 From around the globe, it's theCUBE with digital coverage of AWS re-invent 2020 sponsored by Intel, AWS and our community partners. Hey, it's Keith Townsend, Principal at CTO Advisor and you're watching theCUBE Virtual coverage of AWS re-invent 2020. I'm really excited. Whenever we get to talk to actual end users, builders, the conversation is dynamic. This is no exception. Back on the show, Avanesh Despande, Head of Architecture at Logitech. Avanesh, welcome back to the show. Thanks Keith, good to be here. And on the other side of my screen or depending on how you're looking at it is Anthony Brooks Williams, CEO of HVR. Anthony, welcome back to theCUBE. I know you're kind of tired of seeing us but the conversation is going to be good, I promise. Thanks very much. Look forward to being here. And great, as you said, to talk about a use case for the customer in the real world. So, let's start off by talking about Logitech. What are you guys doing in AWS in general? I mean, I know every company has public cloud but Logitech and AWS and public cloud doesn't naturally come to mind? Help educate the audience. What are you guys doing? Sure, so traditionally, audience knows Logitech as the mice and keyboard company but we do have a lot of brands which are co-brands of Logitech. If you know about gaming, Logitech G is a huge brand for us. We are in video collaboration space. We compete with the likes of Cisco's of the world where we have hardware that goes and works with Zoom, Google, as well as Microsoft ecosystems that has been a huge success in a B2B world for us. We are in music industry, gaming as in Astro gaming, Jay Bird, headphones for athletes. We are also in security system space. And on top of that, we are also in the collaboration space of streaming as in Streamlabs. So, as you can see, Logitech has grown to where a lot of use cases apart from just peri-fedals is out there. We've connected devices. So, we were also looking to move towards a cloud ecosystem where we could be in on our tools to provision information and make sure we are competing to the best of the world. So, we are in AWS. We do a lot more in AWS now compared to what we used to do in the past. Last five years has seen a change and a shift towards more cloud, public cloud usage, pure SaaS environments in AWS as well and we provision data for analysis and it's essentially as a data-driven enterprise now, more so as we move towards more future. And Anthony, talk to me about not necessarily just Logitech, but the larger market. How are you seeing companies such as Logitech take advantage of AWS and public cloud? Yeah, what I think you mean, ultimately we've seen it accelerated this year. I mean, Custle's just looking for a better way to connect with their prospects and leverage data in doing so. And we've seen this driver around digital transformation and that's just been spared up this year given what we've seen around COVID. And so a lot more companies have really pushed forward in adopting the infrastructure and availability of systems and solutions that you find in a platform such as AWS. And that's where we've seen great reduction from our side of customers doing that. We provide the most efficient way for customers to move data to a platform such as AWS and that's where we've seen a big uptake this year. So let's focus the conversation around data, data, the new oil, we've heard the taglines. Let's put some meat on the bone, so to speak, and talk through how are you at Logitech using real-time data in the public cloud? Sure. Yeah, I mean, traditionally if you looked at it, Logitech would sell in hardware and hope it works. For the end consumer, we would not necessarily have an insight into how that product is being used. I think come fast forward today's world, it's a connected devices environment. You want to make sure when you sell something that is working for that consumer, you would want them to be happy about that product, ensuring a seamless experience. So customer experience is big. You might want to see a repeat customer come about, right? So the intent is to have a lot of it is a connected experience where you could provision a feedback loop to the engineering team to ensure stability of the product, but also enhancements around that product in terms of usage patterns. And we play a big role with hardware in virtual gaming, for example. And as you can see that whole industry is growing to where everything is connected, probably people do not buy anything which is a static disk, the same thing. It's all online gaming. So we want to ensure that we don't add latency in the hardware that we have, ensuring a successful experience and repeat customers, right? So essentially intent is at the end of the day to have success with what you sell because there's obviously other options on the market and we want to make sure our customers are happy with the hardware. They are investing more in that hardware platform and adding different peripherals along with it. So that seamless experience is where we want to make sure it's connected devices to get that insight. We also look at what people are saying about our products in terms of reviews on apps or on retail portals to ensure we hear the voice of customer and channel out that energy in a positive way to improve the products as well as trying to figure out if there are marketing opportunities where you could go cross sell and upsell. So that's essentially driving business towards that success and at the end of it, that would essentially come up with a revenue generation model for us. So Anthony, talk to me about how HVR fits into this because when I look at cloud big, that can be a bit overbearing. Mike, where's the starting point? For us, the starting point to answer your question is around acquiring the data. Data is generated in many places across organizations in many different platforms and many systems. And so we have the ability to have a very efficient technique and the way we go acquire data, the way we capture data through this technique called CVC, change data capture, where you're feeding incremental updates of that data across the network. That's the most efficient way to move this data firstly across a wide area network. The cloud is an endpoint of that. And so firstly, we specialize in supporting many different source systems. And so we can acquire that data very efficiently, put it into our very scalable, flexible architecture that we have that's a great fit for this model world, a great fit for the cloud. So not only can we capture data from many different source systems, their complexities and a lot of these type of departments that customers have. And we can take the data and move it very efficiently across that network at scale, because we know, as you've said, data is a new order, that's the lifeblood of organizations today. So we can move that data efficiently at scale across the network and then put it into a system such as Snowflake running in AWS, like we do for Avi and Logitech. And so that's really where we fit. I mean, we support data taken from many sources to many different target systems. We make sure that data is highly accurate when we move that data across that it matches what was in the source to matches what's in the target system. And we do that in this particular use case and what we see predominantly today, the source systems are capturing the data typically today still generated on-prem, could be data that's sitting in an SAP environment, unpack that data, decode that data, it's to be complex to get out and understand it and move it across and put it in that target system that predominantly is sitting in the cloud for all the benefits that we see that the cloud brings around elasticity and efficiency and operational costs and those type of things. And that's probably where we fit into this picture. You know, I think Keith, if I add a little bit there, right? So to Anthony's point, for us, we generate a lot of data. We were looking at billions of rows a day from the edge where people like you and I are using Logitech devices. And we also have a lot of ERP transactions that go in. So the three V's typically that they call about big data is like the variety of data, volume of data and at velocity that you want to consume it. So the intent is, if you want it to be data driven, the data should be available for business consumption as it is being generated, very near real time. And that the intent for some of these platforms like HVR is how efficiently could you move that data, whether it's on-prem or a different cloud into AWS and giving it for business consumption of business analysis in near real time. So, you know, we strive to be in real time, whether it's data from China in our factory on the shop floor, whether it's being generated from people like you and I playing a game for eight hours and generating so many events, we want to ensure all that data is being available for business analysis and gone are the days where we would load that data once a day and in the hope that we do a weekly analysis, right? Today we do analysis and make business decisions on that data as the data is being generated. And that's the key to success with such platforms where we want to make sure we also look at build versus buy rather than us doing all that code and trying to ingest that data, we obviously partner with HVR in certain application platforms to ensure stability of it. And they have proven with their experience, the IP or the knowledge around how to build those platforms, which even if we go build it, we might need bigger teams to build that. I would rather rely on partners for that capability and I bring more business value by enabling and implementing such solutions. So let's go a little color around that skill. Whenever I talk to CDOs, chief data officers, data architects, one of the biggest problems that they have in these massive systems, you're talking about getting data from ERP, internet of things, devices, et cetera, simple data transformation, ETL, data scientists spend a good majority of their time, maybe sometimes 80% of their time on that data transformation process, that slows down the ability to get answers to critical business analytic questions. How is HVR assisted you guys in curling down at time for ETL? Absolutely, so we went to cloud about five years back and the methodology that you talk about ETL is sort of a point term back in the day when you would do maybe couple of times a day ingestion. So it's like in the transition of the pipeline, as you are ingesting data, you would transform and massage the data and enhance the data and provision it for business consumption. Today, we do ELT, we extract, load it into target and natively transform it as needed from business consumption. So we look at HVR, for example, is we'll be replicating all of our ERP data into snowflake in the cloud for real-time ingestion and consumption. If you do all of this analysis on Oracle site to it, typically you would have a processing where you would put in a job to get that data out and the analysis comes back to you in a couple of hours. Out here, you could be slicing and dicing the data as needed and it's all self-serve and provisioning. We do not build analysis for end users. Neither do we do a lot of the data science, but we wanna make sure when business is using that data, they can act on that as it's available. And the example is we had a processing back in the day with demand forecasting, which we do for every product of Logitech for 52 weeks looking ahead for every week, right? And it would run for a couple of days that processing. Today with such platforms and in public cloud, we do that in an hour's time, right? And that's critical for business success because you wanna know the methodology is if you need to fail or have challenges, you probably wanna have them now rather than wait couple of days for that processing to show up and then you do not have enough time to adjust the parameters or bring in back some other business process to augment it. So that's what we look at. The return on investment for such investment are essentially ensuring business continuity and success upfront and faster time to deliver. So, Anthony, this seems like this would really change the conversation within enterprises. The target customer or audience really changes from kind of this IT centric movement to more strategic movement. Talk to me about the conversations you've had with customers and how this has transformed their business. Yeah, a few things don't pack there. One, I mean, obviously customers wanna make decisions on the freshest data. And so they've typically relied on in the past on these batch orientated top data movement techniques which are we touched on then, how are we able to reduce that time window, let them make decisions on the freshest data. Where that takes you to is into other parts of organizations because as we said already, I mean, we know data is the lifeblood of them. There was many, I would say typically IT savvy, but let's call it data savvy people sitting in the business side of organizations if not more than used to sit in the legacy IT side. They want access to this data. They want to be able to access that data easy. And so one, these cloud based system, SaaS based systems have made that a lot easier for them. And the conversations we have are very much driven from not only the chief data officers but the CEOs now. They know in order to get the advantage to win, to survive in today's times, they need to be data driven organizations. And it sounds cliche, and we hear these digital transformation stories of data driven taglines that get thrown out there. But what we've seen is where it's really, it's been put to task this year, it is happening. Projects that would happen nine, 12 months have been given two month windows to happen because it's a matter of survival. And so that's what's really driven. And then you've also had the companies that have benefited as well. You mean, we are fortunate that we are able to as a company globally with Impose on a World to work from home very efficiently, but then support customers like Arby's who are providing these work from home technology systems that can enable a lot of this. And that's where it's really moved. It's driven down from being purely IT driven to it's CEO, CIO, CDO driven because it's what they've got to do. It's no longer just table stakes. I think the lines are great, right? We roll up into CIO, and like I worked for the CIO at Logitech, but we strive to be more service oriented than support. So IT was traditionally looked at as a support R, right? But we obviously are enabling the enterprise to be data driven. So we strive to be better at what we do and how we position ourselves as more of a service org connected to business problem. We understand the business problem and the challenge that they have and ensuring we could find solutions and solution architectures around that problem to ensure success for that, right? And that's the key to it, whether we build versus buy, it's all about ensuring business doesn't have to find stopgap solutions to be successful in finding a solution for their problem. Avi, Anthony, I really appreciate you guys taking the time to peel back the layers and help the audience understand how to take these really abstract terms and make them real for getting answers on real time data and kind of blowing away these concepts of ETL and data transformations and how to really put data to work using public cloud resources against their real time data assets. Thank you for joining us on this installment of theCUBE virtual as we cover AWS re-event. Make sure to check out the portal and see more great coverage of this exciting area of data and data analysis.