 Welcome back to Vegas. It's theCUBE live at AWS re-invent 2022. There are, we're hearing up to 50,000 people here. It feels like the energy at this show is helpable. I love that. Lisa Martin here with Dave Vellante. Dave, we had the keynote this morning that Adam Szilipski delivered lots of momentum in his first year. One of the things that you said that you were looking in your breaking analysis that was released a few days ago, four trends. And one of them you said, under Szilipski's rule in the 2020s, there's going to be a rush of data that will dwarf anything we have ever seen. Yeah, it was at least a quarter, maybe a third of his keynote this morning was all about data. And the theme is simplifying data and doing better data integration, integrating across different data platforms. And we're excited to talk about that. Always want to simplify data. It's like the rush of data is so fast it's hard for us to keep up. It is hard to keep up. We're going to be talking with an alumni next about how his company is helping organizations like Cisco Meraki keep up with that data explosion. Please welcome back to the program Matthew Skolian, the CEO of Matillion. And Hosheng Chenoy joins us, data scientist at Cisco Meraki. Guys, great to have you on the program. Thank you. Thank you for having me. So Matthew, we last saw you just a few months ago in Vegas at Snowflake Summit. We only meet in Vegas. I guess we do. That's okay. Talk to us about some of the things. You know, I know that Matillion has a data transformation solution that was originally introduced for AWS for Redshift. But talk to us about Matillion. What's gone on since we've seen you last? Well, I mean, it's not that long ago but actually quite a lot. And it's all to do with exactly what you guys were just talking about there. This almost hard to comprehend way the world is changing with the amounts of data that we now can and need to put to work. And our world view is there's no shortage of data. But the choke point, certainly one of the choke points, maybe the choke point is our ability to make that data useful, to make it business ready. And we always talk about the end use cases. We talk about the dashboard or the AI model or the data science algorithm. But until before we can do any of that fun stuff, we have to refine raw data into business ready usable data. And that's what Matillion is all about. And so since we last met, we've made a couple of really important announcements and possibly at the top of the list is what we call the Data Productivity Cloud. And it's really squarely addressed at this problem. It's the result of many years of work, really the apex of many years of the outsize engineering investment Matillion loves to make. And the Data Productivity Cloud is all about helping organizations like Cisco Miraki and hundreds of others, enterprise organizations around the world get that data business ready faster. Hosheng, talk to us a little bit about what's going on at Cisco Miraki. How you're leveraging Matillion from a productivity standpoint. I've really been a Matillion fan for a while, actually even before Cisco Miraki at my previous company, Libram. And we brought Matillion to Libram because to Matthew's point, there is a stage in every data growth, as I want to call it, where you have different companies at different stages. But to get data data ready, you really need a platform like Matillion because it makes it really easy. So you have to understand Matillion, I think is designed for someone that uses a lot of code, but also that's someone that uses no code. Because the UI is so good. Someone like a marketer who doesn't really understand what's going on with that data, but wants to be a data-driven marketer, when they look at the UI, they immediately get it. They're just like, oh, I get what's happening with my data. And so that's the brilliance of Matillion. And to get data to that data ready part, Matillion does a really, really good job because what we've been able to do is blend so many different data sources. So there is an abundance of data, data is siloed though, and the connectivity between different data is getting harder and harder. And so here comes Matillion with this really simple solution, easy to use platform, powerful, and we get to use all of that. So to really change the way we've thought about our analytics, the way we've progressed our division, yeah. You're always asking about superpowers, and that is the superpower of Matillion, because low code, no code sounds great, but it only gets you a quarter of the way there, maybe 50% of the way there. So you're kind of an and, not an or. That's 100% Ryan. So I mentioned the data productivity cloud earlier, which is the name of this platform of technology we provide that's all to do with making data business ready. And so I think one of the things we've seen in this industry over the past few years is a kind of extreme decomposition in terms of vendors of making data business ready. You've got vendors that just do loading. You've got vendors that just do a bit of data transformation. You've got vendors that do data ops and orchestration. You've got vendors that do reverse ETL. And so with the data productivity platform, you've got all of that. I'm particularly in this kind of macroeconomic heavy weather that we're now starting to face. I think companies are looking for that. It's like, I don't want to buy five things, five sets of skills, five expensive licenses. I want one platform that can do it. But to your point, David, it's the am not the or. We talk about the data productivity cloud, the DPC, as being everyone ready. And what we mean by that is if you are the tech savvy marketer who wants to get a particular insight, and you understand what a row and a column is, but you're not necessarily a hardcore super geeky data engineer, then you can visual low code, no code. Your data is a point where it's business ready. You can do that really quick. It's easy to understand. It's faster to ramp people onto those projects because it explains itself, faster to hand it over because it's self-documenting. But there'll always be individuals, teams, and or use cases that want to high code as well. Maybe you want to code in SQL or Python, increasingly, of course, in DBT. And you can do that on top of the data productivity cloud as well, so you're not having to make a choice. But is that right? I mean, you use this stuff. So one of the things that Matillion really delivers is speed to insight. I've always said that when you want to be business ready, you want to make fast decisions, you want to act on data quickly, Matillion allows you to, the speed to insight is just unbelievably fast because you blend all of these different data sources, you can find the deficiencies in your process, you fix that, and you can quickly turn things around. And I don't think there's any other platform that I've ever used that has that ability. So the speed to insight is so tremendous with Matillion. The thing I always assume going on in our customers' teams like you run, Hoshang, is that the visual metaphor, be it around the orchestration of data ops jobs, be it around the transformation, I hope it makes it easier for teams, not only to build it in the first place, but to live with it, right? To hand it over to other people and all that good stuff. Is that true? Let me highlight that a little bit more and better for you. So say, for example, if you don't have a platform like Matillion, you don't really have a central repository for all of your coping. You could have a Git repository, you could do all of those things, but for example, for definitions, business definitions, any of those kind of things, you don't want it to live in just a spreadsheet. You want it to have a central platform where everybody can go in, there's detailed notes, copious notes that you can make on Matillion, and people know exactly which flow to go to and be part of. And so I kind of think that that's really, really important because that's really helped us in a big, big way. Because when I first got there, you were pulling code from different scripts and things like that, and you were trying to piece everything together, but when you have a platform like Matillion and you actually see it seamlessly across, it's just so phenomenal. So I want to pick up on something Matthew said about consolidating platforms and vendors because we have some data from ETR, one of our survey partners, and they went out, every quarter they do surveys, and they asked the customers that were going to decrease their spending in the quarter, how are you going to do it? And number one, by far, like over a third said we're going to consolidate redundant vendors. You're way ahead of cloud, we're going to optimize cloud resources. That was next at like 15%. So confirms what you were saying and you're hearing that a lot. Were you, because in IT we never get rid of stuff. We talk about it all the time, we call it GRS, get rid of stuff. Were you able to consolidate or at least minimize your expense around it? Yeah, absolutely. What we were able to do is identify different parts of our tech stack that were just either deficient or duplicate. So they're just like, we don't want any duplicate efforts, we just want to be able to have a single platform that does things well and Matillion helped us identify all of those different and how do we choose the right tech stack. It's also about like, Matillion's so easy to integrate with any tech stack, you know, it's just they have a generic API tool that you can log into anything besides all of the components that are already there. So it's just, it's a great platform to, you know, help you do that. The three things we always say about the data productivity cloud, everyone ready, we spoke about, this is with the low code, no code, quasi technical, quasi business person using it through to a high end data engineer, you're going to feel at home on the DPC. The second one, which Ho-Chang was just alluding to that is stack ready, right? So it's built for AWS, built for Snowflake, built for Redshift, pure tight integration, push down ELT, better than you could write yourself by hand. And then the final one is future ready, which is this idea that you can start now super easy. And we buy software quickly nowadays, right? We spin it up, we try it out and before we know it, the whole organization is using it. And so the future ready talks about that continuum of being able to launch in five minutes, learn it in five hours, deliver your first projects in five days, and yet still be happy that it's an enterprise scalable platform five years down track, including integrating with all the different things. So Matillion's job holding up the end of the bargain that Ho-Chang was just talking about there is to ensure we keep putting the features, integrations and support into the data productivity cloud to make sure that Ho-Chang's team can continue to live inside it and do all the things they need to do. Hushing, you talked about the speed to insight being tremendously fast, but if I'm looking at Cisco Meraki from a high level business outcome perspective, what are some of those outcomes that a Matillion is helping Cisco Meraki to achieve? So I can just talk in general, not giving you like any specific numbers or anything, but for example, we were trying to understand how well our small and medium business campaigns were doing. And we had to actually pull in data from multiple different sources. So not just our instances of Marketo and Salesforce, we had to look at our internal databases. So Matillion helped us blend all of that together. Once I had all of that data blended, it was then ready to be analyzed. And once we had that analysis done, we were able to confirm that our SMB campaigns were doing well. But these are the things that we need to do to improve them. When we did that, and all of that happened so quickly because they were like, well, you need to get data from here and you need to get data from there. And we're like, great, we'll just plug, plug, plug. We put it all together, build transformations, and we produced this insight. And then we were able to reform, refine, and keep getting better and better at it. And we had a 40X return on SMB campaigns. It's unbelievable. And there's the revenue tie-in right there. Matthew, I know you've been super busy, tons of meetings, you didn't get to see the whole keynote, but one of the themes of Adam Salipsi's keynote was, you know, the three-letter word of ETL, you know? They laid out a vision of zero ETL, and then they announced zero ETL for Aurora and Redshift. And you think about ETL, I remember the Hadoop days, they said, okay, we're going to do ELT, which is like raising the debt ceiling. We're just going to kick the can down the road. So what do you think about that vision? How does it relate to what you guys are doing? So there was a, I don't know if this only works in the UK, but it works globally. There was a good line many years ago, rumors of my death are premature. So I think it was an obituary had gone out in the times by accident, and that's how the guy responded to it, something like that. It's a little bit like that. The announcement earlier within the AWS space of zero ETL between platforms like Aurora and Redshift and perhaps more over time, is really about data movement, right? So it's about do I need to do a load of high cost in terms of coding and compute movement of data between one platform and another. And until then we've always seen data movement as an enabling technology, which gets you to the value add of transformation. My favorite metaphor to bring this to life is one of iron. So the world's made of iron, right? World is literally made of iron ore, but iron ore isn't useful until you turn it into steel. Loading data is digging out iron ore from the ground and moving it to the refinery. Transformation of data is turning iron ore into steel. And what the announcements you saw earlier from AWS are more about the quarry to the factory bit than they are about the iron ore to the steel bit. And so I think it's great that platforms are making it easier to move data between them, but it doesn't change the need for Hoshang's business professionals to refine that data into something useful to drive them out to the company. Like that, it's quarry to the factory here. And a very snowflake like in a way, right? You make it easy to get in, once it's in, then we can do... It's like, don't get me wrong, I'm great to see investment going into the Redshift business and to the AWS data analytics staff. We do a lot of business there, but yes, this stuff is also there on snowflake already. I mean, come on, we've seen this for years. You know, I know there's a big love fest between snowflake and AWS because they sell it so much business in the field, but look, we saw it separating compute from storage, then AWS does it, and now, you know, why not? It's a good sense, that's what customers want. They're customer obsessed. Data sharing is another thing. And if you take data sharing as an example from our friends at Snowflake, when that was announced, a few people are possibly, he said, oh, Matthew, what do you think about this? You're in the data movement business. So I was like, ah, I'm not really actually. Some of my competitors are in the data movement business. I have data movement as part of my platform. We don't charge directly for it. It's just part of the platform. And really what it's to do is to get the data into a place where you can do the fun stuff with it, of refining NC Steel. And so if Snowflake or now AWS and the Redshift Group are making that easier, that's just faster to fund for me, really, so. Yeah, for sure. Last question. A question for both of you. If you had, you have a brand new shiny car. You got a bumper sticker that you want to put on that car to tell everyone about Matillion, everyone about Cisco Meraki. What does that bumper sticker say? So for Matillion, it says, Matillion is the data productivity cloud. We help you make your business, your data business ready faster. And then for a joke, I'd write, which you're going to need in the face of this tsunami of data. So that's what mine is saying. Love it. Hosheng, what would you say? I would say that Cisco makes some of the best products for IT professionals. And I don't think you can really do the things you do in IT without any Cisco product. Really phenomenal products. We've gone so much beyond just the IT realm, so it's been phenomenal. Awesome. Guys, it's been a pleasure having you back on the program. Congrats to your now Hosheng and alumni of the Q. Thank you. But thank you for talking to us, Matthew, about what's going on with Matillion. It's so much, since we've seen you last, I can imagine how much more is going to go on until we see you again, but we appreciate, especially having the Cisco Meraki customer example that really articulates the value of data for everyone. We appreciate your insights and we appreciate your time. Thank you. Privilege to be here. Thanks for having us. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage.