 Live from Las Vegas, it's theCUBE, covering the AWS Accenture Executive Summit, brought to you by Accenture. Welcome back everyone to theCUBE's live coverage of the AWS Executive Summit here at the Venetian. I'm your host, Rebecca Knight. We have two guests for this segment. We have Akhtar Said, VP, Solution Delivery, Southern Glacier Wine and Spirits, and Michael Noelle, Managing Director Applied Intelligence at Accenture. Thank you so much for coming on the show. Thank you. Thank you for having us. I think this is going to be a fun one. We're talking about wine and spear. Absolutely. So Akhtar, tell our viewers a little bit about Southern Glacier. Yeah, so Southern Glacier Wine and Spirits is a privately held company. We are in about 44 states, and we are the largest distributor of wine and spirits. Okay, and 44 states, how, what was the business problem you were trying to solve in terms of the partnership that you formed with Accenture? Yeah, so we started this initiative before Southern and Glacier merged. And that was in? Yeah, it was 2016. So Southern was already looking at how to enhance our technology, how to provide better data analytics, and how to create one source of truth. So that's what drove this, and we were looking to partner with an appropriate system integrator and write technology to be able to help deliver value to the company to be able to do analytics and in data analysis. So you had two separate companies merging together, and I like this idea, one source of truth. What does that mean? What did that mean for you? Well, what it means to us is that since we have, we had quite a few data marks out there. And everybody is looking at it, numbers will differently, we spend a lot of time trying to say, hey, is this right or is this right? So we want to bring all the data together, saying this is what the data is, and this is how we're going to standardize it. That's what we're trying to do. Okay, so this one source. Now, Michael, in terms of that, is that a common issue, particularly among companies that are merging, would you say? No, absolutely. You have businesses that might be in the same industry, but they might have different processes to try to get to the same answer, right? And the answer is never really the same. So having this conflict of a clean room that allows you to take your various aspects of a business and combine it from a data point of view, a business metrics point of view and a business process point of view, this one source helps you consolidate and streamline that. So you can see that integrated view across your new business model, really. So where do you begin? So you bring in Accenture and AWS, and where do you start? Yeah, what, as Swin, like you mentioned, 2016 laser and sudden wind spirits came together to merge, it actually accelerated process because we needed what Mike mentioned as a clean room, where we could put this data and wouldn't have to merge our data centers on day one and have the reporting, a common reporting platform being available for the new SGWS. And that's what we started. So we said, okay, what is the key performance indicators, the key metrics that we need going into day one? And that's what we want to popular the data with to begin with, to make sure that information is available when the day one from Merger comes through. Okay, and so what were those indicators? There were several indicators, there were several business reports, people need to supply chain, they need to understand the data, what the inventory looks like, they need to know how we're doing across the markets. So all those indicators, that's what we put together. Okay, okay, and so how do you work with a client in this respect? How do you and AWS sort of help the client, look at what the core business challenges are and then say, okay, this is how we're going to attack this problem? Right, no, that's a good question. I think the main thing is understanding what does the business need and how is the technology going to support what the business needs, right? That's first and foremost, right? And getting alignment and understanding that, really what drives a roadmap to say, here's what we're going to do, here's the order that we're going to do it in and here's the value that we expect to get out of following these steps one by one. And I think one thing we learned is you have to be directionally correct. It may not be exact, but as long as we're making progress in the right direction, you course correct it as you need to, right? Based upon, as the business learns new things and as the market changes and whatnot and that's really how we accomplish this. And is it a co-creative process or how closely are you working with Accenture and AWS? Oh, very closely with Accenture and AWS. It's very co-creative. I mean, we are really working hand in hand. As Mike alluded, you start certain ways and journey and you realize, gee, this may work, but I have to change a little bit here. And there are several things, several times we have to change things in direction, how to get there and how to approach it and to deliver value. Well, let's talk, let's get into the nitty gritty with the architecture and components. So what did this entail, coming to this clean room, this one source of truth? Yeah, in terms of architecture, it's based on AWS platform or Accenture's AIP, Accenture Insights platform which runs on AWS. And we have, what we did from right from the beginning, we said we're going to have a data lake. We're going to have a Hadoop environment where we're going to put all our data in there. And then for analytics, we said we're going to use Redshift. On top of that, for reporting, we use Tableau and we have a homegrown tool called Compass for reporting also that we use. So that's how we initially started. Initially, we were feeding data directly into it because we needed to stand the system relatively quickly. The advantage to us, we didn't have to deal with infrastructure, that was all set up at AWS. We just need to make sure we load our data and make sure we make the reports available. Were you going to add something to that? Yeah, I know the concept around, because of the merger is expediting this clean room, which allows you to stand up in analytics as a service model to start bringing your data, to start building out your reporting analytics quickly. Which really speed the market to understanding their position as an integrated company was so important. So building the Accenture Insights platform on the AWS platform was a huge success in order to allow them to start going down that path. Yeah, I want to hear about some of the innovative stuff you're doing around data analytics and really let's bring it back down to earth too and say actually, so this is what we could learn and see in terms of what was selling, what was not selling, what were you finding out? So at this point, we have about 6,000 users on the platform approximately. Initially, we had some challenges, I'll be very frank upfront, that everything does not go smooth. That's why we didn't say, okay, what do I do differently? We started with dense storage nodes and we soon found it's not meeting our needs. Then we enhanced to go to dense cluster and they helped us about by 70% that it drove the speed, but the queue length was still long. We were still not getting the performance we needed. Then we went to second generation of dense computers and clusters, we got some more leverage, but really the breakthrough came when we said we need to really reevaluate how are we doing our workload management. Some of our queries were very short-term report queries real quick, others were loading data that took a while and that's the challenge we had to overcome with the workload management we were able to create where we were able to bump queries and send them to different direction and create that capacity and that's what really had a breakthrough in terms of technology for us. Till that time, we were struggling, I'll be honest, but once we got that breakthrough, we were able to comfortably deliver what business needed from data perspective and from business perspective. Mike, would you like that? Yeah, I think in addition to AWS using Redshift has really been a really important, I guess, decision and solution in place here because not only are we using it for loading massive amounts of data, but it's also being used for power users to generate very out of Harkin large queries to be able to do some, to support other analytic type needs, right? And I think Redshift has allowed us to scale quickly as we needed to based upon certain time to view or certain market conditions or whatever, Redshift has really allowed us to do that in order to support where the business demands have really grown exponentially since we've been putting this in place. And it all starts with architecting, on the set, and delivering all around the data and then how do you enable the capabilities, not just data as a foundation, but real-time analytics and looking at what could be forecasting and predicting what's happening in the future using artificial intelligence, machine learning, and that's really where the platform is taking us next. I want to talk about that, but I want to ask you quickly about the skills challenge because introducing a new technology, there's going to be maybe some resistance and maybe simply your workers aren't quite up to speed. So can you talk a little bit about that, what you experienced, and then also how you overcame it? Yeah, I mean, we had several challenges. I mean, I'll put in two big buckets. One is just change management. Many times, you're changing technology on this many users. They're comfortable with something, they know a known commodity. Here's something new, that's a challenge. And I once should not ignore, we need to pay a lot of attention to how to manage change. That's one. Second challenge was within the technical group itself because we were changing technology on them also, right? And we had to overcome the skills sets we did. We were not the company who were using open source a lot. So we had to overcome that and saying, how do we train our folks? How do we get the knowledge? And in that case, Accenture was a great partner with us. They helped us tremendously and AWS professional services. They were able to help us and we had a couple of folks from professional services. They really helped us with the technology to help drive that change. So you have to tackle from both sides. But we're doing pretty well at this point. We have found our own place where we can drive through this thing. In terms of what you were talking about earlier, in terms of what is next with predictive analytics and machine learning, can you talk a little bit about the most exciting things that are coming down the pipeline in terms of Southern Glacier? I think that's a great question. You know, I think there's multiple ways to look at it. They're from a business point of view, right? Is how do they gain further insights by looking at as much different data sets as possible? Right? Whether it be internal data, external data, how do we combine that to really understand the customers better, right? And looking at how they approach things from a future point of view. We've been able to predict what's going to happen in the marketplace. So I think it's about, you know, looking at all the different possible data sets out there and combining that to really understand what they can do from an art of the possible point of view. Can you give us some examples of terms of combining data sets? So you're looking at, I mean, I'm treating patterns or what do we have here? I mean, you have third party data, right? TD links and those kinds of things. You pull that data in, then you have our own data. Then we have data from suppliers, right? So that's where we combine saying, okay, what is this telling you? What story is this particular data telling me? I don't think we are there all the way. We have started on that journey. Right now we are, what I call, we put this one source of truth and we still have some more subjectories to load into it. But that's the vision that how do we pull in all those data information and create predictive analysis down the road and be able to see what that means and how would we drive it? And so you're really in the infancy of this? Yes, I mean, it's a journey, right? Some may say that you're not in infancy when the middle somewhere. Somebody say, if they're ahead of us, it's all depending where you want to put this on that chart. But we at least have taken first steps and we have one place where the data is available to us now. We're just going to keep adding to it and now it's a matter of how we start to use it. In terms of lessons that you've learned along the way, and you've been very candid in talking about some of the challenges that you've had to overcome, but what would you say are some of the biggest takeaways that you have from this process? Yeah, biggest takeaway for me would be, already mentioned, change management. Don't ignore that, pay attention to that because that's what really drives it. Second one, our file says probably have a broader vision, but when you execute, make sure you look at the smaller things that you can measure, you can deliver against, because you would have to take some steps to adjust to that. So those are the two things, and third, have the right partners with you because you can't go alone on this, you need to make sure you understand that who you're going to work with and create a relationship with them and saying, hey, it's okay to have tough conversations, we have plenty of challenging conversations when we're having issues, but it's as a team how you overcome those and deliver well, that's what matters. Hi, praise for you, Michael and Accenture here. But what would you say in terms of being a partner with Southern Glacier and having helped and observed this company, what would you say are some of the biggest learnings from your perspective? Yeah, oddly enough, I think the technology is the easier part of all this, right? I think that's fair to say without a doubt, but really, I think really focusing on making the business successful, right? If everything you do is tied around making the business successful, then the rest will just kind of go along the way, right? Because that's really the guiding principles, right? And then you solve it with technology, right? And that's really, I think what we've learned most and foremost is bringing the business along, educating them and understanding what they really need and focusing on listening, right? And trying to answer those specific questions, right? I think that's really the biggest, I think, factor I think we've learned, I think, over the past journey, yeah. And finally, so we're here at AWS re-invent, 60,000 people descending here on Sin City. What most excites you about, why do you come, first of all, and what most excites you about the many announcements and innovations that we're seeing here this week? Yeah, that's all I'll be honest, this is the first time I've come to this conference. But it's been really exciting. What excites me about these things is the new innovation. What, you know, you learn new things. You say, hey, how can I go back and apply this and do something different and add more value back? That's what excites me. Yeah, no, I think you're absolutely right. I mean, AWS is obviously a massive disruptor across any industry and their commitment to new technology, new innovation, and the practicality of how we can start using some of that quickly, I think is really exciting, right? Because we've been working on this journey for a while and now there's some things that they've announced today I think that we can go back and apply pretty quickly, right, to really even further accelerate Southern Glacier's pivot to being a fully digital company. So a fully digital company, this is my last question, sorry, your advice for a company that is like yours, about to embark on this huge transformation. As you said, don't ignore the change management, the technology could sometimes be the easy part, but do you have any other words of wisdom for a company that's in your shoes? Only words of wisdom I'll have is just, I think already mentioned three things, they probably need to focus on just take the first step, right, that's the hardest part, I think Andy even said this morning, that some companies just never take the first step. Take that first step and you have to, this is where the industry is going and data is going to be very important, so you have to take the first step, saying how do I get better handle on the data? Excellent, great. Well, Michael, Akhtar, thank you so much for coming on theCUBE, this has been a real pleasure. Thank you, thank you for having us. Next time, bring some alcohol. Absolutely. Thank you, Rebecca. Yeah, thank you, appreciate it. I'm Rebecca Knight, we will have more of theCUBE's live coverage of the AWS Executive Summit coming up in just a few moments, stay with us.