 this is Christian Buckley with another MVP buzz chat and I'm talking today with Andy. Hello. Hello, Christian. How are you? Brand new MVP. Data platform, correct? Brand new out of the box. I've still got the shrink wrap on. That's right. I'm still so new. I don't have my award kit yet. It's that new plastic smell that you have with you. It's like a fresh car smell. That's right. The new leather seats. That's what I was going for. Yeah. Yeah. You open the door and you've got that hit of newness about it. Well, I will. I will expect the unveiling video, which is a tradition of the unboxing of the kit. Yes. It's a very, it's a very YouTube thing, isn't it now? It is kind of the unboxing of something. So I'm going to record it and then I'll see whether I actually get as far as posting it online. The other thing is you just have to remember is that with renewals every year, you have to be humbled and honored. I think honored and humbled and honored. Anyway, there's like the same words that everybody uses. So yeah, as, as always, of course, as always. So what are you? Folks, I don't know who you are. Why don't you give us the background, who you are, where you are, what you do? Well, so, you know, my name is Andy Cutler. So the kind of short version is that I really only in the last couple of years started to become involved in the data community. Because initially, you know, I moved on from my permanent, permanent role and I set myself up independently. I was, you know, at the time, beginning of, beginning of last year, completing a master's. So my plan at the end of 2019 was to leave my permanent role, which I enjoyed, finish a master's that I'd started, which was in business intelligence and data mining, and then set myself up independently, you know, as a, as a contractor and a consultant. So I started to then become more involved in blogging and speaking. I'll talk a little bit about, you know, a lot more about that in a bit. But I specialized really in the Azure data platform and Power BI. You know, my history really was databases. So I remember, and I know that there's going to be a lot of people that think that SQL Server 2000 is, you know, a pretty new, you know, product from, from their experience. But I remember I worked for a web design company, and this is 20 years ago. This is, you know, just after the millennium and we've got SQL Server 2000. And I was tasked with writing the SQL to create this content management system. And then from there on in, you know, I went to another job and another job where I was given the opportunity to look after the data warehouse. And I'd never touched a data warehouse. I didn't know what a data warehouse was. And this is probably around 2004, 2005. That's my background as well. That's where I kind of started in tech was in that world. The data warehouse in due to March. And I, there was a consultant that I'm still in touch with, touch with now who was a micro strategy consultant. Because that's, that's what the business intelligence tool was. I deployed that business objects, micro strategy, DSS agent. Yes, yes. All that, that world. Yep. But the IT director at the time who was new had tasked me with shadowing this consultant to understand the data warehouse. You know, and, you know, bearing in mind, I just spent the last sort of two or three years learning, you know, third normal form, normalization, database best practices, and then all of a sudden, you know, I'm still in sort of my early 20s, I'm told to flatten everything, denormalize everything, you know, and I'm like, whoa. And that, honestly, that, that sort of began my love affair with everything data warehousing. So the Kimbell books, all of a sudden, you know, I'm reading, you know, the ETL toolkit and the data warehouse toolkit. So for years and years and years, you know, I'm, I'm working with SQL server, you know, 2000, I remember going to Microsoft campus over at Reading in the UK to look at the unveiling of integration services, which was, you know, coming from DTS was amazing, this workflow. And from there on in, you know, up to 2008, 2008 R2, 2012, and finally into Azure around 2016. So I've worked predominantly with Azure for the last few years, but still with SQL server as well on, you know, data warehousing projects. So I sort of very much consider myself, you know, a data warehouse person, you know, if it's going to be my big go to thing, it's going to be data warehousing. You know, in a lot of the early 2010s as well, just like back before we had Ignite, it was the TechEd event and the various TechEds. And I went to some of the global TechEds in Germany and down in Australia, New Zealand, some of the regional TechEds. But we started to see, it's always interesting to look at the vendors that show up at these conferences. And if you attend enough of these events, which, you know, guilty, that you start to see the waves of the changes. And what was starting to happen in 2010 to 2014 is you started to see like the big data vendors and the analytics firms and a lot of that, that concentration, which was new, a relatively new thing to the Microsoft ecosystem to start to see some of these players move in. And so it's great to see the expansion of the MVP program and not just around the products, but have concentrations like, well, like the data platform. But you start to see people that have a more varied background come into the space. And, you know, and so I'm like, look at Azure is not my space, it's, you know, not area there. My, my time, I left the data warehousing world at the end of the 90s. You know, so but it was for that decade was that was my world. Yeah, you know, but I knew enough, you know, to cause some damage, but to also to be aware of some of this, this shift that's happening with a lot of organizations, it's that, you know, every data issue is a big data problem. You know, we have massive amounts of data. I'm in the collaboration space. You think of how much structured and unstructured data just out of the collaboration segment of an enterprise is much less the transactional systems, your ERP and CRM and other intelligent data that's coming from depending on the industry and the machines, you know, the, the, you know, anyway, massive amounts of data that are out there. It just points back to the relevance and the growing need for people that once again, focused in this area of the business. Yeah. And also, I mean, interesting you said about the size as well, because, you know, big struggle to get the context from even the smallest data sets, you know, so, you know, we've got the technology now we can choose and I have this discussion on Twitter quite a lot about different vendors. You know, interesting you were saying about, you know, vendors in the space, you know, yes, we have Microsoft, we've got AWS, Google, Snowflake, Databricks. Back in 2012, 2013, I was using a lot of Redshift, AWS Redshift. Because, yeah, you know, Azure was still growing. It wasn't something that was, you know, you were looking at yet. You know, AWS was still, you know, still, you know, that, that big, that big player. Obviously, Azure was, you know, gathered, you know, gathered, gathered, gathered pace. But I think about, you know, if you look at the data platform side of things, okay, so, you know, recent announcement at Ignite was SQL server 2022, which is going to have, you know, it's an on-premises product, right? You know, we can say on-premises in terms of our data center or our infrastructure in Azure, if we're deploying onto VMs, that's going to have a lot of integration with cloud services. Yeah, so you're going to have, you know, a bit of convergence there. I'm really looking forward to see how that pans out, really, in terms of collaboration. But yeah, yeah, it's interesting points. Yeah, there's a lot going on too. So two years ago, where I started hearing about the, like, the open data initiatives and sharing information with, you know, Adobe and SAP and kind of the other platforms. And I haven't been paying attention to, like, what's been happening in that space. But again, it's this idea that, you know, there's no, I say this a lot, but there's, you know, we are far removed from the day, from the era where you would run into companies that be like, hey, we're just a Microsoft stack. We only have Microsoft technology. No, they're, they've got foot in, you know, AWS here, they might be using Oracle for this solution. We might be doing for productivity and all these things on over in the Microsoft stack. But we're then going and creating as part of our OSS where we want, we have to have integrations in between each of these different systems. Yes. Yes. So where they can play together, where they can talk to each other, where we can then build kind of decision support systems that look into each of these, like, you know, we need that capability. It's there's just so much opportunity in that space, you know, for a lot of the partners that, you know, we talked to that we work with, there, it's all about multi cloud that vendors can't get there fast enough to be able to support, you know, cross cloud, you know, capabilities. And it's the evolution of products as well. So, you know, especially in the data space is you've got this sort of, you know, vendor, new feature, other vendor, new feature, other vendor, new feature, you've got this sort of, you know, constant progression, which it is a bit of it, it's a bit of it's a tricky question and a tricky thing to address because when you talk about a data strategy or a data architecture, right, this is something that you would expect to be in place for a certain amount of time because it's a consideration, especially when you've got a lot of data, right. So with code, code can be transported. Data, there's a lot more of a consideration there about where you're putting it, the format that you're putting in. And of course, with some of the more open source formats that are being used now, a lot more people are finding it a little bit more comfortable that the data can be separated from the engine from the computer. So we can get data, scale out, you know, scale out our data infrastructure, but not tie ourselves into some, you know, a particular product, a particular service, because they're all vying for, you know, vying for attention. But of course, you know, new features that are coming, you know, fast and heavy from different vendors, if you're not, you know, if you're with, you know, a vendor for any specific amount of time, you're always going to be looking to see what's happening, you know, elsewhere, putting maybe a bit of pressure on that product team of the vendor that you're with to bring these features in. So everyone's busy. Everyone's constantly busy evaluating or answering or evolving. Yep. Yeah. So my, most of my career, though, like I say, the second half of my career has been with your product, product teams, product companies. Yeah. And one of the discussions, I mean, back, back when I was constantly reviewing exactly what you're talking about, reviewing vendors constantly, then battling with their development schedule, their feature schedule, because, you know, what inevitably happens, you know, the executives in your company make decisions based on what's there today and the promises for when they're going to deliver those other features. And it's like, you know, you can't, that's like the secret to that. I learned that I was a technical project manager. And I learned that it's like, I never make a purchasing decision today based on promises for tomorrow. If you, you make it based on what is there today and how far we're going. Right. But the other, the complaint was, well, you were so locked into that system. And so our preference was always for those solutions that had those integrations or made it easy to export out or, you know, connect with or export out to get back away from that solution. I know a lot of the fear with product companies is that, well, if we make it easy for people to leave us, then they'll just leave. They can raise more features. It's like, well, you know, you can't think that way. You have to think in terms of what's the best thing for the customer. And to have that, that's why you have, you know, data portability. You're that that concept of it's my core data. I'm utilizing your platform, your system, your set of features, but it's my data. So don't lock me in. Let me move that. And I'm more likely then to work with the platform that might not be as feature rich, you know, but has that portability has that accessibility that integration about it as well. Correct. Yeah. And but anyway, it's I mean, that that's just one factor in a decision making around that, but just something that give a bit away from that world for a long time. I don't know how much of that is an issue any of these days. Well, when you talk about portability, if we if we look at specifically data and the engine that's kind of computing over that data. So at the moment in Azure, if you've got a bunch of data, let's say sat in your data lake, you've got options, you can run Synapse Analytics, you can run Databricks, you can run Databricks SQL snowflakes available. Yeah, you've got these options from these different vendors that Microsoft have said, Hey, yeah, you know what, run your engines in Azure. So that there has been that kind of separation of data and people, you know, I've spoken to people where they've been running testing over different engines and they've been able to do that because they're working off the same data, literally the same data set and the compute is separated. So they have that choice there. They're able to do that and, you know, start to drill into some of their specific use cases about which software is going to work for them. So it, you know, there is certainly a little bit more freeness in terms of how people can evaluate the products now that we've got that kind of separation. There's a, I mean, I know that Microsoft was moving this direction prior to Satya becoming CEO, but I give a lot of credit to Satya when he, one of his first keynotes, I think it was the partner conference. So before it got rebranded as, as Inspire, but one of his first keynotes, and he talked about, you know, very much paraphrasing here, but said, you know, our goal is to create the best products and services that, you know, out there and available. But where we don't have a solution or we don't have the best solution, we need to think in terms of the end to end customer needs. And we might be the best here, the best here, we might be second or third here and not have a solution here. We have to integrate with the competitors and partners that can provide that the rest of that end to end need of our customers. There's no excuse for providing because of, you know, what we do a crappy, you know, end user or customer experience, they need to get their work done. It hurts us even having the best solutions in these areas, it hurts us by them not supporting that end to end perspective. And again, giving the customer choice, right? Giving them choice and also remembering that we're just one player in the mix. There's like, I go back to what I said earlier, it's like, there is no one who says 100% of what we do is within the Microsoft stack. There are competitors, there are other solutions all along the way. And so, you know, anybody, and again, I work for an ISV, we think the same way, like our customers have this business to get done, we might do this piece of it. We want to make sure that what we provide is the best in this category and that we help, you know, we integrate with, we provide the assist to the rest of that so that they have a good end to end experience. Yeah. And that's the, I mean, that's just like, you know, end user focused development, you think that way, the scenario based development where you're thinking of that, you know, the full scenario there and the solutions there, but that's, that's something that we need to think about too, with what I talk about data portability, which I know means something specific, but you know, I'm thinking generically about your portability and usage of that data, the ownership of that data, and respecting that. But it's anyway, it's an interesting space. I know that we just got a couple more minutes here, but you know, for what was your path to becoming an MVP kind of, you know, how did you, you know, find a way, did you know other MVPs or was there specific things that you did to become an MVP? So this was going back to, you know, the last couple of years, which was it, you know, it basically, it's, it's, it's, it seems like an all in all my, all my cards were on the table because, you know, I'd left my permanent job, wanted to finish my masters, wanted to set up myself independently. My initial end game, my goal was wanting to set myself up as, you know, a Microsoft partner. So I'm a silver partner because there's just me. So I, you know, I can, you know, I contract, I consult dependent on, you know, the project. And what I wanted to do is kind of build up that body of knowledge in blogging in my blog. Okay. Because if I'm documenting something, if I'm going through a technical process, I'm going to blog about it. So I started to, started to do that. And initially it was all around Power BI and Synapse Analytics. Now Power BI, you know, it's a massive product. There's lots of different areas to it. Lots of really, really clever people all involved in different bits. And I kind of sit more on the kind of modeling bit that connects to the data sources. Yeah. So I'm not very good at visualizations. I'm not very good at DAX, but I never, you know, I'm very honest about that. So I worked a lot and I started to blog and talk a lot on interacting Power BI with Synapse Analytics. And then from Synapse, I started to talk and blog a lot about serverless SQL. So the engine can query external data. I then started to spin off a separate blog that was dedicated just to serverless SQL pools or specific to serverless SQL pools that just grew. So I put a series together about logical data warehousing with serverless. That was really, really popular. And I've kind of spoken about it for the last year. And it got on the radar and people started to ask me questions and tweet and email and say, oh, I've just started to look at the service. Can you provide some pointers? And then, you know, I've been sort of collaborating a little bit with another MVP who then contacted me and just said, hey, do you want me to nominate you? And I was a bit, I was, you know, it was that just to be thought of as nominated, I thought, yes, not yet, you know, not yet. So we kind of went on that journey and then, you know, still presenting sessions, events, still talking and working on Synapse Analytics and especially the serverless space. Because when you talk about sort of the passion for products, one of the things that I always try and get, you know, sort of front and center with something like serverless SQL pools is the fact that you can just bring in SQL skills. Very, very easy to get started, get set up. It's going to provide value in your BI stack. Right. And if, yes, if you want to use Databricks for something else, fine. Your data is there. You can connect to it from these different computes. Serverless is going to fit in there as well. So that was really that kind of journey is, you know, I started to build up that body of knowledge, that was then blogging, speaking. And yeah, I started to sort of get known a little bit on Twitter for going on about serverless SQL pools. A couple takeaways. I mean, that's a great point to not, to focus on the things that you're passionate about and that you're specifically working on. Like you don't need to be an expert on every possible topic within that category. Because we all, we can't, you know, and we're focused in certain areas. But the other side of that, I mean, I like that of kind of, and I've talked to quite a few MVPs that did the same thing as kind of say, hey, not just yet, let me build up the body of content. Because that's actually something as part of the review process. They look at like your last year, your body of work. And if they don't feel like there's enough of, you know, the contributions to the, to the, to the community there, you actually then don't get, you can't be considered again for many, many months, it actually could take time. And so it's, it's a wise thing to do to go and look at, okay, do I feel like my body of community contributions over the last year is on par with what I see from other MVPs enough to be considered for that? That's just something you should take into consideration. It is. I think, you know, it's, I don't think people should be caught up too much with what someone else is doing. The Joneses. That's right. Yeah. There were a lot of, there were a lot of MVPs who do something every day. In life, that is a good recommendation. Don't worry about what other people are doing. You just gotta, you gotta, gotta keep doing what you believe in and what you're doing. You know, you know, to get there. But yeah, I mean, like, you know, like I said, it's been a, it's been a fantastic journey so far. And I just really want it to continue to be honest. Well, that's awesome. Andy, really appreciate your time. I know over, I got to run, but folks that want to find a, get in contact with you, what's the best ways to reach you? So Twitter. So Mr. Andy Cutler on Twitter. But my, my, yeah, my, well, Andy Cutler was taken unfortunately. There you go. But my blog is not your father's Twitter handle then. Yes. That would be, that would be, yeah, that would be, yeah. Well, actually I should be master Andy Cutler. But yeah, it's, yeah, Mr, you know, M-R-A-N-D-Y-C-U-T-L-E-R. And my main blog for all things serverless is serverlesssequel.com. Well, Andy, well, great to get to know you. Hopefully one of these days we'll get back together for the MVP summits and I'll see you at another event. Here's hoping. Yeah. All right. Well, thanks a lot for your time today. Thank you very much, Christine. You have a good day.