 Live from Las Vegas, it's theCUBE! Covering AWS re-invent 2019. Brought to you by Amazon Web Services and Intel, along with its ecosystem partners. Welcome back to theCUBE. From Las Vegas, we are live at AWS re-invent 19. Lisa Martin with John Furrier. We've been having lots of great conversations. John, we're about to have another one because we always love to talk about customer proof in the pudding. Please welcome a couple of guests. We have Rafael Mejia, Director of Analytics and Data Management from AAA Life. Welcome. Thanks for having me. Really appreciate it. Our pleasure. And from Merkel, Anchor Jane, the SVP of Cloud Platforms. Welcome. Thank you. Thank you so much. Pleasure to be here. So here we are in this, I don't, can't, the sea of people around us is growing exponentially by the hour here. But Anchor, let's start with you. Yes. Give our audience an understanding of Merkel, who you are and what you do. Yeah, absolutely. So Merkel is a global performance marketing agency. We're part of a 10 to two ages network. And it's almost about 9,000 to 10,000 people worldwide. It's a global agency. What differentiates Merkel from the rest of the other marketing agencies is our deep roots in data driven approach. We embrace technology. It's embedded in all our solutions that we take to market. And that's what we pride ourselves with. So that's basically a high level pitch about Merkel. What differentiates us. My role, I lead the cloud transformation for Merkel. Basically think of my team as the think tanks who bring in the new technology, come up with a new way of rolling out solutions, productized solutions, disruptive solutions, which helps our clients and big fortune brands such as Triple A Life Insurance to transform their marketing ecosystem. So let's go ahead. I think a lot of folks probably know Triple A Life, but Rafael, give us a little bit of an overview. This is a 50 year old organization. It is. So we celebrate our 50 year anniversary this year actually. We're founded in 1969. So Triple A Life Insurance, we endeavor to be the provider of choice for Triple A members to help them protect what matters most to them. And we offer a diverse set of insurance products across just about every channel. And we engage with Merkel earlier in 2018 actually to build a technology solution that allows to even better serve the needs of the members. My role, I lead our analytics and data management work, solving us, collect data, manage better, and better leverage it to support the needs of members. So I can't even imagine the volumes of data that you're dealing with, but it's also, this is people's data, right? This is about insurance. It is. Life insurance. It is. But the volume of it, how have you, what were some of the things that you said, all right guys, we need to change how we're managing the data because we know there's probably a lot more business value, maybe new services if we can get our hands on it, our eyes on it. So that was it. So as an organization, I want to underscore what you said. We make no compromises when it comes to the safety of our members data. And we take every step possible to ensure that it is managed in a responsible and safe way. But we knew that on the platform that we had prior to this, we weren't as agile as we wanted to be. We would find that certain processes would take spans of weeks in order to operate or to run. And that just didn't allow us to provide the member experience that we wanted. So we built this new solution and this solution updates every day, right? There's no longer multi-week cycle times and some of our processes happen in real time, which allows us to go to market with more accurate and more responsive programs to our members. Can you guys talk about the Amazon AWS solution? How are you guys using Amazon as a redshift, you guys are using multiple databases? Give us a peek into the Amazon services that you guys are taking advantage of. Can I take that anchor? Yeah, please. So basically when we were approached by AAA Live to kind of come in and present ourselves, our credentials, one thing that differentiated there in that solution page was bringing Amazon to the forefront. Because cloud, one of the issues that Rafael and his team were facing were scalability aspect. The performance was not up to the par. I believe you guys were on a two-week cycle that data was refreshed every two weeks. And how can we turn that around? Can only be possible through disruptive technologies that Amazon brings to the forefront. So what we built was basically it's a complete Amazon-based cloud-native architecture. We leveraged AWS Redshift as the data warehouse platform to integrate basically billions and billions of rows from 100 plus sources that we are bringing in on a daily basis. In fact, actually some of the sources are refreshed on a real-time basis. We are catching real-time interactions of users on the website, and then letting AAA Live make real-time decisions on how to actually personalize their experience. So AWS Redshift, definitely the centerpiece. Then we are also leveraging a cloud-native ELT technology, extract load and transform technology called Matillion. It's a third-party tool, but again, a very cloud-native technology. So the whole solution leverages Python to some extent, and then Ravel can talk about AI and machine learning that how they are leveraging AWS ecosystem there. Yeah, so that was, so Anker said it right, one thing that differentiated Merkle was that cloud-first approach, right? We looked at what all of the analysts were saying, we went to all the key vendors in the space. We saw the architectures, and when Merkle walked in and presented that AWS architecture, it was great for me because the technology immediately made sense. There was no wizardry around. I hope this database scales. I was confident that Redshift and Lambda and Dynamo would scale to our use cases. So it became a lot more about, are we solving the right business problem and less about, do we have the right technologies? So in addition to what Anker mentioned, we're leveraging R, so we're leveraging R and R Studio in AWS as well as Tableau for our machine learning models and for our business intelligence. And more recently, we've started transition from R to Python. As a practitioner on the keynote today, slew a new thing, SageMaker, Studio, an IDE for machine learning framework. I mean, this is like, a common set, like finally. I couldn't have been more excited, right? That was my Super Bowl moment. I was asked, we were actually at dinner yesterday, and I was mentioning to Anker, this is my wish list, right? I want AWS to make a greater investment in that end-user data scientist experience in AutoML, and they knocked it out of the park. Everything announced today. I was just, I was texting Fred, wow, this is amazing. That was, it was, I'm, I can't wait to go play with it. And there's a lot of nuances too in a lot of these announcements. AutoML, for instance. Really big deal the way they did it. And again, the IDE, who would have thought? I mean, this is duh. Why didn't we think about this sooner? Yeah, with AutoML, that, that focus on transparency, right? And then I think about a year ago, we went to market and we ended up not choosing any solutions because they hadn't solved for, once you've got a model build, how do you effectively migrate it from, let's say, an analyst who might not have the, the ML expertise to a data science team, and the fact that AWS understood out of the gate that you need that transparency for it. I'm just really excited for that product. What do you think the impact's going to be more uptake on the data science side? What's the impact of this and that? So I think we're going to see that a lot of our use cases are going to require a lot less effort to spin up. So we're going to see much more, much faster pilots. We're going to have a much clearer sense of is this worth, is this something we should continue to invest in and something we should drive? And I expect that a much larger percentage of my team, the analysts, are going to be involved in data, in data science and machine learning. So I'm really excited about that. And also the ability to, to integrate best practices into what we're doing out of the gate, right? So software engineers figured out profiling, they figured out debugging, and these are things that machine learners are picking up now. The fact that these are front and center is really exciting. I mean, Super Bowl moment, you could be like the New England Patriots. 17 straight AFC championship games. The Boston guys? Yeah. I couldn't resist. They're all Seattle. We don't get those right. They're all Seattle here in Amazon. I don't even bring Seattle Patriots up here at Amazon, at Amazon World. We are the ESPN of tech news. So we have to get in a sports conversation. But I want to kind of talk a little bit, Rafael, about the transformation because presumably in every industry, especially in insurance, there are so many born in the cloud companies that are a lot smaller, they're a lot more agile, and they are chasing what AAA life and your competitors and your peers are doing. What you're establishing with the help of Anker and Merkel, how does this allow you to actually take the data that you had, expand it, but also extract insights for maybe competitive advantages that you couldn't think about before? Yeah, so I think, so as an organization, even though we're 50 years old, one of the things that drew me to the company that was really exciting is it's not only just trusting on its laurels, right? I think there's tremendous hunger and appetite within our executive group to better serve our members and to serve more members. And what this technology has allowed is the technology is not a limiting factor, it's an enabling factor. So we're able to produce more models, more performant models, process more of our data, build more features. We've managed to do away with a lot of the, if you take it and you look at it this way and squeeze it and maybe it'll work and systematize more aspects of our reporting and our campaign development and our model development and the observability, just the ability to be agile and have our data be a partner to what we're trying to accomplish, that's been really great. You talked about the significant reduction in cycle times. If we go back up to the executive suite from a business differentiation perspective, is the senior leadership at AAA understanding what this cloud infrastructure is going to enable their business to achieve? Absolutely, so our successes here, I think have been instrumental in encouraging our organization to continue to invest in cloud and we're actively considering and discussing additional cloud initiatives, especially around the areas of machine learning and AI. And then, Ankur, question for you, in terms of your expertise and your experience, as we look at how cloud is changing, John, you know, educate us on cloud 1.0, cloud 2.0, AI, machine learning, what are as these, as businesses, as industries have the opportunity to, for next-gen cloud, what are some of the next industries that you think are really prime to be completely transformed? I mean, there are so many different business models. If you look around, one thing I would like to actually touch upon what we are seeing from Merkel's standpoint is the digital transformation. You know, how customers in today's world, they are, you know, how brands are engaging with their customers and how customers are engaging with the brands, especially their expectations. Customer is at the center stage here. They are the ones who are driving the whole customer engagement journey, right? How I am browsing a catalog of a particular brand on my cell phone, and then I actually purchase right then and there. And if I have an issue, I can call them, or I can go to social media and log a complaint. So that's whole multi-channel, you know, aspect of this marketing ecosystem these days. I think cloud is the platform which is enabling that, right? This cannot happen without cloud. I mean, look at, Rafael was just describing, you know, real-time interaction, real-time, understanding the behavior of the customer in real-time and engaging with them based on their need at that point of time. If you have technologies like SageMaker, if you have technologies like AWS Redshift, if you have technologies like Glue, Kinesis, which lets you bring in data from all these disparate sources and give you the ability to derive some insights from that data in that particular moment, and then interact with the customer right there and there, that's exactly what we are talking about. And this can only happen through cloud. So that's my two cents over there. What we, from Merkel's standpoint, we are looking into the market, that's what we are helping our brands to do. As a client, I completely agree. I think the change from capital to operation, right, to no longer have to know, these are all the sources and all the use cases and everything that needs to happen before you start the project, and the ability to say, hey, let's get going, let's deliver value in the way that we've had and continue to have conversations and deliver new features, new sources, new functionality, and at the same time having AWS as a partner who's building an incremental value, I think just last week I was really excited with the changes they've made to integrate SageMaker with their databases so you can score directly from the database. So it feels like all these things are coming together to allow us as a company to better accomplish our aims at an exciting time. It is exciting. Well, guys, I wish we had more time that we were out of time. Thank you, Raphael and Anchor, for sharing with us. Thank you, thanks for having us. I hope what Merkel and Triple A are doing. Thank you. It's been a pleasure chatting with you. Thank you very much. Pleasure. All right, take care. For John Furrier, I'm Lisa Martin, and you're watching theCUBE from Vegas. Reinvent 19. We'll be right back.