 Hello, welcome to this CUBE conversation here in Palo Alto, California. I'm John Furrier with theCUBE. We had a great conversation around the rise of the cloud and the massive opportunities and challenges around analytics, data, AI, suggestion there. CEO of ThoughtSpot is here with me for a conversation. Great to see you. Welcome back to theCUBE. How are you? I'm well, John. It is so good to be back. I wish that we could do one of those massive setup that you have and do this face to face, but Zoom is not bad. You guys are doing very well. We've been covering you guys, been covering the progress, great technology enabled business. You're on the wave of this cloud analytics. You're seeing, we've seen massive changes and structural changes for the better. It's a tailwind for anyone in the cloud data business. And you also, on the backdrop of all that, the COVID and now the COVID's looking at, coming out of COVID with growth strategies, people are building modern, or modernizing their infrastructure. And data is not just a department. It's everywhere. You guys are in the middle of this. Take us through, what's the update on ThoughtSpot? What are you guys doing? What do you see the market right now? Honestly, Delta variant's coming strong, but we think we'll be out of this soon. Where are we? Look, I think it all starts with the users, like you said. The consumers are demanding more and more from the business they're interacting with. They're no longer happy with being served like I'm going to put you all in a bucket and then deliver services to you. Everyone's like, look at me. I have likes and dislikes that is probably going to be different from someone that you think are similar to me. So unless you get to know me and deliver bespoke services to me, I'm going to go somewhere else. Who does that? And the core, the way you do that is through the data that I'm giving to you. So the worst thing you can do is to take my data and still treat me like an average in numbers. And what's happening with the cloud is that it is now possible. And it wasn't the case. So I grew up in India where newspapers will always have stock market summary on like one full page full of tickers and prices. And the way it used to work is that you wake up in the morning and look at the newspaper. I don't know if you guys have the same thing. And then you call your brokers based on and in place of that. Can you imagine doing that now? I mean, the information is at your fingertip. Harik, can I, Ida is actually going to enter I don't know, Luciana somewhere. What good is that yesterday morning's data this morning's data? If I'm trying to make a decision on whether I should pack my stuff and move away or if I need to, if I'm home depot supply chain manager, I shouldn't figure out what should I be doing for Luciana in the next two days. This is all about the information that's available to you. If you plan to use it and deliver better services for your consumers, cloud makes it possible. You know, it's interesting. You mentioned that the old way things were, it seems so slow, then you got the 15 minute quotes and then that's now real time. Everything has to be real time and clearly there's two major things happening at the same time, which makes it exciting. The business model and the competitive advantages for leaders in business to use data as critical but also on the developer side where apps are being developed. If you don't have the data access the machine learning won't work well. So as machine learning becomes really core to driving AI, this modern analytics cloud product that you guys announced brings to bear kind of two major lifts. The developer app modernization as well as competitive advantage for the companies that need to deploy this. So you guys have announced this modern approach analytics cloud, so to speak. What are some of the challenges that companies are having because you got to, if you hit both of those you're going to provide a lot of value. What are some of the challenges for people who want to do this modern cloud? I think the challenge is basically all inside in the company. If you ask companies why are they failing to modernize they will point to what's inside. It's not outside the technology is there the stack is there, the vendors are there. It is sometimes lack of courage at the leadership level, which is a huge problem. I'll give an example. We have recently announced what we call PotSport everywhere which is our way of looking at how to modernize and bring the data inside that you're looking for to where you are. Because Lord knows we all have enough apps on our octa or our single sign-on. The last thing you need is one more no matter how good it is. They don't want to log into yet another tool whether it's PotSport or not. But the insights that you are talking about needs to be there when you need it. And the difference is the fundamental approach of data analytics was built on embedded model. What we are proposing is what we call data apps. So the difference between data apps and the typical dashboard being embedded into your analytics model is sort of like think of it newspapers, telephones, and the gap in between. So there is newspapers or radio, there is walkie-talkie and telephone. They're all different. And it's newspapers get printed and it comes to you and you read in the morning. You can talk back to it, you can drag and drop, you can change it, right? Walkie-talkies on the other hand, you could have one conversation and then come back to that. Whereas phone, you can have true direction conversation. They're all different. If you think of embedding, it is sort of like the newspaper, the information that you can't talk back. So somebody's embedding something that came out one day, you're going to a board meeting on Wednesday and you look at that and make decisions. That is not enough. In the new world, you just can't do that. It's not about what. A lot of tools can actually answer what. The real magic, the real value for customers are unlocked when you ask three subsequent questions and answer them. And they will come down to, when you hear what, you have to know so what, right? And then what if? And then the last is what next? Imagine you can answer those three questions. Every business person, every time, no matter how powerful the dashboard is, they will always have the next question. What, so what? Okay, the business customers are churning. So what? Is it good? Is it bad? Is it normal? Or the next question is like, now what? What do I do with it? So the ability to take all these three questions, so what and what if and now what? That requires true interactivity. Start with an intent, end with an action. And that is what we are actually proposing with the data apps, which is only possible if you're sitting on top of a snowflake or a red-shaped kind of really powerful and massive cloud data warehouse where the data comes and moves with agility. So how has this cloud data model rewritten the rules of business? Because what you're bringing up is essentially now full interactivity, really getting in, getting questions that are iterating and building on context to each other. But with all this massive cloud data, people are really excited by this. How is it changing business and the rules of business? Yeah, so think about, I mean, topical thing like there is a hurricane about to hit the cost of the United States. It's a moving target. No one knows exactly where it is going to be. There is going to be 15 models from here, 10 models from Europe. That's going to predict which way it's going to take. Every millimeter change in that map is going to have significant consequences for lives and resources and money, right? This is true for every business. What cloud does is, you have your proprietary data. For example, let's say you're a bank and you have proprietary data, you're launching a new product. And the proprietary data goes to 2025, extremely valuable. But what's not proprietary, but what is available to you, which could make that data so much more relevant if you layer them on top, census data. This was a census here, right? The census data is updated. Do you not want that? Vaccination data. We clearly know that purchasing power parity will vary based on vaccinations in county by county, but is that enough? Do you need to have street by street? Is county data enough if you're going to open a startup as a Starbucks? No, you probably want to know much more granular data. You want to know traffic. Is the traffic picking up? Is this usually an office space where people are not coming to office or is it more of a shopping mall where people are still showing? All of these data is out there for you. What cloud is making it possible? Unlike the old era where you know, your data is in SAP Oracle or Teradata in your data center, it's available for you with a matter of click. But ThoughtSport, modern analytics cloud is a simple thing. We are the frontend to bring all of this data and make sense of it. You can sit on top of any cloud data and then interact with complete sort of freedom without compromising on security, compliance, or relevance. And what happens is the analysts, the people who are responsible for bringing the data and then making sure that it is securely delivered, they are no longer doing incremental in a chart updates and dashboard updates. What they're doing is solving business problems. Business people, they're freely interacting and making bigger decisions that actually adds value to their consumers. This is what your customers are looking for, your users are looking for. And if you're not doing it, your competitor will do that. So this is why cloud is not a choice for you. It's not an option for you. It is the only way. And if you fail to take that way, the other way is taking the world out of a cliff. Yeah, that's, I love it. But I want to get to this topic of ThoughtSport anywhere, but I want to just close out on this whole idea of modern cloud scale analytics. What technology under the hood do you guys see that customers should pay attention to with ThoughtSport? And in general, because there's scale there. So is it just machine learning? We hear data lakes, different configurations of that. Machine learning is always thrown around like a buzzword. What new technology capability should every executive buyer, customer look for when it comes to really doing analytics modern in the cloud? Analytics has to be near real time, which means what? Two things, speed at scale. Make sure it's complex. It can deal with complexity. In data, structure data, complexity is a huge problem. Now imagine doing that at scale and then delivering with performance. That means you have to rethink. Tableau grew out of Excel and Worksheets. That is a market leader. It is a $40 billion market with the largest company having only a billion dollars in revenue. This is a massive place where the problems need to be solved differently. So the underlying technology to me are, like I said, these three things. Number one, can it handle the cloud scale? You will have hundreds of billions of rows of data that you brought. But when you talk about social media, sentiment of customers, analysis of traffic and weather pattern, all of this publicly available, valuable data, we are talking trillions of rows of data. So that is scale. Now imagine complexity. So financial sector, for example, that is it's healthcare where some data is visible, some data is not visible, some is public, some is not. Or you have to take credit data and layer it on top of your marketing data. So it becomes more complex. And the last is when you answer, ask a question, can you deliver with absolute confidence that you're giving the right answer with extremely high performance? And to do that, you have to rebuild the entire stack. You cannot take your stack that was built in 1990s and say, now we can do search. So search that is built for these three things with the machine learning and AI essentially helping at every step of the way so that you're not throwing all this inside directly to a human. Throw it to an AI engine and the AI engine curates what is relevant to you, showing it to you. And then based on your interaction with that insight, I improve my own logic so that the next interaction, the next iteration is going to be significantly better. My point is you cannot take a triple M app and then try to act like it is Google Maps. One is built to zoom in and zoom out and learn from you. The other one is built to give you rich information but doesn't talk back. So the stack has to be fundamentally rebuilt for cloud. That's what CloudSpot is doing. I love it. I love the bi-direction. I love the interactivity. This topic of ThoughtSpot everywhere which you mentioned at the beginning of this conversation, you mentioned data apps, which by the way, I love that concept. I'm going to do a drill down on that. I saw data marketplace is coming. It's somewhat working, but I think it's going to get it better. I love that idea of an app and using it as developers. But you also mentioned embedded analytics. You made a comment about that. So I got to ask you, what's the difference between data apps and embedded analytics? Embedded analytics means that, the dashboards that you love, but the one that doesn't talk back to you isn't going to be available inside the app that you built for your other app. So you have a supply chain app that was built by, that's the Accenture, inside that you'll have a Tableau dashboard without logging into Tableau. Great, but whoop you do. What's the big deal? It is the same thing. My point is, like I said, every time a business user sees a chart, the questions are going to come up. The next 10 question is what the value is unearthed. For example, on Yelp, imagine if Yelp is about, I'm hungry, I want to find a restaurant. And it says, go to this barita place. It doesn't work like that. It's not good enough. The reason why Yelp works is because I start with an intent. I'm hungry. Okay, show me all the restaurants. Okay, I haven't had barita for a while. Let me see the photos. Let me read the reviews. Let me see if my friends have eaten. Let me see some menu. Can I walk there? I do all of this, but guess what? Underneath it, there is a rich set of data that probably Yelp have their own secret source and reviews. And then you have Google map powering some of that. But I don't care. All of that is coming together to deliver a seamless experience that satisfies my hunger, which will be very different from if you use the same app at the same place. You might go to an Italian place and I'll go to barita place, right? That is the power of a data app. In business, people are still sitting with this. I'm hungry. I got to eat barita. That's not how it should be. In the new world, a business user should have the freedom to act exactly what the customer is looking for and solve that problem without delay. That means every application should be powered and enriched with the data where you can interact and customize. That is not something that enterprise customers are actually used to. And to do that, you need, like I said, AI and search powering the Google map underneath it. But you need an app, like a Yelp-like app. That's what we deliver. So for example, just last week we delivered a ServiceNow app on Snowflake. It just changes the game. You are thinking about customer cases. You are a large company. You have support coming from Philippines and India. Some places the quality is good. Some places bad. Dashboards are not good enough. Saying that, okay, 17% of our customers are unhappy, but we are good. That's not the world we live in. That is the tyranny of average. 17% are unhappy. You've got to solve for them. Yeah, you mentioned Snowflake and they just had their earnings. Dave Vellante and I were commenting about how some of the analysts got it all wrong. And you bring up a really good point that kind of highlights the real trend. Not so much how many new customers they got, but customers are doing more, right? So what's happening is that you're starting to see with data apps. It doesn't apply softwares in there. It's because it's an application. So the software wrapping around data. This is interesting because people that are using the Snowflakes of the world and ThoughtSpot, your software and your platform, they're doing more with data. So it's not so much I use Snowflake. It's I use Snowflake, now I'm going to do more with it. That's the scale kicking. So this is an opportunity to look at that more equation. How do you talk about it? That's an important point. When you see that, because that's the real thing. It's like, okay, I bought software. It's a service. But what's the more that's happening? What do you see? That is such an important point. You know, even I haven't thought about it that much, John, but you're absolutely right. That is sometimes people think of Snowflake is taking data data. No, yeah. Yes, data data used to store ones and zeros and they're moving it into cloud. That is not the point. Like I said, marketplace as an example. When you are opening it up for example, bringing the entire worst data with one click accessible to you securely, that is something you couldn't do on prep. Number two, you can have, let's say 100 suppliers and all of a sudden you can now take a single copy of data and then make it available to all of them without actually creating multiple copies and control it differently. That's not something without cloud you potentially could do. So things like that are fundamentally different. It is much more than like one plus one equals two. It is one plus one, it's 30, right? Our view is that when you are replatforming like that, you have to think from customer first. What does the customer do? Does the customer care that you went from on-prem to cloud or you went from parallel to snowflake? No, they will care if their lives are better. Are they able to get better services? Are they able to get it faster? That's what it is. So to me, it is very simple. The destiny of an insight or a data information is action. Right? Imagine you're driving a car and if your car updates the gas tank every Monday morning. Imagine how stressful your life will be for the whole week. I have to wait until next Monday morning to figure out what whether I have enough gas or not. That's not the new world. Information is there. You need to have it real time and act on it. If you go through the Tesla, you realize now that, I'm never worried about mileage because it is going to take me to the supercharger because it knows what I need to get to. It knows how long it is going to be, how bad the traffic is. It is synthesizing all of that to give me peace of mind. So this is a great conversation. Information? Action. This is a great conversation because it really kind of brings in kind of what's happening. You see successful companies that are working with cloud scale and data like you're talking about. It's you get in there, you get the data, the data apps and all of a sudden you hit it. You hit the value equation and it's like almost like discovering oil. All of a sudden you have a gusher and then people just see massive increase in value. It's not like the outcome. It's kind of there. You got to kind of get it in there. And this is the scale piece when you see people having strategies to do that. They say, okay, we're going to get in there. We're going to use the data to iterate but also watch the data, learn where's that value. This is that more trend. And there's a successful one that's developing. So I have to ask you when you talk about people and culture that's not the way it used to be. It used to be like, okay, I'm buying an outcome. I deployed some software mechanisms and at the end of the day there's some value there. Maybe I write it off. Maybe I over time charge it in some accounting thing. All changed. The culture and the people in charge now are transforming the management techniques. What do you see as a successful mindset for a customer as they manage through these new paradigms and new success formulas? I see a fork in leadership when it comes to courage. There are people with the spine and there are people without the spine. And the ones with the spine are absolutely killing it. They are unafraid. They are not saying, look, I'm just going to stick with the incumbents that I've known for the last 20 years. Look, I used to drive a Toyota forever. Of course, I love the Toyota. And then after Nutanix IPO, I went to Lexus, still Toyota, because it was reliable either. I'm not a huge car person, it works. But guess what? I knew they were missing battery. And I care about the environment. I don't want to keep pushing hydrocarbons out there. It's not politics. I don't like burning stuff into the earth atmosphere. So when Tesla came out, it's not like I love the quality. I don't personally like Elon Musk, after that Thailand fiasco of cave rescue and all of that. But I can clearly see that Toyota is not going to catch up to Tesla in the next 10 years. And guess what? My loyalty is much more to doing the right thing for my family and to the world. And I switched, this is what business leaders need to know. They can't simply say, oh, well, Tableau does search too. They're not as good as ThoughtSport. So we'll just stick with them because they have done with us. That's what weak leaders do. And customers suffer for that. What I see, like last two weeks ago, when I was in New York, I met with a business leader for one of the largest banks in the world, with 25,000 people reporting to him. The person walks into the room wearing shorts and t-shirts. And was so full of energy and so full of excitement, I thought I'm going to learn from him. And he was asking questions about how we do our business in bear and learning from me. I was humbled. I was floored and I realized that's what a modern business leader looks like. Even if it is one of the largest and oldest banks in the world, that's the kind of people are making big difference. And it doesn't matter how all the company is, how all their data is, they have mainframes or not. I hear this excuses all the time. Oh, we have mainframes. We can't move. We have cobalt going on. And guess what? You keep talking about that. And here, leaders like him are going to transform those companies. And next thing you know, they are some of the most modern companies in the world. Well, certainly they, we know that they don't have any innovation strategy or any kind of R&D or anything going on. They could be caught flat footed in the companies that didn't have that going on, didn't have the spine or the vision to at least try the cloud. Before COVID, when COVID hit, those companies are really either going out of business or they're hurting. The people who were in the cloud really moved their teams into the cloud quicker to take advantage of the environment that they had to. So this became a skill issue. So this is a big deal. This is a big deal and having the right skills. Are people skilled or will AI both be running everything for them? What is your take on that? This is an important question. You can't just say, you got to do more thing or new things and not take away the old things. You know, there's only eight, nine, 10 hours so you can work a day. Analytics, analytics we see is constantly. If your analysts are sitting there and making incremental dashboards and report change every day and backlog is growing four, five, six days and the users are unhappy because you're not getting answers. And then you ask them to go do new things. It's just not going to be enough and you can't hire your way out of it. You have to make sure that if you say that I have 20 analytics product already I don't want 21st, guess what? Sometimes to be five products you need to probably go to 21. You got to do new things to actually take away the gunk of the old. And in that context, the re-skilling starts with unburdening, unburdening of menial task, unburden of routine task. There is nothing more frustrating than making reports and dashboards that people don't even use. And 90% of the time analysts they have amazing experiences completely wasted when they're making incremental change to tableau reports. I kind of believe ThoughtSpot and CellService on top of cloud data takes away all of that without compromising security. And then you invest the experienced people. Business experience is so critical. So don't just go and hire university students and say, okay, they'll go come and quote everything. The experience that they have in knowing what the business is about and what it matters to their users that domain experience and then up level them, re-skill them and then bring fresh energy to challenge that and then make sure there is a culture that allows that to happen. These three things, that's why I said leadership is not just about hiring a vendor, firing another. It's about cultivating a culture and living that value by saying, look, if I'm wrong call me, call me out in public because I want to show you how I deal with conflicts. So this is, I love this thing because when I see these large companies where they're making these massive changes so fast it's inspires you to say, you know what? If they can do it, anyone can do it. But then I also see if the top leadership is not aligned to that, they are just trying to retire without the stock tanking too much. And let me just get through two more years. The entire company suffers. So that's great to chat with you. You've got great energy. Love your business, love the energy, love the focus. It's a new wave you're on. It's a big wave and it's relevant. It's cool and relevant and it's the modern way and people have to have a spine to be successful. It's not for the faint of heart but the rewards are there if you get this right. This is what I love about this new environment. So I got to ask you just to kind of close it out. How would you plug the company for the folks watching that might want to engage with you guys? What's the elevator pitch? What's the positioning? How would you describe Thought Spot in a bumper sticker or in a positioning statement? Take a minute to talk about that. Remember Mark Anderson said that software is eating the world. I think it is now time to update that. Data is eating everything, including software. If you don't have a way to turn data into bespoke action for your customers, guess what? Your customers are going to go somewhere where that's happening, right? You may not be in the data business but a data company is going to take your business. Thought Spot is very simple. You want to be the frontend for all cloud data when it comes to structured because that's what business value. Numbers is where satisfaction and dissatisfaction for users align. It is important to move data to action and Thought Spot is the pioneer in doing that through search and AI. I really think you guys are doing something very powerful looking forward to chatting with you at the upcoming AWS startup showcase. I think data is a developer mindset. It's an app. It's part of everything. It will, everyone's a data company. Everyone is a media company. Data is everything. You guys are on something really big and people got to program it with it. Make experiences, whether it's simple scripts, point and click, that is a new kind of developer out there. You guys are tapping into it. Great stuff. Thank you for coming on. Thank you, John. It's good to talk to you. Okay, this is a CUBE conversation here in Palo Alto, California. We're remote. We're virtual. This is the CUBE virtual. I'm John Furrier, your host. Thanks for watching.