(upbeat music) >> Announcer: Live, from Las Vegas, It's theCube! Covering Informatica World 2018, brought to you by Informatica. >> Welcome back everyone. It's theCube's live coverage of Informatica World 2018, here in Las Vegas. I'm John Furrier, your host and analyst, with Peter Burris, co-host and analyst at Wikibon and still going on theCube. Our next two guests is Gitesh Ghai, C Vice President, General Manager of Data Quality Security and Governance for Informatica, and Smail Haddad who is the Senior IT Director of Data Governance and Data Delivery Architecture at Toyota, company wide, Great to have you on Gitesh. Great to have you on Smail. So we were just talking before coming on camera, before we went on live about the massive role that you have at Toyota with data. You are looking at everything now. You're touching all the data. But it wasn't always like that. >> Smail: Yeah it wasn't always like that... >> Tell us about your journey and your role at Toyota. >> Yeah thank you. So Toyota, again, started business in North America. People know, maybe not, 65 years ago. And we started as a little dealership in North Hollywood. Bringing these Japanese cars. So we grew from that single dealership in North Hollywood to this big company we are today, with almost 25 plants around North America, Canada, US, and Mexico. And almost 2,600 dealerships across nationwide. So what that came with, it came with a big responsibility, in terms of understanding our customer base and trying to be more closer to what the customer needs. So our supply chains, where we produce the vehicles, it really was mostly a push supply chain, where we build a car and we push it to the customer to buy it. The model works very well, all the way to 2008. Where things change and we all understand what happened back in the financial meltdown and the crisis, that was a worldwide crisis. And that was a turning point for Toyota because we start seeing a shift in the demand. The customers becoming more savvy. Demanding for example, more electrical cars, less gas guzzlers vehicles and so on. The marketing department, which was a different company back then, understood that but the production companies, which was producing the vehicles, they didn't have that knowledge. So the journey to bring these two together became really critical after that 2008 crisis. Because what it forced us to do was the vehicles were being produced everyday, the dealers were not able to sell, and we were just stuck in vehicles around the lot. So why the digital disruption was so key for us, is the data was always there. Data always told us the truth. And that's what the facts are. Where we started looking at, back after that, is hey, if we look at the data and the data always predicted that the shift in the market will happen that way. And we should've have throttled down maybe, our production system better. Why we didn't do it that way? We were not looking at the data. Data was available. So what we undertook, under Toyota IS, we said, "Can we bring all this data across all these silos, "into one place?" So we build our big data solution, where the data is coming from various departments and various business lines. And it's being blended together and correlated. What that gives us is really that 360 view of our business, which we were missing. 'Cause we were looking at the business in silo, in pieces. And with that explosion of data, that we were gathering, obviously that brings a lot of questions about where this data, how good it is, if I'm going to make decisions on it, can I trust it? All that was a good takeaway into the business I'm in, which is the Data Governance. It's basically how can we govern this data that we are collecting on a daily basis today? And so my department is leading basically, the North American Governance and Quality across all the business line in North America. So as we are gathering these data points everyday, on a daily basis, even today we are gathering. What made it even, made it go even further in terms of volume, is we started capturing data coming from the cost, on a real time basis. So this is not just sales data where we capture the experience, the sales, and configuration of the vehicles on a daily basis... >> John: That's a lot of data coming in. >> A lot of it, a lot of it. So the volume exploded. With that, the responsibility to put a solution, where people can go quickly, find the right data. So basically, the time to data became so critical. How can we shorten that time to find the right data you want? And understand it, and trust it, and use it? >> John: So last... >> Sorry John, the Toyota story that you're telling us is especially interesting 'cause Toyota is legendary for empirical based management, lean manufacturing, so you have plants and marketing organizations, and sales organizations who, because of the Toyota way, have grown up on the role that data needs to play in their function. And what you're doing is you're saying, "That was great. "But we had to take it to a next level "and organize our data differently so we could look at it "across the entire company." >> Across the entire company. So absolutely, there are four, basically, goals that Toyota is trying to achieve today. One is understanding our customer in a more personalized way. Understand today's demand and hopefully predict tomorrow's demand. The second important pillar, empower our employees and our team members. By the way, Toyota, we call employees team members. And the third one is optimize our operations. And the fourth is transform our product. In order to achieve all these four goals, data is at the middle of all this. Why it's so important, we understand that today, in this day and age of digital disruption. And by the way, the automotive industry is being disrupted. Not our competition right now, Toyota, is no more the GM, and the Ford, the traditional automotive companies. But our new competition is all the technology companies, Google, Apple, Amazon. And you might have heard the news. Everyday, how they are disrupting these segments where you hear about autonomous driving cars and everybody's jumping on it. And behind all that, taking just the autonomous driving cars. The amount of data behind these so you can make the vehicle drive itself and take you from point a to point b in a safe manner and avoid all the road hazards. That needs a huge amount of data that's behind it, and fuels that. We're able to make huge stride. The new story of Data Governance at Toyota, is really, how we can enable that and not being just about compliance and risk management, which is kind of understood, that's part of the job. But we make that seamless. We wanted our business unit to focus more on the core business and goals, versus worrying about, "Am I in compliance, do I need to do this or that?" Try to seize the opportunities and put Toyota in a competitive way so they can compete with all these new disrupters like I said, Google, and the, the Apple of the world. Because what they have in common, those companies, >> John: They're data companies. >> Exactly. Data companies, technology. They understand how to use data. They understand how to analyze data. This is where traditional automotive companies like Toyota, and GM, and Ford, are basically bound to learn about that. >> But Waymo is not a car manufacturer, Uber is not a car manufacturer, they're companies that are providing a transportation service. And the only way that Toyota could provide a transportation service, is if you started organizing your data differently, in service to the idea of providing consumers a better, and businesses, with better transportation services. Whether you call it personal. I don't want to be the typical analyst that kind of goes off and starts renaming things. But that's fundamentally what you're trying to do. Is you're saying, "Our customers are mainly focused "on getting from point a to point b safely. "Let's make sure that we have products and services "that help them get there. "Perhaps through a lot of intermediaries along the way." But is that kind of how you're organizing things? >> Absolutely, so in order to achieve that goal. We wanted to bring the silos. Like I said, the data was always there but it was always built in silos, stored in silos. What we did in the next, last few years, we started breaking all the silos because we started looking at the data as an enterprise assets and no more as just a departmental assets or as a tool to get to a goal. It became the strategic assets for the company. And in order to achieve that, was to really break the silos. Bring it together so we can see across and understand how are business is operating. And hopefully, put the company in a competitive advantage to see the future coming to. >> It must be really frustrating to know that the data was there the whole time. And you're kind of kicking yourself. What did you do? I mean, you brought Informatica in. What's the Informatica connection, Gitesh? Get a word in, come on. With the Informatica connection, these guys. Are you the core supplier? Do you guys, the connective tissue between Toyota's groups? >> It's all about the data, right? It's all about the data. Informatica's role in all of this, it's a great story. Toyota's, Smail's story, is a great story. What Informatica brought to bear for Toyota, it's actually the promise of big data. The promise of big data is bringing together data that hasn't been analyzed together in a new context before. So breaking down these silos and bringing together the data. What's interesting is when you bring it together, you create a data lake. But there's a very big difference between a data lake and a data swamp. Which is why naturally, governance, quality, trustworthiness became a focus area of bringing all of this data together. >> Well last year, talking about data swamp and data lake as our core theme. This year governance and enterprise catalog is a bigger story because you guys easily could've been swamped out because of all this new data coming in, whether it's car telemetry or new data. 'Cause if you had set the table for your intercompany connective tissue, if you will, then you're like, "Oh, hey we're done, wait a minute." >> But Toyota was applying data to the work of manufacturing, to the work of marketing cars. And now you're trying to apply data to the work of providing better transportation. And the only way to think that through is to see how all this data can be reorganized and brought together. And at the same time, you can still, then turn that data around and still apply it for the work of manufacturing, the work of marketing, and the work of selling. >> Gitesh: Absolutely. >> Also I'd add, to be competitive in a new market, they are going to use their, leverage their assets. Not only data but their physical assets. To compete at a new level, a new playing field. >> Smail: Absolutely. >> With data at the center. >> And I think you said it earlier, you have to bring this data together in the lake. But you need an organized view of all the data that's out there, which starts with our data catalog. So the data catalog gives you a sense of what data do you want to bring in the lake and what data, frankly, is noise, doesn't matter? >> Whole 'nother level of operations, whole 'nother level of intelligence. Competitive advantage, competitive strategy. >> Peter: What a job. >> We're data geeks, geeking out here. Great story, I'd like to do a follow up. I think that this is a real big story of not only of digital transformation, digital evolution, digital disruption, digital business, great story... >> You used to be able to do this job in Southern California. >> Yes, absolutely. >> Thanks for bringing Toyota to the table. Thanks for coming on. >> My pleasure. Thank you for having me on. >> The beginning of a journey that's going to continue it's not ending anytime soon. Toyota company, really bringing data into the center of the action. Of course, we're in the center of the action as theCube, bringing you the data from Informatica World, right here, on theCube. More coverage after this short break. I'm John Furrier, Peter Burris. Stay with us, we'll be right back. (upbeat music)