of how these deals are put together changes. So you need a different kind of approach to how you manage the portfolio of cloud applications. Security is different in the cloud, it's still important, it always has been, it always will be, but it's different in the cloud. You have to look much more at vendor risk management, make sure that you're comfortable with the risk posture of the vendors that you're sourcing your applications from. So those things I would put in the category of, you're trying to accomplish the same thing, you're just doing it differently because your application workload is more likely to be in the cloud. Things that are different though, completely different are expectations. So everyone can see the power of data and the power of having speed and agility in the cloud, but they want it immediately and they don't want to do the hard work to get there. So I find that the CIO sometimes has to be the educator or the evangelist for change to explain that if you want all this data to generate all these miraculous new outcomes, you have to focus on the process and then you have to enable that process within an application that's going to meet your needs today and tomorrow. You have to think end to end, which means you have to integrate applications like Marketo and Salesforce, then you need to find a way to get it all in your data lake. That is completely different, it's a completely different sport from what we were playing as CIOs five years ago. And it's definitely the biggest area of change that I've seen both internally and talking to peers. Graham, we've talked in the past, obviously good to see you again. You're a CIO, you work for Informatica, so you're the CIO of Informatica, so you don't need to be sold on the value of data. You're in the business, the data company who thinks hard and build building products for years. Then private, retooling, you see the way, we've talked about it, you guys been on the same wave, a great wave for four years, everyone else is now on it. So as a CIO who works for a company that's, you're not going to get in trouble for doing a data-driven project. What are some of the things that you got going on because you do have relationship with all the different cloud providers, you do have a great on-premises, large install base. And as you guys as a company, what are some of the projects that you're doing that would be a nice guiding light to folks watching who were really kicking the tires on digital transformation, not just like talking about it, but like, okay, architecture, roadmap, really thinking through all the hairy problems of what's coming down the pike for them. What are you working on? Yeah, so I think our marketing team's done a really good job framing things in the four journeys. So I'll talk about it within that context. So the first one is next-gen analytics. So a lot of companies go into this thinking, great, all I have to do is find where the data lives, ingest the data into my data lake or data warehouse, put Tableau on top of it and job done. Not the case, right? So as soon as you start sharing data across more than one function, marketing are really good at knowing their data. They know how it's generated, they know how it can be used. As soon as you let someone else lose on marketing's data, it's used at your own risk, right? So that introduces the need for governance. If you're going to use data in one organization that was generated in another one, you have to agree on the definition of terms. You have to agree on calculations so that you don't get the finance team and the sales team debating what the renewal rate is. So the next-gen analytics journey for us has been an interesting one. We started with an on-prem data warehouse, it's now on Azure. The tipping point for us was when most of the data is generated in the cloud, why move it back on-prem just to do analytics on it? So we made a decision to build that on the cloud with Azure. So leave it on the cloud as there, and then have the on-premise piece. Go to the cloud. It's for the MDM, it's for the pieces kind of come together. Yep. All right, so the on-prem analytics journey. So I want to give you another curve ball here. So as you come in here, you say, okay, great. The next step is, well, you know, I need to actually make my AI work. Get clear, the clarity starts here, it's a nice slogan, nice play on words there, but AI ultimately is where everyone wants to get to. AI is fed by data, machine learning, other things, really kind of feeding the outcome for AI. But without good data and or data that can help the AI get smarter, this kind of brings up the conversation of more data or diverse data, different data sets. So accessing data sets actually is a new dynamic that people are getting into improving, adds value to AI. How do you see that playing out? Because this really kind of brings up the real complex question, which is that you mentioned earlier, terms, rights, marketplace, sharing data, all these new things. What's your view on this notion of having more data sets feeding an intelligent AI? So part of the increase in enthusiasm about AI and ML is really the convergence of the technologies actually ready to help. It's not a science project off to the side anymore. And the need for it has never been greater. There's no way a human can keep up with all the data that's been generated even in a company like ours. So if you want to find out where the data's created, where it's used, who has access to it, then you're going to have to apply some AI to that. Otherwise there's no shot that you'd need an ever-increasing team of humans who would fail to do the job adequately. So you see data sets merging, not merging, but being merchandised, if you will, for lack of a better word. Yeah, well, you have to manage the lineage of it. So you have to know where it's created, where it's used, who has access to it, is that access appropriate? All those things have to be taken into account, especially when you look at all the compliance and privacy things that we're all faced with now 18 months ago, we weren't all that concerned about. And that really goes back to what you said earlier in our conversation in that the role of the CIO is so much as an educator and an evangelist. So can you talk a little bit about what you've learned in terms of making that message really sink in with employees, in terms of understanding where the data lives, who has access to it, all the obstacles that you just talked about. Yeah, so part of it, there's the managing the IT team and then there's managing the relationships with your business constituents. So let's take the IT team first. Really good IT people, like really good engineers, will work on the most interesting problem available. It's our job as a CIO to make sure that the most profitable problem is also the most interesting one. Fight number one is get people working on the right things because IT people will work incredibly hard. You just need to make sure they're working incredibly hard on the right stuff, with a focus on the right outcome at the end of it. So that's the IT part. Then working with the business stakeholders, it's really setting expectations because quite rightly they want everything as soon as they can describe it, it should be available. There's often a lot of technical debt that we have as organizations. We had a more than 10 year old deployment of Salesforce. You've got to believe there was a ton of technical debt in there because it was built to perfection for our old business. It wasn't built for our new business. So you have to work with the business stakeholders, bring them along with you on what to do first, what to do next, what the dependencies are, and focus on setting expectations that it's not going to be done overnight. It's about governance. Obviously, governance has been around for a while and we've talked about it before, but now more than ever, you're seeing in the news, first year anniversary of GDPR. I predicted that would be, I won't say it, I said it like months before, these bad words, BS basically, but it's reality. More privacy stuff, you're seeing more and more regions and cloud dealing with certain restrictions. So when I hear regulation, I hear constrained data. That goes in my mind here. Oh my God, regulation and innovation are always sometimes at odds. So it's a balancing act. What do you guys do to address that? What's the solution today and how do you see that playing out? Because SaaS is about data and agility. And that's why SaaS has been so popular. That's what digital transformation is going to get to is these SaaS-like benefits. Agile risk taking high reward, low risk high reward kind of things. How do you get the balance between regulation, compliance, risk and innovation? Yeah. So I can talk about how we look at it internally and then a little bit about how our customers look at it. So for us, you can look at it like a tax. It's a tax on innovation or if you look at it a little bit more optimistically, who wouldn't want to honor the customer's right to be forgotten? Who wouldn't want to consult their customer on where you use their data? So you can also look at it as a way that by implementing the GDPR or the California Privacy Standard or whatever it is, it makes your company better. It allows you to be the company that you would like to aspire to be. So you don't have to just look at it as a tax. Then when I look at our customers, they fall into two categories. Those that have to do it because they're in a regulated industry like financial services or healthcare. And then there's those that want to do it because they know it will help them serve their customer better. And you see a lot of governance and compliance projects starting from a place of defensiveness. They have to do it because they have to comply with new regulations that apply to them. And often it's companies that are really trying to make the best use of the data but they want to do it in a really responsible way. It's not, if done properly and responsibly, it can be something that's good for everyone, I believe. I just have one final question about the skills gap and this is something we've been really talking a lot about here. What are you doing to address it and is the problem really as bad as the headlines to make it out to be? Yeah, so there's the macro problem of aging workforce and where the new people coming from. There's that one. It's been with us for a while and it applies across all functions. Then those specific skills areas in IT that are always a shortage. Security is one. It's really, really difficult to find really good IT security, information security people. Often these groups can be ivory towerish. So it's hard to find people that are really practitioners. It's hard to select them and then it's hard to retain them because they always want to build and then move on and build something new. So security is one. Obviously data and analytics is a huge one. Finding people that can that know a little bit more than what an Oracle Data Warehouse is is a challenge. And then once you get those people, you have to make sure that they are working on things that they find worthy of their time so that they're motivated to work as hard as we need them to work. And then other areas like managing cloud vendors is I think a skill set that will start to grow up. These cloud contracts get really expensive as you scale and there's no friction at the point of consumption. We've got engineers that aren't allowed to order a stapler from Amazon without approval. But they can sign the company up to tens of thousands of dollars worth of compute cost obligation. You need governance and skills to manage that. If you ask an engineer, do you want slow or fast and or big and small? They're going to pick fast and large, right? Just a follow up on that skills gap question. For the folks that are graduating college, high school, elementary school, education is obviously kind of a little bit linear but people argue that there's no one playbook for the kinds of courses you need to take to get into the data kind of world. There is, is there any patterns you're seeing where the folks who are really excelling in this new environment have certain skills and classes? So if someone's going into college, maybe honing a class in a particular class or discipline, have you seen some things that work? No, what I have seen that works is finding people who have a track record of solving important business problems and using that to select the people that you hire because having a sound education and the technology is one thing. You've got to understand the business domain and the problem that you're trying to solve. That's where the value comes from. The business stakeholders value someone that can understand their problem that they're trying to solve or the opportunity they're trying to take advantage of. So finding those people that have a track record of solving meaningful problems, to me, has been a way to find the right folks in that area. Multitalented, and it's early too. I mean, Berkeley just had their first graduating class of our girl data science. It's kind of, it gives you an idea of how early this is. Yeah, and it takes two to four years to have a university course accredited, but the time you've done that, it's out of date. So that has to change. My final question for you, Graham, is for the folks that aren't here at Informatica World 2019, what's the summary in your view, the theme of the show, what's the key highlights that people should walk away with this year for the focus at Informatica World 2019? So it's not a new theme. It's more of an expansion on the theme from the last couple of years. So the importance of the platform is key. You can go off as an IT professional and source one product to solve one problem. And before you're done, I guarantee you'll have found an adjacent problem and you're going to wish you'd chosen a platform instead of an individual product. So if you listen to Anil's keynote this morning and Amit going into more detail, it's really about the platform and then the power of Claire and the AI part is part of that overall platform. That's really the theme, but it's not new. It's not something we just came up with last week. It's been a strategy for at least 24 months and we just continue to build on it. Bad data or no data is no AI. Or bad data is bad AI, no data is no AI. That's essentially the reality as AI becomes mainstream. Yeah, all right, thank you. Well, thank you so much for coming on the show, Graham. You're watching theCUBE's live coverage of Informatical World 2019. I'm Rebecca Knight and John Furrier. Thanks for staying tuned.