(bright upbeat music) >> Welcome back everyone to theCUBE's live coverage here in Las Vegas for wall-to-wall coverage. It is re:Invent 2022, our 10th year with theCUBE. Dave and I started this journey 10 years ago here at re:Invent. There are two sets, here, a set upstairs. Great content, I'm here with Paul Gillin, my cohost. Paul's out reporting on the floor, doing some interviews. Paul, what do you think so far? It's pretty crazy activity going on here. >> Well, the activity hasn't declined at all. I mean here we are in day three of the show and it's just as busy out there as it was in day one. And there's just an energy here that you can feel, it's palpable. There is a lot of activity around developers, a lot around data. Which actually brings us a good segue into our next guest because one of the leaders in data management in the cloud is MariaDB. And John Bakke is the CRO at MariaDB, and here to talk to us about your cloud version and how open source is going for you. >> Yeah, thanks for having me. >> Paul: Thanks for joining us. >> To get the update on the product, what do you guys do on the relation to AWS? How's that going? Give us a quick update. >> In the relational database? >> No, no. The relationship with AWS >> Oh, with AWS? >> And SkySQL, what's the update? >> There's no relationship that we have that's more important than the AWS relationship. We're building our cloud, our premier cloud service called SkySQL on AWS. And they offer the best in class infrastructure for a SaaS company to build what they're building. And for us, it's a database service, right? And then beyond that, they help you from the business side, right? They try to get you lined up in the marketplace and make it possible for you to work best with customers. And then from a customer perspective, they're super helpful in not only finding prospective customers, but making that customer successful. 'Cause everybody's got a vested interest in the outcome. Right? >> Yeah, a little tongue twister there. Relational data-based relationship. We've got relational databases, we've got unstructured, data is at the center of the value proposition. Swami's keynote today and the Adam CEO's keynote, data and security dominated the keynotes >> John: Yes. >> and the conversations. So, this is real. The customers are really wanting to accelerate the developer experience, >> John: Yep. >> Developer pipe lining, more code faster, more horsepower under the hood. But this data conversation, it just never goes away. The world's keeping on coming around. >> John: It never goes away. I've been in this business for almost 30 years and we're still talking about the same key factors, right? Reliability, availability, performance, security. These things are pervasive in the data management because it's such a critical aspect to success. >> Yeah, in this case of SkySQL, you have both a transactional and an analytical engine in one. >> John: That's correct. >> Right? >> John: Yep. >> And that was a, what has the customer adoption been like of that hybrid, or I guess not a hybrid, but a dual function? >> Yeah. So the thing that makes that important is that instead of having siloed services, you have integrated data services. And a lot of times when you ask a question that's analytical it might depend on a transaction. And so, that makes the entire experience best for the developer, right? So, to take that further, we also, in SkySQL, offer a geospatial offering that integrates with all of that. And then we even take it further than that with distributed database with Xpand or ready to be Xpand. >> A lot of discussion. Geospatial announcement today on stage, just the diversity of data, and your experience in the industry. There's not the one database that rule them all anymore. There's a lot of databases out there. How are customers dealing with, I won't say database for all, 'Cause you need databases. And then you've got real time transactional, you got batch going on, you got streaming data, all kinds of data use cases now, all kind of having to be rolled together. What's your reaction? What's your take on the state of data and databases? >> Yeah, yeah, yeah. So when I started in this business, there were four databases, and now there's 400 databases. And the best databases really facilitate great application development. So having as many of those services in real time or in analytics as possible means that you are a database for everyone or for all users, right? And customers don't want to use multiple databases. Sometimes they feel like they're forced to do that, but if you're like MariaDB, then you offer all of those capabilities in an integrated way that makes the developer move faster. >> Amazon made a number of announcements this morning in the data management area, including geospatial support on RDS, I believe. How do you, I guess, coordinate yourself, your sales message with their sales message, given that you are partners, but they are competing with you in some ways? >> Yeah, there's always some cooperatition, I guess, that happens with AWS in the various product silos that they're offering their customers. For us, we're one of thousands of obviously partners that they have. And we're out there trying to do what our customers want, which is to have those services integrated, not glued together with a variety of different integration software. We want it integrated in the service so that it's one data provision, data capability for the application developer. It makes for a better experience for the developer in the end. >> On the customer side, what's the big activity? I mean, you got the on-premises database, you've got the cloud. When should a customer decide, or what's the signals to them that they should either move to the cloud, or change, be distributed? What are some of the forcing functions? What does the mark look like? >> Yeah, I've come a long way on this, but my opinion is that every customer should be in the cloud. And the reason simply is the economies that are involved, the pace of execution, the resilience and dependability of the cloud, Amazon being the leader in that space. So if you were to ask me, right now is the time to be in SkySQL because it's the premier data service in the cloud. So I would take my customer out of their on-prem and put them all in AWS, on SkySQL, if I could. Not everybody's ready for that, but my opinion is that the security is there, the reliability, the privacy, all of the things that maybe are legacy concerns, it's all been proven to be adequate and probably even better because of all of the economies of scale that you get out of being in the cloud just generally. >> Now, MariaDB, you started on-premise though. You still have a significant customer base on-premise. What, if anything are you doing to encourage them to migrate to the cloud? >> Well, so we have hundreds and hundreds of customers as MariaDB, and we weren't the first database company to put their database in the cloud, but watching it unfold helped us realize that we're going to put MariaDB in its best form factor in SkySQL. It's the only place you could get the enterprise version of MariaDB in a cloud service, right? So when we look at our customers on-prem, we're constantly telling them, obviously, that we have a cloud service. When they subscribe, we show them the efficiencies and the economies, and we do get customers that are moving. We had a customer go to Telefonica over in the UK that moved from an on-premise to manage their wifi services across Europe. And they're very happy. They were one of our very first SkySQL customers. And that has routinely proven itself to be a path towards not only a better operation for the customer, they're up more, they have fewer outages because they're not inflicting their own self wounds that they have in their own data center. They're running on world class infrastructure on world class databases. >> What are some of those self wounds? Is it personnel, kind of manual mistakes, just outages, reliability? What's the real cause, and then what's the benefit alternative in the cloud that is outside? >> Yeah. I mean, I think, when you repeat the same database implementation over and over on the infrastructure, it gets tested thousands and thousands of times. Whereas if I'm a database team and I install it once, I've tested it one time, and I can't account for all of the things that might happen in the future. So the benefit of the cloud is that you just get that repeat ability that happens and all of the sort of the kinks and bugs and issues are worked out of the system. And that's why it's just fundamentally better. We get 99.9999% uptime because all of those mistakes have been made, solved, and fixed. >> Fully managed, obviously. >> Yes. Right. >> Huge benefit. >> John: Right. >> And people are moving, it's just a great benefit. >> John: Yeah. >> So I'm a fan obviously. I think it's a great way to go. I got to ask about the security though, because big conversation here is security. What's the security posture? What's the security story to customers with SkySQL and MariaDB? >> Right, right, right. So we've taken the server, which was the initial product that MariaDB was founded upon, right? And we've come a long way over the several years that we've been in business. In SkySQL, we have SOC 2 compliance, for example. So we've gone through commercial certifications to make sure that customers can depend that we are following processes, we have technology in place in order to secure and protect their data. And in that environment, it is repeatable. So every time a customer uses our DBaaS infrastructure, databases a service infrastructure called SkySQL, they're benefiting from all of the testing that's been done. They go there and do that themselves, they would've to go through months and months of processes in order to reach the same level of protection. >> Now MariaDB is distributed by design. Is that right? >> Yes. So we have a distributed database, it's called Xpand, MariaDB Xpand. And it's an option inside of SkySQL. It's the same cost as MariaDB server, but Xpand is distributed. And the easiest way to understand what distributed database is is to understand what it is not first. What it is not is like every other cloud database. So most of the databases strangely in the cloud are not distributed databases. They have one single database node in a cluster that is where all of the changes and rights happen. And that creates a bottleneck in the database. And that's why there's difficulties in scale. AWS actually talked about this in the keynote which is the difficulty around multi writer in the cloud. And that's what Xpand does. And it spreads out the reads and the rights to make it scalable, more performant, and more resilient. One node goes down, still stays up, but you get the benefit of the consistency and the parallelization that happens in Xpand. >> So when would a customer choose Xpand versus SkySQL Vanilla? >> So we have, I would say a lot of times, but the profile of our customers are typically like financial services, trade stores. We have Samsung Cloud, 500,000 transactions per second in an expand cluster where they run sort of their Samsung cloud for their mobile device unit. We have many customers like that where it's a commercial facing website often or a service where the brand depends on uptime. Okay. So if you're in exchange or if you are a mobile device company or an IOT company, you need those databases to be working all the time and scale broadly and have high performance. >> So you have resiliency built in essentially? >> Yes, yeah. And that's the major benefit of it. It hasn't been solved by anybody other than us in the cloud to be quite honest with you. >> That's a differentiator for sure. >> It is a huge differentiator, and there are a lot of interested parties. We're going to see that be the next discussion probably next year when we come back is, what's the state of distributed database? Because it's really become really the tip of the spear with the database industry right now. >> And what's the benefits of that? Just quickly describe why that's important? >> Obviously the performance and the resilience are the two we just talked about, but also the efficiency. So if you have a multi-node cluster of a single master database, that gets replicated four times, five times over, five times the cost. And so we're taking cost out, adding performance in. And so, you're really seeing a revolution there because you're getting a lot more for a lot less. And whenever you do that, you win the game. Right? >> Awesome. Yeah, that's true. And it seems like, okay, that might be more costly but you're not replicating. >> That's right. >> That's the key. >> Replicating just enough to be resilient but not excessively to be overly redundant. Right. >> Yeah. I find that the conversation this year is starting to unpack some of these cloud native embedded capabilities inside AWS. So are you guys doing more around, on the customer side, around marketplace? Are you guys, how do people consume products? >> Yeah. It's really both. So sometimes they come to us from AWS. AWS might say, "Hey, you know what," "we don't really have an answer." And that's specifically true on the expand side. They don't really have that in their list of databases yet. Right. Hopefully, we'll get out in front of them. But they oftentimes come through our front door where they're a MariaDB customer already, right? There's over a hundred thousand production systems with MariaDB in the world, and hundreds of thousands of users of the database. So they know our brand, not quite as well as AWS, but they know our brand... >> You've got a customer base. >> We do. Right. I mean people love MariaDB. They just think it's the database that they use for application development all the time. And when they see us release an offering like Xpand just a few years ago, they're interested, they want to use that. They want to see how that works. And then when they take it into production and it works as advertised, of course, success happens. Right? >> Well great stuff, John. Great to have you on theCUBE. Paul, I guess time we do the Insta challenge here. New format on theCUBE, we usually say at the end, summarize what's most important story for you or show, what's the bumper sticker? We kind of put it around more of an Instagram reel. What's your sizzle reel? What's your thought leadership statement? 30 seconds >> John: Thought leadership. >> John? >> So the thought leadership is really in scaling the cloud to the next generation. We believe MariaDB's Xpand product will be the the technology that fronts the next wave of database solutions in the cloud. And AWS has become instrumental in helping us do that with their infrastructure and all the help that they give us, I think at the end of the day, when the story on Xpand is written, it's going to be a very fun ride over the next few years. >> John, thank you. CRO, chief revenue officer of MariaDB, great to have you on. >> Thank you. >> 34-year veteran or so in databases. (laughs) >> You're putting a lot of age on me. I'm 29. I'm 29 again. (all laugh) >> I just graduated high school and I've been doing this for 10 years. Great to have you on theCUBE. Thanks for coming on. >> Thanks guys. Yeah. >> Thanks for sharing. >> Appreciate it. >> I'm John Furrier with Paul Gillin here live on the floor, wall-to-wall coverage. We're already into like 70 videos already. Got a whole another day, finish out day three. Keep watching theCUBE, thanks for watching. We'll be right back. (calm music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante earnings season has shown a conflicting mix of signals for software companies well virtually all firms are expressing caution over so-called macro headwinds we're talking about ukraine inflation interest rates europe fx headwinds supply chain just overall i.t spend mongodb along with a few other names appeared more sanguine thanks to a beat in the recent quarter and a cautious but upbeat outlook for the near term hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis ahead of mongodb world 2022 we drill into mongo's business and what etr survey data tells us in the context of overall demand and the patterns that we're seeing from other software companies and we're seeing some distinctly different results from major firms these days we'll talk more about [ __ ] in this session which beat eps by 30 cents in revenue by more than 18 million dollars salesforce had a great quarter and its diversified portfolio is paying off as seen by the stocks noticeable uptick post earnings uipath which had been really beaten down prior to this quarter it's brought in a new co-ceo and it's business is showing a nice rebound with a small three cent eps beat and a nearly 20 million dollar top line beat crowdstrike is showing strength as well meanwhile managements at microsoft workday and snowflake expressed greater caution about the macroeconomic climate and especially on investors minds his concern about consumption pricing models snowflake in particular which had a small top-line beat cited softness and effects from reduced consumption especially from certain consumer-facing customers which has analysts digging more deeply into the predictability of their models in fact barclays analyst ramo lenchow published an especially thoughtful piece on this topic concluding that [ __ ] was less susceptible to consumption headwinds than for example snowflake essentially for a few reasons one because atlas mongo's cloud managed service which is the consumption model comprises only about 60 percent of mongo's revenue second is the premise that [ __ ] is supporting core operational applications that can't be easily dialed down or turned off and three that snowflake customers it sounds like has a more concentrated customer base and due to that fact there's a preponderance of its revenue is consumption driven and would be more sensitive to swings in these consumption patterns now i'll say this first consumption pricing models are here to stay and the much preferred model for customers is consumption the appeal of consumption is i can actually dial down turn off if i need to and stop spending for a while which happened or at least happened to a certain extent this quarter for certain companies but to the point about [ __ ] supporting core applications i do believe that over time you're going to see the increased emergence of data products that will become core monetization drivers in snowflake along with other data platforms is going to feed those data products and services and become over time maybe less susceptible and less sensitive to these consumption patterns it'll always be there but i think increasingly it's going to be tied to operational revenue last two points here in this slide software evaluations have reverted to their historical mean which is a good thing in our view we've taken some air out of the bubble and returned to more normalized valuations was really predicted and looked forward to look we're still in a lousy market for stocks it's really a bear market for tech the market tends to be at least six months ahead of the economy and often not always but often is a good predictor we've had some tough compares relative to the pandemic days in tech and we'll be watching next quarter very closely because the macro headwinds have now been firmly inserted into the guidance of software companies okay let's have a look at how certain names have performed relative to a software index benchmark so far this year here's a year-to-date chart comparing microsoft salesforce [ __ ] and snowflake to the igv software heavy etf which is shown in the darker blue line which by the way it does not own the ctf does not own snowflake or [ __ ] you can see that these big super caps have fared pretty well whereas [ __ ] and especially snowflake those higher growth companies have been much more negatively impacted year to date from a stock price standpoint now let's move on let's take a financial snapshot of [ __ ] and put it next to snowflake so we can compare these two higher growth names what we've done here in this chart has taken the most recent quarters revenue and multiplied it by 4x to get a revenue run rate and we've parenthetically added a projection for the full year revenue [ __ ] as you see will do north of a billion dollars in revenue while snowflake will begin to approach three billion dollars 2.7 and run right through that that four quarter run rate that they just had last quarter and you can see snowflake is growing faster than [ __ ] at 85 percent this past quarter and we took now these most of these profit of these next profitability ratios off the current quarter with one exception both companies have high gross margins of course you'd expect that but as we've discussed not as high as some traditional software companies in part because of their cloud costs but also you know their maturity or lack thereof both [ __ ] and snowflake because they are in high growth mode have thin operating margins they spend nearly half or more than half of their revenue on growth that's the sg a line mostly the s the sales and marketing is really where they're spending money uh and and they're specialists so they spend a fair amount of their revenue on r d but maybe not as high as you might think but a pretty hefty percentage the free cash flow as a percentage of revenue line we calculated off the full year projections because there was a kind of an anomaly this quarter in the in the snowflake numbers and you can see snowflakes free cash flow uh which again was abnormally high this quarter is going to settle in around 16 this year versus mongo's six percent so strong focus by snowflake on free cash flow and its management snowflake is about four billion dollars in cash and marketable securities on its balance sheet with little or no debt whereas [ __ ] has about two billion dollars on its balance sheet with a little bit of longer term debt and you can see snowflakes market cap is about double that of mongos so you're paying for higher growth with snowflake you're paying for the slootman scarpelli execution engine the expectation there a stronger balance sheet etc but snowflake is well off its roughly 100 billion evaluation which it touched during the peak days of tech during the pandemic and just that as an aside [ __ ] has around 33 000 customers about five times the number of customers snowflake has so a bit of a different customer mix and concentration but both companies in our view have no lack of market in terms of tam okay now let's dig a little deeper into mongo's business and bring in some etr data this colorful chart shows the breakdown of mongo's net score net score is etr's proprietary methodology that measures the percent of customers in the etr survey that are adding the platform new that's the lime green at nine percent existing customers that are spending six percent or more on the platform that's the forest green at 37 spending flat that's the gray at 46 percent decreasing spend that's the pinkish at around 5 and churning that's only 3 that's the bright red for [ __ ] subtract the red from the greens and you net out to a 38 which is a very solid net score figure note this is a survey of 1500 or so organizations and it includes 150 mongodb customers which includes by the way 68 global 2000 customers and they show a spending velocity or a net score of 44 so notably higher among the larger clients and while it's a smaller sample only 27 emea's net score for [ __ ] is 33 now that's down from 60 last quarter note that [ __ ] cited softness in its european business on its earning calls so that aligns to the gtr data okay now let's plot [ __ ] relative to some other data platforms these don't all necessarily compete head to head with [ __ ] but they are in data and database platforms in the etr data set and that's what this chart shows it's an xy graph with net score or as we say spending momentum on the vertical axis and overlap or presence or pervasiveness in the data set on the horizontal axis see that red dotted line there at 40 that indicates an elevated level of spending anything above that is highly elevated we've highlighted [ __ ] in that red box which is very close to that 40 percent line it has a pretty strong presence on the x-axis right there with gcp snowflake as we've reported has come down to earth but still well elevated again that aligns with the earnings releases uh aws and microsoft they have many data platforms especially aws so their plot position reflects their broad portfolio massive size on the x-axis um that's the presence and and very impressive on the vertical axis so despite that size they have strong spending momentum and you can see the pack of others including cockroach small on the verdict on the horizontal but elevated on the vertical couch base is creeping up since its ipo redis maria db which was launched the day that oracle bought sun and and got my sequel and some legacy platforms including the leader in database oracle as well as ibm and teradata's both cloud and on-prem platforms now one interesting side note here is on mongo's earning call it clearly cited the advantages of its increasingly all-in-one approach relative to others that offer a portfolio of bespoke or what we some sometimes call horses for courses databases [ __ ] cited the advantages of its simplicity and lower costs as it adds more and more functionality this is an argument often made by oracle and they often target aws as the company with too many databases and of course [ __ ] makes that argument uh as well but they also make the argument that oracle they don't necessarily call them out but they talk about traditional relational databases of course they're talking about oracle and others they say that's more complex less flexible and less appealing to developers than is [ __ ] now oracle of course would retur we retort saying hey we now support a mongodb api so why go anywhere else we're the most robust and the best for mission critical but this gives credence to the fact that if oracle is trying to capture business by offering a [ __ ] api for example that [ __ ] must be doing something right okay let's look at why they buy [ __ ] here's an etr chart that addresses that question it's it's mongo's feature breadth is the number one reason lower cost or better roi is number two integrations and stack alignment is third and mongo's technology lead is fourth those four kind of stand out with notice on the right hand side security and vision much lower there in the right that doesn't necessarily mean that [ __ ] doesn't have good security and and good vision although it has been cited uh security concerns um and and so we keep an eye on that but look [ __ ] has a document database it's become a viable alternative to traditional relational databases meaning you have much more flexibility over your schema um and in fact you know it's kind of schema-less you can pretty much put anything into a document database uh developers seem to love it generally it's fair to say mongo's architecture would favor consistency over availability because it uses a single master architecture as a primary and you can create secondary nodes in the event of a primary failure but you got to think about that and how to architect availability into the platform and got to consider recovery more carefully now now no schema means it's not a tables and rows structure and you can again shove anything you want into the database but you got to think about how to optimize performance um on queries now [ __ ] has been hard at work evolving the platform from the early days when you go back and look at its roadmap it's been you know started as a document database purely it added graph processing time series it's made search you know much much easier and more fundamental it's added atlas that fully managed cloud database uh service which we said now comprises 60 of its revenue it's you know kubernetes integrations and kind of the modern microservices stack and dozens and dozens and dozens of other features mongo's done a really fine job we think of creating a leading database platform today that is loved by customers loved by developers and is highly functional and next week the cube will be at mongodb world and we'll be looking for some of these items that we're showing here and this this chart this always going to be main focus on developers [ __ ] prides itself on being a developer friendly platform we're going to look for new features especially around security and governance and simplification of configurations and cluster management [ __ ] is likely going to continue to advance its all-in-one appeal and add more capabilities that reduce the need to to spin up bespoke platforms and we would expect enhance enhancements to atlas further enhancements there is atlas really is the future you know maybe adding you know more cloud native features and integrations and perhaps simplified ways to migrate to the cloud to atlas and improve access to data sources generally making the lives of developers and data analysts easier that's going to be we think a big theme at the event so these are the main things that we'll be scoping out at the event so please stop by if you're in new york city new york city at mongodb world or tune in to thecube.net okay that's it for today thanks to my colleagues stephanie chan who helps research breaking analysis from time to time alex meyerson is on production as today is as is andrew frick sarah kenney steve conte conte anderson hill and the entire team in palo alto thank you kristen martin and cheryl knight helped get the word out and rob hof is our editor-in-chief over there at siliconangle remember all these episodes are available as podcasts wherever you listen just search breaking analysis podcast we do publish each week on wikibon.com and siliconangle.com want to reach me email me david.velante siliconangle.com or dm me at divalante or a comment on my linkedin post and please do check out etr.ai for the best survey data in the enterprise tech business this is dave vellante for the cube insights powered by etr thanks for watching see you next time [Music] you

(upbeat music) >> Hey, everyone. Welcome to theCUBE's coverage of the International Women's Showcase for 2022. I'm your host, Lisa Martin. I'm pleased to welcome Nancy Wong, the general manager of Data Protection and Governance at AWS to the program. Nancy, it's great to have you. >> Thanks so much for having me Lisa, and you know, I really hope that this is hopefully the last year that we'll be celebrating International Women's Day all virtually. >> I agree. I agree. Well, we're going in that right direction globally. So let's cross our fingers. Talk to me a little bit about your role at AWS and what you do there. >> Sure. So as a GM of AWS Data Protection and Governance, a lot of, we tackle quite a few problems that our biggest customers face, right? When they think about, "How do I manage my data?" Right. Especially in this digital world. And speaking of the pandemic, how much data has been generated by consumers, by devices, by systems, by servers? How do you protect all of that data? Right. Especially we hear about cyber crime, cyber attacks. Right. Data breaches. It's really important to make sure that all of our customers have a coherent strategy around not just management, right, but also protection and really how you govern your data. Right. And there's just so many awesome conversations that my team and I have had lately with CSOs or chief technology officers on this topic, as it evolves. >> Data protection is so critical. It's one of my favorite topics to talk about, cybersecurity as well. Talk to me about what it means though if we keep this at a bit of a different level to be an operator within the the big ecosystem that is AWS. >> Yeah. And that's actually one of the the favorite aspects of my role. Right. Which is, you know, I get to innovate every day on behalf of my customers. For example, I love having one-on-one dialogues. I love having architecture conversations where we brainstorm. Right. And so those type of conversations help inform how we deliver and develop products. And so in an operator role, right, for the the women in the audience today, is it really gives you that perspective into not just how, what type of products do you want to build that delight your customers but also from an engineering. Right. And a bottom line perspective of, well how do you make this happen? Right. How do you fund this? And how do you plan out your development milestones? >> What are, tell me a little bit about your background and then what makes women in technology such an important initiative for you to stand behind? >> Absolutely. So I'm so proud today to see that the number of women or the percentage of women enrolled at engineering curriculums just continue to rise. Right. And especially as someone who went through an engineering degree in her undergraduate studies, that was not always the case. Right. So oftentimes, you know, I would look around the classroom and be the only woman on the lab bench or only woman in a CS classroom. And so when you have roles in tech, specifically, that require an undergraduate degree in computer science or a degree in engineering, that helps to, or that only serves to really reduce the population of eligible candidates. Right. Who then, if you look at that pool of eligible candidates who then you can invest and accelerate through the career ladder to become leaders in tech, well that's where you may end up with a representation issue. Right. And that's why we have, for example, so few women leaders in tech that we can look up to as role models. And that's really the problem or the gap that I'm very passionate about solving. And also, Lisa, I'm really excited to tell you a little bit more about advancing women in tech, which is a 501c3 nonprofit organization that I started to tackle this exact problem. >> Talk to me about that, cause it's one of the things that you bring up is, you know, we always say when we're having conversations like this, we can't be what we can't see. We need to be able to see those female leaders. To your point, there aren't a ton in comparison to the male leaders. So talk to me about advancing women in technology, why you founded this, and what you guys are accomplishing. >> Absolutely. So it's been such a personal journey as well. Just starting this organization called Advancing Women In Tech because I started it in 2017. Right. So when I really was, you know, just starting out as a product manager, I was at another big tech company at the time. And what I really realized, right, is looking around you know, I had so many, for example, bosses, managers, peer leaders, who were really invested in growing me as a product manager and growing my tech and career. And this is right after I'd made the transition from the federal government into big tech. What that said though, looking around, there weren't that many women tech leaders that I could look up to, or get coffee, or just have a mentoring conversation. And quickly I realized, well, it's not so much that women can't do it. Right. It's the fact that we're not advancing enough women into leadership roles. And so really we have to look at why that is. Right. And we, you know, from a personal perspective, one contribution towards that angle is upskilling. Right. So if you think about what skills one needs as one climbs a career ladder, whether that's your first people management role, or your first manager manager's role, or obviously for bigger leaders when they start managing thousands, tens of thousands of individuals, well all of that requires different skills. And so learning those skills about how to manage people, how to motivate your teams effectively, super, super important. And of course on the other side, and one that I'm, you know, near to dear to me is that of mentorship and executive sponsorship because you can have all the skills in the world, right. And especially with digital learning and AWIT is very involved with Coursera and AWS in producing and making those resources readily available and accessible. Well, if you don't have those opportunities, if you don't have mentors and sponsors who are well to push you or give you a step ladder to those roles, well you're still not going to get there. Right. And so, that's why actually, if you look at the AWIT mission, it's really those two pillars working very closely together to help advance women into leadership roles. >> The idea of mentorship and sponsorship is so critical. And I think a lot of people don't understand the difference between a mentor and a sponsor. How do you define that difference and how do you bring them into the organization so that they can be mentors and sponsors? >> Yeah, absolutely. And there's, you know, these two terms are often used today so interchangeably that I do get a lot of questions around, well, what is the difference? Right. And how does, let's say a mentor become a sponsor? So, maybe just taking a few steps back, right. When you have let's say questions around compensation or, "Hey I have some job offers, which ones do I consider?" And you ask someone a question or advice, well that person's likely your mentor. Right? And typically a mentor is someone who you can ask those questions on a repeated basis. Who's very accessible to you. Well, a sponsor takes that a few steps forward in the sense that they are sponsoring you into a role or into a project or initiative that you on your own may not be able to achieve. And by doing so, I think what really differentiates a sponsor from a mentor is that the sponsor will actually put their own reputation on the line. Right. They're using their own political capital in order to make sure that you get into that role, you get into that room. Right. And that's why it's so key, for example, especially if you have that relationship already with a person who's your mentor, you're able to ask questions or advice from, to convert them into a sponsor so that you can accelerate your career. >> Great definition, description, and great recommendations for converting mentors to sponsors. You know, I only learned the difference about a mentor and a sponsor a few years ago at another women in tech event that I was hosting. And I thought, "It's brilliant. It makes perfect sense." We need more people to understand the difference, the synergies, and how to promote mentors to sponsors. Talk to me now about advancing women in tech plus the power of AWS. How are they helping this nonprofit to really accelerate? >> Sure. So from an organization perspective, right, there's many women, for example, across the the tech companies who are part of Advancing Women In Tech, obviously Amazon of course as an employee has a very large community within who's part of AWIT. But we also have members across the tech industry from startups to VC firms to of course, Google, Microsoft, and Netflix. You name it. With that said, you know, what AWS has done with AWIT is actually very special in the sense that if you go to the Coursera platform, coursera.org/awit you can see our two Coursera specializations. Four courses each that go through the real world product management fundamentals. Or the business side, the technical skills, and even interviewing for mid-career product management roles. And the second specialization, which I'm super excited to share today, is actually geared towards getting folks ramped up and prepared to successfully pass the Cloud Practitioner's Exam, which is one of the industry recognized standards about understanding the AWS Cloud and being functional in the AWS Cloud. This summer, of course, and I'm sharing kind of a sneak peek announcement that I'll be making tomorrow with the University of Pennsylvania, is that we're kicking off a program for the masters of CIS program, or the Computer Information Systems Master students, to actually go through this Coursera specialization, which is produced by AWIT, sponsored by AWS, and AWS Training and Certifications has so generously donated exam vouchers for these students so that they can then go on and be certified in the AWS Cloud. So that's one just really cool collaboration that we are doing between AWS and AWIT to get more qualified folks in the door in tech jobs, and hopefully at jobs in AWS. >> That's a great collaboration. What are some of the goals in terms of metrics, the number of women that you want to get into the program and complete the program? What are some of those on your radar? >> Absolutely. So one of the reasons, of course, that the Master's of CIS Program, the University of Pennsylvania caught my eye, not withstanding, I graduated from there, but also that just the statistics of women enrolled. Right. So what's really notable about this program is it's entirely online, which as a university creating a Master's degree fully online, well, it takes a ton of resources from the university, from the faculty. And what's really special about these students is that they're already full-time adult professionals, which means that they're working a full-time job, they might be taking care of family obligations, and they're still finding time to advance themselves, to acquire a Master's degree in CS. And best of all, 42% of these students are women. Right. And so that's a number that is multiples of what we're finding in engineering curriculums today. And so my theory is, well if you go to a student population that is over 40%, 42 to be exact percent women, and enable these women to be certified in AWS Cloud, to have direct interview prep and mentorship from AWS software development leaders, well, that greatly increases their chances of getting a full-time role, right, at AWS. Right. At which then we can help them advance their careers to further and further roles in software development. >> So is this curriculum also open to women who aren't currently in tech to be able to open the door for them to get into tech and STEM fields? >> Absolutely. And so in my bad and remiss in mentioning, which is students of this Master's in CS Program are actually students not from tech already. So they're not in a tech field. And they did not have a degree in CS or even engineering as part of their undergraduate studies. So it's truly folks who are outside of tech, that are 42% women, that we're getting into the tech industry with this collaboration between AWS, AWIT, and the University of Pennsylvania. >> That's outstanding to get them in from completely different fields into tech. >> Absolutely. >> How do you help women have the confidence to say, "I want to try this." Cause if we think about every company today is a tech company. It's a data company. It has to be to be competitive. You know, the pandemic taught us that everything we're able to do online and digitally, for example, but how do you help women get the confidence to say, "Okay, I'm going to go from a completely different field into tech." >> Absolutely. So if we, you know, define tech of course as big tech or, you know, now the main companies, right, I myself made that transition, which is why it is a topic near and dear to me because I can personally speak to my journey because I didn't start my career out in tech. Right. Yes. I studied engineering. But with that said, my first full-time job out of college was with the federal government because I wanted to go and build healthdata.gov, right, which gave folks a lot of access to the healthcare data, roles, right, that existed within the U.S. government and the CMS, NIH, you know, CDC, so on and so forth. But that was quite a big change from then taking a product management job at Google. Right. And so how did I make that change? Well, a lot of it came from, you know, the mentors that I had. Right. What I call my personal board of directors who gave me that confidence. And sure, I mean even today, I still have imposter syndrome where, you know, I think, "Am I good enough." Right. "Should I be leading this organization," right, "of data protection and governance." But I think what it boils down to is, you know, inner confidence. Right. And goes back to those two pillars of having the right skills and also the right mentors and sponsors who are willing to help sponsor you into those opportunities and help sponsor you to success. >> Absolutely. Great advice and recommendations. Thanks for sharing your background, Nancy, it's outstanding to see where you started to where you are now and also to what you're enabling for so many other females to get into tech with the AWIT program combined with AWS and UPenn. Exciting stuff. Can't wait to talk to you next year to see where you guys go from here. >> Absolutely Lisa. And what I'm really looking forward to sharing with you next year is the personal testimonials of other women who have gone through the AWIT, the AWS, the UPenn Program and have gotten their tech jobs and also promotions. >> That sounds like a great thing to look forward to. I'm looking forward to that. Nancy, thanks so much for your time and the insight that you shared. >> Thanks so much for having me, Lisa. >> My pleasure. For Nancy Wong, I'm Lisa Martin. You're watching theCUBE's coverage of the International Women's Showcase 2022. (upbeat music)

(upbeat music) >> It's my pleasure, to be one of the hosts of theCUBE on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years theCUBE has been following the trail of data. And with the relentless match of data growth this idea of a single version of the truth has become more and more elusive. Moreover, data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand, the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is Manish Sood the CTO and co-founder of Reltio. Manish, welcome to the program. >> Thank you, Dave. It's a pleasure to be here. >> Okay, let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement, cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with data as a source of digital innovation. >> Dave, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011 there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making compute capabilities available at scale to solve large data problems was becoming real and possible. The second thing that we saw was this big trend of you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone and we are seeing more of the best of breed application type of a landscape where even if you look within a specific function let's say sales or marketing, you have more than a dozen applications that any company is using today. And that trend was starting to emerge where we knew very well that the number of systems that we would have to work with would continue to increase. And that created a problem of where would you get the single source of truth or the single best origin of a customer, a supplier, a product that you're trying to sell, those types of critical pieces of information that are core to any business that's out there today. And, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of capability and for us to provide this capability in the cloud as a software, as a service offering. So that's where, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos, and create a unified view of the core critical information that these companies run on. >> Yeah, the cloud is this giant, you know hyper distributed system, data by its very nature is distributed. It's interesting what you were sort of implying about you know, the days of the monolithic app are gone, but my business partner years ago John Furrier at theCUBE said, data is going to become the new development kit. And we've certainly seen that with the pandemic but tell us more about Reltio and how you help customers deal with that notion of data silos, data fragmentation, how do you solve that problem? >> So data fragmentation is what exists today. And, with the Reltio software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented siloed applications or data sources that they have within their enterprise. At the same time, there's a lot of dependence on the third party data. You know, when you think about different problems that you're trying to solve, you have for B2B type of information that in Bradstreet type of data providers, in life sciences you have IQVIA type of data providers. You know, as you look at other verticals that is a specialized third party data provider for any and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. And that's where Reltio fits in as the only platform that can help stitch together this kind of information and create a 360 degree view that spans all the data silos and provides that for real-time use, for BI and analytics to benefit from, for data science to benefit from, and then this emerging notion of data in itself is a, you know, key starting point that is used by us in order to make any decisions. Just like we go, you know, if I they wanted to look at information about you, I would go to places like LinkedIn, look up the information, and then on my next set of decisions with that information. If somebody wanted to look up information on Reltio they would go to, let's say crunchbase as an example and look up, who are the investors? How much money have we raised? All those details that are available. It's not a CRM system by itself but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide as a part of the Reltio platform capabilities. >> Awesome, thank you. And I want to get into the tech, but before we do maybe we just cut to the chase and maybe you can talk about some of the examples of Reltio and action, some of the customers that you can talk about, maybe the industries that are really adopting this. What can you tell us there Manish? >> We work across a few different verticals some of the key verticals that we work in are life sciences and travel and hospitality and financial services, insurance retail, as an example. Those are some of the key verticals for us. But to give you some examples of the type of problems that customers are solving with Reltio as the data unification platform, let's take CarMax as an example,. CarMax is a customer who's in the business of buying used cars, selling used cars servicing those used cars. And then, you know, you as a customer don't just transact with them once, you know, you've had a car for three years you go back and look at what can you trade in that car for? But in order for CarMax to provide a service to you that goes across all the different touch points whether you are visiting them at their store location trying to test drive a car or viewing information about the various vehicles on their website, or just you know, punching in the registration number of your car just to see what is the appraisal from them in terms of how much will they pay for your car. This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points. And the type of information that they use relative for aggregating, unifying, and then making available across all these touch points, is all of the information about the customers, all of the information about the household, you know, the understanding that they are trying to achieve because life events can be buying signals for consumers like you and I, as well as who was the associate who helped you either in the selling of a car, buying of a car, because their business is all about building relationships for the longer term, lifetime value that they want to capture. And in that process, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, there is a lot of information in order to price it right, that needs to be gathered from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio and then made available through APIs or through other methods and means to the various applications, can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run and to end. >> Well, sounds like we come along, (indistinct). >> I was just going to say that's one example and, you know across other verticals, that are other similar examples of how companies are leveraging, Reltio >> Yeah, so as you say, we've come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and you know happy to dig into some other examples, but I wonder how does it work? I mean, what's the magic behind it? What's the tech look like? I mean, obviously leveraging AWS, maybe you could talk about how, so, and maybe some of the services there and some of your unique IP. >> Yeah, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, you know, if you think about the problem itself, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. You know, for example, I have been in this area was responsible for creating some of the previous generation capabilities and most of the friction in those previous generation MDM or master data management type of solutions as the you know, the technical term that is used to refer to this area, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that customers want to capture, whether it is, you know, about a patient or a product or let's say a supplier that you're working with, there is always additional information that you can capture and you know use to better inform the decisions for the next engagement. And that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use add scale compute capabilities in the cloud, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information just locking it in a data warehouse has been sort of the problem in the past, and you talked about the clickstream analysis. Analytics has a place, but most of the analytics is a real view mirror picture of the, you know, work that you have to do versus everybody that we talk to as a potential customer wanted to solve the problem of what can we do at the point of engagement? How can we influence decisions? So, you know, I'll give you an example. I think everybody's familiar with Quicken loans as the mortgage lender, and in the mortgage lending business, Quicken loans is the customer who's using Reltio as the customer data unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time vendor, you know anywhere from 10 minutes to about an hour where if somebody expresses an interest in refinancing or getting a mortgage they have to close that business within that hot vendor. The conversion ratios are exponentially better in that hot vendor versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage at? And they've been able to use this notion of real time data where as soon as you come in through the website or if you come in through the rocket mortgage app or you're talking to a broker by calling the 1800 number they are able to triangulate that it's the same person coming from any of these different channels and respond to that person with an offer ASAP so that there is no opportunity for the competition to get in and present you with a better offer. So those are the types of things where the time to conversion or the time to action is being looked at, and everybody's trying to shrink that time down. That ability to respond in real time with the capabilities were sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities, and now customers are able to benefit from that. >> That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket when you experience that environment, it's totally different, than anything you've ever seen before. So it's helpful to hear you explain like what's behind that because, it's truly disruptive and I'll tell you the other thing that sort of triggered a thought was that we use the word realtime a lot and we try to develop years ago. We said, what does real-time really mean? And the answer we landed on was, before you lose the customer, and that's kind of what you just described. And that is what gives as an example a quick and a real advantage again, having experienced it firsthand. It's pretty, pretty tremendous. So that's a nice reference. So, and the other thing that struck me is, I wanted to ask you how it's different from sort of legacy Master Data Management solutions and you sort of described that they've since to me they've got to take their traditional on-prime stack, rip it out, stick it in the iCloud, it's okay we got our stack in the cloud now. Your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a CTO's perspective, what's your take? >> Yeah, the clean sheet of paper is the luxury that we have. You know, having seen this movie before having, you know looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, you know, across all of our customers, we are today managing about 6.5 billion consolidated profiles of people, organizations, product, locations, you know, assets, those kinds of details. And these are the types of crown jewels of the business that every business runs on. You know, for example, if you wanted to let's say you're a large company, like, you know, Ford and you wanted to figure out how much business are you doing, whether, you know another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. It's been a very difficult to answer to understand what is the total book of business that they have with that other big customer. And, you know, being able to have the right, unified, relevant, ready clean information as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, you know drive any kind of conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. You have to have that foundation of clean data to work with in order to get to those answers. >> Nice, and then I had questions on just analysis, it's a SAS model I presume, how is it priced? Do you have a freemium? How do I get started? Maybe you could give us some color on that. >> Yeah, we are a SAS provider. We do everything in the cloud, offer it as a SAS offering for customers to leverage and benefit from. Our pricing is based on the volume of consolidated profiles, and I use the word profiles because this is not the traditional data model, where you have rows, columns, foreign keys. This is a profile of a customer, regardless of attribution or any other details that you want to capture. And you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, you know, off these different types of data domains, customer, patient, provider, product, asset, those types of details, but then they grow and some of the customers HPInc, as a customer, is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use, the single source of truth capabilities provided by Reltio. >> And, and your relationship with AWS, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >> Yeah, AWS has been a key partner for us since the very beginning. We are now on the marketplace. Customers can start with the free version of the product and start to play with the product, understand it better and then move into the paid tier, you know as they bring in more data into Reltio and, you know be also have the partnership with AWS where, you know customers can benefit from the relationship where they are able to use the spend against Reltio to offset the commitment credits that they have for AWS, you know, as a cloud provider. So, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >> Nice, love those credits. Company update, you know, head count, funding, revenue trajectory what kind of metrics are you comfortable sharing? >> So we are currently at about, you know, slightly not at 300 people overall at Reltio. We will grow from 300 to about 400 people this year itself we are, you know, we just put out a press release where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are looking at crossing the hundred million dollar ARR threshold later this year. So we are on a great growth trajectory and the business is performing really well. And we are looking at working with more customers and helping them solve this, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >> That's some impressive growth, congratulations. We're, I'm sure adding hundred people you're hiring all over the place, but where we are some of your priorities? >> So, you know, the, as the business is growing we are spending equally, both on the R and D side of the house investing more there, but at the same time also on our go to market so that we can extend our reach, make sure that more people know about Reltio and can start leveraging the benefit of the technology that we have built on top of AWS. >> Yeah, I mean it sounds like you've obviously nailed product market fit and now you're, you know, scaling the grip, go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, what was prompted that move? >> Problems of luxury, you know, as I like to call them once you know that you're in a great growth trajectory, and the business is performing well, it's all about figuring out ways of, you know making sure that you can drive harder and faster towards that growth milestones that you want to achieve. And, you know, for us, the story is no different. The team has done a wonderful job of making sure that we can build the right platform, you know work towards this opportunity that we see, which by the way they've just to share with you, MDM or Master Data Management has always been underestimated as a, you know, yes there is a problem that needs to be solved but the market sizing was in a, not as clear but some of the most recent estimates from analysts like Gartner, but the, you know, sort of the new incarnation of data unification and Master Data Management at about a $30 billion, yeah, TAM for this market. So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, I looked at, you know how could we scale the business faster and have the right team to work help us maximize the opportunity. And that's why, you know, we decided that it was the right point in time for me to bring in somebody who's worked at the stretch of, you know taking a company from just a hundred million dollars in ARR to, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, you know, has had that experience and having him take on the CEO role really puts us on a tremendous path or path to tremendous growth and achieving that with the right team. >> Yeah, and I think I appreciate your comments on the TAM. I love to look at the TAM and to do a lot of TAM analysis. And I think a lot of times when you define the the future TAM based on sort of historical categories, you sometimes under count them. I mean, to me you guys are in the digital business. I mean, the data transformation the company transformation business, I mean that could be order of magnitude even bigger. So I think the future is bright for your company Reltio, Manish and thank you so much for coming on the program. Really appreciate it. >> Well, thanks for having me, really enjoyed it. Thank you. >> Okay, thank you for watching. You're watching theCUBEs Startup Showcase. We'll be right back. (upbeat music)

>> Okay listen, we're gearing up for the start of the Snowflake Data Cloud Summit. And we want to go back to the early roots of Snowflake. We got some of the founding engineers here, Abdul Munir, Ashish Motivala and Allison Lee. They're three individuals that were at Snowflake, in the early years and participated in many of the technical decisions. That led to the platform and is making Snowflake famous today. Folks great to see you. Thanks so much for taking some time out of your busy schedules. >> Thank you for having us- >> Same. >> It's got to be really gratifying to see this platform that you've built, taking off and changing businesses. So I'm sure it was always smooth sailing, right? There were no debates, where there ever? >> I've never seen an engineer get into a debate. >> Yeah alright, so seriously. So take us back to the early days, you guys choose whoever wants to start, but what was it like, early on we're talking 2013 here, right? >> That's right. >> When I think back to the early days of Snowflake. I just think of all of us sitting in one room at the time, we just had an office that was one room with 12 or 13 engineers sitting there, clacking away at our keyboards, working really hard, churning out code punctuated by somebody asking a question about hey, what should we do about this? Or what should we do about that? And then everyone kind of looking up from their keyboards and getting into discussions and debates about the work that we were doing. >> So, Abdul was it just kind of heads down, headphones on just coding or? >> I think there was a lot of talking and followed by a lot of typing. And I think there were periods of time where anyone could just walk in into the office and probably out of the office and all they'd hear is probably people typing away their keyboards. And one of my most vivid memory is actually I used to sit right across from Allison and there was these two huge monitors between us. And I would just hear her typing away at her keyboard. And sometimes I was thinking and all that typing got me nervous because it seemed like Allison knew exactly what she needed to do. And I was just still thinking about it. >> So Ashish was this like bliss for you as a developer or an engineer? Or was it a stressful time? What was the mood? >> Then when you don't have a whole lot of customers, there's a lot of bliss, but at the same time, there's a lot of pressure on us to make sure that we build the product. There was a timeline ahead of us. We knew we had to build this in a certain timeframe. So one thing I'll add to what Allison and Abdul said is, we did a lot of whiteboarding as well. There were a lot of discussions and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure everyone was in tune and there we have it. >> Yeah, it is a really exciting time. We can do it any start-up. When you have to make decisions in development and variably you come to a fork in the road. So I'm curious as to what some of those forks might've been, how you guys decided which fork to take. Was there a Yoda in the room that served as the Jedi Master? How are those decisions made? Maybe you could talk about that a little bit. >> That's an interesting question. And as I think back one of the memories that sticks out in my mind is this epic meeting in one of our conference rooms called Northstar and many of our conference rooms are named after ski resorts because the founders are really into skiing. And that's where the Snowflake name comes from. So there was this epic meeting and I'm not even sure exactly what topic we were discussing. I think it was the sign up flow and there were a few different options on the table. And one of the options that people were gravitating to, one of the founders didn't like it. And they said a few times that this makes no sense. There's no other system in the world that does it this way. And I think one of the other founders said, that's exactly why we should do it this way or at least seriously consider this option. So, I think there was always this tendency and this impulse that we needed to think big and think differently and not see the world the way it is, but the way we wanted it to be and then work our way backwards and try to make it happen. >> Allison, any fork in the road moments that you remember? >> Well, I'm just thinking back to a really early meeting with Ashish and a few of our founders where we're debating something probably not super exciting to a lot of people outside of hardcore database people, which was how to represent our column metadata. And I think it's funny that you that you mentioned Yoda, because we often make jokes about one of our founders Thierry and referred to him as Yoda, because he has this tendency to say very concise things that kind of make you scratch your head and say, wow, why didn't I think of that? Or what exactly does that mean? I never thought about it that way. So, when I think of the Yoda in the room, it was definitely Thierry, >> Ashish is there anything you can add to this conversation? >> I'll agree with Allison on the Yoda comment for sure. Another big fork in the road I recall was when we changed one of our meadow store, where we store and are willing to try and metadata. We used to use a tool called my SQL and we changed it to another database called foundation DV. I think that was a big game changer for us. And it was a tough decision. It took us a long time, for the longest time we even had our own little branch it was called foundation DV and everybody was developing on that branch, it's a little embarrassing but those are the kinds of decisions that have altered the shape of Snowflake. >> Yeah, these are really down in the weeds hardcore stuff that a lot of people might not be exposed to. What would you say was the least obvious technical decision that you had to make at the time? And I want to ask you about the most obvious too, but what was the one that was so out of the box? You kind of maybe mentioned it a little bit before, but I wonder if we could double click on that? >> Well, I think one of the core decisions in our architecture is the separation of compute and storage that is really core to our architecture. And there's so many features that we have today, for instance data sharing, zero-copy cloning, that we couldn't have without that architecture. And I think it was both not obvious. And when we told people about it in the early days, there was definitely skepticism about being able to make that work and being able to have that architecture and still get great performance. >> Exactly- >> Yeah, anything that was like clearly obvious, maybe that was the least and the most that separation from compute and store, 'cause it allowed you to actually take advantage of cloud native, but was there an obvious one that is it sort of dogma that you philosophically live behind to this day? >> I think one really obvious thing is the sort of no tuning, no knobs, ease of use story behind Snowflake. And I say it's really obvious because everybody wants their system to be easy to use. But then I would say there were tons of decisions behind that, that it's not always obvious the implications of such a choice, right? And really sticking to that. And I think that that's really like a core principle behind Snowflake that led to a lot of non-obvious decisions as a result of sticking to that principle. >> To wrap to that now you've gotten us thinking, I think another really interesting one was really, should we start from scratch or should we use something that already exists and build on top of that. And I think that was one of these almost philosophical kind of stances that we took, that a lot of the systems that were out there were the way they were because they weren't built for the platforms that they were running on. And the big thing that we were targeting was the cloud. And so one of the big stances we took was that we were going to build it from scratch and we weren't going to borrow a single line of code from any other database out there. And this was something that really shocked a lot of people and many times that this was pretty crazy. And it was, but this is how you build great products. >> That's awesome, all right, Ashish give your last word, we got like just 30 seconds left take, bring us home. >> Till date actually one of those that shocks people when you talk to them and they say, wow, you're not really using any other database? And you build this entirely yourself? The number of people who actually can build a database from scratch are fairly limited. The group is fairly small. And so it was really a humongous task. And as you've mentioned, it really changed the direction of how we designed the database. What does the database really mean to us, right? The way Snowflake has built a database, it's really a number of organs that come together and form the body. And that's also a concept that's novel to the database industry. >> Guys congratulations, you must be so proud and it's going to be awesome watching the next decade. So thank you so much for sharing your stories. >> Thanks Dave. >> Thank you- >> Thank you.

(upbeat music) >> Reporter: From around the globe, it's The Cube with digital coverage of enterprise data automation and event series brought to you by Io-Tahoe. >> Okay, we're back. Focusing on enterprise data automation, we're going to talk about the journey to the cloud. Remember, the hashtag is data automated. We're here with Lester Waters who's the CTO of Io-Tahoe, Lester, good to see you from across the pond on video, wish we were face to face, but it's great to have you on The Cube. >> Also I do, thank you for having me. >> Oh, you're very welcome. Hey, give us a little background on CTO, you got a deep expertise in a lot of different areas, but what do we need to know? >> Well, David, I started my career basically at Microsoft, where I started the Information Security Cryptography Group. They're the very first one that the company had and that led to a career in information security and of course, as you go along with the information security, data is the key element to be protected. So I always had my hands in data and that naturally progressed into a role with Io-Tahoe as their CTO. >> Guys, I have to invite you back, we'll talk crypto all day we'd love to do that but we're here talking about yeah, awesome, right? But we're here talking about the cloud and here we'll talk about the journey to the cloud and accelerate. Everybody's really interested obviously in cloud, even more interested now with the pandemic, but what's that all about? >> Well, moving to the cloud is quite an undertaking for most organizations. First of all, we've got as probably if you're a large enterprise, you probably have thousands of applications, you have hundreds and hundreds of database instances, and trying to shed some light on that, just to plan your move to the cloud is a real challenge. And some organizations try to tackle that manually. Really what Io-Tahoe is bringing is trying to tackle that in an automated version to help you with your journey to the cloud. >> Well, look at migrations are sometimes just an evil word to a lot of organizations, but at the same time, building up technical debt veneer after veneer and year, and year, and year is something that many companies are saying, "Okay, it's got to stop." So what's the prescription for that automation journey and simplifying that migration to the cloud? >> Well, I think the very first thing that's all about is data hygiene. You don't want to pick up your bad habits and take them to the cloud. You've got an opportunity here, so I see the journey to the cloud is an opportunity to really clean house, reorganize things, like moving out. You might move all your boxes, but you're kind of probably cherry pick what you're going to take with you and then you're going to organize it as you end up at your new destination. So from that, I get there's seven key principles that I like to operate by when I advise on the cloud migration. >> Okay. So, where do you start? >> Well, I think the first thing is understanding what you got, so discover and cataloging your data and your applications. If I don't know what I have, I can't move it, I can't improve it, I can't build up on it. And I have to understand there is dependency, so building that data catalog is the very first step. What do I got? >> Now, is that a metadata exercise? Sometimes there's more metadata than there is data. Is metadata part of that first step or? >> In deed, metadata is the first step so the metadata really describes the data you have. So, the metadata is going to tell me I have 2000 tables and maybe of those tables, there's an average of 25 columns each, and so that gives me a sketch if you will, of what I need to move. How big are the boxes I need to pack for my move to the cloud? >> Okay, and you're saying you can automate that data classification, categorization, discovery, correct using math machine intelligence, is that correct? >> Yeah, that's correct. So basically we go, and we will discover all of the schema, if you will, that's the metadata description of your tables and columns in your database in the data types. So we take, we will ingest that in, and we will build some insights around that. And we do that across a variety of platforms because everybody's organization has you've got a one yeah, an Oracle Database here, and you've got a Microsoft SQL Database here, you might have something else there that you need to bring site onto. And part of this journey is going to be about breaking down your data silos and understanding what you've got. >> Okay. So, we've done the audit, we know what we've got, what's next? Where do we go next? >> So the next thing is remediating that data. Where do I have duplicate data? Often times in an organization, data will get duplicated. So, somebody will take a snapshot of a data, and then ended up building a new application, which suddenly becomes dependent on that data. So it's not uncommon for an organization of 20 master instances of a customer. And you can see where that will go when trying to keep all that stuff in sync becomes a nightmare all by itself. So you want to understand where all your redundant data is. So when you go to the cloud, maybe you have an opportunity here to consolidate that data. >> Yeah, because you like to borrow in an Einstein or apply an Einstein Bromide right. Keep as much data as you can, but no more. >> Correct. >> Okay. So you get to the point to the second step you're kind of a one to reduce costs, then what? You figure out what to get rid of, or actually get rid of it, what's next? >> Yes, that would be the next step. So figuring out what you need and what you don't need often times I've found that there's obsolete columns of data in your databases that you just don't need, or maybe it's been superseded by another, you've got tables that have been superseded by other tables in your database. So you got to understand what's being used and what's not and then from that, you can decide, "I'm going to leave this stuff behind, "or I'm going to archive this stuff "cause I might need it for data retention "or I'm just going to delete it, "I don't need it at all." >> Well, Lester, most organizations, if they've been around a while, and the so-called incumbents, they've got data all over the place, their data marts, data warehouses, there are all kinds of different systems and the data lives in silos. So, how do you kind of deal with that problem? Is that part of the journey? >> That's a great point Dave, because you're right that the data silos happen because this business unit is chartered with this task another business unit has this task and that's how you get those instantiations of the same data occurring in multiple places. So as part of your cloud migration journey, you really want to plan where there's an opportunity to consolidate your data, because that means there'll be less to manage, there'll be less data to secure, and it'll have a smaller footprint, which means reduced costs. >> So, people always talk about a single version of the truth, data quality is a huge issue. I've talked to data practitioners and they've indicated that the quality metrics are in the single digits and they're trying to get to 90% plus, but maybe you could address data quality. Where does that fit in on the journey? >> That's, a very important point. First of all, you don't want to bring your legacy issues with you. As the point I made earlier, if you've got data quality issues, this is a good time to find those and identify and remediate them. But that can be a laborious task. We've had customers that have tried to do this by hand and it's very, very time consuming, cause you imagine if you've got 200 tables, 50,000 columns, imagine, the manual labor involved in doing that. And you could probably accomplish it, but it'll take a lot of work. So the opportunity to use tools here and automate that process is really will help you find those outliers there's that bad data and correct it before you move to the cloud. >> And you're just talking about that automation it's the same thing with data catalog and that one of the earlier steps. Organizations would do this manually or they try to do it manually and that's a lot of reason for the failure. They just, it's like cleaning out your data like you just don't want to do it (laughs). Okay, so then what's next? I think we're plowing through your steps here. What what's next on the journey? >> The next one is, in a nutshell, preserve your data format. Don't boil the ocean here to use a cliche. You want to do a certain degree of lift and shift because you've got application dependencies on that data and the data format, the tables on which they sit, the columns and the way they're named. So, some degree you are going to be doing a lift and shift, but it's an intelligent lift and shift using all the insights you've gathered by cataloging the data, looking for data quality issues, looking for duplicate columns, doing planning consolidation. You don't want to also rewrite your application. So, in that aspect, I think it's important to do a bit of lift and shift and preserve those data formats as they sit. >> Okay, so let me follow up on that. That sounds really important to me, because if you're doing a conversion and you're rewriting applications, that means that you're going to have to freeze the existing application, and then you going to be refueling the plane as you're in midair and a lot of times, especially with mission critical systems, you're never going to bring those together and that's a recipe for disaster, isn't it? >> Great analogy unless you're with the air force, you'll (mumbles) (laughs). Now, that's correct. It's you want to have bite-sized steps and that's why it's important to plan your journey, take these steps. You're using automation where you can to make that journey to the cloud much easier and more straightforward. >> All right, I like that. So we're taking a kind of a systems view and end to end view of the data pipeline, if you will. What's next? I think we're through. I think I've counted six. What's the lucky seven? >> Lucky seven, involve your business users. Really, when you think about it, your data is in silos. Part of this migration to the cloud is an opportunity to break down these silos, these silos that naturally occur as part of the business unit. You've got to break these cultural barriers that sometimes exist between business and say, so for example, I always advise, there's an opportunity here to consolidate your sensitive data, your PII, your personally identifiable information, and if three different business units have the same source of truth for that, there's was an opportunity to consolidate that into one as you migrate. That might be a little bit of tweaking to some of the apps that you have that are dependent on it, but in the long run, that's what you really want to do. You want to have a single source of truth, you want to ring fence that sensitive data, and you want all your business users talking together so that you're not reinventing the wheel. >> Well, the reason I think too that's so important is that you're now I would say you're creating a data driven culture. I know that's sort of a buzz word, but what it's true and what that means to me is that your users, your lines of business feel like they actually own the data rather than pointing fingers at the data group, the IT group, the data quality people, data engineers, saying, "Oh, I don't believe it." If the lines of business own the data, they're going to lean in, they're going to maybe bring their own data science resources to the table, and it's going to be a much more collaborative effort as opposed to a non-productive argument. >> Yeah. And that's where we want to get to. DataOps is key, and maybe that's a term that's still evolving. But really, you want the data to drive the business because that's where your insights are, that's where your value is. You want to break down the silos between not only the business units, as I mentioned, but also as you pointed out, the roles of the people that are working with it. A self service data culture is the right way to go with the right security controls, putting on my security hat of course in place so that if I'm a developer and I'm building a new application, I'd love to be able to go to the data catalog, "Oh, there's already a database that has the customer "what the customers have clicked on when shopping." I could use that. I don't have to rebuild that, I'll just use that as for my application. That's the kind of problems you want to be able to solve and that's where your cost reductions come in across the board. >> Yeah. I want to talk a little bit about the business context here. We always talk about data, it's the new source of competitive advantage, I think there's not a lot of debate about that, but it's hard. A lot of companies are struggling to get value out of their data because it's so difficult. All the things we've talked about, the silos, the data quality, et cetera. So, you mentioned the term data apps, data apps is all about streamlining, that data, pipelining, infusing automation and machine intelligence into that pipeline and then ultimately taking a systems view and compressing that time to insights so that you can drive monetization, whether it's cut costs, maybe it's new revenue, drive productivity, but it's that end to end cycle time reduction that successful practitioners talk about as having the biggest business impact. Are you seeing that? >> Absolutely, but it is a journey and it's a huge cultural change for some companies that are. I've worked in many companies that are ticket based IT-driven and just do even the marginalist of change or get insight, raise a ticket, wait a week and then out the other end will pop maybe a change that I needed and it'll take a while for us to get to a culture that truly has a self service data-driven nature where I'm the business owner, and I want to bring in a data scientist because we're losing. For example, a business might be losing to a competitor and they want to find what insights, why is the customer churn, for example, happening every Tuesday? What is it about Tuesday? This is where your data scientist comes in. The last thing you want is to raise a ticket, wait for the snapshot of the data, you want to enable that data scientist to come in, securely connect into the data, and do his analysis, and come back and give you those insights, which will give you that competitive advantage. >> Well, I love your point about churn, maybe it talks about the Andreessen quote that "Software's eating the world," and all companies are our software companies, and SaaS companies, and churn is the killer of SaaS companies. So very, very important point you're making. My last question for you before we summarize is the tech behind all of these. What makes Io-Tahoe unique in its ability to help automate that data pipeline? >> Well, we've done a lot of research, we have I think now maybe 11 pending patent applications, I think one has been approved to be issued (mumbles), but really, it's really about sitting down and doing the right kind of analysis and figuring out how we can optimize this journey. Some of these stuff isn't rocket science. You can read a schema and into an open source solution, but you can't necessarily find the hidden insights. So if I want to find my foreign key dependencies, which aren't always declared in the database, or I want to identify columns by their content, which because the columns might be labeled attribute one, attribute two, attribute three, or I want to find out how my data flows between the various tables in my database. That's the point at which you need to bring in automation, you need to bring in data science solutions, and there's even a degree of machine learning because for example, we might deduce that data is flowing from this table to this table and upon when you present that to the user with a 87% confidence, for example, and the user can go, or the administrator can go. Now, it really goes the other way, it was an invalid collusion and that's the machine learning cycle. So the next time we see that pattern again, in that environment we will be able to make a better recommendation because some things aren't black and white, they need that human intervention loop. >> All right, I just want to summarize with Lester Waters' playbook to moving to the cloud and I'll go through them. Hopefully, I took some notes, hopefully, I got them right. So step one, you want to do that data discovery audit, you want to be fact-based. Two is you want to remediate that data redundancy, and then three identify what you can get rid of. Oftentimes you don't get rid of stuff in IT, or maybe archive it to cheaper media. Four is consolidate those data silos, which is critical, breaking down those data barriers. And then, five is attack the quality issues before you do the migration. Six, which I thought was really intriguing was preserve that data format, you don't want to do the rewrite applications and do that conversion. It's okay to do a little bit of lifting and shifting >> This comes in after the task. >> Yeah, and then finally, and probably the most important is you got to have that relationship with the lines of business, your users, get them involved, begin that cultural shift. So I think great recipe Lester for safe cloud migration. I really appreciate your time. I'll give you the final word if you will bring us home. >> All right. Well, I think the journey to the cloud it's a tough one. You will save money, I have heard people say, you got to the cloud, it's too expensive, it's too this, too that, but really, there is an opportunity for savings. I'll tell you when I run data services as a PaaS service in the cloud, it's wonderful because I can scale up and scale down almost by virtually turning a knob. And so I'll have complete control and visibility of my costs. And so for me, that's very important. Io also, it gives me the opportunity to really ring fence my sensitive data, because let's face it, most organizations like being in a cheese grater when you talk about security, because there's so many ways in and out. So I find that by consolidating and bringing together the crown jewels, if you will. As a security practitioner, it's much more easy to control. But it's very important. You can't get there without some automation and automating this discovery and analysis process. >> Well, great advice. Lester, thanks so much. It's clear that the capex investments on data centers are generally not a good investment for most companies. Lester, really appreciate, Lester waters CTO of Io-Tahoe. Let's watch this short video and we'll come right back. You're watching The Cube, thank you. (upbeat music)

(upbeat music) >> Reporter: From around the globe, it's The Cube with digital coverage of enterprise data automation and event series brought to you by Io-Tahoe. >> Okay, we're back. Focusing on enterprise data automation, we're going to talk about the journey to the cloud. Remember, the hashtag is data automated. We're here with Lester Waters who's the CTO of Io-Tahoe, Lester, good to see you from across the pond on video, wish we were face to face, but it's great to have you on The Cube. >> Also I do, thank you for having me. >> Oh, you're very welcome. Hey, give us a little background on CTO, you got a deep expertise in a lot of different areas, but what do we need to know? >> Well, David, I started my career basically at Microsoft, where I started the Information Security Cryptography Group. They're the very first one that the company had and that led to a career in information security and of course, as you go along with the information security, data is the key element to be protected. So I always had my hands in data and that naturally progressed into a role with Io-Tahoe as their CTO. >> Guys, I have to invite you back, we'll talk crypto all day we'd love to do that but we're here talking about yeah, awesome, right? But we're here talking about the cloud and here we'll talk about the journey to the cloud and accelerate. Everybody's really interested obviously in cloud, even more interested now with the pandemic, but what's that all about? >> Well, moving to the cloud is quite an undertaking for most organizations. First of all, we've got as probably if you're a large enterprise, you probably have thousands of applications, you have hundreds and hundreds of database instances, and trying to shed some light on that, just to plan your move to the cloud is a real challenge. And some organizations try to tackle that manually. Really what Io-Tahoe is bringing is trying to tackle that in an automated version to help you with your journey to the cloud. >> Well, look at migrations are sometimes just an evil word to a lot of organizations, but at the same time, building up technical debt veneer after veneer and year, and year, and year is something that many companies are saying, "Okay, it's got to stop." So what's the prescription for that automation journey and simplifying that migration to the cloud? >> Well, I think the very first thing that's all about is data hygiene. You don't want to pick up your bad habits and take them to the cloud. You've got an opportunity here, so I see the journey to the cloud is an opportunity to really clean house, reorganize things, like moving out. You might move all your boxes, but you're kind of probably cherry pick what you're going to take with you and then you're going to organize it as you end up at your new destination. So from that, I get there's seven key principles that I like to operate by when I advise on the cloud migration. >> Okay. So, where do you start? >> Well, I think the first thing is understanding what you got, so discover and cataloging your data and your applications. If I don't know what I have, I can't move it, I can't improve it, I can't build up on it. And I have to understand there is dependency, so building that data catalog is the very first step. What do I got? >> Now, is that a metadata exercise? Sometimes there's more metadata than there is data. Is metadata part of that first step or? >> In deed, metadata is the first step so the metadata really describes the data you have. So, the metadata is going to tell me I have 2000 tables and maybe of those tables, there's an average of 25 columns each, and so that gives me a sketch if you will, of what I need to move. How big are the boxes I need to pack for my move to the cloud? >> Okay, and you're saying you can automate that data classification, categorization, discovery, correct using math machine intelligence, is that correct? >> Yeah, that's correct. So basically we go, and we will discover all of the schema, if you will, that's the metadata description of your tables and columns in your database in the data types. So we take, we will ingest that in, and we will build some insights around that. And we do that across a variety of platforms because everybody's organization has you've got a one yeah, an Oracle Database here, and you've got a Microsoft SQL Database here, you might have something else there that you need to bring site onto. And part of this journey is going to be about breaking down your data silos and understanding what you've got. >> Okay. So, we've done the audit, we know what we've got, what's next? Where do we go next? >> So the next thing is remediating that data. Where do I have duplicate data? Often times in an organization, data will get duplicated. So, somebody will take a snapshot of a data, and then ended up building a new application, which suddenly becomes dependent on that data. So it's not uncommon for an organization of 20 master instances of a customer. And you can see where that will go when trying to keep all that stuff in sync becomes a nightmare all by itself. So you want to understand where all your redundant data is. So when you go to the cloud, maybe you have an opportunity here to consolidate that data. >> Yeah, because you like to borrow in an Einstein or apply an Einstein Bromide right. Keep as much data as you can, but no more. >> Correct. >> Okay. So you get to the point to the second step you're kind of a one to reduce costs, then what? You figure out what to get rid of, or actually get rid of it, what's next? >> Yes, that would be the next step. So figuring out what you need and what you don't need often times I've found that there's obsolete columns of data in your databases that you just don't need, or maybe it's been superseded by another, you've got tables that have been superseded by other tables in your database. So you got to understand what's being used and what's not and then from that, you can decide, "I'm going to leave this stuff behind, "or I'm going to archive this stuff "cause I might need it for data retention "or I'm just going to delete it, "I don't need it at all." >> Well, Lester, most organizations, if they've been around a while, and the so-called incumbents, they've got data all over the place, their data marts, data warehouses, there are all kinds of different systems and the data lives in silos. So, how do you kind of deal with that problem? Is that part of the journey? >> That's a great point Dave, because you're right that the data silos happen because this business unit is chartered with this task another business unit has this task and that's how you get those instantiations of the same data occurring in multiple places. So as part of your cloud migration journey, you really want to plan where there's an opportunity to consolidate your data, because that means there'll be less to manage, there'll be less data to secure, and it'll have a smaller footprint, which means reduced costs. >> So, people always talk about a single version of the truth, data quality is a huge issue. I've talked to data practitioners and they've indicated that the quality metrics are in the single digits and they're trying to get to 90% plus, but maybe you could address data quality. Where does that fit in on the journey? >> That's, a very important point. First of all, you don't want to bring your legacy issues with you. As the point I made earlier, if you've got data quality issues, this is a good time to find those and identify and remediate them. But that can be a laborious task. We've had customers that have tried to do this by hand and it's very, very time consuming, cause you imagine if you've got 200 tables, 50,000 columns, imagine, the manual labor involved in doing that. And you could probably accomplish it, but it'll take a lot of work. So the opportunity to use tools here and automate that process is really will help you find those outliers there's that bad data and correct it before you move to the cloud. >> And you're just talking about that automation it's the same thing with data catalog and that one of the earlier steps. Organizations would do this manually or they try to do it manually and that's a lot of reason for the failure. They just, it's like cleaning out your data like you just don't want to do it (laughs). Okay, so then what's next? I think we're plowing through your steps here. What what's next on the journey? >> The next one is, in a nutshell, preserve your data format. Don't boil the ocean here to use a cliche. You want to do a certain degree of lift and shift because you've got application dependencies on that data and the data format, the tables on which they sit, the columns and the way they're named. So, some degree you are going to be doing a lift and shift, but it's an intelligent lift and shift using all the insights you've gathered by cataloging the data, looking for data quality issues, looking for duplicate columns, doing planning consolidation. You don't want to also rewrite your application. So, in that aspect, I think it's important to do a bit of lift and shift and preserve those data formats as they sit. >> Okay, so let me follow up on that. That sounds really important to me, because if you're doing a conversion and you're rewriting applications, that means that you're going to have to freeze the existing application, and then you going to be refueling the plane as you're in midair and a lot of times, especially with mission critical systems, you're never going to bring those together and that's a recipe for disaster, isn't it? >> Great analogy unless you're with the air force, you'll (mumbles) (laughs). Now, that's correct. It's you want to have bite-sized steps and that's why it's important to plan your journey, take these steps. You're using automation where you can to make that journey to the cloud much easier and more straightforward. >> All right, I like that. So we're taking a kind of a systems view and end to end view of the data pipeline, if you will. What's next? I think we're through. I think I've counted six. What's the lucky seven? >> Lucky seven, involve your business users. Really, when you think about it, your data is in silos. Part of this migration to the cloud is an opportunity to break down these silos, these silos that naturally occur as part of the business unit. You've got to break these cultural barriers that sometimes exist between business and say, so for example, I always advise, there's an opportunity here to consolidate your sensitive data, your PII, your personally identifiable information, and if three different business units have the same source of truth for that, there's was an opportunity to consolidate that into one as you migrate. That might be a little bit of tweaking to some of the apps that you have that are dependent on it, but in the long run, that's what you really want to do. You want to have a single source of truth, you want to ring fence that sensitive data, and you want all your business users talking together so that you're not reinventing the wheel. >> Well, the reason I think too that's so important is that you're now I would say you're creating a data driven culture. I know that's sort of a buzz word, but what it's true and what that means to me is that your users, your lines of business feel like they actually own the data rather than pointing fingers at the data group, the IT group, the data quality people, data engineers, saying, "Oh, I don't believe it." If the lines of business own the data, they're going to lean in, they're going to maybe bring their own data science resources to the table, and it's going to be a much more collaborative effort as opposed to a non-productive argument. >> Yeah. And that's where we want to get to. Data apps is key, and maybe that's a term that's still evolving. But really, you want the data to drive the business because that's where your insights are, that's where your value is. You want to break down the silos between not only the business units, as I mentioned, but also as you pointed out, the roles of the people that are working with it. A self service data culture is the right way to go with the right security controls, putting on my security hat of course in place so that if I'm a developer and I'm building a new application, I'd love to be able to go to the data catalog, "Oh, there's already a database that has the customer "what the customers have clicked on when shopping." I could use that. I don't have to rebuild that, I'll just use that as for my application. That's the kind of problems you want to be able to solve and that's where your cost reductions come in across the board. >> Yeah. I want to talk a little bit about the business context here. We always talk about data, it's the new source of competitive advantage, I think there's not a lot of debate about that, but it's hard. A lot of companies are struggling to get value out of their data because it's so difficult. All the things we've talked about, the silos, the data quality, et cetera. So, you mentioned the term data apps, data apps is all about streamlining, that data, pipelining, infusing automation and machine intelligence into that pipeline and then ultimately taking a systems view and compressing that time to insights so that you can drive monetization, whether it's cut costs, maybe it's new revenue, drive productivity, but it's that end to end cycle time reduction that successful practitioners talk about as having the biggest business impact. Are you seeing that? >> Absolutely, but it is a journey and it's a huge cultural change for some companies that are. I've worked in many companies that are ticket based IT-driven and just do even the marginalist of change or get insight, raise a ticket, wait a week and then out the other end will pop maybe a change that I needed and it'll take a while for us to get to a culture that truly has a self service data-driven nature where I'm the business owner, and I want to bring in a data scientist because we're losing. For example, a business might be losing to a competitor and they want to find what insights, why is the customer churn, for example, happening every Tuesday? What is it about Tuesday? This is where your data scientist comes in. The last thing you want is to raise a ticket, wait for the snapshot of the data, you want to enable that data scientist to come in, securely connect into the data, and do his analysis, and come back and give you those insights, which will give you that competitive advantage. >> Well, I love your point about churn, maybe it talks about the Andreessen quote that "Software's eating the world," and all companies are our software companies, and SaaS companies, and churn is the killer of SaaS companies. So very, very important point you're making. My last question for you before we summarize is the tech behind all of these. What makes Io-Tahoe unique in its ability to help automate that data pipeline? >> Well, we've done a lot of research, we have I think now maybe 11 pending patent applications, I think one has been approved to be issued (mumbles), but really, it's really about sitting down and doing the right kind of analysis and figuring out how we can optimize this journey. Some of these stuff isn't rocket science. You can read a schema and into an open source solution, but you can't necessarily find the hidden insights. So if I want to find my foreign key dependencies, which aren't always declared in the database, or I want to identify columns by their content, which because the columns might be labeled attribute one, attribute two, attribute three, or I want to find out how my data flows between the various tables in my database. That's the point at which you need to bring in automation, you need to bring in data science solutions, and there's even a degree of machine learning because for example, we might deduce that data is flowing from this table to this table and upon when you present that to the user with a 87% confidence, for example, and the user can go, or the administrator can go. Now, it really goes the other way, it was an invalid collusion and that's the machine learning cycle. So the next time we see that pattern again, in that environment we will be able to make a better recommendation because some things aren't black and white, they need that human intervention loop. >> All right, I just want to summarize with Lester Waters' playbook to moving to the cloud and I'll go through them. Hopefully, I took some notes, hopefully, I got them right. So step one, you want to do that data discovery audit, you want to be fact-based. Two is you want to remediate that data redundancy, and then three identify what you can get rid of. Oftentimes you don't get rid of stuff in IT, or maybe archive it to cheaper media. Four is consolidate those data silos, which is critical, breaking down those data barriers. And then, five is attack the quality issues before you do the migration. Six, which I thought was really intriguing was preserve that data format, you don't want to do the rewrite applications and do that conversion. It's okay to do a little bit of lifting and shifting >> This comes in after the task. >> Yeah, and then finally, and probably the most important is you got to have that relationship with the lines of business, your users, get them involved, begin that cultural shift. So I think great recipe Lester for safe cloud migration. I really appreciate your time. I'll give you the final word if you will bring us home. >> All right. Well, I think the journey to the cloud it's a tough one. You will save money, I have heard people say, you got to the cloud, it's too expensive, it's too this, too that, but really, there is an opportunity for savings. I'll tell you when I run data services as a PaaS service in the cloud, it's wonderful because I can scale up and scale down almost by virtually turning a knob. And so I'll have complete control and visibility of my costs. And so for me, that's very important. Io also, it gives me the opportunity to really ring fence my sensitive data, because let's face it, most organizations like being in a cheese grater when you talk about security, because there's so many ways in and out. So I find that by consolidating and bringing together the crown jewels, if you will. As a security practitioner, it's much more easy to control. But it's very important. You can't get there without some automation and automating this discovery and analysis process. >> Well, great advice. Lester, thanks so much. It's clear that the capex investments on data centers are generally not a good investment for most companies. Lester, really appreciate, Lester waters CTO of Io-Tahoe. Let's watch this short video and we'll come right back. You're watching The Cube, thank you. (upbeat music)

>> Hi, I'm Katie Kupec, Global Portfolio Product Marketing Manager for IBM Master Data Management. Master Data Management is a key part within the DataOps toolchain to deliver a trusted, complete view of your customers, products and to offer unique and personalized digital experiences. To learn more about this, join us at our DataOps crowd chat event on May 27th. Hope to chat with you there.

(upbeat music playing) >> Announcer: Live from San Diego, California, it's theCUBE! Covering KubeCon and CloudNativeCon, brought to you by Red Hat, the cloud native computing foundation and its ecosystem partners. >> Welcome back to theCUBE, here at KubeCon, CloudNativeCon 2019 in San Diego, I am Stu Miniman John Troyer is my co-host and joining us is one of our esteemed Cube alumni multi-time guests. Steve Herrod who is the managing director at General Catalyst. Steve, thanks so much for joining us. Always great to see you. >> It's good to see you again. >> Stu: All right I'm having >> And John. >> A flashback meeting with the two of you at a certain campus in Palo Alto and the like. But, you know it's interesting Steve, before we get into this technology, we kicked off this morning talking about a company, Docker. We knew Docker from the early on. I said, look Docker had the opportunity to be this generation's VM-ware. It has had a huge impact on the market. You know, we wouldn't have 12 thousand people here if it wasn't for them. Give us your take kind of as to, you know, this wave of technology and we'll start there. >> Yeah, well I guess I'll start with Docker the company. I mean, it just shows you boy, it's hard to build big companies these days and I think there will be plenty of people talking about why that didn't work out or did work out. Maybe there was too much stuff given to open source. Maybe not enough, maybe there isn't enough community. But I do think, I think that's the tale of just how hard it is to be out in this world. But on the flip side they certainly moved for the idea of containers and got things going. We always have a saying in the venture business, actually in the startup business, which is it's sometimes the second mouse that gets the cheese. Someone's got to break a little glass and then sometimes someone else comes in afterwards and gets some of the reward for it. >> Well Steve this is a sprawling ecosystem. We went from 8 thousand people last year, 4 thousand the year before to over 12 thousand, and this ecosystem keeps growing. You've got a portfolio company that launched this week. You're checking out the show floor. Maybe let's start with the new one coming out from your side. >> Yeah you know I have several startups that are here but I think what's been interesting is the opportunity to create new companies. If you look at the, I'm sure you've covered a lot of them. But if you look at the sponsor sheets here, there's literally hundreds of booths that you can go see and many of which are in similar areas, many of which are open source. So it's really a challenge, like as you all trained interviewers and me trained looking at the space. Think how complex it is to a customer right now. Do that, think about like which service mesh do I pull together with this and that and which command line and which API tool, so I think that's both the challenge and the opportunity you often see this early on. One company that we just had coming out is called Render and their idea is to build an application platform service kind of on top of all this and just to hide it all from the user which I think is, I think that's what always happens in these ecosystems. You get so many players and then someone will be the bundler and make a suite out of it. Or someone will write a service on top of it all and take it away from you. So I think it's sort of a healthy part of a rapidly changing ecosystem. And Render will be doing some interesting things, but they talk to Application developers, not to infrastructure people. App developers don't want to know about any of this. >> Well we're sitting here at KubeCon in the midst of kind of, right at that margin, right at that boundary between from one perspective it looks very developer-y, But from another perspective, this seems very operator-y here. How do you see, in the market in the place, with the buyers, the CIOs or the technical buyers out there. I mean how are you looking at infrastructure versus developers and cloud et cetera? >> It's funny, you know we're all infrastructure people for the most part. What I often say, I know you all know that as well, like at the end of the day infrastructure is only there to run applications. It has no other purpose in life except to be a great place to run applications. But it's also accountable for doing a lot of the things you need. It has to make it run fairly at a certain performance. It has to make sure it's safe from attack. It needs to make sure the data is backed up. So I always just try to think about that when I'm looking at these startups, and we were just talking about this before the show. When I go up to one of the booths and I ask, I usually ask, how do you make someone's life better? Sometimes you get someone who's not the most senior person at the company and they'll quickly go into the technology on how it's this or that. But if you can't frame it in the context of how some enterprises' applications are better, faster, safer then it's really not that interesting, I think, to a CIO that has all these decision making. So, anyway I keep coming back to that with what ever infrastructure or application companies out there and try to wonder what's going on. >> Yeah, no I do really like that as we often frame it, it's what is the business value? It's, you know, nobody really has a problem that I need to rub Kubernetes on. Yes, I need agility, I need you know, the result of what having a distributed architecture drives from my business is what I need. Not the niggling little details there. Um, so I love that piece of what you do better for a company. The other thing, I walk around and I talk to some of these companies and some of them, I scratch my head a little bit as to the oh well I created a cool project, and we've open sourced it and that's my business. And as you know we've talked about the cautionary tale of Docker. Where are we with open source and business model and what's your latest take on that? >> Boy, that is ever evolving. It's funny though, if you look at even just the last ten years since you've been covering things. The go to model for most open source companies has shifted from maybe supportive subscription to really, some of them are open core meaning that parts of it are closed source. But, more and more that the really well to do ones are running them as a service. So that tends to be what we look for now is, whether you're running it directly, or you're doing something with a Microsoft, Google, Amazon where you get some of the revenue from it, which is a big, a big if. That seems to be one of the better ways to consume it and the people who have control over the software should be the best at operationalizing it. So that's kind of the change that we've seen as of late. >> Yeah, quick follow up on that, when we look at the hyper scale, the public clouds. Their marketplaces are getting more and more, you know, it's just a big force in the marketplace. Especially AWS, but Azure's pushing that way and Google to some extent there. Do you give any advice to your portfolio customers? How they should think about their relationships with the big cloud players? >> Well yeah, I mean that's one of the biggest discussions, not even just for our tech companies, but our commerce companies and everywhere else. But I do think what's kind of interesting, in many cases we're seeing the companies talk about maybe Amazon or someone is running that software as a service and it's maybe it's a little older version or maybe it's not all the bells and whistles. So there's certainly a case where good enough is good enough and it kind of crushes the startup, but you also hear a fair amount of tales of where it introduces them to this concept for the first time and then they're going to move over to perhaps the best of breed case, so obviously getting that right is a big job for the founder as well as for an investor. But, um I really see it as a mixed bag. The notion of being introduced to a customer at a lower cost than ever before matters a lot if they then switch to you. >> Well Steve, another boundary that you're sitting at is the boundary between all these technology providers and the customer. Any particular observations on trends over in the customer side? Are people looking to save money, are people feeling good, are the techies really leading the adoption? Is CIO down? Digital transformation? I mean, you're sitting right there in the middle. >> Yeah I mean the good news for I think all startups are that software matters and the digital transformation that's been going on for many, many years continues in a broad way. I would say at the end of the day though, the one question that I almost ask just back to your point on business value. I ask any startup, tell me why you are at least 10 times better than everyone else in this space. And because it is, the bad news of so many startups and so many cool ideas is how's anyone to choose? So if you ask any of your CIOs, they're just massively confused. They try to look for a bigger vendor who could possibly bundle it all together and make it a suite. That's super enticing as you know to all these guys. But when you have this much churn and change going on, you know someone has to step into that role, so I would just say that the ideal thing is you have smaller number of vendors, that never works with a lot of rapid innovation so somewhere in the middle you need to have startups that are really good at bundling in with other folks and fitting into APIs and doing that. >> Alright, so Steve, we've had an interesting view on what's going on in the security industry this week and I know you've got a perspective on it. Our team did the AWS reinforce show in Boston and it was generally upbeat, talking about all the great things that cloud's doing and you know, modernize everything we're doing. Pat Gelsinger from VMware, you know, banging on the table at VMware saying you know, we need a do-over, we need to start over with security. Here at this show, if some people are very cautiously optimistic that we've solved a bunch of the problems of security. You know, where in your view are we, and where are we going? >> I think we'll never be done with security. However, I do think we've reached a maturity level, if you, well, you were here. A couple years ago, there were so many security companies just for containers and I think, you know that's interesting to some extent, but, every CIO is going to have a mixed environment. And so I think what you see this year and what you saw with Palo Alto's acquisitions, so my companies Alumio I know you've talked to. It's really saying let's have one master policy and have it actually then go out and talk to Amazon, talk to my local infrastructure, talk to containers, talk to server lists. That will be the next wave of things going on. But, um, I think whenever you see a maturing of a company like this, the management tools and the security tools that have to inter operate start to really make a showing. And I actually see that quite a bit in this show, so that's a sign of a little bit of maturity going on here. >> Okay, last thing, Steve, I guess, what's catching your eye? Anything interesting or spaces there that you'd call out that we haven't already touched on? >> Well, I spend a lot of time these days actually on, and I hesitate to say it, but on AI. And I mean specifically it is such a hyped term and it's used in many ways like cloud used to be used, so it's just sort of a marketing term in many ways. But specifically, the picks and shovels that are enabling that, many of which show up here too because it is being deployed in containers, that sort of thing. So certainly the tools, but more importantly the vertical applications that can have a meaningful benefit from it. And I'll say, same thing as with infrastructure. AI is a means to an end, it's not the actual thing you're trying to do. But there's real, there's been a real advance there and so I'm really enjoying watching where you get these 10x improvements because you're using the data and AI there. So I continue to love infrastructure and developer tools and I think especially as they get applied to some of these new areas, like AI. That's where I'm excited about what we'll be seeing. >> Well, Steve, really appreciate you coming by. Congrats to the Demon Render, definitely look to catch up there if we don't catch him this week, we'll get him to our Palo Alto studios sometime. >> Yeah, Render is cool. You can go try it out. Render.com >> All right. For John Troyer, I'm Stu Miniman. Getting towards the end of day 1 of 3 days. Wall to wall coverage. Check out theCUBE.net for all of the coverage, and as always, thanks for watching theCUBE. (upbeat music playing)

>> Narrator: Live from Washington D.C. It's theCUBE. Covering Boomi World '19. Brought to you by Boomi. >> Welcome to theCUBE. Lisa Martin with John Ferrier. We are in Washington D.C., at Boomi World '19. John and I have been here now for two days, and we're pleased welcome another CUBE alumni back to our program, Michael Morton, the CTO of Boomi, Michael J. Morton. >> Thank you! It's so great to be back with you guys. >> Great to see you. >> I love this. This is great. >> So we were geeking out the last day and a half, John and I were, with all of our guests and realized Booomi World 2018 was only 11 months ago. >> John: Yup. >> So here we are in D.C. Lots of news around fed rant marketplace certification. But in such a short period of time, Boomi has scaled to 9,000 plus customers in over 80 countries. Your partner ecosystem is now over 580. All in 11 months. And 11 months ago, one of the things that was very clear from all of the Boomi execs is we're going to redefine the i in iPaaS to be intelligence. Now here we are, fast track a few months later, we're going to be talking about, Boomi is talking about, redefining that i to be intelligent insights. Cool stuff. Talk to us about the insights. >> Okay, so let's talk about intelligence first. So everybody's intelligence happy of course, but we've been very disciplined of actually being articulate about what does intelligence mean, not just the label. So we have a history of intelligence being how can you facilitate customers building solutions on Boomi faster. That's our legacy. And so we'll always continue to add new features to the product, but we had an opportunity that we realized we kept in our back pocket for a little while, right? And that's around insights. So we knew that the way the world uses Boomi is to integrate data. They connect the things. They move data. But now we're kind of shifting a little bit and saying it defines what your business is doing, not what your data's doing. Right? So now comes insights, the first for any iPaaS to do, is now we can intelligently tell you what is your business doing. So now we had to make a decision. We can't just advertise it and say we do this, right? And hey, wave our hands. So we said we're going to pick a business challenge, not a very common one. Just kidding, of course. What's a business challenge that every business has? Data privacy. So we chose the insights to say we want to help customers address a business challenge of data privacy. It makes perfect sense. If Boomi is the traffic to running your business about moving data, what's data privacy? It's about getting your arms around the movement of your data. So it just was a perfect fit, for an integration platform as a service, to expose, in a much different way, where is the data about your business actually coming and going? >> Is it going to be part of the product, chargeable, free? How're you guys thinking about these insights? Is it going to be a module? Is it going to be a connector? How do you guys think about the insights piece of it from a consumption stand point, from a customer stand point. >> Okay, so I'll take it one step at a time. I will just be honest and say we have yet to decide is it a charge for feature? We're still evolving it, but consumption's a very important question, so today what we're doing is we have this capability working today. We talked about it on stage, very comfortable about speaking about it, because we're working with a set of customers that gave us real feedback about what's important and what's not important. The consumption's a very interesting question, because depending on the role, right? If you are a chief security officer, what do you want to see? Do you want to see PDFs? Do you want to see reports? Or do you want APIs to get the data to consume into something else? So, one of our to do's is consumption. How do you want to receive this information? So this is actually in the works. >> So, I can see policy and AI being helpful there. You mentioned privacy. I want to get to that in a second. But why not security? That's the number one problem, too. Data, privacy, and security. Is it just too elusive? Or is it too hard? >> Michael: To me, they go together. >> Okay, so explain. What's going on, how does security fit in to this? >> Yep. I mean, I think there's many aspects of security obviously. But I mean security from an access standpoint, all right? So I'll take the position of access. One of the reasons why customers buy Boomi today is they want to expose a certain amount of data to consumers, either from monetization or to an application or to a consumer or to a website, right? And so one type of security is how do you limit the data that you get access to? And so today I'll go back to intelligence or insights. >> (chuckling) Exactly, same. >> It is not out of the realm of possibility that we actually show you who's accessing the data. >> Yeah, I mean we've seen this moving around. That's when the thieves are also moving around, too, and the bad actors. That's a good observation opportunity. And that's kind of where this comes from, right? This whole ability to observe, observability. >> That's right. Observe access. I mean, impersonations is a very popular thing, you can impersonate people, but the whole ability to observe inbound requests, right? I mean, there's always traffic controls on API gateways and things like that, which we'll fully support. But security? I mean, it comes with access. >> I want to get your thoughts on a couple things while you're here. Observability remind me of this cloud 2.0 conversation we've been having on theCUBE. And we're kind of goofing on web 2.0, cloud 2.0. Cloud 1.0, Amazon storage, computes, scale up, everyone's born there, loves it, no problem, no issues, just grow and buy as you go. It's great stuff. At some point when you're an enterprise, it's not that easy. >> Michael: Right. >> So, from cloud 2.0, observability has really taken network management to a whole 'nother level. And it's a data problem. So people going public, SignalFx got acquired, it's a whole industry now. Automation is evolving out of the configuration management area. RPA has got some AI in it. So if you connect the dots here, I can see you guys know where I'm going with this. >> Yep, yep. >> Observability is data. Automation is about making things easier. >> Michael: Yep. >> How do you see those components fitting into the Boomi world? Because architecturally they're now building blocks for either conversational AI or some sort of insights and intelligence. What is, what's the framework, what's the building blocks to make all this data value come to life? How would you talk about that? >> Well, I mean, you're asking, I broke down your whole tirade there into many sections already. >> John: Tirade, good word. That's a great word. >> So let's talk about, in relationship to Boomi, you used the word infrastructure. You used the word network. You threw a lot of things in there. >> John: Tirade, that's for sure. >> And it's like, okay, now I have a soup. So I'll just try to pick pieces out of the soup that I think are relevant. So, again I'll tie back to intelligence a little bit. Boomi, when you use the product, there's an engine that you run. It's a container, right? So you build in the cloud and Boomi, and then you choose where you want to run, right? And part of our efforts around intelligence is to keep that run time environment healthy and maybe scaling, all right? So automation for Boomi will be, let me look at the workloads that you are using to run on Boomi, and predict when I need to scale your environment. Automation. You'll see slowly even more automation capabilities to make it easier for scaling, sizing. So that's one aspect of hopefully answering what you're asking and trying to dissect a little bit about automation. So one will be automation for ourselves. I mean to help basic, just don't think about your moving around time anymore. It's just going to work. It's just going to scale. So we are planning to get to that point where it's fully automated. >> And that's efficiency for you. Creates value. >> Michael: Yeah, correct. >> Deploy resources to other areas. >> Yes, but here's something else to consider is it also saves our support organization the call. That's the most important thing, is the company when you scale, is you have to put in your company cultures. You build the product. What can you do to avoid that service call coming in? So I do want to talk about culture a little bit, even for intelligence. And I like to give a very simple example about how does a product like Boomi change their culture about building in intelligence into the product. And I have a great example. So let's say I'm a developer that's been assigned to put a new feature in Boomi. And it has five configuration parameters that you need to ask the customer to configure before you can use it. Why? Why five? Can't I just tell the customer what they need for three of those? And now there's only two? And it gets people thinking, oh yeah, I guess I could have gone back into their metadata. They already did this once. So why don't I grab that value that they already did? And that's an interesting mindshift when you think about it is instead of five, I challenge you to get down to two. Get it down to two. So, intelligence is not just an outward facing customer feature. It's a development culture. >> You talk about operating systems. It's really a great conversation, because you know when you look at data, and then and what you're talking about, back to the demo and the privacy conversation that you guys are talking about, is if you think about data holistically, as a system, not as a isolated thing, 'cause that's what you're getting at. It's a systems approach. >> Michael: It is. >> The data's somewhere. Why you have another form? You get it, pull it in, automation. But as you did the demo, people were buzzing about mind blowing, whoa! Look what's flying around! What was the purpose behind the demo? What was your main point? What were you trying to get across in that demo that you wanted people to walk away with? Was it that there's threats out there that's an issue or their problems are going to be solved? Or is this cool? What was the main driver behind the demo and the privacy as the first step? >> That's a very good question. And so I'll give you the first thing that comes to mind. The company and data is a living ecosystem. It never stops. It's always in motion. It's harder to manage. It's harder to observe. Boomi is meant to basically build the engine of your living ecosystem. All right? How can you possibly as a human get insight into that ecosystem? It's impossible. But with a product like Boomi, we're giving you insights into the living part of your business. That's the really the theme. Now applying to, you said threats. Good word. Threats to what? In this case, it's threats to being fined by GDPR. It's not necessarily a security breach. But fines are real now. I mean there's monetary loss. And so that's the message. >> What have some of the, you mentioned the word mindshift in your demo this morning, you mentioned it a minute ago, when you've been working with some of these customers helping you evaluate this intelligent insight capability, what has been the mindshift there, in terms of exposing this information? What are some of the things these customers have been really like whoa, really surprised that this intelligent insights can show them, that they just have no idea about with respect to their business? >> Yep, great question. Because I gauge success on the reaction, all right? And in this case the human reaction is actually seeing a map between countries with lines. It's actually that simple, to visually be able to see as a human, the flow of data. Then on top of that, the flow of private data. >> It's like an x-ray. It's like looking at the bloodstream. >> Ah, that's a good analogy. >> Yeah, I mean the blood's flowing, all aspects. >> Right, you can't see your blood. I can't see it, right? I know it's there. >> John: (laughing) Yeah, I think so. It's red. >> I hope so. >> That's like Superman. You can see through the data points to get into what you want because the data's flowing. You guys make that observable. Now what about the data that's not in the Boomi platform? Connectors, how would people, I mean so obviously not, Boomi's not everywhere, you've got 9,000 customers, not 900,000 customers. So there's a lot of other businesses that aren't using Boomi. Can I leverage it with other platforms? How do you think about that? >> Again I'm going to interpret what you're asking. There's many other sources of data of course that people are not using Boomi to access. But if, this may be a bit of a salesman opinion, the more you use Boomi, the more insights you're going to get. So why wouldn't you connect to those things? >> So but connecting means I can just connect to those things. I'll give you a hypothetical, real world example. We have so much data on these CUBE interviews. In fact, after this CUBE interview's done, your words will be transcribed into a transcript, will be linked to the video. We can make clips out of it. It's a big data set. When people will share those clips, we know who's sharing the data. So we are there, a lot of good data. So I would be like hey, I'd like to tap into that Boomi. Why build it? I can just connect. So do I connect all my applications into Boomi or just my data? >> That's actually interesting. Now, of course, I'm the CTO of the business. I'm going to invent stuff on the fly 'cause that's what I do, right? You have metadata about, you have metadata about these files? >> We have APIs, metadata, all kinds of stuff, yeah. >> What we would expect would be this. You would need to, if you're looking for other insights, all right, you're going to now see start combining data. So analytics is really about taking multiple sources of data, putting it in one place, and mining it for new insights because of correlating things together. >> And that validates your point about being that sales rep, because more data, the better data. Look it, we just did a master class here. Master and student. Real time, on the fly. >> This is the second master class you guys have done. At Dell Technologies World, there was a master class on block chain I sat in between you two. >> I got to say, that's a new format we should look at, this real time invention. >> Michael: I love it. >> Well, Michael, thank you so much for joining John and me on theCUBE. It's been really exciting to see, in 11 months, what's transpired for Boomi. We can't wait for next Boomi World. I can't wait to hear how this double i intelligent-- >> Maybe another i? >> Insights. I cubed? I three? All right, all right. Won't quote you on that, but we appreciate it. >> Great to see you. >> Very cool stuff. For John Ferrier, I'm Lisa Martin. You're watching theCUBE from Boomi World '19. Thanks for watching. (upbeat music)

>> Live from Atlanta, Georgia. It's theCUBE covering Citrix Synergy Atlanta 2019. Brought to you by Citrix. >> Welcome back to theCUBE's continuing coverage of Citrix Synergy 2019 from Atlanta, Georgia. I'm Lisa Martin, my co-host for the event is Keith Townsend and Keith and I are excited to talk to one of the Citrix Innovation Award nominees, Indiana University. We have a couple of folks from Indiana University joining us, Stephanie Cox, Manager of Virtual Platform Services and Matt Link, Associate Vice President of Research Technologies. Guys, thanks so much for joining Keith and me. >> Thank you Lisa. >> Thank you. >> And thank you Keith. >> It's an honor to be here, yeah. >> And congratulations on Indiana University being nominated for an innovation award. I was talking with Tim Minahan, their CMO yesterday saying there was over a thousand nominations, so to even get down to being in the top three is pretty exciting stuff. >> Yeah. >> Awesome. >> So talk to us a little bit about Indiana University. You guys, this is a big, big big organization lots of folks accessing the network through lots of devices. Matt, let's start with you, give us that picture of what's going on there. >> Yeah, so IU is about 130,000 students across seven campuses. We got about 20,000 faculty and staff across those seven campuses. One of the things that makes us a little unique is, we're a consolidated IT shop. So, there are 1200 of us at IU that support the entire university and all the campuses. And at any one point in time, there could be 200,000 devices touching the network and using those services. >> Big, that's big. >> Big. >> Wow, that is big. Stephanie talk, talk to us about your virtual imp, footprint and how big is the location. How many data centers? What's the footprint? >> Well we have two data centers, one of them is in Indianapolis which is my home. It's one of our larger campuses, we call it Indiana University Purdue University, affectionately IUPUI. There is a data center there but our larger data center is at the flagship campus which is in, Bloomington, Indiana. >> And, to support 100,000 plus people and, you said at any given second, 200,000 devices. How have you designed that Virtual Integral Structure to enable access to students, faculty, et cetera and employees? >> So from the network perspective we have several network master plans that have rolled and we're in our second 10 year network master plan. And, the network master plan is designed to continually upgrade the network, both the physical network, the infrastructure, and the wireless network. In our last 10 year budget for that was around $170 million of investment just to support the network infrastructure. And then, Stephanie rides on top of that as the Virtual Platform with Citrix to deliver the images anywhere on campus, whether it's wirelessly or whether it's connected via network connection. >> Yep. >> So seven campuses is already a bit. If you ever look at a map, Indiana sits right smack dab in the middle of the country. It's a big space, right before we hit record, we were just talking about that drive up I-65 from Indianapolis to Chicago is just, a lot of rural area and, I'm sure part of your mission is to make sure technology and education is accessible to everyone in Indiana. Talk to us about the challenges of getting connectivity and getting material, virtual classrooms to those remote areas. >> Yeah, that's really one of the major strengths of our partnership with Citrix. They are really the premier remote solution connectivity offering at Indiana University. So, we built our Citrix environment to encompass everyone. We wanted to make sure we could have enough licenses and capacity for all of our 130,000 faculty, staff, and students to use the service. Now do they all show up at the same time? No, thank goodness. >> Thankfully. >> But we do offer it to everyone which is, I found, in the education arena, very unique to Indiana University. Another thing to have the consolidated IT and then to be able to offer a service like ours to everyone and not just restrict it to separate pockets of the university. With that, we've been able to then extend, offering of any application or something that you might need for a class to any of our other remote locations. So, if you're a student who is working in or lives in rural Indiana and you want to get an Indiana University degree, you can do that without having to travel to one of our campus sites or locations. We have a very nice online program and just a lot of other options that we've really tried to offer for remote access. >> So Citrix has really enabled this, I think you call it the IUanyWare, Indiana University Anywhere Program. >> Yeah. >> Tell us about opening up this access to everyone over the time that you've been a Citrix customer how many more people can you guesstimate have access now that didn't not too long ago? >> Yeah, I think initially, and Matt would probably know more before me, before I even came on the scene, I believe that the original use case was really just trying to extend what we were already doing on premise in what we call just our Indiana University lab supported areas. Right, so just your small, like the old days when you would go to your college campus and you go into your computer lab, we just really wanted to virtualize, or expand, the access to just those specific types of apps and computers. And that was an early design, since then over the years we've really kind of, just really expanded. Really use the Citrix platform to redesign and distribute how we deliver the applications and the virtual desktops. So, now not only do we service those students who would normally come onto the campus just to use your traditional computer lab, we do a lot of specialty programs for other schools. Like we deliver a virtual desktop for our dentistry students, they actually use that whole platform in the dental clinic to see real patients our, third tier, third year doctors do that. We also replicated that same thing and do it in our speech and hearing sciences for our future audiologists. We have certain professors that have wanted to take the particular course that they're teaching and extend it to different pockets all over the world so we might host a class from Budapest or Africa somewhere else, wherever that faculty and staff has resources that they know they need to get to and their content already virtualized. We work to make that happen all the time. >> That's, a lot of what you just said is first of all, initially, maybe before Citrix being able to provide support in the computer labs for your maybe seven core campuses, now you're giving 130,000 plus individuals anywhere, anytime access. That is, the X multiplier on that is massive. But you're also gone global, it's not just online, you're able to enable professors to teach in other parts of the world, where it was before it was just people that were in Indiana. >> Right. >> That's massive. >> And you're just limited by the network. So that's the only drawback when you go to the rural areas way out, you're just limited by the network. The initial program was really, really thought of as a cost saving measure. We were going to put thin clients out, we wouldn't have to do life cycle replacements for desktop machines that were getting more expensive and more expensive 10 years ago, and now the way that we look at it is IU wants to provide services across the breadth of the organization, and make those services at no additional cost. And open to everybody. Open access to everybody, the AT desktop, for example is one of, Stephanie is, the brainchild behind the AT desktop. Took three years of dedicated hard work to create an environment to support the visually impaired. >> Talk to us more about that, because that was part of the video and that captured my attention immediately. What is AT? >> Accessibility. >> Technology. >> Technology. >> Accessibility Technology. >> Accessible, is it Accessible Technology? >> Accessible Technology. >> Yeah, I always get that wrong. (laughs) >> So, hundreds, thousands, and not just those that are sight and hearing. >> Right. >> Yeah, so one of the things that I think was, it's just a wonderful thing about working at a university, we're able to buy software licenses in a big quantity, large quantity right, because we have that kind of buying power. Software that I normally never would see or get access to even in my private sector, I've been a Citrix engineer for a long time, but when you come to a university and then you're selling or you're getting licenses for 50, 60, 70, 80,000, you get to see some of these products that you don't normally, as a regular consumer, (laughs) you like it but you know you can't really afford it. So, with that when we started looking at all of the different applications that they could buy in a large quantity site license way we thought oh my goodness, let's virtualize these and make sure everybody gets access to them. And the ones that were really attractive to us were the ones for the visually impaired. Sure they're a niche and they're very, very expensive but we thought let's just try it. We'll see how well they perform in a virtual environment and with our Citrix infrastructure underneath they performed quite well, plus the apps have evolved a great deal over just the last four years. So, we were really proud to offer our virtual desktop to our blind students. We had to work really hard to make sure that the speech recognition software was fast enough for them. It turns out that blind people listen to speech really, really, really, really, really, fast and so we had to make sure that we kept our platformer working on it, to keep it sped and updated so that it's usable to them, right. Seems functional to me, but they, it really needed to be like, 10 times faster. After I found that out, after even shooting the award video and spending even more time with them I thought, why did you guys tell me it was slow to you? But yeah it's been an honor, really, to be up for that award but to work with those students, to learn more about their needs, to learn more about the different applications that people write for people with all disabilities. I hope we can do more in that space. >> So the young man, in, at IUPUI. >> Yes. >> I don't remember his name. >> Chris Lavilla. >> Chris. >> Yes. >> So share, just quickly about Chris' story. >> If, he watches theCUBE I hope he's listening 'cause I think he's kind of remarkable. >> I think this'll really put some, a little bit of icing on that cake because you're taking an environment and you're empowering a student to do what they want to do, versus what they are able or not able to do, so Chris' story is pretty cool of where he wants to go with his college career. >> Yeah, now I won't say he a big proponent user of the virtual desktop because he's just so advanced, he's like way beyond everything. We're learning from him, but he is Indiana University's I believe I'm saying this right, very first biomedical chemical engineer who is blind since birth, completely blind, yes. >> Wow. >> He is, and he's quite a brilliant young man and we're lucky to have him be our, he will test anything for me, and Mary Stores, who's featured in the video Chris Mire, he's also featured in the video I got to remember their names, I mean, it's a whole, I'm lucky to have a whole community of people that will. Yeah, they know, we want to be there for them, we don't always get it right, but we're going to listen and keep trying to move forward, so. >> But, if you kind of think of, even a what, a year or two ago, not being able to give any of this virtualized desktop access to the visually impaired and how many people are now using it? >> Well we open it up to everyone. We have hundreds and hundreds of users but we know not everyone who uses it is blind. People can, you can use it if you want it or not. We don't really understand why some people prefer to use that one over any other but it does have some advantages, there are different levels of sight impairment too, as I've just been educated right. There are some people who are just at the very beginning of that journey of just losing their sight so, if that happens to be someone that we can extend our environment to it's probably better to use it now and get really familiar with that as you transition to losing your sight later in life, I've been told so. >> So you asked a little bit about the scope of the AT desktop, so I'll layer on a little bit of the scope of IUanyWare. Last year around 65,000 individual unique users over, well over a million logins and-- >> 1.4 million. >> 1.4 million. And the average session time was around 41 minutes. >> That's long. >> So. >> Yeah. >> Our instructors teach with it, our clinicians treat people with it, we've built it to house electronic protected health data. >> So HIPA compliance, got to be critical, right? >> It meets the HIPA standard. >> Right. >> Because you can't say compliance anymore because you can't be compliant with a standard. (Stephanie laughing) They've changed that wording several times in the course of the year. >> We know this. >> So, and we are very familiar with meeting the HIPA standard, we've been doing that for about 12 years now, with, where I came from was the high performance computing area of the university so that's my background that I. >> So, one thing we didn't get a chance touch on, 200,000 devices. We're at Citrix, Citrix is a Microsoft partner. Typically when those companies think of 200,000 users they think for profit, this is a niche use case for 200,000 users. Obviously you guys have gotten some great pricing as part of being an education environment. What I would love to hear is, kind of the research stories because the ability to shrink the world, so to speak high HPC, you're giving access to specialized equipment to people who can't get there normally, you have to be physically in front of GPUs, CPUs, et cetera. What other cool things have been coming out of the research side of the house because of the Citrix enablement? >> So, this is cool I mean. >> You got to, got to. (laughs) >> Right, so one of our groups, Researched Software and Solutions stole the idea from Stephanie to provide a research desktop. >> Borrowed. >> Borrowed. >> Imitation, highest form of flattery, Stephanie. >> That's right, absolutely. So what we've done is we always continually to try to reduce the barriers of entry and access. Supercomputing before, you had to be this tall to ride this ride, well now we're down to here. And, with the hopes that we'll go down even farther. So what we've done is we've taken a virtualized desktop, put it in front of the supercomputers, and now you can be wherever you want to be, and have access to HPC at IU. And that's all the systems, so we have four supercomputers And we have 40 petabytes of spinning disc, 160 petabytes of archival tape library so, we're a large shop. And, we couldn't have done it without looking at what Stephanie has done and really looking at that model differently, right? Because to use HPC before you'd have to use a terminal and shell in. And now, looking at IUanyWare, that gives you just the different opportunity to catch a different and more broad customer base. And I call them customers because we try treat them as customers >> Right. >> And it helps the diversity of what you're doing so last year alone our group, Research Technologies supported 151 different departments. We were on 937 different grants. And we support over 330 different disciplines at IU and so it's deep, but it's also very broad, for as large a campus we are and as large an organization as we are, we're fairly nimble even at 1200 people. >> Wow, from what I've heard it's no wonder that what you've done at Indiana University has garnered you the Innovation Award nominee. I can't imagine what is next with all that you have accomplished. Stephanie, Matt, thank you so much for joining Keith and me, we wish you the best of luck. You can go to Citrix.com, search Innovation Awards where you can vote for the three finalists. We wish you the very best of luck. We'll be waiting with bated breath tomorrow to see who wins. >> So will we, thank you very much. >> Thank you. >> Thank you Lisa. Thank you Keith. >> Our pleasure. For Keith Townsend, I'm Lisa Martin. You're watching theCUBE live from Citrix Synergy 2019. Thanks for watching. (upbeat techno music)

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBEConversation. >> Hi everyone, welcome to the special CUBEConversation. We're in Palo Alto, California, at theCUBE studio. I'm John Furrier, co-host of the CUBE. We're here with Chris Yeh. He's the co-founder and general partner of Blitzscaling Ventures, author of the book Blitzscaling with Reid Hoffman, founder of LinkedIn and a variety of other ventures, also a partner at Greylock Partners. Chris, great to see you. I've known you for years. Love the book, love Reid. You guys did a great job. So congratulations. But the big news is you're now a TV star as one of the original inaugural contestants on the Mental Samurai, just premiered on Fox, was it >> On Fox. >> On Fox, nine o'clock, on which days? >> So Mental Samurai is on Fox, Tuesdays at 9 p.m. right after Master Chef Junior. >> Alright. So big thing. So successful shows. Take us through the journey. >> Yeah. >> It's a new show, so it's got this kind of like Jeopardy vibe where they got to answer tough questions in what looks like a roller coaster kind of arm that moves you around from station to station, kind of jar you up. But it's a lot of pressure, time clock and hard questions. Tell us about the format. How you got that. Gives all the story. >> So the story behind Mental Samurai is it's from the producers of American Ninja Warrior, if you've ever seen that show. So American Ninja Warrior is a physical obstacle course and these incredible athletes go through and the key is to get through the obstacle course. If you miss any of the obstacles, you're out. So they took that and they translated it to the mental world and they said, okay, we're going to have a mental obstacle course where you going to have different kinds of questions. So they have memory questions, sequence questions, knowledge questions, all these things that are tapping different elements of intelligence. And in order to win at the game, you have to get 12 questions right in five minutes or less. And you can't get a single question wrong. You have to be perfect. >> And they do try to jar you up, to kind of scrabble your brain with those devices, it makes it suspenseful. In watching last night at your watch party in Palo Alto, it's fun to watch because yeah, I'm like, okay, it's going to be cool. I'll support Chris. I'll go there, be great and on TV, and oh my, that's pretty interesting. It was actually riveting. Intense. >> Yeah. You have that element of moving around from station to station and it's dramatic. It's kind of a theater presence. But what's it like in there? Give us some insight. You're coming on in April 30th so you're yet to come on. >> Yes. >> But the early contestants, none of them made it to the 100,000. Only one person passed the first threshold. >> Right >> Take us through the format. How many thresholds are there? What's the format? >> Perfect, so basically when a competitor gets strapped into the chair, they call it Ava, it's like a robot, and basically they got it from some company in Germany and it has the ability to move 360 degrees. It's like an industrial robot or something. It makes you feel like you're an astronaut or in one those centrifugal force things. And the idea is they're adding to the pressure. They're making it more of a challenge. Instead of just Jeopardy where you're sitting there, and answering questions and bantering with Alex Trebek, you're working against the clock and you're being thrown around by this robot. So what happens is first you try to answer 12 questions correctly in less than five minutes. If you do that, then you make it through to the next round, what they call the circle of samurai and you win $10,000. The circle of samurai, what happens is there are four questions and you get 90 seconds plus whatever you have left over from your first run, to answer those four questions. Answer all four questions correctly, you win $100,000 and the official title of Mental Samurai. >> So there's only two levels, circle of samurai but it gets harder. Now also I noticed that it's, their questions have certain puzzles and there's certain kinds of questions. What's the categories, if you will, what's the categories they offer? >> Yes, so the different categories are knowledge, which is just classic trivia, it's a kind of Jeopardy stuff. There's memory, where they have something on screen that you have to memorize, or maybe they play an audio track that you have to remember what happened. And then there's also sequence where you have to put things in order. So all these different things are represented by these different towers which are these gigantic television screens where they present the questions. And the idea is in order to be truly intelligent, you have to be able to handle all of these different things. You can't just have knowledge. You can't just have pop culture. You got to have everything. >> So on the candidates I saw some from Stanford. >> Yeah. >> I saw an athlete. It's a lot of diversity in candidates. How do they pick the candidates? How did you get involved? Did your phone ring up one day? Were you identified, they've read your blog. Obviously they've, you're smart. I've read your stuff on Facebook. How did you get in there? (laughs) >> Excellent question. So the whole process, there's a giant casting department that does all these things. And there's people who just cast people for game shows. And what happened with me is many years ago back in 2014, my sister worked in Hollywood when I was growing up. She worked for ER and Baywatch and other companies and she still keeps track of the entertainment industry. And she sent me an email saying, hey, here's a casting call for a new show for smart people and you should sign up. And so I replied to the email and said hey I'm Chris Yeh. I'm this author. I graduate from Stanford when I was 19, blah blah blah blah. I should be on your show. And they did a bunch of auditions with me over the phone. And they said we love you, the network loves you. We'll get in touch and then I never heard. Turns out that show never got the green light. And they never even shot that show. But that put me on a list with these various casting directors. And for this show it turns out that there was an executive producer of the show, the creator of the show, his niece was the casting director who interviewed me back in 2014. And she told her uncle, hey, there's this guy, Chris Yeh, in Palo Alto. I think would be great for this new show you're doing. Why don't you reach out to him. So they reached out to me. I did a bunch of Skype auditions. And eventually while I was on my book tour for Blitzscaling, I got the email saying, congratulations, you're part of the season one cast. >> And on the Skype interviews, was it they grilling you with questions, or was it doing a mock dry run? What was some of interview vetting questions? >> So they start off by just asking you about yourself and having you talk about who you are because the secret to these shows is none of the competitors are famous in advance, or at least very few of them are. There was a guy who was a major league baseball pitcher, there's a guy who's an astronaut, I mean, those guys are kind of famous already, but the whole point is, they want to build a story around the person like they do with the Olympics so that people care whether they succeed or not. And so they start off with biographical questions and then they proceed to basically use flash cards to simulate the game and see how well you do. >> Got it, so they want to basically get the whole story arc 'cause Chris, obviously Chris is smart, he passed the test. Graduate when he's 19. Okay, you're book smart. Can you handle the pressure? If you do get it, there's your story line. So they kind of look from the classic, kind of marketing segmentation, demographics is your storylines. What are some of the things that they said to you on the feedback? Was there any feedback, like you're perfect, we like this about you. Or is it more just cut and dry. >> Well I think they said, we love your energy. It's coming through very strongly to the screen. That's fantastic. We like your story. Probably the part I struggle the most with, was they said hey, you know, talk to us about adversity. Talk to us about the challenges that you've overcome. And I tell people, listen, I'm a very lucky guy. A lot of great things have happened to me in life. I don't know if there's that much adversity that I can really complain about. Other people who deal with these life threatening illnesses and all this stuff, I don't have that. And so that was probably the part I struggled the most with. >> Well you're certainly impressive. I've known you for years. You're a great investor, a great person. And a great part of Silicon Valley. So congratulations, good luck on the show. So it's Tuesdays. >> 9 p.m. >> 9 p.m. >> On fox. >> On Fox. Mental Samurai. Congratulations, great. Great to be at the launch party last night. The watch party, there'll be another one. Now your episode comes out on April 30th. >> Yes. So on April 30th we will have a big Bay area-wide watch party. I'm assuming that admission will be free, assuming I find the right sponsors. And so I'll come back to you. I'll let you know where it's going to be. Maybe we should even film the party. >> That's, well, I got one more question on the show. >> Yeah. >> You have not been yet on air so but you know the result. What was it like sitting in the chair, I mean, what was it personally like for you? I mean you've taken tests, you've been involved with the situation. You've made some investments. There's probably been some tough term sheets here and there, board meetings. And all that experience in your life, what was it compared to, what was it like? >> Well, it's a really huge adrenaline rush because if you think about there's so many different elements that already make it an adrenaline rush and they all combine together. First of all, you're in this giant studio which looks like something out of a space-age set with this giant robotic arm. There's hundreds of people around cheering. Then you're strapped into a robotic arm which basically makes you feel like an astronaut, like every run starts with you facing straight up, right? Lying back as if you're about to be launched on a rocket. And then you're answering these difficult questions with time pressure and then there's Rob Lowe there as well that you're having a conversation with. So all these things together, and your heart, at least for me, my heart was pounding. I was like trying very hard to stay calm because I knew it was important to stay clam, to be able to get through it. >> Get that recall, alright. Chris, great stuff. Okay, Blitzscaling. Blitzscaling Ventures. Very successful concept. I remember when you guys first started doing this at Stanford, you and Reid, were doing the lectures at Stanford Business School. And I'm like, I love this. It's on YouTube, kind of an open project initially, wasn't really, wasn't really meant to be a book. It was more of gift, paying it forward. Now it's a book. A lot of great praise. Some criticism from some folks but in general it's about scaling ventures, kind of the Silicon Valley way which is the rocket ship I call. The rocket ship ventures. There's still the other venture capitals. But great book. Feedback from the book and the original days at Stanford. Talk about the Blitzscaling journey. >> And one of the things that happened when we did the class at Stanford is we had all these amazing guests come in and speak. So people like Eric Schmidt. People like Diane Greene. People like Brian Chesky, who talked about their experiences. And all of those conversations really formed a key part of the raw material that went into the book. We began to see patterns emerge. Some pretty fascinating patterns. Things like, for example, a lot of companies, the ones that'd done the best job of maintaining their culture, have their founders involved in hiring for the first 500 employees. That was like a magic number that came up over and over again in the interviews. So all this content basically came forward and we said, okay, well how do we now take this and put it into a systematic framework. So the idea of the book was to compress down 40 hours of video content, incredible conversations, and put it in a framework that somebody could read in a couple of hours. >> It is also one of those things where you get lightning in a ball, the classic and so then I'd say go big or go home. But Blitzscaling is all about something new and something different. And I'm reading a book right now called Loonshots, which is a goof on moonshots. It's about the loonies who start the real companies and a lot of companies that are successful like Airbnb was passed over on and they call those loonies. Those aren't moonshots. Moonshots are well known, build-outs. This is where the blitzscaling kind of magic happens. Can you just share your thoughts on that because that's something that's not always talked about in the mainstream press, is that a lot of there blitzscaling companies, are the ones that don't look good on paper initially. >> Yes. >> Or ones that no one's talking about is not in a category or herd mentality of investors. It's really that outlier. >> Yes. >> Talk about that dynamic. >> Yeah, and one of the things that Reid likes to say is that the best possible companies usually sound like they're dumb ideas. And in fact the best investment he's been a part of as a venture capitalist, those are the ones where there's the greatest controversy around the table. It's not the companies that come in and everyone's like this is a no-brainer, let's do it. It's the companies where there's a big fight. Should we do this, should we not? And we think the reason is this. Blitzscaling is all about being able to be the first to scale and the winner take most or the winner take all market. Now if you're in a market where everyone's like, this is a great market, this is a great idea. You're going to have huge competition. You're going to have a lot of people going after it. It's very difficult to be the first to scale. If you are contrarian and right you believe something that other people don't believe, you have the space to build that early lead, that you can then use to leverage yourself into that enduring market leadership. >> And one of the things that I observed from the videos as well is that the other fact that kind of plays into, I want to get your reaction, this is that there has to be a market shift that goes on too because you have to have a tailwind or a wave to ride because if you can be contrarian if there's no wave, >> Right. >> right? so a lot of these companies that you guys highlight, have the wave behind them. It was mobile computing, SaaSification, cloud computing, all kind of coming together. Talk about that dynamic and your reaction 'cause that's something where people can get confused on blitzscaling. They read the book. Oh I'm going to disrupt the dry cleaning business. Well I mean, not really. I mean, unless there's something different >> Exactly. >> in market conditions. Talk about that. >> Yeah, so with blitzscaling you're really talking about a new market or a market that's transforming. So what is it that causes these things to transform? Almost always it's some new form of technological innovation, or perhaps a packaging of different technological innovations. Take mobile computing for example. Many of the components have been around for a while. But it took off when Apple was able to combine together capacitative touchscreens and the form factor and the processor strength being high enough finally. And all these things together created the technological innovation. The technological innovation then enables the business model innovation of building an app store and creating a whole new way of thinking about handheld computing. And then based on that business model innovation, you have the strategy innovation of blitzscaling to allow you to grow rapidly and keep from blowing up when you grow. >> And the spirit of kind of having, kind of a clean entrepreneurial segmentation here. Blitzscaling isn't for everybody. And I want you to talk about that because obviously the book's popular when this controversy, there's some controversy around the fact that you just can't apply blitzscaling to everything. We just talk about some of those factors. There are other entrepreneurialship models that makes sense but that might not be a fit for blitzscaling. Can you just unpack that and just explain, a minute to explain the difference between a company that's good for blitzscaling and one that isn't. >> Well, a key thing that you need for blitzscaling is one of these winner take most or winner take all markets that's just enormous and hugely valuable, alright? The whole thing about blitzscaling is it's very risky. It takes a lot of effort. It's very uncomfortable. So it's only worth doing when you have those market dynamics and when that market is really large. And so in the book we talk about there being many businesses that this doesn't apply to. And we use the example of two companies that were started at the same time. One company is Amazon, which is obviously a blitzscaling company and a dominant player and a great, great company. And the other is the French Laundry. In fact, Jeff Bezos started Amazon the same year that Thomas Keller started the French Laundry. And the French Laundry still serves just 60 people a day. But it's a great business. It's just a very different kind of business. >> It's a lifestyle or cash flow business and people call it a lifestyle business but mainly it's a cash flow or not a huge growing market. >> Yeah. >> Satisfies that need. What's the big learnings that you learned that was something different that you didn't know coming out of blitzscaling experience? Something that surprised you, something that might have shocked you, something that might have moved you. I mean you're well-read. You're smart. What was some learnings that you learned from the journey? >> Well, one of the things that was really interesting to me and I didn't really think about it. Reid and I come from the startup world, not the big company world. One of the things that surprised me is the receptivity of big companies to these ideas. And they explained it to me and they said, listen, you got to understand with a big company, you think it's just a big company growing at 10, 15% a year. But actually there's units that are growing at 100% a year. There's units that are declining at 50% a year. And figuring out how you can actually continue to grow new businesses quicker than your old businesses die is a huge thing for the big, established companies. So that was one of the things that really surprised me but I'm grateful that it appears that it's applicable. >> It's interesting. I had a lot of conversations with Michael Dell before, and before they went private and after they went private. He essentially was blitzscaling. >> Yeah. >> He said, I'm going to winner take most in the mature, somewhat declining massive IT enterprise spend against the HPs of the world, and he's doing it and VMware stock went to an all time high. So big companies can blitz scale. That's the learning. >> Exactly. And the key thing to remember there is one of the reasons why somebody like Michael Dell went private to do this is that blitzscaling is all about prioritizing speed over efficiency. Guess who doesn't like that? Wall street doesn't like because you're taking a hit to earnings as you invest in a new business. GM for example is investing heavily in autonomous vehicles and that investment is not yet delivering cash but it's something that's going to create a huge value for General Motors. And so it's really tough to do blitzscaling as a publicly traded company though there are examples. >> I know your partner in the book, Reid Hoffman as well as in the blitzscaling at Stanford was as visible in both LinkedIn and as the venture capitalist of Greylock. But also he was involved with some failed startups on the front end of LinkedIn. >> Yeah. >> So he had some scar tissue on social networking before it became big, I'll say on the knowledge graph that he's building, he built at LinkedIn. I'm sure he had some blitzscaling lessons. What did he bring to the table? Did he share anything in the classes or privately with you that you can share that might be helpful for people to know? >> Well, there's a huge number of lessons. Obviously we drew heavily on Reid's life for the book. But I think you touched on something that a lot of people don't know, which is that LinkedIn is not the first social network that Reid created. Actually during the dot-com boom Reid created a company called SocialNet that was one of the world's first social networks. And I actually was one of the few people in the world who signed up and was a member of SocialNet. I think I had the handle, net revolutionary on that if you can believe that. And one of the things that Reid learned from his SocialNet experience turned into one of his famous sayings, which is, if you're not embarrassed by your first product launch, you've launched too late. With SocialNet they spent so much time refining the product and trying to get it perfectly right. And then when they launched it, they discovered what everyone always discovers when they launch, which is the market wants something totally different. We had no idea what people really wanted. And they'd wasted all this time trying to perfect something that they've theoretically thought was what the market wanted but wasn't actually what the market wanted. >> This is what I love about Silicon Valley. You have these kind of stories 'cause that's essentially agile before agile came out. They're kind of rearranging the deck chairs trying to get the perfect crafted product in a world that was moving to more agility, less craftsmanship and although now it's coming back. Also I talked to Paul Martino, been on theCUBE before. He's a tribe with Pincus. And it's been those founding fathers around these industries. It's interesting how these waves, they start off, they don't get off the ground, but that doesn't mean the category's dead. It's just a timing issue. That's important in a lot of ventures, the timing piece. Talk about that dynamic. >> Absolutely. When it comes to timing, you think about blitzscaling. If you start blitzscaling, you prioritize speed over efficiency. The main question is, is it the right time. So Webvan could be taken as an example of blitzscaling. They were spending money wildly inefficiently to build up grocery delivery. Guess what? 2000 was not the right time for it. Now we come around, we see Instacart succeeding. We see other delivery services delivering some value. It just turns out that you have to get the timing right. >> And market conditions are critical and that's why blitzscaling can work when the conditions are right. Our days back in the podcast, it was, we were right but timing was off. And this brings up the question of the team. >> Yeah. >> You got to have the right team that can handle the blitzscaling culture. And you need the right investors. You've been on both sides of the table. Talk about that dynamic because I think this is probably one of the most important features because saying you going to do blitzscaling and then getting buy off but not true commitment from the investors because the whole idea is to plow money into the system. You mentioned Amazon, one of Jeff Bezos' tricks was, he always poured money back into his business. So this is a capital strategy, as well financial strategy capital-wise as well as a business trait. Talk about the importance of having that stomach and the culture of blitzscaling. >> Absolutely. And I think you hit on something very important when you sort of talk about the importance of the investors. So Reid likes to refer to investors as financing partners. Or financing co-founders, because really they're coming on with you and committing to the same journey that you're going on. And one of the things I often tell entrepreneurs is you really have to dig deep and make sure you do more due diligence on your investors than you would on your employees. Because if you think about it, if you hire an employee, you can actually fire them. If you take money from an investor, there's no way you can ever get rid of them. So my advice to entrepreneurs is always, well, figure out if they're going to be a good partner for you. And the best way to do that is to go find some of the entrepreneurs they backed who failed and talked to those people. >> 'Cause that's where the truth will come out. >> Well, that's right. >> We stood by them in tough times. >> Exactly. >> I think that's classic, that's perfect but this notion of having the strategies of the elements of the business model in concert, the financial strategy, the capital strategy with the business strategy and the people strategy, all got to be pumping that can't be really any conflict on that. That's the key point. >> That's right, there has to be alignment because again, you're trying to go as quickly as possible and if you're running a race car and you have things that are loose and rattling around, you're not going to make it across the finish line. >> You're pulling for a pit stop and the guys aren't ready to change the tires, (snapping fingers) you know you're out of sync. >> Bingo. >> Chris, great stuff. Blitzscaling is a great book. Check it out. I recommend it, remember blitz scale is not for anyone, it's for the game changers. And again, picking your investors is critical on this. So if you picked the wrong investors, blitzscaling will blow up in a bad way. So don't, don't, pick properly on the visa and pick your team. Chris, so let's talk about you real quick to end the segment and the last talk track. Talk about your background 'cause I think you have a fascinating background. I didn't know that you graduated when you're 19, from Stanford was it? >> Yes. >> Stanford at 19, that's a great accomplishment. You've been an entrepreneur. Take us through your journey. Give us a quick highlight of your career. >> So the quick highlight is I grew up in Southern California and Santa Monica where I graduated from Santa Monica High School along with other luminaries such as Rob Lowe, Robert Downey, Jr., and Sean Penn. I didn't go at the same time that they did. >> They didn't graduate when they were 17. >> They did not, (John laughing) and Charlie Sheen also attended Santa Monica High School but dropped out or was expelled. (laughing) Go figured. >> Okay. >> I came up to Stanford and I actually studied creative writing and product design. So I was really hitting both sides of the brain. You could see that really coming through in the rest of my career. And then at the time I graduated which was the mid-1990s that was when the internet was first opening up. I was convinced the internet was going to be huge and so I just went straight into the internet in 1995. And have been in the startup world ever since. >> Must love that show, Halt and Catch Fire a series which I love reminiscing. >> AMC great show. >> Just watching that my life right before my eyes. Us old folks. Talk about your investment. You are at Wasabi Ventures now. Blitzscaling Ventures. You guys looks like you're going to do a little combination bring capital around blitzscaling, advising. What's Blitzscaling Ventures? Give a quick commercial. >> So the best way to think about it is for the entrepreneurs who are actually are blitzscaling, the question is how are you going to get the help you need to figure out how to steer around the corners to avoid the pitfalls that can occur as you're growing rapidly. And Blitzscaling Ventures is all about that. So obviously I bring a wealth of experience, both my own experience as well as everything I learned from putting this book together. And the whole goal of Blitzscaling Ventures is to find those entrepreneurs who have those blitzscalable opportunities and help them navigate through the process. >> And of course being a Mental Samurai that you are, the clock is really important on blitzscaling. >> There are actually are a lot of similarities between the startup world and Mental Samurai. Being able to perform under pressure, being able to move as quickly as possible yet still be accurate. The one difference of course is in our startup world you often do make mistakes. And you have a chance to recover from them. But in Mental Samurai you have to be perfect. >> Speed, alignment, resource management, capital deployment, management team, investors, all critical factors in blitzscaling. Kind of like entrepreneurial going to next level. A whole nother lesson, whole nother battlefields. Really the capital markets are flush with cash. Post round B so if you can certainly get altitude there's a ton of capital. >> Yeah. And the key is that capital is necessary for blitzscaling but it's not sufficient. You have to take that financial capital and you have to figure out how to combine it with the human capital to actually transform the business in the industry. >> Of course I know you've got to catch a plane. Thanks for coming by in the studio. Congratulations on the Mental Samurai. Great show. I'm looking forward to April 30th. Tuesdays at 9 o'clock, the Mental Samurai. Chris will be an inaugural contestant. We'll see how he does. He's tight-lipped, he's not breaking his disclosure. >> I've got legal requirements. I can't say anything. >> Just say he's sticking to his words. He's a man of his words. Chris, great to see you. Venture capitalist, entrepreneur, kind of venture you want to talk to Chris Yeh, co-founder, general partner of blitzscaling. I'm John Furrier for theCUBE. Thanks for watching. (upbeat music)

>> Live from Orlando, Florida It's the Cube covering Enterprise Connect twenty nineteen brought to you by five nine. >> Hello from Orlando. We are at Enterprise Connect twenty nineteen, and we're being very graciously hosted by five nine, which is the intelligent Cloud Contact center. We had a great few days, two minute minute myself talking with customers, partners, vendors on this massive change and enterprise, communication and collaboration. We're excited to welcome back to the key one of our alumni, Zs Caravella, the founder and principal analyst at Zeke Research. These It's great to have you here, >> Dawson. To me. Here >> you are. You should have the i p status at Enterprise Connect because you have been to this event some twenty times. >> I believe it's my twentieth. >> Can't imagine. So they didn't They should have rolled out the red carpet. Maybe we'll put a note >> in next year, >> but Yeah. There you go. I >> want to get my own booth. >> There you go. But I can't imagine how much this event has changed. And just your perspectives on Day three here of e. C nineteen and some of the vendors that you're like, Wow. A few years ago, you would never have seen a so and so here. >> Yeah, the shows massive compared to what it used to be the Remember when I first started coming to the show floor was maybe if I was a quarter the size, I mean generous, and it was really dominated by just a handful of companies. But since then, it's gone through several transitions the i p to software to the cloud on. That's gotten a lot more companies interested. And I think also, finally, businesses starting understand that if you're going to transform digitally right, communications has to be part of that fact. If you look at any piece of research right that I know there's a walker study throwing around saying by twenty twenty customer experience to be the number one brand differentiator, that's that's already happening. It's already the number one brand differentiator. And so because of that, more and more companies are now interested in communications. So, you know, ten years ago, fifteen years ago, we didn't have Amazon here. We didn't have Microsoft here. We didn't have Oracle here, but it's been a great thing for the show to see all these other companies that really have really great presidents validate what we've been saying for a long time, and it's a much different show today than it was. >> Yeah, it's really interesting that the thing that opened my eye is some of the companies that air here. I wish I knew which brand used these technologies so that if and when I do have an issue, I'm not gonna have that horrible customer experience that you know we've had in the past. It's like, you know, if I wanted to make a call, it's like, Can I even make a call? And, you know, do I actually get through the I V R. Things like that? I like how you set it up there. Some of these pendulums swings some of these waves of technology. Um, let's talk a little bit about voice because this used to be called Voice Khan, and it went through a rebranding because, you know, voice was in a little bit of kind. But, you know, we know voices. It's still very important. How does that fit in the hall >> when I went through that rebound, Frankly, voice wasn't sexy anymore. Everyone is talking about unified communications. No one was going to call anybody ever again. We're just gonna message or social each other to death and what's happened is voice is kind of important, right? And I think one of the undersea and friends to look at is that voice is becoming simultaneously less important and more important. What I mean by that is that they sound like a little bit of an oxymoron. But if you look across all age demographics right there, everybody has a prefered mode of communications, and it's rarely voice to start a conversation with the company. You message them your social, um, send them an e mail. But somewhere in there, you you eventually want to talk to somebody, and a that moment s o to start the conversation voices less important. But at that moment, you now want to have a conversation with uneducated agent who knows what your problem is and can help you quickly. And so now voices Mohr important than it's ever been before where, but I think the buried entry wasn't all that high, but voices, you know, it's it's important, it's sexy, and especially when people are dealing with emotional issues, they're dealing with money problems right in front of get a refund. If I'm trying to check on the status of my health, I want to talk to somebody. But when I want to talk to somebody, I want to get that conversation with over. It's possible. I think the bar's been raised as you mentioned to. You used to think that the dreaded Ivy are. If you have a dread and ivy are experience, you just want to business that company anymore, right? And so the stakes are higher than the bar's been raised on. What voices >> are you saying that the customers that you were talking to are now starting to get much more prescriptive in terms of understanding their customer journeys and their preferences? You know, before they used to go, we assume we're talking to millennials. They only want they only want ASA Master. Our company's starting to get more focused on. Alright, let's actually do analysis and determine if a voice only one of the next channels that we need to enable, >> uh, well, I wish they were. I think we're really in the early early innings that I think the best companies in the world are doing that. If you look at companies with very high, uh, NPS scores and customer SAT scores there doing that thing already and I think it's a good lesson for the rest of the industry. If you're not doing that, you're gonna fall behind pretty quickly. And I think that is driving companies more to the Saami Channel experience Where, uh, from, uh, from an analytic standpoint, you really have to understand your customer, not at the demographic level, but almost at a custom level because everyone's different, right? I think that's, uh, that's never been possible before. But today, because we've got bigger data sets. Things were in the cloud rise of artificial intelligence. It's made all the stuff possible. So companies like I said, the best cos the world to taken advantage of and they're having a, you know, big differences. That's why there's been such a huge swings in the market leadership right there cos we never heard of before. Market leaders and brands we trusted loved before they're gone. >> Yeah, I'm glad you brought that up, because every company we talked to this week that that CX is at the center of what they're talking about. So, in your research, what is differentiating though those new leaders and, you know, causing some of those swings in the market place hot out of the customer. Look at these and help differentiate and and ever changing marketplace. >> Well, it's what's going on today. It's really about being more contextual, having a deeper understanding a wire. Customers calling, uh, how you could help him faster understanding maybe what products they own. You know what? What are some of the adjacent ones? Ah, no. I think that's going very quickly, become table stakes. And I think where we're moving to is we're going to shift customer service from being largely inbound, driven and reactive. And that's where they I can help react faster to being Mohr, outbound driven and pearl active. Right? So, for instance, let's say I buy a connected refrigerator and my water filter needs changing. Well, right now, I still have to recognize that. And maybe I call that refrigerator company and they can proactively help me because they understand what I have. And they've got a great arm, the Channel contact center. But ultimately that should be a reverse. They should contact me, maybe through a text message saying, Hey, you're we noticed your water filter needs changing. Can we send you one? Yes, it comes and then maybe I call the agent and say, Can you help me install it? Right? So I think within the next three, four years, we're going to see a lot of customer service, Uh, where contextual is the table stakes and then the ability to predict what your customer wants. That's going to be the differentiator. And frankly, that's really exciting. I mean, if you think we've seen change of this industry as you mentioned in the last five years, wait for the next five. >> When you're talking with customers or even doing research and and other venues, it's to mention CX. We talk. We've been talking about it all week, but I get curious when I hear the customer experience and the agent experience just think, How are they not how they separate because of the Asian isn't empowered to be able to, whether it's no the right channel. But I want to be communicated with or have the information where the context about why I'm calling, then the customer experience, right? >> Yeah, well, they're very tightly linked together. You can't have a good customer experience that a good agent experience and you may have the best trained agents in the world that are the most empathetic that are incredibly sensitive with what people want. But if they don't have the data, you're going frustrate your customer. And everybody's been through that situation where you get transferred to somebody else and you gotta start that whole conversation over again and eventually you just hang up and say, I don't want ever to business. So I think you're right. Agent experience Customer experience are very tightly interwoven, and they're they're really dependent on one another. You can't you can't do without the data. And again, that's where all these friends of a I come into play because they're able to send better information to the agents faster, really, through an assistive technology versus replacement. Right? >> So when we came into this show, we knew that the wave of cloud had made a big transformation. We're starting to hear a I is the next wave everybody's talking about. I believe I read something that that you had written that was talking about, you know, whether that is something just internal the company build in versus how it interacts with the customer. Where do you see I having the biggest impact kind of in the short term, and nowhere is that more long. >> It's a great question because I ask my customers all the time. Should we be using intelligence bots? Or if you saw the Google Duplex Nemo, where they have on a I call in order pizza I think it was or something like that. So is a I ready to talk to people? And I think if you think of the entire world of interactions on a two by two grid is an analyst would like to buy two grids, right? And you put complexity of conversation on one axis and frequency of interactions if it's hiking, or if it's low complexity, high frequency, that might be okay to try and automate through a But other than that, everything should flipped. Agent. And I think right now we're very early in the cycle, and so is a business. I'm not sure I trust today. I tow always have the right answer, but it makes a great assistant technology to recommend to the agent. This is what you should say, and the great thing about that is, if the agent says no, that's stupid and says that wasn't helpful. That becomes the input to the learning mechanism for the A I so overtime will get smarter and smarter. But if you if you want to think about just the role of it now, I always use the analogy is like a self driving car. I'm not sure if either one of you would want to jump in a car that has no driver, no steering wheel, no controls. But there's a lot of great aye aye technology in a car like lane change assist, parallel parking assist things like that that can make you a better driver. So let's make our agents better drivers by giving him those assistive technologies. And that's the the short term vision long term. Who knows? But I But I think oh, if company's heir to aggressively they II, they're actually gonna create a nod. The opposite effect, where they hurt customer experience. It's the people that make a difference, so let's make those people better. >> That's one of the things that we've heard consistently throughout this event is the empathy factor machines can't bring. That's really got to be the humans with the A I to deliver on idea, hopefully optimal experience, too. Whatever customer has whatever issue on the back end. >> Yeah, in fact, Roman always talks about that as well. The CEO of five nine and I think he's right from that. Regarded is about having the knowledge of the customer in the empathy to understand. Put yourself in the customer's position and this to your point. Lisa, about CX. In Asian experience, we tied a couple together. If the Asian distressed because they don't have the right information and they're trying a message, this person, or look something up in the database, that frustration is going to come through to the customer. And that further frustrates the customer, right? So of the agents, armed with the right information, they can spend more time focused on the customer and less time trying to find the data that, frankly, they should have at their fingertips all the time. >> So speaking of five nine, you recently attended their analyst event. >> I did >> on. We've had the executives on the team. You know, Jonathan on earlier this week, you know, rock star background. We're goingto throwing on a little bit later. We know him from his Cisco days without breaking any India's, you know, give us a little bit of the insight as to, you know, five nine. You know, what have they been doing? Well, what's what's the new team driving them forward towards? >> Well, I mean, if you look at their stock price from Roland joined, it's it's more than doubled. So obviously there's, um, some good growth there. I think. What? I've always believed that it's very difficult to compete on product alone, right? And if you believe this whole world of it is this customer experience, that's what they do really well, the customers, their customers have a great experience here with five nine, they have a great service organization that makes sure that when you buy five nine, you have a good on boarding experience that set up the way you want it, and that services business makes a big difference. Now they've always had that. Now, where I think the new executive team has made a difference is helping the company understand the scale, move upmarket, more enterprises because the needs their different than down market. And so I think you know, they're gonna have a big impact on the future of five nine. Frankly, I think a lot of what you've seen for growth in the last year has been stuff that was put in place. But I know they're working on a lot of the AI capabilities. We're not breaking in the NBA's. I can tell you that the demonstrations that Jonathan Rosenberg, who's in there incredibly smart guy, I mean he might be the smartest guy in this industry was giving around. How a I can impact customer experience was the best set of concrete examples that I've seen today because it's really easy to give me a pie in the sky hypothetical things. But he really boiled it down in a very grand your level of this possible. This is possible and I'm expecting over the next year, five nine customers will see those things. >> They've done really well in the enterprise market. I think last year in twenty eighteen, they closed very, very strongly. Also, a lot of growth in there. Custom enterprise customers with a Million and Ahrar plus What are you seeing, though, in terms of some of the smaller businesses that probably are facing a lot of the same challenges that enterprises are? Is this an area where they can also leverage five nine two really dial up and deliver Great CX, >> Yeah, but the line has moved up right of people interested in cloud services that used to be too small businesses, and now it's all kinds. But I think for a small business, you can look like a much larger business. I think there's a lot of companies people sometimes think that's a little risky deal the small company. But five nine is a very, very valuable tool because by having that information right away that agents fingertips, they're able to actually replicates, uh, large company experience and on almost validate that the customer made the right decision using them. So I think up and down the stack it for five nine. They provide value tow companies of all sizes. Today, one of them, you know, the interesting aspects of what I've seen two is everybody talks about this twenty four billion dollars tam for Contact Center. I know I've been in that eye, and may I say that because that twenty four billion dollars tam is based on giving contact, Senator people contact center tools, but what I've been noticing over the last years, when people buy five nine, often it's not contact center people using that using it. It's sales people in marketing people, field service. Anybody that needs customer info is using it. And I'll give an example. One of the customers that was at the five nine day I can't see you. They say who they are. They migrated all fifty contacts and regions five nine. And since then they've added one hundred mohr sales people using the tools. So now we've got one hundred fifty people using five nine when there was only fifty contacts. Generations you can see the value is starting to spread across the company, and I think that's a pretty exciting thing. >> It's been interesting we've seen at the show. And in some of the interviews, that line between kind of unified communications and contact center seems to be blurring. It seems to be that >> well, everybody needs that data on the customer info. I actually cameras closer to forty. Forty five billion. To be frank, really, every anybody who uses a serum tool should have five nine capabilities. >> Zia's Thank you so much for sharing your insights and your energy on Day three. If Enterprise connect nineteen, we appreciate your time Thank you. First two minute, man. I'm Lisa Martin. You're watching the Cube?

[Music] okay welcome back and ready Jeff from here with the cube we're at the conference board event it's called the sixth annual innovation master classes here at Xerox PARC I'm really excited to be the arc spark I've never been here I lived like a stone's throw away and as you know if you're any type of a student of history this is where so many other really the core fundamental foundational technologies were developed what a long time ago mice GUI a lot of fun stuff but that's but now we're talking about today we're talking about helping companies be better at innovation a series of fantastic presentations that were excited to have our first guest he's Vittorio via Rango and he is the VP of cloud security for McAfee just coming off your your presentation so great to see you likewise I'm excited to be here about DevOps and how that that world has really changed in the software development world to get away from waterfall you talking about kind of applying the same principles not just for software development but in marketing and your role as a marketer how did you come to that kind of conclusion that this was probably a better way to get things done yeah well I have an interesting background when I used to run engineer engineering and product management and then I'm moving to the dark side to marketing and and I used successfully use Chrome in building products and if you look at scrum and agile methodologies at the end of the day their methodology methodologies to get things done in a world that changes often and that applies to any functions and so I said why not doing in marketing and so I've been doing in marketing now for six years but you juxtapose that you know it's now December 6th I believe so everyone with the whole room gotta get a good laugh out of them is in the throes of their annual business planning coming off their QPR's as they wrapped up 2018 so you know there is kind of an annual process and there is an annual budget so how did you you know find a convenient way to marry the two things together I think that everything is frantically pretending to know what's gonna happen next year and building plans they go out 12 months that never pan out right now unless you do is something that is the same thing over and over again then you can but if you're doing innovation by definition you don't know what's gonna happen so I think a better approach is to align around the goals and then take that goes decentralize the execution of that goes to the function and then in my case in marketing I take those goals that are applicable to me and I break it down using scrum and I do cycles of two weeks I tell the people I feel the the backlog with all the top initiatives that I think we should do and then when we get into a sprint I say okay what is the most important what are the most important priorities for the next two weeks right I tell the team and then the team tells me what we need to do to achieve those goals in every two weeks I'm in front of them talking about priorities and then reviewing how we move the needles to achieve the goals right so a lot of people hit there's plenty of stuff out there for people that aren't familiar with how scrum works and how about this process so we won't get on that but what I want to talk about is some of the the secondary benefits that maybe people don't understand it there's only looking at kind of the process of these two-week sprints but you you highlight it on a whole bunch of kind of side benefits that come as a result of this process number one being you know constantly reinforcing your priorities which are the company's priorities to your team every two weeks that's a pretty amazing communication flow yeah look every when people think about agile they obsess about the stand-up meeting every day and other people that are obsessed with that they don't get a job what agile is is about constant communication about the priorities letting the team innovate and tell you what to do and then being able every two weeks to adjust to changes so instead of executing against initiatives and plans that you build a year before that may not be relevant based on the market changes you're actually dealing with the reality measuring how you're progressing against the goals and then make changes as as you go and it gives an amazing platform for even junior people in a team to step up you know sometimes in a hierarchical structure you have somebody junior really good that is boxed in in the corner with scrum I come up with the priorities if somebody just out of college says I'll take that okay go ahead do it and then if they deliver good for them good for you right another you touched on so many good topics we could go on and on and on another one you talked about is really the giving up of time you know you try to manage kind of the interruptions for the team you try to be that kind of traffic cop if you will to enable them to use I think you said the target is 75% of the time during those two weeks is actually getting work done and 25% of the time is managing the minutia that we have to manage every day I think that's a really important concept because I think a lot of times it's it's easy it's easy to do the minutia yes it's in front of your face super important role for for a manager look when was the last time you you like being interrupted right and and if you are using your intellect to design to to sell to do whatever you know activity requires using your brain context switches is really expensive and so the ideal scrum is that you plan these two weeks so you don't have to like spend a lot of time thinking about three six months out just let's think about the next two weeks and then during those two weeks you never ever ever change the priorities and so that allows engineers or professionals to stay focused on what they're trying to do and get it done right right another piece that I thought was pretty interesting is is you've got the two weeks sprints and you've got your two weeks priorities and you now have an ability to switch if you need to based on market pressures competitive pressures whatever but how do you continue to tie that back to those goals how do you how do you make sure that you don't lose sight of the fact that maybe didn't have an annual plan because we know that's gonna change but you're still making sure you're driving towards kind of the general direction of where you're trying to go so the way I do it every two weeks we look at all our top goals and we look at how closer we are to achieving those goals and of course I map those goals I split them by quarter and then by weeks so that you at all times you know if you're achieving your goals or not and because of the two weeks interval if the cattle sales in my case comes as you know they they always have big priorities that has to happen tomorrow and yesterday usually I go to them and say hey here's the list of things I'm gonna deliver my team is gonna deliver to you in an axe in average next week right and is what this emergency you're talking about more important than this in most cases the answer is No if the answer is yes then the question is can that wait a week and then you have the full attention of my entire team and so that way you keep doing what you do in the scrum principle you always ship so you always work on things you can actually ship during those two weeks and then you can take the whole team in okay let's now please the head of sales and and I can go ahead with that you know the other thing is because we look at the goals every two weeks I can also look at the other sale say oh you know you won't really want to run this program in pick your region you know South America where we have no we don't have any goals of growth in that area this year so you can also use the constant communication constant interlocking goals to say you know maybe you shouldn't do it right so last thing Victoria just to get your insight is you've been doing this for years you know what's what's the greatest benefit of managing a team this this way that most people just don't get and we talked about the frequency of communications you talked about the frequency of being able to change course you know what is it that people are still kind of doing it the old line way or missed to me scrum forces you as a leader to focus on the two most important things that I think any leader should you know take care of one Chris priorities and communication I think those are the roots of how many companies get in trouble when they don't have clear priorities and all levels and they don't communicate those priorities and there is all there they're achieving and I think scrum really forces you every two weeks to be there on the treadmill with the team and and the third thing I think is to empower the team to size and tell you what to do and how to do it and not you telling them what to do you tell them without the priorities let them tell you what is the best way to achieve the goals it's such a great such a great lesson right be a leader not it not let let your people do what you hired him to do yeah because even more and more to me if you're hiring great people if you're managing them what are you gonna do if you alright people that are better than you if you're manage them what are you gonna do you're going to by definition so let them tell you what how to do give them a direction and get out of the way alright Vittorio thanks for for taking a few minutes and really really enjoyed your talk today all right we're at the innovation masterclass at Xerox PARC you're watching the Q see you next time thanks for watching [Music]

(upbeat music) >> Hey welcome back everybody. Jeff Frick here with theCube. We're at Xerox PARC in Palo Alto, one of the most historic pieces of ground really in the history of computer science. We're excited to be here for a special event. It's the Innovators Master Class put on by the Conference Board. Relatively small event, great content. We've been here all morning and we're excited to have our next guest, she's Maureen Rinkunas. She's the Innovations System Designer, Specialty Products Division for DowDuPont. Maureen, great to see you. >> It's great to be here. >> So you're, you're giving a panel in a little bit about really how do big companies work with little companies to basically be more innnovative, so what are some of the things that you're looking forward to, what are some of the lessons that you've learned, 'cause you've had a very varied experience, you've been in academia, you've been in industry, you've been kind of big company and little company. >> Yes, and I think, you know, you learn a lot from being able to look outside of your sphere. And so that's what I'm really excited about on this panel, we're going to be talking with startups and VCs and it's not surprising, people are really keeping an eye on what's happening in Silicon Valley but I think for large corporations, we have to go beyond that. We have to say, let's not just be observers, let's be active participants in the ecosystem. And so I think that by engaging with some of the startups and businesses on this panel, we're really going to get some pragmatic advice on how to do that in the best way possible. >> Yeah, you had some great statements, I've been doing some research on you, about some tricks to innovation and one of the great ones was, new hires as change agents. I wonder if you could dig into that a little bit because I think, you know, unfortunately new hires, especially at a big company, they don't have status, they don't have title, you know, they don't necessary have formal authority but there's a real opportunity for companies to take advantage of this fresh new outlook to help look at things in a slightly different way. >> Yeah, it's actually been great to be here at the conference for an event because I've talked with a lot of organizations that are bringing in this fresh view and especially in innovation centers where the proportion of people coming from outside the organization is sometimes as high as 80 percent of the team at that facility and so it's really great to have people who aren't carrying the baggage of how we always have done things. >> Right right. >> And they can push the limits a little bit which is sometimes what we need to, to really break out of our routines and I think as well, you know, bringing people in who have experience in startups, people who, perhaps, are coming from the venture world also offers that opportunity for people who have experienced working in that really fast-paced environment, they are very impatient, which is a good thing and I think really push teams to move faster. So it's great to be able to bring that, an element, into your team. >> Right. There was a great presentation earlier today about DevOps and, you know, agile software development and it's easy in software, you know, you can have a two week spread and get something out new. In the chemical world, right, there's lots of different axes of innovation but you guys, kind of by rule, have to move slower. These are much bigger investments in factory and plant, you know, there's ecological implications to all these things. So when you look at the innovation challenges and opportunities at a big company like DowDuPont, what are some of the easier paths to go down that you can, you can help to drive some of that innovative thought process and products? >> Well I think, you know, certainly we don't want to take any shortcuts with safety, and so you're absolutely right, that in some ways we can't move as quick as launching a new app to market, but we really do need to challenge ourselves to think about how we move as quickly as possible. One way to do that is to look at outside innnovations and so, I've just recently was working with a team and they had mapped out their development pipeline, they thought, oh this is 3 to 5 years in the making, and then we were able to connect them with a startup who cut about 4 years out of that and so, they are actually really excited, they're going to be partnering with that startup and moving forward with a customer in a very short timeframe. So, I think there are ways to make that window a much shorter timeline. >> Right. And then what about just the culture clash? I mean, just this example specifically, you've got people that had probably a very comfortable, maybe they thought it was aggressive, timeline that went out for 4 or 5 years, then you bring up this crazy aggressive startup who are doing things much quicker. Was it simply process? Was it a new technology innovation? Was it just a different kind of spin of the lens that they were able to reframe their problem differently? And then how do you get those two groups of people to work together effectively? >> Well you know, I think in the corporate space, there's a lot of this, well we don't care because it wasn't invented here, syndrome. We're very fortunate that at a leadership level at DuPont, there has been very much this perspective that we need to get beyond that, we need to collaborate with our customers, we need to move externally, and so, you know, that helps, having someone who champions looking outside for alternatives, but I think, too, it's helpful to have those change agents within, people who are really brave, people who aren't afraid to push back, often these are the people who are coming outside with the legacy, they're not worried about getting fired and they're pushing for what they know is right and that's moving fast and hopefully making some positive change. >> Right, and not breaking too many things, right? >> (laughs) >> We've kind of got away from the move fast and break things. So final question, you know, we're here at this Innovation Master Class, what are you looking to get out of this type of event? Have you been here before and you know, what types of things do you take away of kind of this small, intimate little affair? >> Yeah so this is my second time here and you know, after seeing what we've learned this morning and reflecting on what I learned last year, I think you always take things away that are really actionable, you know, the folks that come to these events are in the field, they are getting things done, and so you really have an opportunity to learn from people who have tested things, they've learned from those experiments, sometimes they've failed and we can learn from those failures too and so that's what I really appreciate about having this opportunity to be here. >> Well Maureen, thanks for taking a few minutes. Good luck on your panel this afternoon. I can't wait to, can't wait to watch. >> Great, thanks. >> Alright, she's Maureen, I'm Jeff, you're watching theCube. We are at the Innovation Master Class put on by the Conference Board at Xerox PARC. Thanks for watching. (upbeat music)

>> From Palo Alto, California, it's theCUBE, covering the Conference Board's Sixth Annual Innovation Master Class. (fast techno music) >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We are at the Innovation Master Collab at Xerox PARC. It's put on by the Conference Board, a relatively small event, but really, a lot of high-caliber individuals giving really great presentations. And we're excited about our next guest, he kicked the whole thing off this morning, and we could go for hours. We won't go for hours, we'll go about 10 minutes. But Peter Coffee, he's the VP of Strategic Research for Salesforce. Been there a long time, but you were a media guy before that for many, many years? So Peter, great to see you. >> It's good to be with you, thanks. >> So, you talk about so many things. So many things in your opening statement, and I have a ton of notes. But let's just jump into it, I think. One of the big things is you know, the future happens faster than we expect it. And we as humans have a really hard time with exponential growth, because it's not built that way. That's the way things move. >> So how do you as a businessperson kind of deal with that reality? Because the issue is you're never going to be ready for when they come. >> Yeah, well, it's not just humans as individuals, but the institutions and processes we've built. If you look at the process of getting a college degree, it's really seriously misaligned with the timeframe of change. By the time you're a senior, half of the subject matter in your field may be new since your freshman year, and conversely four years after you've graduated, perhaps a third of what you were taught will no longer be considered to be current information. Someone at Motorola once said, "a batch process "no matter how much you accelerate it "doesn't become a continuous flow process". You have to rethink what does a continuous flow look like, and that's useful conversation to have getting back to your actual opening question. When we're talking with customers, we say what are your unvoiced assumptions about the manner in which you have succession of technology, succession of product, and so on? Can we try to see what it would look like if that were a continuous process and not a project process? Many of our partners will tell us that their most difficult conversations with their customers are about getting away from a project mentality, a succession of Big Bang changes, into a process in which transformation is a way of life and not a bold initiative that will take a big sigh of relief and congratulate yourself on having transformed. No, dude, you've gotten your running shoes tied now you can begin to run. But now the hard part begins. >> Right, and the sun comes up tomorrow and you start to run again. You talked on big shifts count on new abundance and use horsepower. >> George Gilder's phrase, "errors are punctuated "by a dramatic change from a scarcity "to an abundance" so for example, horsepower or bandwidth or intelligence. >> So now we're coming into the era of massive big data we are asymptotically approaching free compute, free storage, and free networking. So how do you get business leaders to kind of rethink in an era where they have basically infinite resources, and it always goes back, so what would you build then? Because we're heading that way even if we're not there today. >> A Jedi mind trick that I often use with them is to say, let's not talk about the next couple of quarters, I want you to imagine the next Winter Olympics. When they light the torch four years from now I want you to try to visualize the world you're pretty sure you'll be living in four years from now and work backwards from that and say well if we all agree that within four years that's going to get done, well there's some implications about things we should be doing now and some things that we should stop doing now if we know that four years from now, the world is going to look like this. It helps free your mind from the pressures of incremental improvement and meeting next quarterly goals. And instead saying, ya know, that's not going to be a thing in four years and we should stop getting better at doing something that's simply not going to be relevant in that short of a time. >> So hard though, right? Innovators still, I mean, that's the classic conundrum especially if it's something that you have paying customers and you're driving great revenue to, it's hard to face the music that that may not be so important down the path. >> The willingness to acknowledge that someone will disrupt you, so it might as well be you, you might as well disrupt yourself, the conversation was had with IBM back in the days of the IBM PC, that they thought that that might be a quarter of a million machines they would sell, but whatever you do, don't touch the bread and butter of the 3270 terminal business, right? And they did not ultimately succeed in visualizing the impact of what they had done. Ironically, because they didn't think it was that important, they opened all the technology, and so things like Microsoft becoming what it is and the fact that the bios was open and allowed the compatibles industry like Compact to emerge was a side effect of IBM failing to realize how big of a door they were opening for the world. You can start off a spinoff operation. At Salesforce we have a product line called Essentials which is specifically tasked with create versions of Salesforce that are packaged and priced and supported in a way that's suitable to that small business. And that way you can kind of uncouple from that Clayton Christensen innovators dilemma thing by acknowledging it's a separate piece of the business, it can be measured differently, rewarded differently, and it's going to convey itself maybe even through a genuinely different brand. This is an example that was used once with Disney which when it decided it wanted to get away from family and children's entertainment, and start making movies aimed at more adult audiences, fine, they created the Touchstone brand so they could do that without getting in the way of, or maybe even polluting, a brand that they spent so much time building. So branding is important. A brand is a set of promises, and if you want to make different promises to different people, have a different brand. >> Right, so I'm shifting gears 'cause you touched on so many great things. A really popular thing that's going on now is the conversion of products to services. And repackaging your product as a service. And you talked about the don't taze me bro story which has so many elements of fun and interesting but I thought the best part of it, though, was now they took it to the next step. And we're only a stones throw away from Tesla, a lot of innovation but I think one of the most kind of not reported on benefits of these connected devices and a feedback loop back to the manufacturer is how people are actually using these things, checking in from home, being able to do these updates. And you talk about how the TASER company now is doing all the services, it's not even a service, it's a process. I thought it's awesome. >> Taking a product and selling it at a subscription price does not turn it into a service, even though some people will say, well see now we're moving to a services model. If you're still delivering a product in a lumpy, change-it-every-couple-of-years way, you haven't really achieved that transformation. So you have to go back into more of a sense of I mean, look at the expectation people have of the apps on their smartphones, that they just get better all the time, that the update process is low-burden, low-complexity, low-risk, and you have to achieve that same fluidity of continuous improvement. So that's one of the differences. You can't just take the thing you sell, bill for it on a monthly subscription, and think that you achieved that transition. The thing that they folks who were once TASER and now are Axon, of which TASER is a sub-brand, they managed to elevate their view from the device in a police officer's hand to a process of which that device is a part. Which is the incident that begins, is concluded, results in a report, maybe results in a criminal prosecution, and they broadened the scope of the Axon services package to the point that now it is selling the proposition of increased peace officer productivity rather than merely the piece of hardware that's part of that. So being able to zoom out and really see the environment in which your product is used, and this relates to yet another idea which is that people are saying you got to think outside your box. It doesn't help if you get outside your box, but all of the people with whom you might want to collaborate are all still inside their boxes. And so you may actually have to invest in the transformation and interface development of partners or maybe even competitors, and isn't that a wild idea. Elon Musk at Tesla open sourced a lot of their technology with the specific goal of growing that whole ecosystem of charging stations and other things so Tesla could be a great success. And the comment that I once made is it doesn't help if you're a perfect drop of artisanal oil in a world of water. You have to make the world capable of interacting with you and supporting you if you really want to grow. Or else you're an oddity, you're Betamax, which might have been technically superior but by failing to really build the ecosystem around it, wound up losing big time to VHS for a while. I may have to explain to all of your viewers under the age of 30 what VHS and Betamax even mean. >> I was sellin' those, I could tell you the whole Panasonic factory optimization story, which is whole 'nother piece of that puzzle. So that's good, so I'm going to shift gears again. >> You have to look a big perspective, you have to be prepared to forget that your excellence is your product, and start thinking of that as just the kernel of what needs to be your real proposition which is the need you meet, the pain you address, the process of which you become an inseparable part instead of a substitutable chunk of hardware. >> Well and I think too it's embracing the ongoing relationship as part of the process, versus selling something to your distribution and off it goes you cash the check and you build another one. >> Well that's another aspect, we've got whole industries where there's been a waterfall model. Automobiles were a particular example. Where manufacturers wholesaled cars to distributors who gave them the small markup to dealers who owned the buyer customer. And dealers would be very hostile to manufacturers trying to get involved in that relationship. But now because of the connected vehicles the manufacturer may know things about the manner of use of the vehicle and about the preliminary engagement of the prospective buyer with the manufacturers website. And so improving that relationship from a futile model, or a waterfall model, into a collaborative model is really necessary if all these great digital aspects are to have any value. >> Right, right, right. And as a distribution of information that desire to get a level of knowledge is no longer the case, there's so much more. >> Well it's scary how easy it is to do it wrong. IDC just did a study about the use in retail banking of technology like apps and websites. Which that industry was congratulating itself on adopting in ways that reduce the cost of things like bank office hours. And yet J.D. Power has found that the result is that customers no longer see differentiation among banks, are less loyal, more easily seduced by $50 to open a new bank account with direct deposit. And so innovation's a vector, and if you aim it at cost reduction, you'll get one set of results. And if you aim it at customer satisfaction improvement, you'll innovate differently, and ultimately I think much more successfully. >> Right, right, so we're almost out of time here. I want to go down one more path with you which I love. You talked a lot about visualization, you brought up some old NOPs, really talked about context, right? In the right context, this particular visualization is of value. And there's a lot of conversation about visualization especially with big data. And something I've been looking for, and maybe you've got an answer is, is there a visualization of a billion data point dataset that I can actually look at the visualization and see something, and see the insight. 'Cause most of the ones we see that are examples, they're very beautiful and there's a lot of compound shapes going on, but to actually pinpoint an actionable something out of that array, often times I don't see, I wonder if you have any good examples that you've seen out there where you can actually use visualization to drive insight from a really, really big dataset. >> Well if a big data exercise produces a table of numbers, then someone's going to have to apply an awful lot of understanding to know which numbers look odd. But a billion points, to use your initial question, well what is that? That's an array that's 1,000 by 1,000 by 1,000. We look at 1,000 by 1,000 two-dimensional screens all the time, visualizing a three-dimensional 1,000 by 1,000 cube is something we could do. And if there is use of color, use of motion, superposition of one over another with highlighting of what's changed, what people need most is for their attention to be drawn to what's changing or what's out of a range. And so it's tremendously important that people who are presenting the output of a big data exercise go beyond the high-resolution snapshot, if you will, and construct at least some sense of A B. Back in the ancient days of astronomy, they had a thing called the Blink Camera which would put two pictures side-by-side and simply let you flip back-and-forth between the images, and the human eye turned out to be amazingly good. There could be thousands of stars in that picture, the one dot that's moving and represents some new object, the one dot that suddenly appears, the human brain is very good at doing that. And there's a misperception that the human eye's just a camera. The eye does a lot of pre-processing before it ever sends stuff to the brain. And understanding what human vision does, it impressed the heck out of me the first time I had a consultation on the big data program at a university where the faculty waiting to meet with me turned out to be from the schools of Computer Science, Mathematics, Business, and Visual Arts. And having people with a sense of visual understanding and human perception in the room is going to be that critical link between having data and having understanding of opportunity threat or change. And that's really where it has to go. So if you just ask yourself, how can I add an element of color, or motion, or something else that the human eye and brain have millennia of evolution to get good at detecting, do that. And you will produce something that changes behavior and doesn't just give people facts >> Right, right. Well, Peter, thank you for taking a few minutes. We could go on, and on, and on. >> Happy to do chapters two, three, and four any time you like, yeah. >> We'll do chapter two at the new tower downtown. >> Any old time, thanks so much. >> Thanks for stoppin' by. >> My pleasure. >> He's Peter, I'm Jeff, you're watching theCUBE. We're at the Master Innovation Class at Xerox PARC put on by the Conference Board. Thanks for watching. (fast techno music)