 Hi everyone. Thanks so much for joining us today for this session. My name is Brian Howell. I'm a technical architect on the sales engineering team at ThoughtSpot. I've been at ThoughtSpot for about half a year now, but I've actually been doing embedded analytics within the modern BI market for more than eight years. And with me today is the she-showroom. He's the distinguished engineer who runs the engineering side of the ThoughtSpot everywhere product. And that's what we call our offering here in the embedded analytics market. But what we thought for this session today would be really useful people for everyone, is to think over the checklist or set of decisions that people go through when deciding whether to buy something in the market to fulfill that need for their embedded analytics or to try and build the stuff themselves. More than anything else, this is the biggest decision we see people facing. And there's a lot to it and we want to bring our expertise so that you're making the right decision when you go about this. Now, you may be wondering who we are. If you don't know much about ThoughtSpot, we are a modern BI and analytics vendor, but we approach it from a much different perspective than most of the other products in the market. If you see over on the side where it says technology, search and AI. The primary interface, the thing that's really special about ThoughtSpot and very different from everything else, is that we have taken all of the advances that have been made in search, things that you might be used to from Google or Amazon or Yelp, and made that accessible for data. So you can search against your data and find answers very quickly in a way that feels natural. And that expands the set of people who can use business intelligence. No matter how much we've added to everything from kind of the days of Excel, most things in the market have been building a better version of an analyst tool, an analyst who's already familiar with data analytics principles. Search in the way that ThoughtSpot does it combines AI, all the learnings that we can do by watching how people use things and actually look at their own data and create an experience where there's a natural flow that the people who know what they're trying to answer are able to search and quickly find those answers. These kind of slides right just over a few who we are where we have plenty of enterprise customers. We're starting to expand down to the mid-marketing commercial. We've been noted many different times by Gartner and other folks throughout the industry and we're partnered with all of the cloud data warehouses, all of the public clouds to provide the kind of fast data analytics underlying the service that ThoughtSpot provides. Now just to clarify a little bit more on search, I started to describe it. Here's a picture of what that might actually look like, what's different about ThoughtSpot. We combine indexing, which is knowing all of the values that people might be searching so that we can do instantaneous listings as people type things in. There's sets of keywords, but there's also a whole level of data modeling underneath there that translates the expectations and the selections and what's been made in the search into complex analytic queries. Those run very fast against the modern cloud data warehouses and of course taken into consideration security governance and all the other parts. It's a BI platform built for easy answering of your questions. The principle of that and the success that we've seen within enterprises with a whole different sets of people being able to actually get into their data and understand it by using that search interface has led us to see that there's a whole other market out there for what we're calling interactive data apps. But you may think of this as embedded analytics. People aren't just doing reports, looking at them, doing more reports. What they actually want to do is to take action or to monetize their data or to present their data out to people who have never used it before, but it can assist them in making their offering. To that extent, we have a new offering that we call ThoughtSpot Everywhere that's specifically designed to help integrate the ThoughtSpot search-based analytics into other applications. Whether that's a purpose built data app monetizing data that hasn't been shown before or replacing the kind of traditional reporting that has to be built out by developers, all of those things kind of fall under the aspects of what we consider an interactive data app. That word interactive is very important to us because what we found with ThoughtSpot is because the search interface is something that people can understand and learn very quickly. They continue to interact with the data and do much more with it than they do in a traditional reporting or even a traditional modern BI solution. We started this whole thing with the question, should you build or buy? Obviously, we're in here, we have a product that we're selling, but not everyone should buy our product. Sometimes, you should build. Other times, you get into the whole thing and you realize, man, we're spending all of our time working on these features that everyone else has already worked out because there's a whole domain of problems that BI systems are designed to help you with. I'm going to pass it over to Ashish and he's going to talk you through as a developer all the considerations that you would go through and all the ways that we've tried to make that easier in the ThoughtSpot ever platform. Thank you, Brian. So building a data app and more importantly, capturing the insights from the data in those apps is difficult. As developers, we are familiar with the latest programming tools, but there are a lot of other considerations when working with data to build the most elegant and interactive experience for our users. Considerations that include managing your connection to a data warehouse, integrating the latest chart libraries, integrating dashboards that are created using difficult to use BI tools, building triggers in the application to drive actions and business workflows, and a lot more. So if I were to integrate analytics into Maya, I would evaluate and pick the best analytics platform that fits my needs, integrate and ship. Not only do I get to market faster with this, I do not need to spend resources to maintain my offering. The best software teams in the world are the ones that prioritize their resources. They focus on what they do best and leverage existing solutions for everything else. Now, how do I choose the best tool? It should for sure support core analytics, but at the same time, it should be easy to integrate with your own system, like your own application framework or your own database. It must be extendable to hook into your common workflows. Above all, it should provide your developers with capabilities which help them create the most engaging experience possible for your users. Introducing ThoughtSpot Everywhere. ThoughtSpot Everywhere provides everything you need to successfully build your own data. We have an SDK which enables you to embed the core ThoughtSpot components. Our APIs allow you to extend and customize the platform by enabling automation of your business workflows. It allows you to use ThoughtSpot's powerful analytics platform like it was your own. There are three steps to building a modern data app with ThoughtSpot Everywhere. Connect to your data and model using the ThoughtSpot's modeling interface. Create visualizations using the intuitive search experience and then embed those visualizations using the SDK. You could even embed search, providing your users with a more self-service system. I will now hand over back to Brian to take you through how this can be achieved in ThoughtSpot with the demo. Great. Thanks, Ashish. One moment here and I'll get the demo itself loaded up. As Ashish was talking about, all of these aspects of building or whether you want to build or buy, the real thing to consider is do I need a system? Do I have a single project that's something that's going to be done once and really I just need to add a start to something? You don't need a BI stack for that. You might use one if you're familiar with that stack and you like what it does and you want to integrate it. That's certainly a way you might move into using a BI stack for something that's a little bit simpler. But if you are trying to truly provide complete interactivity, then having something like ThoughtSpot or any of the other systems that are available really can absolutely do something totally different than the kind of things you can just build on your own. Or you could spend all your time trying to match up to the capabilities we're talking about. I'm showing an example here of a system. This is something that our teams here within ThoughtSpot built, but this is not white-labeled ThoughtSpot. It's one application, the data application with an analytics component that is powered by ThoughtSpot using a ThoughtSpot everywhere technologies. Within this system, this aspect here is ThoughtSpot fitting right within the overall look and feel, taking advantage of ThoughtSpot's responsive design, modern UI, and all the things that make it a great platform for someone to choose to do things, things like filter UI and all the other capabilities you would expect out of a BI platform built right in there. What's very different about ThoughtSpot though is because of the underlying search technology in each of this, every bit of these components can turn into a further exploration even for what you would consider a basic type user. Whether it's something like drill down into any field because the data modeling allows for going any direction to any granularity as long as it's in the data or going to what we call an explore functionality, expanding out the one component into a larger view and then taking advantage of AI ML learning that we have about what the users have done on the system. Maybe we want to filter this down by just a particular region but that suggestion is being powered by usage based ranking and other aspects of the search to know which thing would be most common. You don't have to go and build that into your system. It's just part of what you're getting there into even a full edit giving a full free form version into the search capabilities that we're talking about. And the search bar up here being dynamic and something that people once they've seen it realize, hey, this is the kind of thing I use all the time. Maybe they want to do analysis on a different set of things entirely. The full dynamic capabilities of the system then available for them to switch the views, take a look at this in a way that really brings analytics into their experience. Another aspect of ThoughtSpot everywhere is that any component of it that we call things pinning here when you take a given visualization, put it on your own pinboard, which is the ThoughtSpot version of a dashboard. You can make that available to users so they can custom build their own set of views right out of the components that are there or the ones that they've customized in these searches that they've done for themselves. And all of that, which is some of the power that's built into the ThoughtSpot platform is just available in an interface that's completely embeddable within the application. Now, this can look take several other forms, right? That's that wider visualization set being embedded as a pinboard. You can also have pre-saved searches, things that you know that people want to see locked down so that the users can't override them but still available in free form for them to expand using the kind of things, whether it's a natural language type phrase, filtering their data set down or adding a different field or changing the type of visualizations entirely. All of those things can be made as a self-service feature in a way that would be rather difficult to build. You might have a chart picker or something like that, but to really create the kind of search and guided experience that this does, if you had built it, right, you would be spending your time doing what ThoughtSpot's core business is and we've spent a lot of time with a lot of very smart people building all of this out. And of course you can even embed the search directly as a basic version, I should not say a basic version, a total free form version with the data sources that you want the users to go. And so we see people using this as different levels of complexity to solve the different needs of their customers. Some people may need a pre-built content or some pre-built content they'd like to resort into an order they like, other people are begging, let me please do the analysis that I need. Or maybe it's your team begging, please stop making me build custom analysis for each of these customers. We need a way to get out of that and let them have those capabilities to themselves. All of those are totally valid use cases that a system like ThoughtSpot everywhere can handle for you. We do as well have APIs underlying all of this, so if you need custom visualizations or just need to bring the data out that you've made quickly through the searches, we do have ways to bring all that as JSON based data and some other types of format, types of exports. This is a final view, but there's underlying this a whole set of capabilities. I'll get signed in real quick on this one to show you how we facilitate this stuff being set up so quickly. I signed in the front page here and this is the, if you haven't seen ThoughtSpot, there is a whole ThoughtSpot Enterprise application designed for people who are going through the application itself. And if you love the way this part looks, you can embed this within another application, get started very quickly. But what we've custom built out for ThoughtSpot everywhere is a developer portal that includes guides to both the visual embed SDK, the JavaScript component, and the REST API and playgrounds as we call them that lets you embed and quickly generate the JavaScript code necessary to do this kind of embedding. So if you have a particular pin board on your system, it's as quick as selecting these options. You get the code necessary and you can see what those components are and exactly how that would embed within your application. You can take this code, drop it right in, and have things embedded within your overall platform. And we expect over time that even the REST API components will have a similar playground functionality, making it incredibly fast to go from building something within the ThoughtSpot platform to making it available. One last capability I do want to point out here and something else that really is part of a platform is unique is the custom actions capability that we've turned on. This allows you to take what has been selected within ThoughtSpot and add certain menu actions, sending those data packages of whatever was in the visualization to some other code within your platform. And so this lets you tie in the BI portion, the analytics portion with the other things that your application may do. Some applications may be just data applications or the data may be a driving force into the operational aspect of the app. And whether this is sending for deeper analytics through custom ML or adding something to a queue of people to email, there's a ton of different ways that you can take the analytics capabilities and help them drive workflows within the application. That's a pretty good overview through our demonstration of what ThoughtSpot everywhere looks like. I'm going to switch back views real quick and go over just a little bit more of the platform so you can understand of how all of it ties together. As we've shown kind of in action what ThoughtSpot everywhere looks like, how easy it is to integrate it in within your application, how fast it is to take content that exists and integrate it. This image here that we're showing now is just kind of a description of the full platform and really to show you all of the things you get with using a BI stack and embedding it within your platform. One is the capability of making multiple different apps using a consistent technology. And so this really, once you have the kind of expertise in your organization, if you have multiple different applications or multiple different divisions within the organization or any type of many different use cases, because the developer tools are standardized with those APIs and playgrounds all running off of a consistent platform underneath, you can facilitate many different applications running off the same system with a consistent set of tools and people who know what they're doing on the side of creating searches and pin boards can very quickly get you content that can flow up to your end users. Underneath all of that though is the larger platform that's able to deliver all of those things, those capabilities for search, AI and ML, the visualizations engines itself and so forth, all of that lying on top of a very complex, well, I should say it's not overly complex, but a model for data that is capable of seeing the complexity of your underlying tables and things like that, convert the actions of the users at the top into very efficient queries and take advantage of the kind of cloud data warehouses that people are using now. And consistently that's something we've seen people see with the ThoughtSpot platform over and over is that the queries that ThoughtSpot writes from those searches tend to be some of the most efficient ways to get at all of the data that people are now storing in those cloud data warehouses. So that's a main overview of the ThoughtSpot Everywhere platform. I hope as we've gone through this, you've seen all of the different capabilities that if you're looking at whether you should build or just buy, embedding likes capabilities, we think there's just a lot that it would take a long time to build. And even if you had the expertise, you'd probably spend all of that expertise on your core functionality rather than trying to reinvent the wheel. Now, that's not to say if you saw something great and you want to come join us, right? The ThoughtSpot's always looking for people with great ideas about analytics. But we think that there's no reason that you shouldn't be looking for a best of breed. This is intelligence application to fulfill that need for embedded analytics or for creating a data app. And I hope that if what you've seen here is of interest to you, that you'll get in contact with us and we can show you how it can actually fit within your platform. We have a free trial that's available that does include the developer privileges that we show today as well as our community. Thank you all so much for watching. And yeah, you'll have a good day. Thank you guys.