>> Live from New York, it's theCUBE covering theCUBE New York City 2018. Brought to you by SiliconANGLE Media and its ecosystem partners. (techy music) >> Hey, welcome back, everyone. It's theCUBE live in New York City for CUBENYC, formerly Big Data NYC. Now it's turned from big data into a much broader conversation. CUBENYC is exploring all these around data, data intelligence, cloud computing, devops, application developers, data centers, the whole range, all things data. I'm John Furrier here with Peter Burris, cohost and analyst here on the session. Our next guest is Byron Banks, who's the vice president of product marketing at SAP Analytics. No stranger to enterprise analytics. Welcome to theCUBE, thanks for joining us. >> Thank you for having us. >> So, SAP is, you know, a brand that's been doing business analytics for a long, long time, certainly powering-- >> Mm-hm, sure. >> The software for larger enterprises. Supply chain, you name it-- >> Sure. >> ERP, everyone kind of knows the history of SAP, but you guys really have been involved in analytics. HANA's been tailor-made for some speed. We've been covering that, but now as the world turns into a cloud native-- >> Mm-hm. >> SAP has a global cloud platform that is multi-cloud driven you guys kind of see this picture of a horizontally scalable computing environment. Analytics is a big, big piece of that, so what's going on with machine learning and AI, and as analytical software and infrastructure need to be provisioned dynamically. >> Sure, sure. >> This is an opportunity for people who love to get into the data. >> Absolutely. >> This is a great opportunity. What's the uptake? >> Great opportunity for us. We firmly believe that the era of optimization and digitization is over. It's not enough, it's certainly important. It has given a lot of benefits, but just overwhelming every user, every customer with more data, more optimization, faster data, better data, it's not enough. So, we believe that the concept to switch to intelligence, so how do you make customers, how do you serve customers exactly what they need in the moment? How do you give them an offer that is relevant? Not spam them, give them a great offer. How do you motivate your employees to be the best at what they do, whether it's in HR or whether it's in sales, and we think technology's key to that, but at the end of the day, the customer, the organization is the driver. They are the driver, they know their business best, so what we want to do is be the pit crew, if you will, to use a racing analogy, if they're the driver of the race car we want to bring the technology to them with some best practices and advice, because again, we're SAP, we've been in the business for 45 years, so we have a very good perspective of what works based on the companies we see, and serve over 300,000 of them, but it's really enabling them to be their best, and the customers that are doing the best, we call those intelligent enterprises, and that means three components. It needs intelligent applications, what we call the intelligent suite. So, how do we make an HR application that is great at retaining the best employees and also attracting great ones? How do we enable a sales system to give the best offers and do the best forecasts? So, all of that is the intelligent applications. The middle layer for that is called intelligent technologies. So, how do we use these great technologies that we've been developing as an industry over the last three to five years? Things like big data, IoT, sensors, machine learning, and analytics. That intelligent technology layer, how do we make that available, and then finally, it's the digital core, the digital platform for that. So, how do we have this scalable platform, ideally in the cloud, that can pull data from both cloud sources, SAP sources, non-SAP sources, and give the right data to those applications-- >> Yeah. >> And technologies in realtime. >> I love the pit crew example of the race car on the track, because you want to get as much data in the system as possible because more data is, you know, more opportunities to understand and get insights, but at the end of the day, you want to make sure that the car not only runs well on the track, (chuckles) and is cost effective, but it's performing. It actually wins the race or stays in the race. So, customers want revenue, I mean, the big thing we're hearing is, "Okay, let's get some top line benefit, not just "good cost effectiveness." >> Right, right. >> So, the objective of the customer, and whatever, that can be applications, it could be, you know, insight into operational efficiency. The revenue piece of growth is a big part of the growth strategy-- >> Right. >> For companies to have a data-centric system. >> Absolutely. >> This is part of the intelligence. >> But it's not just presenting the data. We introduced a product a couple of years ago, and I promise this isn't going to be a marketing pitch, (chuckles) but I think it's very relevant to what you just said. So, the SAP Analytics Cloud, that's one of those technologies I talked about, intelligent technologies. So, it is modern, built from the ground for SAS applications, cloud-based, built on the SAP cloud platform, and it has three major components. It has planning, so what are my KPIs? If I'm in HR am I recruiting talent or am I retraining talent? What are my KPIs if I'm in sales? Am I trying to drive profitability or am I trying to track new customers? And if I'm in, you know, again, in marketing how effective are we on campaigns? Tied to that is all the data visualization we can do so that we can mix and match data to discover new insights about our business, make it very, very easy, again, to connect with both SAP and non-SAP sources, and then provide the machine learning capabilities. All of that predictive capability, so not just looking at what happened in the past, I'm also looking at what's likely to happen in the next week, and the key point to all of that is when you open the application and start, the first thing it asks you is, "What are you trying to do? "What is the business problem you're trying to solve?" It's a story, so it's designed from the get-go to be very business outcome focused, not just show you 50 different data sources or 100 different data sources and then leave it to you to figure out what you should be doing. >> Yeah. >> So, it is designed to be very much a business outcome driven environment, so that, again, people like me, a marketer, can logon to that product and immediately start to work in campaigns-- >> Yeah. >> And in the language that I want to work in, not in IT speak or geek speak. Nothing wrong with geek speak, but again-- >> Yeah, I want to get into a conversation, because one of the things, we're very data driven as a media company because we have data that's out there, consumption data, but some platforms don't have measurement capability, like LinkedIn doesn't finance any analytics. >> Sure. >> So, this data that's out there that I need, I want, that might be available down the road, but not today, so I want to get to that conversation around, okay, you can measure what you're looking at, so everything that's measurable you've got dashboards for, but-- >> Sure. >> There's some elusive gaps between what's available that could help the data model. These are future data sets, or things that aren't yet instrumented properly. >> Correct. >> As new technology comes in with cloud native the need for instrumentation's critical. How do you guys think about that from a product standpoint, because you know, customers aren't going to say, "Well, create a magic linkage between something "that doesn't exist yet," but soon data will be existing. You know, for instance, network effect or other things that might be important for people that aren't yet measurable but might be in the future. >> Sure. >> They want to be set up for that, they don't want to foreclose that. >> Sure, well and I think one of the balances we have as SAP, because we're a technology company and we built a lot of great tools, but we also work a lot with our customers around business processes, so as I said, when we introduce our products we don't want to give them just a black box, which is a bunch of feeds and speeds technologies-- >> Yeah. >> That they need to figure it out. As we see patterns in our customers, we build an end-to-end process that is analytics driven and we provide that back to our customers to give them a headstart, but we have to have all of the capabilities in our solutions that allow them to build and extend in any way possible, because again, at the end of the day, they have a very unique business, but we want to give them a jumping off point so that they're not just staring at a blank screen. It's kind of like writing a speech. You don't want to start with just a blank screen. If you're in sales and marketing and you want to do a sales forecast, we will provide out-of-the-box, what we call embedded analytics, a fully complete dashboard that will take them through a guided workflow that says, "Hey, you want to do a sales forecast. "Here's the data we think you want to pull, "do you want to pull that? "Here's some additional inference we've seen "from some of our machine learning algorithms "based on what has happened in the last six weeks "of selling and make a projection as to what "we expect will happen between now and next quarter." >> You get people started quickly, that's the whole goal. Get people started quickly. >> Exactly, but we don't lock them into only doing it the one way, the right way. We're not preaching >> Yeah. >> We want to give them the flexibility. >> But this is an important point, because every, almost every decision at some point in time comes back to finance. >> Sure. >> And so, being able to extend your ability to learn something about data and act on data as measurements improve, you still want to be able to bring it back to what it means from a return standpoint, and that requires some agreement, not just some, a lot of agreement-- >> Sure. >> With a core financial system, and I think that this could be one of the big opportunities that you guys have, is because knowing a lot about how the data works, where it is, sustaining that so that the transactional integrity remains the same but you can review it through a lot of different analytics systems-- >> Right. >> Is a crucial element of this, would you agree? >> I fully agree, and I think if you look at the analytics cloud that I talked about, the very first solution capability we built into it was planning. What are my KPIs that I'm trying to measure? Now, yes, of course if you're in a business it all turns into dollars or euros at the end of the end of the day, but customer satisfaction, employee engagement, all of those things are incredibly important, so I do believe there is a way to put measurements, not always at a dollar value, that are important for what you're trying to do, because it will ultimately translate into dollars down the road. >> Right, and I want to get the news. You guys have some hard news here in New York this week on your analytics and the stuff you're working on. What's the hard news? >> Absolutely. Absolutely, so today we announced a bunch of updates to our analytics cloud platform. We've had it around for three or four years, thousands of customers, a lot of great innovation, and what we were doing today, what we announced today, is the update since our SAPPHIRE, our big, annual conference in June this year, so we have built a number of machine learning capabilities that, again, speak in the language of the business user, give them the tools that allow them to quickly benefit from things like correlations, things like regressions, patterns we've seen in the data to guide them through a process where they can do forecasting, retainment, recruiting, maybe even looking for bias, and unintended bias, in things like campaigns or marketing campaigns. Give them a guided approach to that, speaking in their terms, using very natural language processing, so for example, we have things like Smart Insights where you can ask questions about, "Give me the sales forecast for Japan," and you can say it, just type it that way and the analytic platform will start to construct and guide you through it, and it will build all the queries, it will give you, again, you're still in control, but it's a very guided process-- >> Yep. >> That says, "Do you want to run a forecast? "Here's how we recommend a forecast. "Here are some variables we find very, very interesting." That says, "Oh, in Japan this product sold "really well two quarters ago, "but it's not selling well this quarter." Maybe there's been a competitive action, maybe we need to look at pricing, maybe we need to retrain the sales organization. So, it's giving them information, again, in a very guided business focus, and I think that's the key thing. Like data scientists, we love them. We want to use them in a lot of places, but can't have data scientists involved in every single analytic that you're trying to do. >> Yeah. >> There are just not enough in the world. >> I mean, I love the conversation, because this exact conversation goes down the road of devops-like conversation. >> Right. >> Automation, agility, these are themes that we're talking about in cloud platforms, (chuckles) say data analytics. >> Absolutely. >> So, now you're bringing data down. Hey, we're automating things, so it could look like a Siri or voice activated construct for interaction. >> Yeah, absolutely, and in their language, again, in the language that the end user wants to speak, and it doesn't take the human out of it. It's actually making them better, right? We want to automate things and give recommendations so that you can automate things. >> Yeah. >> A great example is like invoice matching. We have customers that use, you know, spent hundreds of people, thousands of hours doing invoice matching because the address wouldn't line up or the purchase order had a transposed number in it, but using machine learning-- >> Yeah, yeah. >> Or using algorithms, we can automate all of that or go, "Hey, here's a pattern we see." >> Yeah. >> "Do you want us to automate "this matching process for you?" And customers that have-- >> Yeah. >> Implemented, they've found 70% of the transactions could be automated. >> I think you're right on, I personally believe that humans are more valuable, certainly in the media business that people think is, you know, sliding down, but humans, huge role. Now, data and automation can surface and create value that humans can curate on top of, so same with data. The human role is pretty critical in this because the synthesis is being helped by the computers, but the job's not going away, it's just shortcutting to the truth. >> And I think if you do it right machine learning can actually train the users on the job. >> Yeah. >> I think about myself and I think about unintended bias, right, and you look at a resume that you put out or a job posting, if you use the term I want somebody to lead a team, you will get a demographic profile of the people that apply to that job. If you use the term build a team, you'll get a different demographic profile, so I'm not saying one's better or the other, but me as a hiring manager, I'm not aware of that. I'm not totally on top of that, but if the tool is providing me information saying, "Hey, we've seen these keywords "in your marketing campaign," or in your recruiting, or even in your customer support and the way you speak with your customers, and it's starting to see patterns, just saying, "Hey, by the way, "we know that if you use these kinds of terms "it's more likely to get this kind of a response." That helps me become a better marketer. >> Yeah. >> Or be more appropriate in the way I engage with my customers. >> So, it assists you, it's your pit crew example, it's efficiency, all kind of betterment. >> Absolutely. >> Byron, thanks for coming on theCUBE, appreciate the time, coming to share and the insights on SAP's news and your vision on analytics. Thanks for coming on, appreciate it. It's theCUBE live in New York City for CUBENYC. I'm John Furrier with Peter Burris. Stay with us, day one continues. We're here for two days, all things data here in New York City. Stay with us, we'll be right back. (techy music)

(techy music) >> Live from Toronto, Canada, it's theCUBE covering Blockchain Futurist Conference 2018, brought to you by theCUBE. (techy music) >> Hello, everyone, and welcome back. This is the live CUBE coverage here in Toronto, Ontario here in Canada for the Untraceable Blockchain Futurist Conference. This is day two of wall-to-wall CUBE coverage. We've got great presentations going on, live content here on theCUBE as well as in the sessions, great networking, but more important all the thought leaders in the industry around the world are coming together to try to set the standards and set up a great future for cryptocurrency and blockchain in general. Our next two guests are very special guests for theCUBE and we're excited to have them on, the Honorable Wayne Caines, Minister of National Security for the government of Bermuda, and Kevin Richards, concierge on the Fintech business development manager, part of the Bermuda Business Development Agency. Thank you guys for coming on, really appreciate the time. >> Thanks very much. >> Thank you for having us. >> Why this is so important is that we heard your presentation onstage, for the folks, they can catch it online when they film it and record it, but the Bermuda opportunity has really emerged as a shining light around the world, specifically in the United States. In California, where I live, Silicon Valley, you guys are now having great progress in hosting companies and being crypto-friendly. Take a minute to explain what's happening, what's the current situation, why Bermuda, why now, what's developing? >> This has all happened over the last eight months. We were looking in November of 2017 to go in the space. In January we went to the World Economic Forum in Davos in Switzerland. When we went to Davos in Switzerland something very interesting happened. People kept coming up to us, I was like the Hound of the Baskerville, or the Pied Piper if you please, and so, so many people were coming up to us finding out more information about Bermuda. We realized that our plan that we thought we could phase in over 18 months, that it had to be accelerated. So, whilst we were at the World Economic Forum in Davos we said to people, "Listen, if you want to change the world, "if you want to help Bermuda to grow, if you're serious," this is a Thursday, "Meet us in Bermuda on the Monday morning." On the Monday morning there are 14 different people in the room. We sat in the room, we talked about what we wanted the world to be, how could Bermuda be in place, what are the needs in this industry, and by the Wednesday we had a complete and total framework, and so we split up into industries. Number one was ICOs, we wanted to look at how to regulate the ICO market. Number two, we wanted to look at digital asset exchanges or cryptocurrencies or how do we regulate security tokens and utility tokens and what do exchanges look like, how do we do exchanges in Bermuda, and then we wanted to talk about education and setting up incubators. And so, come fast forward to July, August, we have an ICO bill in place that allows us to look at setting up ICOs in Bermuda. We wanted to focus on the legal and the regulatory framework, so this is a nascent space. A number of people are concerned about the dark actors, and so we wanted to set up a jurisdiction that traded on our international reputation. Now, remember for the last 60 years reinsurance, finance, captives, hedge funds, people in the financial services market have been coming to Bermuda because that's what we do well. We were trading on the reputation of our country, and so we couldn't do anything to jeopardize that. And so, when we put in place the ICO legislation we had consultants from all over the world, people that were bastions and beasts in industry, in the ICO industry and in the crypto world came to Bermuda and helped us to develop the legislation around setting up an ICO. So, we passed the ICO legislation. The next phase was regulating cryptocurrencies, regulating digital assets, and we set up a piece of legislation called the Digital Asset Business Act, and that just regulates the digital asset space exchanges, and the last piece we wanted to do was a banking piece, and this is the last and we believe the most significant piece. We were talking to people and they were not able to open up bank accounts and they were not able to do, so we said, "Listen, "the Bermuda banking environment is very strong." Our banking partners were like, "Listen, "we love what you guys are doing, "but based on our corresponding banking relationships "we don't want to do anything to jeopardize that space," but how could we tell people to come to Bermuda, set up your company, and they can't open bank accounts? And so, we looked at, we just recently passed creating a new banking license that allows people to set up their business in Bermuda and set up banking relationships and set up bank accounts. That simply has to receive the governor's Royal Assent. As you know, Bermuda's still a British pan-territory, and financial matters have to get the okay of the Queen, and so that is in the final stages, but we're excited, we're seeing an influx, excuse me, a deluge of people coming to Bermuda to set up their companies in Bermuda. >> So, the first two pieces are in place, you have the legislation... >> Mm-hm. >> Mm-hm. >> You have the crypto piece, and now the banking's not yet, almost approved, right? >> It's there, it simply has to get the final sign-off, and we believe that it should take place within the next two weeks. So, by the time this goes to air and people see it we believe that piece will be in place. >> So, this is great news, so the historical perspective is you guys had a good reputation, you have things going on, now you added on a new piece not to compromise your existing relationships and build it on. What have you guys learned in the process, what did you discover, was it easy, was it hard, what are some of the learnings? >> What we've learnt is that KYC, know your customers, and the AML, anti-money laundering, and terrorist financing pieces, those are the critical pieces. People are looking in this space now for regulatory certainty, so when you're talking about people that are in the space that are doing ICOs of $500 million or exchanges that are becoming unicorns, a billion dollar entity in three months, they want a jurisdiction that has regulatory certainty. Not only do they want a jurisdiction with regulatory certainty, they want to open up the kimono. What has this country done in the past, what do they have to trade on? We're saying you can go to a number of countries in the world, but look at our reputation, what we're trading on, and so we wanted to create a space with regulatory certainty, and so we have a regulatory body in Bermuda called the Bermuda Monetary Authority, and they are an independent regulator that they penned the Digital Asset Business Act, and so the opportunity simply for people around the world saying, "Listen, we want to do an ICO, "we want to set up an exchange. "Where's a country that we can go to that has a solid reputation? Hold on, how many countries have law surrounding"-- >> Yeah. >> "The Digital Asset Business Act, how many ICO countries have laws. Guess what, Bermuda becomes a standout jurisdiction in that regard. >> Having a regulation signaling is really important, stability or comfort is one, but the one concern that we hear from entrepreneurs, including, you know, ourselves when we look at the market is service providers. You want to have enough service providers around the table so when I come in and domicile, say, in Bermuda you want to have the banking relationships, you want to have the fiduciary-- >> Yes. >> You want to have service providers, law firms and other people. >> Yes. >> How are you guys talking about that, is that already in place? How does that fit into the overall roadmap for your vision? >> I don't want to beat a horse (laughs) or beat a drum too much, that is what we do as a country. So, we have set up, whether it's a group of law firms and the Bermuda, excuse me, the Bermuda Monetary Authority, the Bermuda that's the register of companies that sets up the companies. We have Kevin, and Kevin will tell you about it, he leads our concierge team. So, it's one throat to choke, one person that needs, so when you come to really understand that the ease of business, a county that's business-friendly with a small country and with a small government it's about ease of reference. Kevin, tell us a little about the concierge team. >> It's like the Delaware of the glove, right? >> Absolutely. >> Come in, domicile, go and tell us how it works. >> I'll give you a little bit of background on what we do on the concierge side. So, one thing that we identified is that we want to make sure that we've got a structure and a very clearly defined roadmap for companies to follow so that process from when they first connect with the BDA in Bermuda to when they're incorporated and set up and moved to Bermuda to start running their business is a seamless process that has very clearly identifiable road marks of different criteria to get through. So, what I do as a concierge manager is I will identify who that company needs to connect with when they're on the ground in Bermuda, get those meetings set up for when they come down so that they have a very clearly mapped out day for their trip to Bermuda. So, they meet with the regulator, they meet with the government leaders, they meet with the folks who've put together legislation that, obviously you mentioned the service providers, so identifying who's the right law firm, corporate service provider, advisory firm on the ground in Bermuda, compliance company, and then making sure that depending on what that company wants to achieve out of their operation in Bermuda they've got an opportunity to connect with those partners on their first trip so that they can put that road map together for-- >> So, making it easy... >> Making it very easy to set up in Bermuda. >> So, walk me through, I want to come down, I want to do business-- >> Yeah. >> Like what I hear, what do I do? >> So, you send me an email and you say, "Listen, Wayne, we're looking at "doing an ICO launch in Bermuda. "I would like to meet with the regulator. "Can you put a couple law firms in place," in an email. I zip that over to Kevin or you go on our Fintech.bm website-- >> Yeah, I was going to say... >> Fintech.bm website, and Kevin literally organizes a meeting. So, when you come to Bermuda for your meeting you have a boardroom and all the key players will be in the boardroom. >> Got it. >> If you need somebody to pick you up at the airport, if you need a hotel, whatever you need from soup to nuts our team actually makes that available to you, so you're not running around trying to find different people to meet, everyone's there in the room. >> And the beauty of Bermuda is that, you know, the city of Hamilton's two square kilometers, so your ability to get a lot done in one day is, I think, second to nowhere else on the planet, and working with the BDA concierge team you're, you know, we connect with the client before they come down and make sure we identify what their needs are. >> The number one question I have to ask, and this is probably the most important for everyone, is do they have to wear Bermuda shorts? (laughs) >> When you come you tell us your size, you tell us what size and what color you want and we'll make sure, so the... I tell this story about the Bermuda shorts. The Bermuda shorts, Bermuda's always had to adapt and overcome. Bermuda, we have something called the Bermuda sloop and it's a sailing rig, and so we... The closest port to Bermuda is Cape Hatteras in North Carolina and we wanted to cut down the time of their voyage, so we created a sailing rig called the Bermuda rig or the Bermuda sloop. Over the years that has become the number one adopted rig on sailing boats. We've always had to adapt and become innovative. The Bermuda shorts were a way to adapt and to get through our very hot climate, and so if you look at just keep that in mind, the innovation of the Bermuda sloop and the Bermuda shorts. Now, this Fintech evolution is another step in that innovation and a way that we take what's going on in the world and adapt it to make it palatable for everyone. >> What's the brand promise for you guys when you look at when entrepreneurs out there and other major institutions, especially in the United States, again, Silicon Valley's one of the hottest issues around-- >> Yes. >> Startups for expansion, right now people are stalled, they don't know what to do, they hear Malta, they hear other things going on. What's the promise that you guys are making to the law firms and the people, entrepreneurs out there trying to establish and grow? >> The business proposition is this, you want a jurisdiction that is trading on years of solid regulation, a country and a government that understands business, how to be efficacious in business. When you come to Bermuda you are trading on a country that this is what we've done for a living. So, you don't have to worry about ethical government, is your money going to be safe. We have strong banking relationships, strong law firms, top tier law firms in Bermuda, but more importantly, we have legislation that is in place that allow you to have a secure environment with a clear regulatory framework. >> What should people look for as potentially might be gimmicks for other countries to promote that, you know, being the Delaware for the globe and domiciling, and what are some of the requirements? I mean, some have you've got to live there, you know, what are some of the things that are false promises that you hear from other potential areas that you guys see and don't have to require and put the pressure on someone? >> When you hear the people say, "We can turn your company around in the next day." That we don't require significant KYC and AML. Red flags immediately go up with the global regulatory bodies. We want when a person comes to Bermuda to know that we have set what we believe is called the Bermuda Standard. When you come to Bermuda you're going to have to jump through some legal and regulatory hoops. You can see regulation, the ICO regulation and the Digital Asset Business Act on BermudaLaws.bm. BermudaLaws.bm, and you can go through the legislation clause by clause to see if this meets your needs, how it will affect your business. It sets up clearly what the requirements are to be in Bermuda. >> What's the feedback from business, because you know, when you hear about certain things, that's why Delaware's so easy, easy to set up, source price all know how to do in a corporation, let's say in the United States-- >> We don't have the SEC handicaps that they have in America, going from jurisdiction to jurisdiction. You're dealing with a colony that allows you to be in a domicile that all of the key players finances... We have a number of the key elements that are Bermuda. We're creating a biosphere that allows a person to be in a key space, and this is, you have first move as advantage in Bermuda. We have a number of things that we're working on, like the Estonia model of e-residency, which we will call EID, that creates a space that you are in Bermuda in a space that is, it's protected, it's governed. We believe that when companies set up in Bermuda they are getting the most secure, the strongest business reputation that a country could have. >> The other thing I would add, I'll just say, you know, quality, certainty, and community is what that brand represents. So, you know, you've got that historical quality of what Bermuda brings as a business jurisdiction, you have the certainty of the regulation and that pathway to setting your company up and incorporating in Bermuda, and then the community piece is something that we've been working on to make sure that any of the players that are coming to Bermuda and connecting with Bermuda and setting up there, they feel like they're really integrated into that whole community in Bermuda, whether it be from the government side, the private sector side. You can see it with the companies that have set up that are here today, you know, they really have embraced that Bermuda culture, the Bermuda shorts, and what we're really trying to do as a jurisdiction in the tech space. >> What can I expect if I domicile in Bermuda from a company perspective, what do I have to forecast? What's the budget, what do I got to do, what's my expectation? Allocate resources, what's going to be reporting, can you just give us some color commentary? >> So, with reference, it depends what you're trying to do, and so there will be different requirements for the ICO legislation. For the ICO legislation a key piece of the document actually is the whitepaper. Within the whitepaper you will settle what your scope of business is, what do you want to do, what you know, everything, everything that you require will be settled in your whitepaper. After the whitepaper is approved and if it is indeed successful, you go to the Bermuda Monetary Authority and they will outline what they require of you, and very shortly thereafter you will able to set up and do business in Bermuda. With reference to the digital asset exchanges, the Digital Asset Business Act, such a clear guideline, so you're going to need to have a key man in Bermuda, a key woman in Bermuda. >> Yeah. >> You're going to need to have a place of presence in Bermuda, so there are normal requirements-- >> There's levels of requirements based upon the scope. >> Absolutely. >> So, if you run an exchange it has to be like ghosting there. >> Yeah, yeah, you need boots on the ground. >> And that's why the AML and the KYC piece is so important. >> Yeah. Well, I'm super excited, I think this is a great progress and this has been a big uncertainty, you know, what does this signal. People have, you know, cognitive dissonance around some-- >> Yes. >> Of the decisions they're making, and I've seen entrepreneurs flip flop between Liechtenstein, Malta, Caymans. >> Right. >> You know, so this is a real concern and you guys want to be that place. >> Not only, we will say this, Bermuda is open for business, but remember, when you see the requirements that we have some companies won't meet the standard. We're not going to alter the standard to accommodate a business that might not be what we believe is best for Bermuda, and we believe that once people see the standard, the Bermuda Standard, it'll cascade down and we believe that high tides raises all boats. >> Yeah. >> We have a global standard, and if a company meets it we will be happy for them to set up and do business in Bermuda. >> Well, I got to say, it's looking certainly that leaders like Grant Fondo in Silicon Valley and others have heard good things. >> Yeah. >> How's been the reaction for some of the folks on the East Coast, in New York and around the United States and around the world? What has been some of the commentary, what's been the anecdotal feedback that you've heard? >> We're meeting three and four companies every day of the week. Our runway is full of Fintech companies coming to Bermuda, from... We have insurtech companies that are coming in Bermuda, people are coming to Bermuda for think tanks, to set up incubators and to do exploratory meetings, and so we're seeing a huge interest in Bermuda the likes have not been seen in the last 20 years in Bermuda. >> Well, it's been a pleasure chatting with you and thanks for sharing the update and congratulations. We'll keep in touch, we're following your progress from California, we'll follow up again. The Honorable Wayne Caines, the Minister of National Security of the government of Bermuda, and Kevin Richards, concierge taking care of business, making it easy for people. >> Oh, yeah, oh, yeah. >> We'll see, I'm going to come down, give me the demo. >> We're open for business and we're looking forward to seeing everybody. (laughs) >> Thank you for the opportunity. >> Thank you very much. >> Thank you. >> Major developments happening in the blockchain, crypto space. We're starting to see formation clarity around, standards around traditional structures but not so traditional. It's not your grandfather's traditional model. This is what's great about blockchain and crypto. CUBE coverage here, I'm John Furrier, thanks for watching, stay with us. More day two coverage after this short break. (techy music)

(techy music) >> Live from Toronto, Canada, it's theCUBE covering Blockchain Futurist Conference 2018, brought to you by theCUBE. (techy music) >> Well, welcome back to theCUBE, we're live here in Toronto for the Untraceable Blockchain Futurist Conference for two days of wall-to-wall coverage. I'm John Furrier, my co-host Dave Vellante, who had to take a step away and our next guest is David Johnston, who's the chairman of the board at Factom, industry legend, he's done a lot of great work from startups, he funds it in early days, really was involved in the original decentralized application framework and part of that community. Great to have you on theCUBE, thanks for spending the time with us. >> It's good to be here. >> So, first of all we are believers, theCUBE, our team, we're pretty biased. We think that decentralized applications is going to be the next really renaissance in software and startups because it's not your grandfather's venture capital or app SAS model, there's a real change going on. Capital formation, entrepreneurial activity-- >> Yep. >> So, congratulations for putting that together. What's going on, what's the status of this? I mean, obviously put all the price crashes on the side, there's real building going on. >> Well, it's really actually an exciting time. A lot of of good projects have started the last few years and I think what we're going to see is those projects come to fruition later this year, early next. I think about what's happening with groups like PolyMath and what they're doing on tokenizing securities. It really started that wave last year, and now we've got Bank to the Future, and what's going on in Malta with the legislation. A lot of jurisdictions are looking to basically embrace that model of okay, if you have a company, now we can turn that equity into a record on the blockchain and really give people global ledger where we can then trade it on multiple exchanges. It gets you global access, global liquidity, and all of these advantages, so I see a stampede of projects headed towards that model, but thinking about decentralized applications, what I want to preserve is still the permission-less nature of this ecosystem. I mean, I wasn't a rich investor when I got into bitcoin in 2012, all right. I was lucky to be an economics nerd and already wanted to get rid of my Fiat and opt into non-government currency, and so, you know, the timing was great for me but there weren't any barriers. I could download a node-- >> Yeah. >> I could access the ecosystem, I could jump right in and get involved, and so as we see the ecosystem mature what I hope we see is preserving that permission-less nature and recently I proposed Smartdrops as a means of distributing tokens and utilities or currencies-- >> Yeah. >> As a way of bootstrapping the network. So, that's what I really see coming next. >> Love the Smartdrop concept because you know, with Smart contracts and Airdrops kind of being wishy-washy, you know what goes on there, I think one of the things I want to get your thoughts on, because we were at the cloud blockchain event yesterday. Cloud computing and cloud-native chain, SAS applications, you start to see operators now be involved in cloud as that matures, what decentralized applications bring kind of changes the game a bit. How do you see software development changing, because what cloud did was create devops culture, it certainly leverages opensource. >> Right. >> And there's a big community around that. Now with decentralized application you've got community as an active part of it, so is opensource, how is it going to change the software development frameworks? >> Well, I think you can cut out a lot of the middle steps and go directly to developers that you want to work with. I mean, I think Ethereum really still set the gold standard when they set aside a chunk of ether for developers that contributed code to their GitHub before launch, and people will forget now it was a heavy lift to get Ethereum launched. It took a good year and a half, two years, to go from a whitepaper to production net deployments and in that time they needed to align people, the smartest people in the world to try to build that platform, and so I think people can still draw from that lesson and say, "Okay, I'm going to enroll developers directly, "I'm going to reward the people that download "the alpha, download the beta," right. Bootstrap this community to my first 1,000, first 10,000 users. I think PolyMath did that really well recently with their Airdrop where they got 50,000 people into a telegram channel and fill out a survey and do the KYC because they didn't make it a rounding error, they made it a meaningful Airdrop of hundreds of dollars worth of Poly at the time, and that really motivated people to get involved, so-- >> Yeah, and I like the slogan, "Let the stampede begin." (laughs) Actually, we covered PolyMath at their PolyCon event-- >> Sure. >> That Tracy and Untraceable did, and this is, again, the new dynamic. So, I want to get your thoughts on economics, right. So, you've got crypto, which is token economics, which is a business concept when you think about a new way. Blockchain's certainly becoming an infrastructure. >> Right. >> Token economics is changing the business landscape, so you saw it as an economics nerd and now people are realizing, "Holy shit, "I can actually do things with it differently. "I can change the equation"-- >> Right. >> "And still get the outcomes I want "faster, cheaper, smarter, of something "that's not efficient," this is a new dynamic. How do you see the token economics evolving, you know, aside all the liquidity nonsense we're seeing in the market, certainly fluctuations are happening. >> Sure. >> But from a build-out standpoint, from a business model innovation, where is the action on token economics? >> Well, I loved when the Vitala coined the term token economics, and you know, crypto-economics, and basically what he was describing is we're using math to screw the past and we're aligning people's economic incentives to secure the future. So, that idea that we can rely on encryption to give us a stable, immutable, transparent ledger is really powerful because it takes away, in a cloud context, the need to create a bunch of infrastructure. Right, before the cloud people had their own servers. >> Yeah, provision them. >> Dot com days, right, they spent millions of dollars provisioning their own hardware-- >> Before they could roll out their app. >> Right, and so we take it for granted today. >> Yeah. >> You can jump on AWS or Rockspace-- >> Yeah. >> And get going in a few minutes. So, I think blockchain is going to do something similar for all the features of Smart contracts, financial integrations around transfer of money, all of these things are now a toolkit that as soon as I hook into Ethereum or Bitcoin Cash or one of these protocols I have this large, established infrastructure, thousands of people running nodes that I don't have to pay for-- >> Yeah. >> As a user, and that's amazing for innovation because it just lowers the barrier-- >> Yeah. >> For the average guy to get involved. >> And accelerates time to value big time. >> Yeah. >> All right, so what was your talk here at the show, what were you speaking about, you had a discussion, what was the speech about? >> Really focused on this idea of Smartdrops because I think, you know, this can be a primer-- >> Explain Smartdrops real quick. >> Sure, sure, so most people are probably familiar with Airdrops. >> Yep. >> Been around for years, hey, you want to give 100,000 users of bitcoin some of your new token. We're going to send it out to all their addresses. It's sort of like a spray and pray strategy, very broad, right? >> Yeah. >> And so what I think we need to move to now that we have 50 million people with cryptowallets is we can much more intelligently target who we're dropping to, hence Smartdrop. Right, really focus in on the people that the app needs. If you're at the development stage you want to develop, you want to Airdrop to 1,000 Ethereum developers-- >> Yeah. >> To test out your app, if you're going into your alpha you need those early adopters to try it out, give you feedback. So, it's a thing that I think we could leverage but people have treated it as sort of an afterthought. Right, oh, I'll take one percent of my tokens and do one of these Airdrops. I think we could actually be distributing 20%, 40%, 60% of tokens via Smartdrops if you're properly targeting them and traunching it out based on the maturity of the projects. >> Yeah, and I think Smart contracts, Smartdrops really add value because it brings intelligence-- >> Right. >> To and targeting and more value you can distribute. It's like policy-based distribution. >> Right. >> All right, final question for you, state of the union, obviously people seeing these fluctuations, Ethereum lost its one-year value, it's back down to where it was a year ago. Largest developer community, people get nervous when you have these short term fluctuations that really aren't based on anything from a build-out standpoint. >> Sure. >> It's really more of market dynamics, Asia, wherever, whatever-- >> Right. >> But this real build is in the developer community going on that are building long term, trying to build long term ventures. >> Right. >> What do you say to that community at Ethereum and others, stay the course, don't waver, don't check the price, head down, grind it, what do you say? >> What I say is think long term. We've been through this like four times already. I remember when bitcoin went from almost nothing to $30 and crashed to $2, right, and it took almost a year-- >> Yeah. >> To recover, 2012, get back to 10 bucks, and then it made it's big run 2013 to $250, and proceeded to crash to $50. >> Yeah. >> Right, and then make a big run thereafter to the thousands-- >> Yeah. >> And crash to $200, and here we've made enormous runs and $19,000, you know, on the bitcoin price and it's crashed to $6,000 or $5,000, whatever it is today, and so you got to keep in mind the long term perspective. We have come so far. >> (laughs) Yeah. >> Like when I got into bitcoin in 2012 it was $10 a bitcoin, there were 10 million bitcoins in circulation, meaning $100 million was the entire digital currency universe, and now today there are hundreds of billions of dollars-- >> Yeah. >> Of assets in this space, and it's only been five or six years. Like it's orders of magnitude, so I keep my eye on usage, on real utility. You look at Ethereum, I mean, they're doing seven, eight, 900,000 transactions a day. People are using-- >> Yeah. >> The platform and I think at this point they've got more usage than all of their blockchains combined. >> Yeah. >> And so, you know, that's really exciting and I think keep your head down, keep building, these are the times when sort of like the fluff falls away-- >> Yep. >> And the projects that didn't make sense, all that gets flushed out of the ecosystem and the real projects come to the forefront. >> Well, David you're having a great career so far. Congratulations on getting in early when it was 10 bucks, and we had our first website developer was so good but he wanted to be paid in bitcoin in 2011, it was 22 cents-- >> Wow. >> At the time, I remember buying it, it was like, "What's bitcoin, what is this craziness?" (laughs) We started covering it then, just started doing videos, so we're going to do more interviews. We'll hopefully get you on again. Real quick, final plug for you, what are you working on right now? Share with the community some of the projects and your interests right now and what's going on. >> Well, Factom is a big focus for me because this solves data on the blockchain and lets you do recordkeeping, documentation, all that sort of stuff, and so that's really hit a chord with enterprise, so we need to get the mainstream into the ecosystem and that's really what Factom is focused on. >> Yeah. >> So, really excited, they've delivered their third version of their software, which is now fully decentralized recently. >> Yeah. >> It's a huge milestone for them. >> So, harden it, make it reliable, stable, and make it easy to consume and use. >> That's right, that's the key. >> That's the goal. >> And let people put millions, billions, or trillions of records on, and what Factom does with Merkle trees, basically you only need one transaction every 10 minutes to anchor all of that data. So, what we've created is scalability, and that's what we need for this to go mainstream. >> All right, David Johnston, chairman of the board at Factom here on theCUBE, industry insider, pioneer, also leader, inspiration. theCUBE bringing you all the live action, all the data here not yet on the blockchain, soon to be. I'm John Furrier, live coverage here in Untraceable's event Futurist event here in Toronto, be back with more. Stay with us, be right back with more content after this short break. (techy music)

>> Live from San Francisco, it's theCUBE covering Google Cloud Next 2018, brought to you by Google Cloud and its ecosystem partners. (techy music) >> Hey, welcome back, everyone, this is theCUBE Live in San Francisco coverage of Google Cloud Next '18, I'm John Furrier with Jeff Frick. Day three of three days of coverage, kind of getting day three going here. Our next guest, Sudhir, as the director of product management, Google Cloud, has the luxury and great job of managing BigTable, BigQuery, I'm sorry, BigQuery, I guess BigTable, BigQuery. (laughs) Welcome back to the table, good to see you. >> Thank you. >> So, you guys had a great demo yesterday, I want to get your thoughts on that, I want to explore some of the machine learning things that you guys announced, but first I want to get perspective of the show for you guys. What's going on with you guys at the show here, what are some of the big announcements, what's happening? >> A lot of different announcements across the board, so I'm responsible for data analytics on the Google Cloud. One of our key products is Google BigQuery. Large scale, cloud scale data warehouse, a lot of customers using it for bringing all their enterprise data into the data warehouse, analyzing it at scale, you can do petabyte scale queries in seconds, so that's the kind of scale we provide. So, a lot of momentum on that, we announced a lot of things, a lot of enhancements within that. For example, one of the things we announced was we have a new experience, new UI of BigQuery, now you can literally do the query, as I was saying, of petabyte scale or something, any queries that you want, and with one click you can go into Data Studio, which is our DI tool that's available, or you can go in Sheets and then from there quickly go ahead and fire up a connector, connect to BigQuery, get the data in Sheets and do analysis. >> So, ease of use is a focus. >> Ease of use is a major focus for us. As we are growing we want to make sure everybody in the organization can get access to their data, analyze it. That was one, one of the things, which is pretty unique to BigQuery, which is there is a real time collection of information, so you can... There are customers that are actually collecting real time data from click-stream, for example, on their websites or other places, and moving it directly into BigQuery and analyzing it. Example, in-game analytics, if in-game you're actually playing games and you're going to collect those events and do real time analysis, you're going to literally put it into BigQuery at scale and do that. So, a lot of customers using BigQuery at different levels. We also announced Clustering that allows you to reduce the cost, improve efficiency, and make queries almost two X faster for us. So, a lot of announcements other than the machine learning. >> Well, the one thing I saw in the demo I thought was, I mean, it was machine learning, so that's hot topic here, obviously. >> Yes. >> Is you don't have to move the data, and this is something that we've been covering, go back to the Hadoop, back when we first started doing theCUBE, you know, data pipeline, all the complexities involved in moving the data, and at the scale and size of the data all this wrangling was going on just to get some machine learning in. >> Yep. >> So, talk about that new feature where you guys are doing it inside BigQuery. I think that's important, take a minute to explain that. >> Yeah, so when we were talking to our customers one of the biggest challenges they were facing with machine learning in general, or a couple of them were, one, every time you want to do machine learning you are to take data from your core data warehouse, like in BigQuery you have petabytes of scaled data sets, terabytes of data sets. Now, if you want to do machine learning on any portion of it you take it out of BigQuery, move it into some machine learning engine, ML engine, auto-ML, anything, then you realize, "Oh, I missed some of the data that I needed." I go back then again take the data, move it, and you have to go back and forth too much time. There are analysis I think that different organizations have done. 80% of the time the data scientists say they're spending on the moving of data-- >> Right. >> Wrangling data and all of that, so that is one big problem. The second big challenge we were hearing was skillset gap, there are just not that many PhD data scientists in the industry, how do we solve that problem? So, what we said is first problem, how do we solve it, why do people have to move data to the machine learning engines? Why can't I take the machine learning capability, move it inside where the data is, so bring the machine learning closer to data rather than data closer to machine learning. So, that's what BigQuery ML is, it's an ability to run regression-like models inside the data warehouse itself in BigQuery so that you can do that. The second we said the interface can't be complex. Our audiences already know SQL, they're already analyzing data, these folks, business analysts that are using BigQuery are the experts on the data. So, what we said is use your standard SQL, write two lines of code, create model, type of the model you want to run, give us the data, we will just run the machine learning model on the backend and you can do predictions pretty easily. So, that's what we are doing with that. >> That's awesome. >> So, Sudhir, I love to hear that you were driven by that, by your customers, because one of the things we talk about all the time is democratization. >> Yeah. >> If you want innovation you've got to democratize access to the data, and then you got to democratize access to the tools to actually do stuff with the data-- >> Yes. >> That goes way beyond just the hardcore data scientist in the organization-- >> Yeah, exactly. >> And that's really what you're trying to enable the customers to be able to do. >> Absolutely, if you look at it, if you just go on LinkedIn and search for data analyst versus data scientist there is 100 X more analysts in the industry, and our thing was how do we empower these analysts that understand the data, that are familiar with SQL, to go ahead and do data science. Now, we realize they're not going to be expert machine learning folks who understand all the intricacies of how the gradient descent works, all that, that's not their skillset, so our thing was reduce the complexity, make it very simple for them to use. The framework, like just use SQL and we take care of the internal hyper-tuning, the complexity of it, model selection. We try to do that internally within the technology, and they just get a simple interface for that. So, it's really empowering the SQL analyst with an organization to do machine learning with very little to no knowledge of machine learning. >> Right. >> Talk about the history of BigQuery, where did it come from? I mean, Google has this DNA of they do it internally for themselves-- >> Yes. >> Which is a tough customer-- >> Yes. >> In Cloud Spatter we had the product manager on for Cloud Spatter. Dip Dee, she was, like amazing, like okay, baked internally, did that have the same-- >> Yes. >> BigQuery, take a minute to talk about that, because you're now making it consumable for enterprise customers. >> Yeah. >> It's not a just, "Here's BigQuery." >> No. >> Talk about the origination, how it started, why, and how you guys use it internally. >> So, BigQuery internally is called Dremel. There's a paper on Dremel available. I think in 2012 or something we published it. Dremel has been used internally for analytics across Google. So, if you think about Spanner being used for transaction management in the company across all areas, BigQuery, or Dremel internally, is what we use for all large scale data analytics within Google. So, the whole company runs on, analyzes data with it, so our things was how do we take this capability that we are driving, and imagine like, when you have seven products that are more than a billion active users, the amount of data that gets generated, the insights we are giving in Maps and all the different places, a lot of those things are first analyzed in Dremel internally and we're making it available. So, our thing was how do we take that capability that's there internally and make it available to all enterprises. >> Right. >> As Sundhir was saying yesterday, our goal is empower all our customers to go ahead and do more. >> Right. >> And so, this is a way of taking the piece of technology that's powered Google for a while and also make it available to enterprises. >> It's tested, hardened and tested. >> Yeah, absolutely. >> It's not like it's vaporware. >> Yeah, it's not. (laughs) >> No, I mean, this is what I think is important about the show this year. If you look at it, you guys have done a really good job of taking the big guns of Google, the big stuff, and not try to just say, "We're Google and you can be like Google." You've taken it and you've kind of made it consumable. >> Yes. >> This has been a big focus, explain the mindset behind the product management. >> Absolutely, there is actually one of the key things Google is good at doing is taking what's there internally used, but also the research part of it. Actually, Corinna Cortes, who is head of our AI side who does a lot of research in SQL-based machine learning, so again, the-- >> Yeah. >> BigQuery ML is nothing new, like we internally have a research team that has been developing it for a few years. We have been using it internally for running all these models and all, and so what we were able to do it bring product management from our side, like hey, this is really a problem we are facing, moving data, skillset gap, and then we were like, research team was already enabling it and then we had an engineering team which is pretty strong. We were like, okay, let's bring all three triads together and go ahead and make sure we provide a real value to our customers with all of that we're doing, so that's how it came to light. >> So, I just want to get your take, early days like when there was the early Google search appliance, I'll just pick that up, and that was ancient, ancient ago, but one of the digs was, right, it didn't work as well in the enterprise, per se, because you just didn't have the same amount of data when you applied that type of technique to a Google flow of data and a Google flow of queries. So, how's that evolved over time, because you guys, like you said, seven applications with a billion-- >> Yep. >> Users, most enterprises don't have that, so how do they get the same type of performance if they don't have the same kind of throughput to build the models and to get that data, how's that kind of evolved? >> So, this is why I think thinking about, when we think about scale we think about scaling up and scaling down, right? We have customers who are using BigQuery with a few terabytes of data. Not every customer has petabytes scale, but what we're also noticing is these same customers, when they see value in data they collect more. I will give you a real example, Zulily, one of our customers, I used to be there before, so when they started doing real time data collection for doing real time analytics they were collecting like 50 million events a day. Within 18 months they started collecting five billion a day, 100 x improvement, and the reason is they started seeing value. They could take this real time data, analyze it, make some real time experiences possible on their website and all, with all of that they were able to go out and get real valuer for their customers, drive growth, so when customers see that kind of value they collect more data. So, what I would say is yes, a lot of customers start small, but they all have an aspiration to have lots of data, leverage that to create operational efficiency as well as growth, and so as they start doing that I think they will need infrastructure that can scale down and up all the way, and I think that's what we're focusing on, providing that. >> You guys look at the possibility, and I've seen some examples where customers are just, like, they're shell-shocked, and you're almost too good, right? I mean, it's like, "We've been doing "Dremel on a large scale, I bought this "data warehouse like 10 years ago," like what are you talking about? (laughs) I mean, there's a reality of we've been buying IT, enterprises have been buying IT and in comes Google, the gunslinger saying, "Hey, man, you can do all this stuff." There's a little bit of shell-shock factor for some IT people. Some engineering organizations get it right away. How are you guys dealing with this as you make it consumable? >> Yeah. >> There's probably a lot of education. As a product manager do you see, is that something that you think about, is that something you guys talk about? >> Yes, we do, so I think I actually see a difference in how customers, what customers need, enterprise customers versus cloud native companies. As you said, cloud native companies starting new, starting fresh, so it's a very different set of requirement. Enterprise customers, thinking about scale, thinking about security and how do you do that. So, BigQuery is a highly secure data warehouse. The other thing BigQuery has is it's a completely serverless platform, so we take care of the security. We encrypt all the data at rest and when it's moving. The key thing is when we share what is possible and how easy it is to manage and how fast people can start analyzing, you can bring the data. Like you can actually get started with BigQuery in minutes, like you just bring your data in and start analyzing it. You don't have to worry about how many machines do I need, how do I provision it, how many servers do I need. >> Yeah. >> So, enterprises, when they look at-- >> Cloud native ready. >> Yeah. >> All right, so take a minute to explain BigTable versus, I mean, BigTable versus BigQuery. >> Yes. >> What's the difference between the two, one's a data warehouse and the other one is a system for managing data? What's the difference between Big-- >> So, it's a no-SQL system, so I will... The simple example, I will give you a real example how customers use it, right. BigQuery is great for large scale analytics, people who want to take, like, petabyte scale data or terabyte scale data and analyze historical patterns, all of that, and do complex analysis. You want to do machine learning model creation, you can do that. What BigTable is great at is once you have pre-aggregated data you want to go ahead and really fast serving. If you have a website, I don't expect you to run a website and back it with BigQuery, it's not built for that. Whereas BigTable is exactly for that scenario, so for example, you have millions of people coming on the website, they want to see some key metrics that have been pre-created ready to go, you go to BigTable and that can actually do high performance, high throughput. Last statement on that, like almost 10,000-- >> Yeah. >> Requests per second per node and you can just create as many as you want, so you can really create high scale-- >> Auto-scaling, all kinds of stuff there. >> Exactly. >> And that's good for unstructured data as well-- >> Exactly. >> And managing it. >> Absolutely. >> Okay, so structured data, SQL, basically large scale-- >> Yes. >> BigTable for real time-- >> Yes. >> New kinds of datas, different data types. >> Absolutely, yes. >> What else do you have in the bag of goodies in there that you're working on? >> The one big thing that we also announced with this week was a GIS capability within BigQuery. GIS is geographical information, like everything today is location-based, latitude, longitude. Our customers were telling us really difficult to analyze it, right, like I want to know... Example would be we are here, I want to know how many food restaurants are in a two-mile radius of here, which ones are those, how many, should we create the next one here or not. Those kind of analyses are really difficult, so we partnered with Earth Engine, Earth Engine team within Google with Maps, and then what we're launching is ability to do geospatial analysis within BigQuery. Additionally along with that we also have a visualization tool that we launched this week, so folks who haven't seen that should go check that out. One great example I will give you is Geotab, their CEO is here, Neil. He was showing a demo in one of the sessions and he was talking about how he was able to transform his business. I'll give you an example, Geotab is basically into vehicle tracking, so they have these sensors that track different things with vehicles, and then with, and they store everything in BigQuery, collect all of that and all, and his thing was with BigQuery ML and a GIS capability, what he's now able to do is create models that can predict what intersections in a city when it's snowing are going to be dangerous, and for smart cities he can now recommend to cities where and how to invest in these kind of scenarios. Completely transforming his business because his business is not smart cities, his business was vehicle tracking and all, he's like, but with these capabilities they're transforming what they were doing and solving-- >> New discoveries. >> New discoveries, solving new problems, it's amazing. I wonder if you could just dig at a little bit to, you know, the fact that you've got this, these seven billion activities or apps that you can leverage, you know, specific functionality or goals or objectives or priorities in those groups, and now apply those, pull that data, pull that knowledge, pull those use cases into a completely different application on the enterprise. I mean, is that an active process-- >> I don't think that's how people. >> Do people query? >> No, no. >> But how does that happen? >> No, we don't-- >> As a customer. >> As a customer completely different, right? Our focus in Google Cloud is primarily enabling enterprises to collect their data, process their data, innovate on their data. We don't bring in, like, the Google side of it at all, like that's their completely different area that way, so we basically, enterprises, all their data stays within their environment. They basically, we don't touch it, we don't get to access it at all, and they can know it. >> Yeah, yeah, no, I didn't mean that, I meant, you know, like say Maps for instance, it's interesting to see how Maps has evolved over all these years. Every time you open it, oh, and it's directions-- >> Yep. >> Oh, now it's better directions, oh, now it's got gas stations, oh, now it's where the... And it triggered because you said the restaurants that are close by, so it's kind of adding value to the core app on that side, and as you just said, now geolocation can be used on the enterprise side-- >> Yeah, yes. >> And lots of different things, so that-- >> Exactly. >> That's where I meant that kind of connection-- >> Exactly right, so-- >> In terms of the value of what can I do with geolocation. >> Absolutely, exactly, so like, that's exactly what we did. With Earth Engine we had a lot of learnings on geospatial analysis and our thing was how do you make it easy for our enterprise customers to do that. We've partnered with them closely and we said, "Okay, here are the core pieces of things "we can add in BigQuery that will allow you "to do better geospatial analysis, visualize it." One of the big challenges is lat longs, I don't think they're that friendly with analysts, like oh, numbers and all that. So, we actually will turn a UI visualization tool that allows you to just fire a query and see visually on a map where things are, all the points look like and all. >> Awesome. >> So, just simplifying what analysts can do with all these. >> Sudhir, thanks for coming on, really appreciate it and congratulations on your success. Got a lot of great, big products there, hardened internally, now-- >> Yes. >> Making consumable, it's clear here at Google Cloud you guys are recognized that making it consumable-- >> Yep. >> Pre-existing, proven technologies, so I want to give you guys props for that, congratulations. >> Thank you, thanks a lot. >> Thanks for coming on the show. >> Thanks for coming on. >> Thank you. >> It's theCUBE coverage here, Google Cloud coverage, Google Next 2018. I'm John Furrier with Jeff Frick, stay with us, we've got all day with more coverage for day three. Stay with us after this short break. (techy music)

>> Live from San Francisco, it's theCUBE covering Google Cloud Next 2018, brought to you by Google Cloud and its ecosystem partners. (techy music) >> Hello everyone, welcome back to theCUBE's live coverage here. We're in San Francisco for Google Cloud's major conference, Next 2018. I'm John Furrier, here for three days. Wall to wall coverage on day one. We've got two great guests from SignalFX, Karthik Rau, founder and CEO, and Rajesh Raman, who's the chief architect. Signal's a hot startup in the area. Way ahead of its time, but now as the world gets more advanced, the solution is front and center as the value proposition if cloud moves into the mainstream, devops going to a world at large scale. Not just networking, monitoring, applications, you've got service meshes booming, great topic. Karthik, great to see you, Rajesh, thanks for joining us. >> Thank you. >> John, great to be on. >> So, first of all let's just get it out of the way, you guys have some fresh funding in May, so just quickly give an update on the company. You guys raised-- >> Yeah >> A series... >> A series D. >> Series D, give us, but how much? >> Yeah, so we raised $45 million from General Catalyst leading the round back in May, been building a ton of momentum as a company, close to a couple hundred people today. We're using a lot of that to expand internationally. We've got a team in Europe now, just opened up a team in Australia. So, things have been going great. >> Congratulations, we've had chats before, always been impressed. You guys have a great stable of awesome engineers and talent in the company doing some great work, but it begs the question, I always like to get into the what ifs. What if I could have large scale application development environments with programmable infrastructure, how does that change things? So, Karthik, what's... How as that what if changes, now that is what's happening you're starting to see the cloud at scale for the common masses of enterprises, where old ways of doing things are kind of moving away. It's like horse and buggy versus having a car for the first time-- >> Yeah. >> Jobs are changing, but the value doesn't necessarily change. You still go from point A to point B, you still got an engine, people who care about fixing cars, so people just want to drive the cloud, some people want to get under the hood, whole new architecture. >> Yeah. >> What's the what if of if I could have all these resources, what's the challenges and what do you guys solve. >> Well, I think there are a couple of challenges in this new environment. One is the number of components are just orders of magnitude more than they used to be in a cloud environment, right? We went from having physical machines that live for three years in a data center, divide it up into VMs 10 years ago, now divided up into containers for every process. Not only that, but these containers get spun up and spun down every few minutes or every few hours, and so it's just the number of components in the churn is just massive. So, that in and of itself requires a far more analytics-based approach to understand patterns rather than what's happening on an individual component. The second thing that's changed is the operating model's fundamentally different, because now you're building and running web services, and when you're running web services the people who build the software are the ones who technically are responsible for operating it. And so, you know, you have more updates, you've got more people involved, you've got lots of different components that all need to interact with one another, and so having a communication framework across all of these disparate teams become really, really, really critical. So, those are the two fundamental changes as you move from, you know, for operating these modern, massively distributed-- >> Yes. >> Applications. >> And I'll just add just some observation data that we've seeing in theCUBE is those same folks building aren't necessarily operators, so they want to be in and out fast, right? (laughs) >> They don't want to be running and operating all the time, they want to push some code. Melody Meckfessel here at Google ran a survey with developers and said, you know, "What makes you happy," and it was two things that bothered developers: technical debt and speed for deployments, commits, and the commit number was around minutes. If you can't get something done in minutes then they're onto something else, so the mind share attention of developers and technicos. So, this is a challenge at scale when you have technical debt, which we've seen companies come out of the woodwork, "Oh, yeah, "I'm going to automate something, "I'm going to throw some compute at it with the cloud "with the best monitoring package on the planet "and look how great it is," but all they did was just code some instrumentation and that's it. >> Mm-hmm. >> They weren't dealing with a lot of moving parts. Now as more things come in this is a challenge that a lot of companies face. You guys kind of solved this problem... >> Yeah, absolutely, so maybe Rajesh was a part of the team at Facebook that built the Facebook monitoring system, and that's actually what gave us a lot of the vision to start SignalFX five-and-a-half years ago, so maybe-- >> Tell about the protection, the vision-- >> Yeah. >> And what you guys are doing. >> Yeah, so CICD, you know, it kind of, like, underlies a lot of this vision of, like, moving fast. You mentioned that people wanted, like, you know, push their code in a few minutes... The thing that makes that possible is for you to have observability into what's happening while that push happens, because it's one thing to push very fast, it's another thing to recognize that you might have pushed something bad and to be able to revert it very quickly, too. And so, you'd only need, like, you know, good observability into all the things that matter that characterize the health of your system to be able to quickly recognize patterns, to be able to quickly recognize anomalies, and to be able to maybe push forward or even roll back very quickly. So, I think, like, observability is like a very key aspect of this entire CICD story. >> That's great, and that's great to know that you were over at Facebook because obviously Facebook built, at scale from the ground up, a lot of opensource. Obviously they contributed a lot to opensource, but it's interesting, as they matured and you start to see their philosophy change. It used to be move fast, break stuff. >> Yeah. >> To move fast, be reliable. >> Yeah. >> This is now the norm that's the table stakes in cloud. You have to move fast, you got to push code, but you got to maintain an operational integrity. This is, like, not like an option. This is, like, standard. >> Absolutely. >> How do you guys help solve that problem? >> So, I think there are a few different aspects to it. So, the first is to, you know, people need to ensure that they have observability into their application, so this is ensuring that you have the right kind of instrumentation in place. Thankfully this is kind of becoming commoditized right now and getting metrics from your system. The second part, and the more key part, is then being able to process this data in a real time way. You know, have high resolution, very low latency, and then to be able to do real time streaming analytics on this data. In highly elastic environments when things come and go very quickly, the identity of any individual, like, component is less important than the aggregate system behavior, and so you really need the analytics capability to kind of, like, go across this data, do various kinds of aggregations, compare it against past data, do predictive analytics, that sort of thing. So, analytics becomes the very key concept of, you know, how you operate these environments. >> It sounds so easy. >> Yeah, well one thing I'll add to that, so you know, to your point a lot of big companies sometimes are scared by this. You know, "How do we," you know... "We can't move quickly and break things," and everything that they've designed is around having process and structure to check and make sure everything is clean before they push changes out, and now we're in this world where, you know, an intern or a developer can push directly on a production, how do you manage that? The key thing in this modern world when you're trying to release software quickly, Rajesh hit on this earlier, you need the magic undo button. >> Yeah. >> That is the key to this entire process. You need to design your software, you need to design your process, and you need to design your tools so that if you introduce something bad you catch it immediately and you can roll it back. So, lots of devops practices are oriented around this, right? The idea of a canary release, I'm going to roll out an update to one percent of my systems and users, test it out, observe all the metrics, make sure everything is clean before I roll it out to everyone else, and the ability to roll back quickly is also important. But in order to do all of this you need the visibility, you need the metrics, and you need to be able to do analytics on it quickly to identify the patterns as they emerge. >> That's a great point and I'd love to just double down on that and get your thoughts because some of the Google Cloud people who are operating at this scale, I put them on this whole service-centric architecture, because they're services. We're talking about services, managing sets of services, having analytics, observation space, the reverting back and the undo button, the magic button do-over, whatever you want to call it, but the interesting thing is clean. Having a clean service whether it's an API, message queue, or an event, this stuff's happening all over the place in the new services world. How do you guys help there, is that where you guys get involved? Do you see up in that layer, how far up are you guys looking at some of the instrumentation and the insights? >> Yeah, you want to take that? >> Yeah, sure, so you know, the one thing that we really like about SignalFX and we were very keen on when we built the platform is that we are very agnostic about metrics. We're happy to accept metrics from anywhere, we'll take instrumentation-- >> (chuckles) You don't discriminate against metrics. >> We'll take instrumentation from cloud environment, we'll take, you know, metrics from opensource systems and premier applications, so you know, some of these systems are already kind of built in to get metrics from. You know, we talk to the Kafkas and Cassandras of the world, for example. We can also talk to GCP and AWS and grab metrics from their system. I think the interesting question is like when people really are taking the devops philosophy of, like, so how do you instrument your own application, what questions do you want to ask from your environment that answer the critical questions that you kind of have, and so you know, that's the one, that's the next step in the hierarchy of needs is for people to ask the right kinds of questions, and you know, instrument their applications properly. But like having done that, we can go up and down the stack in terms of, like, insight into whether all the way from your cloud environment through opensource systems, all the way up-- >> So, you guys'll take data from anyone, just stream it in-- >> Yeah. >> Normal mechanisms there, what's the value added, where's the secret sauce on SignalFX? >> So, I think value, it's all about analytics. We are all about analytics, so we are able to look at patterns of the data, we can go up and down the stack and correlate across different layers of software, look at interactions across components in your microservice, for example. You know, one really interesting thing that's happening, as you might be aware, like the whole service mesh aspect of it, which lets us, gives us insight into interactions between components-- >> Yeah. >> In a microservices architecture, so you know, we are able to get all that data and give you insight into how your whole system is working. >> So, you guys, you can see in the microservices layer? >> Absolutely. >> Yeah. >> That's powerful. >> And the key point is monitoring really has become an analytics problem, that's what we keep saying, right, because what's happening on an individual component is no longer as interesting as what's happening across the entire service, so you have to aggregate the information and look at the trend across the entire service, but the second thing that's really important is you need to be able to do it quickly, and this is where our streaming real time system really mattes. And people might ask, "Why does it "matter to do something real time." Like, "Seconds versus minutes, can a human actually "process something in seconds versus minutes?" Perhaps not, but everyone's moving towards automation, right? >> Yeah. >> So, if you want to move to a system where you have a closed loop, you have automation, and guess what, all of these modern systems, all the stuff that Google's talking here is all about automation. >> Yeah. >> And in that world seconds versus minutes, it means a tremendous amount of difference, right, where if you can find signals that will tell you there's an emerging problem within seconds and then you can revert a bad code push or you can auto-scale a cluster or you can, you know, change your load balancing algorithms all within seconds, that is what enables you to deliver, you know, 4.9s, 5.9s type of availability. >> And the consequences of not having that is outages-- >> Yeah, outages. >> Performance. >> Performance degradations, unhappy customers. I mean the cost to a brand now of having any kind of a performance issue is enormous, right? People are on Twitter before your team knows about it. (chuckles) >> Actually, you guys have a lot of the things you're solving, what is the core problem that you solve, what's the value proposition if you narrow it down that's high order bit for SignalFX? What's the corporate problem you solve? >> Well, we're solving the monitoring and observation problem for people operating cloud applications, so what happens is when you use SignalFX you have the confidence to move quickly, right? It gives you the safety net to be able to deploy changes on a daily basis, to have the shared context across a distributed team, so if you've got hundreds of two pizza box teams working together we give you that framework, the communication framework and the proactive intelligence to find issues as they emerge and proactively address them. And bottom line what that means is you can move as quickly as a Google or a Facebook or a Netflix even if you're a traditional Fortune 500 company that's regulated, and you know, you think you may not be able to do it but you really can. >> You give them the turbo charge, basically, for the analytics. All right, here's a question for you, what are the core guiding principles for the company? You guys obviously have a lot going on so you've got a core tech team, I mentioned it earlier. >> Mm-hmm. >> What are some of the guiding principles as you guys hire, build product, talk to customers, what's the key DNA of SignalFX? >> Yeah, I would say we are a very impact-driven company, so I'm, you know, very, very proud of all the people that we have on the team. We've got a lot of entrepreneurs who are focused on solving big problems, solving problems that customers may not necessarily know they need at the time, but as the market evolves we're there to solve it for them. So, we're a very customer-centric company. We have fantastic, we invest aggressively in technology, so it's not just about wrapping a pretty UI around, you know, Bolton Tech. We have real differentiated technology that solves real problems for people, and you know, I think we've in general just tried to skate to where the puck is and understand where the market's headed as a company. >> What are some of the customer feedback that you're getting? For folks that don't know SignalFX, what are some of the things that you're hearing from customers, why are you winning, what are some of the examples, can you share some color commentary? >> Yeah, I'll give one example, a Fortune 500 company that has been very aggressively investing in cloud the past, you know, four or five years, built an entire digital team, and their entire initiative is, like a lot of people in the Fortune 500 now, is to have a direct-to-consumer type of a relationship, and one of the things that they struggled with early was how do they move quickly, support product launches that might have massive load, and have the visibility to know that they can do that and catch issues as they emerge, and they didn't have a solution that could give that visibility to them until they leveraged SignalFX. And so now, if you talk to people there they'll say that they've essentially gone from defense every time they did one of these product launches to being on offense and really understanding what it takes to successfully launch a product and they're doing way more of these, so-- >> Moving the needle on time to market. >> Moving their business forward, you know, and digital transformation just by-- >> Yeah. >> Having SignalFX as a core enabler. >> It's the cloud version of putting out fires, so to speak, when you do product launches, right? >> Yeah. >> I got to ask you guys a question. You guys are both industry veterans, obviously Facebook has a storied history. We know all the great things that happen on the infrastructure side. Karthik, you've been in VM where you've seen the movie before where VM, where it made the market, changed IT for the better, still talk about the VMwares now. Now as we see cloud taking that next transformational push, describe the wave we're on right now, because it's kind of an interesting time in tech history where the talent that's coming in is pretty amazing. The young guns coming in with opensource the way it's flourishing is pretty phenomenal. Some of the smartest computer science and/or engineering talent is really solving what was old school B2B problems that really no one really wanted to solve. I mean, it was people were buying IT. Now you're talking about building operating systems, so the computer science kind of mojo in the enterprise has upped a bit. >> Mm-hmm. >> What's this wave about, how would you describe the wave of this time in history of the tech industry? >> Do you want to... (laughs) I'll add my take but why don't you go first. >> I think the thing that I find striking is just like, you know, when people used to talk about big data, you know, a few years ago, and now that is like, that's just normal. >> Yeah. >> And like, the amount of compute and the amount of storage that people are able to, you know, bring to command at-- >> Yeah. >> On any problem, it's just incredible, and that's just going to, I think, like continue to grow, right? That's going to be an amazing thing to watch. I think, you know, what this means... It also has interesting implications for, you know, companies like SignalFX who are trying to be in the monitoring space because the mojo used to be you had to have all this complicated software to do the instrumentation. Well, the instrumentations part is easy, but now all the value that's going to come about monitoring is in what you do with all that data, how you analyze it and look for, like, you know, so the whole AI ops and all that is going to be the key of the whole monitoring problem going forward, you know, five, 10 years from now, but we already see that analytics is such a key aspect of the whole thing, so... >> Yeah, I'm very, I think we're at the beginning, still at the beginning of a massive 30 to 40 year cycle, and this hasn't happened since the PC revolution in the 1970s, right, so the smartphone comes out 2007, massively opens up the market for software-based services to several billion people who are connected all the time now, drives a massive refresh of the backend infrastructure, drives the adoption of opensource, and so we're at this magical point now where the market for software-based services is just exploding, and every enterprise, you know, is becoming a software company, and you know, I think the volume of data that we're accumulating is just growing exponentially and what you can do with AI at this point, it's just... We're just beginning to see the benefit of it, so I think this is a really, really exciting time and I think we're just at the beginning. Most of the enterprises, and even the tech companies, are just beginning to capitalize on what is in store for us in the industry. >> I find it to be intoxicating, fun, and just great people coming in. To your point about the beginning of a 40 year run, also the nature of software development is being modernized at an extremely accelerated pace, so as people in the enterprise start re-imagining how they do software, because if they're a software company they've never had product managers. I mean, so the notion of what is a product, how do you launch a product, is all kind of first generation problems and opportunities, so I think to me it's really the enablement... And this is really what I think people are looking for is who can take the burden off my shoulders, help me move faster, more gas, less brake. >> Mm-hmm. >> Go faster, drive value, and then ultimately compete, because competitive advantage with technology... What does that mean to you guys, because how do you react to that because what you essentially are doing is creating instrumentation for enabling companies to create new value faster with technology and software, in some cases at a level that they've never seen before. What do you, how do you react to that? >> Well, I think that's exactly what we do, right, I mean, every company, I think most companies realized that they had to invest in software and focus on all these new opportunities at the early part of this decade. First thing they had to do was figure out who's going to build all this software, so most of them had to go hire engineers or build digital teams. They had to decide where are they going to run, the cloud wars of, you know, the early part of this decade. Do we build a private cloud, do we use a public cloud, I think both of those things have happened and people are now comfortable with those decisions. The third leg, which is squarely in the space that we're in, which is how do you operationalize this new model, and I think people are working through that now. As they get through that in the next few years, the companies like SignalFX helping every company, operationalize it very quickly, I think that's when the true promise of this new digital era will be realized where you'll start to see all of these fantastic applications, mobile apps, web service apps, direct-to-consumer streamlined supply chains. We're just beginning to see the benefit of that, and we'll see when that happens then the volume of data that they're collecting will increase exponentially and then the promise of machine learning and AI will take an altogether nother step. >> You got to know how to automate it before you can automate it, basically. What's next, final question for you guys, what's going on with SignalFX, what are you guys going to conquer, what's the next major milestones for you guys, what are you looking to do? >> Yeah, well we're continuing to focus on driving value for our customers, so we're expanding our geographic presence, so we're doing a lot of international expansion at this point. We're hiring a lot of engineers, so if anyone is interested in a development job, reach out to us. >> What kind of engineers are you looking to hire? >> Rajesh, you want to take that, sorry. (chuckles) What kind of engineers... >> What kind of engineers you looking to hire? >> Everything. (chuckles) >> I mean, all kinds of engineers, especially distributed systems engineers, front end engineers, full stack engineers, like real tech, all the good engineers we can get. >> (chuckles) Awesome. >> A lot of product development, there's a lot of interesting things happening in this space, and so we're, you know, continuing to invest very aggressively. >> Large scale distributed systems. >> Yep. >> You've got decentralized right around the corner, so you've got a lot of stuff happening. >> Yeah. >> Yeah. >> Great job to have you coming on, thanks for coming on, Karthik. >> Great, great to be on. >> Rajesh, thank you so much. >> My pleasure. >> SignalFX here in the cloud of Google here at Next, it's theCUBE, theCUBE cloud, CUBE data, we're bringing it all to you. I'm John Furrier, thanks for watching. More coverage, stay with us, we'll be back after this short break. (techy music)