Informatica Inc. (INFA) Earnings Call Transcript & Summary

All right, we're going to close it out, closing our conference. Close out the conference with Informatica, Amit Walia, CEO; Mike McLaughlin, CFO. You didn't come last year. I don't think you were here.

No, I was here. Oh, I was not. Sorry.

Must be a different conference. So welcome to your first Goldman Sachs Communacopia & Technology Conference, both you guys. Thanks for coming. I have my fellow panelists -- fellow moderator, Matt Martino. Sorry, it's been 3 days. At the end of the 3 days, I cannot even recollect your last name, clearly, but it's been a great conference. It's been an amazing conference, and thanks to our clients for sticking with us.

So Amit, the company has 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 5 years? I guess it will 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 5 years from now?

Sure. Thank you, Kash, for the opportunity. And this must be the brave few people who are sticking out until the end of the conference, so you should offer free drinks right now. We should have sat here with a beer, that would be fun. So if I kind of step back and tell you how we thought about the company 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 billion, $60 billion, $70 billion, you pick your number, so a pretty large TAM. And it's still very fragmented. And I think our belief has been that we want to be the platform player with the most expansive data management services, period. That has not changed. If anything, that has accelerated. Number two, in that context, our vision has always been that we want to be a cloud-first company. And 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. But through that cloud-native platform, we can serve any workload. That did not change, it accelerated. In fact, when we went IPO, our thought was given where we are, maybe that could be '24, '25. And we -- the cloud has done very well. Customer demand has moved towards cloud. We accelerated that until 2023. That, not changed, accelerated. And the third one for me has been that we want to be maniacally focused on being a Fortune 5000 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 are a balanced grower. Again, that's when we become even more surgically focused on, not changed, accelerated. So 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 all together as the world has changed around us.

And can you recap for us the key business drivers? What are the big trends that are driving your business?

So if you -- I'll come to Gen AI last here because I know that we can begin with that and we can spend a whole discussion on that one. By the way, 7, 8 years ago, when we were all looking at the world of digital transformation, 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 are automating the business workflow, so cloud application came, so on and so forth, but the world has now become a data first world. And in that AI is accelerating that because there is no AI without data. In fact, we just -- formally, we just started a marketing campaign, [ the world there is ]. Everybody is ready for AI, I guess, but not your data. That takes hard work to get it ready for AI. And when you look at the 2 demand drivers in that, there is -- one is analytics, whether it's analytics for analytical purposes, operational purposes, data science purposes, core analytics, running your business, which is where we could think of a 360-degree view of a customer, a product or a supplier from front end to back end, supply chain, customer centricity initiatives as well as back-end modernization. Third one is data governance and privacy. We see huge vectors driving all 3 of them.

Got it. So to you, Mike, tell us about your background for people that may not be completely aware, because it's your first Goldman Sachs conference.

Yes, sure. So I was 25 years, more or less, in your business as a banker, 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 here.

Everyone's good friends in this business.

And where were you prior to that?

So prior to that, I was at BofA Securities in San Francisco, also doing tech. I did 15, 16 years as tech and 10 in other industries prior to that. So the last 8 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 2 businesses under the hood, one of which is the FICO score, which everybody knows, but also has a big enterprise software business 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, as 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.

And what are your -- 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?

So this is a balanced growth company with a hyper growth engine at the core and 2 pieces -- 2 buckets of revenue that strategically and intentionally are going to decline 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 2 businesses and the growth of the third business and put investments in the right place against them and 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. It's mathematically impossible. And it's also we want to deliver profitability as well as growth. So it's to take the current sort of mid-single-digit growth in aggregate that we're delivering and help turn that into high single-digit, low double-digit growth as the growth, it gets bigger and the declining 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. And 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 and making sure that we're tracking all that and delivering a robust business model that's actually creating value, not just empty calorie growth in the growth part of the business. And then in the declined part of the business -- and again, declined sounds negative, but it's declining for the right reason. 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? And are we using that cash flow, which is ample, wisely in the reinvestment for the other part of the business? So it's a lot of blocking and tackling, frankly, and making sure that we have the information and we have the visibility and the telemetry of the business so that we can make the best decisions at every step of the way.

Got it. What kind of time frame are we giving ourselves, a range 3 to 4 years, 2 to 3 years, 2 to 4 to get to this promised land?

So obviously, without providing '24 or '25 or '26 guidance, as you can see, obviously, from our financials over the last couple of years, that aggregate growth has been declining, 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. So 3%, 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 and not -- again, not providing '24 guidance, but certainly plausible mathematically that, that could happen in '24. And at our Investor Day in December, we'll give you more specific updates on that. And then from there, that growth rate is going to continue. And we're not going to sacrifice margins, so you're going to see continued growth in profitability. And getting into the mid-30s of operating margin in the next 3, 4, 5 years is not heroic at all. And then beyond that, if we maintain the market position and the leadership that we think we have and as sales get more efficient and R&D gets more efficient, getting in the high 30s, even in the 40s over a 5- to 7-year basis is, again, completely plausible.

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?

Yes. 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 2 options, and there are different paperwork, different terms, so on and so forth. And obviously, the comp model has created that you'll have to comp them. All of that stuff goes way. So it's a dramatic simplification, only have the cloud platform to sell. It's all on a consumption basis. That's it. So you don't -- you factor it. 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 because 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 [ bad net ] this year. So no issues there. With the customer, needless to say, customers see that we are moving towards the cloud. And if you take 3 steps back, arguably there's no enterprise customer who's not hitting the word in the 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. So it actually helps. Now of course, if in Q4 of last year, a rep was presenting you self-managed deals, they have to work with the customer to move back to cloud, and that may take some time. And that we were very open in articulating that, that we bake that stuff into it. And that's happening. I sat with a 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 Q1 as he was talking to [ our reps ] when they went back in cloud. He came to Informatica, well, and he says, "I'm going to cloud." Because I can see the amount of innovation going over there, I would have picked something that you would not innovate on. So that's moving out over the course of this year. 90% to 94% of our pipe is cloud. So I feel that that's going pretty well. It's not been an issue for us.

One just side bar 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 apply to accelerate the transition from your installed base of customers going to the cloud?

Is that question on the context of migration or there was a debate on [indiscernible].

Migration, yes.

So I think if I understand correctly, I think the question you're asking is about migrating our legacy customers who are on maintenance with power center to our cloud? Absolutely. And I think...

Yes. You should have the toolkit.

We have the toolkit. So -- and that, by the way, has gone -- in some ways, what do we have, 4.5% of our maintenance converted to cloud. And I think I've said that to you also that I would want that to be 10%, 15%, 20% and at a certain point, a bigger number here. And I think that has been [ impactful ] in some ways because there is -- 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. So last, this year, we've been scaling it with -- last year, we spent a lot of time training the partner, 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. And 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. 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, on that, just kind of moving back to cloud. If we think about 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? What are the benefits this model brings to Informatica and the customer base?

Yes. 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 [indiscernible] consumption pricing, but it's one product, basically, how much data goes in there. 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 in the marketplace, all of those kind of things. They are 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 create a quality project. 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, and we didn't want to tinker with it. It's consumption. So it's a dramatic [ innovation ]. 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'll ever see. 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 are doing a migration deal with us, bought the IPU. And even after buying the IPU -- by the way, it's getting better every year. I had this chat with them that you can actually do a governance project with this IPU. You already have it. Like he couldn't believe it, in a good way. 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 going to be a tailwind for us.

If I can add to that. One of the potential downside of a consumption-based pricing model like an IPU is variability, both for ourselves, that if there's an optimization trend or whatever, our usage goes down. For any reason, we could see quarter-to-quarter volatility. 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, 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. And 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 e-mail say, send me some more IPUs. So there's just lots of goodness associated with them, and that's what I think you're hearing in the marketplace.

So Amit, I want to talk a little bit about 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?

Yes. 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, and more so in the world of gen AI, when you're thinking of -- what we want to do is democratize data. But no large enterprise, I mean, take Goldman Sachs, if you wanted to democratize data, anybody in Goldman Sachs has some access to data, that would 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, their great set of people, and we just accelerated the roadmap for them.

Excellent. And look, I think Informatica has -- 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?

We are central. Again, one of the strategic points, I think as, Kash, you were asking like what are the fundamental beliefs for us here, 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 large -- we focus on Fortune 5000. 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 on that customer, which means that we have to partner with everybody. So along with that journey, started for us back in the days. I remember like flowing up -- flying up to Seattle to build a partnership with AWS and Microsoft and then later GCP, later comes Snowflake, later came Databricks. Our goal is to partner with all of them and our partnership is straightforward. The world is a lot of hybrid and gray, 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 a cloud. We do all of that stuff for everybody. And in a large enterprise, typically, they want to standardize on something. So they're doing a little bit with at least 2 of them. So partners are very important. And lastly, we are available through most of these guys' marketplace, also we have the marketplace. So it makes it for a end customer to [ burn down the credits ] a lot easier. So -- and product integrations, deep native integration. So materially important in the context of the customer.

And from a data integration perspective, it does sound like Snowflake and Databricks do some of this themselves. So how do you think about that relative to Informatica?

I think that's why I said there's 25 shades of gray. I don't want to invoke the movie name, but yes. And I think that will always be the case. But you have to go back and look, 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 connected data there. In a large enterprise, they want to not do extract 5 different ways. They don't want to do transform 10 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 it will happen. I think I said back, 50 billion TAM, our revenue is $1.6 billion, $1.7 billion. There is a tremendous amount of upside for us. I look at that.

And then maybe we could just pivot to generative AI. 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 get to talk for 10 minutes. Yes. So look, first of all, if I step back, everything we've done is being very thoughtful. We launched CLAIRE 4 years ago. So we've not been new to this AI journey. So CLAIRE has been working on all kinds of machine learning models already. You've got to realize that we run almost 35, 40 petabytes of metadata through which we run CLAIRE. So we've been at this -- it's part of our platform. As Gen AI came, it allowed us to provide that value very quickly. So CLAIRE copilot, it's what copilot does. It's available today. By the way, if you are a user, you come in, let's say, a trading data pipeline then a [ store data 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 3 other things, or you did this thing that's wrong, fix it like this. So it just really accelerates productivity. And because we've seen these things done millions of ways, we can really shortcut that very quickly. And 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 copilot. CLAIRE GPT is exactly what you see. It's a chat-like interface to do data [ in an exact way ]. That, by the way, is in private preview mode right now. Our goal is to basically a lot of our enterprise customers are using it.

Can it output SQL?

Sorry?

Can it output SQL?

It will do SQL. So I'll give you an example, and we demoed that at Informatica World this year, and we'll be the way, talk about that more at the Investor Day -- Analyst Day later this year. Think of 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? But that's a serious amount of work that has to happen. It has to go find customers from the Western region at risk of churn, SQL code is being written, goes pulls data from many places. All of that stuff it's going to do behind [indiscernible]. But it's extracted that for you as a business user. So that's exactly what it will do, and it will generate that work. It will show you the output, you don't have to do the grunt work anymore.

This is like way out in 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 that scenario, we wouldn't need databases and data integration, et cetera. So do you -- do you think there's more chance we might get to a state like that at some point?

Pretty technical question, and I'll put it this way. Look, data -- there are 3 fundamental technological things that will never go away. Data will be created. So it has to be put somewhere. And that somewhere could be -- 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. And I think that repository will definitely change over a period of time. I mean we've all lived the world of transactional databases to [ move ]. So I think the repository will always be here. I think the question you're asking is your right question, and I think we have -- that's what CLAIRE GPT's first version is. 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. Even a basic task of -- just to give -- to print your credit card bill, I'd like to give you an example. I came to this country and my first project was working on printing for telecom bills. You have no idea how arcane the systems were and they still are. They use to print bills for people who've died. Yes. And then manually somebody will throw them away if they don't get pushed. So data is always very complicated because of systems. I think what we will run into, a stage which was what to do that, eliminate that workflow will get very, very compressed. And anybody can run the workload. In that, I don't think that the world will be the world of LLM as we see today. I think today, we are looking at LLMs -- by the way, 99.9% of the enterprises don't need an LLM. They need a language model, you don't need a large language model. The large language model is for the Internet. I think that what will happen is that, just like machine learning was a part of it, there will be many language models and we will all democratize that very quickly. I think where Meta is headed towards -- I think that's the right way. And then we will all take those language models and customize them for different use cases. 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? Do you give your customers a trained LLM?

I think that's the world will be, that if you're looking -- I think the world may very well be that if you're doing a supply chain optimization project, we would have had internally a LM that will be curated for that. If you're doing this analysis related for that because we would know that office LLM, break it up, there are 10,000 LMs running around, you can start marketing it just like you do for machine learning a lot of them today. We know we use NLP and 5 others for a particular use cases. That's where the world will go. I think this is just we're scratching the surface on this one. 5 years, this will be very different than 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 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?

Yes. Our fundamental belief is right now, we want to drive more IPU consumption. So I look at this way that, give it to the customer, it basically allows more users to do more stuff with our product. Activity drives IPU consumption. There can be a healthy debate that should you price it separately, a separate SKU. I think look, I think that the jury is out on that one. Ultimately, we want [ frictionless ] selling with more consumption, whichever we are getting. If I create a separate SKU, then you have to create a selling cycle where you kind of almost prove to a customer why this is 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're on the -- the experimentation is on the right path. But we will be open to doing different things.

That makes sense. And 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 what's happening underneath the hood in terms of the demand environment?

I think it's 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. 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 wallet more quickly or wider. So steady as she goes is probably the way to think about it.

And then just a quick follow-up there on just kind of 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 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 the 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 or 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 of that very, very closely. It gives us confidence that, that is the right forecast. In a world of uncertainty, you can never can be 100% sure, but we feel good about it.

It's great to hear. Amit, maybe just moving back to the maintenance opportunity. How important of a role do the GSIs play in driving that maintenance conversion opportunity? Can you talk a little bit about that?

Yes. I think it more -- that's why I said when we -- this year, I forget the number, but definitely north of 3/4 of the migration deals are with GSIs and we had to give them a playbook. Most of them have now created factories for migration. And the reason we want them is, and we had to also help them optimize the migration work effort they put in because it's a larger transformation of the entire tech stack and they love to participate in that. Because when we migrate power center to IDMC, it's an operational workload. That's not just that. It's like, okay, now the whole thing moves and customers are ready to do the whole thing. They participate in not just a tech migration, but they're also partnered in a business process transformation. They love it. 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 -- the last 2 weeks, I've talked to a lot of partners, it was like 2 weeks of talking to partners. And everybody is 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. So how much of the business is operational versus analytical?

Terrific question. When we say analytics can be -- analytics can be an operational workload. Our analytics and some -- most of it is operational. When I say like, for example, take a 10-K, 10-Q, that's an operational analytical workload. So our analytic workloads end up very few being, what is nice to have, experimentation workloads. 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. That is not nice to have, that goes away.

Got it. Anybody who wants to ask a question? We have 45 seconds to go. Probably not. Do you have any final question?

Yes, sure. Maybe just lastly, one area we didn't touch on is just competition more broadly, right? So kind of how are you viewing the competitive landscape?

Including the cloud data integration folks, you can touch on them. That would be great.

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 a -- what we do in data management, the cloud-native guys don't do. They partner with us very closely. We're an Azure-native service. We have a design partner with AWS. We've won many awards. Everybody will do a little bit of something. I don't look at that as ever anything [ ugly ]. Our individual point product competitors were all born in the world of free money. And we compete very well with them. And where they go downmarket to certain categories, we don't compete with them. We focus on Fortune 5000. And I 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 you 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 -- while 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 [ maniacally ] with all of those guys you mentioned. And a lot of hope.

We hit the 0 mark. Thank you so much, guys.

Well, thank you again. Thank you.

Thank you for maintaining energy level and enthusiasm even as the day faded. This is the end. This is the end. This is the end of [indiscernible] but we should resume next year. You're welcome. Bye.

Next year.

Thanks so much.