Close it out, close out the conference. Hope so. Close out the conference with Informatica. Amit Walia, CEO, and Mike McLaughlin, CFO. You didn't come last year. I don't think you were here last year. No, I was here. You were here last year? Yeah, yeah, yeah. Oh, I was not. Sorry. I keep- Must be a different conference. So welcome to your first Goldman Sachs Communacopia + Technology Conference, both of you guys. Glad to be here. Thanks for coming. I have my fellow panelist, sorry, fellow moderator, Matt Martino. Sorry, it's been three days. At the end of the three days, I cannot even recollect your last name that clearly. But, but it's been a great conference. It's been an amazing conference, and thanks to our clients for sticking with us. So Amit, company's been public for nearly a couple of years now. How has your vision for the company changed or not changed? Where do you want the company to be in the next five years? I guess it'll be 100% cloud, no on-prem, no legacy stuff, but I don't want to put words in your mouth. How do you want to see Informatica five years from now? Sure. So thank you, Kash- Mm-hmm ... for the opportunity, and this must be the brave few people who are sticking out till the end of the conference, so you should offer free drinks right now. Yes, on me. We should have sat here with a beer, that'd be fun. So, you know, if I kind of step back and tell you how we, how we thought about the company- Mm-hmm ... and what part of it has changed or not changed, my belief has been that, look, in every part of the software stack, if you see, there is usually one player that takes, becomes the platform player in that space. There is always many running around. Data management is a very large TAM, 50, 60, 70, you pick your number, it's a pretty large TAM, and, and I think our belief has been that we want to be the platform player with the most expansive data management services, period. Mm-hmm. That has not changed. Mm-hmm. If anything, that has accelerated. Mm-hmm. Number two, in that context, our vision had always been that we want to be a cloud-first company. And by the way, when we say cloud-first, our belief is the world will be multi-hybrid forever. Multi-hybrid means there'll be ground and cloud, and multi-cloud. Mm-hmm. But through that cloud-native platform, we can serve any workload. Mm-hmm. That did not change, accelerated. Mm-hmm. In fact, when we went IPO, our thought was, given where we are, maybe that would be 2024, 2025, and we... The cloud has done very well, customer demand has moved towards cloud, we accelerated that to, to 2023. That not changed, accelerated. And the third one for me has been that we want to be maniacally focused on being a Fortune 5,000, mission-critical workload-serving company, not changed. And lastly, if anything, we accelerated that, being a balanced growth company. We want to be a top-line grower. In that, of course, given the business model transition, we want to inflect the curve and have the total top-line growth, given that journey is going from on-prem to cloud, but manage the bottom line very, very maniacally and create operating leverage, so we're a balanced grower. Mm-hmm. Again, that one we've become even more surgically focused on. Mm-hmm. Not changed, accelerated. Mm-hmm. Things for us have just worked out in a way that we've accelerated these journeys, and we've not had to go do a student body left or move the strategy altogether as the world has changed on us. Mm-hmm. And, can you recap for us the key business drivers? What are the big trends that are driving your business? I'll come to GenAI last. Yeah ... because I know that we can begin with that, and we can spend a whole- Yeah, exactly ... discussion on that one. Yeah. By the way, 7, 8 years ago, when we were all looking at the world of digital transformation- Mm-hmm ... we would talk about, "Hey, it's going to be a data-first world, or data will become a front and center," and that's becoming more and more true. Every initiative is a data initiative. In the past, what happened was that people were automating the business workflows, so a cloud application came, so on and so forth, but the world has now become a data-first world. Mm-hmm. In that, AI is accelerating that because there is no AI without data. Mm-hmm. In fact, we just, For me, we just started a marketing campaign. The word there is, everybody's ready for AI, I guess- Mm ... but not your data. That takes hard work to get it ready for AI. And when you look at the two demand drivers in that, there is, one is analytics. Mm-hmm. Whether it's analytics for analytical purposes, operational purposes, data science purposes, core analytics, running your business, which is where we can think of a 360-degree view of a customer, a product, or a supplier, from front end to back end, supply chain- Mm-hmm ... customer centricity initiatives- Mm ... as well as back end, modernization. Third one is data governance and privacy. We see huge vectors driving all three of them. Mm-hmm. Got it. So, to you, Mike, tell us about your background for people that may not be completely aware. It's because it's your first Goldman Sachs conference. Yeah, sure. So, I was, 25 years, more or less, in your business- Okay ... as a banker. Mm-hmm. last 12 years of which was at your nemesis, Morgan Stanley, and had the opportunity to become a CFO. We don't have any competition. Hear, hear, everyone's good friends in this business. Where were you prior to that? So prior to that, I was at BofA Securities. Okay ... in San Francisco, also doing tech. I did 15, 16 years as tech, and 10 in other industries prior to that. Okay. So, the last eight or so were out here in Silicon Valley. And then had the opportunity to be a first-time CFO at Fair Isaac, starting in 2019, which has two businesses under the hood, one of which is the FICO Score, which everybody knows, but also has a big enterprise software business- Mm-hmm ... that was going through a transition, that looks a lot like the transition that Informatica is in as well. Informatica is further along, but ended up having some complementarity and some similarities, I said to Informatica, and when this opportunity came along, it was a pretty compelling and kind of no-brainer move for me to join this part of the journey. I guess, what are the aspirations of the company that you can fulfill as a CFO? How do you see yourself as a partner to Amit and the rest of the management team? This is a balanced growth company with a hyper-growth engine at the core and two pieces, two buckets of revenue that strategically and intentionally are going to decline- Mm-hmm Over the next number of years. And so as the CFO, it's making sure that we have the instrumentation so that we can manage intelligently the decline of those two businesses and the growth of the third business- Mm-hmm ... and put investments in the right place against them, and- Mm-hmm do our best to migrate the declined parts of the business to the growth part of the business, so that years from now, when we are essentially all cloud, that we're best positioned for the future. And translate all of that into a business model that, during the transition, is still appealing to investors and creates value. That model is one where we're not aspiring to grow like Snowflake. Mm-hmm. It's mathematically impossible, and it's also we want to deliver profitability as well as growth. Mm-hmm. It's to take the current sort of mid-single-digit growth in aggregate that we're delivering- Mm-hmm ... and help turn that into high single digit, low double-digit growth as, the growth bit gets bigger and the decline bit gets smaller, while we continue to improve operating margins, and therefore deliver, free cash flow, operating income, and EBITDA, that's growing crisply in the double digits on a sustainable basis. What are the things that need to happen in order to hit that aspiration? The mix of business, talk about that, the ASP, retention, et cetera, as you manage through the transition. Well, so first and foremost, we need to continue to grow the cloud business. Mm-hmm. That starts with my partners who actually produce the product and make it the best in breed out there, which I really believe that it is, and then sell it efficiently with the right acquisition cost ratios and the right, efficiency per rep- Mm-hmm ... and making sure that we're tracking all that and, and delivering a robust business model that's actually creating value, not just, you know, empty calorie growth in the growth part of the business. Mm-hmm. And then in the decline part of the business, and again, a decline sounds negative, but it's declining for the right reason. Mm-hmm. Are we making sure that we're keeping those customers happy so that they're going to move to Informatica with their new workloads and with their existing workloads? Mm-hmm. Are we using that cash flow, which is ample, wisely in the reinvestment for the other part of the business? Mm-hmm. So it's a lot of blocking and tackling, frankly- Mm-hmm ... and making sure that we have the information, and we have the visibility and the telemetry on the business so that we can- Mm-hmm make the best decisions at every step of the way. Got it. What kind of time frame are we giving ourselves to range, you know, 3-4 years, 2-3 years, 2-4, to get to this promised land? Obviously, without providing 2024, 2025 or 2026 guidance- Yeah ... as you can see, obviously from our financials over the last couple of years, that aggregate growth has been declining. Mm-hmm. And that's because we're putting our eggs in the growth basket, and those other pieces are shrinking. There's some ASC 606 accounting implications to that, too, because the shrinking parts are on-prem, where you used to be able to accelerate a lot of revenue. Yeah. Yeah. So 3%, and we, we guided to 5% revenue growth this year. It would have been 8% on a mix constant basis. But first, we need to inflect that and start that growth rate going, like I said, from mid single digits to high single digits, and we think that's going to happen in the near term. Mm-hmm. Not, again, not providing 2024 guidance, but you know, certainly plausible mathematically that that could happen in 2024. Mm-hmm. At our Investor Day in December, we'll give you more specific updates on that. Mm-hmm. From there, that growth rate is gonna continue. Mm-hmm. We're not gonna sacrifice margins, so you're gonna see continued growth in profitability and getting into the, you know, the mid-thirties of operating margin in the next, you know, 3, 4, 5 years is not heroic at all. Mm-hmm. And then beyond that, if we maintain the market position and the leadership that we think we have, and as sales gets more efficient and R&D gets more efficient, you know, getting in the high thirties, even in the forties over a 5- to 7-year basis is, again, completely plausible. Mm-hmm. So Amit, we talked a little bit about Informatica making the strategic decision to fully pivot to cloud this year, right? So can you just talk about some of the go-to-market changes you needed to make to accomplish this, and really any friction in deals from customers that may have initially preferred self-managed? Yeah. So from a rep point of view, in the pre this year, the reps would have gone with the cloud portfolio IDMC, and they would have had certain self-managed products. So in fact, it was more friction then, because obviously now you're presenting two options, and there are different paperwork, different, you know, terms, so on and so forth. And obviously, the comp model is created that, you know, you'll have to calm them. All of that stuff goes away. So it's a dramatic simplification. Only have the cloud platform to sell. It's all on consumption basis. That's it. So you don't... You-- Actually, for the sales rep, it's not-- We didn't have to go tell them that you should do this, and that was not a stick. It was, they were happy with it. And that's why we accelerated the cloud product journey, and we were ready with that. That's why we took the band-aid this year. So no issues there. But the customer, needless to say, customers see that we are moving towards the cloud. And if you take three steps back, arguably, there's no enterprise customer who's not hearing the word cloud. I mean, arguably, if I presented cloud and non-cloud, you kind of almost are telling yourself I have old and new, as much as the non-cloud may be new. So it actually helps... Now, of course, if in Q4 of last year, a rep was presenting a self-managed deal, they have to work with the customer to move that to cloud, and that may take some time. And that we were very open in articulating that that's a big patch stuff into it. You know, that's happening. I've, I've, I talked to the customer at Informatica World, who in December was looking to do a self-managed deal with us. And by the way, he still insisted on doing it in, in Q1 as he was talking to our reps when they went back in cloud. Mm-hmm. He came to Informatica World, and he says, "I'm going to cloud, because I can see the amount of innovation going over there. Why would I pick a something that you will not innovate on?" So that's smoothing out over the course of this year. 92%-94% of our pipe is cloud, so I feel that that's going pretty well, not been an issue for us. And then, maybe- I have one just sidebar question before I turn it back over to Matt. You're a data integration company, and so integrating data integration from on-prem to cloud should be, like, completely within your control, right? So how much of those techniques can you employ to accelerate the transition from the install base of customers going to the cloud? Is that question in the context of migration, or there was a different question? Data migration. Yeah. Yes. So I think, if I understand correctly, I think the question you're asking is about migrating our legacy customers- Yes ... who are on maintenance with PowerCenter- Yeah to our cloud. Yeah. So absolutely, and I think- Yeah. You should have the toolkit. We have the toolkit. That is you. So, and that, by the way, has gone- Yes ... in some ways, what do we have? 4.5% of our maintenance converted to cloud. Yes. I think, I think I've said that to you also that, I would want that to be 10, 15, 20, and at certain point, a bigger number. Sure. I think that has been thoughtful in some ways because these are operational workloads, and we want to make sure that the cost for the customer is down, and there is work to be done there. We did a fair bit of work. We created the playbooks where we wanted to do some of the implementation ourselves to create a playbook. We want to get the partners over there. This year, we've been scaling it. Last year, we spent a lot of time training the partners, scaling with them, helping, giving all the toolkit and everything. By the way, this year, first half, the majority of our migration deals are with partners. Mm-hmm. As we sit here today, we just launched the next version of the tech for migration that further simplifies the migration. We do believe that should be a tailwind to us as we think about the next few years. Mm-hmm. And the other thing we've done is that we had a lot of migration utilities that we held ourselves. Now we're giving it to our customers directly. So giving them the ability to do it at their own pace, which reduces the friction for them to do something. So we look at all of those things, and we see migration to accelerate over time. So, Amit, just kind of moving back to cloud, you know, if we think about, you know, this consumption model that you introduced, the IPU-based model, it seems like it's gaining a lot of traction, a large portion of your net new bookings. So can you just talk a little bit about how the IPU model works for maybe those less familiar? You know, what are the benefits this model brings to Informatica and the customer base? Yeah. So I think all of us in software have used the word consumption-based pricing, and I think everybody here in this room probably gets it or is listening to us. Our consumption-based pricing is actually even more unique, in a good way. So, Snowflake has consumption-based pricing and, but it's one product, basically, how much data goes in this. In our case, what we've done is that the IDMC platform, Intelligent Data Management Cloud, has many capabilities. It's the integration capabilities, ELT, ETL, app integration, data quality, data catalog, data marketplace, all of those kind of things. They're all available through one pricing metric that we call IPUs. So if a customer buys one IPU, they can literally do anything, which means I can do an analytics project, I can do a governance project, I can do a quality project, anything. The only thing that is not an IPU, has its own consumption-based pricing, is MDM, because it's sold by the record. That's how customers like to buy it- Mm-hmm. and we didn't want to tinker with it. It's consumption. So it's a dramatic simplification. I think we are still in our... By the way, if you read Gartner's notes, they're like, "This is the biggest simplification of pricing we've ever seen." But I also think that we are in the very early innings of our customers fully understanding it. I was talking to the CTO of a large bank who were doing a migration deal with us, bought the IPU, and even after buying the IPU, and, and by the way, it's getting better every year. When I, when I had this chat with him, that you can actually do a governance project with this IPU. Mm-hmm. You already have it. Like, he, he couldn't believe it, in a good way. Mm. Like, "Are you really telling me that I can use, even though I bought you for analytics, but that IPU can be done for data governance?" "Yes." So I think that has increased this year. So I believe that's, that's going to be a tailwind for us. Well, if I can add to that, one of the potential downside of a consumption-based pricing model like an IPU is variability. Mm-hmm ... both for ourselves, that if there's an optimization trend or whatever, or usage goes down for any reason, we could see quarter-to-quarter volatility. Ours, the IPU is a minimum plus overage model. It's a multiyear commitment to a number of IPUs that you use on a monthly basis, use it or lose it, paid annually in advance. So during the term of the contract, which is typically 2, 3, 4 years, we have 100% revenue predictability from that customer unless they go over, so we don't have downside variability. Furthermore, variability from the customer side is bad, too. So if they can't predict their bill or they get a surprise that they used more than they thought they were going to, again, the actual consumption of the IPUs is very simple. It's on a rate card. We send them dashboards, regularly, so that they don't have those kind of negative surprises. The third real benefit of the IPU that our customers and Gartner and others are talking about is how easy it is, as Amit said, to move across the platform and upsell, cross-sell yourself. If you decide that you want to use the next feature on the IDMC or the next use case, you actually don't have to talk to your Informatica sales rep. You don't have to negotiate price with us again. You don't have to enter into a new contract. You just use the IPUs you already have, and if you try it, and it works well, you then just, with a phone call or an email, say, you know, "Send me some more IPUs." So, there's just lots of goodness associated with it, and that's what I think you're hearing in the marketplace. ... So Amit, I want to talk a little bit about your, your recent Privitar acquisition. Can you just talk about the strategic rationale for that deal? Kind of what product functionality gaps that fills for the IDMC platform? Yeah, that's a pretty strategic deal for us. So what Privitar does is data access management. And when you're thinking of—by the way, in, and more so in the world of GenAI, when you're thinking of, you know, what we want to do is democratize data. But no large enterprise, I mean, take Goldman Sachs, if you wanted to democratize data, and anybody in Goldman Sachs have access to data, that'll be a Wild West. You want it to be done in a governed way, right? So that's where our data governance capabilities come very handy. So we have a marketplace through which you can publish any data. People come there and get access to data. Now, what happens is that just like identity and access management, accessing data has a lot more rules and capabilities. So there is granular access capability, which controls you want to put, how you're tracking it, that is needed, and that is becoming even more important than profound. So we saw that, we heard that from our customers. We were going to go build it ourselves, and that was a market that got created, and of course, it became a feature in the market for itself. We felt like, as we were looking, like, can we accelerate that? And we found Privitar, they had great set of people, and we just accelerated the roadmap over there. Excellent. And look, I think Informatica's partners with some of the biggest names in the market, whether it be the hyperscaler or Snowflake, Databricks. Can you just talk about the importance of these partnerships and where you're seeing the most momentum across those buckets? Incredibly important. We, we, our central, again, one of the strategic points, I think, as Kash, you were asking, like, what the fundamental beliefs for us, we are the Switzerland of data. I look at it from the context of not a partnership, first in the context of a customer. What do—We, we focus on Fortune 5,000. What is their landscape? What do they want to do? And in that world, it's a pretty hybrid, complex architecture. So we want to focus that customer, which means that we have to partner with everybody. So and by the way, that journey started for us back in the days. I remember, like, growing up, flying up to Seattle to build a partnership with AWS and Microsoft and, then later GCP, then later comes Snowflake, and later came Databricks. Our goal is to partner with all of them, and a partnership is straightforward. We... The world is a lot of hybrid and gray, and you can hear many words. The reality is that with all of them, their goal is to drive their data warehouses or lakes or whatever it is. They want to drive more consumption into it. They're all duking it out with each other. We sit on top of them, bringing data in, transforming it, loading it, governing it, moving it out from there into the BI landscape, to a Tableau or Power BI. We do all of that stuff for everybody, and in the large enterprise, typically, they'll want to standardize on something. So they're doing a little bit with at least two of them. So partnership is very important, and lastly, we are available through most of these guys' marketplace, whosoever has a marketplace. So it makes it for an end customer to burn down the credits a lot easier. So, and product integrations, deep native integrations, so materially important in the context of the customer. From a data integration perspective, it does sound like Snowflake and Databricks do some of this themselves. How do you think about that relative to Informatica? Yeah, I think that's what I said, is 25 shades of gray. I don't want to go to the movie name, but yes, and I think that will always be the case. But you have to go back and say, "What's the primary business they are in?" Snowflake's primary business is data warehousing. Databricks' primary business is whatever it is, competing with them now. They will have a connector here and there. In a large enterprise, they want to not do extract five different ways. They don't want to do transform ten different ways. That's how it works out. Now, in some cases, they may have a narrow feature over there, and somebody may use them for a small use case. That's fine, too. That happens, had happened before also, and I think will happen. I think to... I'll step back 50 billion TAM. Our revenue is $1.6-$1.7 billion. There is a tremendous amount of upside for us. I look at that. Right. And then maybe we could just pivot to generative AI. Mm-hmm. We wanted to talk about this, opportunity for Informatica. You recently announced CLAIRE Copilot and, CLAIRE GPT, so can you help us understand kind of the value these products or features will bring to your customers? 10 minutes to go. Now we'll talk for 10 minutes. Yeah. Yeah. Yes. So look, first of all, if I step back, everything we've done is pretty very thoughtful. We launched CLAIRE four years ago. Mm-hmm. We've not been new to this AI journey. Mm-hmm. So CLAIRE has been working on all kinds of machine learning models, already algorithms, and we run almost 35-40 PB of metadata through which we run CLAIRE. So we've been at this, it's part of our platform. As GenAI came, it allowed us to provide that value very quickly. So CLAIRE Copilot is what Copilot does. It's available today. By the way, if you are a user, you come in, let's say you're creating data pipelines in a Snowflake project or a Databricks project. I'll sit there. Here is the things that you can do. By the way, you started doing something, you should do three other things. Oh, you did this thing, that's wrong. Fix it like this. So just a, just really accelerates productivity. And because we've seen these things done millions of ways, we can really shortcut that very quickly. I know, by the way, when some new data or a database comes up, CLAIRE can come tell you, "Hey, you go add that so that your workflows are more complete." So that's a copilot. CLAIRE GPT is exactly what you see. It's a chat-like interface to do data activity. That, by the way, is in private preview mode right now. Our goal is to basically... A lot of enterprise customers are using it. Can it output SQL? Sorry? Can it output SQL? It will do SQL. Yeah. Okay. So, I'll give you an example, and we demoed that at Informatica World this year, and we'll, by the way, talk about that more at the investor day, analyst day, later this year. Think of this, you can ask a customer: Can you give me, can you bring for me from the western region of the United States, the customers that are most at risk of churn? Plain English language. English language, yeah. Yeah. Yeah. That's serious amount of work that has to happen. Mm-hmm. It has to go find customers from the western region- Yeah ... at risk of churn. SQL code is being written- Mm-hmm ... goes, pulls data from many places. All of that stuff is gonna go behind the scenes. Yeah. But it's abstracted that for you as a business user. Mm-hmm. So that's exactly what it'll do. Mm-hmm. It'll generate that work. It'll show you the output. You don't have to do the grunt work anymore. ... This is like way out into the future, but, let's say you build an application purely on an LLM stack, and it accesses data that's just carelessly stored. In, in that scenario, we wouldn't need databases and data integration, et cetera. So do you, do you think there's a remote chance we might get to a state like that at some point? Pretty technical question, and I'll put this way. Look, data, there are three fundamental atomic things that will never go away. Yeah. Data will be created, so it has to be put somewhere. Mm-hmm. That somewhere could be it. It has to be some state of rest, whether we call it a database in the future or not, but there has to be some repository. Sure. Yeah. I think that repository will definitely change over a period of time. Mm-hmm. I mean, we've all lived the world of transactional databases to move it. So I think the repository will always be needed. Mm-hmm. I think the question you're asking is the right question- Mm-hmm. I think we are go, we have... That's what CLAIRE GPT's first version is. Mm-hmm. We want to remove the complexity to do these things that gives you the final answer. Because in the world of data, whether we like it or not, there is so much complexity. Mm-hmm. Even a basic task of, you know, just to give to print your credit card bill. I'd like to give an example. I came to this country, and my first project was working on printing your telecom bills. You have no idea, you have no idea how arcane the systems were, and they still are. They used to print bills for people who've died. Yes. And then manually, somebody will throw them away, so they don't get pushed. So data is always very complicated because of systems. I think what we will run into a state which what we'll do is that eliminate that workflow will get very, very compressed, and anybody can run the workflow. In that, I don't think that the world will be the world of LLM as we see it today. Mm-hmm. I think today we are looking at LLMs. By the way, 99.9% of the enterprises don't need an LLM. Mm-hmm. They need a language model. They're a large- They don't need a large language model. Mm-hmm. The large language model is for the Internet. Mm-hmm. I think that what will happen is that, just like machine learning algorithms, there will be many language models- Mm-hmm and we will all democratize that very quickly. I think, I think where Meta is headed towards demo-- I think that's, that's the right way. Mm-hmm. We will all take those language models and customize them for different use cases. Mm-hmm. Mm-hmm. That's what will happen, and we will do that kind of work for our customers. How do you see that, playing out for you guys? That- Do you give your customers a trained LLM, or...? I think that's the world will be. Yeah ... if you're looking, I think the world may very well be that if you're doing a supply chain optimization project- Mm-hmm and we would have had an internal LLM, that'll be curated for that. Yeah. If you're doing this analysis, curated for that, because we would know that of this LLM, break it up, there are 10,000 LMs running around. You can start bucketing it, just like you do for machine learning algorithms today. Mm-hmm. We know we use NLP and five others for a particular use case. That's where the world will go. Mm-hmm. I think this is just, we're scratching the surface on this one. Five years, this will be very different when we will be on the other side of the spectrum. I mean, like, philosophically, how should we think about kind of CLAIRE Copilot? Like, it, it seems very value add, but should we think of this as kind of like a feature enhancement to the platform, or is there some associated pricing with that? I mean, how do we think about that? Yeah, our fundamental belief is, right now, we want to drive more IPU consumption. Mm-hmm. So I look at it this way, that give it to the customer. It basically allows more users to do more stuff with our product, ultimately drives IPU consumption. There can be a healthy debate that should you price it separately, a separate SKU. I think, look, you know, like, I think that's the, the jury is out on that one. Ultimately, we want frictionless selling with more consumption, whichever way I get it. If I create a separate SKU, then you have to create a selling cycle where you kind of almost prove to a customer why it's more expensive. If I drive IPU consumption, I'm more than happy with that. I want expanded usage of the platform. I think right now, we are on the, the experimentation is on the right path. Right. But we will, we will be open to doing different things. That makes sense. Mike, maybe to bring it back to the fundamentals, can you just talk a little bit about what you've been observing in the macro? I think you called out stability in 2Q relative to 1Q. So can you just remind us, you know, what's happening underneath the hood in terms of the demand environment? I think it's the same as what you've heard me say before. It is not getting better, it's not getting worse, and that probably in and of itself is getting better. Mm-hmm. Maybe there's a little less fear that it's getting worse, but we're not really seeing acting on that fear in terms of opening up the walls more quickly or wider. Sure. So, steady as she goes is probably the way to think about it from our perspective. Then, yeah, just a quick follow-up there on just kinda like the net new cloud ARR trends. Like, I think a big focal point was kind of the implied step up going into 4Q, just given that you guys reiterated the 35% cloud ARR guide. So, you know, what are you seeing in the pipeline, top of funnel activity, just demand gen more broadly, to kind of give you the confidence that you can hit that target? So the first thing I'd say is, we think about the guidance and the performance on a yearly basis. Of course, everybody wants to look at it on a quarterly basis, and we do, too. But enterprise software is lumpy and unpredictable, and big deals can land in one quarter, first of the month, the next quarter. So I would encourage everybody to think about the guidance that we affirmed at the end of the second quarter as the rest of the year. The Q is important, of course, but there's a higher standard deviation around that, and we feel good about both numbers, but particularly the full year number. The pipeline to support that looks good. We track coverage ratios, conversion ratios, commit levels, all that, very, very closely, and it gives us confidence that that is the right forecast. And the world is uncertain, you never can be 100% sure, but, we feel good about it. That's great to hear. Amit, maybe just moving back to the maintenance opportunity, you know, how, how important of a role do the GSIs play in, in driving that maintenance conversion opportunity? Can you talk a little bit about that? Yeah, I think important. Like I said, when we this year I forget the number, but definitely north of three-quarters of the migration deals are with GSIs. We had to give them a playbook. Most of them have now created factories for migration. The reason we want them is, we had to also help them optimize the migration work effort they put in, because it's a larger transformation of their entire tech stack, and they love to participate in that. Because when we migrate PowerCenter to IDMC, it's an operational workload. That's not just that. It's like, okay, now the whole thing moves, and customer is ready to do the whole thing. They participate in not just a tech migration, but they also participate in a business process transformation. They love it. Yeah. So I think it took them a while to get there because they were looking at the smaller piece of the pie. They were not trained on that, but I think they're excited. I think—I tell you, last week, last two weeks, I've talked to a lot of partners. It was my two weeks of talking to partners, and everybody is in, like, we are in with migration, and we want to create the migration factory, the ones who had not done it. So that was the big work we had to do last year, and that's paying dividends this year. You said operational workload, right? Yeah. So, how much of the business is operational versus analytical? Terrific question. Mm-hmm. When we say, analytics can be an operational workload. Mm-hmm. Our analytics ends up most of it is operational. When I say, like, for example, printing a 10-K, 10-Q- Mm-hmm. That's an operational analytical workload. Mm-hmm. Our analytic workloads end up very few being what if, nice to have- Mm-hmm. experimentation workloads. Mm-hmm. They all end up being mission-critical, like the CFO, CEO's dashboard, quarterly QBR reporting, so on and so forth. So most of our analytics work that we do is operational, which is what I mean mission-critical. Mm-hmm. That is not nice to have, that goes away. Mm-hmm. Mm-hmm. Got it. Yeah. Anybody wants to ask a question? We have 45 seconds to go. Probably not. Yeah. Do you have any final questions? Yeah, sure. Maybe just lastly, the one area we didn't touch on is just competition more broadly, right? So kind of, you know, how are you viewing the competitive landscape? Including the cloud-native, data integration folks, you can touch on them that as well. I think, we can spend any amount of time... I look at it this way, that there is always going to be competition. There is what we do in data management, the cloud-native guys do it too. They partner with us very closely. We are an Azure native service. We are the design partner with AWS. We've won many awards. Everybody will do a little bit of something. I don't look at that as- Right ... anything else. Our individual point product competitors were all born in the world of free money, and, you know, we compete very well with them. And where they go downmarket to certain categories, we don't compete with them. Mm-hmm. Focus on Fortune 5000. I kind of, kind of almost step back always to look at it this way, that $50 billion TAM, $1.6 billion revenue company, tremendous. We have very sticky workloads. If we can just make sure we can execute in that very well, it's very easy. We can double our company or triple our company without having to worry about why we worry about competition, but not lose sleep over them. Philosophically, focus the customer. Large enterprises have tremendous complexity. We have a lot of room to serve them. We partner monetarily with all of those guys you mentioned. Mm-hmm. There is a lot of hope. We hit the zero mark here. Thank you so much, guys. Well, thank you, Kash. Thank you. Thank you very much, guys. You're such troopers and maintaining your energy level and enthusiasm even as the day faded. This is the end. Well- This is the end. This is the end. Well- This is the end of the conference. We love it. But we shall resume next year. You're welcome back next year.