 Live, from Las Vegas, it's theCUBE. Covering Informatica World 2019. Brought to you by Informatica. Welcome everyone, you are watching theCUBE. We are kicking off a two day event here at Informatica World 2019 in Las Vegas. I'm your host and I'm co-hosting along with John Furrier. It's great to have you, great to be here. Great to see you again. So Informatica is really sitting in the sweet spot of a fast growing area of technology, cloud and big data. I want to ask you a big question, where is the market? What do you see happening in this sweet spot area? Well we're here in Informatica World. I think that's our fourth CUBE coverage. We've been following these guys since they've gone private two years ago in depth. Interesting change over, right? They went private, just like Michael Dell did with Dell Technologies and then they went public in great performance. We said at that time if they can go private with the product skills that they have in this senior leadership, they could do well. And they've been on the same trend line which has been really positive, data. Now data is the hottest thing on the planet. This is the theme of the industry. Data is everything. Machine learning needs data. Data feeds machine learning, machine learning feeds AI. This is a core innovator. Now the challenge is on the enterprise side is that data is structured. It's in all these different databases. So in an enterprise, data kind of has all these legacy structures and legacy systems. And the cloud, for instance, cloud is where SaaS wins. And SaaS winners like Zoom Communications, Airbnb, you name all those successful cloud native companies. Data is at the heart of their value proposition. And data is unencumbered. There's no restrictions. They use data. There's data as analysis. They look at customer behavior, A-B testing. So data is the heart of innovation. This is Informatica's plan here. Claire is their AI product and their theme is kind of clever. Clarity starts here. And this is really the focus for Informatica. Their opportunity is to be that independent vendor supplier. The Switzerland has been called. The neutral third party to bring data together on-premise and cloud. That's what they're saying. That's their opportunity. The challenges are high. The data business is being regulated. We talked about it last time. You know, privacy, GDPR, one-year anniversary, Microsoft calling for more privacy. As more regulation comes in, that puts more restrictions on data. That requires more software. That creates overhead. Overhead is not good for SaaS business models. And that is where the conflict is. This is the opportunity. And if they can overcome that as a supplier, they could do well. And data growth is just massive. Cloud, IoT Edge, you name it. Data is the center of the value proposition. Well, and we're going to have a lot of great guests on the program this week. In particular, we're going to have Sally Jenkins talking about these four customer journeys that customers are going on. And in fact, data governance and privacy is one of the big tenants. So they are making, they are saying, this is our wheelhouse. We can do this. We can help you do this. Well, the thing is, we're going to ask every guest of the question of the week is, what's the skill gaps? Because digital transformation, although very relevant, is only as good as the people and the culture that's behind it. And that's a theme that we hear all throughout our different CUBE events. If people have the culture for it, they could do it. DevOps is another word that's been kicked around. But ultimately, if you don't have the people and just machines, it's really going to be a tough balance to strike. You need the machines, you need the data, you need the people. And this is where the challenge is in the industry. I think the skill gaps is a huge problem for digital transformation. It's, to me, the big blocker in seeing innovation accelerate. So customers are now having that journey and they're starting to really think about how to architect their enterprise with an on-premise with the legacy and cloud-native with full SaaS. And the companies that can get to a SaaS business model, managing the on-premises legacy will have a winning shot at taking new market share or toppling down incumbents in leadership positions. And I'm really excited about this idea of asking people about the skill gap and where the next generation of jobs are going to be in big data. I saw a survey from Google, 94% of IT managers can't find qualified candidates for open cloud roles. That's astonishing. I also saw an interesting quote from Tim Cook, who recently said that half of Apple's new hires are not going to have a college degree this year. And he said, when our own founder didn't have one, kind of really shows you what you can do. You might not need this degree. Well, first of all, it's really, first of all, I agree that the degrees don't really matter. In some cases, the old degrees might not apply to kind of the new jobs. I'll give an example. My daughter just graduated from Cal Berkeley this week, and they had the inaugural class of data, data science, data analytics for the first time, first graduating class. That's a tell sign that we're at the early, early stages. But data sciences can come from anyone. You could be anthropologist, you could be any skill. If you can solve a problem, you're good at math, you can see the big picture. You're seeing data science really being a career. And again, there's just not enough job openings. And data science isn't just for the data jockeys out there who want to do data. There's cybersecurity, huge data driven. Everything is data driven. The big growth area in the enterprise is the IoT, the Edge, as devices come online from manufacturing to oil rigs to wind farms. The Edge computing is a huge thing and that's a data problem. Everything is a data problem. So this is where I think the industry is focused. I think Informatica was really on it early and now everyone's jumping in. You got Amazon, Google, Microsoft, the big cloud players and you got all the existing incumbent enterprise suppliers all putting data at the center value proposition. So you got a lot of competition now for Informatica and they have to make some good moves here. And what I'm going to be looking for Rebecca is how they transform as a company because I think that they have to be an integration company. They want to be that Switzerland. They got to integrate to all the clouds. They got to integrate to all the different platforms and environments on the enterprise and create that one operating model. And this is something that they say they want to do and we're going to ask them. And you've not called them Switzerland. They've called themselves Switzerland and so I think that they are, they do want that. They want that for themselves. They are having these partnerships with all of the major cloud providers. So what you said, this is what you're going to be asking, this is what you're going to be looking for. What is it that you think will set them apart? I think ultimately I think Informatica's got a great management team when it comes to product and engineering. One of the things I've been impressed with is they get the product around data. That the only thing I think that could be a headwind for them is a challenge is this regulatory environment. I brought that up earlier. I think this could be a challenge and an opportunity and it could be a difference maker because there's no question that there are value propositions around how they're dealing with data management, their deals we're going to hear about with the cloud and all the new innovation they have with Clare and AI, certainly that's good. But if you don't have data feeding machine learning and the data is hard to get at and it's regulated, you've got clouds with geographies and countries have new regulation, this is a complicated problem. If they could create software to make that easier and create an abstraction layer and use the power of the cloud, I think they could have a winning performance. So to me, that's a killer opportunity and then making data work for SaaS oriented business models on premise and in the cloud. I think you're absolutely right and we heard Anil Chakravarty say this today, data needs machine learning and AI, AI and machine learning need data and any application of AI and machine learning is only as good as the data that's been collected. So the other big challenge is what I think is going to be really exciting about for this show is seeing all these use cases. These in industry after industry, we are seeing applications of AI and machine learning transforming business models and approaches and leadership and big ideas around these important game changers in our industry. You know, one of the things that's interesting I had an interview in the studio with Howie Shu who's formerly a BMWARE engineer, entrepreneur, sold his company to Zscaler, he's an AI guy and we talked about the SaaS business model and one of the things that's key is if you don't have the data feeding SaaS it's not going to work. So to me, if they could get that data back in to the system quicker with all that regulation that's going to be a game changer and I think they got to start thinking how they can show the customer proof points that's going to be interesting when the customer start adopting it at scale. And as we've also said many times on theCUBE the governance is kind of a mess itself. I mean, Washington doesn't quite know what to do with this and how to regulate it. I mean, how do you think that these technology companies should be working with Washington on this? Well, that's a loaded question. First of all, I think the government is not the bellwether for technology innovation. In fact, I think innovation is stifled by too much regulations, it's got to have a balance there. One of the things that's positive is in the cybersecurity era, you see private public partnerships go on where there's some joint sharing. I think cloud is going to be a catalyst. We're going to have the VPN marketing from Amazon, web services on I'm going to ask them that direct question. This is where the action is. So I think this notion of collaboration the enterprise and cloud players is going to be key because if you look at like just how search engines used to work back in the old days, if it was not encumbered by all this legacy infrastructure in the enterprise, it worked great. The more you add complexity to things, the more you need software. The more you need software, you need horsepower, compute. You need more storage. So all these things are creating a different environment than it was just three years ago. So, you know, can they adjust? Can the industry shape itself out? I think the industry needs to lead here, not the government. What about the idea of Informatica working together with customers and making sure that they are in fact deriving value? Because I mean, I think that's the other thing is that all of these companies know they need to have an AI strategy. They need to be using more machine learning. It's very complicated, as you said. But then there's also this question of am I really going to see a return of investment on this? Well, I think Informatica can do a good job working with cloud architecture and looking at, because you got the again, IoT edge is coming around the corner, they can nail the architecture between on-premises and cloud, that is a great start. The second thing that Informatica can help customers at, and this is a customer challenge is where do you store the data? Because moving data around is very expensive. So this scenario is where you want it all in the cloud. The scenarios you want it all on-premise and the scenarios where you want it on both locations. And then with the edge, you want to move data, I mean compute to where the data is. So data becomes a very critical piece of the overall architecture and whoever can build this operating systems mindset will have a winning formula. And again, being neutral is a critical strategy and the more Informatica can help enterprises be more like consumer companies, the better. If you look at Slack for instance, it's an IPO candidate coming out, very popular, it's just a chat, kind of message board app. What made Slack successful is they built connectors and APIs into all different tools. If Informatica could do that, that would be a winning formula because they want to be data brokering, they want to be data connecting and they want to feed the applications and machine learning data. If they can't get the data to the machine learning and AI, then the AI will not be sufficient and that will be a problem. Well, this is all the things we're going to be talking about for the over these next two days. John, I look forward to it. All right, be good. I'm Rebecca Knight, you are watching theCUBE.