>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Hey, is Keith Townsend, principal at CTO Adviser, and you're watching the Cube virtual coverage of AWS reinvent 2020. I'm really excited whenever we get toe talk to actual end users. Builders. The conversation is dynamic. This is no exception. Back on the show, Al Vanish despondent head off architectures at logic I've been ish. Welcome back to the show. >>Thanks, Kate. Good to be here >>and on the other side of my screen or how you depend on how you're looking at it is Anthony Brooks Williams C E O off HBR Anthony, Welcome back to the Cube. I know your kind of tired of seeing us, but the conversation is gonna 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 I'll be let's start off by talking about lodge attacking. What are you guys doing in a W s in general? I mean, e no. Every company has public cloud, but Logitech and AWS and Public Cloud doesn't naturally come to mind. Help educate the audience. What do 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 cool brands off logic tech If you know about gaming, Logitech G is a huge brand for us. We are in video collaboration space. We compete with the likes off Ciscos of the world, where we have hardware that goes on bond works with Zoom Google as well as Microsoft ecosystems. That has been a huge success in a B two b well for us. Beyond music industry gaming as an Astro gaming Jay Bird head phones for athletes. We are also in security system space. On top of that were also in the collaboration space off streaming as in stream labs so a Z can see logic has grown toe where that a lot off use cases, apart from just peripherals, is out there. We connected devices, so we're also looking to move towards a cloud ecosystem where we could be in on on our toes, toe provisioning information on DNA, make sure we are computing 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 SAS environments in the ws as well And we provisioned data for analysis and essentially a data driven enterprise. Now more so on V as we move towards more future >>and Anthony talked to me about not necessarily just largest heck, but the larger market. How are you seeing companies such as logic? Heck take advantage off A W s and Public cloud. >>Yeah, but I think you mean ultimately we've seen it accelerated the show. Me Castle's just looking for a better way to connect with their prospects, you know, and leverage data in doing so. And we've seen this this driver around digital transformation and that's just being sped up the shirt, given what we've seen around covert and so a lot more companies have really pushed forward and adopting, you know, the infrastructure and the availability off systems and solutions that you find in a platform such as AWS on bets that we've seen grand deduction from our side of customers doing that, we provide the most efficient way of protesters to move data to so platforms such as I don't yes, and that's what we've seen. A big uptick picture. >>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 logic Tech using real time data in the public cloud? >>Sure, Yeah. I mean, traditionally, if you look at it, uh, logic could selling hardware. Andi hope it >>works for >>the end consumer. Uh, 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, it is working for that consumer. You would want them to be happy about that product, ensuring a seamless experience. Eso customer experience is big. You might want to see a repeat customer come about right. So So the intent is to have a lot off. It is connected experience where you could provisional feedback loop to the engineering team toe to ensure stability off the product, but also enhancements around that product in terms off usage patterns. And and we play a big role with hardware in what you're gaming, for example. And as you can see, that whole industry is growing toe where everything is connected. Probably people do not buy anything, which is a static discussing thing. It's all online gaming. So we want to ensure we don't add Leighton. See in the hardware that we have, ensuring a successful experience and repeat customers right? The essential 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 you want to make sure our customers are happy with the hardware they are investing. Maurin that hardware platform and adding different, very fills along with it so that seamless experiences where we wanna make sure it's connected devices to get that insight. We also look at what people are saying about our products in terms off reviews on APS are on retail portals to ensure we we hear the wise off customer on channel. How's that energy in a positive way to improve the products as well as trying to figure out if there are marketing opportunities were you could go across sailing up cells, 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 talked to me about how HBR fits into this, because when I look at cloud big, that can be a bit overbearing, like, where's where's the starting point? >>So I mean, for us, you mean the starting point Answer questions 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 in the way we go acquire data the way we capture data through this technique called CBC Chinese share the capture where you're feeding incremental updates off off the data across the network. That's the most efficient way to move this data. Firstly, across a wide area network cloud is an endpoint. Uh, you mean off that, And so, firstly, we specializing in supporting many different source systems and so we can acquire that data very efficiently, put it into our into a very scalable, flexible architecture that we have. That's that's a great foot for this modern world of great foot for the cloud. So not only can we capture data from many different source systems, their complexities and a lot of these type of the moments that customers have, we could take the data and move it very efficiently across that network at scale. Because we know, as you've said, data is the new oil 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 a snowflake running in AWS like we do for a hobby and a larger taken. So that's really where we fit. I mean, we can, you know, we support data taken from many sources, too many different target systems. We make sure that data is highly accurate. When we move that data across that matches what was in the source of matches, what's in the 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 SFP environment. Unpack that data. Decode that data is to be complex to get out and understand it on moving across and put it in their target system, that predominance sitting in the cloud for all the benefits that we see that the cloud brings around elasticity and efficiency and operational costs the most type of things. And that's probably human in where we fit into this picture. >>You know, I think if I add a little bit there, right, So to Anthony's point for us, we generate a lot of data. You're looking at billions off rolls a day from the edge where people like you and I are using logic devices and we also have a lot off prp transactions That going so the three V s Typically that they call about big data is like the variety off data volume of data at velocity that you want to consume it. So the intent is if you need 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 H we are, is How efficiently could you move that data, whether it's on Prem or a different cloud into AWS on giving it for business consumption of business analysis in near real time. So you know we strive, Toby Riel 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 on generating so many events, we're gonna ensure all that data is being available for business analysis and gone out of those 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 on 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 vs buy rather than us doing all that core and trying toe in just that data we obviously partner with which we are in certain application platforms to ensure stability off it. And they have proven with their experience the I P 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 put 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 E. AARP uh, Internet of things devices, etcetera is simple data transformation. E t l data scientists spend a good droid at a 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 HBR assistant you guys and curling down at time for detail? >>Absolutely. So we we do not. We went to cloud about five years back, and the methodology that you talk about e t. L is sort of a point back in the day when you would do, you know, maybe a couple of times a day ingestion. So it's like in the the transition off the pipeline. As you are ingesting data, you would transform and massage the return, enhance the data and provisioned it for business consumption. Today we do lt we extract loaded into target and natively transform it as needed from business consumption. So So we look at each. We are, for example, is, uh, we're replicating all off our e r P data into snowflake in the cloud for real time ingestion and consumption. Uh, if you do all of this analysis on article side to it, typically you would have ah, processing where you would put put in a job toe, get that data out, and analysis comes back to you in a couple of hours out here, you could be slicing and dicing the data as needed on it's all self serve on provisioning. We do not build analysis foreign users. Neither do we do a lot off the data science. But we want to make sure when businesses using that data they can act on that as it's available on the example is we had a processing back in the day with demand forecasting, which we do for every product off logic for 52 weeks, looking ahead for for every week, right, and it will run for a couple of days that processing today with such platforms on in public Lot. We do that in an hour's time. Right now That's critical for business success because you want to know the methodologies you feel need Tofail or have challenges. You probably wanna have them now rather than wait a couple of days for that process in the show up, and then you do not have enough time to, at just the parameters are bringing back some other business process toe augmented. So that's what we look at. The return on investment for such investment are essentially ensuring business continuity and success outfront on faster time to deliver. >>Yeah, >>so, Anthony, this seems like this would really change the conversation within enterprises. The target customer or audience really changes from kind of this IittIe centric movement tome or strategic move. We talked to me about the conversations you've had, what customers and how this has transformed their business. >>Yeah, a few things to unpack there, um, one. You mean, obviously, customs wanna make decisions on the freshest data, so they typically relied on in the past on these batch orientated tough data movement techniques, which which will be touched on there and how we're able to reduce that that time window. Let them make decisions on the freshest data where that takes, you, choose into other parts of organizations. Because, Azzawi said, already, I mean, we know that is the lifeblood of them. There was many, I would say, Typically, I t semi, but let's call it data. Seven people sitting in the both side of organizations, if not Mawr, than used to sit in the legacy I t side. They want access to this data. They want to be able to access their daily easy. And so one of these things cloud based system SAS based systems have made that a lot easier for them. And the conversations. We have a 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. We hear these digital transformation stories and data driven taglines. They get thrown out there, but what we've seen is where it's really it's been put to toss this year it is happening. Projects that would happen 9 12 months have been given to month Windows to happen because it's a matter of survival and so that's what's really driven. And then you also have the companies that benefit as well. You mean we're fortunate that we are able as a company globally, with composer of all to work from her very efficiently. But then support customers like Obvious who or providing these work from home technology systems that can enable another? The semester It's really moved. That's driven down from being purely I t driven to its CEO, CEO, CEO driven because its's what they've got to do. It z no longer just table stakes. >>I >>think the lines are great, right way we roll up into CEO and like I work for the CEO at at large detect. But we strive to be more service oriented than support. So I t was traditionally looked at as a support our 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 as more off service are connected to business problem, we understand the business problem and the challenge that they have on 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, vs, buy it. It's all about ensuring business doesn't have toe 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 thes really abstract terms and make them rial for getting answers on real time data and kind of blowing away these concepts of E t l and data transformations and how toe really put data toe work using public cloud resource sources against their real time data assets. Thank you for joining us on this installment of the Cube virtual as we cover A W s re event, make sure to check out the portal and Seymour great coverage off this exciting area off data and data analysis

(upbeat electronic music) >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are at Oracle Park in San Francisco for a really special event. It's called Sports Tech Tokyo World Demo Day, really bringing together a bunch of innovative companies in the sports tech space, really with a focus on not only sports but beyond sports. And we're happy to have really one of the key players here that made this all happen from Dentsu. He's Fumihiko Nakajima, the Senior Director of Business Development from Dentsu. Welcome. >> Hi, nice to meet you. >> Yeah absolutely. So for people that aren't familiar with Dentsu, give us a little overview of Dentsu as a company and then we'll get into the specific event. >> Yeah, Dentsu has a long history focusing on broadcasting rights and sponsorship for event globally. But combining such kind of global asset and new technology to create a new business in sports tech industry and beyond sports industry. >> Right. So pretty interesting way to do that, so you didn't just go find some interesting companies, you guys have created this event to bring a lot of companies together, demonstrate their technology. What was kind of the thinking and how did you guys get involved? >> Yeah. Combining the new asset and technologies and global asset, there are lot of the Japanese company global brand, SoftBank, ITOCHU, Sony Music, Microsoft, and CBC. Such kind of companies very interested in, create new business with innovative staff all over the world. So that's a basis of this event. >> Right, right. So, you got the Tokyo Olympics coming up in a year, so that's kind of a catalyst to make all this happen. Is there anything special that you see between, you know, kind of sports technology and managing teams, sports technology applied to the athletes, and then sports technology applied to the fan experience that you're most excited about? >> Yeah, that's correct. This is a beginning. Next month world Rugby World Cup, the next year, Tokyo Olympic and Paralympic we have. That's a beginning, so, you know the, the sports and live entertainment beyond live entertainment, health cares, biometrics, bio mechanics, from the point of sports. But we enter into the new field and explore the new business field. >> Jeff: Right. >> With the great start-ups and industry leaders on the basis, that who joining these communities. >> Right, right. No, it's pretty interesting because you know the, companies spend so much money now on the players and really look at them as investments. A lot of players get hundred million dollar contracts now. So it's pretty interesting on kind of the health care and the like we talked earlier, sleep and nutrition-- >> Yeah. >> And all these things to keep that athlete performing, are really applicable to everyday people like you and me. >> Yeah. You know that Dentsu has more than one century history in marketing and branding all over the world. And our assets, such kind, properties and, global network, will really help the new technologies and new start up, the new business field. >> Jeff: Right. >> Grow rapidly. >> Jeff: Right. >> All over the world. >> Right. It's interesting, too, that so much of the stuff around the sports, you talked about sponsorship and rights beyond just the score, you know, is so important these days. To feed the 24/7 news cycle, to do fantasy sports, the changes in the gambling law, so there's so much stuff around sports that's beyond the sport that's watched in this industry grow and grow and grow. >> Yeah it's a very interesting point. We know new, legal we will need, a new legal and a new set-up structure for the new business. >> Jeff: Right. >> In specific Tokyo, a lot of specialist joined to help such kind of structures for the futures. >> Right. So before I let you go, it's a busy day, have you been to this park before, home of the Giants, and what do you think? >> Yeah very, very, very special day. It will be very memorable day that one of the best historic venue in America, the San Francisco Giants stadium, Oracle Park. We really excited to share our progress, concrete progress, and want to expand our trial to all over the world. >> Great, well thanks for inviting us and we're, we're excited to watch the story unfold. >> Yeah, thank you. >> Alright. He's Fumihiko, I'm Jeff, you're watchin' theCUBE. We're at Oracle Park in San Francisco, thanks for watching. (upbeat music)

>> From Mountain View, California, it's theCUBE covering the 15th annual Grow Awards. Brought to you by ACG SV. >> Hey, Lisa Martin, on the ground with theCUBE at the 15th annual ACG SV Grow Awards, Association for Corporate Growth Silicon Valley, is what that stands for. Can you hear the energy and the innovation going on back here? It's amazing tonight. I'm very pleased to welcome to theCUBE, one of tonight's winners from Arista Technologies Kenneth Duda, the CTO, SVP of software engineering, and one of the founders of Arista Technologies. Kenneth, thank you so much and congratulations! >> Thank you so much, we're honored by the award. >> Well, it's been amazing. Outstanding Growth Award winner, congratulations. I was just looking at some of the recent earnings from Arista, nice Q4 earnings from FY-18. >> Thank you. >> Above the guidance, stock price rising this year. Last month Goldman Sachs added Arista to its conviction buy list. You guys are on nice trajectory, tell me about that. >> Well, it's just been a fantastic journey, you just don't get this many chances to participate in something like Arista from the ground up. Our growth has been driven in no small part thanks to the incredible growth of cloud computing. Cloud computing is changing the world and the cloud data centers need a different kind of network infrastructure. They need something that scales, meet their needs, and is customizable to integrate with all of their management systems, automation, and we've been able to provide that and be part of that journey, it's been incredibly gratifying. >> So you specifically talk with customers a lot, I was reading about one of your recent big wins in Canada, CBC Radio Canada facility in Montreal, but talk to me about what's some of the things now that you're hearing from customers especially those customers who are still in the process of transforming and transitioning workloads to the cloud. What are some of the things that surprise you about where customers are in any industry in this journey. >> Right, well, so I spend most of my time talking to the enterprise customers because there are so many of them and what we've learned there is a couple of things. One is they are very impacted by cloud. Cloud's a big deal, they're moving somewhere closer to the cloud, they're also building their own internal environments in a more cloud-like fashion and, as such, benefit from Arista's approach. But the most interesting thing I've learned is that neither of those is the most important thing. The most important thing is the network has got to work and it might sound strange, but networking gear isn't always reliable and what we've been able to achieve through our architectural approach and through our focus on automated testing has enabled us to produce a higher quality product which has been a major attractor of the enterprise customer. So you need to cover all those bases to succeed in this business. >> You're right, that network is absolutely essential. When anything goes down, whether it's a Facebook outage, it's world news. Tell me, what is the Arista advantage? >> The key advantage is the quality of our products. It's the fact that we have built an architecture that is more resilient to software and hardware errors. It's the way we test. We've made a tremendous investment in automated testing, so that our product has gone through hundreds of thousands of tests before it ever sees a customer. But actually the most important element behind quality, is the culture of your company, what do you believe? What's important to you? What gets you up in the morning? What are you thinking about and talking about to your employees? What's the most important thing, is it profitability? Is it making a deal, is it hitting a schedule? Or is it making sure the network works? We are 100% focused on that and it's been really gratifying to see the impact that's had. >> So last question, and thank you for speaking over the drum noise going on behind us, by the way, to get people into the auditorium. In terms of culture and the impact, what do you think this award means to your peers, your teams at Arista? >> Oh, it's just such an affirmation of the journey we've come through so far and the journey we still have ahead of us. We're very grateful for the award. >> So, I see so much momentum coming into 2019. What are some of the exciting things we can expect from Arista this year that you might be able to share with us? >> I think we're seeing a real transition from network designers focusing on the control plane of their network first to focusing on the management of the network first because management is actually the key to smooth operations. Our cloud vision product addresses that need. We're really excited about that transformation. >> Well, Kenneth, again, congratulations to Arista and yourself and your teams on the Outstanding Growth Award from ACG SV. We also thank you for spending some time with us on theCUBE. >> Thank you very much, it was my pleasure. >> I'm Lisa Martin and you're watching theCUBE. (energetic music)

>> Announcer: Live from Las Vegas, it's The Cube, covering Interconnect 2017, brought to you by IBM. >> Okay, welcome back everyone. Here, live in Las Vegas for IBM Interconnect 2017, this is SiliconANGLE's The Cube's coverage. Three days, a lot of great interviews, more in day two here. I'm John Furrier, my co-host Dave Vellante, our next guest is Tanya Seajay, founder and CEO of Orenda Software Solutions. Welcome to The Cube. >> Thank you so much. >> So, your company does a lot of cool things with data. One of the things, obviously, in the news, you can't read a story these days without hearing something about Trump, Uber, bad behavior. >> Dave: Fake news. >> Fake news, there's always scandal. It's the internet, for crying out loud. Everything's going on, but reputation now is measurable and data is out there and companies now as they go on to digital as a medium end to end for marketing and engaging customers, they got to be careful. What's your take? What's going on in this marketplace? >> There's a couple of things that are happening simultaneously. One is, we talked about this just briefly, the Edelman Trust Barometer. It's a global survey that's done every year, and it started I believe in 2010. In 2017, the findings were that we are in a trust crisis globally, and you would have heard that from Marc with Salesforce today. That's what he was referencing. At the same time, PricewaterhouseCooper came out with another survey across North America, and it was that we are in the midst of a trust economy and trust is growing. So, at one point, we used to make our buying decisions on whether or not a product was convenient or a good sale price, those kinds of things. Now, we want to know whether or not we trust the brand, whether or not we trust the CEO, and whether or not the companies have purpose. So, our buying decisions are changing, so not only are we in a trust crisis but we are also a trust economy. So, measuring trust is exceptionally important and a value to all brands globally. >> This purpose thing is interesting. We've been seeing the same thing, and we just had South by Southwest, Intel. We were headlining the Intel AI Lounge, and they had this program, AI for Social Good, which has got a great program. It's on our YouTube channel, youtube.com/siliconangle, folks that are watching, but there's a counterculture going on right now, we're seeing in this world. The younger audience is coming in, the new generation, the digital natives. They're living in a digital world 100%, so there seems to be a counterculture of anti-what it was, pre-now, internet, what it was before, trolling, all this stuff's been around for a while. But you're starting to see people really focus in on good and mission purpose. There's an element where there's a new generation saying, we want to apply tech for good, and you're seeing it with equality, they mentioned a lot of things on the stage today. But beyond that, it's kind of this post-9/11 generation where, like, hey what are you, all you old people bickering about? Just do social good. I mean, do you seeing that too? We're seeing a lot of it across the board. Can you share any stories in this area? >> Yeah, social good is really important in terms of giving back to your community, and in the communities where you do business, you want to have that connection. So, when we were creating Orenda, the software that measures trust, it also measures a few other things. We went back into about 30 years of research in social science and selected, there are six key factors to a healthy relationship, and what we were calling corporate social responsibility is now just more or less social good. So, you want to do things that are good to the communities that you do business in, and there's also the exchange of benefits. I do something for you, you do something for me, which brings in the more collaborative systems and partnership ecosystems that exist. >> It's a community model, too. With open source growing, connected internet, everyone's connected to each other. That's a community framework. >> That's right. >> And that's kind of the, seems to be the trend. >> It is a trend, and at one point, companies used to market to their customers. Now, you see something quite different. Customers are empowered and they're engaging through content so the exchange is continuous. One of the examples we have is with Apple. So, every time your heart beats, someone is talking about Apple. It is so huge. >> The velocity, you mean the velocity. >> Yeah, just the velocity. There's so much information coming out. We were following 25 different companies in December, and we pulled in five million data points. So, that's the amount of information that is coming at us and at brands at any particular time. What we need to do was turn that into insights in real time. If not, it's useless. >> It's interesting you mention Apple. So, we have a data science group within SiliconANGLE, The Cube. We call it our cognitive beta program. We haven't released it yet, but we're looking at all the Twitter data and we can actually see all the tweets. And then, we can extrapolate the users and obviously get all the data, which phone they're using, tweeting from. And that came out, you saw Trump was on an Android, an iPhone. And here at this show, based on the data that we have, 76% of this audience, here and online, is iPhone over Android. So, you say, okay, big deal, ho-hum. Actually, demographically, it matters. Now, some shows, the more geeky shows, you'll see Android over iPhone, so it's a small little data point. But you can almost, like that movie Contact, where you open up one door, you can get all those different insights. So, a small data point like that could add to other data. >> It could, and it's unlocking it, like you said, that is the most important part. You can get all this data. You can get it continuously. But unlocking it and telling everybody what it means to them, and it can mean something different depending on what kind of solution or problem that you're trying to overcome. But yeah. >> Yeah, and the other concepts we follow a lot in the big data world is data at rest and data in motion. And Dave and I were just at breakfast this morning, talking about content and motion brands and motion. So, your company really is measuring the brand in motion, right? >> That's right. >> So, this is kind of a cool new cutting edge coolness. >> It's really cool. >> Explain what's going on there. What's the cutting edge tech? What are some stories? Good, bad, and the ugly? >> One of the interesting things that we just did is we were following five of the biggest banks in Canada, and at the same time, CBC, which is the national broadcasting company, did this go public article and it was extremely negative. And we were tracking them, so we were able to show in real time the trust levels dropping. And in correlation to that, we looked at the stock prices of those companies, and they were also dropping. So, to be able to demonstrate that the brand itself, the reputation, particularly trust, was what the issue was, and that makes a lot of sense. It's money, it's banks, it's trust. That's what's going to be impacted the most. But being able to correlate that, it's a piece of information that we haven't been able to use before. >> So, that's insight. So now, the actionable insight is, wow we should send someone in there digitally, parachute into the virtual news cycle, and provide content or perspective. I'm saying, they can get in, stop that bleeding. >> Get in and stop the bleeding. And the other thing is that they were five national banks, but only one of them was taking the hit for it. They were the actual face of the issue. So, to be able to say, we're all being hit by this particular news story, yes, but you're being hit the most. >> It's a classic public relations problem. If you don't react, then it gets settled in, it becomes a matter of fact. >> Yeah, so you need to be able to deal with that escalation in real time. >> So, what do you guys do that's different than, a lot of sentiment analysis and it's kind of an overcrowded space. >> Tanya: It's a busy space, yeah. >> What's unique in what you guys do? >> What's unique is the actual social science on top of that. So, there is positive, negative, which gives you a little bit of information. What we did is just put on a whole other filter, and we use social science to do that. So, in order to show the brand momentum that needs to exist for a more resilient company, we said we need to know whether or not trust is increasing or decreasing, commitment with the brand or loyalty to the brand is increasing or decreasing. This is really important information. Positive, negative just doesn't tell you enough. So, when you are doing your messaging from a public relations point, you know to talk about integrity if there's a trust issue that you're dealing with. If it's satisfaction, then it's something that you want to do better in terms of a particular product. So, you get to focus on what the actual problem is, so that's how we're absolutely unique, is that we're able to measure emotion in a very different way, through social science and key factors that need to exist for a healthy brand. >> And the secret sauce behind the tech is what? Is it some cognitive, it's data science? >> We do a couple of things. So, one of the reasons why we partnered with IBM and are using Watson, the APIs, is that we built our own algorithms and we have it interact with a huge dictionary of words that we use. And we had to be able to customize that because the way we use language is always different. The way we talk about oil gas is different than we would talk about Coca-Cola, say. So, we had to be able to customize the dictionary so that if we use the word recall with a car manufacturer, that's extremely negative. But recall within the healthcare system is probably neutral. So, we had to be able to make those differences. So then, we also use AI. We use the Personality Insights tool within Watson, so we can take a whole customer buying group, look at them as an individual's huge amounts of data, millions and millions of data points, and say this is what this particular customer group or stakeholder group, this is what they need as a group, this is what they value, these are their key personalities. So again, you just get that deeper insight into who's buying your product. >> And the data sources? Talk about where the data comes from. >> The data comes from social media, and why that's really important is because within public relations and communications, there's always been focus groups, right, where you try to pull out insights into our brand from focus groups or surveys. >> Weeks and weeks and weeks of research. >> Right? Weeks and weeks of research. And you still have just a certain amount of data that you get to deal with. This, we treat social media as a huge focus group with tremendous amounts of data, tremendous amounts of insights, and we can pull it out in real time. So, if there's an issue that is escalating, we can say this is what your customer base is saying about you, this is how the impact is. We don't have to go through months of research to deal with an issue we need to deal with within 10 minutes, usually. >> So, Twitter's obviously a huge source of data, is that correct? >> Twitter's huge. >> 'Cause it's so real time and there's so much of it. What other sources? Is that the primary or a primary source? >> Facebook is interesting. You can get public information, but you can't private. Instagram is another. Blogs are a great source of information as well. Almost any online information where there's engagement, so there's a conversation that's taking place. If it's static, it doesn't, it doesn't really have an impact on you, right? >> Is there third party data sources that you use that other people use as well? Is it Twitter Firehose? Is it RSS feeds? Is there like a syndicate of data sources? >> We use GNIP, so that's owned by Twitter. Yeah, that's what we use. >> But for blogs, how do they get the blogs? >> You scrape them. >> So you scrape them. So RSS feeds and. >> Yeah, and I really enjoy the fact that a lot of governments are going into open source data, so the more we get, the better it is. We have a couple of relationships, partnerships with national media sources as well, so we're able to use that and go back into time, thankfully, from their end. >> Tanya, what's the coolest or weirdest discovery you've made with the data? Because as you get all this gesture data, I'm sure there's some things that just, whoa. >> One of the funnest for me, I'm a bit of a political nerd, and so I really, really enjoy politics. And when we were building out Orenda, we used the federal election in Canada, and yes we did do some with the US election too, but it was so much data, it was. (John and Dave laugh) >> John: Big tsunami. >> Yeah, thanks a lot, John. >> It's not stopping by the way either. It's continuing to go on. >> But yeah, the funniest moment, that one, just as an aside, was the whole, would you rather have Trump or a mozza stick as president, which was, really gained popularity. But for the federal election, what we did was follow the four federal candidates, and we were able to show when we stopped as a nation talking about Thomas Mulcair as the next leader and when we started talking about Justin Trudeau. And we were able to predict that Justin Trudeau's brand was building momentum, weeks before the polls came out and said that the machine changed. >> This year's contender. Alright. Well, Tanya, thanks so much for coming on The Cube. Really appreciate it. I love what you guys do. I think that's, you're on the cutting edge of really compelling social science, and as the culture deals with autonomous driving cars and smart cities, I think this is going to be an ongoing field of study of understanding the relationship between data and humans with respect to societal changes. So, again, this is I think one small use case of really an exploding area. So, thanks for sharing. It's The Cube here live in Las Vegas. For more Interconnect coverage, after this short break, I'm John Furrier with Dave Vellante. We'll be right back. Stay with us.