 Good afternoon, Cloud Nerds, and welcome back to beautiful Las Vegas, Nevada. We are at AWS re-invent day four, afternoon of day four here on theCUBE. I'm Savannah Peterson, joined by my fabulous co-host, Paul Gillan. Paul, you look sharp today. How you doing? You're just as fabulous, Savannah. You always look sharp. I appreciate that. They pay you enough to keep me buttered up over here. It's wonderful. You're holding up well. Thank you. I'm excited about our next conversation. Two fabulous gentlemen, please welcome Sam and Monty. Welcome to the show. Thank you. And it was great of the PR team to send the most interesting man alive. Yeah, in person. Yeah. In the flesh. Our favorite guest so far. So how's the show been for you guys? It's been phenomenal. Yeah. Yeah. Just spending a lot of time with customers and partners in AWS. Been great. Been great. It is great. It's really about the community. It feels good to be back. Eating good food, getting my steps in above goals. I feel like the balance is good. We walk enough of these convention centers where you can enjoy the libations and the delicious food that's in Las Vegas and still not go home feeling like a cow, which is awesome. It's a win-win. To Sam's point though, meeting with customers, meeting with other technology providers that we may be able to partner with and most importantly, in my role especially, meeting with all of our AWS key stakeholders in the partnership. So yeah, it's been great. Everyone's here. So it's just different having a conversation in person, even like us right now. So just in case folks aren't familiar, tell me about Talent. Yeah. Talent is a data integration company and we've been around for a while. We have tons of different ways to get data from point A to point B, lots of different sources, lots of different connectors. And it's all about creating accessibility to that data. And then on top of that, we also have a number of solutions around governance, data health, data quality, data observability, which I think is really taking off. And so that's kind of how we're changing the business here. Casual change, data and governance. I don't know if anyone's talking about that at all. Yeah. It's been a big topic here. We've had a lot of conversations with the customers about that. So governance, what new dynamics has the cloud introduced into data governance? Yeah. Well, I think historically, like customers have been able to have their data on-prem, they put it into things like data lakes and now having the flexibility to be able to bring that data to the cloud is, it opens up a lot of doors, but it also opens up a lot of risks. So if you think about the chief data officer role where you have, okay, I want to be able to bring my data to the users. I want to be able to do that at scale operationally, but at the same time, you have a tension then between the governance and the rules that really restrict the way that you can do that. And you want to, so like the very, very strong tension between those two things. It's a, it really is a delicate balance. And especially as people are trying to accelerate and streamline their cloud projects, a lot to consider. How do you all help them do that? Monty, let's go to you. Yeah. We keep saying data, data. What is it really? It's ones and zeros. In this day and age, everything we see, we touch, we do, we either use data or we create data. And then that, We are data. We literally are data. And so then what you end up with is all these disparate data silos and different applications with different data. And how do you bring all that together? And that's where customers really struggle. And what we do is we bring it all together and we make it actionable for the customer. We make it very simple for them to take the data, use it for the outcomes that they're looking for in their business initiatives. What is the span on that? What do you mean make it actionable? Do you tag it? Do you organize it in some way? What's different about your approach? I mean, it's a really flexible platform. And I think we're part of a broader ecosystem. So even internally, we are a data-driven company. Coming into the company in April, I was able to come in and get this real-time view of, hey, here's where our teams are. And it's all in front of me in a Tableau dashboard that's populated from talent integration bringing data out of our different systems, different systems like Workday or where we're giving offers out to people, right? And so everything from managing headcount to where our AWS spend is, all of that stuff. Now, we've heard a lot of talk about data. And in fact, the keynote yesterday that was focused mainly on data and getting data out of silos. How do you play with AWS in that role? Because AWS has other data integration partners. For sure. What's different about your relationship? Go ahead. We've had a strong relationship with AWS for many years now. We've got more than 80 connectors into the different AWS services. So we're not new to the AWS game. We align with the sales teams. We align with the partner teams. And then of course we align with all the different business units and verticals so that we can enact that co-sell motion together with AWS. And I think from a product standpoint, again, just being a hyper flexible platform, being able to put, again, any different type of source of data to any type of different destination. So things like Redshift, being able to bring data into those cloud data warehouses is really how we do that. And then I think we have, between bringing data from A to B, we're also able to do that along a number of different dimensions, whether that's just like, hey, we just need to do this once a day to batch all the way down to event-driven things, streaming and the like. That customization must be really valuable for your customers as well. So one of the big themes of the show has been cost reduction. Obviously with the economic times we're potentially dipping our toes into as well as just in general, always wanting to increase margins. How do you help customers cut cost? Well, you know, it's cost cutting but it's also speed to market. The faster you can get a product to market, the faster you can help your customers and let's say healthcare life sciences, pharmaceutical companies, patient outcomes. Great and timely example there. Patient outcomes. How do they get drugs to market quicker? Well, AstraZeneca leveraged our platform along with AWS and they even said for every dollar that they spend on data initiatives, they get $40 back. That's a billion dollars savings by getting a drug to market one month faster. Everybody wins. It's incredible. How do you accelerate that process? Well, by giving them the right data, taking all the massive data that I mentioned, siloed and everywhere and making it so that the data scientists can take all of this data and make use of it, make sense of it and move their drug production along much quicker. Yeah, and I think there's other things too, like being very flexible in the way that it's deployed. Again, I think like you have this historical story of like it takes forever for data to get updated, to get put together. I need it now and in context. And I think where we're coming from is almost more of a developer focus where like your jobs are able to be deployed in any way you want. If you want to containerize those, if you want to scale them, you need to schedule them that way. Like we've plugged into a lot of different ecosystems. So that's, I think that's a differentiation as well. Yeah, I want to hang out on this one just for a second because it's such a great customer success story and so powerful. I mean, in VC land, if you can take one a dollar and make two, they'll give you a 10X valuation. 40, that is so compelling. How do you think, I mean, do you think other customers could expect that kind of savings? A billion dollars is nothing to laugh at, especially when we're talking about developing a vaccine. Yeah, go for it, Sam. Yeah, I think, I think, and it really depends on the use case, right? Like I think, you know, what we're trying to do is being able to say, hey, we have, it's not just about cost cutting, but it's about tailoring the offerings. So, you know, we have other customers like, you know, major, major fast food vendors. You know, they have mobile apps and when you pull up that mobile app and you're going to do a delivery, they want to be able to have a customized offering, right? And it's not like mass market, you know, 20% off. It's like, they want to have a very tailored offer to that customer or, you know, to that person that's pulling open that app. And so, you know, we're able to help them architect and bring that data together so that it's immediately available and, you know, reliable to, you know, to be able to give those promotions. We had AARP on the show yesterday. We're talking about 50 million subscribers and how they customize each one of their experiences. We all want it to be about us and we don't want that generic at, yeah, go for it, Paul. Oh, okay. Yeah. Well, I don't want to break the rhythm here, but one area where you have differentiated, about two years ago, you introduced something called the trust score. Yeah. Can you explain what that is and how that is resonated with your customers? Ooh, yeah, let's talk about that. Yeah, so think, yeah, the thing about the trust score is, you know, how many times have you gotten a set of data and you look at it and you say, where did you get this data? Something doesn't look right here. And with the trust score, what we're able to do is quantify and value the different attributes of the data, whether it's how much this is being used. We can look at, we can profile the data and we have a trust score that runs over time where you can actually then look at each of these data sets. You can look at aggregates of data sets to then say, you know, if you're the data engineer, you can say, oh my, something has gone wrong with this particular data set. Go in, quickly pull up the data. You can see if some third-party integration has polluted your data source. I mean, this happens all the time. And I think, you know, if you sort of compare this to the engineering world, you know, you are, like you're always looking to like solve those problems sooner, you know, earlier in the chain. You know, you don't want your consumer calling you saying, hey, I've got a problem with the data. You don't want them to know there was ever a problem in theory. Yeah, so the trust score helps those data engineers and those people that are taking care of the data. Address those problems sooner. Yep. And how challenging, how much data does somebody need to be able to get to the point where they can have a trust score? If you know what I'm trying to say, how do we train that? I mean, it can be all the way from just like a single data source that's getting updated all the way to like, you know, very, you know, very large, complex ones. That's where we've introduced like this hierarchy of data sets. So it's not just like, hey, we have, you've got, you know, a billion data sources here and like here are the trust scores. But it's like, you can actually architect this to say like, okay, well, I have these data sets that belong to finance, right? And then like finance will actually get, here's a, you know, here's the trust score for these data sets that they rely on. What causes data sets to become untrustworthy? Yeah, yeah, well, I think, I mean, it happens all the time. A lot of different things, right? And I mean, you know, in my history, you know, in the different companies that I've been at, you know, on the product side, we have seen, you know, different integrations that maybe somebody changes something. You know, in upstream, you know, some of those integrations can actually be quite brittle. And as a consumer of that data, it's not necessarily your fault, but that data ends up getting put into your production database. All of a sudden, your data engineering team is spending two days unwinding those transactions, fixing the data that's in there. And all the while that, you know, that bad data that's in your production system is causing a problem for somebody that is ultimately relying on that. Is that usually a governance problem? You know, I think governance is probably a separate, you know, it's probably a separate set of constraints. I think this is really like, you know, this is sort of the tension between wanting to get all of the data available to your consumers versus like wanting to have the quality around it as well. It's tough balance. And I think that it's really interesting. Everybody wants great data. And you could be making decisions that affect people's wellness quite frankly. Right, for sure. Very dramatically if you're ill-informed. So that's very exciting. To your point, we are all data. Right. If data is bad, we're not going to get the outcomes that we want ultimately. And we certainly want the best outcomes for ourselves. And so we track that data health for its entire life cycle throughout the process. That's cool. And that probably increases your confidence in the trust score as well, because you're looking at so much data all the time. What, you got a smart thing going on over here. I like it. I like it a lot. We believe in it. And so does AWS. Because they are a strong partner of ours and sort of customers, I think we mentioned. We've had some phenomenal customer conversations along with SES story and case study. I want to dust your shoulders off right now if I wasn't tethered in. That's super impressive. So what's next for y'all? Yeah, so I think we're going to continue down this path of data health and data governance. Again, you're talking about data health being this differentiator on top of just moving the data around and being really good at that. I think you're also going to have different things around country level or state level governance, I mean, literal laws that you need to comply with. Being able to save, I mean, among a long list of people. Oodles, yeah, yeah, yeah. I think we're going to be doing some interesting things there. We're continuing to proliferate the sources of data that we connect to. We're always looking for the latest and greatest things to put the data into. And I think you're going to see some interesting things come out of that too. And we continue to grow our relationship with AWS, our already strong relationship. So you can procure talent products to the AWS marketplace. We just announced Redshift serverless support for talent. All the rage. Which sounds amazing, but because we've been doing this for so long with AWS, dirty little secret, that was easy for us to do. Because we're already doing all the stuff. So we made the announcement and everyone was like, congratulations, thanks. Look at y'all full of the humble brags, I love it. So about talent has gone through some twists and turns over the last couple of years. Company went private, was purchased by Tomo Bravo about a year and a half ago. At that time, your CEO said that it was a chance to really refocus the company on some core strategic initiatives and move forward. Both of you joined obviously after that happened. But what did you see about sort of the new talent that attracted you, made you want to come over here? For sure. Yeah, I think when I got a chance to talk to the board and talk to Chris, our chair, we talked about there being the growth thesis behind it. So I think Tomo's been a great partner to talent. I think we're able to do some things internally that would be I think fairly challenging for companies that are in the public markets right now. I think especially just a lot of pressure on different prices and cost of capital and all of that. Right now. That was a really casual way of stating that. But yeah, just a little pressure. Yeah, just a little bit of pressure. I also think, and who knows, who knows how long that's going to last. But I think we've got a great board in place. They've been a very strong strategic partner for us talking about all the different ways that we can grow. And so I think it's been a good partner for us to get things going. Have you found one of the strengths of Tomo's strategy is synergy between the companies that they've acquired? Oh, for sure. They've acquired about 40 software companies. Are you seeing synergy talk to those other companies a lot? Yeah, well, so I have an operating partner. I talk with him on a weekly, sometimes daily basis. If we have questions or like, hey, what are you seeing in the space? We can get plugged into advisors very quickly. So I think it's been a very helpful thing where otherwise you're relying on your personal network or things like that. This is why Monty was saying it was easy for you guys to go serverless. Yes, yeah. And we keep talking about trust. But in this case, Tomo Bravo really trusts our senior leadership team to make the right decisions that Sam and I are here making as we move forward. So yeah, it's a great relationship. It sounds like it. All the love. I can feel the love even from you guys talking about it. It's genuine. You're not just getting paid to show this. That's fantastic. Are we getting paid for this or is it? I mean, some folks in the audience are probably going to want your autograph after this. But although you get that a lot. Pictures are available after the record. Yeah, selfies are 10 bucks. That's how I get my boost budget. So last question for you. We have a challenge here on the Cuba re-invent. We're looking for your 30 second hot take. Think of it as your thought leadership sizzle reel. Biggest takeaway, key themes from the show are looking forward into 2023. Sam, you're ready to rock. You're going to continue to hear the tension between being able to bring the data to the masses versus the simplicity and being able to do that in a way that is compliant with all the different laws, but also and then clean data. It's like a lot of different challenges that arise when you do this at scale. And so I think if you look at the things that AWS is announcing, that you look at the things that any sort of vendor in the data space are announcing, you see them sort of coming around to that set of ideas. And so I think we're in a, it gives me a lot of confidence in the direction that we're going, that we're doing the right stuff, and we're meeting customers and prospects and partners, and everybody is like, we kind of get into this conversation and I'll say, yeah, that's it. We want to get involved in that. You can really feel the momentum. Yeah, it's true, it's great. What about you, Monty? I mean, I don't need 30 seconds. I mentioned it. Between talent and AWS, we're aligned from the sales teams to the product teams, the partner teams and the alliances. We're just moving forward and growing this relationship. I love it, that was perfect. And on that note, Sam, Monty, thank you so much for joining us. Thanks for having us. I'm sure your careers are going to continue to be rad at talent and I can't wait to continue the conversation. It's a great team. Yeah, clearly, I mean, look at you two. If you're any representation of the culture over there, they're doing something great. Thank all of you for tuning in to our nearly, well, shoot, I think now over 100 interviews at AWS re-invent in Sin City. We are hanging out here. Paul and I have got a couple more for you. So we hope to see you tuning in with Paul Gillan. I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage.