 Hey, good afternoon everyone. It's theCUBE, the leader in live tech coverage. We're live at Snowflake Summit 2023 from Caesars Forum in warm, sunny Las Vegas. Lisa Martin here with Dave Vellante. Dave, we have two and a half days of break content. One of the themes that we've been talking a lot about lately is sustainability, companies wanting to be net zero. We're going to be talking with our CubeLum Matillion and their British customer EDF energy and how they're helping Britain be net zero with Snowflake and with Matillion. Great topic. Big topic, yep. Big topic. Please welcome back one of our alumni. Matthew Scullin is here, the founder and CEO of Matillion. Thanks, Lisa. You're bright green. So nice to have these t-shirts back. We went kind of low key for a couple of years and we thought, no, we like the bright green. So we can spot you anywhere. It feels like home. Doesn't it? Alex Reed is here as well, senior manager of data platforms for EDF energy. Welcome, Alex. Welcome, Matthew. Great to have you guys. Thank you. Thank you for having us. We talked about, and I saw there was a video this morning, a customer montage in which EDF energy was featured talking about Britain being net zero. That's a hot topic for any organization to achieve. Give the audience just a little bit of understanding of EDF energy. I mentioned you're out of Britain, but give us kind of that backstory. Sure, so at EDF we have a mission to help Britain achieve net zero. My role within that is making sure we bring data into our data platform that can serve data science products that help our customers reduce their energy, which then plays a dual role of helping Britain achieve net zero. So that's something I'm passionate about as well. Something that currently is passionate about. And yeah, that's mainly my focus as a data. Can you explain net zero versus carbon neutral for the audience? Sure, so net zero is helping, making sure that we've got the right energy mixes in the mix, say renewables, nuclear, solar, wind power, that helps the carbon offset of Great Britain. All right. So Matthew, I love this story because last year you remember we had Harveer Singh on from Western Union. So as a financial example, now you're in energy so you're proving that you're horizontally scalable here. So give us the update on Matillion. Yeah, and Dave on that, it's sophisticated data teams for whom productivity is important. So that's the common DNA between Alex and his team at EDF, between our friends at Western Union and the over 1,000 other joint snowflake customers that Matillion's lucky to partner with. So that's the common thread. The world's most ambitious data teams use our platform. The update on this occasion is a big one. Matillion was launched in October of 2015 and the product that we're perhaps most famous for is Matillion ETL. But today, this morning, we have launched the next generation platform, the Data Productivity Cloud, which is an end to end integrated platform building on the years of experience we've had across tens of thousands of users making data business ready to make data teams wildly more productive, which we think is important on what the industry's been asking for. So that's the update, Dave. So how does that affect you, Alex? Are you taking advantage of the data productivity capabilities? How are you applying them? Oh, absolutely. So as you can imagine at EDF, we have a bunch of data sources, first party data, market data, third party data, industry data. And the big challenge for us right is bringing that data into one location and making it business ready. So Matillion Data Productivity Cloud is enabling us to bring the data into our data platform, store it in one location that they can then conserve multiple products across the organization. And that data platform is Snowflake? Snowflake, yep. Or Snowflake Plus, we saw Fidelity that 170 databases up in the keynote today. No, very much, Matillion, Snowflake hand in hand, driving those data products together. That really is the data strategy, is coalescing around that step. We had thought that unashamedly, less is more tech strategy. So before we had, you know, dozens of tech vendors, data siloed across multiple different platforms, different ETL tools. And recently we've undergone a different initiative, is quite literally getting the minimum amount of vendors that we need in order to drive data outcomes. And this is very common. I think in the kind of the first stab that the industry took at doing data integration, what we've seen is a proliferation of vendors doing part of the story. There'll be a vendor that moves the data, a vendor that transforms the data, maybe a vendor that's then brought in to orchestrate that because it's become complicated and required special skills. And so I think what Alex is talking about there and hold me to account if you disagree, but the Data Productivity Cloud is a platform that allows customers to move, transform, orchestrate data in one place. And you know, in today's economic weather particularly, I think that's becoming an imperative for customers. But you've got to do it in a way that's not compromised and we call that everyone ready. And so you have the low code, no code visual experience which allows a wider audience of people to make data business ready, but also a high code experience where SQL and Python and DBT developers can also build on the platform and get benefits that it's impossible to get if they're doing it, not being on an integrated platform like Data Productivity Cloud. So is that true? That's one of the game changes for us. So historically, as you can imagine on historical tooling, we would have had to have large teams with data engineers, dev ops engineers in order to provision data platforms and then build our data pipeline, sorry, with Matillion, because it's a low code, no code user friendly UI, we can roll that tool out to, you know, quite medium-skilled data analysts, for example, who can then go on via the tooling and start playing with data, driving data outcomes via the Matillion tooling. So that has been a game changer. A game changer, how long have you guys been using this and what are some of the key business outcomes in terms of EDF's overall mission that this is helping to facilitate? Okay, sure. So we've been using Matillion for about 12 months now and if I think about some real core outcomes at Strove, aligned with our mission statement, so first of all, Energy Hub. So Energy Hub is a tool that allows customers to review their energy usage and the appliances and then they can naturally start tailoring it to their needs. And Matillion was key in bringing data to the data model that drove that. Then customer proposition, so targeting Green Deal energy products that our customers. And again, Matillion played a key role in bringing the data into the data platform, bringing it, getting it data-ready, targeted at customers. And finally, the two turn down tools. So that was a national energy grid sort of initiative in order to get customers to reduce their consumption at peak times. So again, Matillion was key in bringing data and getting it in business-ready shape and format. For those end users to be able to really understand exactly what they're using, dial that down so they can save money. Hugely impactful. Yes. It makes you super proud to be a part of it, to be honest. This business outcomes are EDF and Alex's team, but to be a small part of helping the way a large nation manages its energy demands. And we see this across our customers. And I think it's because the data engineering piece is so important, right? I mean, it's 80% of the work in delivering a data use case is making the data business ready. So if you can unlock a drastic increase in the productivity of teams and organizations to make data business ready, you can be a part of delivering these amazing outcomes that, in Alex's case, literally make the country and the world a better place. So you obviously have a lot of data, a lot of metrics. What are the ones that you really look at? And can you, like you mentioned, DBT, can you API-FI them? What are the key metrics that you're really, that are really driving your business? Okay, so customer value is one. So making sure that we understand our customers, understand their needs, what products they want to use, what services they want to use. Then other value metrics are things like our regulatory requirements. So that plays a big factor in how we use tools and the data that we use and how we provide those services. And then making sure that tooling is available to users, right? Data accessibility, that's another key value metric that we measure against, says, how accessible is our data? Or how easily can users get their hands on data and then use that to drive their data science products, drive their analysis and visualizations, whatever that outcome is. What do we need to know about this survey? Again, 90% of data experts seek to alleviate workload increases from fragmented pipelines and overwhelming business demands, right? Is this? So, thanks for bringing the survey up. The fundamental raise on that, you're of Matillion, is to help organizations, teams and individuals to become wildly more productive in the quest to make that data business ready, which, as I mentioned a moment ago, is the bulk of the work. It's the bit below the waterline of the iceberg in any data use case. So, we thought, well, gosh, we better bring some science and research to that story. And we surveyed 900 data teams, individuals, some current Matillion customers, many not, to ask them what was going on. And the results were marked and striking, really. So, the first thing that I'd mention is 90% of those surveyed said that they had more demand for what they were doing today than only a year ago. And nearly 90%, I think it was 83%. I was trying to remember all the stats. 84, thank you. 84%, talked about the difference in the maximum amount of work that they can get done, the maximum amount of data they can make business ready to serve use cases in the organization, being less than the demands of the organization. You know, that's having some impact. So, third of the people that we spoke to were reporting being burnt out. And I think that's why we see high turnover, which not only has a human impact, but does to the business as well. Because with complex made up of bits and pieces, tech stacks, the ramp time of new people onto projects is really high. But maybe the most startling one, and the one that we feel that our company, and certainly today, the launch of the Data Productivity Cloud is all about, is 99.8. I don't know who the one person was that disagreed with this, but 99.8% of the people that we surveyed said we can do this better. The way that we're doing it now is not optimized for the best level of productivity that we can achieve. It's that story, that feedback from those 900 survey respondents that we built the Data Productivity Cloud for, like, for that audience. Well, I'm happy to confirm I wasn't the one. Yeah, you're right. Thank you. But you know, not yet. Not yet, no. So the Data Productivity Cloud, big news announced this morning. Where could customers get their hands on it? What's kind of the evolution for existing customers to be able to take advantage of this? As you said, 99.8% said we can do this better, so the opportunity is there. Yeah, so the really good news about the Data Productivity Cloud is it's super easy to get up and running with. So if you're here at Snowflake Summit, you can come by to our enormous and very beautiful booth, is this color, obviously. You can also go to our experience center at Chao, where we've got dozens of our sales engineers and team giving out demos and signing people up at the event. But for the wider audience and beyond Snowflake Summit, you can go to the all-new Matillion.com. It has our lovely new branding and it all moved over this morning to talk about the Data Productivity Cloud. And you can launch a free trial, get 500 free credits. A key design goal for the Data Productivity Cloud is a concept we call 10 Minutes to Wow. And that's going from Matillion.com to having built your first working data pipeline in under 10 minutes. And in reality, it takes three to four minutes. And that's not, your sign-up's done, that's a working data pipeline. Now we're here at Snowflake Summit and we've chosen to launch Data Productivity Cloud with Snowflake as our launch partner, share over a thousand customers together. Snowflake are actually a co-owner of Matillion, an investor on our cap table. And so we're launching at Snowflake Summit. Support on the Data Productivity Cloud is for Snowflake and on AWS. And as part of the 10 Minutes to Wow experience, if you don't have access yet to a Snowflake Data Warehouse or Cloud Data Platform, or you do, but it's hard for you to get the credentials, as part of that 10 Minutes to Wow will actually stand you up, your own Snowflake Data Warehouse. And you can go crazy and play around with the product. So that's how you get started. There was another part to the question, Lisa. I'm just so excited, I forgot. I'm just so, 10 Minutes to Wow, that's impressive in terms of how quickly you can get customers on board and making impact within their organizations to be able to maximize the value of all their data. That's it, there was two or three design goals we went for, 10 Minutes to Wow, unlimited scalability. And so I said I'd say something controversial for you. I will tell you, we have found the product to be so scalable that we accidentally killed Snowflake a few times, not the company, but our Data Warehouses a few times. It has this concept called unlimited scalability. You could be loading one file of data and transforming it 100, 1000 or 100,000 and the job execution time will basically be the same because it can parallelize it in an unlimited way. It has this amazing hybrid architecture which means you get all the benefits of SaaS but can run it optionally and if you want fully securely with the agents inside your public cloud account. And then finally, this concept of everyone ready where a low code, no code user like the ones Alex was describing, those kind of tech savvy business analysts through to a data engineer, through to a hardcore DBT or Python coder can all get a great experience. And on the DBT side in particular, I'll mention if you build your DBT jobs and choose to run them on data productivity cloud you can do things and get benefits that you can't by running them just normal DBT core or even on some of the dedicated DBT platforms. So we're really excited about it. And that SaaS element as well is another game changer for me. So being a platform design manager, I want to manage as little infrastructure as possible, right? So a hybrid architecture works perfectly for us and the more that cloud providers and software providers can manage the infrastructure for us, that helps us with not just skills retention but also provisioning services quicker. So that's another game changer in my eyes. So Alex, you're a year in, I'm inferring that even in that short time it's made an impact on your business, made you more competitive. If you had to do it again, if you had a mulligan, none of you guys golf, what would you do differently? Anything you would do to maybe accelerate that time to value? Yeah, sure. I probably would have took a more product focus quicker. So we have quite a traditional hierarchical structure and that's the way we attack data products and services. What we're looking to do now is transform our business from an organizational perspective as well and focus dedicated teams at dedicated products with cross functional skillset. So that's the journey we're going on. That's probably the trick we missed at the beginning from like an organizational perspective. Even with that said, when you're asked by prospects or other folks who might be interested in working with Matillion and Snuff Lake, what's your answer to when they say, why should I? Sorry, I didn't... Why should I work with Matillion and Snuff Lake? When people come and ask you for your opinion, what's your recommendation? Well, I think first of all, the relationship. We have a great relationship with Matillion. Matillion, I've been really honest brokers with us. Secondly, as I said, the software is a great, it's a fantastic platform, right? It caters for all audiences, I think. I think from hardcore coders down to data analysts with low code skills. And thirdly, the vision with data productivity cloud for me. Friendly UI, very slick feel, as you said about, what was it, the 10 minutes to wow? The 10 minutes to wow, yeah. We're super proud of that. So yeah, that's definitely a journey we're excited to be a part of. The thing that stands out for me, Alex, if you don't mind me saying, is the way that EDF have successfully widened the audience, put more players on the pitch in terms of making data business ready, because you've used the kind of easy to use user experience that we provide in the low code, no code piece, to say, well, look, you understand the business metrics and the business outcome we're trying to drive, I'm just going to give you the tools directly. And that's, well, we see that with a bunch of customers, but I think EDF have done that extremely well, paying you the compliment, my friend. That is true data democratization. Exactly. Your energy, Matthew, matches your green shirt. Thank you so much for joining us on the program. I'm excited to be on the show, that's why. I can tell when we love it, we're excited to have you, Alex, great to have you as well. Thank you, been a pleasure. Great work, guys. We can't wait to see and follow this journey and to see what happens in the next year. Once you get it done here, Lisa, come and try out 10 minutes to wow. I can't wait. I got to get 10 minutes from the boss, though. Okay. It'll be later, it won't be today. Okay. We have no time today. Can I get a green shirt? But tomorrow or Thursday. All right, I'll be there. Thank you so much for having us. Our pleasure for our guest and for Dave Vellante. I'm Lisa Martin. Up next, Snowflake and Instacart on advancements to the Snowflake platform, lots of stuff that was announced today. How it's helping customers like Instacart, which you might be a user of, with data cloud cost optimization and an update on the Aplica acquisition. Stick around, Dave, and I'll be right back with our next guest.