Good afternoon. Welcome to Informatica's Investor Day. We're excited to share our story, and we're thrilled to have you join us in person and on the webcast. Before we get started, a friendly reminder, we will be using some forward-looking statements regarding our business operations, product innovation, and financial objectives. There are certain risks and uncertainties involved in these statements, so please see our most recent SEC filings for more information. Additionally, we'll be sharing GAAP and non-GAAP financial measures, and a reconciliation of these measures will be provided in our PowerPoint presentation deck, which will be posted after the event. We have a packed agenda. Over the next few hours, we will be sharing a variety of discussions on our vision, our strategy, our go-to-market, product innovation, customer success, and we're also privileged to have BMO Financial Group and Deloitte with us here today to share their experiences with Informatica. At the end, we'll wrap up with a financial overview and share some early thoughts on 2024 and a brand-new midterm outlook through 2026. We will be taking questions online, so for those joining us over the webcast, please email me at investors.informatica.com, and I'll weave in your questions during the live Q&A session. We will have two Q&A sessions built into the agenda. What are we planning to address today? Well, we've been public for two years. We've answered hundreds of questions during that time, so we'll address these and many, many more. Importantly, since this is our inaugural Investor Day, we want to be able to share our story with you, our journey to today, where we're heading in the future, and why Informatica is the data management choice for the enterprise. We have a world-class management team who is here with us today, and you'll hear from Amit, Mike, Jitesh, John, and Ansa throughout the day. So with that, it is my pleasure to introduce our Chief Executive Officer, Amit Walia. Thank you, Vic. Well, good afternoon, and for folks in the room, thank you for coming, and everybody else on the webcast, hopefully, the energy is equally there on the webcast. Look, I think all of you, we've talked many times in the last few years, and I think I've got to know almost all of you over the course of time. What I thought we'd do today is share with you the unique story of the new Informatica that was built in the last few years, share with you where we are today, and why we are so pumped up and excited about our success. And of course, very importantly, share with you where we are going from here and why we are so optimistic and excited about our future as we look forward. Of course, you'll hear from the rest of the management team, and we'll double-click and talk about many other things. Well, let's begin. This year actually is a very special year for Informatica. It's actually our 30th year as a company. Now, the first 22 years, which is the pre-private time, Informatica was a great company. Until that time, the company was primarily a single product PowerCenter, on-prem licensed software company, and at that time, when we went private, it was a billion-dollar revenue company. Coined the words ETL, which sometimes I feel like I have to erase here and there. That was the company. And then we went private in mid-2015, and from that day till today, it's been eight years. And in those eight years, this company has innovated at a whole different level. These eight years are years that are split, where we actually reinvented ourselves as a cloud company and where we are today as a modern cloud company. In these eight years, we dedicated $1 billion to innovate ourselves from within our R&D. We launched our cloud offerings. We released the IDMC platform. We transitioned to subscription completely, and we launched our IPU pricing model. In the last leg of that transformation journey, when we entered this year, in January 2023, we walked into a cloud-only, consumption-driven strategy. We ended sales of all on-premise products, by the way, including the new products that we launched after we went private. Some of them were on-prem. The world was not ready for cloud at that point. All our cloud offerings are at scale. There is a global infrastructure across the globe to host those offerings, and we also have our CLAIRE Copilot and GPT out there. In these eight years, while in 22 years, we built one primary product and created a billion-dollar company. Pause with me and reflect. In these eight years, we built a platform, we built new market-leading products, and those net new product-based ARR that we've guided to this year is $1.1 billion. What took the company eight years, we've done more in 22 years, we've done more in eight years. That's the journey we took, and we are proud of that journey. Another way to look at that is, in these last 30 years that we've existed, many a technology trends have come and gone. You can see many logos on this slide of companies that were leaders in their own space. Some of them don't exist. Some of them just got stuck in their own way. Some of them went by the wayside. Remember Hadoop in the last few years? Was supposed to take over the world. The one company that kept punching and innovating is at the bottom, called Informatica. These things don't happen by accident. They happen by deliberate strategy and execution. That's the journey we took, and as we stand here today, I repeat, we're proud of that. Now, when we think about our state today, each and every word on this slide means something very important to us. We deliver innovation-led data management products, powered by the industry's only AI-powered data management platform in a multi-vendor, multi-cloud, hybrid approach. And let's pick apart each one of it one by one. The story of Informatica has two pillars: Innovation and Customer Centricity. Let's go on the Innovation side. Three core components to it. One is that billion-dollar R&D that I talked about was focused on building best data management products, born in the cloud, architected for the new modern data architecture, validated by every industry analyst, and each one of them is powered by AI already today. And if that was not enough, we actually went about building the industry's only data management platform, IDMC. It's AI-powered, and it has one simple pricing model. I think everybody in this room knows three alphabets: IPU. And the third foundation of those best products and platform is being a multi-vendor, multi-cloud, hybrid company. We have the broadest set of connectivity across the globe, 50,000+ connections. We obviously serve any data type from any vendor in any way, shape, or form, and we pride ourselves in being the Switzerland of data. That matters a lot to our customers because their environment is complex. These are the three core principles of our innovation strategy. Let me click a little deeper. Let's begin with best data management products. There are seven core product categories we are in. Data catalog, which, by the way, we pioneered. We launched the industry's first data catalog in 2016. The category didn't exist, we created it. Data integration and Data Engineering, App Integration and API management, Data Quality and Data Observability, MDM and MDM apps. We created the industry's first MDM apps. Data governance and privacy, data marketplace. We created the concept of a data marketplace. We have not only created the best products, we have created categories. That's not just for me to say. Take Gartner. You pick any Magic Quadrant we compete in, and there's only one place you will find Informatica: top right-hand corner. You can go Magic Quadrant by Magic Quadrant, and we're not just in the top right-hand corner, we have sustained our position in that corner. Remember, being at the top, you can get there by chance sometimes. Staying there is very hard. By the way, if you've heard of something called Gartner does a vendor rating, only 30+ companies across the globe they rate because these are important technology companies that they believe create value for enterprises. This includes Salesforce, Adobe, Amazon, Microsoft, Deloitte, Accenture. We are the only one from the data space in that. Not just Gartner, you pick Forrester. You pick any Wave that Forrester comes with, and you will see Informatica in the top right-hand corner, and we have sustained that leadership position. Because of that, we have been the leader of market share in our core market. If you look at how IDC combines and calculates this market, we have the number one position, and not just number one overall, we are number one in every subcategory. All of these things don't happen by accident. They happen by building great products that help customers solve real business problems and create value. If I talk about the platform that these best products sit in, we have the industry's only IDMC platform that no one else even has anything remotely close to it. Now, again, this didn't happen by accident. I'm gonna take you through some slides that I actually used with our customers at Informatica World in the last many years. In 2015, our vision was to create a platform. We knew that customers will get immense value by having a single platform. In 2016, we put ourselves out there to make that comment, and this is exactly the slide I used. We called it the Intelligent Data Platform as a concept at that point. 2017. 2018. See something over there in 2018? CLAIRE. This is exactly the slide we used to launch CLAIRE at Informatica World 2018 in May, Las Vegas. Because we knew it takes many years to hone CLAIRE, doesn't happen by accident. From there, CLAIRE went through many years of scaling and scaling and scaling. This is 2019. This is 2020. As we continued to double down and accelerate our cloud transformation, we came to what we call Intelligent Data Management Cloud in 2021. We unveiled that because our cloud offerings were getting at scale. In 2022, and here we are as of today, IDMC, with all the best-of-breed offerings at scale, with CLAIRE, the AI engine, running for many years already, and our unparalleled connectivity that connects anything and everything within an enterprise. That's the platform we have built, ground up from scratch, with so many core capabilities that a modern platform should have. It's elastic, it's serverless, it is API-based, it's flexible, it's open, it's best of breed. It actually incorporates many open-source capabilities like Spark, like Kafka. I t is incredibly easy for customers to use because it's had what? The IPU pricing model. That's the beauty that we built in the last many years, brick by brick, over the course of many years. And then we come to our unique strategy of being multi-vendor, multi-cloud, and hybrid. Through the one common cloud IDMC platform and its products, we can serve a complete cloud use case, we can serve a hybrid use case, we can do anything. We simplify that for our customers through a single pane of glass. Why is that? Because if you look at an enterprise, fundamentally, it's the exciting news is not data growth. The challenge they face is that while the data has been growing exponentially, tremendous fragmentation of that data. So many technologies have come. They haven't gone away, some of them survive and persist. Fragmentation is a massive problem. And then, on the other hand, there is structured, semi-structured, unstructured data, batch, real-time, streaming. There are business users, technical users. They all want access to different types of things. So imagine a large enterprise's complexity. That's what we solve. And you can see other stats. Enterprises have hundreds of different applications they're using. They have PB and PB of data that sometimes they don't even know exists. They don't even know what to do with it. Of course, every leader wants more and more people to have access to that data, to make tomorrow's decision yesterday, to create value today. That's what people want to do. It is in that world, we, Informatica, pride ourselves to be the Switzerland of data. It's not just being Switzerland to support everything. We future-proof our customers. When they move from an old technology to a new technology under the covers, seamlessly, Informatica technology moves, and we're also future-proofing them from the forward-looking stuff. Our customers had Hadoop stuff. When Hadoop died, they could easily take the Informatica mappings and all the stuff and move it to the new cloud architecture. They did not have to rearchitect that. They did not have to rearchitect the Informatica part of the world. That's the strength. Now, as we built our cloud platform, in 2015, it was in its infancy. The usage was very, very small, 0.2 trillion transactions a month. Last time I met a lot of you, at the end of the last quarter's earnings call, that number was 71 trillion transactions a month. Across AWS, Azure, GCP, Snowflake, Databricks, OCI, Salesforce, Tableau, you pick any of these. As of today, that number is 85 trillion transactions and counting. And I've always said that to you, I'm always happy to see that the transaction counts move faster than cloud ARR. That means our customers are using more, and that creates, gives us more stickiness, more value within an enterprise. And I guarantee you, when I meet you next time in the next earnings call, this number will be bigger. Our partner network is very broad. I talked about the ecosystems. We have deep technology and go-to-market partnerships with them. We'll cover a lot over the course of the day today, but we also have an amazing partnership with the GSIs. You'll hear from Deloitte today how we partner with them to serve our large customers. And of course, in a good part of the world, we have many other regional partners, and of course, a lot of ISVs also work and build on top of our IDMC to create value for their customers, like ZoomInfo, like Dun & Bradstreet. That's an amazing, amazing network effect that we have created, and we'll continue to invest in that. The second part of Informatica journey is customer centricity. We are a company that bends our back to make our customers happy. We're never, ever short on that one. We have an amazing set of 5,000-plus customers across the globe in all, every vertical. There are some great stories, and I've shared many of them over the course of these last couple of years, and these customers are complex, large customers that need a lot of stuff. Take an example, Unilever. 96 countries, their entire supply chain goes through Informatica, onboarding every supplier, tracking how every supplier is operating across the globe, which product comes to that supplier, so that they can make sure that the right product from the right supplier goes to the right end user at the right time. Or a Hyatt, running their whole customer loyalty program on Informatica. Or Saudi Airlines. Saudi Arabia is trying to transform into a mega place for tourism, and it begins with making sure that Saudi Airlines can be at the hub of that one. Or Kroger, when they want to stock their inventory just in time, they want real-time POS data, they want batch data, they want to take all of this stuff and make decisions. During COVID, they were making decisions on fulfilling that demand from their warehouse or their in-store. The CEO, CFO dashboard goes through a catalog. Or Chubb, that they close their books at us. These are mission-critical workloads. Having five features doesn't make a product. Creating enterprise value creates a business. That's what we do every day. I get the question, who we compete against? Well, we have the legacy providers whom we barely see anymore. We obviously have the point providers who barely have a set of narrow capabilities, sure. 5 data quality features don't make a data quality product, in my opinion. Then, of course, we do have an overlap with the ecosystems. We deeply partner with them. Customers will begin a small workload them, but very quickly, in a multi-cloud hybrid environment, they come to us. But in reality, our competition is one thing: hand coding or do nothing. That's our biggest competitor. When you ask my sales team, customers not doing something or delaying to do something is our biggest competitor. That's the Informatica today. And when I look at the next five, 10 years. I'm extremely excited about the opportunity in front of us to fuel our cloud growth. I mean, let me take you through the three areas where we see the tailwinds coming towards our cloud growth. Well, look, digital transformation is not done. When you move from Silicon Valley and you go to any other part of the world, there are people still in the middle of their digital transformation, and there is tremendous amount of work still to be done to help customers become an innovative digital companies. I know, by the way, in that is another area that we are seeing is vendor consolidation. A platform company like us, with many, all the best-of-breed capabilities, bring all the use cases to a single platform, and consumption model makes it very easy. Still, a lot of tailwind over here. And if that was not enough, we have something very unique to Informatica, which is our billion-dollar on-prem install base, maintenance and self-managed. Migrating that to our cloud is tremendous tailwind to us, and we are on that path. We've made great runway, and we'll share with you why we are extremely bullish about us as we look at the next few years. If those two are not enough, how can we not have GenAI? It's just getting started. There is no GenAI without data, and I'll cover that separately in a few minutes later, so we can contextualize our GenAI opportunity. When you look at a TAM, and Mike will go through that in more detail, of the overall TAM, we have $62 billion worth of cloud TAM, growing at 27% CAGR. That's a massive TAM for us to be in. As you can note, we are growing faster than the TAM because of all of the competitive advantages we have as a best-of-breed, best data management product company, a platform company, and of course, our strategic data strategy. These three are continuing to fuel our growth, and we'll make sure that we drive continued cloud growth because that's the area of growth for the company, which allows us to drive overall total growth. We'll go through that later in the day when Mike talks. And then, of course, we'll never forget that we are a balanced growth company. Profitability is equally important to us. That's what we see when we think about the next five, 10 years, and we are very bullish about our strategy. So hopefully, as I started the day, you got a context for the new Informatica that was built in eight years, more in eight years of our 30-year existence than the previous 22 years. And if I asked you in this room, how many billion-dollar ARR companies were created in the last eight years? You will have to probably just count a handful of them. Informatica is one of them. We are firing on all cylinders today, growing faster than the market, and when I see the future, I have no doubt that we're firing on all cylinders and growing faster than the market. Now, I shared with you the overall context. What I'd love to do is now begin with going deeper into the product side of things, and then we'll go into the go-to-market side of things. So with that, let me invite our Chief Product Officer, Jitesh Ghai, on stage to go deeper into our innovation strategy. Jitesh, come on up. Thank you. Good afternoon, everyone. Really great to be here with all of you at our Investor Day for 2023, and with all of you online as well. Super excited about all of the innovation that the team has delivered over the course of the year, and some really exciting things coming, going into next year. But to start, I wanted to go back to what Amit shared just now about how we've reinvented ourselves as a modern cloud company. No small feat. We've heard that many times from all of you. We hear that often, and we oftentimes, as CPO, I get the question of: How did you accomplish it? What did you do to become a modern cloud company? You know, first, it started with laying out a very clear vision that if an organization is going to be data-driven, our customers, they have to rely and need a data management platform. They cannot rely on bespoke tactical tools. They need an end-to-end data management platform to treat data strategically to drive digital transformation. Equally, we knew that while we were innovating on an on-premises technology stack, we needed to reinvent ourselves on a cloud-native, microservices-based, API-driven technology stack, reinvent all capabilities of data management. And while we were optimized in the first Informatica, the PowerCenter Informatica, while we were optimized for those legacy architectures, data warehouse appliances, data marts, we partnered deeply with the AWS's, Azures, GCPs, Snowflakes, Databricks, innovated and built out data management innovations together to realize a modern data architecture for our customers. Of course, we support specific use cases, but with a data management platform, the potential for us to empower our customers' digital journeys required us to focus on end-to-end business imperatives that didn't just rely on one capability, but multiple capabilities integrated together. And through this process, on premises, we had over 1,000 - several thousand SKUs for pricing. We were very focused on simplifying the experience for our customers. I was in multi-month workshops with the team, pushing to simplify, simplify, simplify, and we now have just eight SKUs in the cloud, all driving consumption-based pricing. And it was through all of that that our innovation, the team's innovation, went from 100% on-premise to now, over the last few years, 100% in the cloud. So that was what we did, and then the question becomes: well, how did you make that happen? That's very hard to do. Back in 2015 when we embarked on this journey, of the approximately 1,100 folks in R&D, only 50 were exclusively dedicated to cloud. We recognized we needed to accelerate our cloud roadmap, and we went through an exercise where we moved over 1,000 folks that were innovating for many years on an on-premises technology stack, we invested in them. We retrained them and moved all of them to innovate on a cloud-native technology stack. And over the course of the years, we added an additional 1,000 designers, engineers, that were born in the cloud to scale and deliver on all the innovation to realize the Intelligent Data Management Cloud. And it's through the last few years with this team that we have realized a born-in-the-cloud architecture with the benefit of over $1 billion in R&D spend. That is how we conceived and built the industry's only Intelligent Data Management Cloud, unparalleled in its breadth and depth of capabilities, 50,000 metadata-aware connections, powered by our AI and ML engine, CLAIRE. Now, central to our strategy that Amit walked you through is building the best data management products in the industry, powered on the industry's only data management platform, supporting extremely difficult workloads that are multi-cloud, hybrid, multi-vendor. Against these three pillars, I'd like to now share some really awesome updates. Now, I'll start with best data management products, but I recognize I might run the risk of sounding like a proud parent, but I also have the report card to back it up. Let's start with Data Cataloging. As you heard Amit earlier, we conceived this concept of a data catalog when many customers were experimenting with Hadoop, realizing they had a data swamp, and they needed the data indexed and cataloged. We enable our customers with IDMC to scan all their data across the enterprise, through all enterprise data sources, to auto-tag, auto-curate, index all of this metadata that we derive, leveraging AI and ML, to give them a simple, consumable experience to understand where all their data is, how it's being processed, how the business relies on it. And it's for this innovation that we are recognized as the best data catalog offering in the industry. But we continue to raise the bar for ourselves on what it means to be the best, and I'm super excited about CLAIRE Copilot and auto-classification. Classification is the process of identifying different data types, first name, last name, purchase order, et cetera, by looking at the structure of data and based on the structure, determining what that data type is, what type of data, what its relevance is, customer data, supplier data, so on. An automotive manufacturer of ours, a customer of ours, for their connected car data lake, had PB of data, and it took 10 data stewards two years to develop 200 classifications for their proprietary data formats. We pointed auto-classification at their data lake. We identified those 200 classifications. We also identified another 200 classifications, and we did it in eight minutes. You folks can do the math on the kind of productivity we're delivering for Data Cataloging with our AI ML engine, CLAIRE. Now, let's talk about data integration and engineering. There's many bespoke tools that do ingestion, replication, ELT, reverse ETL, and we've been a leader in data integration for many years, supporting mission-critical enterprise workloads, because we recognize that ingestion in and of, in and of itself is incomplete. ELT in and of itself is incomplete. Reverse ETL in and of itself is incomplete. You need all of it. You need it all integrated to really support enterprise-scale workloads. It's for this reason, this is a Forrester Wave for cloud data pipelines that actually just came out last month, that we are recognized as having the strongest offering for data integration. And I'm super excited to share, hot off the press, as of yesterday, Gartner equally recognizes us again as the best data integration product in the industry. Now, we continue to innovate and define what best means for data integration, and one of our commitments is meeting our customers, our users, where they are. While we pioneered this concept of no-code integration, we recognize there's a class of folks that just like to code. They're most comfortable doing Python, PySpark, SQL coding in their favorite development environment. And so we recognize this, and we wanted to bring the power of IDMC to them. O ur 50,000 metadata aware connections, our advanced transformations, and so we built a plugin called INFACore. INFACore can be plugged into your favorite Jupyter Notebook environment for data scientists, data engineers, your favorite SQL development environment for data analysts. And once plugged in, you can use our APIs and get access to all of our advanced connectors, all of our advanced transformations. Enable data engineers and data scientists to build data pipelines, to build their AI and ML models. And super exciting, we also launched ModelServe. ModelServe is a new service that enables our customers to not just build their AI and ML models, train them with trusted data, but also, once ready, operationalize these models using our ModelServe capability, fulfilling the life cycle from provisioning, training, building, and then operationalizing the AI ML models to deliver business outcomes to our customers. Let's talk API and application integration, also known as iPaaS, integration platform as a service, by many analysts, industry analysts. We pioneered the iPaaS category many years ago, and essential to iPaaS is having API management capabilities, having application integration and synchronization capabilities, being able to automate business processes, order to cash, procure to pay, by moving integrations and trusted data across systems of records. We offer all of these capabilities in a single, no-code experience, simplified experience, with out-of-the-box SaaS connectors to enable our customers to drive digital workloads, drive consumption, and deliver to their digital outcomes. And we continue to innovate and simplify things for our customers to drive greater workloads faster with API Center. We recently launched API Center. It is a no-code experience, enabling developers to build APIs rapidly, simply, and once built, by invoking the API, automate and orchestrate complex integrations behind the scenes, making them super productive and delivering outcomes hyper fast. Now, data quality and observability. We are able to scan PB of data, as Amit was describing it, enterprise scale. As we scan, we're able to identify where we believe data quality issues to exist. We're able to auto-generate the data quality fixes needed to address those issues. As a data owner agrees that those are in fact issues, we will auto-deploy those fixes. Critical to data quality is not just doing it at a point in time, but ensuring that the quality improvements that one makes are durable, and for that, you need data observability. We have a very strong point of view on data observability. A bunch of pretty dashboards without a metrics engine that can generate the data quality stats, that can generate the data quality fixes, is incomplete. You need to be able to generate, scan, profile at enterprise scale so that you can populate those observability dashboards with confidence and with trust. Gartner recognizes this, and that is why we are recognized as the best data quality and observability products in the industry. We partner deeply with our hyperscaler partners, in recognizing our leadership in data quality and observability. Microsoft, Arun Ulag, who's the CVP at Microsoft for Fabric and Power BI, specifically requested that we bring our market-leading data quality and observability as a native experience as part of Fabric. And that was a big announcement a couple of weeks ago at Ignite, where we are bringing this as part of a native Fabric experience, using Fabric's visual design language and user experience standards to provide a seamless experience for the hundreds of thousands of Fabric users. MDM and 360 applications. Master Data Management is about bringing customer data that exists in multiple systems of records within the organization together to build a critical single source of truth. And our multi-domain MDM does this for products, suppliers, any domain, jet engines, cell phone towers, whatever is deemed to be business critical to an organization. Bringing this together can take several months, 16-18 months, typically, to get to production. We had a very clear vision that we are going to make MDM a SaaS, an application, an out-of-the-box type of experience, and in doing so, our customers are getting to production in 16-18 weeks, as opposed to the 16-18 months it's historically taken. For that reason, we are recognized as the best master data management. I told you guys, I told you folks that I'd have many report cards to back it up, the best master data management offering in the industry. And we continue to make it simpler for our customers to onboard more data sources, more systems of record. With CLAIRE Copilot, our customers can point us to a new source of data, a new system of record. We know the master data model, we know the fields, the attributes in that master data model that need to be populated. We can automatically profile scan the source that they point us to, identify the fields in the source, and auto-generate the data pipeline, auto-generate the data quality, and do the matching and merging to populate the master data model, the master data model with this updated system of record information, making it even faster and more productive for our customers. Data governance and privacy. When we started this business about six, seven years ago, we had a very clear point of view that policy definition without implementation is documentation, and documentation is instantly obsolete. Our customers at the largest banks came to us and said, "You folks have everything to make this real. Can you please bring this together and help us govern, actually govern, not just document?" And so applying AI and ML with CLAIRE, we built intelligent data governance so that governance teams could document their policies, and we would operationalize them through data quality, through privacy, through data access management capabilities. It's for this reason that we are recognized, again, as the best data governance and privacy offering in the industry. And we continue to make it simpler and democratize access to data quality, to governance. With Quick Look, a simple plugin for Chrome browsers, our customers can be in any experience. They can be in Power BI, they can be in Tableau, they can be in Workday or their favorite ERP, and they see a term, and they can look up its definition through Quick Look. They see a data set that they're working with, they can look up its data quality score within their experience, again, meeting them where they are. Data marketplace, this is something we pioneered because our customers were building data products. They wanted to democratize these data products, but it was very hard to break down these silos. Inspiration from the Amazon shopping experience, we built a, an Amazon.com-like shopping experience for data products, enabling data product managers to onboard, publish data products, enabling data consumers to browse, discover, identify products of interest, and then literally put them in a shopping cart and request access. And once approved, we will auto-provision the data product to wherever they want, Tableau, Power BI, their favorite S3 bucket. And because we're simplifying and democratizing data, we are again recognized as the leader in the data marketplace category. We continue to make it easier for data product managers and data consumers to come together through collaboration capabilities, gamification, enabling data consumers to ask data product managers for what they need, enabling data product managers to meet the requirements of their customers, these data consumers. Those are the best data management products. Now, I'll cover some innovations on the industry's only data management platform. Central to our strategy, the force multiplier is really bringing these best data management products together on a single, integrated, AI-powered data management platform. Critically important to us is ensuring that we are open, extensible, and embeddable for all workloads in a complex enterprise, in the Global 2000. All of this is integrated and available within one login. As opposed to bespoke tooling, where you have to go from one tool to another, and Alt+Tab, and this and that, and you create artifacts here, and another tool is disconnected, is none the wiser elsewhere. All of this is integrated as a single experience, both on the front end and back end, making it extremely easy for our customers to use a single service, but more likely, multiple services to drive their end-to-end business imperatives. This platform is powered with 36 PB of metadata. Our AI ML engine, CLAIRE, is applying super exciting techniques against this 36 PB of metadata to deliver predictive data intelligence, and from it, data management automation. Now, we are the metadata system of record. Our customers, the data teams, CDOs, CDAOs, rely on us. There are many repositories for metadata. They rely on us for helping them build the authoritative source of metadata. There's many systems of record for data. We are the system of record for metadata. And to do so, and bear with me, this is the best we could come up with, because scanning all the data sources within an enterprise is a complex task. But we wanted to give you the complete information of the breadth and scale at which we scan, from PaaS services, SaaS services, databases, on-premises, in the cloud, warehouses, lakehouses, derive metadata from coding and scripting where none exists, to build that system of record for metadata. And we continue to expand the core platform capabilities. We shared with you our acquisition of Privitar back in July and going into the first half of next year. The data access management technology that Privitar is known as a leader for will be a native platform capability available to all of our customers to consume through IPUs, supporting all IDMC platform services. Super excited about extending IDMC's capabilities. Now, it's incredibly important to us to be the most secure and trusted data management platform, and for that, we're governed by rigorous security certifications, SOC 2, SOC 3, FedRAMP, UK Cyber Essentials, and we continue to evolve the certifications based on our customers' evolving security requirements, based on their evolving data sovereignty needs. All these services that I've described, all these best data management products on this integrated data management platform, are available through IPUs. Whether you have one IPU or ten thousand IPUs, you get access to all of these products. We make it easy for our customers through a simple calculator to specify their integration workloads, their quality workloads, catalog and governance workloads, and then we tell them, "This is how many IPUs you need." And we provide the transparency for them to track their consumption. We provide analytics and forecasting for them to understand when they'll need more and how to repurpose their IPUs. Full transparency on their use of our cloud platform. Those were the two pillars, best data management products, industry's only data management platform, and critical for us to do what we do, the hard work that we do, is to support multi-vendor, multi-cloud, hybrid workloads. Central to doing that is having the broadest connectivity in the industry. We, again, as you heard, Amit, we connect everything everywhere within the enterprise. 50,000 metadata-aware connections, all those words are extremely important. A connector in and of itself without metadata awareness delivers very little value. 50,000 metadata-aware connections, and oftentimes we get asked, "But this vendor has 50 connectors. Why do you have 50,000? That vendor has 120, why do you need 50,000?" Because a modern data architecture and the problems it's solving are extremely complicated. Let me give you a sense of what 50,000 metadata-aware connections means. Of course, it's connectors. All the connectors to everything you know and love, data lakes, lake houses, warehouses, on-premises, in the cloud. But these connectors need to be optimized for multiple patterns. They need to be optimized for ELT SQL, ELT Spark, for change data capture and replication. So yes, there might be a vendor that is just doing replication and has 100 connectors for that, but our customers expect us to support all patterns. These patterns need to be supported across the best data management products on IDMC, and for hybrid workloads, oftentimes these connectors are deployed within the customer environment, behind the customer's firewall and the customer's tenant, in the customer's data center, and we have to support multiple flavors of operating systems and multiple versions. That is the extremely hard job of modern data management and a modern data architecture. All of this is natively built on AWS, Azure, GCP, and most recently, Oracle Cloud, and globally available to meet our customers' workloads where they are, to meet and address their data sovereignty requirements as required. As we natively build IDMC on our hyperscaler partners, we're very deliberate in ensuring we're using the native services and providing optimized compute experiences to provide the requisite security, performance, and scale expected of a multi-vendor, multi-cloud, hybrid workload leader. Now, many customers, upon learning about the latest and greatest from Informatica, you know, oftentimes the question is, is, "Hey, I'm a long-standing PowerCenter customer. How do I get access to all of these amazing innovations? How do I scale my cloud workloads?" And I'm super excited to share that in July, actually, in August, we launched a cloud edition for PowerCenter. We've spoken to a lot of you about migrations and what does that look like, and we have a Migration Factory, and our customers have typically been migrating over a period of two years. With PowerCenter Cloud Edition, we've radically simplified that, and our customers can now migrate with a 75% reduction in the time and effort needed to do so. In fact, while we say six months here, I'm aware of customers that have done it in six weeks. We view this as an amazing game changer to accelerate our customers' cloud modernization journeys with PowerCenter, moving to IDMC. It is all of these innovations across these many years that have enabled us to build the best data management products in the industry, on the only data management platform in the industry, to support extremely difficult, extremely difficult workloads that are multi-cloud, multi-vendor, and hybrid, to drive unprecedented value for our customers and realize their digital outcomes with Informatica's Intelligent Data Management Cloud. Thank you. I'm ready for AI to help me streamline my supply chain. And create a memorable shopping experience. I'm ready for AI to help accelerate drug discovery. Help me expand some minds. I'm ready for AI to help our business take sustainability seriously. Help me design the future of mobility. The future of air travel. The future of finance. I'm ready for AI to automate my entire enterprise. Everybody's ready for AI, except your data. Make sure your data is holistic, governed, and trusted, so you can unlock the power of AI. Informatica: Where data and AI come to life. All right. Well, I think you heard so far, obviously, where we are with our innovation and what makes us extremely unique, strategic, and high growth. I promised you GenAI is a tailwind of a different nature, and I'll contextualize that opportunity separately. So let me just dive into it right away. Look, no doubt, we sit in this unique time where we can all say that GenAI is clearly one of these completely orthogonal technologies that's gonna shape everything around us, and we believe that. I think digital transformation is gonna be fundamentally changed by GenAI. Now, to put that in some context, if you look at the last 10, 15 years of digital transformation, it started classically with application software: Salesforce, Workday, all of the on-prem workloads going to cloud from an application software point of view. Then came the second leg, which is what we are in actually, by the way, the harder one, of taking infrastructure up to the cloud. Data centers, our data layer going to the cloud, data warehouses, data lakes, data management, and that's a more complicated thing because of a lot of reasons, you know, data is hard, security, all of those kind of things. And we are nowhere close to be done on this phase. Still going on. But when we look at the next five, 10 years, the third leg of digital transformation will be driven by GenAI, and it'll be data and GenAI fueled. And to be candid, if you look around any report, what is AI without data? What is a model without data? You guys have all Excels up on your laptop right now, right? If there is no good data in that Excel model, what is it gonna tell you? Nothing. Junk! And in my opinion, as we walk into that third leg, value creation will be exponentially bigger. Companies are gonna derive a lot more value from this third leg of digital transformation as we stand here today, and we believe that. So we are walking into a really exciting time for all of us. But what does that mean? Like I said, AI by itself doesn't do anything. Your brain by itself, without reading, without learning, cannot output anything. And fundamentally, for GenAI to be of any value, it needs core data management and a few very critical attributes. Holistic data. You can touch the elephant from wherever you sit, it'll give you a different answer. Unless you bring complete information within a model, it's gonna give you incomplete answers. I know, by the way, I think it's pretty obvious, but bad quality in means bad quality out. Data quality becomes even more paramount in the world of GenAI. If we want AI to run things, automate things, create productivity, and we want it to be on its own, unbelievably, we want to give it good data and holistic data. And then, in fact, it has become the first thing, everybody's worried about the governance of all of these things. Governance of GenAI and all the stuff we do around it is incredibly important. And last but not the least, everybody wants to democratize this, right? We don't want to hold it in the hands of a few. We want every user across a company of different type to be creating value for what they do with the help of GenAI, which means democratization of data, but in not a Wild West way. Last I checked, these are all things that are fundamental to data management. So to me, the third leg of digital transformation will be fueled by data management, and in that, we have a two-pronged strategy. One is Informatica for GenAI. Well, no GenAI project will be successful without the IDMC platform and the best-of-breed products sitting on it, and a multi-vendor, multi-cloud strategy. But we're not stopping there. We want to create value of GenAI from Informatica. Remember, 2018, we launched CLAIRE. We already have CLAIRE embedded in our products, that I showed you. CLAIRE Copilot is live today, and we're gonna take that forward with CLAIRE GPT as well. We can do that very uniquely because, like I said, we are the system of record for metadata. Google indexed the World Wide Web, we're indexing the enterprise data. The more you can apply AI on top of that, the richer an enterprise would be. Today, in the world of cloud, we sit on 36 PB of metadata. Metadata is data about data. So 36 PB of metadata is a lot more in the terms of data, and we are just getting started. We believe we're sitting on something unbelievably differentiated, at scale, and exciting. That's where our journey for GenAI is gonna be starting even more so. Informatica for GenAI with IDMC and products, and CLAIRE Copilot and GPT to help our customers automate, be intelligent, do more with less, and we are super excited about that. Now, that's a lot of PowerPoint. I promised some exciting stuff, so for that, let's see a demo, and let's see a demo of CLAIRE GPT. And for that, join me in welcoming Jitesh Ghai back up on stage, with Gaurav Pathak, our VP of Product Management. Come on up, guys, and let's show the demo. Thank you, Amit. Gaurav, go on up. Okay. I'm back. With me, I've got, Gaurav, our VP of Product Management for CLAIRE, all things AI ML, so Copilot and now CLAIRE GPT. Gaurav, we shared this concept at Informatica World in May of a chat-based experience in CLAIRE GPT. Where are we now? What's the status? We have about 250 customers signed up for the private preview, all doing really exciting things with this revolutionary technology, using AI for probing their data estate. So can't wait to share that with the audience here. Yeah, what are they doing? What are they doing with the, as part of this private preview of CLAIRE GPT? What are they up to? So, one of the scenarios that I have to show here is what we have, you know, in enterprises it's even simple things get very complicated. Now, in this demo, I'm going to play a marketing manager at a retail firm, trying to figure out a good campaign for my end users. Now, doing something like that requires data from Salesforce, because you want to know the customer purchase history. You want to get behavioral data that's coming from product. You want to get information from market research that comes from Marketo. And getting all of these things together, collected in a central place, modeled, integrated, solve all the data quality problems, remove all customer information, and anonymize all of that, it takes a long time, as you can see on the slide. Yeah, I mean, just looking at this, it's a highly iterative process. You find a dataset, it doesn't have quite what you need, so you go back and ask for other datasets. And at least in this scenario, this is half a year, almost, 22 weeks to actually build a campaign. Now, imagine Google taking 22 weeks for a query, search query- Yeah. but, that's, that's what's happening with getting access to the right data in organizations today. Just so we're clear, this is not what CLAIRE GPT enables. This is what is happening today. What is CLAIRE GPT gonna do? Let me show you. All right. Let's go. All right. So I have CLAIRE GPT over here. Amit talked a lot about the metadata system of record, a place where we have information about all the data assets in an organization. And what we have done is we have trained Informatica large language model that's specialized in data management, and we've put that in front of that metadata system of record. Now, as that marketing manager, I need to get access to that dataset, so I'll start asking about the sales KPI dashboard that I know about. Now, this sales KPI dashboard has a lot of metrics that I have used in the past. Mm-hmm. What CLAIRE GPT will allow me to do is then interrogate it further, like what data assets are used in this CLAIRE GPT in this sales KPI dashboard. So you CLAIRE told you that, there is a Tableau dashboard that has all the sales KPIs, and now you're going to ask what data is feeding these KPIs? Yes. So I'll ask it in natural language: "Show me data assets that feed sales KPI," and the system will understand that as a data lineage query. It will bring in all the different datasets that feed that sales KPI report, the customer purchase history, the online behavior data, the market research, and I have all of it right in front of me. You've already, in two sentences, done the discovery of finding datasets for your campaign. We are already six weeks ahead of everyone else. Moving fast. Keep going. So now from here, we ask it. It supports multi-turn conversations like ChatGPT. So I can go ahead and ask, "Show related sales data from above," and it will understand that we are looking for sales data from this lineage diagram, and it will bring in all those datasets that are feeding into that sales KPI report. So now you've discovered data, you've also now discovered related datasets, and so you have a more complete corpus to work with for this campaign. Absolutely. And now I can start probing further. I can go into datasets like the website dataset and then seeing what user dataset that we have available for creating this market campaign. And again, this goes back to that metadata system of record, brings in all the key metrics available there, along with data quality statistics that we have gathered for this dataset. So the definition, the fields, as well as the, you know, quality to give you confidence of what you're working with. Absolutely. Okay. Now I can go even deeper. Let's ask it what data exists in this as well. So I can say, "Show sample data from above dataset," and again, it will understand that we are looking for the consumer website data, and it will bring in the sample data from there. Now, this is, just so you know, behind the scenes, it's this, essentially, it's a data integration job. It was written in a sentence, and now it's gone, connected to a system of record, pulled a subset of the data. Absolutely. And it also needs to take care of governance and needs to make sure that I can have access and see all of this data as well. As we integrate Privitar into all of this, we'll make sure that only the right people have access to the right datasets as well. Awesome. Now, now, I'll show you something more interesting. So from here, you can start asking this data questions as well. So, we have gone ahead- And for the record, all transparency, this part was not quite working yesterday. This is a live demo, so Gaurav promises me that it's gonna hum today, but go for it. I have done sacrifices to the demo god, so hopefully, this will all run well. From here, so here it shows me all the different metrics that are available, like transaction IDs, product IDs. You can see data quality statistics, first names, last names. Because I have the right permissions, you can see a lot of this information over here. And from here, you can start asking questions like show me sales, show me average sales amount. And in this demo, I'm showing you questions that go against a single dataset. We will have the system go against multiple datasets at the same time, with joining tables automatically figuring out from the query what are the right datasets required, and getting those answers right away. So, this is interesting, because now you're not asking it to do data management, you're also asking questions about the data itself. Absolutely. As a marketing manager, I can now explore these datasets even before I use it, so that I know what's in them. Got it. Now, because it's a large language model, it has knowledge of the world. I can ask, "Show average sales amount before COVID," and it should understand when COVID happened, what I'm talking about, and it gets the COVID date right, the March of 2020. But more importantly, it got this column called Transaction Date right. It figured out what's the right column to filter against and generate the right query for me to bring it here as well. Awesome. Very cool, and it's working. It's working as well, so the sacrifices worked. At the demonstration outside, please take time and ask more interesting questions of this dataset as well. But I'll also show you some of the things that our data team members can do. Yeah. So, this brings data to the business users, asking all questions, and then getting answers right away. Right without worrying about IT, getting access to X data, Y data, brings it all altogether. But we have not forgotten our data team members, data engineers. For them, they can create a data pipeline directly with a prompt as well. So I can come here and say, "Create a mapping," which is our data pipeline, "from enriched sales to Snowflake," and it will understand what are the source datasets to go for. It will understand what is the target data in Snowflake to connect to, because CLAIRE already does that in our data integration product and brings them here within CLAIRE GPT. This is, again, the metadata system of record understands the metadata and the source system and what fields are needed, much like we do for MDM. Understands where that data needs to sit in Snowflake, and then auto-generating a data pipeline. Absolutely. CLAIRE GPT sits like a conductor in an orchestra. All IDMC services, like Master Data Management, data catalog, data integration, are called through from this interface. Orchestrated from here, and it looks like it wants to do some cleansing. Yes. So because we are operating from that metadata system of record, it knows that there are data quality issues. We also have out-of-the-box data quality transformations that can fix those issues, so it's already suggesting those as well. I just press a button, and the standardizations of credit card types, et cetera, can happen within the pipeline very, very easily. Auto-generated data pipelines, auto-generated data quality. Okay, so the big question is, with private preview, Gaurav, this is amazing innovations that I know many of our customers— How many have signed up for private preview? You said 250? 250. 250 organizations are playing with CLAIRE GPT. When is this generally available? We are targeting first half of 2024 to make this available to everybody. He's committed that to me in the past, now he's committing it to all of you as well. Great job, Gaurav. Thank you. Thank you, Jitesh. Hopefully, you get a sense, I mean, we all recognize that GenAI is gonna be revolutionary for how we operate, how we work. What Gaurav shared with you is a very typical process of, "I need to go find data, and I need to go talk to a data team, and I need to put in a service ticket in ServiceNow, and then that data team needs to go and figure out what type of data, and then test it with me." And as you go through this process, you discover the data. Then you need to get a data pipeline built, then you need to cleanse. This is literally weeks, in this scenario, six months of work, that in approximately seven minutes, with the awesome power of Informatica's GenAI, CLAIRE GPT, we automated. We transformed a process within a common enterprise from several weeks to several minutes. And this is what's exciting for us as innovators, is this is just one example of many that CLAIRE GPT is going to be addressing. We've got a huge roadmap for CLAIRE-powered innovations going into 2024. So for now, as excited as I am, all I can say to all of you is just stay tuned. We live in exciting times, and there's a lot more coming from Informatica and Informatica's CLAIRE. Thank you. Great. Thank you. Got a couple of mics here. If you have a question, please raise your hand, and I'll point to you. Howard. Howard. Hi, great. Thank you. Howard Ma, with Guggenheim Securities. So my question is, and I'm and I'm a little—I'm gonna caveat my question, 'cause I'm a little wary of leading the witness, and I don't wanna ask too narrow of a question. But the question is... It seems like most large enterprises and even smaller enterprises are, they're now exploring, I mean, you guys see all the data just as we do, right? They're exploring how to use a large language model in conjunction with their own enterprise data and maybe other data sources, and to extrapolate value, which is really the holy grail or the end state. And so the question is, can you bring us into the room, or, you know, maybe the virtual room, when you're having these conversations with these 250 customers in private preview, what are they trying to solve? Like, are they piecing together kind of what I just described, and that's why I'm saying I don't want to lead the witness. But are they trying to think of, well, how do you use Informatica together with the enterprise data using CLAIRE GPT as the front-end interface to solve? 'Cause just saving hundreds of hours of engineering time, that's not, that's great, but that's not the end state, I imagine. So, you know, there, that's the question. Thank you. Let's break it into. Why don't, Jitesh, you share some of the stuff that our customers are doing in the preview, and I'll kind of, kind of contextualize the conversations we are having, Howard. Yeah. From a preview standpoint, CLAIRE GPT is really about enabling, democratizing access to data management and data, to enable organizations to be data-driven and drive digital. Period, end of story. Now, what's unique about CLAIRE GPT is it's not just for data teams. It's, in this case, it was a marketing analyst. A marketing analyst that previously would not be able to be data-driven, that would have to rely on multiple organizations and multiple functions. So our customers' data teams recognize that they are a center of excellence to enable the line of business to be more data-driven. And what's super exciting about CLAIRE GPT is it's enabling that end user, that wants data when they want it, to be super productive, get access to that data in minutes. Equally, for data teams to leverage IDMC to train their own large language models, to take the power of large language models and fine-tune them for specific use cases for their business and for their respective customers. Use cases and architectures like RAG, as well, as well as fine-tuning of multiple large language models. All of it requires IDMC marrying out-of-the-box large language models with enterprise data from that specific organization. Howard, if you can take a few steps back, there are two ways to look at it. While the team showed you a demo 22 weeks, in a lot of cases, customers don't even know where to begin and how to do and solve that problem. And what happens is that either they solve a narrow problem, or they basically solve a problem by throwing tremendous amount of bodies and a lot of time. And I'll give you an example. We're talking to one of our customers, which basically is a very large insurance customer, and they have obviously reimbursements. And one of the issues for them is, you know, either they make mistakes or they have fraud that they have to protect against. When they go about it, as you can imagine, it's a very manual process, and sometimes they don't even know where to begin with, and it may take years, and it can bring lawsuits also. Stuff we saw in that was, like, literally an automated process to do things like this, where they can save $ hundreds of millions in terms of whether it's a fraud case or not, or whether they've missed a particular claim or not, which can cause them a lawsuit later. So I think it's in two categories. One is, customers just don't even know where to begin, but they want to do something, and then they see the amazing productivity. And make no mistake, there are so many innovative projects we see customers want to do in the world of digital transformation. The biggest challenge I see, last I checked, and I talked to our own CIO, Graeme, over there, nobody's getting a budget increase of 10% or 20%, whereas everybody wants to do 10% or 20% more innovative projects. So being able to do things you could not do before is one part of it, but saving tremendous resource pool to go do those things is a tremendous game changer for customers. And then, stuff they cannot do at the scale we have is a whole different thing that Jitesh talked about. Noah? There's a mic coming. There's a mic coming. Hi. Thanks. Noah Herman with J.P. Morgan. I thought the announcement with the integration with Microsoft Fabric was really interesting. Just curious how that came about, and, you know, when should that be expected to roll into the platform in the near future? Thanks. So, first of all, this is not our first announcement with Microsoft. They're a very strategic partner for us for many years. I mean, if you guys have noticed, last many years, Scott's come to Informatica World. He was there in a year before. He was also there during the COVID years. We've talked about a partnership, and each year, we've just only scaled and scaled and scaled. So this is not the first time we landed doing something with Microsoft. In fact, this is a testament of the deep strategic product and go-to-market partnership we do have, which culminated into... And in fact, last time he was there, we talked about this at Informatica World, where you'll see IDMC natively integrated on Azure, and that's what led to this. So as they were thinking about Fabric, which is a big announcement of Microsoft, their BI, Power BI, their own data warehousing capabilities, they need a partner of our scale to bring all of that data into all of those things that they want to do, and that's where they depended upon us. I'll let Jitesh share some of the specifics we have, but this is not our first, this is many, and it's now become a big one. Yeah, the goal has always been with the partnership to provide seamless experiences for our joint customers, our joint users. And with Fabric launching at, at Ignite, couple of weeks ago, key element was provide the power of IDMC, specifically around data quality and observability to start, as a seamless experience for, you know, the hundreds of thousands of Fabric users. This is something we will be launching and releasing as generally available in the first half of next year, and we're in active discussions to explore other common use cases that, our joint customers and users can benefit from, in data quality and observability, as well as other best data management products on our platform. And you should have seen our announcement, we're also gonna be partnering with them very closely on a lot of common AI use cases, because they are betting big on this, we are betting big on that, so expect more to come in that area. This is a very strategic and a very rich partnership. Great, I don't have any questions online, so thank you. We have another Q&A session in the later in the afternoon. So thank you, Amit. Thank you, Jitesh. Thank you all. Thank you. Paycor is a human capital management software as a service company, so we support things such as payroll, time, talent, and recruiting. Data is really important at Paycor, from the executive level all the way down to the data analysts that are putting those reports together. It's really critical that that's aligned, and that really helps us to get our executive committee aligned so that they can make decisions faster. Every single week, we align on what kind of KPIs are gonna go to the executives, and there's a lot. But we couldn't do any of that if we didn't have the data foundation that's enabled by Informatica. We can do pretty much anything with the data, and anytime there's a change or a request for something new, we can turn that around in minutes. So we have really reduced some of the data wrangling times by, you know, as much as 90% in some areas. At Paycor, the typical reporting cycle was monthly or more than monthly. Informatica changed the game for us. Paycor has aggressive growth goals, and we need to make sure that whatever we're using, we can grow into. We acquired Snowflake and Informatica to be our data platform. So Informatica and Snowflake both are growing as Paycor grows, and that's really helpful to know that they're gonna be able to scale and support our needs today and in the future. We have a variety of enterprise applications for managing our business. We have call centers, we have homegrown applications, and all of that flows directly into our data lakes in Snowflake via Informatica. So we're able to do quite a bit of this work with a relatively lean team, and so we can actually have just a few data engineers manage this entire platform, and that really makes a difference. Paycor is really focused on making sure that we have the right data, and what that does is it really enables Paycor to bring our strategy to life. Now, please welcome Chief Revenue Officer, John Schweitzer. Good afternoon. Thrilled to be here with you in the room, and of course, those of you online. This journey that Amit and Jitesh have talked about is absolutely pure gold for a salesperson, and certainly as Informatica's CRO. What this tells me is that we have big time to market advantage in things like metadata system of record, the best AI capabilities available today. But in a bigger perspective, a bigger view, when you could take to the market the best products to handle all use cases and deliver on the only platform that's AI-enabled, and attack all data types in a multi-vendor, multi-cloud, hybrid way, nobody else does this. Pure gold. I promise you, my salespeople wake up every day knowing that they can attack this market in a very confident way. So I'm gonna put the lens over with customer and partner for everybody. And let me just start with this: when I joined about three years ago, I remember meeting Amit for coffee, and he says, "We need scale. We have amazing tech. John, you have 30 years of experience in data, databases, and data management, and analytics. We need scale. We need your help." And what I found was a great organization. You're gonna hear from my partner in a minute, Ansa. But together, we created a set of systems and processes that enabled scale, cross-functional collaboration, that focused on customer value. Turns out, when you deliver successful projects, your customer will buy more from you. So we focus on customer value, delivering very successful outcomes across use cases. And what's in it for Informatica? Well, cloud growth and predictability. We understand how to sell. I'm gonna walk you through this in just a little bit. Our sales strategy this year is really focused in four areas, and this is enduring for the, for the next several years to come, I might add. Customer-focused go-to-market, scaled coverage, simple pricing model. You've heard about it. I'm gonna dive into why it's really magic. And then our unmatched partner network, and how we use that to amplify and multiply everything that we do here. Let me start with customer focus, business model. Look, I've known Informatica for a long time. I've probably known it for 30 years, and they built, we built a great business on focusing on IT, delivering for IT, IT operations, data stewards, data wranglers. ETL innovated for 22 years, as you heard. But in order to get the cloud growth that we need, we need to tell them how to use our products and why it's important, and why and what use cases are important as our customers in develop these cloud journeys. So we started to focus, and build, and cultivate a community of CDOs, which today is hundreds deep, right? We're really engaged with them, but we also focus on line of business leaders, where the money is, marketing, finance, sales, et cetera. That opens up use cases. So we focus on these persona relevant use cases, all with a business value framework. We train our salespeople on it. We train them to talk in the language of customers, to talk about business outcomes and stories that bring your data to life. That's why I love this. My sales team loves this moniker. They do, because when I tell my kids what I do, they look at me cross-eyed. They They say, "What does that really mean?" What I find myself doing is talking about the business outcomes, right? We help one of the world's largest retailers improve same-store sales and wrangle all of that data into one place, deliver it in the cloud in a very clean, trusted data format. My kids start to understand that. So the other thing we've done on the industry side is we've organized our company and our go-to-market around industries you see here. Not all of them, but the ones we feel we have momentum in. I'll talk about the sales structure here in just a second, but let me be really clear, we land fast on a use case. We make sure our customers are successful, and then we go get the next one, and the next one, and the next one. What I've found is about the third use case or so, we are in the right to have an enterprise conversation with the CIO or the CTO. But it takes a couple of use cases, right? It takes that time to build trust. So scale. We're a global company. We, we transact in more than 70 countries. You could see here in the orange, we have an acute focus on the high cloud growth countries and markets. And we don't ignore the other ones at all. In fact, we go to market there in the blue with partners. Takeaway here is we're global in scale, and, and we're prepared better than anybody in the market to capture market share. Okay, this is kind of motherhood and apple pie a little bit. Everybody's seen these kinds of structures. We're focused, we're still maniacally focused on the Global 2000. There's enough gold in there for us to grow the business, as you'll hear from Mike in a bit. We have the lens of industry. We enjoy about 45% penetration in the Global 2000. So what that means is, I organized a focus on net new logo wins, net new customers. We go after those every single quarter, and then we expand, right? We got a lot of white space to upsell and cross-sell into the install base. Maniacally focused on Global 2000. In commercial, we take a more digital approach, more scalable approach, an approach that is more transactional, but a good business for us, right? All along the way, we're going to market with partners, you see on the left. I'll lead into partners here in just a second. Critical. We're a piece of the puzzle. We're not the entire, the entire puzzle. So I'm gonna share a little story about IPUs. This is one of the secret sauces of the company. It really is, and I know Jitesh talked about it a little bit more. What we were doing prior to deploying this was selling just like all the competitors do today. They sell a point service or product, and they. You license it, and in some cases, you pay maintenance on it, or you pay a subscription, it doesn't matter. But the little dots signify all the different transactions that are probably happening. What's different about an IPU for us is you buy one token, one thing, and you can use it anywhere across all of these eight products that Amit and Jitesh talked about. Here's the story. Not long ago, and this happens often, literally last week, a customer called in, and my, you know, my sales team, we were doing a review on a transaction, and they said, the customer, one of our really good customers, says: "We're gonna launch an RFP for catalog. We trusted you and Snowflake to lay down the data pipes, and we're good. But now we want a catalog and governance strategy to overhang our new cloud data strategy." And I stopped the meeting, I said, "You need to go back and just say, 'You already own, you have the capability.' Let's just do a proof.'" And I get my pre-sales team in there. And that's exactly what happened. No RFP. We continued our journey with that customer. So competitive box out is real, it's something that my team is excited about, and it's something IPU enables. Partners, we don't get anything done without them, right? You're gonna hear from Dave Kucher, from Deloitte in a minute. Thank you again, Dave, for being here with us. It's often that we don't only work with one of these great brands, we work with multiple. One example, I was just in London not long ago, and we were working on a transformational project with one of London's biggest, or U.K.'s biggest, car manufacturers, who are moving from legacy cars and you know, combustion engine to EV. Great strategy, multi-billion-dollar strategy at the board level. But they forgot that early on, regulation required tracking and traceability of batteries. So they've got these cars going out on the market, no tracing. It's costing them millions and millions of dollars in regulatory fines because they don't have a solution to bring all the data in. That was our first use case. It was brought to us by TCS. We've worked with Snowflake and AWS to deliver the solution. We give a total program overview for the executive staff, they're just outside of London, and today we're working on our second, third, and fourth transaction with this customer, starting with mission-critical battery traceability. Right? We're changing. We're changing how business runs, we really are. So just a little deep dive on ecosystems and GSIs in just a minute. Sure, we have a line go-to-market and a line training with our partners. Yeah, we just launched another new strategic partnership with Mongo last week, and I'm certainly really excited about working with Cedric, their CRO, on the go-to-market elements of that. But I guess to really bring this to life, there's another story, a healthcare company here locally, who really wanted to bring patient outcomes to a different level, and this transaction happened to come directly from Microsoft, where Microsoft said, "We're uncertain of the complexity of this, and we think we need you." So we engaged with Microsoft and Snowflake again in this case, and not only did we bring together a comprehensive solution for the customer, but we delivered it on the Microsoft marketplace, and that deal went from x to 10x. Now, follow me here for a minute, for a second. On marketplaces, where we transact every day. By the way, year over year, we're up 300%, I understand from my team, on marketplaces, marketplace transaction. What that means is we get access to budget in a really efficient contracting approach and process. So we got access to more money, we got access higher for a strategic project, and we got the project done quickly because the terms and conditions were there with Microsoft. We leveraged all of it. It was beautiful. We're doing this more and more every day. GSIs, critical to shaping the vision for our customers, what the possibility is. They're inspiring our customers before we even show up. But when we do show up, we show up together. In a particular case here, Deloitte brings us in in June into one of the world's largest life sciences companies, and at the end of the day, it's an AWS and Databricks solution, you know the one, where we're wrangling very significant disparate data everywhere. That's a mess, but it's external. We got third-party syndicated data coming in, and they not only want it complete, but they want it trusted, and it needed to be ready for drug distribution and increasing time to market for drugs. So just another example, but listen, there are three things that we focus on here I want you to take away. One is certifications. We have to enable our partners to understand how to position what we do, so we teach them, and then we teach them how to implement. So get this: we certify probably more than 10,000 now, Richard, 10,000 year to date through the end of Q3, practitioners globally. 10,000. That's on top of the thousands from last year, by the way. The scorecard really is down to two metrics: sourced and co-sell. Sourced meaning, how much business actually came from a partner? You know, I mentioned TCS a minute ago, Deloitte. 32% of our business year to date through Q3 was brought to Informatica by a partner. You know how excited my salespeople are about that? They're pretty excited. Now, leads don't just fall out of the sky all the time. Don't let me. They're gonna make me increase my forecast if I tell them that. But it's, it's just, it's magic. It really is. And then co-sell tells us the connectedness and the teaming. We track all this in Salesforce. Are we teaming to close and work with Deloitte or others along the way? And 71% of the time, we are doing that. It's another metric that's highly important. It tells us whether or not we're successful in working with our partners. Okay, so these four things: go-to-market strength, coverage, unique pricing approach, and our unmatched metric. Just, that's the magic that I talked about, the gold at the end of the day that really, I think, makes us special. Let me just move quickly to some more customer results and give you an idea, and then I'll wrap up. But, this cloud-only, consumption-driven, go-to-market strategy is delivering really strong business outcomes for our customers, as you can read here. There's a couple of examples that I'll give you, but underneath each one of these logos is a story. I can look at this and remember a lot of trips, travel, boardrooms, customer offices. Each and every industry has its own focus, but we're covering all of it. And we're also covering all geographies to bring these stories to life. We really are. One of them is, you can see here, a pharmaceutical company where we had just a pretty common situation where we had—they had limited visibility, data being stored off-site, in the cloud, sorry, on-site, offsite at third-party locations. Really complex and costly to bring together. Not only that, but it wasn't trusted. So obviously, the solution in a cloud integration sort of way with trusted data now that is cataloged and managed, it delivers an outcome. Here, you get to see improved data drug discovery and decreased third-party costs, as those third parties were syndicating data in and charging this pharmaceutical. So they're able to save millions of dollars that way, too. The other side of the story I just want to point you to is this land and expand story, a picture here in this graph. We started doing business with this company in 2017. That was the first land. You can see it was minute. Today, fast-forward, we have about $7 million worth of ARR. Everything in between those little steps were new projects and new products. And to me, that graph, that up and to the right, when it looks like this, they trust us. They trust us to deliver. And when that happens, ARR and this customer goes up, the wallet share increases, and that's goodness for Informatica. Similar story, just a different customer. The thing that's interesting about this one is the modernization hasn't even started here. So this is cloud-only. Started with cloud-only IDMC, focus on inventory risk and minimizing write-offs, millions of dollars worth of write-offs. We need to again, once again, lay down some modern data pipelines with our partners to achieve sort of just-in-time inventory for their distribution channels, to decrease inventory obsolescence of, you know, most probable. But here, this is IDMC growth, and in 2023, I can tell you right now in the moment, and next year, we will then modernize their PowerCenter state. So this customer started from a much different place than others, who sometimes start with modernization. Okay, I'm gonna pause for a minute. Let's listen to Yamaha's explanation of their partnership with Informatica. My name is Maninder Mann. I'm a Senior Manager at Yamaha Motor Corporation. My name is Soumya Shetty. I'm E-commerce Application Manager for Yamaha Motor Corporation. I'm Anand Hir, and I am Group Manager for Yamaha Financial Services for Data Analytics. We want to build the One Yamaha brand, and not only to the customers externally, but within Yamaha as well. I would call One Yamaha as a movement rather than an initiative. Yamaha, as a company, is a great cross-pollinator. We have a lot of people moving around, establishing all the skill sets and all their legacies in different business units. My goal is to establish, like, a data intelligence platform. So we took that approach to see how we can bring synergies between different teams and set up this one unified platform as Yamaha. We did select IDMC as our one unified platform in line with the One Yamaha initiative because we see how different systems, different data sets, different sources of data can talk to each other, and we can bring this into this unified platform. The plan for us is to really grow our middleware and standardize that across the organization, making an enterprise-wide solution. We had different reasons to transition to the cloud, digital transformation being one of them. The way Informatica has moved forward with cloud and IPU, it's been an easy transition to that and how we can really leverage IPU and take advantage of different modules within that, so it's been great transition. Informatica not only helps us with the data integration, but also the goal is to use Informatica to do application integration, Data Cataloging, and all the other cool stuff that we have with that platform. There was very little initial investments required in terms of the infrastructure and setting up, so it really gives us a scalable solution, which can be scaled up and down based on business requirements. These are the kind of examples on why we want to go to the cloud and why we want to partner with companies like that and bring products in that allow us to be more flexible and really speed to market so that we can really push the One Yamaha initiative throughout the company. In my recent project, we used IDMC to make it a real-time flow. The positive business outputs for this project was great customer experience. We had less order cancellations as we moved from a complete batch to a real-time processing. The fact that we could implement Informatica Cloud within two months and set that up for all the real-time order taking from the front end to the back end systems was amazing. So another great story. We're super proud to partner with them, too. They own just about every service we deliver to the market. So that they're on their journey. We're super proud. I, I think the, the final comment I just want to leave you with on the Infow ay is, I've talked to you a little bit about selling. I've started to get into sort of the adoption and consumption of what we do, the land and expand part. I'm gonna give this, you know, next time to, to my data and customer homie, Ansa, to walk through what it really means to close the loop on the Infoway. All right, Ansa. Here we go. Well, thank you, John. Good afternoon, everyone, and a big hello to the folks on the webcast as well. I thought John shared some great stories. I thought I'll recap a conversation I had yesterday morning. This was with a prospect, a global 2000 company based in Denmark. I think the world's largest renewable source company, they make energy through wind. I was on the call with this head of business transformation, and this particular company is embarking on a large digital transformation where they're looking for a partner, not a supplier. They were looking for a partner to drive their growth initiatives and operational efficiency. In my 30-minute conversation with him, all he asked me was two: "Can I count on Informatica to have joint ownership and accountability?" I said a big yes. said, "That is what we do as a company." And then he closed the call by saying, "This is going to be a massive opportunity for both of us." Keep in mind, this is a prospect, a net new logo. I'm counting on John to sign this transaction this quarter, and I'm sure he will. But today, you'll hear me talk about how we make this promise a reality for our customers. My brief presentation today is gonna be centered on three areas. One, how we tailor the right customer engagement model to drive outcome for our customers. Second, Infoway, our consumption operating model, wherein we will unlock business value for our customers. And third, drive net retention and growth. As we drive consumption, we have seen great success in expansion, and we also have a program to reduce churn. Net-net, growing NRR. Now, you heard Amit talked about our journey to be a modern cloud leader. I echo everything he said. I'm just gonna repeat something he said, the last eight years has been truly transformational. What we have transformed from a single product company to be the one leading data management platform. And I can say a big yes with a lot of conviction, the only reason, I have been in this company for 28 years, and I have seen this journey, I have lived this journey. I still feel like we're just getting started. We are also the leading data management choice for the enterprise. You heard Jitesh talk about it in great detail. What is our strategy around delivering customer experience and outcomes? The customer is at the center of everything we do. Our charter is to connect our best-in-class product offerings to customers' value. That is the job of 1,800+ people at Informatica, to connect our product offerings to their business value. This has been the center of everything we do. It has always been about creating a long-term position to grow customer lifetime value. What is the operating model behind this? John previewed Infoway. This is our flywheel. It's no longer sales team, it's no longer post-sales team, it's one team to drive value for our customers. When you drive value for our customers, consumption goes up. We discover more use cases. John had many examples. He shared a few today. This flywheel is unique to Informatica. It is operating at scale. What is the underpinning of this operating model? I'm gonna talk about three vectors: our customer success model, how we have AI-powered customer engagement, and then how we drive expansion. We have 5,000+ customers. Not all customers are the same. Complexity, the number of use cases varies by customer. I have seen so many customers who start off with one point solution. In a few years, they make Informatica as a standard for data management. I have seen their journey over and over again. We have a great segmentation model, which a great blend of CSMs, people assigned to accounts, and a great digital platform to drive customer success. You know, and I wanna double-click into the customer success playbook. It's all around alignment, something which Informatica does well, which other enterprise companies don't do a great job. And the reason, one reason I'm saying that is. When you talk about a partnership, partnership is all about alignment. It's not about firing up the product and starting to code right away. We spend the time to understand what the outcome is needs to be driven. The partnership is about agreeing to the customer what they expect of Informatica, and me telling the customer what we expect of them. That is the partnership which we have a great playbook, which is repeatable. Once we align, we work with the partners, or work with the customer, or sometimes our professional services, we are well on the way to driving value for the customer, and we open up more opportunities for expansion as well. At the end of the day, it's our intent to make every customer a referenceable customer. And, modernization is a big growth driver. Success of modernization is even more critical. 18 months ago, we set up the Informatica Migration Factory to do modernization at scale. Our products drives 90% automation to convert PowerCenter assets to the IDMC platform. Now, we are operating at scale with partners being in a position to drive modernization as well. So this is a program which is running well at scale. We have this in play for PowerCenter, and we are starting off with MDM modernization as well. Now, I talked about, you know, we have the best-in-class platform to drive value for the customers. It's a blend of people, technology. Let me show you a slide on how—what's the digital backbone at Informatica? Any exec in a company would want to know the answer to the question: Is this customer on track to realize value? I challenged the team. I want that question to be answered. Is the customer on track to realize value? You could ask the next question: Is this customer sticky? You could ask the question: Is this customer referenceable? You could ask the question: What new use cases can I next sell to this customer? Guess what? We have an intelligence platform at Informatica, which can answer those questions. This was built by Informatica in 2018. The reason we built it, because there was no product out in the market which could help us do it. It was built by Informatica. Even more cool, it's built on Informatica. And what's more exciting to me, working with Gautam and team, the next release is gonna be powered by CLAIRE GPT. This is our secret sauce for scale. If my words is no proof, just a couple of weeks ago, we received a patent for this application. Two weeks ago. So I'm highlighting this to show that we have a great platform to operate at scale. What are the results showing up as we drive consumption, opening up more use cases for expansion? You can see that in the results. Nearly one in three customers have an upsell tied to their renewals. We are doing more IPU expansion, and our cloud NRR at the end of Q3 is 118%. I just feel like it's just the beginning. I think the fruits, Amit said, "You know, the results of all the hard work is starting to show." I fully expect this number to go up. I could say a lot on how we drive value for the customers. What really matters is what this—what do the customers say to us? This is our track record for customer excellence. We have solid renewal rates. Nearly 78% of our customers on their support interactions gave us a five on five. That number says 75, Amit, the latest number is 78%. I'm not sure how many enterprise software companies. Let me tell you, there's no data management company which is certified by J.D. Power. Not one. We have been certified three years in a row. If there was a Magic Quadrant for customer experience and outcome, we will be there, right there as the leader. There's no quadrant for that. We are proud of everything we do. We feel like the team, as part of Informatica, we are working for the customers, not for Informatica. In closing, Jitesh used the word force multiplier. I'm going to repeat that word. We have the best-in-class products. Informatica is the force multiplier. Because of our unique scale and experience, we're gonna drive customer success and growth in our cloud-only, consumption-driven go-to-market. Somebody asked me, "How would you summarize your presentation in six words or maybe seven words?" He gave me 30 seconds, and I know some of you are taking notes, so I'm gonna leave you with those seven words. Simple words: Customers love us, and we are sticky. Thank you. Love to hear from you as how you see the state of the partnership today and going forward. Yeah. Well, I mean, I think to be successful in any, you know, really data-led cloud journey, you need really to have trust, you need guidance, you need the capabilities to really address the most critical data challenges. And the deep integration and strategic partnership between Informatica and Microsoft is really driving success, you know, as you can see, all these logos, in terms of a very broad customer base. And this logo slide is really testament to kind of the commitment that Microsoft and Informatica really share to work closely with our customers every day, to help them expand the art of the possible, when it comes to data for both their employees and their own customers. Yeah, this is a really great partnership, and we've been partners with Informatica for years. We have thousands of customers using the combinations of our products, and we're truly both best of breed in our spaces. And, you know, Oracle, great product, great database technology, Informatica, great data integration technology, and together, we have a great platform up in the cloud, all cloud native. And it's just a great combination for all of you, hopefully, to benefit as you modernize your infrastructure in the cloud. Informatica, in December of last year at AWS re:Invent, received the 2022 Global Design Partner of the Year. So I mentioned that we have over 100,000 partners in the AWS Partner Network, so it was amazing that, that you, We were so proud that you won that because it combined the data governance architecture that we kept hearing about, the Intelligent Data Management Cloud with AWS Lake Formation, and so that allowed users to be able to access the governed data lakes in AWS and make those data-driven decisions that they need to make. It's an incredible time for our partners. We have very exciting times. We love how we have a joint value proposition for our customers. This time, a lot of the focus was around data governance. Right. We love that Informatica has, like, the full life cycle of data. It's not just about extracting, and loading, and transforming data, but the rest of the life cycle. How do you think about data quality? How do you think about metadata management, master data management? That's the focus of the partnership. We're very excited. Now, the great partnership with you has been helping people make it easy to move their data, to govern their data, to manage their data, and the combination of your tools and ours have allowed many companies to understand their data and get value from it quicker and easier. You know, Informatica has really been on this journey with us, bringing IDMC to deliver, like, cloud-native, simple, low-code, no-code solutions for ETL for our data engineers, and data analysts, and other data professionals so that they can basically take advantage of kind of the best of both platforms. It allows you to build, you know, start small with transformations, but also scale elastically to deliver those PB-scale workloads that are sometimes needed for these big ML projects. Please welcome to the stage Richard Ganley, Senior Vice President, Global Partners. Hello, good afternoon, everyone, and hello to everybody joining online. Well, you've heard a lot about many of our customers and partners today. You've even heard on the videos from some of our customers and partners. I'm delighted that we're now gonna be joined in the room by one of our customers and one of our partners to talk about their journey with us. Joining me today, first up, we have Sandeep Sahota, who is the Enterprise Chief Data and Analytics Officer with BMO. Sandeep has spent 3.5 years with BMO and was previously with BNY Mellon. I'm also gonna be joined by Dave Kucher, who is a Managing Principal, Global and Strategic Business Initiatives at Deloitte. Dave has spent more than 30 years with Deloitte. He's overseen their technology, strategy, partnerships with a great focus on data, AI, cloud, and cyber. So without further ado, please welcome Sandeep and Dave to the stage. Thanks, Sandeep. Hey, Dave. Take this side. Okay, so Sandeep, we're gonna start with you, first of all, and we're gonna tell your incredible story. If you can just take your, take your mind back and go right back to the start of our journey together. What were the key business problems that you were looking to solve with Informatica? Well, it's really back to 2020. I'm not sure I wanna go back to 2020, but I will for this moment. Listen, I think what you heard from Amit earlier about fragmentation, it's real. Data fragmentation is an issue in many organizations, and if you're a complex organization, not only is the rate of data growth happening, but the fragmentation itself is a real challenge that you have to deal with. The second, it's really data management first. A lot of organizations talk about data governance. The framework is around governance, but it's management first, and you have to get that right. And really, for us, as a complex organization with a lot of diverse businesses working with data, it was all about: how do we give them diversity? So solid core, flex edge, that was the core operating principle. And what can we give them in terms of a solid core foundation for data management and data practices, and how do we allow for the right flexibility across the organization to get value? Those were the three areas that we were focused on when we started the journey. Fantastic. Could you also maybe describe what it was like at the start of the journey, really before, you know, what was the situation like before you had IDMC, and then contrast that with afterwards? Kinda give us a real picture of that before and after. I mean, look, I'll offer the biggest proof point, which here in California, some of you may have noticed, we just completed an acquisition, Bank of Montreal did, of Bank of the West, and that acquisition, 23 months in the making, was all built on a core foundation of that strategy, was a data migration. Ultimately, 2+ million customers, 2.7 million accounts. We now have a presence in 32 states. All of that was taking the technology that existed at Bank of the West and moving across all the data, PB of data, that was central for our future combined bank. We couldn't have done that without the capabilities we have in place through IDMC. And I'll, I'll give you a couple of examples. When people think about data quality, now you imagine you're moving 2.something million customers over to your platforms, you have to understand, who are these customers? What do we know about them? And traditionally, you get a score, or you get some view on, this is what the quality of this information looks like. For us, that was a proof point on the operating model around the data. And it was looking at that data set and saying: What is the operating model? How are people using it? How are they cataloging it? How are they actually entering it? What's the technology around it? Do we need to think about the process around these data sets? The way I'd contrast it is, you know, this acquisition, for us, was a proof point that we can migrate content from one organization to another, really accelerate our growth strategy, and focus on the fact the data itself was the key ingredient. We left all the systems at the finish line and walked away with the data integrated into our platforms, offering a combined experience to our customers, and that was the key distinguishing factor. Good customer experience, built on our capabilities, strong data assets, all linked to provide that value. Amazing. By the way, you've done a fantastic job with the acquisition. Your brand is all over California. You cannot miss it. Everyone knows what BMO is now, I guess. So what is a BMO? Just BMO. BMO. When you think back to the selection process, and you were sort of looking at the way forward, what were the criteria that sort of led you to IDMC? For us, the core principle was solid core, flex edge. Give our businesses as much flexibility as we can. Have the principled conversation about what gives us the strongest solid core possible. And for us, Informatica was the biggest Swiss Army knife, except you made no compromises. Every aspect of that knife, that Swiss Army knife, gave you industrial scale, and we wanted that optionality because with that, we could drive that solid core and allow for flexibility in the businesses. We didn't wanna have this institutional conversation about whose tool is better or how does it work? We wanted everything that was there and integrate it as quickly as possible. And through that integration, it gave us the opportunity to really drive the acquisition forward, as an example. It gave us the opportunity, to the earlier conversation about AI and utilizing new emerging capabilities, that's the fastest path to value. And what IDMC offered us is that opportunity to build a really solid core and continue to evolve it as new capabilities show up. And that, I think, has been really the key launch point for our program, and with this proof point of the acquisition, with continued work we're doing in customer experience-centered capabilities, especially around emerging concepts, it, it's really been a forward, a real positive forward move for the organization. Amazing. It's amazing what you've accomplished, and impresses me that you bought IDMC, and then the acquisition came afterwards, so the order is very important there. So now that you've done this, you've eliminated several non-scalable manual processes, you've enabled an enterprise view of your data, you've democratized the data, you've put it in the hands of people in the business on a self-service basis, so what comes next? What's next for BMO? So it's growth. We're really centered on our growth, and our growth is gonna come from our customers today, future customers that we're able to acquire, but more importantly, generating the kind of customer experience that'll be central for our journey. So we've really anchored on our marketplace. So we have a data and analytics marketplace that's available for all our, all our employees to be able to drive execution and value, whether that's new modeling, AI, ML, whether that's new datasets, curated datasets. How do we accelerate the path to value? How do we get that in the forefront of the opportunity as it's happening? So while we are looking at the marketplace and thinking about the current wave that's happening with GenAI, we're also thinking about, how do we ensure that we can take the next wave that's coming? We're not sure what it is. No one's really certain, but it'll come faster and faster. Data management first, get an offering around data, ensure that it's fully integrated, gives you the opportunity to drive value through analytics, and ensure that we can keep up with the pace of change. That's really what's next. Great. Congratulations. It's truly amazing what you've accomplished. Congrats to you and your team. Thank you. Dave, let me turn to you now, and let's talk a little bit about the Deloitte partnership with Informatica. We've had a strategic partnership now for 17 years, but we've really doubled down over the past few months. Can you talk about why you chose us as one of your strategic partners? Yeah, well, it's, it's both an easy answer and a long, extended answer, because when we meant—when you say partnership, for us, it's actually multidimensional. So we also are a, a global customer, and proud and thankful of that. We've got, as a company that's almost $70 billion in size and over 400,000 employees, that operates in almost every country in the world, getting to data quality, data management, data standards at enterprise scale is extremely complex. And so, some of your charts that you showed previously about sort of landing, developing the use cases, proving those use cases, such as data management, data quality, we're very much one of those hockey sticks. As that foundation now expands, and as we drive towards more interoperability and then better use cases of that data, the foundation expands as well. So that's one as a customer, and then as a partner, what is really exciting. So again, with a company the size and scale as that I mentioned, nearly half of our revenues are generally done in conjunction with one of our ecosystem partners, and they're very much similar to the ecosystem partners that you outlined there. And oftentimes, some of those partners compete with one another. What's really unique about Informatica is that you're a complementary part with almost every one of those partners. So our teams in the field don't have to drive choice or have our clients drive choice. It's actually easy for us to bundle with the ecosystem. So where the entry point comes directly from Informatica, or the entry point comes the client doing something else, it's an integral part, so it can be a natural extension and allows us to integrate some of those solutions faster, so our clients can get time to value faster than that. And then the third is, we actually build some of our solutions on top of your platform. And so it allows us to offer data as a service, whether it's our client's data that we're giving to them cleaner, more accessible, higher quality, or whether they're incorporating ecosystem data with their own data into how to use it for best managing their desired outcomes. So it's a multi-pronged partnership, but all those are really important. Awesome. That partnership you spoke of there, Dave, that kind of strategic ecosystem, could you bring it to life a little bit and maybe mention some of the other partners who are part of that? Well, as I mentioned, all the logos that you had on there are really significant partners for us. So again, with about half of our revenues being in conjunction with those, and about 90% of that mix of revenues are from our top 12 or 13 partners. So there's a really high density, and Informatica is one of those as well. And so again, the interoperability with those ecosystem partners allows us to serve our clients more holistically, and again, with multiple entry points to bring the solution to bear. Fantastic. So I know our partnership goes, it's been, been existing for many years, it goes very deep. Can you maybe bring it to life with a few key numbers, a few key metrics for us? Yeah, well, I think I'm proud to say that just over the course of this year, I think we've passed now 500 joint clients that we have served together across the globe. I believe we've passed over 6,000 now employees that are either fully certified in the Informatica stack or are very proficient executors and implementers. And again, I think those numbers are just gonna continue to scale because it is very much that hockey stick where we're seeing more and more momentum. Fantastic. And, it's obviously been, we've talked about this a lot today, an amazingly exciting year for AI. But what, a s you meet often with customers, and what are the things you think people could be doing now to prepare for what's coming next? Yeah, I think many of the speakers today had talked to it. We've all been caught up in the AI and GenAI sort of flurry over the last year. And so there's a couple of things that are really, really important that we've both observed and are promoting. One, clarity of the use case, whether it's accelerating product innovation, whether it's taking significant costs out from either software development time or other operational processes, the specificity of the use case, and then the specificity of the underlying data that is gonna enable that use case. But when I say specificity, it's one, access to it, it's two, the quality and integrity of that data, and it's three, the sustainability. Is this a one-time thing, or am I gonna have access to this data continuously to improve upon it, to harness it, to take it to the next level? And so what we've seen with all of the, what I would say, pilots or proof of concepts that most of our client base are experimenting with on AI, what they're now realizing to go to scale with it, they've got to have the elements of that underlying data component in a really good place that they can be sustainable and scalable and trustworthy. Fantastic. Dave, thank you. Sandeep, thank you. Really appreciate the partnership from BMO and from Deloitte, and thank you both for joining us today. Let's hear it for Dave and Sandeep. Thank you. I'm Vamsi K rishna Dhalli, Senior Data Manager at NRMA. NRMA, it helps people move around Australia for over 100 years. It's a membership-based organization. For example, we have NRMA Parks and Resorts, our roadside assistance, and also like six rental car business. We have got around 3 million plus members, meaning serving the need on disparate channels. So everywhere it's about what is the best personalization you can do for the member to find the value for them. So where data is all siloed and fragmented across the business units. We would like to have a single data platform within the entire NRMA, so that we can connect better with our data, we can connect better with our customers, what exactly they are expecting, providing the best number value. Since we are heading towards a single data platform, we decided to have Informatica Data Management Cloud as a data management platform. What we have decided is let's start with small, which is, Cloud Data Integration, and then we jump onto the Cloud Application Integration, data quality, and also we are heading towards the metadata management and the rest as well. So right now, we are building a Customer 360 using the data quality engine behind the scenes, and also building some customer applications, based on the needs of the data strategy. Informatica, first of all, it has got built-in connectors to Google out of the box, Google BigQuery, easily connectable. So all we need to do is set up the simple configuration steps, and off you go. You should be able to build any kind of mappings or mapping templates. If you have to build any recommendation AI modules, how exactly that can play with. And also, we were sharing the same information to our end marketing channels. It used to be 10 days, we brought it down to 30 minutes. We are still five people, but still we are doing enormous amount of work. Just roughly like, you know, on a yearly basis, we are running $1 million worth of pipelines. Productivity rate has grown tremendously. It's all getting automated. We are no longer silo management tool or the orchestration framework. It's all sitting at one place, where we will be able to see all the operating information of all the loads and the pipelines at one place. That's how exactly Informatica is taking us forward. Now, please welcome Chief Financial Officer, Mike McLaughlin. Thanks, everybody. Over the course of this afternoon, you've heard from Amit, Jitesh, John, and Ansa about the transformation journey that Informatica has been on since 2015. You've heard about the strategy and vision that's guided it. You've heard about the significant amount of resources and the hard work that went into executing it, and you've heard about the transformation that it's affected across all parts of our business, including product, go-to-market, customer success, and renewals and expansion. You've heard from those folks, and you've heard from our customers and partners about why Informatica is the data management choice for the enterprise. We have the best products across every category of data management. We deliver it on the industry's only true cloud platform, and we serve the multi-vendor, multi-cloud and hybrid needs of the enterprise. Informatica today is ideally positioned to capitalize on the massive opportunity that exists in data management and AI. I'm going to spend the first part of my discussion today to talk about how we are delivering against that opportunity in three ways. First of all, we are winning net new cloud business, new workloads and new use cases from existing customers, and brand new customers who have never done business with Informatica before. Secondly, Informatica is the data management solution for the modern data architecture. You heard at length from Jitesh about how the product is architected that way. I'm going to give you some data about how the product is actually being used to prove that that is, in fact, what's happening in the field. And third, you heard from John, and especially Ansa, how, the IDMC with IPU-based pricing is a tremendously powerful expansion engine. Again, I'm going to give you some data to show how that's actually working in the field and how it's, that flywheel effect of the Infoway is increasing our net retention rate and delivering total ARR growth today and going forward. Let's start with the topic of net new. For those of you who've listened to our earnings calls for the last couple of quarters, you know Amit and I have been highlighting this in an approximate way. We've used words like, "Approximately 85% of our net new comes from new use cases and workloads." This is the actual data over the last four quarters, ending September 30th of this year. 83% of our NAR, our net new ARR, over the last four quarters was from new workloads, new customers. 17% from migration. Now, that 83% is net of churn, so the actual booking number is higher and closer to 85% or 86%. If you double-click into that 83%, 38% of that NAR comes from brand-new customers to Informatica. They've never done business before with us, were introduced to our cloud and started their journey with Informatica. Now, that 62%, we have over 5,000 customers, 65% of the Fortune 500, 44% of the Fortune 2,000. That's a great base that knows us and trusts us, and we're finding new workloads and new use cases with those folks on the cloud every day. It's a great source of growth. But make no mistake, we're winning net new customers every day. Both of those factors have contributed to what has been a very robust growth in the actual customer count on our cloud over the last five years, with a CAGR of over 11%. Let's talk about the modern data architecture. So as the company that effectively invented the category of data management over the last 30 years, we manage every legacy architecture you can imagine. Most of that is done on-prem, and those customers pay us for maintenance or self-managed subscription. However, because of the hybrid capabilities of the IDMC, we manage legacy architectures with the IDMC also. If you look at the actual total rows processed by the IDMC for these legacy data architecture targets, you can see it's about 39% of the processing power that's going into that today. On the other hand, if you look at the modern data architecture targets of Snowflake, Azure, GCP, 61%, and it's growing faster than the legacy data architecture targets. This is a really important topic, so I'm going to click into this a couple of different ways, and I'm going to go by modern data architecture environments one by one and show you how those are being used by our customers and how that's growing. Let's start with AWS, which is our oldest and biggest cohort among the modern data architecture environments. We were the data management launch partner with Redshift in 2012. Even that, as our largest base, has been growing at a 43% CAGR over the last two years. Our second largest modern data architecture environment is Azure. That's been growing at 64% CAGR over the last two years. Snowflake, 102% CAGR. GCP, 342% CAGR. And Databricks, from nowhere two years ago, growing today at an exponential rate, and that rate continues. There's another way to look at this. We can look at what our customers are actually using their IPUs for on the IDMC platform, and we can see, we can look at the modern data architecture solutions and use cases or products, if you will, that they're consuming and see how those are growing and being consumed. Let's start with Cloud Data Loader, loading application data, database data, files, and streaming data. That's been growing at a 201% CAGR since January 2022. Database Change Capture, another key modern data architecture action in the cloud, growing at 88%. Application Change Data Capture, again, a product that was introduced in late 2022, growing like crazy. SQL ELT, this is ELT, not ETL, right? Advanced pushdown, the modern data architecture way to do this. You can see that's growing at a very attractive rate. Spark ELT, it's another way to do ELT. Again, tremendous growth. Cloud Data Quality and observability, which is a key capability for today's and tomorrow's AI applications, growing very, very strongly. Finally, Cloud Data Catalog and governance, which, again, is going to be key in the world of GenAI and traditional AI going forward. The data is very clear. Informatica is the modern data architecture company. That's where we're winning, and that's what's driving our cloud growth. Third, let's talk about the expansion engine that is the IDMC. John and Ansa did a great job of talking about the IPU as well as, as well as Jitesh. So just as a reminder, it's a fungible token that our customers buy from us, and they can use that token to buy any of the 33 services that are available to them today on the IDMC. And thanks to Jitesh and his team, that number seems to grow every day. And to give an example of how that works, the consumption of the IPU is driven by scalers that are relevant to each service. So for example, elastic data integration consumes IPUs based on the number of compute hours that the customer uses. Data catalog is based on the number of data assets, etc. The beauty of this model is that customers can use the IPUs they already own, once they've launched and put into production their initial use case, to experiment with other services and products across the platform. They can do so in a way that doesn't require any contract or any additional commitment beyond what they've already made, and if they get value from it, they start consuming more of their IPUs, and once they, and when they do that, then they need to come back to us and buy more IPUs in terms of the contract, not only at renewal. All sounds great on paper. You heard from John and Ansa how, what the magic that it is for them in the marketplace. Let's look at some data to support it. Six-month anniversary is more or less when most of our cloud customers are up and running. Takes a lot less time for a lot of them, but by six months, pretty much everybody has implemented their initial use case on the IDMC when they make their first purchase with us. At that time, the average number of services consumed on the platform is about three. Roll the clock 12 months forward, the average number of services is almost double. So now this is the number of services consumed, not the number of IPUs consumed. That's growing, too. But that can be just because you're doing more with the stuff you started doing with us. This is showing that customers are doing that, but they're also doing more things with us that's consuming more IPUs as time goes on. All of that contributes to what we consider to be our best-in-class net retention rate. You can see that that figure for the cloud has stabilized in the 116-118 range in the last couple of quarters. It's important to understand that we define net retention rate in a way that's more conservative than many other, than many other publicly traded software companies do. This is a little bit technical, so bear with me. We define the measurement unit, the measurement cohort for NRR at the beginning of the period, it's usually a year, at the end user customer level. Now, a lot of our end user customers are part of larger organizations. So for example, a global bank would have one parent, and they'd have a number of regional operating subsidiaries. For us, each one of those operating subsidiaries is a measurement unit for ARR. A year ago, we then calculate how much that cohort is using today. If you were to define the metric, change nothing about the math or our business, just redefine the metric to measure on the parent level, which many other public software companies do, our net retention rate is 4%-6% higher, just structurally, mathematically higher if you do it that way. There's nothing right or wrong about either way; it's just different choices you make to define the metric. But either way, it is clear that the IDMC is a really powerful net retention engine that allows us to expand with our existing customers to complement the wins that we are making, the net new wins that we're enjoying in the marketplace. All right, let's shift gears, and let's talk about the go forward for Informatica. We want to take the opportunity of our inaugural investor and analyst day to give you a preview of what we think is going to happen financially in 2024, and give you an updated medium-term model about the trajectory of the business in fiscal 2026 and going into 2027. I'm going to start my discussion of this topic with an acknowledgement of the perception out there that Informatica is complicated. As a software transition story, you know, that's understandable and perhaps to some extent, inevitable. So I'm going to try to simplify it as best I can, particularly the top-line drivers, and give you some touch points and directional guidance, at the very least, about what's going to drive the top line of Informatica, and then we'll bring that down to the actual 2024 and beyond guidance that we're going to offer today. As you probably already know, our key top-line guidance metrics today in terms of ARR: our total ARR, subscription ARR, and cloud ARR. That's what you see in every quarterly result, and that's what we report at the end of Q4 every year. Underlying those three metrics, there are two more: maintenance ARR, which is complement to subscription to add up to the total, and self-managed, which is a complement to cloud, which adds up to subscription. I admit that's a lot to keep track of. Trying to figure out how five different metrics are moving is a challenge for anybody. It's really, though, three pretty simple categories: cloud ARR, self-managed ARR, and maintenance, all of which add up to the total. What I'm going to do is walk through each one of those one by one and give you some of the key facts and dynamics that drive them today and going forward. Let's start with maintenance. We have about 3,000 maintenance customers. They've been with us a long time, 10+ years, average tenure, and the average ARR per, per customer is $166,000. As you know, we haven't sold a perpetual license in a long time, and therefore, our maintenance revenue is going down because we're not selling more maintenance on perpetual revenue. If you look back at the last 12 months and the decline that we experienced in the last 12 months, it was about 6% of the starting period number. It's important to break apart that decline or that churn into two pieces. One is the non-migration churn, so that's customers who are no longer paying us maintenance because they went out of business or because the use case that they were using for us was abandoned. We don't lose a lot of these customers to the competition, but we lose them for exogenous reasons that are out of our control. The rest of the migration, which has been small in the past, is due to migration, customers that are moving with the migration factory or in Q3, we had eight customers moving with PowerCenter Cloud Edition from on-prem PowerCenter to the IDMC in the cloud. When they do that, they do so at what has historically been a greater than two-to-one ratio, and so it's not just taking money out of the left pocket and putting it in the right. It's increasing the total ARR of the business by at least as much as the original maintenance was to begin with. So now, how can you think about that going forward? We're not going to give you guidance in this level of granularity today, but I can give you some directional ways to think about it. That non-migration churn bar should continue to be at roughly the same rate that it's been historically. This is a very seasoned, very predictable base of business, and that 6% historical non-migration churn should be pretty consistent going forward. That's what we're planning on. Now, migration to cloud, you can see that that bar is a little bigger than it was in the last 12 months. That's going to accelerate. We're seeing that real time. You've heard about it, the IDMC itself is getting more attractive and more capable and pulling more people to the cloud, and PowerCenter Cloud Edition is making it easier to do. So that's going to be an increasing contributor to our growth in the future. It's still going to be a minority of our growth, but going to grow in importance. Self-managed. We have 2,751 customers. They haven't been with us as long, 5-year average tenure, because these are the modern products that we started selling when the journey began in 2015, and they have an ARR of about $205,000. Now, this business has started to turn down because we took those products end of sale at the beginning of fiscal 2023. If you look back at the last 12 months in a similar way to what we did with the maintenance base, there was some new in the bucket because we were actively selling it in Q4 2022, and when these customers were new, sometimes they want to stay on-prem for another cycle, and we get a price increase from them, and sometimes they expand themselves. So there is some positive that went into that bucket in the last 12 months. But the churn, the decline, we should think about it in the exact same way that we do for maintenance. There's the non-migration natural churn that happens to any subscription software business, and because this is a less seasoned group, it's going to be higher than the maintenance base. It was 11% in the last 12 months. That's a perfectly normal rate, and we think that that's roughly going to be the rate of that non-migration churn going forward. Migration to cloud, again, this is at an uplift multiple, so that bar being bigger is a good guy, going forward, and we expect it to be bigger going forward. Again, no specific guidance at this level of granularity today, but as you think about 2024 and beyond, there will be a small amount of new in this bucket, and that's almost entirely about price uplift at renewal for those who choose to stay on-prem for another cycle and if they need a little bit of expansion, ARR. But the non-migration churn, we think is going to be consistent with what it's been in the last 12 months, low double digits, and the migration to cloud will be an increasing portion. And again, every percentage point of that increase is good for Informatica. All right, enough talk about decline. Not very exciting. Let's talk about growth. Our cloud business, as you know, has been growing very well, 35% CAGR over a four-year period, 37% in the last period. In that group, as you saw before, we have over 2,200 customers with a relatively new tenure, still in the expand portion of their relationship with us, which is great. And almost a $250,000 average ARR per customer, and that average ARR is growing, reflecting our focus on the Fortune 2,000 and the large enterprise customer. So this is a growth business, not a churn business, so you need to think about it a different way. Growth starts with a large and growing TAM. On the left side of the page in front of you, you see the IDC-produced TAM for Informatica back when we went public two years ago. For the purposes of this session, we asked them to update that TAM. This is what they came back with. Good news is, TAM is bigger and it's growing faster. Not a big shock, given all the exciting stuff that's happening in data management around us. However, that right side TAM, which is hot off the press, was the right way to look at our business two years ago when we were actively selling self-managed and cloud. So we asked IDC to split it into the on-prem and the cloud portion. Here's the on-prem portion. Updated TAM, but just the on-prem portion. It's almost half of the TAM today, but it's only growing at 3%, and it's going to be less than 25% of the TAM in 2027 because the cloud part of the data management business is going to grow at a really attractive rate, 27% according to IDC. And by that time, $62.4 billion, which will be more than 75% of the business that's available for us to win. If anybody out there still questions our strategic decision at the beginning of this year to go cloud-only, you need to look no farther than this page. All right, so no company grows at that kind of a TAM, no software company, just by showing up, so I'm going to remind you of the Informatica-specific growth drivers that we think are going to allow us to grow at that rate, and in fact, better, in the planning period we're going to share with you. First of all, digital transformation is as strong of a megatrend in IT as it has ever been, and Informatica, as we've talked about, is the modern data architecture solution, with the best products delivered on the industry's only platform, serving the multi-vendor, multi-cloud, and hybrid needs of the enterprise. It gives us great confidence that our core net new business growth before migration is going to grow at least as well as the TAM is, because we're going to win our fair share of the business, and I'm confident we're going to win more of that. Second, we have $1 billion of on-prem that's a candidate to be migrated over time. We're seeing that that migration is accelerating real time. It's always going to be a minority of our growth, but it is going to get to be a bigger component and a bigger contributor to the total growth in the years ahead. And then finally, GenAI. We talked about the tailwind that we all expect it's going to provide to the data management market, and we think that it's likely that the full effect of that tailwind is not yet in the TAM estimates of some of the third parties like IDC, who estimate that. So let's bring it back to where we started and talk about what that means for where we think cloud subscription ARR is going to go for Informatica in 2024 and beyond. Over the last 12 months, this is a different way to look at the data we talked about in the net new section, 30 percentage points of our 37 percentage points of growth over the last year was from net new use cases and workloads from existing customers and brand-new customers to Informatica. Seven percentage points or 17% of the total growth was from migration from either maintenance customers on-prem or self-managed customers on-prem. Going forward, think about it with the same two components: net new ARR from the new customers and new workloads. Again, for planning purposes and forecast purposes, we're assuming that we can grow at least as fast as that TAM that you saw from IDC on a couple of pages forward, enhanced by a growing portion of migration contribution as it becomes easier and more compelling for our customers to move from our on-prem base to the cloud. Now, contrary to what I showed you in the maintenance and the self-managed base, we are going to give you specific numbers for this one. We're committing today to grow the cloud subscription ARR at 35% for another year. That's going to be the combination of those two pieces. Net new wins in the marketplace, because of the fantastic product that we have to sell and an increasing pace of migrations. Okay, so how does that roll all up into the pre-guidance, as we're calling it, for fiscal 2024? So first of all, you've already got this punchline: 35% growth for cloud subscription ARR in fiscal 2024. Total ARR and GAAP total revenue, those are going to grow faster in fiscal 2024 than they will in fiscal 2023. Those of you who've been following us know that our total ARR and total revenue growth rate has been declining over the last couple of years as we work through this transition of the big on-prem base, the relatively small cloud base that's growing, and so the overall growth rate has declined. That stops in fiscal 2023. The growth rate in 2024 is going to be higher than 2023, the growth rate in 2025 is going to be higher than 2024, and so on, as the growing cloud business gets to be a bigger and bigger portion of the base. We haven't talked much about the operating leverage that exists in our business as it gets simpler and more streamlined because of our cloud-only strategy. That operating leverage is real, and we're committing to at least 350 basis points of non-GAAP operating income margin expansion in fiscal 2024 over fiscal 2023. Then finally, with respect to the important valuation metric of adjusted unlevered free cash flow after tax, we believe we're going to convert at roughly a 100% rate of non-GAAP net income into unlevered free cash flow. With some variability from period- to- period, around things like working capital and cash tax timing, we think that's the conversion rate that's gonna persist for the years ahead. Medium term, let's start with cloud subscription ARR again. For all the reasons that you've heard about through the course of the day, we are confident that cloud subscription ARR is gonna grow at a 31%-32% CAGR from fiscal 2023 to 2026. Total ARR, it's gonna get to $2 billion by fiscal 2026, and it's gonna be growing at 11% when we exit fiscal 2026. So Q4 ARR growth rate, fiscal 2026 is gonna be 11%. Important to know that at that time, the growing part of our business, cloud subscription ARR, is gonna be roughly 70% of total ARR. Simple math. Unless some step function happens with the growth rate of that growth portion or something, step function happens with this much smaller decline portion, our ARR growth rate should continue to accelerate in 2027 and beyond. Just the simple math of how those buckets of ARR should work. GAAP total revenue, in any software business, any growing software business, revenue lags ARR, both in dollars and in growth rate, and it does the same if you're shrinking. So we think that we're gonna hit double-digit total revenue growth in fiscal 2027, and in fiscal 2027, we're going to have, of our total revenue base, cloud subscription revenue is gonna be approximately 70% of the total. Same comment, if our growth business is 70% of the total, the shrink business is 30%, we should just mathematically see continued acceleration of the growth rate, growth of the growth rate, in the years after fiscal 2027. Then finally, with respect to profitability, non-GAAP operating income and adjusted unlevered free cash flow after tax, both of those metrics, because of the operating leverage in the business, we're confident that we can deliver better than 12% CAGR in those two metrics over the 2023 to 2026 period. No discussion like this would be complete without at least a few words around capital allocation. No new news here. It's the same as what it was when we went public and what it has been over the last couple of years. We continue to prioritize investment and growth. We will pursue strategic M&A when attractive opportunities present themselves, and everything we don't spend on those first two uses will be applied to deleveraging on both a gross and a net basis. So let me just wrap it up. Informatica today is winning net new in the cloud. We are serving modern data architectures with our products today, and we enjoy a tremendous expansion engine with the IPU-based IDMC that allows us together to deliver what we think is a very attractive financial profile, a balanced growth profile for the business in the years ahead. 35% cloud subscription growth next year, greater than 30% CAGR through 2026, inflecting total revenue and ARR growth in 2024, realizing double-digit ARR growth in 2026, double-digit revenue growth in 2027, and better than 12% CAGR in non-GAAP operating income and adjusted unlevered free cash flow. Thank you for your time this afternoon. That's the last part of the prepared remarks. And now I'm gonna bring up my presenting partners, Amit, John, Jitesh, and Ansa, and we're gonna give you an opportunity for a little bit of Q&A to close out the day. Thanks again. All righty. I'm gonna get started with Q&A. I've got some questions from our folks online. So why don't I get started while we get the mics going in the room? First question, so maybe to Amit or to Mike: How do you plan to monetize AI? So I'm gonna start. Well, I mean, I think we've said that before. First of all, you saw that our ability to take CLAIRE, leverage it currently in AI, and then to take it into the GenAI world has been pretty fast. Copilot is already there, and GPT comes out next year. I think I shared that in the last earnings call. Look, there are multiple ways to monetize it. There is, like, a separate SKU. You can have a high-priced IPU, or you can continue to have CLAIRE GPT be there and drive increased use of the current IPUs. We're looking at all options, and I don't, I don't think that we want to get ahead of ourselves and say that one is better than the other. To be candid, there is no perfect answer right now in the industry also. So I think we are gonna continue to look at all of those. Our goal, ultimately, is gonna be to make sure that our customers use CLAIRE in a widespread way, because we know one thing: We are very sticky. Once customers use us, you saw the NRR numbers the team shared, we grow the share of the wallet, and we're going to continue to remain flexible on how we monetize it. A lot of work is going on, and I think we'll share more as we come closer to the GA timeframe. We have time for that. Okay. Hi, Howard Ma again, with Guggenheim. By the way, thanks again for putting together everything today. I'm sure a lot of work—it looks like a lot of work went into it. The demo is great, and it's certainly no easy task to forecast, you know, to give three-year targets, which just from a quick glance seems to be above where street estimates are. But I really want to, Mike, I just have two financials-related questions. One is, can you remind us when, what is the revenue up—so it's just a two-parter. Number one is, what is the revenue uplift when you move from self-managed IDMC? And then, the second question is, when you migrate from either on-prem maintenance or self-managed IDMC to fully managed IDMC, is there, I think there's a revenue lag or can you elaborate what that, you know, what that revenue kind of looks like? Thanks so much. Sure. The first question regarding the uplift. You know, publicly, what we've talked about is that it's been an average between both buckets, both maintenance and self-managed, of a little bit more than two, 2.1 last four quarters was the average. Self-managed has been a smaller part, so it's kind of been 70-75% maintenance migration and a smaller portion of self-managed migration. We're not going to share specific splits between the two, but we think that two-to-one ratio will continue across the blend of the two going forward. The value that folks realize from the cloud is as high, whether you're coming from PowerCenter maintenance or self-managed, self-managed on-prem. Yes, there are some accounting complexities that we can't get around. We're not trying to manipulate the numbers. It's the way our accountants, our auditors force us to recognize the ARR and the revenue when we migrate a customer, and we provide them with credits for the maintenance that they're already paying for the migration period, because they shouldn't be double paying for the cloud and maintenance at the same time. And sometimes there are some professional services that we provide to help them with the move. It gets complicated pretty fast, but you're right, but the end result is, there is a lag between recognizing the revenue, the full revenue in ARR from the maintenance migration to when the contract is signed. If you were paying attention, you notice that the maintenance churn number related to migrations on that waterfall chart is a very small number, like 0.3% of the total, which doesn't quite seem to sync with the seventeen percent of our, all of our NAR comes from migrations. That's because of that, that's because of that lag, that we don't lose it in maintenance quite at the same timing as we gain it in cloud. You're never going to be able to model that accurately. There's just too many moving pieces. You're going to have to trust us to understand it at the high level, or at least forecast it accurately at the high level. But what I will say as a final piece of this, you know, very technical and probably unsatisfying answer, is that PowerCenter Cloud Edition minimizes that dramatically because it happens so much more quickly, and there's so much less credit against maintenance involved, that that mismatch, that lag between maintenance and cloud ARR recognition shrinks dramatically. So it's going to be more, much more direct drive in our P&L and in our ARR metric with PowerCenter Cloud Edition. Dan? Hi, guys, Dan Kurnos from Deutsche Bank. Thanks for a great presentation today. A lot of detail in there, and good to see a lot of the disclosure there. I think it's super helpful. Maybe start with Amit, and then a follow-up from Mike. Amit, you talked about your biggest competition being more customers not doing anything or delaying projects. When you think about the conversations you have with customers, what is it that kind of moves them from that position to looking at Informatica? Is it that they're happy with the solution they have, or is it more of a paralysis of they don't really know where to go? As you think about AI and the role that drives in data management, do you see them looking more for a, you know, an established enterprise-grade solution like Informatica? Yeah. So it's never when they do nothing. It's never that they have another product or something. A lot of times, customer will begin a very simple use case by hand coding. "Let me just kind of cobble something together. You know, I can connect to three systems very easily. I can hand code a data quality rule," and off you go, "I created a simple data pipe." That delays a transaction, so that's what we call hand coding. And I think Dave was nodding his head. We see that every day, because when you walk into a customer, sometimes like, "Oh, you know what? And I can do it now, and maybe nine months later we'll have a conversation." So to me, that's what the... It's the time lag between customer realizing, "Oh, shoot, this can't scale. There is no, there's no life cycle of this pipe. There's nothing I can. My business won't accept this. Oh, my gosh, there's a governance problem." So to me, that's the biggest challenge, to educate a customer that, "Hey, look, you're just wasting time." So it's not like they're doing something with another product, they're just hand coding their way. That's what we see. And look, I do believe that when you saw a lot of GenAI stuff, we'll be able to give so much ease of use, so much productivity, that I think that bar will go down. I also think at the same time, every customer is realizing more and more with GenAI that the conversation of data has now become a boardroom conversation.... You know, we make this comment at our events: everybody's ready for AI except your data. I haven't seen a single boardroom where AI is not a conversation. So now the pressure is coming that I cannot punt it for 12 months and cobble something together because the world is moving very fast. So I think that gap should shrink over a period of time. Awesome. And then, Mike, you know, it, it's great to see some, some numbers being kind of put behind, and what you've been talking about for, for a while now in terms of working through this transition and now the acceleration out the other side. Just to kind of make sure that it kinda contextualize that, you know, you know, you talked about from kind of the top-down TAM from IDC supporting that. From kind of a bottoms-up level, if you think about that, can you help us maybe think about. I know you're not going to give exact numbers, but you talk about 45% of the G2K customers, you talk about strong NRR. Like, what do you need to do from an NRR versus a new customer acquisition perspective to hit those numbers? Then also, just want to make sure any incremental M&A impact factor factored into those numbers. I know you talked about that as a growth driver. And then maybe generative AI. I know it's still maybe a little too early to talk about exactly your plans, but how you thought about that, if at all, incorporating that into the forecast. I'll take those in reverse order. So GenAI, as Amit mentioned, we don't have any specific intentions today as to exactly how we're going to monetize it. For now, in the forecast, we think it's going to be a, you know, a tailwind in general to the TAM. But as I mentioned, we're not forecasting that our net new wins before migration is going to be anything greater than the TAM, but we think that that's a tailwind, and that's all. It's not explicitly in the numbers. M&A, no, there's zero in it for that. You know, we'll see if and when something comes along. And then, what do we have to do from a bottoms-up level to grow the net new business at that TAM rate? Look, it's really, this is a, you know, an overly simplistic way to put it, but it's really current course and speed. You know, keep the net retention rate where, where it is, which reflects the expansion within our existing base. Continue to win net new at the rate we have been winning it, and accelerate our migration, not by a heroic amount, but by an amount that seems perfectly reasonable given the acceleration we see in it today. Now, behind that, we've got to hire more reps, and we've got to continue to scale some things in sales marketing. We've got to open new pods so that we can service the cloud delivery, you know, as, as the base grows, but that's all sort of normal case execution. Nothing needs to fundamentally change versus what we're doing today to hit the numbers that I shared with you a few minutes ago. If you just add to that, we are seeing the other things I'll add to that, we are seeing the need for complex data management activities in large enterprises. And it's not just global too. I mean, I would just say if you look at the 5,000, Global 5,000, there's tremendous opportunity and complexity over there, and they have barely scratched the surface of actually putting a proper end-to-end data management flow. By the way, we're also seeing consolidation. The last five, 10 years was just like all—thousands or millions of flowers bloom. Customers can't handle any of that stuff, especially in the world of GenAI or anything. You have to do something at scale. People want to reduce the footprint of many things around that. We're seeing that happen also. Can't have 10 things running around in one organization, 5 running around another business unit. That, that world we see going away. So some of the, a nd then the IPU, you saw Ansa talk about the expansion. I mean, that we are seeing as we speak right now. So we have all of those things that give us tremendous conviction, that we don't have to do anything silly and stupid and heroic to get to this. I'll add another observation to that. You saw from John's examples, where he had the bar charts of the ARR that grew over time. You know, those are Fortune 2000 customers, I think, which are part of that 44%, but you can see how much growth we've been able to obtain out of those folks who were already our customers. Data management is not like your CRM application, where you decide you're going to use Salesforce, and you buy the number of seats you need, and then, you know, there will be incremental growth in that as you need more seats. Data management is about, there's an initial use case that's pretty simple. "Wow, this works great, and we already own the IPUs. We can try this and this and this," and expand it to use case after use case after use case. The TAM within these Global 5,000 companies, just the per company TAM, is really big. In very few companies are we really doing more than scratch the surface of that per company TAM. Alan? Hey, guys. Allan Verkhovski on for Alex Zukin from Wolfe Research. Two questions from me. Can you guys talk about how you view strategic M&A to play out in the space going forward? And the guide on cloud ARR is very strong. Can you guys give a sense for conservatism versus aspirational, and what gives you some of that visibility? Thanks. I'll take the first, and Mike, you can add to the second. I mean, look, first of all, no M&A big can do this. We're very clear this is an organic plan. And second is for us is that, we are going to look, absolutely. I mean, we are in a, I think, in a privileged position. You see how the market has corrected itself, and there's a lot of companies running around. We have a very great cash position. We have built out the platform. We have everything out there. We're not going to be, w e we don't need to rush. We have enough organic technology of our own to monetize, so there's no rush for us that we need an M&A to fill anything. But for sure, we look and we—if there's something shows up that makes a lot of sense to accelerate something, we will absolutely do that. But for us, there is no compelling reason right now out there to go find something to make this number. And I'll first begin, and then I'll have Mike on it. I think if there's one thing you have seen from us. We've been a very thoughtful company. We don't go out just throwing numbers. In fact, I go back to last year. We were growing cloud ARR at 40% for three quarters in a row. Economy had a whole downturn, and we had to lower our guide for cloud ARR from 40% to 35%, and we delivered 40% by the end of the year. I can say that as a company, we do not aspire to being swinging to the fences. That's just not our DNA. We guide very thoughtfully, we deliver against that very thoughtfully. So I cannot forget that year. Look, I lived through that year where we actually had to lower our guide, and I talked to many of you, and it hurt me so much that when we again out-delivered that guide, but we felt it was the right thing to do, so we said that to you all. We'll never go swing to the fences like that. So that's how I'll say it, and I'll let Mike add more to the Well, look, I am completely in sync with that philosophy, with the addition of we're not sandbaggers either. Right? That we've, t he guidance that we've offered to you is really based upon our fundamental view of what the building blocks of the growth are over the multi-year period we've talked about, and what we really think it's gonna add up to, with the caveat that we don't want to talk ourselves into swinging for the fences and setting up expectations that are more likely than not to miss. Great. Natalie? Hey. Hey, this is Natalie Howe. I'm I'm from Bank of America Securities, here for Koji Kato. Thanks for taking our question. So I wanted to ask about PowerCenter Cloud. You guys talked about how it shortened the time from migration. So we have two questions. First, when could we really see that contribution from the acceleration become more material? And secondly, is there an eventual path to migration from PowerCenter Cloud to IDMC? Thanks. So I think let me correct myself. PowerCenter Cloud is getting on IDMC. What we did over there was, in the old days, there was a forklift we had to start and literally undo everything on PowerCenter, every capability, and move it to IDMC. That was a bit of an extensive root canal, and to be honest, customers needed to take a deep breath, and they signed up for it, but it took time. PowerCenter Cloud Edition basically puts literally IDMC on top of PowerCenter from day one, and then it allows customers to basically, over a piece part, start moving things at their own leisure and time, but they can start using all of the IDMC capabilities on top of PowerCenter, like, instantly. So that's why we call it, i t's not a separate product, that there is another step, and then there is another step. I would not look at it like that at all. Secondly, look, I go back to the question that I was asked before. We're being taught, we saw the tailwind that we saw from PowerCenter Cloud Edition right away in Q3. We absolutely see the excitement, and we see that that will create a tailwind to do more migrations. It's a kind of damn you do, damn you don't. We, in this model, have factored in certain amount of migration that is definitely accelerated from the past few years. But we've also not tried to kind of get too cute and assume 50% of the base migrates. So we have not done that also to the question I think, Dave, you asked over there, right? I think if I'm not wrong, roughly about only two-thirds of our overall on-prem base migrates in this three-year model. If you do the simple math based upon the 70% of total that we offered with respect to 26 and 27 ARR and revenue respectively, that means that we're still left with, you know, roughly $700 million of on-prem ARR that is yet to be migrated or churned, you know, that far out in the future. So it is going to be a growing part of the contribution to our total growth, as I talked about, but it's still gonna be a minority by far. And again, just directionally, we're not gonna provide you with guidance either today or in February, that's gonna specifically say that, you know, X point Y% is gonna come from migrations and, you know, A point B is gonna come from net new. But philosophically, we're planning to grow our net new at about the rate of what we're told by the external world and what we feel in our gut is the growth of the TAM, and that we think that the pathway to getting the rest of the growth to 35% is there to achieve through migration. Of course, we want to do more migration, but as I said, if I do less, then there's a question: can you do more? If I do a lot, then you can argue you're being very over-optimistic. So I think we have the right balanced middle of the fairway, what we believe can definitely be done. A question I received online, Mike, "Where is the operating leverage coming from in fiscal year 2024 and beyond? So our business, now that we are cloud-only consumption driven, is just a lot simpler than it was when we were selling self-managed and cloud. And you know, one... Jitesh didn't, you know, talk about it directly, but there was a lot of very heavy fundamental lifting that had to be done to build the platform itself and the microservices that underlie it. And now that we have the infrastructure of the platform, putting new services on top of that in the cloud, particularly because you don't have to make the service available on-prem and cloud, is just more efficient. So there's R&D operating leverage that we'll see in 2024 and beyond, and then go to market. It's simpler to go to market if you've got one set of stuff in your bag rather than two, and when you have the best data management products delivered on the industry's only cloud, multi-vendor, multi-hybrid, and multi-cloud, and hybrid, that's an easier sale fundamentally than if you have a second-rate product. So we think there's sales marketing leverage to be had as well over the period of time. I mean, I think the way I look at it is that we just need. We will be hiring as we go forward. We'll just need less of that than we've had- Yeah in the last 5, 10 years to do more because it's just a much more simpler business. Yep. Great! Well, if there are any more final questions in the room, otherwise, we'll wrap up this executive Q&A session. Before I hand it back over to Amit, I'd like to thank John, Ansa, Mike, and Jitesh. Over to you, Amit. Thank you. Thank you. Well, look, first of all, thank you very much for spending the day with us in the room, for the folks here and, of course, folks on the phone. The ones online, you're missing, gonna miss some great cocktails outside, so we'll have, we'll have more on your behalf for the folks who are in the room. Well, look, I think you heard from me, and you heard from the leadership team. We got something very unique here. It is innovation and customer centricity. We had to do a lot of hard work in building that innovation engine, and you saw that in eight years, we did more than this company did in 22 years. In these eight years, we built a $1.1 billion ARR business from new products, and I challenge you to find more than 10 companies that did $1.1 billion+ in the last eight years from scratch. You know, sometimes I hear the fact that, "Well, the story is still not out there." I say that if we can grow so much with the story not being out there, imagine the story getting out there will do so much more for us. And we count on our partners and customers to help us do that. So that innovation engine of having the best of breed data management products on the only AI-powered data platform, IDMC, and the multi-vendor, multi-cloud neutral position we have, hybrid, is amazing. And then you saw we completely rethought our go-to-market model, the Info Way. We just didn't take that and throw it on the current go-to-market model. I mean, the selling, the post-selling, in fact, that's not even the way we look at it. It's driving consumption and business value. And you saw Mike share about a profitable, accelerated growth. That's simply, if you can take away the day, that's what it is, and we feel very good about it. And if I literally had to repeat the things that we did today, and I will read it, it's we are the data management platform of choice for the enterprise. There is none, zero in our space. That was the belief we had. In software, platform vendors take excess value. We built for that. We are delivering the best data management products on the only AI-powered platform in the multi-vendor, multi-cloud, hybrid landscape. We can deliver hybrid from one cloud platform. We don't have to have multiple products. Our CLAIRE AI capabilities you saw, both CLAIRE Copilot and CLAIRE GPT, they deliver. They're driving new workloads, new use cases for customers. Of course, our IPU consumption-driven strategy is allowing us to win new logos. You saw what Mike shared with you. A lot of times people get confused. Are we winning new logos or not? New logos and new workloads are coming to us, and our partnerships are our secret sauce, both with the hyperscalers and our partners, the GSIs over here, who have practices on us. Then, of course, we're excited. We see an accelerating growth path in front of us in 2024, and of course, in the medium- to long-term as we look at the 2023 to 2026 model that Mike shared with you. Once again, thank you for joining us. It's our privilege to have you in the room and folks on the phone as well. Thank you once again, and I look forward to enjoying cocktails outside with the folks here in the room. Thank you.