Episode 14: The Power of Cloud Transformation

Intro: Welcome to InConfidence, the podcast for data ops leaders. In each episode, we ask thought leaders and futurists to break down the topics and trends concerning IT and data professionals today, and to give us their take on what the data landscape will look like tomorrow. Let’s join the data conversation.

Tina: Welcome to InConfidence, the podcast for data ops leaders. My name is Tina Tang, and I’m your host here today with Miles Ward, CTO of SADA. Now, Miles, you have a lot of achievements in your CV, but two of them that I really wanted to point out here, because it’s very relevant to our discussion: you built the AWS solutions architecture team, kind of big.

Miles: I was the fifth member and Rudy Valdez is really one who proposed it. And Paul Horvath was the first member together with Matt Tavis, but five of us sat together to go, “Okay, what do we call this thing?” And somebody proposed solutions architect, I forget whether it was Max Ramsey, or what but we all thought that sounded fantastic. So right after that I did work, kind of as the first representative for solutions architecture with Microsoft was responsible for them, and then started to help with the partner solutions architecture function together with Tom Stickle. So this isn’t like the first $50 million of AWS revenue in the first several years of the business now it’s a $60 billion run rate business. So there’s thousands of solutions architects today.

Tina: Amazing. That’s incredible. And then you also established the architecture practice at Google Cloud as well. 

Miles: Yeah, I met Eric Schmidt, as a part of the Obama campaign in 2012. And his ask was, you know, after I swore at him a bunch, because I didn’t recognize him and thought he was suggesting that we use App Engine for bad reasons, which was certainly not the solution to the problem that the Obama team had. And he asked me to come help. I read the Spanner white paper, and the rest was history. It was a match made in heaven between all of the engineering and innovation that was happening inside of Alphabet, and just the opportunity to take that out to market so yeah, was in the very beginning of that one too.

Tina: Phenomenal! At first I thought you meant you yelled at Obama, then I realized it was Eric Schmidt. But still that’s kind of…Seemly

Miles: Yeah. No, no, no yelling at Obama. He, he walks into the room, you have to stand up big and tall, like Dad’s watching. And so so I don’t think I would dress him down, did a good job. 

Tina: Right. And so was it natural to say Mr. President all the time, or did it just roll off the tongue?

Miles: No,well, he, you know, he hadn’t been reelected yet, right? So it was kind of, you didn’t want to jinx things. So it was just you know, just boss. It was probably you

Tina: Boss! That works! Yeah. Let’s get warmed up. Best binged episodic show?

Miles: Surprised to me. Out of nowhere. My wife was very excited about watching Game of Thrones. But we ended up sort of watching it like you’re watching Days of Our Lives, like little 20 minute slices of those 60 minute episodes with lots of, lots of clarification as to which of the long haired people is which and, but we’ve marched our way all the way through. We had a great time chewing that one up. You know, dragons. I’m on board. 

Tina: Dragons. Yeah. Anything with dragons, I’ll watch it. Literally. 

Miles:Yeah, sold. Sign me up. 

Tina: Yeah. Favorite cheat day indulgence? I know you have one. 

Miles: I would go… I would go Filet O Fish. That’s, that’s not, not a bad pick. I mean, that, that gets you way, way off the deep end at that point, but there’s some spots. I don’t know where I was at where they were showing that you could order a double Filet O Fish, which is just double trouble if you get right down to it. 

Tina: Just to clarify, we’re talking McDonald’s Filet O Fish? 

Miles: Yes, Yes, the original! Hamburglar be damned. You go straight, straight to Grimaces,Filet O Fish. It’s just too good. There’s no, there’s no filets and there’s no fish in there, right. That’s a, that’s an unholy combination. 

Tina: Okay, you totally caught me by surprise there. I wasn’t expecting that answer. 

Miles: No, delicious stuff. Childhood treat.

Tina: A childhood treat, right? Comfort food. And comfort you know, is, it’s all good these days. All good. So Miles, let’s, um, let’s talk about what you’re doing now. You know, working with your customers on some pretty ambitious projects around Google Cloud. Do you want to give us like some context here? What are we – what kind of scope and scale and you know, are we talking about? 

Miles: Sure. I mean, it applies right to what we were just talking about. I’ve got some 2300 customers under management. And every one of them that’s running on GCP takes advantage of Alphabet, not just Google or Google Cloud’s commitment to sustainability. So every customer that I close, that I help move their infrastructure into Google’s infrastructure system, they’re using what is far and away one of the most power efficient data center facilities anywhere in the world, Google consistently wins that race. They are also entirely green power at this point. They’re working now to get to continuous like in, in time, every single time that they’re running use of renewable resource power for all of the some 32 regions of clusters of data centers that they now operate. So, so we think that there’s, you know, it’s really important to get customers into that environment, environmental benefits are part of it, the efficiency of those businesses is critical. The, the the, their ability to access new customers and to grow their product and grow sophistication. And in the subject of this podcast, to be able to extract all this value that sits in their data is never easier than in Google’s environments. So we work across every different vertical, I’ve got people making movies to people, you know, curing diseases and healthcare companies, we got folks that are making games and folks that are working in the federal government, we have every range of scale of huge companies to little tiny startups, bootstrap startups that are just one or two folks. Each of them take different benefit from Google’s environments, but, but by working with that kind of breadth, we’ve been able to bring the lessons that you learn in one area into the other, right, every startup wants to be big and strong, like an enterprise, every enterprise wants to be fast and awesome, like a startup. So it’s been fun to be able to pull together this cohort of the innovators and, and help them go to what’s next. 

Tina: Well, so speaking of, you know, one wants what the other has, I mean, are, their challenges are different, though, you know. Can you, can you help us get a picture of what are some of the biggest challenges that these clients are experiencing? 

Miles: Sure. I mean, you can do real simple basic napkin math. My data center is old and broken, and to renew it as a capital expense in the millions of dollars. I don’t know some of the software that’s running in it. I don’t have anybody to project manage rationalizing this infrastructure, and reducing it to a system that can be deployed to cloud and managed in a radically lower level of operational risk and security risk and sort of financial operational risk. So we help people do that migration to turn off old broken data centers. Some companies have never been in a data center, they don’t know what you’re talking about, when you say something like that. They’re building new applications, they want to bolt on machine learning functions or automatic retargeting for customers, or they’re looking at better algorithms for engaging with different cohorts of their customers. So there, there’s all sorts of pre built tools in the Google Cloud environment that help with that. We start bolting those capabilities on. You have companies that, that they’re already in cloud, but have deployed have a legacy data warehousing system, right there, you know, a virtual machine running SQL commands in SQL Server someplace. Well, you know, it turns out BigQuery is, about four orders of magnitude faster for some of those kind of analytical queries, by helping them re-platform data into more efficient systems. We let them take care of that. And I mean, it’s, it is hard to summarize, because you’ve got so many different customers, that’s one of the great superpowers of these platforms is how facile they are. So even just writing down the use cases for public cloud, I sat together with the solutions architecture team I built on the Google side. And we gave up after an afternoon and a bunch of pizza and a list of 1700 different viable use cases. And we’re like, we should just we shouldn’t we could we had no problem writing more. I was like, “no one’s going to fill in all the architecture diagrams and best practices guides and reference reference systems for for these 1700s”. So well, let’s wait and do this again in a year and see if we get any further. So it’s a that’s, that’s its blessing, and it’s curse. It’s really good at all sorts of things, kind of like computers. 

Tina: Yeah, kind of like so. Um, are there- are there different kinds of services that you provide at different stages? And, you know, depending where the client is, could you give us an idea of what those are? 

Miles: Sure, really easy example, we work together. Great customer of ours. They’re a blockchain analytics for ad tech company called Mad Hive. Spectacular folks. They had absolutely rejected Google Cloud as inefficient too slow to be able to run the virtual machine automatic launching process that they were excited about, we introduced them to this new technology from Google called Kubernetes. And a thing that’s called GKE, and showed them that it was much faster for the problem that they had. So they’re like, oh, okay, well, we just wanted a system that was faster. That sounds great. We assessed the situation, right? Think of kind of an OODA loop, we built an orientation, we found a direction that would have a positive effect for them, we demonstrated that positive effect, and then helped them implement it so that they could actually take benefit from that. That is a loop. And so we ran it a bunch more times. After we help them with that problem, let’s get to chargeback and financial accounting so that each of your teams know how much they use. Once they are doing that, they’re wanting to do a lot of analytics. Well, you know, BigQuery is pretty great. So we’re helping them adopt that product, help them consolidate analytics, and reporting and visualization. Once they get through that they’re going to look, we’re gonna want to learn off this data. Can you teach us a little about TensorFlow? Sure, okay. In goes a machine learning operations team, maybe you don’t need to learn TensorFlow, you can just use AutoML and cheat, right? There’s all of the tricks in the bag from the Google operation system that we can continue to roll out as we help build credibility and get increasing value with customers. So there’s no one starting place. Almost everybody wants to have kind of a, assessment of the state of affairs. And we use the solutions architecture function that I, that I helped revise and ratify over the course of the decade with the public cloud providers to follow that method to get a real engineer who has done this a bunch of times in your market space in room and say, Okay, there’s a whiteboard, let’s beat it up for a couple hours so I can really understand what’s going on in your company. And that gives us the ability to make real concrete tractable recommendations. And what’s great at SATA, I actually have the professional services function. If you say you can’t go do the stuff I told you you just oughta then I can help you do it. I’m happy to come in and bring the technicians that have done that stuff before. So that we can help take you to what’s next. 

Tina:So it, it sounds like you are… you become part of their innovation teams. 

Miles: Sure, sure. There’s, there’s a lot of spots where you know, whether you’re following the kind of DORA methodology and Westrom generative culture kind of framework or, or that stuff all sounds like foreign languages to you, and you just want somebody to help you go faster, like. We’re doing a lot to help set up not just the technical innovations, but the cultural changes that have to happen to make it so that teams develop quickly. Easy example, like, Peter Mark, one of my team members that I worked with the folks at Spotify, and this is like a modern, you know, cloud native by and large, although at the time they were in data centers and AWS. And I thought, you know, quite an efficient development team. They were doing two production releases of their web facing and mobile app systems a day – two releases a day! If I go to an enterprise, they go, are you kidding me, we do two releases a quarter, maybe, maybe we do two releases a year. They’re doing two a day. We implemented the DORA system, which is documented in, in the book Accelerate, to describe just a more efficient, always continuously integrated, continuously deployed system, all of the trunk based development patterns, and the cultural shift to make it so that they’re doing blameless post mortems. And some of the stuff out of the Essary practice, they are now at 5000 Production launches a day. Because they’re microservice oriented, and they’ve decoupled their deployment pipelines. So they’re faster, everybody can go faster, right? So our job is to identify and to think through the real state of every one of our customers and help them take that sort of next productive leap forward. 

Tina: So you touched a bit about how some of your customers, you know, are generating and collecting vast amounts of data. Can you give us… What, what – So I’m assuming like some of these customers, you know, I heard the name, some of them are based in the US, but some of them are in other countries as well. Does the issue of data privacy, sovereignty, do these issues come up in any of your engagements? 

Miles: Absolutely. You know, I think it’s one of those spots where having a cloud provider and having the level of rigor and consistency in an API accessible system prevents a bunch of the problems that you can run into in these environments. Folks go I don’t know, cloud means my data doesn’t I don’t know where it is, and, and it’s hard for me to control it. I go, where are your USB keys? Do you have any idea where your data currently is? In the cloud, I can run a command and receive an exact list of exactly the locations that it’s in. And I have rigorous API based controls as to how it moves from place to place and a complete log of that which is un-manipulable by some bad actor or developer on your side, right? The, the controls and the guardrails that had been put in place by public cloud, in particular, by Google Cloud, really make it so people can be compliant with these rather direct rules, whether there’s GDPR stuff or pieces out of the MPAA, or stuff that’s being done as a part of FedRAMP, or other regulatory regimes. The, it, like anything that is powerful, you have to, you know, configure it in the right way. You can poke the wrong button. And in particular, you can give the permissions to your employees to poke the wrong button, maybe that’s the root of the problem, to break those kinds of compliance regimes. So it’s one of the real points of advantage where SATA will work together with customers is to help them see the best practices for the rights management and access control limitations, and all the structural stuff they can put in place to prevent themselves from causing self harm. It’s, it’s a really powerful way to automate a business. 

Tina: And also, I think that, you know, in this day and age where everyone’s end customer is so much more aware of digital rights, you know, the rights that they have, as owners of their own data. I feel like for a company, who is making the effort to do things, the right and responsible way that it becomes, you know, an important differentiator.

Miles: Well, it’s yeah, it’s, it’s either that they’re doing it the right way and that lets them be confident and articulate with their next customer who has the pointed questions. They can just produce the report and hand them the answers and move on to the next part of the deal, where their competitors may be struggling and playing with sock puppets and it’s generally kind of a mess. The other side of that is, it’s, it’s not like the future is less rigorous or less complex. So if you already find it difficult to administer this stuff, and keep track of it in a spreadsheet, and, you know, make sure that you sort of check in and check out the hard drive from the little cage enclosure, I’ve seen this stuff that all sorts of different companies do to do this. It’s just gonna get harder. So the work that we’re working on with companies now sets them up for an increasingly granular future where these controls will become more important over time. 

Tina: So, okay, we’ve already established the track record is very impressive. What would you, what would you attribute to your success, you know, and the company’s success, what’s the secret sauce here? 

Miles: Sure, SATA  has grown radically, over the last three years, where, I started it just over 100 employees, and now there’s nearly 700, or actually over 700 now. And the number of customers and the size of the customers that we’ve been able to really help is is growing rather radically, too. And there’s, there’s a couple of drivers to that. One, we have to have and we have to be incredibly aggressive self directed learners. There’s an unlimited amount of information and opportunities if you have, you know, the full library of possible solution components at your, at your ready. We’ve spent a lot of times with customers where, you know, half of the value add is, I just know the next thing they ought to read. And because I already read it and and some other customer that I’ve worked with prompted it because that was the critical, you know, last long pole in the tent for their innovation path. So there’s a lot of work where learning all the time, being ready for what’s next is important. The tech, you know, Hadoop, everybody’s heard of a Hadoop. Hadoop is literally the technology system that saved my startup. We did, we cut in a 100th our indexing costs versus doing it in SQL Server. It is now the product that I spend most time removing from customers because it’s so woefully inefficient. It’s silly that they run it ,read like that didn’t take long. It was only about 12 years. And you know, five years ago, we were building solutions for efficient hosting a Hadoop on Google Cloud to make sure people knew how to do that stuff. So you have to be on the front foot of learning the new building blocks learning the new technologies and you know helping people be aware of all that. Another, another bit that’s really, really critical is the service oriented customer first problem centered approach. There’s, there’s way too much stuff to fix. Like, everybody’s got problems, right? And I think far too often we come to a sales or a new customer engagement with the thing that I want to, I want us, you know, I have two of these, can you have to, you know, does anybody have a need for a hammer, because I’m looking for nails? The, the advantage of these big integrated platforms in the ecosystem of software that surrounds those platforms is, it’s not a single solution, right? It’s the whole tool shed with every conceivable is that you’d like so you can’t it’s so it’s silly. Like, if I just went into a customer to just tell them the names of the Google Cloud products, it would be a half an hour meeting, and I would run out of time. So instead, I can’t even start. I just got to ask them about their problems. Like what, what sucks? What’s in the way? What do you think is making things slow? When we get into a relationship, when we’re in years, two and three, it’s been fun. Like Sony Pictures, Imageworks, they’ve been with us for six years now, like, working hard together in pursuing problem solutions. And at that point, right, we start to be able to go, you may not have heard of this thing in this corner over here, you’re gonna need it here in about six months, let’s, let’s help you with it. But at the beginning, it’s all got to be, you know, this Socratic question asking, find, find, find what hurts and see if we can use the tools we have to, to solve that problem. That’s, that’s a fun part of the gig. 

Tina: I mean, it sounds like it really starts with that growth mindset. But then it’s also like you and your team, understanding what’s available to them,you know, as a resource, and like, you don’t have to start from scratch, you know, here are all these services that you can bring together. And you know, you’re already part way there, and then just applying them in different creative ways to help that customers business. 

Miles: Yeah, well, and it’s, it’s the, it’s the balance of, you know, every customer has a place where they’re the most sophisticated in the world, and every customer has a place where they’re dead last. 

Tina: Right, yeah, so true. Well said!

Miles: Right and so, right, like we ,we work hard to pay close attention to the smart innovators at our customers, sometimes they teach us stuff, right, we have to be working. I remember working with Crux. Crux is trying to build a queuing system to digest this unbelievable flow of input information that they scan across a zillion different upstream API’s to vendor that down downstream to their users, so that they don’t have to do all this integration headache. And we’re saying, like, you know, hey, you know, how do we orchestrate these kinds of collections? And, you know, I know, the program I’m most familiar with for doing this is, you know, Apache Airflow. There’s a solution and Google Cloud cloud called Cloud Composer. They cut me off in the middle of a sentence like, no, no, no, no, that’s five minutes scheduling, that’s terrible! There’s a brand new project called Prefect, you gotta check it out. I’m like, okay, have you heard of Astronomer you gotta look at Astronomer. Okay, look great. So, you know, at the same time they go, how do you? We’ve heard of this thing in BigQuery called slots. Could you tell us about slots? Like, yeah, you’re gonna need to really know about slots, but but happy to go study all, here’s the takeaway from the meeting: I’ll go read Prefect docs, you read, go read the slots docs, we’re gonna get back together tomorrow and we’ll be able to push each other forward. So that that kind of, you know, real collaboration appears, is what a lot of our customers are dying for, right? They want somebody to get into the trenches with them, to treat their moonshot like the moonshot that it is, right? I mean, it’s everybody’s trying to do something big, something aggressive, that changes the trajectory of the business. And there are few places where you can so consistently do that than in technology and data.

Tina: Okay, here’s one. Is there a commonly held belief amongst the, you know, the industry that you disagree with? Like, vehemently. Is there something that’s like commonly held as truth, you know, truth and it’s just not true?

Miles: Well, ah, I’ll, I’ll clarify, I’ll go, you know, maybe not true yet. You know, that’s one of the things that’s hard is,you know, for everybody that’s trying to push forward this date, a technology we’re all stuck in, in making predictions and trying to figure out when a given thing with land, right. I built a social media startup in, in 2007, which is the wrong time to do it because Twitter and Facebook haven’t even been founded yet so like, “Oops, you’ve done it wrong!”. There’s an easy, an easy belief is like, multi cloud is bad, multi cloud is systematically inefficient. You’re just vaporizing dollars, you have no idea how complicated that’s going to be. It’s not one plus one equals two is one plus one equals 18. The heck are you doing? So, that you know. Dearly beloved, that is absolutely true. If you are a brand new startup, please listen to me carefully. Don’t do that. You’re gonna harm yourself. It’s way more work than you want. But if I go hang out with George Lee, he’s the CIO at Goldman Sachs, and say, Hey, multicloud, he goes, Well, the, what do you mean? I go, right? Are you going to, you’re going to experiment with multicloud? He’s like, I have presence in all six of the cloud providers that we participate in, we have automatic orchestration of deployment and management across them. I have systematic financial controls. What do you mean, multi cloud is hard. Now, the reason he has the ability to do that is he’s managing trillions of dollars in assets. And it’s worth it, right? Rich companies, huge companies are doing stuff that most customers don’t do, that aren’t ready for those kinds of problems. I know that’s true, because so much of the technology that Google Cloud has brought out to its customers is because Google had to go fight with this problem way earlier than they had to. Everybody talks about orchestrating containers today, Google was doing that literally 12-13 years ago in the earlier versions of Omega. And that sets up the problem spaces of the giant companies become the problem spaces of little companies. Over time, all this stuff trickles downhill. So I think multicloud is going to be obvious and straightforward and trivial, just like you can use an AMD processor or an Intel processor, just like it doesn’t matter whether you have a Hitachi hard drive or a Seagate hard drive anymore. They’re all interoperable, and it all functions, that’s going to be true for the basic building blocks for the places where an API and a system has been ratified. You right now, for Google Cloud, if you want to use the s3 API from AWS, you can just write to GCS using the same API, it still works. So storage is maybe one of the front runners where this kind of compatibility kicks in early. But over time, things like Google’s Anthos, all of the work in Kubernetes, those are all ,at least in part, an exercise to make more and more of this a commodity and make that barrier of the positive negative the breakeven, the real ROI for multicloud turned into a positive thing for a larger and larger percentage of businesses. So it’s, it’s early days, right? We’re, we got decades to go, but soon. 

Tina: What about in data analytics? Is there any such seamlessness in that area? 

Miles: Sure, I mean, I think that you’ve got, you’ve got a whole bunch of spots where once, once developers have a tool chain, and it works, right, if you’re a data engineer, and you’ve gotten good at writing stuff in Spark, you’re gonna hold on to the Spark IDE and be building in a way you pry that out of your cold, nerdy, dead hands, right? The, I think there’s a lot where, in the same kind of patterns, the tools are getting better, right? I mean, I watched a bunch of our customers that we’re building in Spark, take a look at, at Dataflow at the Google product and the Apache open source project version of it called Beam. And it’s just, it’s less boilerplate, code gets pulled together faster, there’s less test to write, you have less structure to build, you know, you’re, you’re creating more useful, valuable output faster. And so, you know, if we tie it back, I think we’re far from done in the data science ecosystem. There’s, you know, there’s more startups that are building simpler tool packages and refining the experience for that cost of developers, almost than there are for the overall developer experience, right? How many new? You know, like, we just met great engineers at the folks at Datarobot, trying to help people build machine learning infrastructure more easily more straightforward that just reduces the barrier of entry makes it simpler and simpler to, for developers to have a big effect. 

Tina: Is there a mistake that customers are making when it comes to data protection, that you see? 

Miles: Sure, you know, I would say it is really easy to get, I think into the weeds in some of the smaller exploit cases, right? Like, I’ve got to do you know, I can’t use old encryption for my storage. I got to make sure I’m on like the most modern encryption cipher keys or, you know, I gotta, you know, it’s a supply chain attack that I’m really worried about.  Pro tip, here’s the thing. Your users are the vulnerability, like humans are the weak link, it doesn’t matter what you’re talking about, it is so much more straightforward for me to offer what in most cases, it turns out to be the equivalent of the cost of a candy bar to most of your employees and get their password and their second factor. If they have a second factor. They all have a second factor, right? Oh, boy. So like, so if you’re off noodling through logging, telemetry on accesses and trying to make sure you’re, you know, encrypted in rest, and transit and computation, which is a real thing, you can actually do that on Google Cloud. now. Assured workloads does encryption in computation, I can’t even believe I can say that sentence out loud. But folks focusing in on that layer of the problem where there are like, a couple 100 attackers in the world that can maybe take advantage of that, as opposed to your users credentials are fishable, which is 1000s, and 1000s, and 1000s and 1000s of attackers, who can take advantage of that. I think it’s really important to, you know, defend the endpoint, defend the the individual access layer and move up from there. 

Tina: Is there any like initiative or technology that, that you know, of that more companies should be taking advantage of? 

Miles: Well I mean like to tie into that, right? I mean, use something from the FIDO Alliance, something that’s a universal second factor, hardware keys are the correct answer, you do not want to be using SMS authentication. It’s a, you go to every blackout every year, and it takes them six minutes to take over your phone account and voila! Now I have admin credentials. So you know, I think shipping out Titan keys or Yubikeys or other FIDO compliant devices is a great first step. We also, that’s one of the reasons that SATA operates such a breadth of Google’s systems. It’s one thing for me to go like, get you on BigQuery and get you on homomorphic encryption, and your storage layer and all that. But I can also help you deploy Workspace, so that every one of your users’ emails has a second factor, right. It’s like the number one principle bit, Google is administering billions, billions of mailboxes. And when they have the second factor enabled, they do not get fished. It is just like a binary binary difference. So, really tryna help people be – 

Tina: I get so frustrated when people don’t have it. 

Miles: Right, you’re like, hold on a minute, what? You attacked to what? Like, that’s about okay. So it’s stuff like that, where it’s boring, right to do the basics, but you got to do it. 

Tina: Okay, let’s go to the next question, which is, what should people stop doing? 

Miles: Sure. Sure. You know, I mean, I think, I think there’s a, you know, an easy axiom that you just can’t let perfect be the enemy of the good. I think, especially in data, folks try to like, arrive on the grand vision of all possible use cases, and all possible datasets, and every conceivable downstream customer and all the different output modalities, like, stop it. Like go go find some specific stakeholder that needs a specific output and build what they need this afternoon, and document all the places where it’s sucked to build what they need. All the places you ran into friction, now that you’ve got a friction log, you start chewing those items, you work on one at a time, there’s no replacement for systematic grind on increasing ease of use. Yes, you’re gonna evaluate products. Yeah, you’re gonna bring in new tools, all that stuff. But there’s very, very few places where you need to make whole hog systematic end to end planning before you can take a productive step. 

Tina: That’s great. So Miles, any last bits of advice for audience? What’s the big takeaway? 

Miles: Sure. I mean, I think, you know, getting started today goes a long way. There’s nothing, there’s nothing out here that’s too big, or that there isn’t somebody that’s done way bigger. So, you know, use, use advisors and help to be able to accelerate your path to value. I think it’s, it’s really important to recognize, you know, you know, there’s, there’s only two days you can’t do anything, yesterday and tomorrow. So you got to do it today. And, you know, I’d encourage everybody, there’s, there’s great materials being produced both by Google and the broader, open source ecosystem that surrounds them. Some really useful new data podcasts and some some really good stuff that’s being launched on the Google blog. I know they just got done doing a data series we’re going to end up doing, you know a roadshow and a crash course on our data programs that’s coming soon. So there’s, there’s no shortage and stuff to learn. So, you know, take take a listen, find something that you found applicable and put it to work. 

Tina: Great advice. Miles Ward, thank you very much!

Miles: Tina, thank you! Great questions!  I thought it was super fun!

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