On this episode of The Six Five – On the Road, hosts Daniel Newman and Patrick Moorhead are joined by Cloudera’s Charles Sansbury, CEO and Luke Roquet, Senior Vice President of Marketing, at Cloudera Headquarters, for a discussion on how Cloudera has uniquely enabled their customers to solve problems around data management, helping to guide them in making impactful, transformative, disruptive business decisions with their data.
Their conversation covers:
- What drove the decision behind Charles taking the position as Cloudera’s new CEO, and what he is most focused on delivering for their customers
- The current trends on the horizon driving Cloudera’s growth
- We discuss some of the challenges facing enterprises today in managing data across multiple environments, and where Cloudera is investing in order to meet those challenges
- What Cloudera is doing to ensure they’re delivering on the opportunities of AI and Machine Learning
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Patrick Moorhead: Hi, this is Pat Moorhead and The Six Five is live on the road at Cloudera Headquarters in sunny Santa Clara. Dan, how are you my friend?
Daniel Newman: It’s great to be here.
Patrick Moorhead: It is. It is. Man, I love Six Five remote. I love Six Five at events, but we know I love the most. I do love a smaller, more intimate scenario and here we are, Cloudera Headquarters.
Daniel Newman: Absolutely, and I love having the opportunity to talk to the business leaders, especially when we get to break some of the newest CEOs here in the valley, have a conversation with them about something important like big data, AI, future of the enterprise.
Patrick Moorhead: It’s funny, I started my career a long time ago.
Daniel Newman: It was a long time ago.
Patrick Moorhead: A few years before you did. I think you might’ve been in high school maybe before.
Daniel Newman: That was a long time ago.
Patrick Moorhead: But data has always fundamentally been the basis for anything great that comes out of the other end for businesses and even governments. And it is great to be here and I do want to introduce Charles, how are you?
Charles Sansbury: Good. How are you doing?
Patrick Moorhead: Good to see you, Luke.
Luke Roquet: Great to see you guys again.
Patrick Moorhead: Six Five veteran. We’ve seen you at Evolve, we’ve seen you remote. It’s great to see you again, but Charles, new CEO, super happy to see you.
Charles Sansbury: Thank you. It’s great to be here. Although I’m a little concerned. I feel like he might’ve been in middle school when I started my career, so I’m wrestling with that.
Patrick Moorhead: It’s okay, we can both go to therapy and talk about it.
Daniel Newman: I have a feeling this might be a conversation we’re going to have to have later. But Charles, it is great to have you here. We’ve been following Cloudera very closely for a long time and the company’s been doing a lot of very interesting things and it finds itself at this really important inflection. It’s important moment with data and we’ll talk more about that throughout, but let’s start with the big question. You’ve got a pretty extensive pedigree, you’ve done some great work in the past, Cloudera came knocking on your door. What drove the decision and what’s your big mandate here now that you’ve joined as CEO of Cloudera?
Charles Sansbury: Dan, I appreciate the question. The challenge here is… Or the opportunity is growth. If you think about Cloudera, one of the foundational companies in Big Data, the coming together of Hortonworks and Cloudera created the current company. There was a big project, tons of R&D, to bring the two platforms together. We’ve now introduced and brought to market CDP, which is really a combination of the best of both worlds of Cloudera and Hortonworks. The vast majority of our customers are now on that platform. So now the focus is on adding value, adding technology so we can really start to deliver on some of the opportunities that are created by increased focus on AI and ML, and big hunks of data to train ML models, but we had to get to this foundational platform space first. So when the investors in the company came to me and said, “Are you interested in joining Cloudera?”
The criteria I thought about were a company that makes a difference in markets that matter with some industry tailwinds, the aforementioned AI and ML trends. And really when you look at that opportunity set, I was very excited about joining and it’s an honor to be involved in the company at this stage. This is kind of a point of inflection, right? Looking back, we’ve laid a foundation for a lot of growth, and going forward, we have, I think, some differentiated technology, point number one. But point number two, I think we also have a tailwind at our back. I’m just hopeful we can do the right work to leverage and maximize that opportunity.
Patrick Moorhead: It’s incredible. If I look at the history of data and what gets done at companies, essentially it’s fractalizing. It’s everywhere. There were the days where at a monolithic all your data… Actually your data was part of the application, and then it became a little bit disconnected, but it was always in the same box. And the fractal of the data is just this amazing thing to see and it just keeps happening. I am curious though, Luke, you talk to customers every day, what are they saying right now? I’m going to use very large areas here, data and AI. What are they telling you right now?
Luke Roquet: It’s just such an interesting moment because not only do we have an inflection in the company’s history, but there’s a huge inflection in the market. And what I would say is the third huge hype wave of the last 15 years. You went back to 2010, every company on planet Earth was saying, “We have to do big data.” A CEO would read a Harvard Business Review that if you’re not doing big data, you’re going to go out of business. So I was at Hortonworks at the time, and every company you walked into, they would say, “We need to do big data.” And I’d say, “Well, what do you want to do?” “I don’t know. We just have to do it or we’re going to be out of business.” Then you had a similar wave happened with cloud where every company was like, “We have to go all in the cloud and we’re going to be irrelevant.” And now you see the same thing with AI, and specifically generative AI.
The conversations I have with customers are very similar, they repeat themselves over and over again, which is, customers are understanding that they have to do generative AI, but they don’t know what to do, how to do it. And there’s been this huge hype for probably nine months now, but very little has been delivered. And the problem is because most companies don’t have a great data strategy and without the data you don’t have AI.
Daniel Newman: Isn’t it interesting though, what they’re all saying isn’t very different than 2010? They’re still saying the whole thing about data management, data layer, Luke. The AI didn’t change any of the fact that if you didn’t have your data right, you can’t do all the AI stuff. And it was the same thing with the first wave of big data.
Luke Roquet: That’s exactly right. And data is the constant. We have generational leap forwards in processing technologies, analytic technologies, AI, ML, but what doesn’t change is the data layer. And so that’s what we’ve been focusing on for the last 15 years, is how do we build a sound secure govern managed data layer that enables the hot AI and ML tools du jour, but then also what’s going to come 18 months from now.
Patrick Moorhead: You guys really did… I mean, you nailed it there. Cloudera did start big data. And here we are, we’re suddenly into this generative AI area. I’m curious, what trends are you watching right now, and I’ll give this one to you, Charles. What trends are you watching out there that take us to this next generation, dare I say, Cloudera 2.0, Cloudera 3.0?
Charles Sansbury: I think a couple of big things, but first and foremost, the trend toward making AI part of your business, you can make better business decisions. It used to be a very small number of very large companies could afford to make those investments in what we just called big data. That bar is coming down, so it might’ve been the two or 3000 biggest companies in the world, now it’s the 5,000 biggest. And so that trend toward thinking about AI, not as an esoteric research project, but really what can I do to harness my data to help me make better business decisions? I think that’s critical step one. And then two, something you said earlier about the idea of data being resonant everywhere, going back to the days of we had embedded in databases back in the day.
Patrick Moorhead: Exactly.
Charles Sansbury: Now, data exists in on-prem structures, in private clouds, increasingly moving to public clouds. And the challenge, I think, that a large global corporation has is how to manage data across those multiple environments. Put control around it so you can use it to go and train big models to go and bring the power of multiple data sources together. Think about a bank. A bank has 17 different data sources, US based, non-US based, on-prem, cloud. What we’re trying to do right now, what is the next big trend, is to create ability to manage workloads across that hybrid environment. What that means is we’re spending time, and effort, and money on building out a much more usable, much more accessible hybrid control layer, which is a huge step in terms of the usability of the technology from a business user’s perspective.
Patrick Moorhead: The single pane of glass to be able to manage all that data gets so important as you move forward. And listen, just because I called the hybrid multi-cloud 10 years ago… We analysts, we do a little victory laps every once in a while.
Charles Sansbury: Looks like you’re going to be right.
Patrick Moorhead: I know I’m going to be right. And for me it wasn’t too far, because quite frankly, it’s what customers want. They don’t want to be told what to do and where to do it. And typically data gravitates to… The data in the compute go to the best place it possibly can to be the most efficient and useful. As long as you can manage that data and you can manage those systems as far out as you can, everything works. And I really do appreciate the investments that the company has made into CDP that basically says, “On-prem Cloud, Azure, Google Cloud, AWS, it’s there.
Daniel Newman: We’ll talk more about investments in a minute, by the way, because I want to hit you up about that. But beforehand, I’ve actually judged your data awards multiple years now, and so one of the things I always found to be very compelling about having spent the time to read your customers long… I mean, this is a process. I read these things. Some of these… When you have some time, Charles, in your new role, go through some of these because it was fascinating for me to hear from the customers how they’ve approached these problems and how Cloudera uniquely enabled the company to solve those problems. So Luke, as you’re listening to Charles talk about his vision and the trends, I kept thinking about some of these global banks in Malaysia where I would read this and it seems like they’re really dealing with these exact things.
Luke Roquet: And like Pat said, it’s efficient and useful place for the data to run, but also it’s economical. OCBC Bank’s a great example, huge multinational bank based in Singapore. They just spoke at one of our events about a month ago. It was one of the most compelling presentations I’ve seen from anyone on AI. They today make 4 million decisions a day powered by AI, driven by AI. That’s before generative AI. They see generative AI then as a leap forward in what they can do with enterprise AI. But for them, they have to look at where should they run these workloads. Obviously ChatGPT, OpenAI open a lot of eyes, open a lot of possibilities, and so they’ve done a lot of experimentation, development in the cloud where they have lots of resources and availability, but also a lot of costs.
But they experiment there. They play with things, they test out ideas and hypotheses. Then once they want to productionalize it and get into a cost-effective constraint, they run those machine learning workloads on premises using open source LLMs. But the constant, again, back to my original point is the data in both cases, whether it’s OpenAI in the cloud or it’s open source LLMs on-premises, the data is in Cloudera. It’s secured, managed, governed centrally by Cloudera and then served up to whatever AI engine they want to use it’s most economical and most beneficial to their business. But I think that just layering on that too, this open Lakehouse concept has been super interesting to watch. I know you guys have been tracking that for a while, but-
Patrick Moorhead: You were one of the first to jump on it, I gave you some credit there.
Luke Roquet: Once we announced we had an open data lakehouse, the next week I saw five other vendors in open data lakehouse, it’s interesting.
Patrick Moorhead: Surprise.
Luke Roquet: But what’s happened, again back to economics, is that you’ve got people wanting to take advantage of all of these really powerful analytic tools and applications today. And what’s happened is data just gets replicated and moved around to all these different places and you have a data governance nightmare and a cost nightmare. So I’m talking to customers, in fact, just last week I was at the largest healthcare company in the world talking about their data architectures and platforms, and they stream in real time all their patient data, it gets streamed, it gets put into a cloud data warehouse. But then when they want to do machine learning, they have to then export it and import it into a machine learning tool. We’re working a lot with customers right now saying, how do you manage all your data wherever it lies, manage it once and centrally, store it in an open interoperable format, and then use any tooling of your choice on top of that to make business insights and business power?
Daniel Newman: It’s very complex and I love that you mentioned the compliance and governance around data because that’s probably one of the unsung complications that every enterprise. Your company has historically taken the largest customers in the world. I believe you have some monumental number in terms of the amount of data under management at Cloudera.
Charles Sansbury: 25 exabytes, so probably as much as anyone has.
Patrick Moorhead: That’s right up there with the hyperscalers.
Charles Sansbury: Yeah.
Daniel Newman: And that’s a massive undertaking, but dealing with the compliance, the PII data, sovereignty across borders is complex and something you’ve really focused on. But in order to stay competitive and in this new role, Charles, you’re going to be under pressure to invest. The market is going to expect Cloudera to keep up. Of course, you also partner and compete with the biggest hyperscalers on the planet, but you have decades of experience and knowledge. I’m guessing though, the world’s going to want to hear, what are you going to invest in, what are the things you’re going to focus on now to get that growth?
Charles Sansbury: See, the good news is we live in a nice neighborhood. The bad news is the cost of upkeep is very high. And just something that Luke said I wanted to add on to, and it’s also an area of investment, but the idea that we’ve seen customers early on, whether it’s business use case or information governance use case. So we’re learning a lot about how the biggest customers are tackling their biggest challenges. And I think there’s an opportunity there. But going back to your broader point, the focus is around growth and growth is go-to-market initiatives, but also new product initiatives. So we’re launching investments around a couple of key areas that we think are going to start to pay dividends, probably not in the next six months, but in the next nine to 12 months around improving our capabilities around AI and helping customers manage their big hunks of data, serving AI, around building or accelerating the build of that single pane of glass that we talked about in terms of the requirements around managing hybrid workloads.
And then lastly, I think a lot of investments around our public cloud capability, whether that’s technology or go-to-market initiatives. And then finally, you’ll start to see Cloudera actually have a broader public presence in terms of seeing and hearing our name in places you haven’t heard it previously. And all those things are big initiatives for us. And one of the things that the board wanted to make sure that we did here is basically to realize the opportunity that’s in front of the company. And a big part of that is making the right investments right now.
Patrick Moorhead: You talked a little bit about AI and multi-cloud, but I’m curious, obviously you’re not just coming up with the roadmap on your own, the two of you’re collaborating just a little bit on this, but-
Charles Sansbury: They don’t let me in the roadmap discussions in the early stages. I get to see the charts when they’re done.
Daniel Newman: Observer.
Patrick Moorhead: But I’m curious-
Charles Sansbury: Advice and consent.
Patrick Moorhead: …Do you specifically react to some of the specific investments that he’s talking to? Obviously, you got these from customers or you’ve seen this movie before, you know them so well, what they’re going to be asking for, you have specifics on that?
Luke Roquet: We have to make it easier for customers to build generative AI applications. The thing that we all love about generative AI is it’s so easy. I can go to ChatGPT, I can ask questions, it’s fast, I get answers. But when an enterprise wants to go implement generative AI, there’s a lot of questions and considerations they have to take in. And so that’s what we need to work on. Not every customer is like, “Go see BC Bank where they have a huge slew of engineers that they can go and invest and build these apps. We need to help customers build apps easier.
Patrick Moorhead: Correct me if I’m wrong, I am thinking that generative AI is a lot different than machine learning and deep learning from a data perspective, if nothing else. For the first time, you’re combining different types of data in a very big way, and I’m not talking about just doing a customer service chatbot that looks at PDFs that you use from what the engineers put there as notes and how to use this. I’m talking about connecting ERP to finance, to CRM, to marketing, manufacturing, all of this. Doesn’t that just raise the game?
Luke Roquet: It raises a lot of concerns for major enterprises, especially highly regulated enterprises. I recently did a CIO roundtable, and I was surprised to hear how many customers are saying they need to do generative AI on premises precisely because of those security concerns. In fact, federal government entity was saying that they have executive orders that require them to do AI in a private cloud environment because of ethical AI. So they need to constrain all the data that you’re talking about, the potentials of generative AI also provide a lot of risk as well. So unlimited possibilities, unlimited risk, that’s what we need to help customers manage.
Daniel Newman: But so much risk, so much complexity creates so much opportunity.
Luke Roquet: So much opportunity.
Daniel Newman: And so for Cloudera, at least my take as an analyst is, this story isn’t over yet. And the complexities that enterprises are facing to try to address the opportunity with data means they need very capable partners. They have to be constantly able to deal with the shifting and changing of business models, but at the same time, the experience matters. And that’s been one of the reasons, Charles, why I really do think Cloudera is in a very good position, is people want to discount at times, “The new cloud player on the block, born on…” But that’s not how the enterprise is functioning. For all the people out there that are maybe hearing from you, this might be the first time they’re hearing from you, how do you rile up the troops? How do you get the Cloudera customers, the Cloudera employees fired up for what should be the next decade of really exciting growth?
Charles Sansbury: Again, looking forward versus looking back, we have so much opportunity delivering CDP, getting it to where it’s an amazingly capable platform for data management is a starting point for us, not an endpoint. You look at how you can add capabilities onto that platform, the problems we’re solving for customers right now, a lot of the customers are solving those problems, as Luke said, with the expertise of their own internal folks. Productizing or using abstractable case studies or best practices opens up an aperture of market opportunity that we’ve never seen before as a company. And so I think what’s most exciting to me is being here very early in what I think is a next generation wave of opportunity in a company that has a startup-like opportunity, but with a foundation of our customers are the leaders in every industry. We’ve got more than a billion dollars of revenue, we have global scale, I think that’s a pretty rare opportunity to find in the software space these days. So we are very excited about it.
Luke Roquet: And I think it’s exciting. Again, having someone who’s here in the early days of big data, helping consultatively guide customers to make impactful, transformative, disruptive business decisions with their data is what really fueled me and drove me in the early days of Hortonworks. And we’re doing the same thing again right now with generative AI, which is extremely exciting.
Charles Sansbury: Those of us have been in software for a long time, we forget that the software actually exists so our customers run their businesses better, and we are really well positioned to go deliver that.
Daniel Newman: I think that’s a great way to end it here. Luke, Charles, thanks so much for joining the Six Five.
Charles Sansbury: Thank you guys very much.
Patrick Moorhead: Thanks.
Luke Roquet: Pleasure.
Daniel Newman: All right, everyone hit that subscribe button. Join Patrick and I for all of the episodes here on The Six Five. We are on the road here in Santa Clara at beautiful Cloudera Headquarters. We’ve got to go for now. Thanks for tuning in.