Episode Transcript
[00:00:00] Speaker A: Foreign welcome to this episode of our show, True DataOps. In fact, it is the last episode for season three. I'm your host, Kent Graziano, the Data Warrior. In each episode, we try to bring you podcasts discussing the world of DataOps with the people that are making DataOps what it really is today.
Now, be sure to look up and subscribe to the DataOps Live YouTube channel, because that's where you're going to find all the recordings from our past episodes. So if you missed any of the prior episodes this season or prior seasons, you can catch up there now. Better yet, go to truedataops.org and you can subscribe to the podcast.
As I mentioned, this is the last episode for season three. Season four will start up again in September after we have a good long holiday break for the summer.
Also, this is going to be the last episode for me. After three years, it's time for me to hang up the microphone and pass it on to someone else.
It's been a really awesome run chatting about the seven pillars of true data ops and the DataOps philosophy with some of the smartest people in our industry.
But even the great samurai warrior Miyamoto Musashi hung up his sword and became a hermit after years of successful duels. Well, I'm not going to become a hermit, but the Data Warrior is. Got to take another step down the road to retirement and spend some more time hanging out at the beach like I enjoy and seeing the country with my wife.
Now today, my guest is again co founder and CTO of DataOps live, my good friend Guy Adams. Guy is also one of the original contributors and authors of the true DataOps philosophy and the seven pillars of true DataOps. And also the co author of our book DataOps for Dummies.
With him making another special appearance in second time in basically a month, Snowflake Data superhero and data ops field CTO Keith Belanger. Welcome to the show, guys.
[00:02:04] Speaker B: Thanks for having us.
[00:02:06] Speaker A: Well, everybody knows, you guys. We don't have to go through the usual introductory stuff, but yesterday the news wires went crazy with the announcement about that strategic partnership with Snowflake that Keith and I talked about about a month ago. And then last episode with with John Marchese, we were talking about it. So tell me about that guy.
[00:02:30] Speaker C: Yeah, it's. I mean, yes, it's been crazy, but I think it's a, it's a lovely way to wrap up kind of three seasons. You know, when I look back to where we started, Ken, you know, way back when, you know, we would, you know, we, we set a lot of this up as a, you know, as an education exercise. You know, I, I, I remember that, you know, when we sat down and what do we want to achieve out of this? You know, so much of it was about trying to educate people about what day drops is, why it's important to them, you know, what is and isn't true data drops and that sort of thing like to come back three seasons later, you know, and, and to the day be able to announce, you know, and, and, and, and you know, now it's come, come mainstream, you know, the announcement of the strategic partnership with Snowflake where you know, not only do people, you know, know what data drops is and know why it's valuable, but we're now at the point where we're able to bring it to mass market basically for free.
So I think that you know, three, three seasons and you know, three years, that's a, you know, that's a heck of a development of the industry. So you know, it's, it's been pretty wild here as you can imagine.
You know, we've had, you know, I think we, the response to even the private preview has been phenomenal.
You know, more customers that we can, than we can really keep up with or having to, you know, really keep a reign on the private preview.
But you know, my team on the engineering side has been working incredibly hard to make sure that we are ready to go ga in summits. At that point, you know, all of the, all the limits are off. You know, everybody can go to the Snowflake marketplace and click go and enjoy the, the, the frictionless transformation and the frictionless delivery. So yeah, it's been pretty crazy but yeah, really enjoying it.
[00:04:06] Speaker A: Yeah, I know it's hard for me to get my head around the fact that customers are now actually going to get free access to the DataOps live platforms like the most advanced technology out there for actually running now what DBT on Snowflake and managing DBT infrastructure in addition to doing cicd, all the things we originally envisioned, given where we started. How does that make you feel, Guy? You know, it seems like, you know, kind of pretty good vindication of your original vision on all this.
[00:04:35] Speaker C: Yeah, you know, you start, you start out, you think you, you know, you think you have a good idea about a problem that you know, needs to be solved.
But back in those early days, you know, I, I remember the number of times, you know, when you, we, we just got on the call with people and you know, like, you know, what stay shocks all About. Well, you know, this is the way I've always done it, you know, so for, for an organization the size of Snowflake to come along and say, not only is this a problem, but this is a sufficiently big problem for the vast majority of customer base that we're prepared to, you know, invest a considerable amount of money and our partnership into, you know, into you so that you can bring all of this, you know, to, to the mass market customer base. So it is a vindication, It's a vindication that this, you know, I've, I've described it for many years as a niche industry, data drops as a niche industry. And in the big wide world of, of IT and technology, it's, it's, it's pretty small. But in the world of data, it's no longer niche, you know, it's no longer a nice to have, it' longer a, you know, you know, it's a leg up, it's, it's table stakes. If you're not doing this, you are radically falling behind everybody else. And you know, that's a, a maybe a good time to, you know, bring in the man that needs no introduction. You know, Keith, he was on the, the been on two or three times. I, I know, Keith, you're the 16th episode. The first time you wrong was actually the second most popular of all time on Spotify and Audible. So great, great kudos for that.
But you know, I think you've been a big practitioner, Keith, for many, many years, you know, across multiple organizations. Maybe you can reflect on, you know, what those challenges have, those recent challenges and why the frictionless offerings are facing so much for people.
[00:06:19] Speaker B: Yeah, I mean, absolutely.
You know, I went through my first Snowflake implementation back in 2020, which actually started in 2019.
Prior to that I was, you know, 15 years. We were over large teradata implementation. And when we were doing Snowflake, you know, the, I guess you could say the, the new terms around like, you know, infrastructure as code cloud was coming around, all these new regulations, all these things were, I want to say, pushed upon myself as the lead architect in terms of like, what are we going to do?
How are we going to do this? Snowflake was stood up in a matter of seconds. Here's your URL. We're ready to go. Didn't have to word or I didn't have to order infrastructure or worry about power air conditioning like we used to have. But here was this other problem which was how are we going to manage all of this stuff within Snowflake? All this stuff within aws, everything else that we're doing as code and we built at the time we called it Foundational Services. Now we're calling it Data Ops, but we were just calling it Foundational Services. And that put a good six months of extra work on our team because we were highly regulated organization and we need to have separation of duty. We had to have all the audits and controls, all the regulatory reporting and everything. We couldn't do anything inside Snowflake, at least not knowing who did it.
And we did that eventually. Along the way, met folks from, from Data Ops. And when I get in my consulting and future implementations, I'm like, we got to bring in Data Ops. I go, I'm not spending another three to six months building these foundational services again.
Yeah, again. Although all these developers love doing it, right? They love developing stuff, but you're not delivering business value. Right? Everything that we do from a data warehousing analytics position perspective is for the business, right? So the faster we're getting time to insight, time to value for businesses, the better.
And from my perspective, Data Ops brought that.
But now, you know, what I'm excited about is that we've even shrunk down like how fast we can do it. And I don't have to go through, you know, a customer out there does not have to go through a procurement process. Right. You can go to the Snowflake, you know, marketplace and you want to implement a CICD pipeline. Like you said, it's for free. You click on it, a few minutes later, we reverse engineer your current environment and boom, you have a modern enterprise grade CICD solution. And you know that you can grow into it. And eventually if you start getting the volume and you need cost, you're paying with Snowflake credits that everybody's accustomed to. So I think we really now fit into how everybody else uses Snowflake and everything else. You just start accumulating consumption and you pay with it with credits. And I think we're really much aligned in where Snowflake is going to, in, in general.
[00:09:08] Speaker C: So, yeah, I think you used a, used a key word there, enterprise. I think one of the things that's, you know, great that maybe a lot of people don't realize is, you know, the difference between, hey, I built it myself and it took me six months and I bought it. It's not six months. The difference is after six months I have something that is at level zero maturity as opposed to after one day I've got something that is battle hardened, you know, we count the other day, you know, 11,000 over 11, 000 data products. You go into production every day on data drops live. So you know, when we talk about these frictionless offerings, they're, they are brand new, they're, they're private preview, they're going ga. But in practice, the underlying technology there is battle hardened technology that we've been working on for over half a decade. So you know, it's, it's new in terms of the way we're delivering it, but the actual technology and the maturity is, is incredibly robust, empowering, you know, some of the world's biggest, biggest organizations out there.
[00:10:01] Speaker B: Absolutely. Yeah. It's been, I'm excited for the potential and I think every Snowflake customer out there will gain value with you. There's no customer that is not excluded from making and using, having value from what we're bringing to the table.
[00:10:21] Speaker A: Yeah, the ability to do CICD seamlessly was I think the original gap that we identified back when I was still the evangelist at Snowflake and working with a guy and Justin at Datalytics, like, you know, where are the problems? And yeah, everybody, every sales engineer at Snowflake, every professional services person at Snowflake that was out working with, you know, substantial customers was having to write this code like you said, spent six months developing the code. They were doing sessions at Snowflake Summit about how to do CID CD and you know, people trying to put out stuff in GitHub Open source libraries to, to figure out how to do this. And now you guys have like, it's, it's done right. Nobody needs to waste another second on figuring out how to do it. Because again, you know what, it's been what, five years, guy, you know, they've been able to do it in the DataOps Live platform and all the customers that have proven it out. And as you said, it's now, it is battle hardened. And now with the, in the marketplace offering, the frictionless offering, it's been packaged so you don't have to be an expert at all of this coding. You just have to understand the concepts. And now you can, now you can go out and do it.
[00:11:40] Speaker C: And I think the other thing that people are really starting to realize now, you know, in terms of build versus buy, it's all about opportunity cost. It's like, what would you rather do? Would you rather spend, you know, six, nine, 12 months, you know, banging your head against the wall trying to piece together, you know, 23 individual components or would you rather spend the same time, you know, at the other end of the spectrum, you know, learning how like the latest, you know, cortex AI stuff can, can move the needle for your business, right? Valuable, you know, just re engineering well solved problems or using the, you know, looking at the bleeding edge stuff and saying how, you know, how can I be a hero and change the way my business works with AI, you know, and more and more people saying I've got no interest in, you know, solving that stuff. On the left, that's kind of mundane table stake stuff. Let's just, you know, check the box. Let's go and let's use the time we freed up to explore this, the bleeding edge, the exciting stuff.
[00:12:28] Speaker B: One thing I want to add in there that I think is a hidden gem in what DataOps does in its CICD process is people are used to well, I have a dev environment, I have a QA environment and you do this test process.
We leverage the powers of Snowflake Zero copy cloning. And so now I have feature branch ephemeral environments that have production grade data in them to test with so I can test at scale and when I'm done tear it down, not pay the extra cost.
To me that was when we were delivering. I had up to 13 agile squads going. How do you keep 13 agile squads going at scale and at pace? Right? It's boom. Each of you have a feature branch environment, each of you are doing what you need and it's bringing those concepts but also to the scale that enterprise organizations and data engineering teams need and being agile with them and then having a quality solution when you're bringing it to production.
[00:13:33] Speaker A: Yeah, Zero copy clones got to be my all time favorite. It was one of the selling points when I originally went to work for Snowflake when, when they started talking about that, one of the presentations is like, yeah, I mean sign me up and.
[00:13:48] Speaker C: You know, those have been working with so long, you know, we just forget the benefits of that. But I think, you know, and it's true across all of the true data ops philosophies but what we're now seeing is some of those technologies and as they're implementation ops actually starting to get a brand new lease of life. I was talking to a customer the other day and they were, they were bemoaning, you know, that they're using, you know, generative AI for, for all sorts of stuff on their back end and they're promoting, you know, new models coming out every week and you know, Snowflake supporting all these new models. But you, how do we know which model is going to work best for me. It took us six months to pick our first model. It's like, that's not going to work. So I showed them how they can use that same concept that we use for feature branch development. Say, look, just put a list of the latest models in here, press go. It'll spin up 10 environments automatically. It'll run your pipeline with each of the 10 different models and you can look at the results. At the end, you decide which one of those is best and merge it to dev and that's it, you know. So it's now a completely automated process set that to run once a month. And every month you're now, you know, with, you know, 10 minutes of visual checking which one you like best. You're now constantly able to move forward with models as the new ones come out. And they were, they were blown away by that. They knew the capability, but they only thought about it in terms of feature brush and they hadn't thought about it as a mechanism to kind of, you know, parallel try, try the model development new things.
So it's really cool.
[00:15:09] Speaker A: Yeah, that's awesome. So recently again with the press release and some things that happened here in the last couple of months, there's a lot of focus on DataOps live right now.
[00:15:19] Speaker C: Yeah, it's been, it's been incredible to win the Data Ops Company of the year from the Data Breakthrough Awards.
On the back of our huge award from Snowflake Summit last year.
I'm actually in a little under an hour doing a webinar with Matt Aslit, the director of research at isg. They've done an incredibly comprehensive set of actually five different buyers guides across all, all different aspects of data drops. And it's a total, think it's 85 players in total they analyzed and Data Ops is in the top three in every single category and the number one overall in terms of data functionality. So, you know, that's a, for us data for Data Ops Live. That's an incredible validation. And this is going up against Microsoft and you know, Google and aws. I mean this is going toe to toe with the, the biggest and baddest organizations out there and saying, you know, what if you're trying to do data drops, particularly drops from Snowflake, you know, there's, there's only one place to go. So a lot of great recognition and you know, more in the pipeline, more I can't comment on yet, but you know, watch the space.
[00:16:25] Speaker A: Awesome. Awesome. So throughout the, the season three here we've been spending a Lot of time discussing the seven Pillars, their continued relevance in the data world, especially with the massive growth of AI adoption as you're kind of referring to. So as we close out the season, I thought it'd be great if we do a little time traveling retrospective on the seven pillars and everything that led us to really envision what we, we called hashtag truedataops. And we did take a lot of flack for that, by the way, early on.
How dare you call it True Data Ops like the rest of us aren't doing it. Well, you aren't. So sorry. But truth is the truth. Yes. Like, we gotta refine, we got to find these things, we got to make people think about it. And apparently we did.
So I think, you know, who better to discuss all this with than you guys since this really started when you joined Justin at Datalytics all those years ago.
So let's hop into the wayback Machine here and let's talk a little bit about how started and how we got from DevOps to now.
True Data Ops.
[00:17:34] Speaker C: It's, it's funny, you know, the, the true data drops.org website, you know, once a year or something I, you know, I'll go revisit and you know, with the, with the view in my head that, you know, look, right, you know, four years has passed, you know, five years has passed. You, we've gotta, you know, we've got to do a refresh of this. We've got to bring it up, you know, we've, we have the, the, the industry has evolved, you know, beyond all recognition since we, since we did this. It's got to be out of date. And then you go back and you look at it, you think, actually, you know, I could look at every one of those pillars and I could, you know, I could absolutely, adequately explain why it's as relevant today as it was, you know, nearly five years ago now. The interesting, the explanation might be different. The world's moved on. So what we mean inside those are somewhat different. But the fact that the actual pillars themselves are still as valid today as the day they were created, I think is a, it's a great kind of reflection for all those involved in this in the early days, you know, including yourself, Kent, that, you know, we built something that's really stood the test of time. I mean, like, you know, if I, as an example, you know, working with a customer a couple of days ago on, you know, and we look at some of the pillars like, you know, component design and maintainability, you know, breaking things into Small reusable components, you know, and automated testing as two separate pillars.
You know, one of the things that they're doing is enterprise semantic validation. They're defining within Data Ops these global concepts like, hey, this is a satellite ID or this is a customer id. They're defining it once, but they're not just defining it, but they're saying, right, this is what it should look like. This is how we're going to test it, this is how we're going to validate it. And then they're saying, right. And that now appears in 65 places across 27 data products, across 14 teams. But all we have to do is with a semantic definition every single time.
It applies all the same tests, you know, across the board. Now we never envisaged that was way beyond our horizon when we came up with this. So it's a new use cases, new problems, but they fit into the, you know, they fit into those same models. So, you know, it's, it's been nearly five years. I think it's absolutely still valid. I'm, you know, hopefully we get together in another five years and see if the same is still true.
[00:19:41] Speaker A: Yeah, I guess it's fair to say that when we, we develop that, I mean, I know we patterned it kind of after the principles of Agile because you had the Agile Manifesto and you had the principles of Agile and so somebody had already done the Data Ops manifesto, but there wasn't any of the lower level things that we kind of, this was kind of our goal, right, to build things to help people understand really what it was and what the component parts needed to be there. I use the term component even there to, in order to really approach this Data Ops thing and make it successful.
[00:20:27] Speaker C: The other thing that I think, you know, that the industry has, you know, truedayshops.org to thank for is, you know, that true bit because, you know, I mean, it was what, 18 months, two years after we started out that all of a sudden, you know, Data Ops as a, as a principle hit that point of the hype cycle that everybody wanted to be data drops and you know, everybody that got a, you know, a Data fabric, a 10 year old data fabric tool, you know, put a couple of basic automation features in and called it day drops, you know, and I remember going to, you know, Snowflake Summit and Big Data London, you know, and you go around and you count, you know, last year I counted, you know, two companies with data drops in their branding. Then the following year it was 22 and then it became 40 and you know, I used to call it Data Ops Washing it was, it was a cool thing and everyone wanted to be identified with it. But, you know, I spoke to customers who said, we used those principles of true Data ops. Org as a check and balance and say to customers, okay, you know, Mr. Vendor claiming to be, you know, a Data Ops product, Data Ops capability, show me how you fit in with the pillars. And they look a bit sheepish and say, well, actually we don't at all. We, we do one thing that's sort of orthogonal to that. So I think one thing it really did do was act as a, as a framework for customers to be able to separate, you know, for a better phrase, you know, the, the true Data Ops players from those who were, you know, on a bit of a marketing mission. And I think what that has done is we've got over that hump now. You know, there are very, you know, many of those players that adopted Data Ops branding have now kind of moved away from it to something else. You know, a lot of them, you know, probably replace it with AI or something different.
But you know, in the main, the players left that are talking about data drops are in some way shape or form genuine daytrops players. So I think that's something that, you know, we all have two day drops as a set of principles to thank.
[00:22:09] Speaker A: Yeah, well, along those lines, let's talk a little bit about, you know, the evolution of this concept. I mean, really, we kind of, it defined a whole new market and a tool category. You know, what you're talking about there.
[00:22:23] Speaker C: Yeah, I mean, you know, when we first started out, you know, you know, I won't, I won't name necessarily all of the names, but I remember, you know, we were doing analyst briefings and, you know, we were talking about data drops and I would see like, you know, whole big chunks of sentences and paragraphs of mine appearing in, you know, people's, you know, market guides and things like that. And you know, back in the early days, you know, we were really driving that. But these days, you know, every analyst has got it as a, as an area. You know, every market guide, every, every magic quadrant or every, you know, everyone's got their own quadrant. You know, all the buying guides, all the product guys, you know, now all have this as a very well understood category.
So, yeah, it's mainstream. There's no better way to describe it. It's fully mainstream.
[00:23:06] Speaker A: Well, even inside of Snowflake, the Snowflake Solutions center that you guys helped develop, I mean, it's being used by what, over a thousand sales engineers and field CTOs all over the world now inside of Snowflake to help deliver to Snowflake's customers.
[00:23:23] Speaker C: Yeah, and in fact one of the, one of the more recent developments we've been working on with Snowflake as another way of using the data ops platform is hands on labs. You know, real, real big challenge for, for any organization that's tried to do it. You know, you get 100 people in the room of whom 99 have not got the prerequisites, 98 haven't got the right permissions, you know, 90s haven't great account set up, you know, and the success rate in terms of getting customers from signing up to the aha moment that you hoped when you built the lab, you know, I think across the industry is single digit percentage and pretty low single digit percentage of that.
We, we start, we pioneered this or rolled this out to test at Snowflake's Build a Mirror event. And we got, I think 95 of people in the room actually got on, started doing the lab. I think we had 65% of people hit that aha moment. Now 65 doesn't sound a lot until you compare it to, you know, the industry historical average which is, you know, sort of 5%. So that was incredible. And now Snowflake are using that and that's going to be an enormous feature at Snowflake Summit coming up. I think there's north of 20 labs and you know, potentially 7 to 8,000 people are going to be doing labs at Summit that are all powered by datashops live.
[00:24:37] Speaker A: Yeah, that's awesome because I remember early Snowflake Summits and how much work people had to put in to set labs up. And having done that at the Data Vault conference and a couple of other places over the years myself, it's like, you know, trying to get demo set up and get everybody actually in the demo, the hands on session working within five minutes like nobody was ever able to do, nobody ever pulled that.
[00:25:00] Speaker C: It's one of the easiest things to say if you, if you meet a person that's ever tried to run a hands on lab themselves, you don't need to sell it. You say it does five things for you, like yeah, done, that's it.
Yeah, I know the pain of doing that.
So I think it's, you know, I mean, turning it around a little bit. Ken, you know, we talked about three seasons and it seems, it seems longer. I mean the, the chunky seasons as well. You know of the TDO podcast I think it's 53 episodes in total.
You know, 1600 minutes ago, 26 and a half hours of podcast. That's a full, A full day of your life, Ken, over the last how many years?
[00:25:36] Speaker A: That's just the on air part.
[00:25:38] Speaker C: That's just the on air part. Yeah. I mean, you know, people, people don't realize how much goes into the front and back end of this to make it all happen. And, you know, all the people, you know, behind the scenes that, that, that we depend on, you know, I think it's well, well north of 31,000 people have watched these podcasts in, in some form or other. And so many great guests over the years. You know, you know, Wayne Erson, you know Barz and Frank Bell, Mark Balindy, Sanjeev Allison, Sa Graves, Randy, Dan Linstead, you know, Joe Rice, Kevin Blair, Andrew Helison from Snowflake, Dan we were talking about earlier, Paul Rankin, Mike Ferguson, you know, even, even Bob Mulier, you know, the former CEO of Snowflake.
It was so many fantastic guests. And, you know, and credit to you, Kent, for, for getting so many of those on board. You know, we can't name them all. And of course, you know, the, the elephant in the room, the one person who we, we kick this off with, you know, you and, you know, you and I, Justin, who, you know, we lost last year, which, you know, so, but it's, you know, he would be incredibly proud of, of, you know, where we are and what we're doing. So.
Do you have any particular memorable episodes from such a big back catalog? Must be hard to pick.
[00:26:42] Speaker A: Yeah, yeah. I mean, and then you have people like Keith, who's actually been on three times, at least I think through the evolution of his career, because the first time he was on, he was a practitioner. That's why that episode was so popular because, hey, we got somebody who actually is doing data ops in the field, doesn't work for Snowflake, didn't work for you guys at the time. He was out there as a consultant.
You know, he's been on multiple times. Frank Bell, always a popular guy. You know, great, great conversations with him, having Dan Linstead on and then Cindy Meyerson from the, the Data Vault alliance and being able to see how what we had developed here in the data ops world matched so well with their data vault methodology. You know, that, that was, that was great.
Talk about, I try to remember who I talked to Data Mesh, talking about Data Mesh and how this fit in great with Data Mesh.
I think, you know, my, my Favorite one probably, probably was Bob, you know, having. Having Bob Mowgli on as he was starting down, had just published his book about the datapreneurs and about the future of AI because, you know, Bob was the CEO who, who I first met when I joined Snowflake and He was the CEO and it was 100 people.
And my first experience actually getting to work directly with a senior executive and somebody who had been president of the server division at Microsoft. He literally went to work for Microsoft when he graduated from college and stayed there up until shortly before he ended up as CEO of Snowflake. And so getting to work with him, you know, I learned a lot from him and then being able to then have him on the show as he was now on to his, his next, next part of his career out there as an advisor and, you know, helping really shape, shape the industry. So I think that was great. And then having Vernon Tan on when from Snowflake, when we were talking about the Snowflake Solutions center again, having been at Snowflake very early and know what, having had to build a demo myself and, and go through the process to be able to see that evolution and talk to Vern about his vision and what they were doing with the data ops stuff to, to empower, you know, which was now, now, you know, a thousand people inside of Snowflake when, you know, there was 100 people when I joined and now there's just a thousand sales engineers and field CTOs all over the globe. So that, that was a lot of fun. And of course, every year you and Justin and I got on at the beginning of the year and did the, you know, what's going to happen this year in the world of data ops, you know, so that, that was always fun and enjoyable since, you know, again, this was being able to talk about the joint vision that you and Justin and I had early on and what we were going to do. So, you know, a lot of good memories there. Definitely.
A lot, A lot of fun, a lot of very interesting conversations and, you know, go.
Conversations that went in a lot of different directions sometimes that, you know, none of us expected.
All right, so, you know, we gotta wrap up here pretty soon. So coming up next, it's, I guess Snowflake Summit. It's a few weeks away. Right.
What are you going to be doing there, Guy?
[00:30:10] Speaker C: Yes, we'll be there in fourth. Keith and I will both be there sporting our rather natty jackets.
Superhero jackets. Yeah. So I'm doing a lot of presentations mainly around, yeah, the, the frictionless Offerings, but particularly focusing I think on, on the enterprise dbt. You know, how do you, how you take the, you know, the, the DBT project you've got today, you know, and, and add all, you know, with completely seamless import at all of those enterprise capabilities of environment management and proper governance and you know, proper deployment and auditability and traceability and all the other good things that you know, kind of the, the, the top 10% of, of customers have been able to enjoy and just bringing that to, you know, bringing that to everybody. So that's kind of really our focus and you know, we're, we're expecting a, a huge.
But you know, one of the things about building you know, product LED products is that, you know, everything is self service, everything is just you know, click, click, you know, you know, guides. You could, you can understand the entire product in 10 mouse clicks. You know, so it's, it's really great to move from, you know, what's historically been, you know, very enterprise motion to that, that product led.
So yeah, it's going to be a great, it's going to be a great event. Keith's going to be there as well, you know, doing a lot of data stuff, doing a lot of his own stuff as well.
[00:31:31] Speaker B: Yeah, I mean I'm hoping to, you know, this is, you know, every single person at Summit, right, has the ability to leverage what we have to offer. And so, you know, how many people can we get the word to, right? Whether it's like you said, you know, operationalizing their DBT or every single snowflake customer has to deploy objects into snowflake, right? How are they doing that? So that, so 100 of the people there, you know, and so, you know, my, I'm hoping to connect and interact with as many people there is to really get them to understand what we're doing and how it can benefit them. So it's, I'm looking forward to it and yeah.
[00:32:13] Speaker A: Awesome. Okay, so you, the booth, the data ops booth at Summit booth number 1901. 1901. So be sure, you know, look these guys up there. And then on June 3rd at 2:30, something's going on in Basecamp North.
[00:32:31] Speaker B: Yeah, Guy's doing his theater demonstration of our dynamic apps.
[00:32:36] Speaker A: Yeah, awesome.
[00:32:37] Speaker C: Live demo is always good fun.
[00:32:41] Speaker A: Very good. Yeah, that's always fun. So you were obviously focused on Summit, but Guy, I know you're always working a few cycles ahead. What should we be looking out for in say the next six months over the summer here?
[00:32:55] Speaker C: Well, I mean the first thing is these two frictionless apps delivery and transformation are just the first two in, in what we envision to be a, a larger suite.
So we're going to have things coming on board for building Cortex AI applications, streamlit applications for leveraging Snowflake Notebook. So there'll be a, there'll be a, a range of additional, you know, focus use cases in, in the Frictionless, in the Dynamic suite.
I think there's going to be, you're going to see a lot more from us about your data products. I think really taking, you know, we, we way back in those early days, you know, in, in data drops for dummies and data products for dummies. We were some of the, the very early proponents of this and you know, a lot of product work's been done, but I think, you know, we're now at kind of, I would say almost like a v, a complete v2 of data products in terms of really understanding, you know, what they mean and, and how you get massive enterprise evaluation. Because, you know, we, I don't think we've got a customer that I'm working with that isn't really just trying to do things in a very, very productized, you know, way. And then I think the third piece is, you know, I, and it's hard because everybody says it, but we had a, we had a huge engineering and product off site for a whole week where we essentially came away with, you know, this is how we're going to restructure both internally how we work but also how our product works for our customers to be fundamentally AI first. And you know, the, the figures that, the figures that I see and the experiments that I see coming out of our engineering product teams are just phenomenal. You know, I remember, I remember when the customer that came to us and said it takes us three months to get the data products into production and came back and said, hey, we're doing it in 15 to 30 minutes. Was blown away. Now I look at 15, 30 minutes. How is it taking that long? We're now looking at people building these products using our Data Ops assist engine and you're going from concept to data products in production in a minute or two minutes. It's just incredible, you know, getting to the point now where it can't get much faster than that because it's faster than anyone can think anyway. You know, we're, we're very much kind of hitting that, very much hitting that sort of, you know, Moore's Law limit of our own brains. But you know, it just the ability to build the so much so quickly and then, you know, allow people free up people's time and effort to focus on, you know, the really interesting stuff. The stuff, you know, the stuff they never got to work on before because they were too, you know, stuck in just grinding through the day to day of building these transformations and these automated tests. Once all that's gone away, you know, the thing, you know, the thing I'm most excited about is what, what our customers are going to be able to spend the time on once they don't have to worry about any of that, once that's just, you know, happening in, you know, they get all of that work done by 9:30, then what they're going to do for the rest, that's. That's really, really exciting.
[00:35:34] Speaker A: Yeah. Yeah. So for those that aren't going to be able to go to Summit, what's the best way to connect with you guys?
[00:35:41] Speaker C: Either by website, data Drops Live or, you know, both Keena, Keith and I on LinkedIn, you can find both of us pretty, pretty quickly.
[00:35:47] Speaker A: Awesome.
[00:35:48] Speaker C: Great.
So, yeah, I think we're probably coming up on time.
You know, before we wrap up, you know, just want to say, you know, on behalf of me and Keith, everybody who's been on the show, everybody at Day Drops Live, everyone in the industry, you know, people not in the. Not with us anymore, like Justin, you know, just a massive thanks to you, Kent, for being, you know, a cornerstone, a rock that, you know, the, the industry, but particularly this podcast has, has sat upon, sat upon your broad shoulders for, for a long time. So we, you know, well, well, well, deserve that retirement. I've seen the beach by your house. It's gorgeous. You need to spend a lot more time there.
[00:36:28] Speaker A: That's true. You have been there, haven't you?
[00:36:30] Speaker C: Right by your house. We had a great time there. So, yeah, spending more time there. Enjoy it.
[00:36:35] Speaker A: That's what, that's the plan.
Well, thanks, guys. Thanks for being here and being, being the guest close out this season.
Always a pleasure chatting with you and thanks to everybody online who joined us today. As I mentioned, this is the last episode of season three. Season four will start up again in September, and as I said, I'm not going to be the host, but I'm really glad to announce today that I'm leaving the show in the great hands.
Mr. Keith Belanger will be taking over as the host for the True Data Ops podcast.
So looking forward to seeing what he does with it. You know, when I'm not on the beach, you know, I might have to watch the replays.
[00:37:19] Speaker B: Replays.
Yeah, it's, it's, you know, I get some big shoes to fill. You've been a true warrior, you know, the Data Warrior over the years. You know, I, I seem, everywhere I go, Kent, I'm like right behind you. Kent's over here. And there's Keith coming right behind him. So kind of following in this foot spits of Kent, you know, you were the, the OG superhero, you know, now I'm there and, and I'm happy to be here, Take on the baton and keep on the battle in the fight to, to bring this message to, to the, to the folks in the, in the data space. So looking forward to it.
[00:37:59] Speaker A: Excellent.
[00:38:00] Speaker B: Maybe we can do an episode, a guest episode up on the beach. That'd be pretty fun.
[00:38:06] Speaker A: And I have as many people, the people have been watching the show for three years. I've done quite a few of these from the deck at the beach house when we've had the nice weather down there. So I've had the real palm trees in the background instead of the old zoom virtual palm trees that everybody used to use. This is great to be able to do that. Well, in any case, everybody be sure to like the replays from today's show. Tell your friends about the True Data Ops podcast and don't forget to go to truedataops.org subscribe to the podcast so you don't miss any of season three with Keith. And I'm sure there'll be a few appearances from Guy in the next season as well.
So as we say here in Texas, adios. And via condios, this is Kent Graziano, the Data Warrior, signing off.
[00:38:54] Speaker C: Thanks everyone.
[00:38:55] Speaker B: Bye bye, everybody.
