>> From Seattle Washington, it's theCUBE, covering AWS Imagine, nonprofit. Brought to you by Amazon Web Services. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're actually on the waterfront in Seattle at the AWS Imagine nonprofit event. We were here a couple weeks ago for the AWS Imagine education event. This is really about nonprofits and solving big, big problems. So Dave Levy and team have you know dedicated to some of these big problems. And one of the big problems in the world is human trafficking, and problems that people are encountering and all kinds of nasty situations all over the world. And we're really excited to have someone who's tackling that problem, and really trying to bring a voice to those people that wouldn't otherwise have a voice. And she's Hend Alhinnawai, she's the CEO of Humanitarian Tracker. Hend, good to see you. >> Thank you Jeff, good to be here. >> Absolutely. So before we jump into it, impressions on this event? >> Wonderful event bringing together technologists, people in nonprofits, really creating synergies for people to collaborate and talk to each other and network and learn how they can advance their organizations. >> Such important work. >> Yes. >> So give us kind of the background on what you're up to, what Humanitarian Tracker's all about. >> So Humanitarian Tracker's a nonprofit forum. It was created to connect and empower citizens using innovation and technology, but specifically for humanitarian events. We were among the first to combine crowdsourced reports with data mining and artificial intelligence and apply them to humanitarian disasters, conflicts, human rights violations, disease outbreak. All the way to tracking the UN's Sustainable Development Goals. Really giving a holistic view of what's happening. >> It's interesting, you know, it's probably like the middle eastern spring, I can't remember the exact term that people use, where it was kind of the first use of regular people using their mobile phones to kind of grab a ground swell of action. You're not looking at the politics specifically, you're looking more at humanitarian disasters. But pretty amazing kind of what a connected phone represents to anyone anywhere in the world now to communicate what's happening to them. To share that story. We really didn't have anything like that before. To get that personal event on the ground. >> No it's really a new way of consuming, creating and consuming information. So the cell phone has really given people on the ground a chance to tell their own story. But it's not enough. If you have an event that happens to you. Something happens to you. And you record it, it stops there. But the unique thing with Humanitarian Tracker is it gives people that forum to show the world and tell them what's happening to and around them. >> Right, but it's not just about the individual. And what you guys are doing is using cutting edge technology, obviously you're here as part of the AWS event. In terms of machine-learning and big data to grab a large number of these reported events and distill it into more of an overarching view of what is actually happening on the ground. How did you do that, where did you get that vision, how are you executing that? >> Well, we're all about empowering the citizen. And in our line of work we deal with a lot of data, a lot of information, most of it is unstructured, most of it is crowdsourced. So we use machine-learning to help us extract important details. Information on time. Event location, what is happening. And at the same time we really cared that this reporter, stays anonymous for their own safety. We, privacy and security is utmost importance to us. So that's always our focus. So in that space, we de-identify them. We take out any information that could be identifiable, that could lead to their arrest, or could lead to someone identifying that it was them that reported. >> And how do you get this information to the people that are suffering this activity ground? How do they know about you, how do they know that you are anonymizing their information so there's not going to be repercussions if they report. You know, how do, kind of I guess your go-to-market, to steal a business terms, in making sure that people know this tool's available for help? >> It depends on the situation. For example in the conflict situation, we rolled it out, and we kept it low key for awhile. Because we didn't want government attacks, we didn't want people to be arrested, or to be tried. So we rolled it out. And it was word of mouth that spreads. And people started submitting supports. Actually the first project we did with conflict, we weren't sure if we were going to get one report, zero reports. The first week we got nothing. And then slowly as people learned about it they started submitting their reports. And we see our job as really elevating the otherwise marginalized voice. So you submit a report to us, we then take it. We verify it. We make it public. And that, we welcome, we encourage, we want people to consume it. Whether you're a student, whether you're a journalist, whether you're a government, whether you work in a nonprofit, the UN. It's been used to address human rights violations, it's been used to identify humanitarian hotspots. The data's phenomenal, and what you get from it. It's not just collecting data. We're not just about collecting the data. We want to make sure it's meaningful, and we want to derive insights. So we want to know what is the data actually telling us? >> Right, right. So just to be clear for people that don't know, so you're making that data available, you're cleansing the data, you're running some AI on it to try to get a bigger picture, and anyone with a login, any kind of journalist can now access that data in support of whatever issue or topic or story they're chasing? >> That's it Jeff. >> That's phenomenal. And just kind of size and scope. You've been at this I think you said since 2011. You know kind of how many active, activities, crisis, I don't know, what the definition is of a bucket of these problems. Are you tracking historically at a given point in time? Give us some kind of basic sizing type of dimensions. >> It really ranges, because it could, when we were tracking conflict for example, we were really focused on one area, and the surrounding countries. Because you had refugee population, you had displacement, you had all sorts of issues. But it could be anywhere from five projects, it just depends. And we want to make sure that each project we're taking on we're giving it our full attention, full scope. And I like to run the organization like a two-team pizza team. And so I don't take on more than I could handle. >> Right, right. So then how did it morph from the conflict to the Global Sustainability Goal? So we've worked with Western Digital, they're doing a lot of work, ASP's doing a lot of work on kind of these global sustainability goals. How did you get involved in that, and how did the two kind of dovetail together? >> So the elasticity of the cloud has helped our operation scale tremendously. And in 2016 we were selected as a top 10 global innovation, that could be applied to the Sustainable Development Goals, and-- >> So they found you, the UN find you, or did you get nominated? How did that happen? >> We were nominated, and from over 1,000 solutions we were chosen. >> Congratulations. >> Thank you. And we were showcased at the Solutions Summit which is hosted at the United Nations. And just based on that experience of meeting people that were doing really cool things in their respective communities, we launched the Global Action Mosaic. Because we wanted to create one place where people that are doing projects in their communities could submit it, and have it showcased. And the goals are not only to crowdsource the SGD's, but to also be a part of the effort to track what's happening. Who's doing what where, make it easy for people to search say, Jeff you decided to get involved in a project with education. You can go onto our Global Action Mosaic, search projects on education in your community or in other parts of the world and then get involved in it. So it's really creating a centralized place where people can get information on the global goals. >> Awesome. So that's pretty much the Global Action Mosaic. It's pretty much focused on the UN global goals versus your core efforts around the Humanitarian Tracker. >> Yes. >> That's great. So we're here at AWS. Have you always been on AWS? Is this something new? How does being on kind of the AWS infrastructure help you do your mission better? >> We are, we've been partners in running AWS since we actually started. >> Since the beginning. >> Yes we have Yusheheedi as one of our partners, development partners, AWS. And because one of the core, one of the most important things to us is privacy and security, we want to make sure that whatever data is being handled and received is stored securely. >> Right, right. >> And that information transmitted, handled is also being done so in a secure way. Like I mentioned, the elasticity of the cloud has helped us scale our mission tremendously. It's affordable, we've been able to us it, we've learned their machine-learning stock to de-identify some of the data that comes in. So we're firm believers that AWS is essential to how we run our operation. >> Because do the individual conflicts kind of grow and shrink over time? Do you see it's really a collection of kind of firing up hotspots and then turning down versus one long, sustained, relatively flat, from kind of a utilization and capacity point of view? >> Yeah, no it definitely, it flares up and you'll have like a year, months, weeks sometimes where it's just focused on one area. But one of the things we focus on, it's not just. So what is the data actually telling us? So say you're focusing on point A. But just down the street in location B there is a dire humanitarian emergency that needs to be addressed. The crowdsourced reports, combined with the data mining and the AI, helps us identify those hotspots. So everybody could be focused here, but there could be an emergency down the street that needs to be addressed as well. It just depends. >> And do you have your own data scientists or do you, do other people take your data and run it through their own processes to try to find some of these insights? >> We have both. >> You have both. >> Yeah. >> So what's been the biggest surprise when you anonymize and aggregate the data around some of these hotspots? Is there a particular pattern that you see over and over? Is there some insight, that now that you've seen so much of it, from kind of the (muffled speaking) that you can share and reflect on? >> I think it' very unique to each project to do. But there is one thing that I strongly support, that I don't see enough of, and that's the sharing of data within the organizations. And so, for example just getting to that culture where sharing your data between organizations is encouraged and actually done. Could help create a, create a pool of knowledge. So, for example we worked with 13 different organizations that were all tackling humanitarian events. The same one, in Syria. And the 13 did not share data and did not talk to each other. And so we found that for example, they were all focused on one area. When just a few miles down, there was a need that wasn't being addressed. But because they don't share information, they had no idea. >> Right. >> It was only when we were able to take a look at it, kind of from the, from an overarching view, looking all their data, we were able to say you know, it would be helpful, it would actually, you could save on resources, and less time, and less effort, and you guys are tackling a small funding pool to begin with. If you shared information and tackled different things, instead of focusing on one area, because you don't know what the other guys doing. >> And were they using crowdsource data, is there source data, or were they just trying to collect their own from the field? >> They were collecting their own. >> So I assume that the depth, and the richness, and the broadness of data is nothing like you're collecting. >> Well you get a different kind of, you get different kind of information when the individuals actually telling you what's happening versus you asking a very direct question like, "Are you healthy? Yes or No?". Whereas you give them the chance, they might tell you that they haven't eaten, and their diabetic and you know, give you other pieces of information. Where they're living, are they refugees? Are they healthy? Are they not healthy? Do they go to school? Do their kids go to school? How many kids they have? Are they a female-run household? All this information could help guide development in the proper way. >> Right, right. All right. So give you the final word, how should people get involved if they want to help? >> You can go to humanitariantracker.org if you want to volunteer with us. And if you're doing a project that is related to the UN's Sustainable Development Goals, I would like you to go to globalactionmosaic.org, and map it there, and be part of our community. >> So Hend, thank you for taking a few minutes to share your story, and for all the good work that you're doing out there. >> Thank you Jeff it was a pleasure. >> All right, she's Hend, I'm Jeff, you're watching theCUBE, we're at AWS Imagine nonprofit. Thanks for watching we'll see you next time. (techno music)

>>Welcome back here on the Cube. I'm John Walls. We are in Las Vegas at the Venetian, and this is Reinvent 22 in the Executive Summit sponsored by Accenture. Glad to have you with us here as we continue our conversations. I'm joined by Paul Puckett, who's the former director of the Enterprise Cloud Management Services at the US Army. Paul, good to see you sir. Hey, you as well, John. Thank you. And Justin, she who is managing director and cloud go to market lead at Accenture Federal Services. Justin, good morning to you. Good morning, John. Yeah, glad to have you both here on the cube. First time too, I believe, right? Yes sir. Well, welcome. I wish we had some kind of baptism or indoctrination, but I'll see what I can come up with in the next 10 minutes for you. Let's talk about the Army, Paul. So enterprise cloud management, US Army. You know, I can't imagine the scale we're talking about here. I can't imagine the solutions we're talking about. I can't imagine the users we're talking about. Just for our folks at home, paint the picture a little bit of what kind of landscape it is that you have to cover with that kind of title. >>Sure. The United States Army, about 1.4 million people. Obviously a global organization responsible for protecting and defending the United States as part of our sister services in the Department of Defense. And scale often comes up a lot, right? And we talk about any capability to your solution for the United States Army scale is the, the number one thing, but oftentimes people overlook quality first. And actually when you think of the partnership between the Army and Accenture Federal, we thought a lot when it came to establishing the enterprise Cloud management agency that we wanted to deliver quality first when it came to adopting cloud computing and then scale that quality and not so much be afraid of the, the scale of the army and the size that forces us to make bad decisions. Cuz we wanted to make sure that we proved that there was opportunity and value in the cloud first, and then we wanted to truly scale that. And so no doubt, an immense challenge. The organization's been around for now three years, but I think that we've established irreversible momentum when it comes to modernization, leveraging cloud computing >>For the army. So let's back up. You kind of threw it in there, the ecma. So this agency was, was your a collaboration, right? To create from the ground up and it's in three years in existence. So let's just talk about that. What went into that thinking? What went into the planning and then how did you actually get it up and run into the extent that it is today? >>Sure. Well, it was once the enterprise cloud management office. It was a directorate within the, the CIO G six of the United States Army. So at the headquarters, the army, the chief information Officer, and the G six, which is essentially the military arm for all IT capability were once a joint's organization and the ECMO was created to catalyze the adoption of cloud computing. The army had actually been on a, a cloud adoption journey for many years, but there wasn't a lot of value that was actually derived. And so they created the ecma, well, the ECMO at the time brought me in as the director. And so we were responsible for establishing the new strategy for the adoption of cloud. One of the components of that strategy was essentially we needed an opportunity to be able to buy cloud services at scale. And this was part of our buy secure and build model that we had in place. And so part of the buy piece, we put an acquisition strategy together around how we wanted to buy cloud at scale. We called it the cloud account management optimization. OTA >>Just rolls right off the >>Tongue, it just rolls right off the tongue. And for those that love acronyms, camo, >>Which I liked it when I was say cama, I loved that. That was, that was, >>You always have to have like a tundra, a little >>Piece of that. Very good. It was good. >>But at the time it was novetta, no, Nevada's been bought up by afs, but Novea won that agreement. And so we've had this partnership in place now for just about a year and a half for buying cloud computing net scale. >>So let's talk about, about what you deal with on, on the federal services side here, Justin, in terms of the army. So obviously governance, a major issue, compliance, a major issue, security, you know, paramount importance and all that STEM leads up to quality that Paul was talking about. So when you were looking at this and keeping all those factors in, in your mind, right? I mean, how many, like, oh my God, what kind of days did you have? Oh, well, because this was a handful. >>Well, it was, but you could see when we were responding to the acquisition that it was really, you know, forward thinking and forward leaning in terms of how they thought about cloud acquisition and cloud governance and cloud management. And it's really kind of a sleepy area like cloud account acquisition. Everyone's like, oh, it's easy to get in the cloud, you know, run your credit card on Amazon and you're in, in 30 seconds or less. That's really not the case inside the federal government, whether it's the army, the Air Force or whoever, right? Those, those are, they're real challenges in procuring and acquiring cloud. And so it was clear from, you know, Paul's office that they understood those challenges and we were excited to really meet them with them. >>And, and how, I guess from an institutional perspective, before this was right, I I assume very protective, very tight cloistered, right? You, you, in terms of being open to or, or a more open environment, there might have been some pushback was they're not. Right? So dealing with that, what did you find that to be the case? Well, so >>There's kind of a few pieces to unpacking that. There's a lot of fear in trepidation around something you don't understand, right? And so part of it is the teaching and training and the, and the capability and the opportunity in the cloud and the ability to be exceptionally secure when it comes to no doubt, the sensitivity of the information of the Department of Defense, but also from an action acquisition strategy perspective, more from a financial perspective, the DOD is accustomed to buying hardware. We make these big bets of these big things to, to live in today's centers. And so when we talk about consuming cloud as a utility, there's a lot of fear there as well, because they don't really understand how to kind of pay for something by the drink, if you will, because it incentivizes them to be more efficient with their utilization of resources. >>But when you look at the budgeting process of the d od, there really is not that much of incentive for efficiency. The p PPE process, the planning program, budgeting, execution, they care about execution, which is spending money and you can spend a lot of money in the cloud, right? But how are you actually utilizing that? And so what we wanted to do is create that feedback loop and so the utilization is actually fed into our financial systems that help us then estimate into the future. And that's the capability that we partnered with AFS on is establishing the closing of that feedback loop. So now we can actually optimize our utilization of the cloud. And that's actually driving better incentives in the PPE >>Process. You know, when you think about these keywords here, modernized, digitized, data driven, so on, so forth, I, I don't think a lot of people might connect that to the US government in general just because of, you know, it's a large intentionally slow moving bureaucratic machine, right? Is that fair to characterize it that way? It >>Is, but not in this case. Right? So what we done, >>You you totally juxtapose that. Yeah. >>Yeah. So what we've done is we've really enabled data driven decision making as it relates to cloud accounts and cloud governance. And so we have a, a tool called Cloud Tracker. We deployed for the army at a number of different classifications, and you get a full 360 view of all of your cloud utilization and cloud spend, you know, really up to date within 24 hours of it occurring, right? And there a lot of folks, you know, they didn't never went into the console, they never looked at what they were spending in cloud previously. And so now you just go to a simple web portal and see the entire entirety of the army cloud spend right there at your fingertips. So that really enables like better decision making in terms of like purchasing savings plans and reserved instances and other sorts of AWS specific tools to help you save money. >>So Paul, tell me about Cloud Tracker then. Yeah, I mean from the client side then, can you just say this dashboard lays it out for you right? In great detail about what kind of usage, what kind of efficiencies I assume Yeah. What's working, what's not? >>Absolutely. Well, and, and I think a few things to unpack that's really important here is listen, any cloud service provider has a concept. You can see what you're actually spending. But when it comes to money in the United States government, there are different colors of money. There's regulations when it comes to how money is identified for different capabilities or incentives. And you've gotta be very explicit in how you track and how you spend that money from an auditability perspective. Beyond that, there is a move when it comes to the technology business management, which is the actual labeling of what we actually spend money on for different services or labor or software. And what Cloud Tracker allows us to do is speak the language of the different colors of money. It allows us to also get very fine grain in the actual analysis of, from a TBM perspective, what we're spending on. >>But then also it has real time hooks into our financial systems for execution. And so what that really does for us is it allows us to complete the picture, not just be able to see our spend in the cloud, but also be able to able to see that spending context of all things in the P P P E process as well as the execution process that then really empowers the government to make better investments. And all we're seeing is either cost avoidance or cost savings simply because we're able to close that loop, like I said. Yep. And then we're able to redirect those funds, retag them, remove them through our actual financial office within the headquarters of the army, and be able to repurpose that to other modernization efforts that Congress is essentially asking us to invest >>In. Right. So you know how much money you have, basically. Exactly. Right. You know how much you've already spent, you know how you're spending it, and now you how much you have left, >>You can provide a reliable forecast for your spend. >>Right. You know, hey, we're, we're halfway through this quarter, we're halfway through the, the fiscal year, whatever the case might be. >>Exactly. And the focus on expenditures, you know, the government rates you on, you know, how much have you spent, right? So you have a clear total transparency into what you're going to spend through the rest of the fiscal. Sure. >>All right. Let's just talk about the relationship quickly then about going forward then in terms of federal services and then what on, on the, the US Army side. I mean, what now you've laid this great groundwork, right? You have a really solid foundation where now what next? >>We wanna be all things cloud to the army. I mean, we think there's tremendous opportunity to really aid the modernization efforts and governance across the holistic part of the army. So, you know, we just, we want to, we wanna do it all with the Army as much as we can. It's, it's, it's a fantastic >>Opportunity. Yeah. AFS is, is in a very kind of a strategic role. So as part of the ecma, we own the greater strategy and execution for adoption of cloud on behalf of the entire army. Now, when it comes to delivery of individual capabilities for mission here and there, that's all specific to system owners and different organizations. AFS plays a different role in this instance where they're able to more facilitate the greater strategy on the financial side of the house. And what we've done is we've proven the ability to adopt cloud as a utility rather than this fixed thing, kind of predict the future, spend a whole bunch of money and never use the resource. We're seeing the efficiency for the actual utilization of cloud as a utility. This actually came out as one of the previous NDAs. And so how we actually address nda, I believe it was 2018 in the adoption of cloud as a utility, really is now cornerstone of modernization across all of the do d and really feeds into the Jo Warfighting cloud capability, major acquisition on behalf of all of the D O D to establish buying cloud as just a common service for everyone. >>And so we've been fortunate to inform that team of some of our lessons learned, but when it comes to the partnership, we just see camo moving into production. We've been live for now a year and a half. And so there's another two and a half years of runway there. And then AFS also plays a strategic role at part of our cloud enablement division, which is essentially back to that teaching part, helping the Army understand the opportunity of cloud computing, align the architectures to actually leverage those resources and then deliver capabilities that save soldier's >>Lives. Well, you know, we've, we've always known that the Army does its best work on the ground, and you've done all this groundwork for the military, so I'm not surprised, right? It's, it's a winning formula. Thanks to both of you for being with us here in the executive summit. Great conversation. Awesome. Thanks for having us. A good deal. All right. Thank you. All right. You are watching the executive summit sponsored by Accenture here at Reinvent 22, and you're catching it all on the cube, the leader in high tech coverage.

>> Well, quick introductions for everybody kind of out there watching in the Data Summit. I'm Ali Tierney. I am the GVP. I run EMEA Sales for Snowflake, and I'm joined today with Michael Gillespie. Quick, just to introduce himself, what he does, and the DPE come structure as it goes. Go ahead, Micheal. >> Thanks, Ali. So as you said, I'm CDTO at Domino's Pizza Enterprises. So the company that I work for, we have the franchise rights and run Australia and New Zealand, France, Belgium, Netherlands, Germany, Japan, Luxembourg, and Denmark. And that's obviously Domino's Pizza for those markets. I look after four different verticals within the business. IT for the group, Strategy and Insights where our BI team resides and has a lot to do with Snowflake. Our Store Innovations Team, our Store Innovation Operations team which look at everything from robotics in store, how to use data better in store to be working at optimum level, and our digital team which is where I started in, actually, 13 years ago. And they're guiding our digital platform at a global level and how we localize it with the local marketing teams. >> Brilliant, I'm American and I grew up with Domino's Pizza, so help me understand, kind of, from a high structure. You've been there 13 years. My growing up experience was picking up a phone and pushing buttons and calling Domino's, and clearly a ton of modernization has come in the last 20 years, and you've been with the company for 13. What have you seen as you've grown into the DPE digital kind of space and you're driving that market? How are you guys using data? What have you seen happen over the last 13 years? >> Domino is itself, or at least DPE as well, has always been a data-driven business. What we've seen, though, as we've become more of a business that utilizes digital and technology to enhance, whether the customer experience or our store operations or our enterprise team. Is the availability of data to make decisions or to actually find insights. And if I look back, I've been lucky to go on a journey of 13 years with DPE. The power of analytics and data was apparent in a digital space. And it gave us a level of insight over a purchase that we never had before. So a great example of our first use of real data in a customer experience outside callbacks people are late, where we could give real-time feedback to a customer around their progression of their order through something called Pizza Tracker, which is shared across all and used across most Domino's in the world. And they're most common for most purchasing processes. Since then, we've gone from, I could count, very easily in between this call, how many orders would make in a day online, to now over 70% of our businesses online. We have a huge amount of data coming in from different, different areas of business. And now the challenge for myself and my team is how do we make this data readily available? To the local marketing teams, local operations teams. To really get better insights on the local market. So we've just gone from having a small pool of data to a tremendous quantum of data. >> So as you look to kind of localize your markets, right? I think you just mentioned seven or eight different markets that you're in. And I would assume then you have some data sharing that goes on within DPE, right? So Belgium wants something that's different than the Netherlands that was different than Japan, right? So how are you right now democratizing that data and giving it to your customers so that your end users can see how to use that, right? In local marketing in local, kind of, business uses. >> Correct. So, we have, we have nine markets now within DPE and all those markets, every market has unique needs and wants and challenges that they're trying to solve for. So our goal is to really try to simplify the access. And that's what we talk about democratizing data. We have a series of reports so we can build customized reports so that we don't have to do as many ad hoc requests. Then when giving those dashboards having the ability to customize and benchmark where you need to. And then when it comes down to a unique customer experience that's obviously going to be a localized marketing on them because different customers bought certain, certain volumes of pizza or sides and different market that's different. So we need to make the tools that each of them and or allow our marketing teams around the world to get access to the data that they can really help them make the most informed decisions to support their franchisees and stores. >> How much of your technology has moved in general to the cloud? And then secondarily to that question, as you've moved there, and I assume significant multi-clouds because you've got so many different regions and locations, how are using Snowflake to help move data into the cloud? >> I would say from a cloud perspective we're well advanced in being clouded for a majority of our platforms or at least moving in that direction. And we're being cloud friendly economic solution and some of that data solutions for quite a while. We still have some on-premise data, like most companies, and we're in the process of migrating. And we have to be aware that we operate within markets like Europe, where GDPR is there. And we have to, we have to be well across requirements from that ability that perspective. But regardless of GDPR or not with any form of customer data or employee data or any personal data we have, we know it's a privilege to hold. So anytime we are working with data we always want to make sure that we're storing it and accessing it in the most secure way. And then beyond that, we want to make sure that, as I talked about, we want to democratize data and make it more accessible. So, you know, I'm really looking forward to seeing as we build out and continue to build out our data strategy, how we continue to work with the likes of Snowflake to just bring faster and more insightful, you know, visibility into each particular market and at a global level as well. So that our global leaders can understand how the business is performing but also get micro where they need to. >> How, as you go through your cloud journey and then and with Snowflake specifically, how did you guys look to governance and how did you look to ensure your security around data? >> Yeah. So know for us, it's all about making sure we've got the right governance and controls and processes. So working with our security team, working with the right architects on data flow and processes, working with our legal team and representatives in each market and that's vital. You know, having policies and governance around any form of activity whether it be data or around changes on the website or changes even in any operational processes is important. So. >> Yeah >> And the greatest thing is if he can, you know, through, if you're making dashboards that are unquantifiable non-personal data, you know that's a lot easier to manage, as well. Because that's giving you a representation of groups not actually down to the particular customer. >> That makes perfect sense. How have you found migrating to Snowflake? Talk through that journey a little bit and I know you're relatively early in the journeys but talk at your experience has its been so far. >> You know, the BI team, my BI team and Strategy and Insights Team have definitely been huge fans of Snowflake and the support from the team there and and the partners we're using for integration. You know, one thing that I know that, that excites me from a strategic level, it's Snowflake's ability to be cloud agnostic and for us everything we build in the future we have chosen partners that we work with in the cloud space. We shouldn't be, we should always be having that ability to be flexible or we're always going to have some fragmented data sets and the ability to utilize a solution that can stretch out into those is very important. So you know, from a strategic level that's a great level of flexibility and from a micro level, and to look at how the team operate when they're coming with stories around greater efficiency, greater flexibility, reduced processing time, reduce, reduce time, reduction in costs and certain activities. That's a great story to be told. That's what I like about this story is that they were all wins. You know, I'm getting from the team that I can run more intensive workloads now. You know, that they can they can do more immediate action. You know, they are cutting down time, as I said, something down from hours to minutes down getting some early results and that's so important. >> So, tell me what kind of business insights you're delivering back to your stakeholders when you get through this process? The quick wins. >> Yeah, well I guess it's just us being able to get reports out faster. Get information out faster, Get access to any acts, build, build bespoke things quicker. It's all about Domino's as a business that's quite an entrepreneurial fast moving. So if you can find efficiencies that, like any business, that's, that's the point. But if we can find efficiencies within our team what it means is we've got a quantum of work the team can do or a service can do, or a bucket of costs can do. If we can reduce that quantum of whether it be cost or time and human effort, that means we can output more. One thing that we're also looking at is we talked about democratizing data earlier, but how can we empower, empower teams to get insights faster? Or to go, I always think there should be no one key holder. There should be key holders of obviously the security of the data and the, and the safety and the and the rules around it. But, in regards to broad insight data or in visibility of results, we should be trying to make that as accessible as possible so that teams can find the reading sites. You've got then thousands or hundreds of people that are looking. Whether it be franchisees at store or team members that had offices in different departments. If they can get greater visibility at a top level data and drill in micro and performance, imagine the insights you continue to do or if you can get reports in their hands faster. Time in a fast moving business a day or two of lost opportunity is huge. So how do you get to make those decisions faster? And how do you stay ahead of your game? >> So as you think of data cloud and as you think of how you're going to build out a DPE specific data cloud, where do you see that going? How, where do you get where's your nirvana and end goal from your data club? >> How do we make better use of that data? So, how do we win? We know that our data repositories are only going to continue to grow. You know, we're a business that was growing at a relatively strong rate. If you look at our previous results, we have a multitude of countries. We have 2,600 stores around the world pumping out pieces every night. And that's creating different forms of data. We have 70% of our customers online. When you're capturing a continuous amount of data. One thing that we want to do is not only manage it efficiently We know that capturing data is a privilege as well, so that we're capturing the right data. And then when you're capturing the right data we still know that the quantum of that will increase. So then how we are storing it and making sure that as we add more data to our repositories we are not actually making its harder to access or it's slower to access. So it's bringing down our reports that we're continuing to optimize and what we're seeing and I touched on when you're bringing time down from hours to minutes with a tool. We're doing that. We're bringing down those solutions. So being able to manage the increasing volume of data we're getting in a more efficient way. Being able to democratize the access of it in a safe, secure, but insightful way. But, you know, having the backing of a service like Snowflake in the background, supporting access and functioning about data. Hopefully, this just means that it will give us more ability to be nimble and do more in the future. >> As you've broken down data silos with using Snowflake and started to democratize data and put it all in one spot your ML becomes richer and more able to make better decisions because you got it all out of silos at this point. >> Yeah.We've got a better floral collection about data. And we can make those data repositories more accessible or no more efficient in accessing them. It's only going to enrich our models and it's going to challenge us. I can challenge and the business can challenge the strategy and insights and BI team to look at a multitude of ways as part of supporting the business. Because they've always got a backlog of reports or solutions they want to deliver. So, we had started a journey of being a data driven company. We have started the journey of a digital company many, many years ago. >> So as we leave today Michael and we wrap up. Last question I have for you is, as you know, everybody's coming and saying do the next bread is coolest next thing. What would you recommend the users of our conference? What would you say? Like how would you, how would you say to go to market and do it the right way? >> Yeah. Let's say the main thing is for those people to reflect upon their own business and understand the challenges at hand. it's very easy to be asked, why aren't we doing AI? Why aren't we doing machine learning? Why aren't we? But those are just solutions. You should be trying to take time to say okay, but what are some of that challenges? And then can we apply those technologies to it? or could a rudimentary approach, approach of just a simple report or a very basic algorithm solve for that. But if you could take your system to the next level with ML, don't do it for ML's sake or if you could take it with a complex data extract. Make sure you've got an angle inside of what you want to deliver. And then know, once you go down the path of anything more complicated, especially with things like machine learning, that it's a never-ending story. And you're probably not going to get the result you like in the first couple of weeks or month because that's what it is. It's a learning solution. It's a ever evolving beast and you can't just throw it out there and say, "Oh, everyone will be happy." So make sure you've got a fair commitment to getting into that game. And that you've got an envision in hand, and that envision will, I can tell you, usually move once you achieve it. Because you're only going to unlock more realities or more alternative solutions that'll grow from it. >> Absolutely. >> So be strong and want the challenges. >> I love that, and it's how we like to think about the data cloud in general, right? Is we are delivering to the business. At the end of the day, data is useless if you're not giving insights and ability for your business to make decisions and move forward. So I completely agree and I really appreciate the time you took today to sit down with me and educate me on Domino's and educate the world on how you're using data to make better decisions in the business. Thanks, Michael. >> Thanks for your time.