(upbeat music) >> Welcome back to Supercloud 2. This is Dave Vellante. We're here exploring the intersection of data and analytics in the future of cloud and data. In this segment, we're going to look deeper into the life sciences business with Jesse Cugliotta, who leads the Healthcare and Life Sciences industry practice at Snowflake. And Nicholas Nick Taylor, who's the executive director of Informatics at Ionis Pharmaceuticals. Gentlemen, thanks for coming in theCUBE and participating in the program. Really appreciate it. >> Thank you for having us- >> Thanks for having me. >> You're very welcome, okay, we're go really try to look at data sharing as a use case and try to understand what's happening in the healthcare industry generally and specifically, how Nick thinks about sharing data in a governed fashion whether tapping the capabilities of multiple clouds is advantageous long term or presents more challenges than the effort is worth. And to start, Jesse, you lead this industry practice for Snowflake and it's a challenging and vibrant area. It's one that's hyper-focused on data privacy. So the first question is, you know there was a time when healthcare and other regulated industries wouldn't go near the cloud. What are you seeing today in the industry around cloud adoption and specifically multi-cloud adoption? >> Yeah, for years I've heard that healthcare and life sciences has been cloud diverse, but in spite of all of that if you look at a lot of aspects of this industry today, they've been running in the cloud for over 10 years now. Particularly when you look at CRM technologies or HR or HCM, even clinical technologies like EDC or ETMF. And it's interesting that you mentioned multi-cloud as well because this has always been an underlying reality especially within life sciences. This industry grows through acquisition where companies are looking to boost their future development pipeline either by buying up smaller biotechs, they may have like a late or a mid-stage promising candidate. And what typically happens is the larger pharma could then use their commercial muscle and their regulatory experience to move it to approvals and into the market. And I think the last few decades of cheap capital certainly accelerated that trend over the last couple of years. But this typically means that these new combined institutions may have technologies that are running on multiple clouds or multiple cloud strategies in various different regions to your point. And what we've often found is that they're not planning to standardize everything onto a single cloud provider. They're often looking for technologies that embrace this multi-cloud approach and work seamlessly across them. And I think this is a big reason why we, here at Snowflake, we've seen such strong momentum and growth across this industry because healthcare and life science has actually been one of our fastest growing sectors over the last couple of years. And a big part of that is in fact that we run on not only all three major cloud providers, but individual accounts within each and any one of them, they had the ability to communicate and interoperate with one another, like a globally interconnected database. >> Great, thank you for that setup. And so Nick, tell us more about your role and Ionis Pharma please. >> Sure. So I've been at Ionis for around five years now. You know, when when I joined it was, the IT department was pretty small. There wasn't a lot of warehousing, there wasn't a lot of kind of big data there. We saw an opportunity with Snowflake pretty early on as a provider that would be a lot of benefit for us, you know, 'cause we're small, wanted something that was fairly hands off. You know, I remember the days where you had to get a lot of DBAs in to fine tune your databases, make sure everything was running really, really well. The notion that there's, you know, no indexes to tune, right? There's very few knobs and dials, you can turn on Snowflake. That was appealing that, you know, it just kind of worked. So we found a use case to bring the platform in. We basically used it as a logging replacement as a Splunk kind of replacement with a platform called Elysium Analytics as a way to just get it in the door and give us the opportunity to solve a real world use case, but also to help us start to experiment using Snowflake as a platform. It took us a while to A, get the funding to bring it in, but B, build the momentum behind it. But, you know, as we experimented we added more data in there, we ran a few more experiments, we piloted in few more applications, we really saw the power of the platform and now, we are becoming a commercial organization. And with that comes a lot of major datasets. And so, you know, we really see Snowflake as being a very important part of our ecology going forward to help us build out our infrastructure. >> Okay, and you are running, your group runs on Azure, it's kind of mono cloud, single cloud, but others within Ionis are using other clouds, but you're not currently, you know, collaborating in terms of data sharing. And I wonder if you could talk about how your data needs have evolved over the past decade. I know you came from another highly regulated industry in financial services. So what's changed? You sort of touched on this before, you had these, you know, very specialized individuals who were, you know, DBAs, and, you know, could tune databases and the like, so that's evolved, but how has generally your needs evolved? Just kind of make an observation over the last, you know, five or seven years. What have you seen? >> Well, we, I wasn't in a group that did a lot of warehousing. It was more like online trade capture, but, you know, it was very much on-prem. You know, being in the cloud is very much a dirty word back then. I know that's changed since I've left. But in, you know, we had major, major teams of everyone who could do everything, right. As I mentioned in the pharma organization, there's a lot fewer of us. So the data needs there are very different, right? It's, we have a lot of SaaS applications. One of the difficulties with bringing a lot of SaaS applications on board is obviously data integration. So making sure the data is the same between them. But one of the big problems is joining the data across those SaaS applications. So one of the benefits, one of the things that we use Snowflake for is to basically take data out of these SaaS applications and load them into a warehouse so we can do those joins. So we use technologies like Boomi, we use technologies like Fivetran, like DBT to bring this data all into one place and start to kind of join that basically, allow us to do, run experiments, do analysis, basically take better, find better use for our data that was siloed in the past. You mentioned- >> Yeah. And just to add on to Nick's point there. >> Go ahead. >> That's actually something very common that we're seeing across the industry is because a lot of these SaaS applications that you mentioned, Nick, they're with from vendors that are trying to build their own ecosystem in walled garden. And by definition, many of them do not want to integrate with one another. So from a, you know, from a data platform vendor's perspective, we see this as a huge opportunity to help organizations like Ionis and others kind of deal with the challenges that Nick is speaking about because if the individual platform vendors are never going to make that part of their strategy, we see it as a great way to add additional value to these customers. >> Well, this data sharing thing is interesting. There's a lot of walled gardens out there. Oracle is a walled garden, AWS in many ways is a walled garden. You know, Microsoft has its walled garden. You could argue Snowflake is a walled garden. But the, what we're seeing and the whole reason behind the notion of super-cloud is we're creating an abstraction layer where you actually, in this case for this use case, can share data in a governed manner. Let's forget about the cross-cloud for a moment. I'll come back to that, but I wonder, Nick, if you could talk about how you are sharing data, again, Snowflake sort of, it's, I look at Snowflake like the app store, Apple, we're going to control everything, we're going to guarantee with data clean rooms and governance and the standards that we've created within that platform, we're going to make sure that it's safe for you to share data in this highly regulated industry. Are you doing that today? And take us through, you know, the considerations that you have in that regard. >> So it's kind of early days for us in Snowflake in general, but certainly in data sharing, we have a couple of examples. So data marketplace, you know, that's a great invention. It's, I've been a small IT shop again, right? The fact that we are able to just bring down terabyte size datasets straight into our Snowflake and run analytics directly on that is huge, right? The fact that we don't have to FTP these massive files around run jobs that may break, being able to just have that on tap is huge for us. We've recently been talking to one of our CRO feeds- CRO organizations about getting their data feeds in. Historically, this clinical trial data that comes in on an FTP file, we have to process it, take it through the platforms, put it into the warehouse. But one of the CROs that we talked to recently when we were reinvestigate in what data opportunities they have, they were a Snowflake customer and we are, I think, the first production customer they have, have taken that feed. So they're basically exposing their tables of data that historically came in these FTP files directly into our Snowflake instance now. We haven't taken advantage of that. It only actually flipped the switch about three or four weeks ago. But that's pretty big for us again, right? We don't have to worry about maintaining those jobs that take those files in. We don't have to worry about the jobs that take those and shove them on the warehouse. We now have a feed that's directly there that we can use a tool like DBT to push through directly into our model. And then the third avenue that's came up, actually fairly recently as well was genetics data. So genetics data that's highly, highly regulated. We had to be very careful with that. And we had a conversation with Snowflake about the data white rooms practice, and we see that as a pretty interesting opportunity. We are having one organization run genetic analysis being able to send us those genetic datasets, but then there's another organization that's actually has the in quotes "metadata" around that, so age, ethnicity, location, et cetera. And being able to join those two datasets through some kind of mechanism would be really beneficial to the organization. Being able to build a data white room so we can put that genetic data in a secure place, anonymize it, and then share the amalgamated data back out in a way that's able to be joined to the anonymized metadata, that could be pretty huge for us as well. >> Okay, so this is interesting. So you talk about FTP, which was the common way to share data. And so you basically, it's so, I got it now you take it and do whatever you want with it. Now we're talking, Jesse, about sharing the same copy of live data. How common is that use case in your industry? >> It's become very common over the last couple of years. And I think a big part of it is having the right technology to do it effectively. You know, as Nick mentioned, historically, this was done by people sending files around. And the challenge with that approach, of course, while there are multiple challenges, one, every time you send a file around your, by definition creating a copy of the data because you have to pull it out of your system of record, put it into a file, put it on some server where somebody else picks it up. And by definition at that point you've lost governance. So this creates challenges in general hesitation to doing so. It's not that it hasn't happened, but the other challenge with it is that the data's no longer real time. You know, you're working with a copy of data that was as fresh as at the time at that when that was actually extracted. And that creates limitations in terms of how effective this can be. What we're starting to see now with some of our customers is live sharing of information. And there's two aspects of that that are important. One is that you're not actually physically creating the copy and sending it to someone else, you're actually exposing it from where it exists and allowing another consumer to interact with it from their own account that could be in another region, some are running in another cloud. So this concept of super-cloud or cross-cloud could becoming realized here. But the other important aspect of it is that when that other- when that other entity is querying your data, they're seeing it in a real time state. And this is particularly important when you think about use cases like supply chain planning, where you're leveraging data across various different enterprises. If I'm a manufacturer or if I'm a contract manufacturer and I can see the actual inventory positions of my clients, of my distributors, of the levels of consumption at the pharmacy or the hospital that gives me a lot of indication as to how my demand profile is changing over time versus working with a static picture that may have been from three weeks ago. And this has become incredibly important as supply chains are becoming more constrained and the ability to plan accurately has never been more important. >> Yeah. So the race is on to solve these problems. So it start, we started with, hey, okay, cloud, Dave, we're going to simplify database, we're going to put it in the cloud, give virtually infinite resources, separate compute from storage. Okay, check, we got that. Now we've moved into sort of data clean rooms and governance and you've got an ecosystem that's forming around this to make it safer to share data. And then, you know, nirvana, at least near term nirvana is we're going to build data applications and we're going to be able to share live data and then you start to get into monetization. Do you see, Nick, in the near future where I know you've got relationships with, for instance, big pharma like AstraZeneca, do you see a situation where you start sharing data with them? Is that in the near term? Is that more long term? What are the considerations in that regard? >> I mean, it's something we've been thinking about. We haven't actually addressed that yet. Yeah, I could see situations where, you know, some of these big relationships where we do need to share a lot of data, it would be very nice to be able to just flick a switch and share our data assets across to those organizations. But, you know, that's a ways off for us now. We're mainly looking at bringing data in at the moment. >> One of the things that we've seen in financial services in particular, and Jesse, I'd love to get your thoughts on this, is companies like Goldman or Capital One or Nasdaq taking their stack, their software, their tooling actually putting it on the cloud and facing it to their customers and selling that as a new monetization vector as part of their digital or business transformation. Are you seeing that Jesse at all in healthcare or is it happening today or do you see a day when that happens or is healthier or just too scary to do that? >> No, we're seeing the early stages of this as well. And I think it's for some of the reasons we talked about earlier. You know, it's a much more secure way to work with a colleague if you don't have to copy your data and potentially expose it. And some of the reasons that people have historically copied that data is that they needed to leverage some sort of algorithm or application that a third party was providing. So maybe someone was predicting the ideal location and run a clinical trial for this particular rare disease category where there are only so many patients around the world that may actually be candidates for this disease. So you have to pick the ideal location. Well, sending the dataset to do so, you know, would involve a fairly complicated process similar to what Nick was mentioning earlier. If the company who was providing the logic or the algorithm to determine that location could bring that algorithm to you and you run it against your own data, that's a much more ideal and a much safer and more secure way for this industry to actually start to work with some of these partners and vendors. And that's one of the things that we're looking to enable going into this year is that, you know, the whole concept should be bring the logic to your data versus your data to the logic and the underlying sharing mechanisms that we've spoken about are actually what are powering that today. >> And so thank you for that, Jesse. >> Yes, Dave. >> And so Nick- Go ahead please. >> Yeah, if I could add, yeah, if I could add to that, that's something certainly we've been thinking about. In fact, we'd started talking to Snowflake about that a couple of years ago. We saw the power there again of the platform to be able to say, well, could we, we were thinking in more of a data share, but could we share our data out to say an AI/ML vendor, have them do the analytics and then share the data, the results back to us. Now, you know, there's more powerful mechanisms to do that within the Snowflake ecosystem now, but you know, we probably wouldn't need to have onsite AI/ML people, right? Some of that stuff's very sophisticated, expensive resources, hard to find, you know, it's much better for us to find a company that would be able to build those analytics, maintain those analytics for us. And you know, we saw an opportunity to do that a couple years ago and we're kind of excited about the opportunity there that we can just basically do it with a no op, right? We share the data route, we have the analytics done, we get the result back and it's just fairly seamless. >> I mean, I could have a whole another Cube session on this, guys, but I mean, I just did a a session with Andy Thurai, a Constellation research about how difficult it's been for organization to get ROI because they don't have the expertise in house so they want to either outsource it or rely on vendor R&D companies to inject that AI and machine intelligence directly into applications. My follow-up question to you Nick is, when you think about, 'cause Jesse was talking about, you know, let the data basically stay where it is and you know bring the compute to that data. If that data lives on different clouds, and maybe it's not your group, but maybe it's other parts of Ionis or maybe it's your partners like AstraZeneca, or you know, the AI/ML partners and they're potentially on other clouds or that data is on other clouds. Do you see that, again, coming back to super-cloud, do you see it as an advantage to be able to have a consistent experience across those clouds? Or is that just kind of get in the way and make things more complex? What's your take on that, Nick? >> Well, from the vendors, so from the client side, it's kind of seamless with Snowflake for us. So we know for a fact that one of the datasets we have at the moment, Compile, which is a, the large multi terabyte dataset I was talking about. They're on AWS on the East Coast and we are on Azure on the West Coast. And they had to do a few tweaks in the background to make sure the data was pushed over from, but from my point of view, the data just exists, right? So for me, I think it's hugely beneficial that Snowflake supports this kind of infrastructure, right? We don't have to jump through hoops to like, okay, well, we'll download it here and then re-upload it here. They already have the mechanism in the background to do these multi-cloud shares. So it's not important for us internally at the moment. I could see potentially at some point where we start linking across different groups in the organization that do have maybe Amazon or Google Cloud, but certainly within our providers. We know for a fact that they're on different services at the moment and it just works. >> Yeah, and we learned from Benoit Dageville, who came into the studio on August 9th with first Supercloud in 2022 that Snowflake uses a single global instance across regions and across clouds, yeah, whether or not you can query across you know, big regions, it just depends, right? It depends on latency. You might have to make a copy or maybe do some tweaks in the background. But guys, we got to jump, I really appreciate your time. Really thoughtful discussion on the future of data and cloud, specifically within healthcare and pharma. Thank you for your time. >> Thanks- >> Thanks for having us. >> All right, this is Dave Vellante for theCUBE team and my co-host, John Furrier. Keep it right there for more action at Supercloud 2. (upbeat music)

(upbeat music) >> Welcome back to Vegas, baby. Lisa Martin here with theCUBE. We are live at Caesar's Forum covering Snowflake Summit 22. This is day two of our wall to wall coverage on theCUBE you won't want to miss. We've got an exciting customer story to talk to you about next with Novartis and Snowflake. Please welcome two guests to theCUBE. Loïc Giraud, Global head digital delivery, Novartis. I hope I got the name right. >> Yes. Hi, thank you. >> I did my best. >> Absolutely. >> Lisa: (laughs) Jesse Cugliotta also joins us. Global Industry Lead, Healthcare and Life Sciences at Snowflake. Welcome with theCUBE, gentlemen. >> Thank you for having us. Good morning. >> So it was great to hear Novartis is a household word now, especially with what's gone on in the last two years. I had a chance to see the Keynote yesterday, heard Novartis mention in terms of a massive outcome that Snowflake is delivering that we're going to get to. But Loic talk to us about Novartis global 500 organization. You rank among the world's top companies investing in R&D, the massive portfolio and you're reaching nearly 800 million patients worldwide. That's huge, but there's been a lot of change in the healthcare and life sciences industry, especially recently. Talk to us about the industry landscape. What are you seeing? >> As you described, Novartis is one of the top life science company in the world. We are number three. We operate in 150 countries, and we have almost 120,000 employees. Our purpose is actually to reimagine medicine for the use of data science and technology and to extend people's life. And we really mean it. I think, as you mentioned, we treat eight or 9 million patient per year with our drugs. We expect to treat more than a billion patients in near time soon. Over the last few years, especially during COVID, our digital transformation help us to accelerate the drug discovery and then the commiseration of our drug to markets. As it was mentioned in the Keynote yesterday, we have actually been able to reduce our time to market. It used to take us up to 12 years and cost around 1.2 billion to discover and commercialize drug. And now we've actually use of technology like Snowflake, we have been able to reduce by two to three years, which ultimately is a benefit for our patients. >> Absolutely. Well, we're talking about life and death situations. Talk about... You mentioned Novartis wants to reimagine medicine. What does that look like? Where is data in that and how is Snowflake an enabler of reimagining medicine? >> So data is core for our asset, is a core of enterprise process. So if you look at our enterprise, we are using data from the research, for drug development, in manufacturing process, and how do we market and sell our product through HCPs and distribute it to reach our patients. If you build through our digital transformation we have created this integrated data ecosystem, where Snowflake is a core component. And through that ecosystem, we are able to identify compounds and cohorts, perform clinical trials, and engage HCPs and HGOs so that can prescribe drugs to serve our patient needs. >> Jesse, let's bring you into the conversation. Snowflake recently launched its healthcare and life sciences data cloud. I believe that was back in March. >> It was. >> Just a couple of months ago. Talk to us about the vertical focus. Talk to us about what this healthcare and life sciences data cloud is aiming to help customers like Novartis achieve. >> Well, as you mentioned there, Snowflake has made a real pivot to kind of focus on the various different industries that we serve in a new way. I think historically, we've been engaged in really, all of the industries across the major sectors where we participate today. But historically we've been often engaging with the office of IT. And there was a recognition as a company that we really need to be able to better speak the language of our customers in with our respective industries. So the entire organization has really made a pivot to start to build that capability internally. That's part of the team that I support here at Snowflake. And with respect to healthcare and life sciences, that means being able to solve some of the challenges that Loic was just speaking about. In particular, we're seeing the industry evolve in a number of ways. You bring up clinical research in the time that it takes to actually bring a drug to market. This is a big one that's really changed a lot over the last couple of years. Some of the reasons are obvious and other ones are somewhat opportunistic. When we looked at what it takes to get a drug to market, there's several stages of clinical research that have to be participated in, and this can often take years. What we saw in the last couple of years, is that all of a sudden, patients didn't want to physically participate in those anymore, because there was fear of potential infection and being in a healthcare facility. So the entire industry realized that it needed to change in terms of way that it would engage with patients in that context. And we're now seeing this concept of decentralized clinical research. And with that, becomes the need to potentially involve many different types of organizations beyond the traditional pharma, their research partners, but we're starting to see organizations like retail pharmacies, like big box retailers, who have either healthcare delivery or pharmaceutical arms actually get involved in the process. And of course, one of the core things that happens here is that everyone needs a better way to collaborate and share data amongst one another. So bringing this back to your original question, this concept of being able to do exactly that is core to the healthcare and the life sciences data cloud. To be able to collaborate and share data amongst those different types of organizations. >> Collaboration and data sharing. It seems to me to be a differentiator for Snowflake, in terms of being able to deliver secure, governed powerful analytics and data sharing to customers, partners to the ecosystem. You mentioned an example of the ecosystem there and how impactful to patients' lives, that collaboration and data sharing can be. >> That's absolutely right. It's something that if you think about all of the major challenges that the industry has had historically, whether it is high costs, whether it are health inequities, whether it is physicians practicing defensive medicine or repeat testing, what's core to each one of these things is kind of the inability to adequate collaborate and share data amongst all of the different players. So the industry has been waiting for the capability or some sort of solution to be able to do this, I think for a long, long time. And this is probably one of the most exciting parts of the conversations that we have with our customers, is when they realize that this is possible. And not only that it's possible within our platform, but that most of the organizations that they work with today are also Snowflake customers. So they realize that everyone's already here. It's just a matter of who else can we work with and how do we get started? >> Join the party. >> Exactly. >> Loic talk to us about Novartis's data journey. I know you guys have been, I believe using Snowflake since 2017 pre pandemic. But you had a largely on-premises infrastructure. Talk to us about the decision of Novartis to go to the cloud, do it securely and why you chose to partner with Snowflake. >> So when we started our journey in 2018, I think the ambition that our CEO, was to transform all enterprise processes for the use of digital tech. And at the core of this digital tech is data foundation. So we started with a large program called Formula One, which aim to integrate all our internal and external data asset into an integrated platform. And for that, I think we've built this multicloud and best upgrade platform, where Snowflake is a core component. And we've been able to integrate almost 1,000 data asset, internal and external for the platform to be able to accelerate the use of data to create insight for our users. In that transformation, we've realized that Snowflake could be a core component because of the scalability and the performance with large dataset. And moreover, when Snowflake started to actually open collaboration for their marketplace, we've been able to integrate new data set that are publicly available at the place that we could not do on ourself, on our own. So that is a core component of what we are trying to do. >> Yeah, and I think that's a great example of really what we're talking about here is that, he's mentioning that they're going out to our marketplace to be able to integrate data more easily with some of the vendors there. And that is kind of this concept of the healthcare and life sciences data cloud realized, where all of a sudden, acquiring and bringing data in and making it ready for analysis becomes much faster, much easier. We continually see more and more vendors coming to us saying, I get it now, I want in. Who else can I work with in this space? So I think that's a perfect example of how this starts to become real for folks. >> Well, it sounds like the marketplace has been an enabler, Loic, of the expansion of use cases. You've grown this beyond drug development. I read that you're developing new products and services for healthcare providers to personalize treatments for patients, which we all are demanding patients. We want that personalized care. But talk about the marketplace as a facilitator of those expanding use cases that Snowflake is powering. >> Yes. That's right. I mean we have currently almost 65 use cases in production and we are in advanced progress for over 200 use cases and they go across all our business sector. So if you look at drug development, we are monitoring our clinical trials using Snowflake. If you look at our omnichannel marketing, we are looking at personalization of information with our HCPs and HGOs using snowflake. If you look at our manufacturing process, we are looking at yet management, freight optimization, inventory, insight. So almost across all the industry sectors that we have, I think we are using the platforms to be able to deliver faster information to our users. >> And that's what we all want. Faster information. I think in the pandemic we learned that access to real time data in every industry wasn't a nice to have. That was a- >> Necessity. >> Absolute necessity. >> Yeah. >> And made the difference for companies that survived and thrived and those that didn't. That's something that we learned. But we also learned that the volume of data just continues to proliferate. Loic, you've been in the industry a couple of decades. What do you see? And you've got, obviously this great foundation now with Snowflake. You've got 65 use cases you said in production. What's the future of the data culture in healthcare and life sciences from your perspective? >> So my perspective. It is time now we give the access to our business technologies to be able to be self-sufficient using digital product. We need to consumerize digital technology so they can be self-sufficient. The amount of problems that we have to solve, and we can now solve with new technology has never been there. And I think where in the past, where in the next few years that you will see an accelerated generation of insight and an accelerated process of medicine by empowering the business technologies to use a technology that like Snowflake and over progress. >> What are your thoughts Loic, of some of the, obviously a lot of news coming out yesterday from Snowflake, we mentioned standing room only in the Keynote. This I believe is north of 10,000 attendees. People are ready to engage in person with Snowflake, but some of the news coming out, what is your perspective? You've been a partner of theirs for a while. What do you see from Snowflake in terms of the news, the volume of customers it's adding, all that good stuff? >> I must say I was blown away yesterday when Frank was talking about the ramp up of customers using Snowflake. But also, and I think in Benoit and Christian, and they talk about the innovation. When you look at native application or you look at hybrid tables, we saw a thing there. And the expansion of the marketplace by monetization application, that is something that is going to accelerate the expansion, not only on the company, but the integration and the utilization of customers. And to Jesse's point, I think that it is key that people collaborate using the platform. I think we want to collaborate with suppliers and providers and they want to collaborate with us. But we want to have a neutral environment where we can do that. And Snowflake can be that environment. >> And do it securely, right? Security is absolutely- >> Of course. I mean that's really table stake for this industry. And I think the point that you just made Loic, is very important, is that, the biggest question that we're often asked by our customers is who else is a customer within this industry that I can collaborate with? I think as Loic here will attest to, one of the challenges within life sciences in particular is that it is a highly regulated industry. It is a highly competitive industry, and folks are very sensitive about referenceability. So about things like logo usage. So to give some ideas here, people often have no idea that we're working with 28 of the top 50 global pharma today, working with seven of the top 12 global medical device companies today. The largest CROs, the largest distributors. So when I say that the party is here, they really are. And that's why we're so excited to have events like these, 'cause people can physically introduce themselves to one another and meet, and actually start to engage in some of these more collaborative discussions that they've been waiting for. >> Jesse, what's been some of the feedback that you've heard the last couple of days on the healthcare and life sciences data cloud? You've obviously finally gotten back to engaging with customers in person. But what are some of the things, feed on this street have said that you've thought, we made the absolute right decision on this pivot? >> Yeah, well I think some of it speaks to the the point I was just speaking about, is that they had no idea that so many of their peers were actually working with Snowflake already and that how mature their implementations have actually been. The other thing that folks are realizing is that, a lot of the technologies that serve this ecosystem, whether they're in the health tech space, whether they're clinical management or commercial engagement or supply chain planning technologies, those companies are also now pivoting to Snowflake, where they're either building a part or the entirety of their platform on top of ours. So it offers this great way to start to collaborate with the ecosystem through some of those capabilities that we spoke about. And that's driving new use cases in commercial, in supply chain, in pharmacovigilance, in clinical operations. >> Well, I think you just sum up beautifully why the theme of this conference is the world of data collaboration. >> Yes, absolutely. >> The potential there, that Snowflake is unleashing to the world is I think is what's captivating to me. That you just scratch on the surface about connecting and facilitating this collaboration and this data sharing in a secure way across industries. Loic, last question for you. Take us home with what is next for Novartis. You've done a tremendous amount of digitalization. 65 use cases in production with Snowflake. What's next for the company? >> See, I think that in next year's to come, open collaboration with the ecosystem, but also personalization. If you look at digital medicine and access to patient's informations, I think this is probably the next revolution that we are entering into. >> Excellent. And of course those demanding patients aren't going to want anything slower or less information. Guys, thank you for joining me on the program talking about the Novartis-Snowflake collaboration. The partnership, the outcomes that you're achieving and how this is really dramatically impacting the lives of hundreds of millions of people. We appreciate your time and your insights. >> Thank you for having us. This was fun. >> My pleasure. >> Thank you. >> For my guests, I'm Lisa Martin. You're watching theCUBE. This is live from Las Vegas, day two of our coverage of Snowflake Summit 22. I'll be right back with my next guest, so stick around. (upbeat music)