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(upbeat techno music) >> Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions, and they were largely confined to regulated industries that had to comply with public policy mandates. But as the cloud went mainstream the tech giants showed us how valuable data could become, and the value proposition for data quality and trust, it evolved from primarily a compliance driven issue, to becoming a linchpin of competitive advantage. But, data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper-specialized skills, to develop data architectures and processes, to serve the myriad data needs of organizations. And it resulted in a lot of frustration, with data initiatives for most organizations, that didn't have the resources of the cloud guys and the social media giants, to really attack their data problems and turn data into gold. This is why today, for example, there's quite a bit of momentum to re-thinking monolithic data architectures. You see, you hear about initiatives like Data Mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business users. You hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver, like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that but also, how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. In other words, while it's enticing to experiment, and run fast and loose with data initiatives, kind of like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated and intelligent. Governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is going to use data that is entrusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. Hello and welcome to theCUBE's coverage of Data Citizens made possible by Collibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Vellante and I'm one of the hosts of our program which is running in parallel to Data Citizens. Now at theCUBE we like to say we extract the signal from the noise, and over the next couple of days we're going to feature some of the themes from the keynote speakers at Data Citizens, and we'll hear from several of the executives. Felix Van de Maele, who is the co-founder and CEO of Collibra, will join us. Along with one of the other founders of Collibra, Stan Christiaens, who's going to join my colleague Lisa Martin. I'm going to also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Haslbeck. He's the Vice President of Data Quality at Collibra. He's an amazingly smart dude who founded Owl DQ, a company that he sold to Collibra last year. Now, many companies they didn't make it through the Hadoop era, you know they missed the industry waves and they became driftwood. Collibra, on the other hand, has evolved its business, they've leveraged the cloud, expanded its product portfolio and leaned in heavily to some major partnerships with cloud providers as well as receiving a strategic investment from Snowflake, earlier this year. So, it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. (upbeat rock music) Last year theCUBE covered Data Citizens, Collibra's customer event, and the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know starting with the Hadoop movement, we had Data lakes, we had Spark, the ascendancy of programming languages like Python, the introduction of frameworks like Tensorflow, the rise of AI, Low Code, No Code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives, and we said at the time, you know maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation. Meaning, making it easier for domain experts to both gain insights from data, trust the data, and begin to use that data in new ways, fueling data products, monetization, and insights. Data Citizens 2022 is back and we're pleased to have Felix Van de Maele who is the founder and CEO of Collibra. He's on theCUBE. We're excited to have you Felix. Good to see you again. >> Likewise Dave. Thanks for having me again. >> You bet. All right, we're going to get the update from Felix on the current data landscape, how he sees it why data intelligence is more important now than ever, and get current on what Collibra has been up to over the past year, and what's changed since Data citizens 2021, and we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends and we're not just snapping back to the 2010s, that's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s, from the previous decade, and what challenges does that bring for your customers? >> Yeah, absolutely, and and I think you said it well, Dave and the intro that, that rising complexity and fragmentation, in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use, has only gotten more more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under, respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well. Which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity, and fragmentation. So, it's become much more acute. And to your earlier point, we do live in a different world and and the past couple of years we could probably just kind of brute force it, right? We could focus on, on the top line, there was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, how do we truly get the value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale with data, not just from a a technology and infrastructure perspective, but how do we actually scale data from an organizational perspective, right? You said at the, the people and process, how do we do that at scale? And that's only, only, only becoming much more important, and we do believe that the, the economic environment that we find ourselves in today is going to be catalyst for organizations to really take that more seriously if, if, if you will, than they maybe have in the have in the past. >> You know, I don't know when you guys founded Collibra, if you had a sense as to how complicated it was going to get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >> Yeah, absolutely. We, we started Collibra in 2008. So, in some sense and the, the last kind of financial crisis and that was really the, the start of Collibra, where we found product market fit, working with large financial institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis. And kind of here we are again, in a very different environment of course 15 years, almost 15 years later, but data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So, what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it Data Citizens, we truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we still relatively early in that, in that journey. >> Well that's interesting, because you know, in my observation it takes 7 to 10 years to actually build a company, and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your current momentum? >> Yeah, absolutely. Again, there's a lot of tailwind organizations that are only maturing their data practices and we've seen that kind of transform or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world with its Adobe, Heineken, Bank of America and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in the, in the market with some of the cloud partners like Google, Amazon, Snowflake, Data Breaks, and and others, right? As those kind of new modern data infrastructures, modern data architectures, are definitely all moving to the cloud. A great opportunity for us, our partners, and of course our customers, to help them kind of transition to the cloud even faster. And so we see a lot of excitement and momentum there. We did an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course data quality isn't new but I think there's a lot of reasons why we're so excited about quality and observability now. One, is around leveraging AI machine learning again to drive more automation. And a second is that those data pipelines, that are now being created in the cloud, in these modern data architecture, architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously, has become absolutely critical so that they're really excited about, about that as well. And on the organizational side, I'm sure you've heard the term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believed in. Federated, focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations, and so that aligns really well with our vision and from a product perspective, we've seen a lot of momentum with our customers there as well. >> Yeah, you know, a couple things there. I mean, the acquisition of OwlDQ, you know Kirk Haslbeck and, and their team. It's interesting, you know the whole data quality used to be this back office function and and really confined to highly regulated industries. It's come to the front office, it's top of mind for Chief Data Officers. Data mesh, you mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So, let's chat a little bit about the, the products. We're going to go deeper into products later on, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the the under the covers in security, sort of making data more accessible for people, just dealing with workflows and processes, as you talked about earlier. Tell us a little bit about what you're introducing. >> Yeah, absolutely. We we're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission. Either customers are still start, are just starting on that, on that journey. We want to make it as easy as possible for the, for organization to actually get started, because we know that's important that they do. And for our organization and customers, that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again to make it easier for, really to, to accomplish that mission and vision around that Data Citizen, that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving, a lot of kind of ease of adoption, ease of use, but also then, how do we make sure that, as clear becomes this kind of mission critical enterprise platform, from a security performance, architecture scale supportability, that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme. From an innovation perspective, from a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One, is around data marketplace. Again, a lot of our customers have plans in that direction, How to make it easy? How do we make How do we make available to true kind of shopping experience? So that anybody in the organization can, in a very easy search first way, find the right data product, find the right dataset, that they can then consume. Usage analytics, how do you, how do we help organizations drive adoption? Tell them where they're working really well and where they have opportunities. Homepages again to, to make things easy for, for people, for anyone in your organization, to kind of get started with Collibra. You mentioned Workflow Designer, again, we have a very powerful enterprise platform, one of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a, a new Low-Code, No-Code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around Collibra protect, which in partnership with Snowflake, which has been a strategic investor in Collibra, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PIA data, is managed as a much more effective, effective rate. Really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily, and quickly, and widely as we can? Moving that to the cloud has been a big part of our strategy. So, we launch our data quality cloud product, as well as making use of those, those native compute capabilities and platforms, like Snowflake, Databricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down, so we're actually pushing down the computer and data quality, to monitoring into the underlying platform, which again from a scale performance and ease of use perspective, is going to make a massive difference. And then more broadly, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical, and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So that's a lot coming out, the team has been work, at work really hard, and we are really really excited about what we are coming, what we're bringing to market. >> Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you you talked about, you know, the marketplace, you know you think about Data Mesh, you think of data as product, one of the key principles, you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been, been so hard. So, how do you see sort of the future and, you know give us the, your closing thoughts please? >> Yeah, absolutely. And, and I think we we're really at a pivotal moment and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not going to fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to, deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can, as kind of our, as our mission. And so I'm really, really excited to see what we, what we are going to, how the marks are going to evolve over the next, next few quarters and years. I think the trend is clearly there. We talked about Data Mesh, this kind of federated approach focus on data products, is just another signal that we believe, that a lot of our organization are now at the time, they're understanding need to go beyond just the technology. I really, really think about how to actually scale data as a business function, just like we've done with IT, with HR, with sales and marketing, with finance. That's how we need to think about data. I think now is the time, given the economic environment that we are in, much more focus on control, much more focus on productivity, efficiency, and now is the time we need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >> Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much. Good luck in, in San Diego. I know you're going to crush it out there. >> Thank you Dave. >> Yeah, it's a great spot for an in-person event and and of course the content post-event is going to be available at collibra.com and you can of course catch theCUBE coverage at theCUBE.net and all the news at siliconangle.com. This is Dave Vellante for theCUBE, your leader in enterprise and emerging tech coverage. (upbeat techno music)

Published Date : Nov 2 2022

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Felix Van de Maele, Collibra | Data Citizens '22


 

(upbeat music) >> Last year, the Cube covered Data Citizens, Collibra's customer event. And the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hadoop movement. We had data lakes, we had Spark, the ascendancy of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of AI, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives. And we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights from data, trust the data, and begin to use that data in new ways, fueling data products, monetization, and insights. Data Citizens 2022 is back, and we're pleased to have Felix Van de Maele, who is the founder and CEO of Collibra. He's on the Cube. We're excited to have you, Felix. Good to see you again. >> Likewise Dave. Thanks for having me again. >> You bet. All right, we're going to get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever, and get current on what Collibra has been up to over the past year, and what's changed since Data Citizens 2021. And we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends, and we're not just snapping back to the 2010s. That's clear. And that's really true, as well, in the world of data. So what's different in your mind in the data landscape of the 2020s from the previous decade, and what challenges does that bring for your customers? >> Yeah, absolutely. And I think you said it well, Dave, in the intro that rising complexity and fragmentation in the broader data landscape that hasn't gotten any better over the last couple of years. When we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use, has only gotten kind of more difficult. So that trend is continuing. I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under with respect to data, as data becomes more mission critical, as data becomes more impactful and important, the level of scrutiny with respect to privacy, security, regulatory compliance, is only increasing as well. Which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. So it's become much more acute. And to your earlier point, we do live in a different world, and the past couple of years, we could probably just kind of brute force it, right? We could focus on the top line. There was enough kind of investments to be had. I think nowadays organizations are focused, or are in a very different environment where there's much more focus on cost control, productivity, efficiency. How do we truly get value from that data? So again, I think it's just another incentive for organizations to now truly look at that data and to scale that data, not just from a technology and infrastructure perspective, but how do we actually scale data from an organizational perspective, right? Like you said, the people and process, how do we do that at scale? And that's only becoming much more important. And we do believe that the economic environment that we find ourselves in today is going to be a catalyst for organizations to really take that more seriously if you will than they maybe have in the past. >> You know, I don't know when you guys founded Collibra, if you had a sense as to how complicated it was going to get, but you've been on a mission to really address these problems from the beginning. How would you describe your mission, and what are you doing to address these challenges? >> Yeah, absolutely. We started Collibra in 2008. So in some sense in the last kind of financial crisis. And that was really the start of Collibra, where we found product market fit working with large financial institutions to help them cope with the increasing compliance requirements that they were faced with because of the financial crisis, and kind of here we are again in a very different environment of course, 15 years, almost 15 years later. But data only becoming more important. But our mission to deliver trusted data for every user, every use case, and across every source, frankly has only become more important. So while it's been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to, again, be able to provide everyone, and that's why we call it Data Citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy manner. That mission is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we're still relatively early in that journey. >> Well, that's interesting because, you know, in my observation, it takes seven to 10 years to actually build a company, and then the fact that you're still in the early days is kind of interesting. I mean, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your your current momentum? >> Yeah, absolutely. Again, there's a lot of tailwinds, organizations are only maturing their data practices, and we've seen it kind of transform, or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world, whether it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the market with some of the cloud partners like Google, Amazon, Snowflake, Databricks, and others, right? As those kind of new modern data infrastructures, modern data architectures, are definitely all moving to the cloud. A great opportunity for us, our partners, and of course our customers, to help them kind of transition to the cloud even faster. And so we see a lot of excitement and momentum there. We did an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging AI, machine learning, again to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously has become absolutely critical. So we're really excited about that as well. And on the organizational side, I'm sure you've heard a term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believed in. Federated, focused on domains, giving a lot of ownership to different teams. I think that's the way to scale the data organizations, and so that aligns really well with our vision, and from a product perspective, we've seen a lot of momentum with our customers there as well. >> Yeah, you know, a couple things there. I mean, the acquisition of OwlDQ, you know, Kirk Haslbeck and their team, it's interesting, you know, the whole data quality used to be this back office function and really confined to highly regulated industries. It's come to the front office, it's top of mind for chief data officers, data mesh, you mentioned. You guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're a critical part of many ecosystems, and you're developing your own ecosystem. So let's chat a little bit about the products. We're going to go deeper into products later on at Data Citizens '22, but we know you're debuting some new innovations, you know, whether it's, you know, the under the covers in security, sort of making data more accessible for people, just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. >> Yeah, absolutely. We're super excited, a ton of innovation. And if we think about the big theme, and like I said, we're still relatively early in this journey towards kind of that mission of data intelligence, that really bold and compelling mission. Either customers are just starting on that journey, and we want to make it as easy as possible for the organization to actually get started, because we know that's important that they do. And for our organization and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for, really to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving, a lot of kind of ease of adoption, ease of use, but also then, how do we make sure that as Collibra becomes this kind of mission critical enterprise platform from a security performance architecture scale, supportability that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme. From an innovation perspective, from a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One is around data marketplace. Again, a lot of our customers have plans in that direction. How do we make it easy? How do we make available a true kind of shopping experience so that anybody in your organization can, in a very easy search first way, find the right data product, find the right data set that data can then consume, use its analytics. How do we help organizations drive adoption, tell them where they're working really well, and where they have opportunities. Home pages, again, to make things easy for people, for anyone in your organization, to kind of get started with Collibra. You mentioned workflow designer, again, we have a very powerful enterprise platform. One of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code, kind of workflow designer experience. So really customers can take it to the next level. There's a lot more new product around Collibra Protect, which in partnership with Snowflake, which has been a strategic investor in Collibra, focused on how do we make access governance easier? How do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data, is managed in a much more effective way. Really excited about that product. There's more around data quality. Again, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud has been a big part of our strategy. So we launched our data quality cloud product as well as making use of those native compute capabilities in platforms like Snowflake, Databricks, Google, Amazon, and others. And so we are bettering a capability that we call push down. So we're actually pushing down the computer and data quality, the monitoring, into the underlying platform, which again, from a scale performance and ease of use perspective is going to make a massive difference. And then more broadly, we talked a little bit about the ecosystem. Again, integrations that we talk about, being able to connect to every source. Integrations are absolutely critical, and we're really excited to deliver new integrations with Snowflake, Azure, and Google Cloud Storage as well. So there's a lot coming out. The team has been at work really hard, and we are really, really excited about what we are coming, what we're bringing to markets. >> Yeah, a lot going on there. I wonder if you could give us your closing thoughts. I mean, you talked about the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles. You think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been been so hard, so how do you see sort of the future? And, you know, give us your closing thoughts please. >> Yeah, absolutely. And I think we're really at this pivotal moment, and I think you said it well. We all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not going to fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, the data intelligence platform. We are still early, making it as easy as we can. It's kind of our, as our mission. And so I'm really, really excited to see what we are going to, how the markets are going to evolve over the next few quarters and years. I think the trend is clearly there, when we talk about data mesh, this kind of federated approach, focus on data products is just another signal that we believe that a lot of our organizations are now at the time, they understand the need to go beyond just the technology, how to really, really think about how to actually scale data as a business function, just like we've done with IT, with HR, with sales and marketing, with finance. That's how we need to think about data. I think now's the time given the economic environment that we are in, much more focus on control, much more focus on productivity, efficiency, and now's the time we need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >> Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much, and good luck in San Diego. I know you're going to crush it out there. >> Thank you Dave. >> Yeah, it's a great spot for an in person event, and of course, the content post event is going to be available at collibra.com, and you can of course catch the Cube coverage at thecube.net, and all the news at siliconangle.com. This is Dave Vellante for the Cube, your leader in enterprise and emerging tech coverage. (light music)

Published Date : Oct 24 2022

SUMMARY :

And the premise that we put Thanks for having me again. of the 2020s from the previous decade, and the past couple of years, and what are you doing to and kind of here we are again What do people need to know And on the organizational side, And of course we see you at all the shows. for the organization to the technology to work and now's the time we need to look beyond I know you're going to crush it out there. and of course, the content post event

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Data Citizens '21 Preview with Felix Van de Maele, CEO, Collibra


 

>>At the beginning of the last decade, the technology industry was a buzzing because we were on the cusp of a new era of data. The promise of so-called big data was that it would enable data-driven organizations to tap a new form of competitive advantage. Namely insights from data at a much lower cost. The problem was data became plentiful, but insights. They remained scarce, a rash of technical complexity combined with a lack of trust due to conflicting data sources and inconsistent definitions led to the same story that we've heard for decades. We spent a ton of time and money to create a single version of the truth. And we're further away than we've ever been before. Maybe as an industry, we should be approaching this problem differently. Perhaps it should start with the idea that we have to change the way we serve business users. I E those who understand data context, and with me to discuss the evolving data space, his company, and the upcoming data citizens conference is Felix van de Mala, the CEO and founder of Collibra. Felix. Welcome. Great to see you. >>Great to see you. Great to be here. >>So tell us a little bit about Collibra and the problem that you're solving. Maybe you could double click on my upfront narrative. >>Yeah, I think you said it really well. Uh, we've seen so much innovation over the last couple of years in data, the exploding volume complexity of data. We've seen a lot of innovation of how to store and process that data, that, that volume of data more effectively or more cost-effectively, but fundamentally the source of the problem as being able to really derive insights from that data effectively when it's for an AI model or for reporting, it's still as difficult as it was, let's say 10 years ago. And if only in a way it's only become more, uh, more difficult. And so what we fundamentally believe is that next to that innovation on the infrastructure side of data, you really need to look at the people on process side of data. There's so many more people that today consume and produce data to do their job. >>That's why we talk about data citizens. They have to make it easier for them to find the right data in a way that they can trust that there's confidence in that data to be able to make decisions and to be able to trust the output of that, uh, of that model. And that's really what is focused on initially around governance. Uh, how do you make sure people actually are companies know what data they have and make sure they can trust it and they can use it in a compliant way. And now we've extended that into the only data intelligence platform today in the industry where we just make it easier for organizations to truly unite around the data across the whole organization, wherever that data is stored on premise and the cloud, whoever is actually using or consuming data. Uh, that's why we talk about data citizens. I >>Think you're right. I think it is more complex. There's just more of it. And there's more pressure on individuals to get advantage from it. But I, to ask you what sets Culebra apart, because I'd like you to explain why you're not just another data company chasing a problem with w it's going to be an incremental solution. It's really not going to change anything. What, what sets Collibra apart? >>Yeah, that's a really good question. And I think what's fundamentally sets us apart. What makes us unique is that we look at data or the problem around data as truly a business problem and a business function. So we fundamentally believe that if you believe that data is an asset, you really have to run it as a, as a, as a strategic business functions, just like your, um, uh, your HR function, your people function, your it functioning says a marketing function. You have a system to run that function. Now you have Salesforce to run sales and marketing. You have service now to run your, it function. You have Workday to run your people function, but you need the same system to really run your data from. And that's really how we think about GDPR. So we not another kind of faster, better database we know than other data management tool that makes the life of a single individual easier, which really a business application that focuses on how do we bring people together and effective rate so that they can collaborate around the data. It creates efficiency. So you don't have to do things ad hoc. You can easily find the right information. You can collaborate effectively. And it creates the confidence to actually be able to do something with the outcomes of it, the results of all of that work. And so fundamentally I'm looking at the problem as a, as a business function that needs a business system. We call it the system of record or system of engagement for the, for the data function, I think is absolutely critical and, and really unique in the, in our approach. So >>Data citizens are big user conference, data citizens, 21, it's coming up June 16th and 17th, the cubes stoked because we love talking about data. This is the first time we're bringing the cube to that event. So we're really gearing up for it. And I wonder if it could tell us a little bit about the history and the evolution of the data citizens conference? >>Absolutely. I think the first one is set at six years ago where we had a small event at a hotel downtown New York. Uh, most of the customers as their user conference, a lot of the banks, which are at the time of the main customers at 60 people. So very small events, and it exploded ever since, uh, this year we expect over 5,000 people. So it's really expanded beyond just the user conference to really become more of almost the community conference and the industry, um, the conference. So we're really excited, a big part of what we do, why we care so much about the conference. That's an opportunity to build that data citizens community. That's what we hear from our customers, from all attendees that come to the conference, uh, bring those people to get us all care about the same topic and are passionate about doing more at data, uh, being able to connect, uh, connect people together as a big part of that. So we've always, uh, we're always looking forwards, uh, through the event, uh, from that perspective >>Competition, of course, for virtual events these days with them, what's in it for me, what, who should attend and what can attendees expect from data citizens? 21. >>Yeah, absolutely. The good thing about the virtual event, uh, event is that everybody can attend. It's free, it's open from across the road, of course, but what we want for people to take away as attendees is that you learn something at pragmatics or the next day on the job, you can do something. You've learned something very specific. We've also been, um, um, excited and looked at what is possible from an innovation perspective. And so that's how we look at the events. We bring a lot of, um, uh, customers on my realization that they're going to share their best practices, very specifically, how they are, how they are handling data governance, how they're doing data, data, cataloging, how they're doing data privacy. So very specific best practices and tips on how to be successful, but then also industry experts that can paint the picture of where we going as an industry, what are the best practices? >>What do we need to think about today to be ready for what's going to come tomorrow? So that's a big focus. We, of course, we're going to talk about and our product. What are we, what do we have in store from a product roadmap and innovation perspective? How are we helping these organizations get their foster and not aspect as we were being in a lot of partners as well? Um, and so that's a big part of that broader ecosystem, uh, which is, which is really interesting. And I finally, like I said, it's really around the community, right? And that's what we hear continuously from the attendees. Just being able to make these connections, learn new people, learn what they're doing, how they've, uh, kind of, um, solved certain challenges. We hear that's a really big part of, uh, of the value proposition. So as an attendee, uh, the good thing is you can, you can join from anywhere. Uh, all of the content is going to be available on demand. So later it's going to be available for you to have to look at as well. Plus you're going to be farther out. You're going to become part of that data, citizens community, which has a really thriving and growing community where you're going to find a lot of like-minded people with the same passion, the same interest that McConnell learned the most from, well, I'd rather >>Like the term data citizen. I consider myself a data citizen, and it has implications just in terms of putting data in the hands of, of business users. So it's sort of central to this event, obviously. W what is a data citizen to Collibra? >>Yeah, it's, it's a really core part of our mission and our vision that we believe that today everyone needs data to do their job. Everyone in that sense has become a data citizen in the sense that they need to be able to easily access trustworthy data. We have to make it easy for people to easily find the right data that they can trust that they can understand. And I can do something like with and make their job easier. On the other hand, like a citizen, you have rights and you have responsibilities as a data citizen. You also have the responsibility to treat that data in the right way to make sure from a privacy and security perspective, that data is a as again, like I said, treated in the right way. And so that combination of making it easy, making it accessible, democratizing it, uh, but also making sure we treat data in the right way is really important. And that's a core part of what we believe that everyone is going to become a data citizen. And so, um, that's a big part of our mission. I like that >>We're to enter into a contract, I'll do my part and you'll give me access to that data. I think that's a great philosophy. So the call to action here, June 16th and 17th, go register@citizensdotcollibra.com go register because it's not just the normal mumbo jumbo. You're going to get some really interesting data. Felix, I'll give you the last word. >>No, like I said, it's like you said, go register. It's a great event. It's a great community to be part of June 16 at 17, you can block it in your calendar. So go to citizens up pretty bad outcome. It's going to be a, it's going to be a great event. Thanks for helping >>Us preview. Uh, this event is going to be a great event that really excited about Felix. Great to see you. And we'll see you on June 16th and 17th. Absolutely. All right. Thanks for watching everybody. This is Dave Volante for the cube. We'll see you next time.

Published Date : May 12 2021

SUMMARY :

At the beginning of the last decade, the technology industry was a buzzing because we were on Great to be here. So tell us a little bit about Collibra and the problem that you're solving. effectively or more cost-effectively, but fundamentally the source of the problem as being able to to be able to trust the output of that, uh, of that model. But I, to ask you what sets Culebra apart, And it creates the confidence to actually be able to do something with the the cubes stoked because we love talking about data. So it's really expanded beyond just the user conference to really become more of almost the community Competition, of course, for virtual events these days with them, what's in it for me, what, it's open from across the road, of course, but what we want for people to take Uh, all of the content is going to be available on demand. So it's sort of central to this event, You also have the responsibility to treat So the call to action here, June 16th and 17th, go register@citizensdotcollibra.com It's a great community to be part of June Uh, this event is going to be a great event that really excited about Felix.

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Felix Van de Maele, CEO, Collibra


 

(upbeat music) >> At the beginning of last decade technology industry was a buzzing because we were on the cusp of a new era of data. The promise of so-called big data was that it would enable data-driven organizations to tap a new form of competitive advantage. Namely insights from data at a much lower cost. The problem was data became plentiful, but insights, they remain scarce. A rash of technical complexity combined with a lack of trust due to conflicting data sources and inconsistent definitions led to the same story that we've heard for decades. We spent a ton of time and money to create a single version of the truth. And we're further away than we've ever been before. Maybe as an industry, we should be approaching this problem differently. Perhaps it should start with the idea that we have to change the way we serve business users i.e. those who understand data context. And with me, to discuss the evolving data space, his company and the upcoming Data Citizens Conference is Felix Van De Maele, the CEO and Founder, of Collibra. Felix, welcome. Great to see you. >> Great to see you. Great to be here. >> So tell us a little bit about Collibra and the problem that you're solving. Maybe you could double click on my upfront narrative. >> Yeah, I think you said it really well. We've seen so much innovation over the last couple of years in data, the exploding volume complexity of data. We've seen a lot of innovation of how to store and process that data, that volume of data more effectively, more cost-effectively. But fundamentally the source of the problem as being able to really derive insights from that data effectively when it's for an AI model or for reporting is still as difficult as it was let's say 10 years ago. And it only... In a way it's only become more difficult. And so what we fundamentally believe is that next to that innovation on the infrastructure side of data you really need to look at the people on process side of data. There are so many more people that today consume and produce data to do their job. That's why we talk about data citizens. They have to make it easier for them to find the right data in a way that they can trust that there's confidence in that data to be able to make decisions and to be able to trust the algorithm of that model. And that's really what Collibra is focused on. Initially, around governance. How do you make sure people actually or companies know what data they have and make sure they can trust it and they can use it in a compliant way. And now we've extended that into the only data intelligence platform today in the industry where we just make it easier for organizations to truly unite around the data across the whole organization. wherever that data stored on premise and the cloud whoever is actually using or consuming that data. That's why we talk about data citizens. >> I think you're right. I think yours is more complex. There's more of it. And there's more pressure on individuals to get advantage from it. But I want to ask you, what sets Collibra apart because I'd like you to explain why you're not just another data company chasing a problem with it's going to be an incremental solution, it's really not going to change anything. What sets Collibra apart? >> Yeah, that's a really good question. And what fundamentally sets us apart, or makes us unique is that we look at data or the problem around data as truly a business owner and a business function. So we fundamentally believe that if you believe that data is an asset, you really have to run it as a strategic business function. Just like you run your HR function, your people function, your IT function your sales and marketing function. You have a system to run that function. And you have Salesforce to run sales and marketing. You have service now to run your IT function. You have word day to run your people function. Like you need the same system to really run your data function. And that's really how we think about Collibra. So we're not another kind of faster better database. We're not another data management tool that makes the life of a single individual easier. We're truly a business application that focuses on how do we bring people together and effective rates so that they can collaborate around the data. It creates efficiency. So you don't have to do things ad hoc. You can easily find the right information. You can collaborate effectively. And it creates the confidence to actually be able to do something with the outcomes or with the results of all of that work. And so fundamentally, looking at the problem as a business function that needs a business system. We call it the system of record or system of engagement. For the data function, I think it's absolutely a critical and really unique in our approach. >> So Data Citizens your big user conference. Data Citizens '21 it's coming up June 16th and 17th cubes stoked because we love talking about data. This is the first time we're bringing theCUBE to that event. And so we're really gearing up for it. And I wonder if you can tell us a little bit about the history and the evolution of the Data Citizens conference? >> Absolutely. I think the first one it started six years ago where we had a small event at a hotel downtown New York mostly customers as their user conference, a lot of the banks, which are at the time are the main customers at 60 people. So very small events. And it's exploded ever since this year, we expect over 5,000 people. So it's really expanded beyond just a user conference to really become more of almost a community conference and an industry conference. So we're really excited. A big part of what we do, why we care so much about the conference. That's an opportunity to build that data citizens community. That's where we hear from our customers, from all attendees that come to the conference, bring those people together that all care about the same topic and are passionate about doing more with data, being able to connect people together as a big part of that. So we've always... We're always looking forward to event from that perspective. >> Well, a lot of competition of course, for virtual events these days with them. What's in it for me? Who should attend? And what can attendees expect from Data Citizens '21? >> Yeah, absolutely. The good thing about the virtual event is that everybody can attend. It's free, it's open from across the world, of course. But what we want for people to take away as attendees is that you learn something pragmatic. So the next day on the job, you can do something. You've learned something very specific. We've also been excited and looked at what is possible from an innovation perspective? And so that's how we look at the event. We bring a lot of customers and organization that are going to share their best practices. Very specifically, how they're handling data governance. How they're doing data cataloging. How they're doing data privacy. So very specific best practices and tips on how to be successful, but then also industry experts that can paint a picture of where we're going as an industry, what are the best practices? What do we need to think about today to be ready for what's going to come tomorrow? So that's a big focus. We, of course, we're going to talk about Collibra and our product. What do we have in store from a product roadmap. And innovation perspective, how we're helping these organizations get there faster and all that aspect as we bring in a lot of partners as well. And so that's a big part of that broader ecosystem which is really interesting. And I finally, like I said it's really around the community. That's what we hear continuously from the attendees. Just being able to make these connections, learn new people, learn what they're doing how they've kind of solved certain challenges. We hear that's a really big part of the value proposition. So as an attendee, the good thing is you can join from anywhere. All of the content is going to be available on demand. So later it's going to be available for you to have to look at as well. Plus you're going to be part, or you're going to become part of that data citizens community. Which is a really thriving and growing community where you're going to find a lot of like-minded people with the same passion, the same interest, that we can all learn a lot from. >> I rather like the term data citizen. I consider myself a data citizen and it has implications just in terms of putting data in the hands of business users. So it's just sort of central to this event, obviously. What is a data citizen to Collibra? >> Yeah. It's a really core part of our mission and our vision that we believe that today everyone needs data to do their job. Everyone in that sense has become a data citizen in the sense that they need to be able to easily access trustworthy data. We have to make it easy for people to easily find the right data that they can trust, that they can understand and they can do something with and make their job easier. On the other hand, like a citizen, you have rights and you have responsibilities. As a data citizen, you also have the responsibility to treat that data in the right way. To make sure from a privacy and security perspective, that data is as again like I said, treated in the right way. And so that combination of making it easy, making it accessible, democratizing it but also making sure we treat data in the right way is really important. And it's a core part of what we believe that everyone is going to become a data citizen. And so that's a big part of our mission. >> I like that. We're going to enter into a contract. I'll do my part and you'll give me access to that data. I think that's a great philosophy. So the call to action here, June 16th and 17th go register at citizens.collibra.com go register because it's not just the normal mumbo jumbo. You're going to get some really interesting data. Felix, I'll give you the last word. >> No, like I said, like you said, go register. It's a great event. It's a great community to be part of at June 16th and 17th you can block it in your calendar. So go to citizens.collibra.com. It's going to be a great event. >> Well, thanks for helping us preview this event. It's going to be a great event that we're really excited about. Felix, great to see you. And we'll see you on June 16th and 17th. >> Absolutely. >> All right. Thanks for watching everyone. This is Dave Vellante for theCUBE. We'll see you next time. (upbeat music)

Published Date : May 10 2021

SUMMARY :

and the upcoming Data Citizens Conference Great to be here. and the problem that you're solving. in that data to be able to make decisions it's really not going to change anything. And it creates the confidence to actually and the evolution of the a lot of the banks, And what can attendees expect and tips on how to be successful, What is a data citizen to Collibra? in the sense that they need to be able So the call to action here, It's a great community to be part of It's going to be a great event We'll see you next time.

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Gabriela de Queiroz, Microsoft | WiDS 2023


 

(upbeat music) >> Welcome back to theCUBE's coverage of Women in Data Science 2023 live from Stanford University. This is Lisa Martin. My co-host is Tracy Yuan. We're excited to be having great conversations all day but you know, 'cause you've been watching. We've been interviewing some very inspiring women and some men as well, talking about all of the amazing applications of data science. You're not going to want to miss this next conversation. Our guest is Gabriela de Queiroz, Principal Cloud Advocate Manager of Microsoft. Welcome, Gabriela. We're excited to have you. >> Thank you very much. I'm so excited to be talking to you. >> Yeah, you're on theCUBE. >> Yeah, finally. (Lisa laughing) Like a dream come true. (laughs) >> I know and we love that. We're so thrilled to have you. So you have a ton of experience in the data space. I was doing some research on you. You've worked in software, financial advertisement, health. Talk to us a little bit about you. What's your background in? >> So I was trained in statistics. So I'm a statistician and then I worked in epidemiology. I worked with air pollution and public health. So I was a researcher before moving into the industry. So as I was talking today, the weekly paths, it's exactly who I am. I went back and forth and back and forth and stopped and tried something else until I figured out that I want to do data science and that I want to do different things because with data science we can... The beauty of data science is that you can move across domains. So I worked in healthcare, financial, and then different technology companies. >> Well the nice thing, one of the exciting things that data science, that I geek out about and Tracy knows 'cause we've been talking about this all day, it's just all the different, to your point, diverse, pun intended, applications of data science. You know, this morning we were talking about, we had the VP of data science from Meta as a keynote. She came to theCUBE talking and really kind of explaining from a content perspective, from a monetization perspective, and of course so many people in the world are users of Facebook. It makes it tangible. But we also heard today conversations about the applications of data science in police violence, in climate change. We're in California, we're expecting a massive rainstorm and we don't know what to do when it rains or snows. But climate change is real. Everyone's talking about it, and there's data science at its foundation. That's one of the things that I love. But you also have a lot of experience building diverse teams. Talk a little bit about that. You've created some very sophisticated data science solutions. Talk about your recommendation to others to build diverse teams. What's in it for them? And maybe share some data science project or two that you really found inspirational. >> Yeah, absolutely. So I do love building teams. Every time I'm given the task of building teams, I feel the luckiest person in the world because you have the option to pick like different backgrounds and all the diverse set of like people that you can find. I don't think it's easy, like people say, yeah, it's very hard. You have to be intentional. You have to go from the very first part when you are writing the job description through the interview process. So you have to be very intentional in every step. And you have to think through when you are doing that. And I love, like my last team, we had like 10 people and we were so diverse. Like just talking about languages. We had like 15 languages inside a team. So how beautiful it is. Like all different backgrounds, like myself as a statistician, but we had people from engineering background, biology, languages, and so on. So it's, yeah, like every time thinking about building a team, if you wanted your team to be diverse, you need to be intentional. >> I'm so glad you brought up that intention point because that is the fundamental requirement really is to build it with intention. >> Exactly, and I love to hear like how there's different languages. So like I'm assuming, or like different backgrounds, I'm assuming everybody just zig zags their way into the team and now you're all women in data science and I think that's so precious. >> Exactly. And not only woman, right. >> Tracy: Not only woman, you're right. >> The team was diverse not only in terms of like gender, but like background, ethnicity, and spoken languages, and language that they use to program and backgrounds. Like as I mentioned, not everybody did the statistics in school or computer science. And it was like one of my best teams was when we had this combination also like things that I'm good at the other person is not as good and we have this knowledge sharing all the time. Every day I would feel like I'm learning something. In a small talk or if I was reviewing something, there was always something new because of like the richness of the diverse set of people that were in your team. >> Well what you've done is so impressive, because not only have you been intentional with it, but you sound like the hallmark of a great leader of someone who hires and builds teams to fill gaps. They don't have to know less than I do for me to be the leader. They have to have different skills, different areas of expertise. That is really, honestly Gabriela, that's the hallmark of a great leader. And that's not easy to come by. So tell me, who were some of your mentors and sponsors along the way that maybe influenced you in that direction? Or is that just who you are? >> That's a great question. And I joke that I want to be the role model that I never had, right. So growing up, I didn't have anyone that I could see other than my mom probably or my sister. But there was no one that I could see, I want to become that person one day. And once I was tracing my path, I started to see people looking at me and like, you inspire me so much, and I'm like, oh wow, this is amazing and I want to do do this over and over and over again. So I want to be that person to inspire others. And no matter, like I'll be like a VP, CEO, whoever, you know, I want to be, I want to keep inspiring people because that's so valuable. >> Lisa: Oh, that's huge. >> And I feel like when we grow professionally and then go to the next level, we sometimes we lose that, you know, thing that's essential. And I think also like, it's part of who I am as I was building and all my experiences as I was going through, I became what I mentioned is unique person that I think we all are unique somehow. >> You're a rockstar. Isn't she a rockstar? >> You dropping quotes out. >> I'm loving this. I'm like, I've inspired Gabriela. (Gabriela laughing) >> Oh my God. But yeah, 'cause we were asking our other guests about the same question, like, who are your role models? And then we're talking about how like it's very important for women to see that there is a representation, that there is someone they look up to and they want to be. And so that like, it motivates them to stay in this field and to start in this field to begin with. So yeah, I think like you are definitely filling a void and for all these women who dream to be in data science. And I think that's just amazing. >> And you're a founder too. In 2012, you founded R Ladies. Talk a little bit about that. This is present in more than 200 cities in 55 plus countries. Talk about R Ladies and maybe the catalyst to launch it. >> Yes, so you always start, so I'm from Brazil, I always talk about this because it's such, again, I grew up over there. So I was there my whole life and then I moved to here, Silicon Valley. And when I moved to San Francisco, like the doors opened. So many things happening in the city. That was back in 2012. Data science was exploding. And I found out something about Meetup.com, it's a website that you can join and go in all these events. And I was going to this event and I joke that it was kind of like going to the Disneyland, where you don't know if I should go that direction or the other direction. >> Yeah, yeah. >> And I was like, should I go and learn about data visualization? Should I go and learn about SQL or should I go and learn about Hadoop, right? So I would go every day to those meetups. And I was a student back then, so you know, the budget was very restricted as a student. So we don't have much to spend. And then they would serve dinner and you would learn for free. And then I got to a point where I was like, hey, they are doing all of this as a volunteer. Like they are running this meetup and events for free. And I felt like it's a cycle. I need to do something, right. I'm taking all this in. I'm having this huge opportunity to be here. I want to give back. So that's what how everything started. I was like, no, I have to think about something. I need to think about something that I can give back. And I was using R back then and I'm like how about I do something with R. I love R, I'm so passionate about R, what about if I create a community around R but not a regular community, because by going to this events, I felt that as a Latina and as a woman, I was always in the corner and I was not being able to participate and to, you know, be myself and to network and ask questions. I would be in the corner. So I said to myself, what about if I do something where everybody feel included, where everybody can participate, can share, can ask questions without judgment? So that's how R ladies all came together. >> That's awesome. >> Talk about intentions, like you have to, you had that go in mind, but yeah, I wanted to dive a little bit into R. So could you please talk more about where did the passion for R come from, and like how did the special connection between you and R the language, like born, how did that come from? >> It was not a love at first sight. >> No. >> Not at all. Not at all. Because that was back in Brazil. So all the documentation were in English, all the tutorials, only two. We had like very few tutorials. It was not like nowadays that we have so many tutorials and courses. There were like two tutorials, other documentation in English. So it's was hard for me like as someone that didn't know much English to go through the language and then to learn to program was not easy task. But then as I was going through the language and learning and reading books and finding the people behind the language, I don't know how I felt in love. And then when I came to to San Francisco, I saw some of like the main contributors who are speaking in person and I'm like, wow, they are like humans. I don't know, it was like, I have no idea why I had this love. But I think the the people and then the community was the thing that kept me with the R language. >> Yeah, the community factors is so important. And it's so, at WIDS it's so palpable. I mean I literally walk in the door, every WIDS I've done, I think I've been doing them for theCUBE since 2017. theCUBE has been here since the beginning in 2015 with our co-founders. But you walk in, you get this sense of belonging. And this sense of I can do anything, why not? Why not me? Look at her up there, and now look at you speaking in the technical talk today on theCUBE. So inspiring. One of the things that I always think is you can't be what you can't see. We need to be able to see more people that look like you and sound like you and like me and like you as well. And WIDS gives us that opportunity, which is fantastic, but it's also helping to move the needle, really. And I was looking at some of the Anitab.org stats just yesterday about 2022. And they're showing, you know, the percentage of females in technical roles has been hovering around 25% for a while. It's a little higher now. I think it's 27.6 according to any to Anitab. We're seeing more women hired in roles. But what are the challenges, and I would love to get your advice on this, for those that might be in this situation is attrition, women who are leaving roles. What would your advice be to a woman who might be trying to navigate family and work and career ladder to stay in that role and keep pushing forward? >> I'll go back to the community. If you don't have a community around you, it's so hard to navigate. >> That's a great point. >> You are lonely. There is no one that you can bounce ideas off, that you can share what you are feeling or like that you can learn as well. So sometimes you feel like you are the only person that is going through that problem or like, you maybe have a family or you are planning to have a family and you have to make a decision. But you've never seen anyone going through this. So when you have a community, you see people like you, right. So that's where we were saying about having different people and people like you so they can share as well. And you feel like, oh yeah, so they went through this, they succeed. I can also go through this and succeed. So I think the attrition problem is still big problem. And I'm sure will be worse now with everything that is happening in Tech with layoffs. >> Yes and the great resignation. >> Yeah. >> We are going back, you know, a few steps, like a lot of like advancements that we did. I feel like we are going back unfortunately, but I always tell this, make sure that you have a community. Make sure that you have a mentor. Make sure that you have someone or some people, not only one mentor, different mentors, that can support you through this trajectory. Because it's not easy. But there are a lot of us out there. >> There really are. And that's a great point. I love everything about the community. It's all about that network effect and feeling like you belong- >> That's all WIDS is about. >> Yeah. >> Yes. Absolutely. >> Like coming over here, it's like seeing the old friends again. It's like I'm so glad that I'm coming because I'm all my old friends that I only see like maybe once a year. >> Tracy: Reunion. >> Yeah, exactly. And I feel like that our tank get, you know- >> Lisa: Replenished. >> Exactly. For the rest of the year. >> Yes. >> Oh, that's precious. >> I love that. >> I agree with that. I think one of the things that when I say, you know, you can't see, I think, well, how many females in technology would I be able to recognize? And of course you can be female technology working in the healthcare sector or working in finance or manufacturing, but, you know, we need to be able to have more that we can see and identify. And one of the things that I recently found out, I was telling Tracy this earlier that I geeked out about was finding out that the CTO of Open AI, ChatGPT, is a female. I'm like, (gasps) why aren't we talking about this more? She was profiled on Fast Company. I've seen a few pieces on her, Mira Murati. But we're hearing so much about ChatJTP being... ChatGPT, I always get that wrong, about being like, likening it to the launch of the iPhone, which revolutionized mobile and connectivity. And here we have a female in the technical role. Let's put her on a pedestal because that is hugely inspiring. >> Exactly, like let's bring everybody to the front. >> Yes. >> Right. >> And let's have them talk to us because like, you didn't know. I didn't know probably about this, right. You didn't know. Like, we don't know about this. It's kind of like we are hidden. We need to give them the spotlight. Every woman to give the spotlight, so they can keep aspiring the new generation. >> Or Susan Wojcicki who ran, how long does she run YouTube? All the YouTube influencers that probably have no idea who are influential for whatever they're doing on YouTube in different social platforms that don't realize, do you realize there was a female behind the helm that for a long time that turned it into what it is today? That's outstanding. Why aren't we talking about this more? >> How about Megan Smith, was the first CTO on the Obama administration. >> That's right. I knew it had to do with Obama. Couldn't remember. Yes. Let's let's find more pedestals. But organizations like WIDS, your involvement as a speaker, showing more people you can be this because you can see it, >> Yeah, exactly. is the right direction that will help hopefully bring us back to some of the pre-pandemic levels, and keep moving forward because there's so much potential with data science that can impact everyone's lives. I always think, you know, we have this expectation that we have our mobile phone and we can get whatever we want wherever we are in the world and whatever time of day it is. And that's all data driven. The regular average person that's not in tech thinks about data as a, well I'm paying for it. What's all these data charges? But it's powering the world. It's powering those experiences that we all want as consumers or in our business lives or we expect to be able to do a transaction, whether it's something in a CRM system or an Uber transaction like that, and have the app respond, maybe even know me a little bit better than I know myself. And that's all data. So I think we're just at the precipice of the massive impact that data science will make in our lives. And luckily we have leaders like you who can help navigate us along this path. >> Thank you. >> What advice for, last question for you is advice for those in the audience who might be nervous or maybe lack a little bit of confidence to go I really like data science, or I really like engineering, but I don't see a lot of me out there. What would you say to them? >> Especially for people who are from like a non-linear track where like going onto that track. >> Yeah, I would say keep going. Keep going. I don't think it's easy. It's not easy. But keep going because the more you go the more, again, you advance and there are opportunities out there. Sometimes it takes a little bit, but just keep going. Keep going and following your dreams, that you get there, right. So again, data science, such a broad field that doesn't require you to come from a specific background. And I think the beauty of data science exactly is this is like the combination, the most successful data science teams are the teams that have all these different backgrounds. So if you think that we as data scientists, we started programming when we were nine, that's not true, right. You can be 30, 40, shifting careers, starting to program right now. It doesn't matter. Like you get there no matter how old you are. And no matter what's your background. >> There's no limit. >> There was no limits. >> I love that, Gabriela, >> Thank so much. for inspiring. I know you inspired me. I'm pretty sure you probably inspired Tracy with your story. And sometimes like what you just said, you have to be your own mentor and that's okay. Because eventually you're going to turn into a mentor for many, many others and sounds like you're already paving that path and we so appreciate it. You are now officially a CUBE alumni. >> Yes. Thank you. >> Yay. We've loved having you. Thank you so much for your time. >> Thank you. Thank you. >> For our guest and for Tracy's Yuan, this is Lisa Martin. We are live at WIDS 23, the eighth annual Women in Data Science Conference at Stanford. Stick around. Our next guest joins us in just a few minutes. (upbeat music)

Published Date : Mar 8 2023

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but you know, 'cause you've been watching. I'm so excited to be talking to you. Like a dream come true. So you have a ton of is that you can move across domains. But you also have a lot of like people that you can find. because that is the Exactly, and I love to hear And not only woman, right. that I'm good at the other Or is that just who you are? And I joke that I want And I feel like when You're a rockstar. I'm loving this. So yeah, I think like you the catalyst to launch it. And I was going to this event And I was like, and like how did the special I saw some of like the main more people that look like you If you don't have a community around you, There is no one that you Make sure that you have a mentor. and feeling like you belong- it's like seeing the old friends again. And I feel like that For the rest of the year. And of course you can be everybody to the front. you didn't know. do you realize there was on the Obama administration. because you can see it, I always think, you know, What would you say to them? are from like a non-linear track that doesn't require you to I know you inspired me. you so much for your time. Thank you. the eighth annual Women

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Charu Kapur, NTT Data & Rachel Mushahwar, AWS & Jumi Barnes, Goldman Sachs | AWS re:Invent 2022


 

>>Hey everyone. Hello from Las Vegas. Lisa Martin here with you, and I'm on the show floor at Reinvent. But we have a very special program series that the Cube has been doing called Women of the Cloud. It's brought to you by aws and I'm so pleased to have an excellent panel of women leaders in technology and in cloud to talk about their tactical recommendations for you, what they see as found, where they've helped organizations be successful with cloud. Please welcome my three guests, Tara Kapor, president and Chief Revenue Officer, consulting and Digital Transformations, NTT Data. We have Rachel Mu, aws, head of North America, partner sales from aws, and Jimmy Barnes joins us as well, managing director, investment banking engineering at Goldman Sachs. It is so great to have you guys on this power panel. I love it. Thank you for joining me. >>Thank >>You. Let's start with you. Give us a little bit of, of your background at NTT Data and I, and I understand NTT has a big focus on women in technology and in stem. Talk to us a little bit about that and then we'll go around the table. >>Perfect, thank you. Thank you. So brand new role for me at Entity Data. I started three months back and it's a fascinating company. We are about 22 billion in size. We work across industries on multiple innovative use cases. So we are doing a ton of work on edge analytics in the cloud, and that's where we are here with aws. We are also doing a ton of work on the private 5G that we are rolling out and essentially building out industry-wide use cases across financial services, manufacturing, tech, et cetera. Lots of women identity. We essentially have women run cloud program today. We have a gal called Nore Hanson who is our practice leader for cloud. We have Matine who's Latifa, who's our AWS cloud leader. We have Molly Ward who leads up a solutions on the cloud. We have an amazing lady in Mona who leads up our marketing programs. So a fantastic plethora of diverse women driving amazing work identity on cloud. >>That's outstanding to hear because it's one of those things that you can't be what you can't see. Right. We all talk about that. Rachel, talk a little bit about your role and some of the focus that AWS has. I know they're big customer obsession, I'm sure obsessed with other things as well. >>Sure. So Rachel Muir, pleased to be here again. I think this will be my third time. So a big fan of the Cube. I'm fortunate enough to lead our North America partner and channel business, and I'll tell you, I've been at AWS for a little under two years, and honestly, it's been probably the best two years of my career. Just in terms of where the cloud is, where it's headed, the business outcomes that we can deliver with our customers and with our partners is absolutely remarkable. We get to, you know, make the impossible possible every day. So I'm, I'm thrilled to be here and I'm thrilled to, to be part of this inaugural Women of the Cloud panel. >>Oh, I'm prepared to have all three of you. One of the things that feedback, kind of pivoting off what, Rachel, one of the things that you said that one of our guests, some of several of our guests have said is that coming out of Adams keynote this morning, it just seems limitless what AWS can do and I love that it gives me kind of chills what they can do with cloud computing and technology, with its ecosystem of partners with its customers like Goldman Sachs. Jimmy, talk to us a little bit about you, your role at Goldman Sachs. You know, we think of Goldman Sachs is a, is a huge financial institution, but it's also a technology company. >>Yeah. I mean, since the age of 15 I've been super passionate about how we can use technology to transform business and simplify modernized business processes. And it's, I'm so thrilled that I have the opportunity to do that at Goldman Sachs as an engineer. I recently moved about two years ago into the investment banking business and it's, you know, it's best in class, one of the top companies in terms of mergers and acquisitions, IPOs, et cetera. But what surprised me is how technology enables all the businesses across the board. Right? And I get to be leading the digital platform for building out the digital platform for in the investment banking business where we're modernizing and transforming existing businesses. These are not new businesses. It's like sometimes I liken it to trying to change the train while it's moving, right? These are existing businesses, but now we get to modernize and transform on the cloud. Right. Not just efficiency for the business by efficiency for technologists as >>Well. Right, right. Sticking with you, Jimmy. I wanna understand, so you've been, you've been interested in tech since you were young. I only got into tech and accidentally as an adult. I'm curious about your career path, but talk to us about that. What are some of the recommendations that you would have for other women who might be looking at, I wanna be in technology, but I wanna work for some of the big companies and they don't think about the Goldman Sachs or some of the other companies like Walmart that are absolutely technology driven. What's your advice for those women who want to grow their career? >>I also, growing up, I was, I was interested in various things. I, I loved doing hair. I used to do my own hair and I used to do hair for other students at school and I was also interested in running an entertainment company. And I used actually go around performing and singing and dancing with a group of friends, especially at church. But what amazed me is when I landed my first job at a real estate agent and everything was being done manually on paper, I was like, wow, technology can bring transformation anywhere and everywhere. And so whilst I have a myriad of interest, there's so many ways that technology can be applied. There's so many different types of disciplines within technology. It's not, there's hands on, like I'm colder, I like to code, but they're product managers, there are business analysts, there are infrastructure specialist. They're a security specialist. And I think it's about pursuing your passion, right? Pursuing your passion and identifying which aspects of technology peak your interest. And then diving in. >>Love that. Diving in. Rachel, you're shaking your head. You definitely are in alignment with a lot of what >>Duties I am. So, you know, interesting enough, I actually started my career as a civil engineer and eventually made it into, into technology. So very similar. I saw in, you know, heavy highway construction how manual some of these processes were. And mind you, this was before the cloud. And I sat down and wrote a little computer program to automate a lot of these manual tasks. And for me it was about simplification of the customer journey and really figuring out how do you deliver value. You know, on fast forward, say 20 plus years, here I am with AWS who has got this amazing cloud platform with over 200 services. And when I think about what we do in tech, from business transformation to modernizing to helping customers think about how do they create new business models, I've really found, I've really found my sweet spot, and I'll say for anyone who wants to get into tech or even switch careers, there's just a couple words of advice that I have. And it's really two words, just start. >>Yes, >>That's it. Just start. Because sometimes later becomes never. And you know, fuel your passion, be curious, think about new things. Yes. And just >>Start, I love that. Just start, you should get t-shirts made with that. Tell me a little bit about some of your recommendations. Obviously just start is great when follow your passion. What would you say to those out there looking to plan the letter? >>So, you know, my, my story's a little bit like jus because I did not want to be in tech. You know, I wanted an easy life. I did well in school and I wanted to actually be an air hostess. And when I broke that to my father, you know, the standard Indian person, now he did, he, you know, he wanted me to go in and be an engineer. Okay? So I was actually push into computer engineering, graduated. But then really two things today, right? When I look back, really two pieces, two areas I believe, which are really important for success. One is, you know, we need to be competent. And the second is we need to be confident, right? Yes, yes. It's so much easier to be competent because a lot of us diverse women, diverse people tend to over rotate on knowing their technical skills, right? Knowing technical skills important, but you need to know how to potentially apply those to business, right? Be able to define a business roi. And I see Julie nodding because she wants people to come in and give her a business ROI for programs that you're executing at Goldman Sachs. I presume the more difficult part though is confidence. >>Absolutely. It's so hard, especially when, when we're younger, we don't know. Raise your hand because I guarantee you either half the people in the, in the room or on the zoom these days weren't listening or have the same question and are too afraid to ask because they don't have the confidence. That's right. Give me, let's pivot on confidence for a minute, Jim, and let's go back to how would you advise your younger self to find your confidence? >>That's, that's a tough one because I feel like even this older self is still finding exercise to, to be real. But I think it's about, I would say it's not praise. I think it's about praising yourself, like recognizing your accomplishments. When I think about my younger self, I think I, I like to focus more on what I didn't do or what I didn't accomplish, instead of majoring and focusing on all the accomplishments and the achievements and reminding myself of those day after day after day. And I think it's about celebrating your wins. >>I love that. Celebrating your wins. Do you agree, Rachel? >>I do. Here's the hard part, and I look around this table of amazing business leaders and I can guarantee that every single one of us sometime this year woke up and said, oh my gosh, I don't know how to do that. Oh >>Yeah. But >>What we haven't followed that by is, I don't know how to do that yet. Right. And here's the other thing I would tell my younger self is there will be days where every single one of us falls apart. There will be days when we feel like we failed at work. There will be days when you feel like you failed as a parent or you failed as a spouse. There'll be days where you have a kid in the middle of target screaming and crying while you're trying to close a big business deal and you just like, oh my gosh, is this really my life? But what I would tell my younger self is, look, the crying, the chaos, the second guessing yourself, the successes, every single one of those are milestones. And it's triumphant, it's tragic, but every single thing that we have been through is fiercely worthwhile. And it's what got us >>Here. Absolutely. Absolutely. Think of all the trials and tribulations and six and Zacks that got you to this table right now. Yep. So Terry, you brought up confidence. How would you advise the women out there won't say you're gonna know stuff. The women out there now that are watching those that are watching right there. Hi. How would you advise them to really find their, their ability to praise themselves, recognize all of the trials and the tribulations as milestones as Rachel said, and really give themselves a seat at the table, raise their hand regardless of who else is in the room? >>You know, it's a, it's a more complex question just because confidence stems from courage, right? Confidence also stems from the belief that you're going to be treated fairly right now in an organization for you to be treated fairly. You need to have, be surrounded by supporters that are going to promote your voice. And very often women don't invest enough in building that support system around them. Yeah. Right. We have mentors, and mentors are great because they come in and they advise us and they'll tell us what we need to go out and do. We really need a team of sponsors Yes. Who come in and support us in the moment in the business. Give us the informal channel because very often we are not plugged into the informal channel, right. So we don't get those special projects or assignments or even opportunities to prove that we can do the tough task. Yeah. So, you know, my, my advice would be to go out and build a network of sponsors. Yes. And if you don't have one, be a sponsor for someone else. That's right. I love that. Great way to win sponsorship is by extending it todos. >>And sometimes too, it's about, honestly, I didn't even know the difference between a mentor and a sponsor until a few years ago. And I started thinking, who are I? And then I started realizing who they were. That's right. And some of the conversations that we've had on the cube about women in technology, women of the cloud with some of the women leaders have said, build, and this is kind of like, sort of what you were saying, build your own personal board of directors. Yeah. And that, oh, it gives me chills. It's just, it's so important for, for not just women, but anybody, for everybody. But it's so important to do that. And if you, you think about LinkedIn as an example, you have a network, it's there, utilize it, figure out who your mentors are, who your sponsors are, who are gonna help you land the next thing, start building that reputation. But having that board of directors that you can kind of answer to or have some accountability towards, I think is hugely very >>Important. Yeah. >>Very important. I think, you know, just for, just for those that are listening, a really important distinction for me was mentors are people that you have that help you with, Hey, here's the situation that you were just in. They advise you on the situation. Sponsors are the people that stick up for you when you're not in the room to them. Right. Sponsors are the ones that say, Hey, I think so and so not only needs to have a seat at the table, but they need to build the table. And that's a really important delineation. Yeah. Between mentors and sponsors. And everybody's gotta have a sponsor both within their company and outside of their company. Someone that's advocating for them on their behalf when they don't even know it. Yeah. Yeah. >>I love that you said that. Build the table. It reminds me of a quote that I heard from Will I am, I know, very random. It was a podcast he did with Oprah Winfrey on ai. He's very into ai and I was doing a panel on ai, so I was doing a lot of research and he said, similar for Rachel to build the table, don't wait for a door to open. You go build a door. And I just thought, God, that is such brilliant advice. It is. It's hard to do. It is. Especially when, you know, the four of us in this room, there's a lot of women around here, but we are in an environment where we are the minority women of color are also the minority. What do you guys think where tech is in terms of de and I and really focusing on De and I as as really a very focused strategic initiative. Turner, what do you think? >>So, you know, I just, I, I spoke earlier about the women that we have at Entity Data, right? We have a fabulous team of women. And joining this team has been a moment of revelation for me coming in. I think to promote dni, we all need to start giving back, right? Yes. So today, I would love to announce that we at Entity would like to welcome all of you out there. You know, folks that have diverse ideas, you know, ISV, partners with diverse solutions, thought leaders out there who want to contribute into the ecosystem, right? Customers out there who want to work with companies that are socially responsible, right? We want to work with all of you, come back, reach out to us and be a part of the ecosystem because we can build this together, right? AWS has an amazing platform that gives us an opportunity to do things differently. Yes. Right. Entity data is building a women powered cloud team. And I want to really extend that out to everyone else to be a part this ecosystem, >>But a fantastic opportunity. You know, when we talk about diversity and inclusion and equity, it needs to be intentional for organization. It sounds very intentional at ntt. I know that that intention is definitely there at AWS as well. What are your thoughts on where tech is with respect to diversity? Even thought diversity? Because a lot of times we tend to go to our comfort zones. We do. And so we tend to start creating these circles of kind of like, you know, think tanks and they think alike people to go outside of that comfort zone. It's part of building the table, of building the, is the table and getting people from outside your comfort zone to come in and bring in diverse thought. Because can you imagine the potential of technology if we have true thought diversity in an organization? >>Right? It's, it's incredible. So one of the things that I always share with my team is we've got the opportunity to really change the outcome, right? As you know, you talked about Will I am I'm gonna talk about Bono from you too, right? One of, one of his favorite quotes is, we are the people we've been waiting for. Oh, I love that. And when you think about that, that is us. There is no one else that's gonna change the outcome and continue to deliver some of the business outcomes and the innovation that we are if we don't continue to raise our hand and we don't continue to, to inspire the next generation of leaders to do the same thing. And what I've found is when you start openly sharing what your innovation ideas are or how you're leveraging your engineering background, your stories and your successes, and, and frankly, some of your failures become the inspiration for someone you might not even know. Absolutely. And that's the, you know, that's the key. You're right. Inclusion, diversity, equity and accessibility, yes. Have to be at the forefront of every business decision. And I think too often companies think that, you know, inclusion, diversity, equity and accessibility is one thing, and business outcomes are another. And they're not. No, they are one in the same. You can't build business outcomes without also focusing on inclusion, diversity, equity, accessibility. That's the deliberate piece. >>And, and it has to be deliberate. Jimmy, I wanna ask you, we only have a couple of minutes left, but you're a woman in tech, you're a woman of color. What was that like for you? You, you were very intentional knowing when you were quite young. Yeah. What you wanted to do, but how have you navigated that? Because I can't imagine that was easy. >>It wasn't. I remember, I always tell the story and the, the two things that I really wanted to emphasize today when I thought about this panel is rep representation matters and showing up matters, right? And there's a statement, there's a flow, I don't know who it's attributed to, but be the change you want to see. And I remember walking through the doors of Goldman Sachs 15 years ago and not seeing a black female engineer leader, right? And at that point in time, I had a choice. I could be like, oh, there's no one look like, there's no one that looks like me. I don't belong here. Or I could do what I actually did and say, well, I'm gonna be that person. >>Good, >>Right? I'm going to be the chain. I'm going to show up and I am going to have a seat at the table so that other people behind me can also have a seat at the table. And I think that I've had the privilege to work for a company who has been inclusive, who has had the right support system, the right structures in place, so that I can be that person who is the first black woman tech fellow at Goldman Sachs, who is one of the first black females to be promoted up the rank as a, from analysts to managing director at the company. You know, that was not just because I determined that I belong here, but because the company ensure that I felt that I belong. >>Right. >>That's a great point. They ensure that you felt that. Yeah. You need to be able to feel that. Last question, we've only got about a minute left. 2023 is just around the corner. What comes to your mind, Jimmy will stick with you as you head into the new year. >>Sorry, can you repeat >>What comes to mind priorities for 2023 that you're excited about? >>I'm excited about the democratization of data. Yeah. I'm excited about a lot of the announcements today and I, I think there is a, a huge shift going on with this whole concept of marketplaces and data exchanges and data sharing. And I think both internally and externally, people are coming together more. Companies are coming together more to really de democratize and make data available. And data is power. But a lot of our businesses are running, running on insights, right? And we need to bring that data together and I'm really excited about the trends that's going on in cloud, in technology to actually bring the data sets together. >>Touro, what are you most excited about as we head to 2023? >>I think I'm really excited about the possibilities that entity data has right here, right now, city of Las Vegas, we've actually rolled out a smart city project. So saving citizens life, using data edge analytics, machine learning, being able to predict adverse incidents before they happen, and then being able to take remediation action, right? So that's technology actually working in real time to give us tangible results. We also sponsor the Incar races. Lots of work happening there in delivering amazing customer experience across the platform to millions of users real time. So I think I'm just excited about technology coming together, but while that's happening, I think we really need to be mindful at this time that we don't push our planet into per right. We need to be sustainable, we need to be responsible. >>Absolutely. Rachel, take us out. What are you most excited about going into 2023? >>So, you know, there are so many trends that are, that we could talk about, but I'll tell you at aws, you know, we're big. We, we impact the world. So we've gotta be really thoughtful and humble about what it is that we do. So for me, what I'm most excited about is, you know, one of our leadership principles is about, you know, with what broad responsibility brings, you know, you've got to impact sustainability and many of those other things. And for me, I think it's about waking up every day for our customers, for our partners, and for the younger generations. And being better, doing better, and making better for this planet and for, you know, the future generations to come. So >>I think your tag line just start applies to all of that. It does. It has been an absolute pleasure. And then really an honor to talk to you on the program. Thank you all for joining me, sharing your experiences, sharing what you've accomplished, your recommendations for those others who might be our same generation or older or younger. All really beautiful advice. Thank you so much for your time and your insights. We appreciate it. >>Thank you. Thank you. >>For my guests, I'm Lisa Martin. You're watching The Cube, the leader in live enterprise and emerging tech coverage. Thanks for watching.

Published Date : Nov 30 2022

SUMMARY :

It is so great to have you guys on this power panel. Talk to us a little bit about that and then we'll go around the table. So we are doing a ton of work on edge analytics in the That's outstanding to hear because it's one of those things that you can't be what you can't see. the business outcomes that we can deliver with our customers and Jimmy, talk to us a little bit about you, your role at Goldman Sachs. And I get to be leading the digital platform What are some of the recommendations that you would have for other And I think it's about pursuing Rachel, you're shaking your head. So, you know, interesting enough, I actually started my career as a And you know, fuel your passion, be curious, What would you say to And when I broke that to my father, you know, the standard Indian Give me, let's pivot on confidence for a minute, Jim, and let's go back to how would you advise your And I think it's about celebrating your wins. Do you agree, Rachel? don't know how to do that. And here's the other thing I would tell my younger self is there and Zacks that got you to this table right now. And if you don't have one, be a sponsor for someone else. some of the women leaders have said, build, and this is kind of like, sort of what you were saying, build your own personal board Yeah. Sponsors are the people that stick up for you when you're not in the room I love that you said that. You know, folks that have diverse ideas, you know, ISV, And so we tend to start creating these circles of kind of like, you know, think tanks and they think alike And when you think about that, that What you wanted to do, but how have you navigated that? but be the change you want to see. And I think that I've Jimmy will stick with you as you head into the new year. And I think both internally and We need to be sustainable, we need to be responsible. What are you most excited about going into 2023? this planet and for, you know, the future generations to come. And then really an honor to talk to you on the program. Thank you. and emerging tech coverage.

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Noor Shadid, Wells Fargo | AnsibleFest 2022


 

(melodic music) >> Good afternoon. Welcome back to Chicago. Lisa Martin here with John Furrier. Day one of our coverage of Ansible Fest 2022. John, it's great to be back in person. People are excited to be here. >> Yeah. We've had some great conversations with folks from Ansible and the community and the partner side. >> Yeah. One of the things I always love talking about John, is talking with organizations that have been around for a long time that maybe history, maybe around nearly a hundred years, how are they embracing technology to modernize? Yeah, we got a great segment here with the financial services leader, end user of Ansible. So it's be great segment. >> Absolutely. Please welcome Noor Shadid to the program, the senior SVP, excuse me, senior technology manager at Wells Fargo. Noor it's great to have you on theCUBE. Thank you for joining us. >> Of course. Happy to be here. >> Thanks. >> Talk a little bit about technology at Wells Fargo. I was mentioning to you I've been a longtime customer and I've seen the bank evolve incredibly so in the years I've been with it. But... >> Yeah. >> ...talk about Wells Fargo was a technology-driven company. >> Yeah. So I like to consider Wells, right? Being in a financial institution company. So I consider us a technology company that does banking as a customer, right? Like we were talking about. There's so much that we've been able to release over the couple of years, right? I mean, decades worth of automation and technology has been coming out, but lately, right? The way we provide for our customers, how fast at scale, what we're doing for our customers, it's been, it's been significant, right? And I think our goal is always how can we enhance the process for our customers and how can we provide them the next best thing? And I think technology has really allowed us to evolve with our customers. >> The customers. We are so demanding these days. Right? I think one of the things that short supplied in the last two years was patience and tolerance. >> Yes. >> People. And I don't think that's going to rubber band back? >> Yeah. No, I don't think so. >> So how, talk to us about how Wells is using automation to really drive innovation and, surprise and delight those customers on a minute by minute basis. >> Yeah. And so, you know, if you think about banking, we've been able, with automation, we've been able to bring banking into the 21st century. You do not have to go to a branch to manage your money anymore. You do not have to go, you know, go to deposit your check inside of a branch. You can do it through your mobile app, right? That's driven by automation and innovation, right? And, you know, we have all of these back ends tools working for us to help get us to this next generation of, of banking. We can instantly send money to each other. We don't have to worry about, I need to go and figure out how I'm going to get money to this person and I need to wait, you know, X amount of days. You, you have the ability and you have, you feel safe being able to manage your money at the organization. And so automation has really allowed us to get to this place where we can constantly enhance and provide features and reliability to our customers. >> It's interesting you mentioned that you guys are a technology can have it do banking reminds me of the old iPhone analogy. It's a computer that happens to make phone calls. >> Yeah. >> So like, this is the similar mindset. How do you guys keep up? >> Yeah. >> With the technology? >> So it's tough, right? Because there's so much that comes out. And I think the only thing that's constant in technology is change, right? Because it's constantly evolving. But what we do is we, integrate very well with these new tools. We do proof of concepts where we try to, you know, what's on the market, what's hot, how can we involve, like, how can we involve these new tools in our processes? How can we provide a better end result for our customers by bringing in these new tools? So we have a lot of different teams that bring, you know, their jobs are to like, do these proof of concepts and help us build and evolve our own strategies, right? So it keeps us, it keeps us on our toes and I think it keeps, you know, all these new things that are coming out in the market. We're a part of it. We want to evolve with those, what the latest and greatest is. And it's, it's been working right as customers of financial services and us managing our money through, you know, through banks. It's been great. >> So the business is the application. >> Yes. >> And how do you guys make that happen when it comes down to getting the teams aligned? What's the culture like? Explain. >> Yeah. So at Wells we have evolved so much over the, over the last few years. The culture right now is we want to make changes. You know, we are making changes. We want to drive through innovation. We want to be able to provide our, you know, it's a developer centric approach right now, right? We want to push to the next and the greatest. And so everybody is excited and everybody's adapting to all of what's happening in the environment right now. So it's been great because we are able to use all of these new features and tools and things that we were just talking about by allowing our developers to do that work and allowing people to learn these new skills and be able to apply them in their jobs, which is now creating this, you know, a better result for our customers because we're releasing at such a faster pace. And at scale. >> Talk about how, you talked about multiple groups in the organization really investing in innovative technology. How do you get buy-in? What's that sort of pyramid like up to the top level? >> Yeah. >> Because to your point, you're making changes very quickly and consumers demand it. >> Yep. >> You can do everything from home these days. >> Yep. >> You don't have to go into a branch. >> Yeah, yeah. >> Which has changed dramatically in the last it's. >> Powerful few years. Yeah. >> But how, what's that buy-in conversation like from our leadership? >> Yeah. If you don't have leadership buy-in, it's very difficult to make those changes happen. But we at Wells have such a strong support from our leadership to be a part of the change and be, you know, constantly evolve and get better. So the way we work, cause we're such a large organization, you know, we bring in our business, you know, our business teams and we talk to them about what is it that's best going to better our customers. How do we also not just support external but internal, right? How do we provide these automated tools or processes for people to want to do this next work and, and do these, you know, these new releases for our customers. And so we bring in our business partners and, and we bring in our leadership and, our stakeholders and we kind of present to them, you know, this is what we're trying to do. This is the return that you'll get. This is what our customers will also receive. And this is, you know, this is how we keep evolving with that. >> How has the automation culture changed? Because big discussion here is reuse, teamwork, I call it multiplayer kind of organizations where people are working together. 'Cause that's a big theme of automation. >> Yeah. >> Reuse, leverage. >> Yep. >> Can you explain how you guys look at that? >> Yeah. It's changed the way that we do banking because we're eliminating a lot of the repetitive tasks in the toil because we have partners that are developing these, you know, services. So specifically with Ansible, we have these playbooks, rather than having every customer write the same playbook but with their own little, you know, flavor to it, we're able to create these generic patterns that customers can just consume simply by just going into a tool, filling out you know, filling out that playbook template, credentials, or whatever it is that they need and executing it. They don't have to worry about developing something from scratch. And it also allows our customers to feel safe because they don't have to have those skills out the box to be able to use these automation tools, right? They can use what's already been written and executed. >> So that make things go faster with the benefits or what? Speed? >> Faster stability, right? We're now speed, stability, scalability, because we're now able to use this at scale. It's not just individual teams trying to do this within small spaces. We're able to reliable, right? Automation allows us to be reliable internally and for our customers. Because you're not asking, there's no human intervention when you're automating, right? You have these opportunities now for people to just, it's one click, you know, one click solution or you're, you're end to end. You got self-healing involved. It's really driving the way that we do our work today. >> So automation sounds like it's really fueling the internal employee experience at Wells... >> Yes. >> ...as well as the customer experience. And those two things are like this to me. They're inextricably linked. >> A hundred percent because if you need it, they need to be together, right? You want your internal to also be happy because they want to be able to develop these solutions and provide these automation opportunities for our teams, right? And so with the customers, they're constantly seeing these great features come out, right? We can, you know, with AIML today, we're now able to detect fraud significantly. What we would've, what we could've done a couple years ago. And, and developers are excited to be able to do that, right? To be able to learn all these new tools and new technologies. >> What's interesting Wells is you guys are like an edge application. Obviously everyone's got banking in their hand. FinTech obviously money's involved. So there's people interested in getting that money. >> Yeah. >> Security hackers or whatnot. So when you got speed and you got the consistency, I get that. As you look at securing the app, that becomes a big part of what, what's the conversations like there? >> Yeah. >> 'Cause that's the number one concern. And it's an Edge app. I got my mobile, I got my desktop. >> Yeah. >> Everything's in the cloud on premise. >> Yeah. And, and I think for us, security is number one. You know, we want to make sure that we are providing the best for our customers and that they feel safe. Banking, whatever financial service you're working with, you want to feel like you can trust that your money with those services. Right? So what we do is we make sure that our security partners are with us from day one. They're a part of the process. They're automating their pieces as well. We don't want to rely on humans to do a lot of the manual work and do the checking and the logging. You want it to be through automation and new tools, right? You want it to be done through trusted services. You don't, you know, security is right there with us. They're part of our technology organization. They are in the technology org. So they're the ones that are helping us get to that next generation to provide, you know, more secure processes and services for customers. >> And that's key for trust. >> Yes. >> And trust is critical to reduce churn and to, you know, increase the customer lifetime value. But, but people, I mean, especially with the amount of generations that are alive today in banking, you need to be able to deliver that trust intrinsically to any customer. >> Yes, a hundred percent. And you want to be able to not only trust the service but yourself that you can do it. You know, when you go into your app and you make a payment, or when you go in and you want to send, you know, you want to send money to a different, you know, a different bank account, you want to be able to know that what you just did is secure and is where you plan to send it. And so being able to create that environment and provide those services is, is everything right for our customers. >> What are some of the state-of-the-art kind of techniques or trade craft around building apps? 'Cause I mean, basically you're digitally transformed. I mean, you guys are technology first. >> Yeah. >> The app is the company. >> Yeah. >> That's, that's the bank. How do you stay current? What's some of the state of the art things that you guys do that wasn't around just a few years ago? >> Yeah, I mean, right now just using, we're using tools like Terraform and Ansible. We're making sure that those two are hand in hand working well together. So when we work on provisioning, when we, during provisioning where it's all, you know, it's automated, fully end to end, you know, AI ops, right? Being able to detect reoccurring issues that are happening. So if you have a incident we want to learn from that incident and we want to be able to create, you know, incident tickets without having to rely on a human to find that, you know, that problem that was occurring and self-healing, right? All of this is starting to evolve and bringing in the, the proper alerting tools, bringing in the pro, you know, the right automation tools to allow that self-healing to work. That's, you know, these are things that we didn't have, you know, year, decade ago. This is all coming out now as we're starting to progress and, and really take innovation and, you know, automation itself.... >> What's the North star internally when you guys say, hey, you know, down five years down the road, bridge to the future, we're transforming, we've continued to innovate. Scale is a big deal. Data, data sovereignty, all these things are coming up. And what's the internal conversation like when you talk about a future state? >> Yeah, I think right now we're on our cloud transformation journey, right? We're moving right now. We have workloads into our two CSPs or public cloud. Also providing a better service for infrastructure and being able to provide services internally at a faster space, right? So moving into the public cloud, making sure everything's virtualized, moving away from hard, you know, physical hardware or physical servers. That's kind of the journey that we're on right now. Right? Also, machine learning. We want to be able to rely on these, you know, bots. We want to be able to rely on, on things learning from what we're doing so that we don't make the same mistakes again. >> Where would you say the most value or the highest ROI that you've gotten from automation today? Where is that in the organization? >> There's so much, but what I mean because of all of the work that we're doing, there's a lot that I could list, but what I will say is that the ability to allow self-healing in our environments without causing issues is a very big return. Automating failovers, right? I think a lot of our financial institutions have made that a priority where they want to make sure that their applications are active, active and also that when things do go wrong, there is something in place to make sure that that incident actually doesn't, you know, take down any problems. I think it's just also investing in people. Right now, the market is hot and we want to make sure that people feel like they're being able to contribute, they're using the latest and greatest tools. They're able to upskill within our own environments at the firm. And I think our organization does an amazing job of prioritizing people. And so we see the return because we're prioritizing people. And I think, you know, a lot of institutions are trying, you know, people first, people first. But I can say that at Wells, because we are actually driving this, we're allowing, you know, we're enforcing that. We want our engineers to get the certifications. We're providing, you know, vouchers so that people can get those clouds certifications. It's when you do that and you put people first, everything kind of comes together. And I think, you know, a lot of what we see in our industry, it's not really the technology that's the problem, it's process because you're so, you know, we're working at large scales. Our environments are massive. So, you know, my three years at Wells have seen a significant amount of change that has really driven us to be.... >> On that point better. How about changing of the roles? IT, I mean, back in the day, IT serves the business, you know, IT is the business now, right? As, as you've been pointing out. What does the roles change of as automation scales in, is it the operator? I mean, we know what's going on with dev's devs are doing more IT in the CICD pipe lining. >> Yep. >> So we see that velocity check, good cloud native development. What's the op scene look like? It seems to be a multi-tool role. >> Yeah. >> Where the versatility of the skill set... >> Yep. >> ...is the quick learner. >> Yep, able to adapt. >> And yeah, what's your view on this new persona that's emerging from this new opportunity? >> Yeah, and I think it's a great question because if you think about where we're going, and even the term DevOps, right? It means so many things to different people. But literally when you think about what DevOps is allowing our developers and our operations to work together on one team, it's allowing, you know, our operation engineers aren't, you know, years ago, ops engineers were not doing the development work. They were relying on somebody to do the development work and they were just supporting making sure our systems were always available, right? Our engineers are ops are now doing the development work. They're able to contribute and to get, they're writing their own playbooks. They're able to take them into production and ensure that they're, being used correctly. We are change driven execution organization. Everything is driven through change and allowing our ops engineers or production score engineers to write their own playbooks, right? And they know what's happening in the environment. It's powerful. >> Yeah. You're seeing DevOps become a job title. >> Yeah (laughs). >> Used to be like a function of philosophy... >> Yeah, yeah. >> ... and then SRE's... >> SRE's. >> SRE are like how many servers do you have? I don't know, a cloud, what's next? (all laugh) >> What's next? Yeah, I think with SREs it's, you know, it's important that if you have site reliability engineers, you're working towards, you know, those non-functional requirements... >> Yeah. >> ...making sure that you're handling those key components that are required to ensure that our systems, our applications and our integrations, you know, are up there and they're meeting the standards that we set for those other faults. >> And, and I think Red Hat Ansible nailed it here because infrastructure is code. We get that infrastructure has configuration as code, but OPS says code really is that SRE outcome. SRE also came from the Google background, but that means infrastructure's just doing, it's thing. >> Yes. >> The ops is automated. >> Yes. >> That's an interesting concept. >> Yeah, because it's not, you know, it's still new, right? A lot of organizations used to see, and they probably still see operations as being the, you know, their role is just to make sure that the lights are on and they have specific access so they, you know, they're not touching code, but the people that are doing the work and know the environment should really be the ones under creating the content for it. So yeah, I mean it's crazy what's happening now. >> So I got an analogy that's going to be banking analogy, but for tech, you know, back in the automation, Oh, going to put my job out of business, ATMs are going to put the teller out of business as more tellers now than there are before the ATMs. So that metaphor applies into tech where people are like, "What am I auto? What's automating away? Is it my job?" And so actually people know it's not. >> Yeah. >> But what does that free up? So if you assume, if you believe that's good, you say, okay, all the grunt work and the low level on differentiated heavy lifting gets automated away. >> Yeah. >> Great. What does that free up the talent to do? >> Yeah, so when you, and that's great that you bring it up because I think people fear, you know, of automation, especially people that weren't doing automation in the past and now their roles are now they're able to automate those roles out. They're fearful that they don't have a space, a role anymore. But that's not the case at all. What we prioritize is now that those new engineers have this new skill set, apply them. Start using it to be a part of this transformation, right? We're moving from, we went from physical to virtual to now, you know, we're moving into the public, moving into the cloud, right? And that, that transformation, you need people who are ramping up their skill sets, you know, being a part of one of the tools that I own is terraform at Wells that, you know, right now our priority is we're trying to ramp up the organization to learn terraform, right? We want people to learn, you know, this new syntax, this new, you know, HCL and it's, you know, people have been automating some of the stuff that they're doing in their day to day and now trying to learn something new so that they can contribute to this new transformation. >> So new functionality, higher value services? >> Yes, yeah. >> It brings tremendous opportunity for those folks involved in automation. >> Yes. >> or on so many levels. >> Yep. >> Last question, Noor for you is what, you know, as we are rounding out calendar year 2022, entering into 2023, that patience is, that we talked about is still not coming back. What's next for Wells as a technology company that does banking? >> I mean, you name it, we're working on it, because we want to be able to deliver the best for our customers. And I think right now, you know, our digital transformation strategy and, and moving into the public cloud and getting our applications re-architected so that we are moving into microservice driven apps, right? We're moving these workloads into the public cloud in a seamless way. We're not lifting and shifting so that we're not causing more problems into the environment. Right. And I think our, our, our goal is right, Like I was saying earlier, people and evolving with the technology that's coming out. We're not, you know, we are a part of the change and we are happy to be a part of that change and making those changes happen. >> People first. >> Awesome, awesome stuff. >> Automation first sounds outstanding and I will never look at Wells Fargo as a bank again. >> Yeah. (laughter) >> Perfect. Perfect. >> Yeah, that's awesome. >> It's been such a pleasure having you on the program, talking about how transformative Wells has been and continues to be. >> Yeah. >> We appreciate your insights and your time. >> Thank you. >> Thank you so much. It was lovely being her. Pleasure here. Thank you guys. >> For our guest and John Furrier, I'm Lisa Martin. You've been watching theCUBE all day, I'm sure, live from Chicago at Ansible Fest 2022. We hope you have a wonderful rest of your day and John and I will see you tomorrow morning.

Published Date : Oct 19 2022

SUMMARY :

John, it's great to be back in person. and the community and the partner side. One of the things I always Noor it's great to have you on theCUBE. Happy to be here. I was mentioning to you I've ...talk about Wells Fargo So I like to consider Wells, right? short supplied in the last that's going to rubber band back? So how, talk to us about You do not have to go, you know, mentioned that you guys are a How do you guys keep up? teams that bring, you know, And how do you guys make that provide our, you know, How do you get buy-in? Because to your point, You can do everything dramatically in the last it's. Yeah. the change and be, you know, How has the automation culture changed? out the box to be able to it's one click, you know, it's really fueling the internal things are like this to me. We can, you know, with AIML today, is you guys are like an edge So when you got speed and 'Cause that's the number one concern. generation to provide, you know, reduce churn and to, you know, to a different, you know, you guys are technology first. the art things that you guys do bringing in the pro, you know, you know, down five years down the road, on these, you know, bots. And I think, you know, you know, IT is the business now, right? It seems to be a multi-tool role. of the skill set... aren't, you know, years ago, Yeah. Used to be like a with SREs it's, you know, integrations, you know, SRE also came from the Google background, access so they, you know, but for tech, you know, So if you assume, if you believe What does that free up the talent to do? HCL and it's, you know, those folks involved in automation. for you is what, you know, I think right now, you know, I will never look at Yeah. Perfect. having you on the program, We appreciate your Thank you so much. We hope you have a wonderful

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Rainer Richter, Horizon3.ai | Horizon3.ai Partner Program Expands Internationally


 

(light music) >> Hello, and welcome to theCUBE's special presentation with Horizon3.ai with Rainer Richter, Vice President of EMEA, Europe, Middle East and Africa, and Asia Pacific, APAC Horizon3.ai. Welcome to this special CUBE presentation. Thanks for joining us. >> Thank you for the invitation. >> So Horizon3.ai, driving global expansion, big international news with a partner-first approach. You guys are expanding internationally. Let's get into it. You guys are driving this new expanse partner program to new heights. Tell us about it. What are you seeing in the momentum? Why the expansion? What's all the news about? >> Well, I would say in international, we have, I would say a similar situation like in the US. There is a global shortage of well-educated penetration testers on the one hand side. On the other side, we have a raising demand of network and infrastructure security. And with our approach of an autonomous penetration testing, I believe we are totally on top of the game, especially as we have also now starting with an international instance. That means for example, if a customer in Europe is using our service, NodeZero, he will be connected to a NodeZero instance, which is located inside the European Union. And therefore, he doesn't have to worry about the conflict between the European GDPR regulations versus the US CLOUD Act. And I would say there, we have a total good package for our partners that they can provide differentiators to their customers. >> You know, we've had great conversations here on theCUBE with the CEO and the founder of the company around the leverage of the cloud and how successful that's been for the company. And obviously, I can just connect the dots here, but I'd like you to weigh in more on how that translates into the go-to-market here because you got great cloud scale with the security product you guys are having success with. Great leverage there, I'm seeing a lot of success there. What's the momentum on the channel partner program internationally? Why is it so important to you? Is it just the regional segmentation? Is it the economics? Why the momentum? >> Well, there are multiple issues. First of all, there is a raising demand in penetration testing. And don't forget that in international, we have a much higher level number or percentage in SMB and mid-market customers. So these customers, typically, most of them even didn't have a pen test done once a year. So for them, pen testing was just too expensive. Now with our offering together with our partners, we can provide different ways how customers could get an autonomous pen testing done more than once a year with even lower costs than they had with a traditional manual pen test, and that is because we have our Consulting PLUS package, which is for typically pen testers. They can go out and can do a much faster, much quicker pen test at many customers after each other. So they can do more pen test on a lower, more attractive price. On the other side, there are others or even the same one who are providing NodeZero as an MSSP service. So they can go after SMP customers saying, "Okay, you only have a couple of hundred IP addresses. No worries, we have the perfect package for you." And then you have, let's say the mid-market. Let's say the thousand and more employees, then they might even have an annual subscription. Very traditional, but for all of them, it's all the same. The customer or the service provider doesn't need a piece of hardware. They only need to install a small piece of a Docker container and that's it. And that makes it so smooth to go in and say, "Okay, Mr. Customer, we just put in this virtual attacker into your network, and that's it and all the rest is done." And within three clicks, they can act like a pen tester with 20 years of experience. >> And that's going to be very channel-friendly and partner-friendly, I can almost imagine. So I have to ask you, and thank you for calling out that breakdown and segmentation. That was good, that was very helpful for me to understand, but I want to follow up, if you don't mind. What type of partners are you seeing the most traction with and why? >> Well, I would say at the beginning, typically, you have the innovators, the early adapters, typically boutique-size of partners. They start because they are always looking for innovation. Those are the ones, they start in the beginning. So we have a wide range of partners having mostly even managed by the owner of the company. So they immediately understand, okay, there is the value, and they can change their offering. They're changing their offering in terms of penetration testing because they can do more pen tests and they can then add others ones. Or we have those ones who offered pen test services, but they did not have their own pen testers. So they had to go out on the open market and source pen testing experts to get the pen test at a particular customer done. And now with NodeZero, they're totally independent. They can go out and say, "Okay, Mr. Customer, here's the service. That's it, we turn it on. And within an hour, you are up and running totally." >> Yeah, and those pen tests are usually expensive and hard to do. Now it's right in line with the sales delivery. Pretty interesting for a partner. >> Absolutely, but on the other hand side, we are not killing the pen tester's business. We are providing with NodeZero, I would call something like the foundational work. The foundational work of having an ongoing penetration testing of the infrastructure, the operating system. And the pen testers by themselves, they can concentrate in the future on things like application pen testing, for example. So those services, which we are not touching. So we are not killing the pen tester market. We are just taking away the ongoing, let's say foundation work, call it that way. >> Yeah, yeah. That was one of my questions. I was going to ask is there's a lot of interest in this autonomous pen testing. One because it's expensive to do because those skills are required are in need and they're expensive. (chuckles) So you kind of cover the entry-level and the blockers that are in there. I've seen people say to me, "This pen test becomes a blocker for getting things done." So there's been a lot of interest in the autonomous pen testing and for organizations to have that posture. And it's an overseas issue too because now you have that ongoing thing. So can you explain that particular benefit for an organization to have that continuously verifying an organization's posture? >> Certainly. So I would say typically, you have to do your patches. You have to bring in new versions of operating systems, of different services, of operating systems of some components, and they are always bringing new vulnerabilities. The difference here is that with NodeZero, we are telling the customer or the partner the package. We're telling them which are the executable vulnerabilities because previously, they might have had a vulnerability scanner. So this vulnerability scanner brought up hundreds or even thousands of CVEs, but didn't say anything about which of them are vulnerable, really executable. And then you need an expert digging in one CVE after the other, finding out is it really executable, yes or no? And that is where you need highly-paid experts, which where we have a shortage. So with NodeZero now, we can say, "Okay, we tell you exactly which ones are the ones you should work on because those are the ones which are executable. We rank them accordingly to risk level, how easily they can be used." And then the good thing is converted or in difference to the traditional penetration test, they don't have to wait for a year for the next pen test to find out if the fixing was effective. They run just the next scan and say, "Yes, closed. Vulnerability is gone." >> The time is really valuable. And if you're doing any DevOps, cloud-native, you're always pushing new things. So pen test, ongoing pen testing is actually a benefit just in general as a kind of hygiene. So really, really interesting solution. Really bringing that global scale is going to be a new coverage area for us, for sure. I have to ask you, if you don't mind answering, what particular region are you focused on or plan to target for this next phase of growth? >> Well, at this moment, we are concentrating on the countries inside the European Union plus United Kingdom. And of course, logically, I'm based in the Frankfurt area. That means we cover more or less the countries just around. So it's like the so-called DACH region, Germany, Switzerland, Austria, plus the Netherlands. But we also already have partners in the Nordic, like in Finland and Sweden. So we have partners already in the UK and it's rapidly growing. So for example, we are now starting with some activities in Singapore and also in the Middle East area. Very important, depending on let's say, the way how to do business. Currently, we try to concentrate on those countries where we can have, let's say at least English as an accepted business language. >> Great, is there any particular region you're having the most success with right now? Sounds like European Union's kind of first wave. What's the most- >> Yes, that's the first. Definitely, that's the first wave. And now with also getting the European INSTANCE up and running, it's clearly our commitment also to the market saying, "Okay, we know there are certain dedicated requirements and we take care of this." And we are just launching, we are building up this one, the instance in the AWS service center here in Frankfurt. Also, with some dedicated hardware, internet, and a data center in Frankfurt, where we have with the DE-CIX, by the way, the highest internet interconnection bandwidth on the planet. So we have very short latency to wherever you are on the globe. >> That's a great call out benefit too. I was going to ask that. What are some of the benefits your partners are seeing in EMEA and Asia Pacific? >> Well, I would say, the benefits for them, it's clearly they can talk with customers and can offer customers penetration testing, which they before even didn't think about because penetration testing in a traditional way was simply too expensive for them, too complex, the preparation time was too long, they didn't have even have the capacity to support an external pen tester. Now with this service, you can go in and even say, "Mr. Customer, we can do a test with you in a couple of minutes. We have installed a Docker container. Within 10 minutes, we have the pen test started. That's it and then we just wait." And I would say we are seeing so many aha moments then. On the partner side, when they see NodeZero the first time working, it's like they say, "Wow, that is great." And then they walk out to customers and show it to their typically at the beginning, mostly the friendly customers like, "Wow, that's great, I need that." And I would say the feedback from the partners is that is a service where I do not have to evangelize the customer. Everybody understands penetration testing, I don't have to describe what it is. The customer understanding immediately, "Yes. Penetration testing, heard about that. I know I should do it, but too complex, too expensive." Now for example, as an MSSP service provided from one of our partners, it's getting easy. >> Yeah, and it's great benefit there. I mean, I got to say I'm a huge fan of what you guys are doing. I like this continuous automation. That's a major benefit to anyone doing DevOps or any kind of modern application development. This is just a godsend for them, this is really good. And like you said, the pen testers that are doing it, they were kind of coming down from their expertise to kind of do things that should have been automated. They get to focus on the bigger ticket items. That's a really big point. >> Exactly. So we free them, we free the pen testers for the higher level elements of the penetration testing segment, and that is typically the application testing, which is currently far away from being automated. >> Yeah, and that's where the most critical workloads are, and I think this is the nice balance. Congratulations on the international expansion of the program, and thanks for coming on this special presentation. I really appreciate it. Thank you very much. >> You're welcome. >> Okay, this is theCUBE special presentation, you know, checking on pen test automation, international expansion, Horizon3.ai. A really innovative solution. In our next segment, Chris Hill, Sector Head for Strategic Accounts, will discuss the power of Horizon3.ai and Splunk in action. You're watching theCUBE, the leader in high tech enterprise coverage. (steady music)

Published Date : Sep 27 2022

SUMMARY :

Welcome to this special CUBE presentation. Why the expansion? On the other side, on the channel partner and that's it and all the rest is done." seeing the most traction with Those are the ones, they and hard to do. And the pen testers by themselves, and the blockers that are in there. in one CVE after the other, I have to ask you, if and also in the Middle East area. What's the most- Definitely, that's the first wave. What are some of the benefits "Mr. Customer, we can do a test with you the bigger ticket items. of the penetration testing segment, of the program, the leader in high tech

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Breaking Analysis Further defining Supercloud W/ tech leaders VMware, Snowflake, Databricks & others


 

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 at our inaugural super cloud 22 event we further refined the concept of a super cloud iterating on the definition the salient attributes and some examples of what is and what is not a super cloud welcome to this week's wikibon cube insights powered by etr you know snowflake has always been what we feel is one of the strongest examples of a super cloud and in this breaking analysis from our studios in palo alto we unpack our interview with benoit de javille co-founder and president of products at snowflake and we test our super cloud definition on the company's data cloud platform and we're really looking forward to your feedback first let's examine how we defl find super cloudant very importantly one of the goals of super cloud 22 was to get the community's input on the definition and iterate on previous work super cloud is an emerging computing architecture that comprises a set of services which are abstracted from the underlying primitives of hyperscale clouds we're talking about services such as compute storage networking security and other native tooling like machine learning and developer tools to create a global system that spans more than one cloud super cloud as shown on this slide has five essential properties x number of deployment models and y number of service models we're looking for community input on x and y and on the first point as well so please weigh in and contribute now we've identified these five essential elements of a super cloud let's talk about these first the super cloud has to run its services on more than one cloud leveraging the cloud native tools offered by each of the cloud providers the builder of the super cloud platform is responsible for optimizing the underlying primitives of each cloud and optimizing for the specific needs be it cost or performance or latency or governance data sharing security etc but those primitives must be abstracted such that a common experience is delivered across the clouds for both users and developers the super cloud has a metadata intelligence layer that can maximize efficiency for the specific purpose of the super cloud i.e the purpose that the super cloud is intended for and it does so in a federated model and it includes what we call a super pass this is a prerequisite that is a purpose-built component and enables ecosystem partners to customize and monetize incremental services while at the same time ensuring that the common experiences exist across clouds now in terms of deployment models we'd really like to get more feedback on this piece but here's where we are so far based on the feedback we got at super cloud 22. we see three deployment models the first is one where a control plane may run on one cloud but supports data plane interactions with more than one other cloud the second model instantiates the super cloud services on each individual cloud and within regions and can support interactions across more than one cloud with a unified interface connecting those instantiations those instances to create a common experience and the third model superimposes its services as a layer or in the case of snowflake they call it a mesh on top of the cloud on top of the cloud providers region or regions with a single global instantiation a single global instantiation of those services which spans multiple cloud providers this is our understanding from a comfort the conversation with benoit dejaville as to how snowflake approaches its solutions and for now we're going to park the service models we need to more time to flesh that out and we'll propose something shortly for you to comment on now we peppered benoit dejaville at super cloud 22 to test how the snowflake data cloud aligns to our concepts and our definition let me also say that snowflake doesn't use the term data cloud they really want to respect and they want to denigrate the importance of their hyperscale partners nor do we but we do think the hyperscalers today anyway are building or not building what we call super clouds but they are but but people who bar are building super clouds are building on top of hyperscale clouds that is a prerequisite so here are the questions that we tested with snowflake first question how does snowflake architect its data cloud and what is its deployment model listen to deja ville talk about how snowflake has architected a single system play the clip there are several ways to do this you know uh super cloud as as you name them the way we we we picked is is to create you know one single system and that's very important right the the the um [Music] there are several ways right you can instantiate you know your solution uh in every region of a cloud and and you know potentially that region could be a ws that region could be gcp so you are indeed a multi-cloud solution but snowflake we did it differently we are really creating cloud regions which are superposed on top of the cloud provider you know region infrastructure region so we are building our regions but but where where it's very different is that each region of snowflake is not one in instantiation of our service our service is global by nature we can move data from one region to the other when you land in snowflake you land into one region but but you can grow from there and you can you know exist in multiple clouds at the same time and that's very important right it's not one single i mean different instantiation of a system is one single instantiation which covers many cloud regions and many cloud providers snowflake chose the most advanced level of our three deployment models dodgeville talked about too presumably so it could maintain maximum control and ensure that common experience like the iphone model next we probed about the technical enablers of the data cloud listen to deja ville talk about snow grid he uses the term mesh and then this can get confusing with the jamaicani's data mesh concept but listen to benoit's explanation well as i said you know first we start by building you know snowflake regions we have today furry region that spawn you know the world so it's a worldwide worldwide system with many regions but all these regions are connected together they are you know meshed together with our technology we name it snow grid and that makes it hard because you know regions you know azure region can talk to a ws region or gcp regions and and as a as a user of our cloud you you don't see really these regional differences that you know regions are in different you know potentially clown when you use snowflake you can exist your your presence as an organization can be in several regions several clouds if you want geographic and and and both geographic and cloud provider so i can share data irrespective of the the cloud and i'm in the snowflake data cloud is that correct i can do that today exactly and and that's very critical right what we wanted is to remove data silos and and when you instantiate a system in one single region and that system is locked in that region you cannot communicate with other parts of the world you are locking the data in one region right and we didn't want to do that we wanted you know data to be distributed the way customer wants it to be distributed across the world and potentially sharing data at world scale now maybe there are many ways to skin the other cat meaning perhaps if a platform does instantiate in multiple places there are ways to share data but this is how snowflake chose to approach the problem next question how do you deal with latency in this big global system this is really important to us because while snowflake has some really smart people working as engineers and and the like we don't think they've solved for the speed of light problem the best people working on it as we often joke listen to benoit deja ville's comments on this topic so yes and no the the way we do it it's very expensive to do that because generally if you want to join you know data which is in which are in different regions and different cloud it's going to be very expensive because you need to move you know data every time you join it so the way we do it is that you replicate the subset of data that you want to access from one region from other regions so you can create this data mesh but data is replicated to make it very cheap and very performant too and is the snow grid does that have the metadata intelligence yes to actually can you describe that a little bit yeah snow grid is both uh a way to to exchange you know metadata about so each region of snowflake knows about all the other regions of snowflake every time we create a new region diary you know the metadata is distributed over our data cloud not only you know region knows all the regions but knows you know every organization that exists in our clouds where this organization is where data can be replicated by this organization and then of course it's it's also used as a way to uh uh exchange data right so you can exchange you know beta by scale of data size and we just had i was just receiving an email from one of our customers who moved more than four petabytes of data cross-region cross you know cloud providers in you know few days and you know it's a lot of data so it takes you know some time to move but they were able to do that online completely online and and switch over you know to the diff to the other region which is failover is very important also so yes and no probably means typically no he says yes and no probably means no so it sounds like snowflake is selectively pulling small amounts of data and replicating it where necessary but you also heard him talk about the metadata layer which is one of the essential aspects of super cloud okay next we dug into security it's one of the most important issues and we think one of the hardest parts related to deploying super cloud so we've talked about how the cloud has become the first line of defense for the cso but now with multi-cloud you have multiple first lines of defense and that means multiple shared responsibility models and multiple tool sets from different cloud providers and an expanded threat surface so listen to benoit's explanation here please play the clip this is a great question uh security has always been the most important aspect of snowflake since day one right this is the question that every customer of ours has you know how you can you guarantee the security of my data and so we secure data really tightly in region we have several layers of security it starts by by encrypting it every data at rest and that's very important a lot of customers are not doing that right you hear these attacks for example on on cloud you know where someone left you know their buckets uh uh open and then you know you can access the data because it's a non-encrypted uh so we are encrypting everything at rest we are encrypting everything in transit so a region is very secure now you know you never from one region you never access data from another region in snowflake that's why also we replicate data now the replication of that data across region or the metadata for that matter is is really highly secure so snow grits ensure that everything is encrypted everything is you know we have multiple you know encryption keys and it's you know stored in hardware you know secure modules so we we we built you know snow grids such that it's secure and it allows very secure movement of data so when we heard this explanation we immediately went to the lowest common denominator question meaning when you think about how aws for instance deals with data in motion or data and rest it might be different from how another cloud provider deals with it so how does aws uh uh uh differences for example in the aws maturity model for various you know cloud capabilities you know let's say they've got a faster nitro or graviton does it do do you have to how does snowflake deal with that do they have to slow everything else down like imagine a caravan cruising you know across the desert so you know every truck can keep up let's listen it's a great question i mean of course our software is abstracting you know all the cloud providers you know infrastructure so that when you run in one region let's say aws or azure it doesn't make any difference as far as the applications are concerned and and this abstraction of course is a lot of work i mean really really a lot of work because it needs to be secure it needs to be performance and you know every cloud and it has you know to expose apis which are uniform and and you know cloud providers even though they have potentially the same concept let's say blob storage apis are completely different the way you know these systems are secure it's completely different the errors that you can get and and the retry you know mechanism is very different from one cloud to the other performance is also different we discovered that when we were starting to port our software and and and you know we had to completely rethink how to leverage blob storage in that cloud versus that cloud because just of performance too so we had you know for example to you know stripe data so all this work is work that's you know you don't need as an application because our vision really is that applications which are running in our data cloud can you know be abstracted of all this difference and and we provide all the services all the workload that this application need whether it's transactional access to data analytical access to data you know managing you know logs managing you know metrics all of these is abstracted too such that they are not you know tied to one you know particular service of one cloud and and distributing this application across you know many regions many cloud is very seamless so from that answer we know that snowflake takes care of everything but we really don't understand the performance implications in you know in that specific case but we feel pretty certain that the promises that snowflake makes around governance and security within their data sharing construct construct will be kept now another criterion that we've proposed for super cloud is a super pass layer to create a common developer experience and an enabler for ecosystem partners to monetize please play the clip let's listen we build it you know a custom build because because as you said you know what exists in one cloud might not exist in another cloud provider right so so we have to build you know on this all these this components that modern application mode and that application need and and and and that you know goes to machine learning as i say transactional uh analytical system and the entire thing so such that they can run in isolation basically and the objective is the developer experience will be identical across those clouds yes right the developers doesn't need to worry about cloud provider and actually our system we have we didn't talk about it but the marketplace that we have which allows actually to deliver we're getting there yeah okay now we're not going to go deep into ecosystem today we've talked about snowflakes strengths in this regard but snowflake they pretty much ticked all the boxes on our super cloud attributes and definition we asked benoit dejaville to confirm that this is all shipping and available today and he also gave us a glimpse of the future play the clip and we are still developing it you know the transactional you know unistore as we call it was announced in last summit so so they are still you know working properly but but but that's the vision right and and and that's important because we talk about the infrastructure right you mentioned a lot about storage and compute but it's not only that right when you think about application they need to use the transactional database they need to use an analytical system they need to use you know machine learning so you need to provide also all these services which are consistent across all the cloud providers so you can hear deja ville talking about expanding beyond taking advantage of the core infrastructure storage and networking et cetera and bringing intelligence to the data through machine learning and ai so of course there's more to come and there better be at this company's valuation despite the recent sharp pullback in a tightening fed environment okay so i know it's cliche but everyone's comparing snowflakes and data bricks databricks has been pretty vocal about its open source posture compared to snowflakes and it just so happens that we had aligotsy on at super cloud 22 as well he wasn't in studio he had to do remote because i guess he's presenting at an investor conference this week so we had to bring him in remotely now i didn't get to do this interview john furrier did but i listened to it and captured this clip about how data bricks sees super cloud and the importance of open source take a listen to goatzee yeah i mean let me start by saying we just we're big fans of open source we think that open source is a force in software that's going to continue for you know decades hundreds of years and it's going to slowly replace all proprietary code in its way we saw that you know it could do that with the most advanced technology windows you know proprietary operating system very complicated got replaced with linux so open source can pretty much do anything and what we're seeing with the data lake house is that slowly the open source community is building a replacement for the proprietary data warehouse you know data lake machine learning real-time stack in open source and we're excited to be part of it for us delta lake is a very important project that really helps you standardize how you lay out your data in the cloud and with it comes a really important protocol called delta sharing that enables you in an open way actually for the first time ever share large data sets between organizations but it uses an open protocol so the great thing about that is you don't need to be a database customer you don't even like databricks you just need to use this open source project and you can now securely share data sets between organizations across clouds and it actually does so really efficiently just one copy of the data so you don't have to copy it if you're within the same cloud so the implication of ellie gotzi's comments is that databricks with delta sharing as john implied is playing a long game now i don't know if enough about the databricks architecture to comment in detail i got to do more research there so i reached out to my two analyst friends tony bear and sanji mohan to see what they thought because they cover these companies pretty closely here's what tony bear said quote i've viewed the divergent lake house strategies of data bricks and snowflake in the context of their roots prior to delta lake databrick's prime focus was the compute not the storage layer and more specifically they were a compute engine not a database snowflake approached from the opposite end of the pool as they originally fit the mold of the classic database company rather than a specific compute engine per se the lake house pushes both companies outside of their original comfort zones data bricks to storage snowflake to compute engine so it makes perfect sense for databricks to embrace the open source narrative at the storage layer and for snowflake to continue its walled garden approach but in the long run their strategies are already overlapping databricks is not a 100 open source company its practitioner experience has always been proprietary and now so is its sql query engine likewise snowflake has had to open up with the support of iceberg for open data lake format the question really becomes how serious snowflake will be in making iceberg a first-class citizen in its environment that is not necessarily officially branding a lake house but effectively is and likewise can databricks deliver the service levels associated with walled gardens through a more brute force approach that relies heavily on the query engine at the end of the day those are the key requirements that will matter to data bricks and snowflake customers end quote that was some deep thought by by tony thank you for that sanjay mohan added the following quote open source is a slippery slope people buy mobile phones based on open source android but it's not fully open similarly databricks delta lake was not originally fully open source and even today its photon execution engine is not we are always going to live in a hybrid world snowflake and databricks will support whatever model works best for them and their customers the big question is do customers care as deeply about which vendor has a higher degree of openness as we technology people do i believe customers evaluation criteria is far more nuanced than just to decipher each vendor's open source claims end quote okay so i had to ask dodgeville about their so-called wall garden approach and what their strategy is with apache iceberg here's what he said iceberg is is very important so just to to give some context iceberg is an open you know table format right which was you know first you know developed by netflix and netflix you know put it open source in the apache community so we embrace that's that open source standard because because it's widely used by by many um many you know companies and also many companies have you know really invested a lot of effort in building you know big data hadoop solution or data like solution and they want to use snowflake and they couldn't really use snowflake because all their data were in open you know formats so we are embracing icebergs to help these companies move through the cloud but why we have been relentless with direct access to data direct access to data is a little bit of a problem for us and and the reason is when you direct access to data now you have direct access to storage now you have to understand for example the specificity of one cloud versus the other so as soon as you start to have direct access to data you lose your you know your cloud diagnostic layer you don't access data with api when you have direct access to data it's very hard to secure data because you need to grant access direct access to tools which are not you know protected and you see a lot of you know hacking of of data you know because of that so so that was not you know direct access to data is not serving well our customers and that's why we have been relented to do that because it's it's cr it's it's not cloud diagnostic it's it's you you have to code that you have to you you you need a lot of intelligence while apis access so we want open apis that's that's i guess the way we embrace you know openness is is by open api versus you know you access directly data here's my take snowflake is hedging its bets because enough people care about open source that they have to have some open data format options and it's good optics and you heard benoit deja ville talk about the risks of directly accessing the data and the complexities it brings now is that maybe a little fud against databricks maybe but same can be said for ollie's comments maybe flooding the proprietaryness of snowflake but as both analysts pointed out open is a spectrum hey i remember unix used to equal open systems okay let's end with some etr spending data and why not compare snowflake and data bricks spending profiles this is an xy graph with net score or spending momentum on the y-axis and pervasiveness or overlap in the data set on the x-axis this is data from the january survey when snowflake was holding above 80 percent net score off the charts databricks was also very strong in the upper 60s now let's fast forward to this next chart and show you the july etr survey data and you can see snowflake has come back down to earth now remember anything above 40 net score is highly elevated so both companies are doing well but snowflake is well off its highs and data bricks has come down somewhat as well databricks is inching to the right snowflake rocketed to the right post its ipo and as we know databricks wasn't able to get to ipo during the covet bubble ali gotzi is at the morgan stanley ceo conference this week they got plenty of cash to withstand a long-term recession i'm told and they've started the message that they're a billion dollars in annualized revenue i'm not sure exactly what that means i've seen some numbers on their gross margins i'm not sure what that means i've seen some numbers on their net retention revenue or net revenue retention again i'll reserve judgment until we see an s1 but it's clear both of these companies have momentum and they're out competing in the market well as always be the ultimate arbiter different philosophies perhaps is it like democrats and republicans well it could be but they're both going after a solving data problem both companies are trying to help customers get more value out of their data and both companies are highly valued so they have to perform for their investors to paraphrase ralph nader the similarities may be greater than the differences okay that's it for today thanks to the team from palo alto for this awesome super cloud studio build alex myerson and ken shiffman are on production in the palo alto studios today kristin martin and sheryl knight get the word out to our community rob hoff is our editor-in-chief over at siliconangle thanks to all please check out etr.ai for all the survey data remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcasts i publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante at siliconangle.com or dm me at devellante or comment on my linkedin posts and please as i say etr has got some of the best survey data in the business we track it every quarter and really excited to be partners with them this is dave vellante for the cube insights powered by etr thanks for watching and we'll see you next time on breaking analysis [Music] you

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AWS Partner Showcase S1E3 | Full Segment


 

>>Hey, everyone. Welcome to the AWS partner, showcase women in tech. I'm Lisa Martin from the cube. And today we're gonna be looking into the exciting evolution of women in the tech industry. I'm going to be joined by Danielle GShock, the ISP PSA director at AWS. And we have the privilege of speaking with some wicked smart women from Teradata NetApp. JFI a 10th revolution group, company and honeycomb.io. We're gonna look at some of the challenges and biases that women face in the tech industry, especially in leadership roles. We're also gonna be exploring how are these tech companies addressing diversity, equity and inclusion across their organizations? How can we get more young girls into stem earlier in their careers? So many questions. So let's go ahead and get started. This is the AWS partner showcase women in tech. Hey, everyone. Welcome to the AWS partner showcase. This is season one, episode three. And I'm your host, Lisa Martin. I've got two great guests here with me to talk about women in tech. Hillary Ashton joins us the chief product officer at Terry data. And Danielle Greshaw is back with us, the ISV PSA director at AWS ladies. It's great to have you on the program talking through such an important topic, Hillary, let's go ahead and start with you. Give us a little bit of an intro into you, your background, and a little bit about Teradata. >>Yeah, absolutely. So I'm Hillary Ashton. I head up the products organization. So that's our engineering product management office of the CTO team. Um, at Teradata I've been with Terra data for just about three years and really have spent the last several decades. If I can say that in the data and analytics space, um, I spent time, uh, really focused on the value of, of analytics at scale, and I'm super excited to be here at Teradata. I'm also a mom of two teenage boys. And so as we talk about women in tech, I think there's, um, uh, lots of different dimensions and angles of that. Um, at Teradata, we are partnered very deeply with AWS and happy to talk a little bit more about that, um, throughout this discussion as well. >>Excellent. A busy mom of two teen boys. My goodness. I don't know how you do it. Let's now look, Atter data's views of diversity, equity and inclusion. It's a, the, it's a topic that's important to everyone, but give us a snapshot into some of the initiatives that Terra data has there. >>Yeah, I have to say, I am super proud to be working at Teradata. We have gone through, uh, a series of transformations, but I think it starts with culture and we are deeply committed to diversity, equity and inclusion. It's really more than just a statement here. It's just how we live our lives. Um, and we use, uh, data to back that up. Um, in fact, we were named one of the world's most ethical companies for the 13th year in a row. Um, and all of our executive leadership team has taken an oath around D E and I that's available on LinkedIn as well. So, um, in fact, our leadership team reporting into the CEO is just about 50 50, um, men and women, which is the first time I've worked in a company where that has been the case. And I think as individuals, we can probably appreciate what a huge difference that makes in terms of not just being a representative, but truly being on a, on a diverse and equitable, uh, team. And I think it really, uh, improves the behaviors that we can bring, um, to our office. >>There's so much value in that. It's I impressive to see about a 50 50 at the leadership level. That's not something that we see very often. Tell me how you, Hillary, how did you get into tech? Were you an engineering person by computer science, or did you have more of a zigzaggy path to where you are now? >>I'm gonna pick door number two and say more zigzaggy. Um, I started off thinking, um, that I started off as a political science major or a government major. Um, and I was probably destined to go into, um, the law field, but actually took a summer course at Harvard. I did not go to Harvard, but I took a summer course there and learned a lot about multimedia and some programming. And that really set me on a trajectory of how, um, data and analytics can truly provide value and, and outcomes to our customers. Um, and I have been living that life ever since. Um, I graduated from college, so, um, I was very excited and privileged in my early career to, uh, work in a company where I found after my first year that I was managing, um, uh, kids, people who had graduated from Harvard business school and from MIT Sloan school. Um, and that was super crazy, cuz I did not go to either of those schools, but I sort of have always had a natural knack for how do you take technology and, and the really cool things that technology can do, but because I'm not a programmer by training, I'm really focused on the value that I'm able to help, um, organizations really extract value, um, from the technology that we can create, which I think is fantastic. >>I think there's so much value in having a zigzag path into tech. You bring Danielle, you and I have talked about this many times you bring such breadth and such a wide perspective. That really is such a value. Add to teams. Danielle, talk to us from AWS's perspective about what can be done to encourage more young women to get and under and underrepresented groups as well, to get into stem and stay. >>Yeah, and this is definitely a challenge as we're trying to grow our organization and kind of shift the numbers. And the reality is, especially with the more senior folks in our organization, unless you bring folks with a zigzag path, the likelihood is you won't be able to change the numbers that you have. Um, but for me, it's really been about, uh, looking at that, uh, the folks who are just graduating college, maybe in other roles where they are adjacent to technology and to try to spark their interest and show that yes, they can do it because oftentimes it's really about believing in themselves and, and realizing that we need folks with all sorts of different perspectives to kind of come in, to be able to help really, um, provide both products and services and solutions for all types of people inside of technology, which requires all sorts of perspectives. >>Yeah, the diverse perspectives. There's so much value and there's a lot of data that demonstrates how much value revenue impact organizations can make by having diversity, especially at the leadership level. Hillary, let's go back to you. We talked about your career path. You talked about some of the importance of the focus on de and I at Tarana, but what are, what do you think can be done to encourage, to sorry, to recruit more young women and under groups into tech, any, any carrot there that you think are really important that we need to be dangling more of? >>Yeah, absolutely. And I'll build on what Danielle just said. I think the, um, bringing in diverse understandings, um, of, of customer outcomes, I mean, I, the we've really moved from technology for technology's sake and I know AWS and entirety to have had a lot of conversations on how do we drive customer outcomes that are differentiated in the market and really being customer centric and technology is wonderful. You can do wonderful things with it. You can do not so wonderful things with it as well, but unless you're really focused on the outcomes and what customers are seeking, um, technology is not hugely valuable. And so I think bringing in people who understand, um, voice of customer who understand those outcomes, and those are not necessarily the, the, the folks who are PhD in mathematics or statistics, um, those can be people who understand a day in the life of a data scientist or a day in the life of a citizen data scientist. And so really working to bridge the high impact technology with the practical kind of usability, usefulness of data and analytics in our cases, I think is something that we need more of in tech and sort of demystifying tech and freeing technology so that everybody can use it and having a really wide range of people who understand not just the bits and bites and, and how to program, but also the value in outcomes that technology through data and analytics can drive. >>Yeah. You know, we often talk about the hard skills, but this, their soft skills are equally, if not more important that even just being curious, being willing to ask questions, being not afraid to be vulnerable, being able to show those sides of your personality. I think those are important for, for young women and underrepresented groups to understand that those are just as important as some of the harder technical skills that can be taught. >>That's right. >>What do you think about from a bias perspective, Hillary, what have you seen in the tech industry and how do you think we can leverage culture as you talked about to help dial down some of the biases that are going on? >>Yeah. I mean, I think first of all, and, and there's some interesting data out there that says that 90% of the population, which includes a lot of women have some inherent bias in their day, day behaviors when it comes to to women in particular. But I'm sure that that is true across all kinds of, of, um, diverse and underrepresented folks in, in the world. And so I think acknowledging that we have bias and actually really learning how, what that can look like, how that can show up. We might be sitting here and thinking, oh, of course I don't have any bias. And then you realize that, um, as you, as you learn more about, um, different types of bias, that actually you do need to kind of, um, account for that and change behaviors. And so I think learning is sort of a fundamental, um, uh, grounding for all of us to really know what bias looks like, know how it shows up in each of us. >>Um, if we're leaders know how it shows up in our teams and make sure that we are constantly getting better, we're, we're not gonna be perfect anytime soon. But I think being on a path to improvement to overcoming bias, um, is really, is really critical. And part of that is really starting the dialogue, having the conversations, holding ourselves and each other accountable, um, when things aren't going in, in a, in a Coptic way and being able to talk openly about that, that felt, um, like maybe there was some bias in that interaction and how do we, um, how do we make good on that? How do we change our, our behavior? Fundamentally of course, data and analytics can have some bias in it as well. And so I think as we look at the, the technology aspect of bias, um, looking at at ethical AI, I think is a, a really important, uh, additional area. And I'm sure we could spend another 20 minutes talking about that, but I, I would be remiss if I didn't talk more about sort of the bias, um, and the over the opportunity to overcome bias in data and analytics as well. >>Yeah. The opportunity to overcome it is definitely there you bring up a couple of really good points, Hillary. It, it starts with awareness. We need to be aware that there are inherent biases in data in thought. And also to your other point, hold people accountable ourselves, our teammates, that's critical to being able to, to dial that back down, Daniel, I wanna get your perspective on, on your view of women in leadership roles. Do you think that we have good representation or we still have work to do in there? >>I definitely think in both technical and product roles, we definitely have some work to do. And, you know, when I think about, um, our partnership with Teradata, part of the reason why it's so important is, you know, Teradata solution is really the brains of a lot of companies. Um, you know, the what, how, what they differentiate on how they figure out insights into their business. And it's, it's all about the product itself and the data and the same is true at AWS. And, you know, we really could do some work to have some more women in these technical roles, as well as in the product, shaping the products. Uh, just for all the reasons that we just kind of talked about over the last 10 minutes, um, in order to, you know, move bias out of our, um, out of our solutions and also to just build better products and have, uh, better, you know, outcomes for customers. So I think there's a bit of work to do still. >>I agree. There's definitely a bit of work to do, and it's all about delivering those better outcomes for customers at the end of the day, we need to figure out what the right ways are of doing that and working together in a community. Um, we've had obviously a lot had changed in the last couple of years, Hillary, what's your, what have you seen in terms of the impact that the pandemic has had on this status of women in tech? Has it been a pro is silver lining the opposite? What are you seeing? >>Yeah, I mean, certainly there's data out there that tells us factually that it has been, um, very difficult for women during COVID 19. Um, women have, uh, dropped out of the workforce for a wide range of, of reasons. Um, and, and that I think is going to set us back all of us, the, the Royal us or the Royal we back, um, years and years. Um, and, and it's very unfortunate because I think we we're at a time when we're making great progress and now to see COVID, um, setting us back in, in such a powerful way. I think there's work to be done to understand how do we bring people back into the workforce. Um, how do we do that? Understanding work life balance, better understanding virtual and remote, working better. I think in the technology sector, um, we've really embraced, um, hybrid virtual work and are, are empowering people to bring their whole selves to work. >>And I think if anything, these, these zoom calls have, um, both for the men and the women on my team. In fact, I would say much more. So for the men on my team, I'm seeing, I was seeing more kids in the background, more kind of split childcare duties, more ability to start talking about, um, other responsibilities that maybe they had, uh, especially in the early days of COVID where maybe daycares were shut down. And, um, you had, you know, maybe a parent was sick. And so we saw quite a lot of, um, people bringing their whole selves to the office, which I think was, was really wonderful. Um, uh, even our CEO saw some of that. And I think, um, that that really changes the dialogue, right? It changes it to maybe scheduling meetings at a time when, um, people can do it after daycare drop off. >>Um, and really allowing that both for men and for women makes it better for, for women overall. So I would like to think that this hybrid working, um, environment and that this, um, uh, whole view into somebody's life that COVID has really provided for probably for white collar workers, if I'm being honest for, um, people who are in a, at a better point of privilege, they don't necessarily have to go into the office every day. I would like to think that tech can lead the way in, um, you know, coming out of the, the old COVID. I don't know if we have a new COVID coming, but the old COVID and really leading the way for women and for people, um, to transform how we do work, um, leveraging data and analytics, but also, um, overcoming some of the, the disparities that exist for women in particular in the workforce. >>Yeah, I think there's, there's like we say, there's a lot of opportunity there and I like your point of hopefully tech can be that guiding light that shows us this can be done. We're all humans at the end of the day. And ultimately if we're able to have some sort of work life balance, everything benefits, our work or more productive, higher performing teams impacts customers, right? There's so much value that can be gleaned from, from that hybrid model and embracing for humans. We need to be able to, to work when we can, we've learned that you don't have to be, you know, in an office 24, 7 commuting, crazy hours flying all around the world. We can get a lot of things done in a ways that fit people's lives rather than taking command over it. Wanna get your advice, Hillary, if you were to talk to your younger self, what would be some of the key pieces of advice you would say? And Danielle and I have talked about this before, and sometimes we, we would both agree on like, ask more questions. Don't be afraid to raise your hand, but what advice would you give your younger self and that younger generation in terms of being inspired to get into tech >>Oh, inspired and being in tech? You know, I think looking at technology as, in some ways, I feel like we do a disservice to, um, inclusion when we talk about stem, cuz I think stem can be kind of daunting. It can be a little scary for people for younger people. When I, when I go and talk to folks at schools, I think stem is like, oh, all the super smart kids are over there. They're all like maybe they're all men. And so, um, it's, it's a little, uh, intimidating. Um, and stem is actually, you know, especially for, um, people joining the workforce today. It's actually how you've been living your life since you were born. I mean, you know, stem inside and out because you walk around with a phone and you know how to get your internet working and like that is technology right. >>Fundamentally. And so demystifying stem as something that is around how we, um, actually make our, our lives useful and, and, and how we can change outcomes. Um, through technology I think is maybe a different lens to put on it. So, and there's absolutely for, for hard sciences, there's absolutely a, a great place in the world for folks who wanna pursue that and men and women can do that. So I, I don't want to be, um, uh, setting the wrong expectations, but I, I think stem is, is very holistic in, um, in the change that's happening globally for us today across economies, across global warming, across all kinds of impactful issues. And so I think everybody who's interested in, in some of that world change can participate in stem. It just may be through a different, through a different lens than how we classically talk about stem. >>So I think there's great opportunity to demystify stem. I think also, um, what I would tell my younger self is choose your bosses wisely. And that sounds really funny. That sounds like inside out almost, but I think choose the person that you're gonna work for in your first five to seven years. And it might be more than one person, but be, be selective, maybe be a little less selective about the exact company or the exact title. I think picking somebody that, you know, we talk about mentors and we talk about sponsors and those are important. Um, but the person you're gonna spend in your early career, a lot of your day with a lot, who's gonna influence a lot of the outcomes for you. That is the person that you, I think want to be more selective about, um, because that person can set you up for success and give you opportunities and set you on course to be, um, a standout or that person can hold you back. >>And that person can put you in the corner and not invite you to the meetings and not give you those opportunities. And so we're in an economy today where you actually can, um, be a little bit picky about who you go and work for. And I would encourage my younger self. I actually, I just lucked out actually, but I think that, um, my first boss really set me, um, up for success, gave me a lot of feedback and coaching. Um, and some of it was really hard to hear, but it really set me up for, for, um, the, the path that I've been on ever since. So it, that would be my advice. >>I love that advice. I it's brilliant. I didn't think it choose your bosses wisely. Isn't something that we primarily think about. I think a lot of people think about the big name companies that they wanna go after and put on a resume, but you bring up a great point. And Danielle and I have talked about this with other guests about mentors and sponsors. I think that is brilliant advice and also more work to do to demystify stem. But luckily we have great family leaders like the two of you helping us to do that. Ladies, I wanna thank you so much for joining me on the program today and talking through what you're seeing in de and I, what your companies are doing and the opportunities that we have to move the needle. Appreciate your time. >>Thank you so much. Great to see you, Danielle. Thank you Lisa, to see you. >>My pleasure for my guests. I'm Lisa Martin. You're watching the AWS partner showcase season one, episode three. Hey everyone. Welcome to the AWS partner showcase. This is season one, episode three, with a focus on women in tech. I'm your host, Lisa Martin. I've got two guests here with me, Sue Peretti, the EVP of global AWS strategic alliances at Jefferson Frank, a 10th revolution group company, and Danielle brushoff. One of our cube alumni joins us ISV PSA director, ladies. It's great to have you on the program talking about a, a topic that is near and dear to my heart at women in tech. >>Thank you, Lisa. >>So let's go ahead and start with you. Give the audience an understanding of Jefferson Frank, what does the company do and about the partnership with AWS? >>Sure. Um, so let's just start, uh, Jefferson Frank is a 10th revolution group company. And if you look at it, it's really talent as a service. So Jefferson Frank provides talent solutions all over the world for AWS clients, partners and users, et cetera. And we have a sister company called revelent, which is a talent creation company within the AWS ecosystem. So we create talent and put it out in the ecosystem. Usually underrepresented groups over half of them are women. And then we also have, uh, a company called rubra, which is a delivery model around AWS technology. So all three companies fall under the 10th revolution group organization. >>Got it. Danielle, talk to me a little bit about from AWS's perspective and the focus on hiring more women in technology and about the partnership. >>Yes. I mean, this has definitely been a focus ever since I joined eight years ago, but also just especially in the last few years we've grown exponentially and our customer base has changed. You know, we wanna have, uh, an organization interacting with them that reflects our customers, right. And, uh, we know that we need to keep pace with that even with our growth. And so we've very much focused on early career talent, um, bringing more women and underrepresented minorities into the organization, sponsoring those folks, promoting them, uh, giving them paths to growth, to grow inside of the organization. I'm an example of that. Of course I benefit benefited from it, but also I try to bring that into my organization as well. And it's super important. >>Tell me a little bit about how you benefited from that, Danielle. >>Um, I just think that, um, you know, I I've been able to get, you know, a seat at the table. I think that, um, I feel as though I have folks supporting me, uh, very deeply and wanna see me succeed. And also they put me forth as, um, you know, a, represent a representative, uh, to bring more women into the organization as well. And I think, um, they give me a platform, uh, in order to do that, um, like this, um, but also many other, uh, spots as well. Um, and I'm happy to do it because I feel that, you know, if you always wanna feel that you're making a difference in your job, and that is definitely a place where I get that time and space in order to be that representative to, um, bring more, more women into benefiting from having careers in technology, which there's a lot of value there, >>A lot of value. Absolutely. So back over to you, what are some of the trends that you are seeing from a gender diversity perspective in tech? We know the, the numbers of women in technical positions, uh, right. There's so much data out there that shows when girls start dropping up, but what are some of the trends that you are seeing? >>So it's, that's a really interesting question. And, and Lisa, I had a whole bunch of data points that I wanted to share with you, but just two weeks ago, uh, I was in San Francisco with AWS at the, at the summit. And we were talking about this. We were talking about how we can collectively together attract more women, not only to, uh, AWS, not only to technology, but to the AWS ecosystem in particular. And it was fascinating because I was talking about, uh, the challenges that women have and how hard to believe, but about 5% of women who were in the ecosystem have left in the past few years, which was really, really, uh, something that shocked everyone when we, when we were talking about it, because all of the things that we've been asking for, for instance, uh, working from home, um, better pay, uh, more flexibility, uh, better maternity leave seems like those things are happening. >>So we're getting what we want, but people are leaving. And it seemed like the feedback that we got was that a lot of women still felt very underrepresented. The number one thing was that they, they couldn't be, you can't be what you can't see. So because they, we feel collectively women, uh, people who identify as women just don't see enough women in leadership, they don't see enough mentors. Um, I think I've had great mentors, but, but just not enough. I'm lucky enough to have a pres a president of our company, the president of our company, Zoe Morris is a woman and she does lead by example. So I'm very lucky for that. And Jefferson, Frank really quickly, we put out a hiring a salary and hiring guide a career and hiring guide every year and the data points. And that's about 65 pages long. No one else does it. Uh, it gives an abundance of information around, uh, everything about the AWS ecosystem that a hiring manager might need to know. But there is what, what I thought was really unbelievable was that only 7% of the people that responded to it were women. So my goal, uh, being that we have such a very big global platform is to get more women to respond to that survey so we can get as much information and take action. So >>Absolutely 7%. So a long way to go there. Danielle, talk to me about AWS's focus on women in tech. I was watching, um, Sue, I saw that you shared on LinkedIn, the Ted talk that the CEO and founder of girls and co did. And one of the things that she said was that there was a, a survey that HP did some years back that showed that, um, 60%, that, that men will apply for jobs if they only meet 60% of the list of requirements. Whereas with females, it's far, far less, we've all been in that imposter syndrome, um, conundrum before. But Danielle, talk to us about AWS, a specific focus here to get these numbers up. >>I think it speaks to what Susan was talking about, how, you know, I think we're approaching it top and bottom, right? We're looking out at what are the, who are the women who are currently in technical positions and how can we make AWS an attractive place for them to work? And that's all a lot of the changes that we've had around maternity leave and, and those types of things, but then also, um, more flexible working, uh, can, you know, uh, arrangements, but then also, um, early, how can we actually impact early, um, career women and actually women who are still in school. Um, and our training and certification team is doing amazing things to get, um, more girls exposed to AWS, to technology, um, and make it a less intimidating place and have them look at employees from AWS and say like, oh, I can see myself in those people. >>Um, and kind of actually growing the viable pool of candidates. I think, you know, we're, we're limited with the viable pool of candidates, um, when you're talking about mid to late career. Um, but how can we, you know, help retrain women who are coming back into the workplace after, you know, having a child and how can we help with military women who want to, uh, or underrepresented minorities who wanna move into AWS, we have a great military program, but then also just that early high school, uh, career, you know, getting them in, in that trajectory. >>Sue, is that something that Jefferson Frank is also able to help with is, you know, getting those younger girls before they start to feel there's something wrong with me. I don't get this. Talk to us about how Jefferson Frank can help really drive up that in those younger girls. >>Uh, let me tell you one other thing to refer back to that summit that we did, uh, we had breakout sessions and that was one of the topics. What can cuz that's the goal, right? To make sure that, that there are ways to attract them. That's the goal? So some of the things that we talked about was mentoring programs, uh, from a very young age, some people said high school, but then we said even earlier, goes back to you. Can't be what you can't see. So, uh, getting mentoring programs, uh, established, uh, we also talked about some of the great ideas was being careful of how we speak to women using the right language to attract them. And some, there was a teachable moment for, for me there actually, it was really wonderful because, um, an African American woman said to me, Sue and I, I was talking about how you can't be what you can't see. >>And what she said was Sue, it's really different. Um, for me as an African American woman, uh, or she identified, uh, as nonbinary, but she was relating to African American women. She said, your white woman, your journey was very different than my journey. And I thought, this is how we're going to learn. I wasn't offended by her calling me out at all. It was a teachable moment. And I thought I understood that, but those are the things that we need to educate people on those, those moments where we think we're, we're saying and doing the right thing, but we really need to get that bias out there. So here at Jefferson, Frank, we're, we're trying really hard to get that careers and hiring guide out there. It's on our website to get more women, uh, to talk to it, but to make suggestions in partnership with AWS around how we can do this mentoring, we have a mentor me program. We go around the country and do things like this. We, we try to get the education out there in partnership with AWS. Uh, we have a, a women's group, a women's leadership group, uh, so much that, that we do, and we try to do it in partnership with AWS. >>Danielle, can you comment on the impact that AWS has made so far, um, regarding some of the trends and, and gender diversity that Sue was talking about? What's the impact that's been made so far with this partnership? >>Well, I mean, I think just being able to get more of the data and have awareness of leaders, uh, on how <laugh>, you know, it used to be a, a couple years back, I would feel like sometimes the, um, uh, solving to bring more women into the organization was kind of something that folks thought, oh, this is Danielle is gonna solve this. You know? And I think a lot of folks now realize, oh, this is something that we all need to solve for. And a lot of my colleagues who maybe a couple years ago, didn't have any awareness or didn't even have the tools to do what they needed to do in order to improve the statistics on their, or in their organizations. Now actually have those tools and are able to kind of work with, um, work with companies like Susan's work with Jefferson Frank in order to actually get the data and actually make good decisions and feel as though, you know, they, they often, these are not lived experiences for these folks, so they don't know what they don't know. And by providing data and providing awareness and providing tooling and then setting goals, I think all of those things have really turned, uh, things around in a very positive way. >>And so you bring up a great point about from a diversity perspective, what is Jefferson Frank doing to, to get those data points up, to get more women of, of all well, really underrepresented minorities to, to be able to provide that feedback so that you can, can have the data and gleamy insights from it to help companies like AWS on their strategic objectives. >>Right? So as I, when I go back to that higher that, uh, careers in hiring guide, that is my focus today, really because the more data that we have, I mean, the, and the data takes, uh, you know, we need people to participate in order to, to accurately, uh, get a hold of that data. So that's why we're asking, uh, we're taking the initiative to really expand our focus. We are a global organization with a very, very massive database all over the world, but if people don't take action, then we can't get the right. The, the, the data will not be as accurate as we'd like it to be. Therefore take better action. So what we're doing is we're asking people all over the, all over the world to participate on our website, Jefferson frank.com, the se the high, uh, in the survey. So we can learn as much as we can. >>7% is such a, you know, Danielle and I we're, we've got to partner on this just to sort of get that message out there, get more data so we can execute, uh, some of the other things that we're doing. We're, we're partnering in. As I mentioned, more of these events, uh, we're, we're doing around the summits, we're gonna be having more ed and I events and collecting more information from women. Um, like I said, internally, we do practice what we preach and we have our own programs that are, that are out there that are within our own company where the women who are talking to candidates and clients every single day are trying to get that message out there. So if I'm speaking to a client or one of our internal people are speaking to a client or a candidate, they're telling them, listen, you know, we really are trying to get these numbers up. >>We wanna attract as many people as we can. Would you mind going to this, uh, hiring guide and offering your own information? So we've gotta get that 7% up. We've gotta keep talking. We've gotta keep, uh, getting programs out there. One other thing I wanted to Danielle's point, she mentioned, uh, women in leadership, the number that we gathered was only 9% of women in leadership within the AWS ecosystem. We've gotta get that number up, uh, as well because, um, you know, I know for me, when I see people like Danielle or, or her peers, it inspires me. And I feel like, you know, I just wanna give back, make sure I send the elevator back to the first floor and bring more women in to this amazing ecosystem. >>Absolutely. That's not that metaphor I do too, but we, but to your point to get that those numbers up, not just at AWS, but everywhere else we need, it's a help me help use situation. So ladies underrepresented minorities, if you're watching go to the Jefferson Frank website, take the survey, help provide the data so that the woman here that are doing this amazing work, have it to help make decisions and have more of females and leadership roles or underrepresented minorities. So we can be what we can see. Ladies, thank you so much for joining me today and sharing what you guys are doing together to partner on this important. Cause >>Thank you for having me, Leah, Lisa, >>Thank you. My pleasure for my guests. I'm Lisa Martin. You're watching the cubes coverage of the AWS partner showcase. Thanks for your time. Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host, Lisa Martin. We've got two female rock stars here with me next. Stephanie Curry joins us the worldwide head of sales and go to market strategy for AWS at NetApp and Danielle GShock is back one of our QM ISV PSA director at AWS. Looking forward to a great conversation, ladies, about a great topic, Stephanie, let's go ahead and start with you. Give us an overview of your story, how you got into tech and what inspired you. >>Thanks so much, Lisa and Danielle. It's great to be on this show with you. Um, thank you for that. Uh, my name's Stephanie cur, as Lisa mentioned, I'm the worldwide head of sales for, uh, AWS at NetApp and run a global team of sales people that sell all things AWS, um, going back 25 years now, uh, when I first started my career in tech, it was kind of by accident. Um, I come from a different background. I have a business background and a technical background from school, um, but had been in a different career and I had an opportunity to try something new. Um, I had an ally really that reached out to me and said, Hey, you'd be great for this role. And I thought, I'd take a chance. I was curious. Um, and, uh, it, it turned out to be a 25 year career, um, that I'm really, really excited about and, and, um, really thankful for that person, for introducing me to the, to the industry >>25 years in counting. I'm sure Danielle, we've talked about your background before. So what I wanna focus on with you is the importance of diversity for high performance. I know what a machine AWS is, and Stephanie'll come back to you with the same question, but talk about that, Danielle, from your perspective, that importance, um, for diversity to drive the performance. >>Yeah. Yeah. I truly believe that, you know, in order to have high performing teams, that you have to have people from all different types of backgrounds and experiences. And we do find that oftentimes being, you know, field facing, if we're not reflecting our customers and connecting with them deeply, um, on, on the levels that they're at, we, we end up missing them. And so for us, it's very important to bring people of lots of different technical backgrounds experiences. And of course, both men, women, and underrepresented minorities and put that forth to our customers, um, in order to make that connection and to end up with better outcomes. So >>Definitely it's all about outcomes, Stephanie, your perspective and NetApp's perspective on diversity for creating highly performant teams and organizations. >>I really aligned with Danielle on the comment she made. And in addition to that, you know, just from building teams in my, um, career know, we've had three times as many women on my team since we started a year ago and our results are really showing in that as well. Um, we find the teams are stronger, they're more collaborative and to Danielle's point really reflective, not only our partners, but our customers themselves. So this really creates connections, which are really, really important to scale our businesses and, and really, uh, meet the customer where they're at as well. So huge proponent of that ourselves, and really finding that we have to be intentional in our hiring and intentional in how we attract diversity to our teams. >>So Stephanie let's stay with you. So a three X increase in women on the team in a year, especially the kind of last year that we've had is really incredible. I, I like your, I, your thoughts on there needs to be a, there needs to be focus and, and thought in how teams are hired. Let's talk about attracting and retaining those women now, especially in sales roles, we all know the number, the percentages of women in technical roles, but what are some of the things that, that you do Stephanie, that NetApp does to attract and retain women in those sales roles? >>The, the attracting part's really interesting. And we find that, you know, you, you read the stats and I'd say in my experience, they're also true in the fact that, um, a lot of women would look at a job description and say, I can't do a hundred percent of that, that, so I'm not even going to apply with the women that we've attracted to our team. We've actually intentionally reached out and targeted those people in a good way, um, to say, Hey, we think you've got what it takes. Some of the feedback I've got from those women are, gosh, I didn't think I could ever get this role. I didn't think I had the skills to do that. And they've been hired and they are doing a phenomenal job. In addition to that, I think a lot of the feedback I've got from these hires are, Hey, it's an aggressive sales is aggressive. Sales is competitive. It's not an environment that I think I can be successful in. And what we're showing them is bring those softer skills around collaboration, around connection, around building teams. And they do, they do bring a lot of that to the team. Then they see others like them there and they know they can be successful cuz they see others like them on the team, >>The whole concept of we can't be what we can't see, but we can be what we can't see is so important. You said a couple things, Stephanie, that really stuck with me. And one of them was an interview on the Cub I was doing, I think a couple weeks ago, um, about women in tech. And the stat that we talked about was that women will apply will not apply for a job unless they meet 100% of the skills and the requirements that it's listed, but men will, if they only meet 60. And I, that just shocked me that I thought, you know, I, I can understand that imposter syndrome is real. It's a huge challenge, but the softer skills, as you mentioned, especially in the last two years, plus the ability to communicate, the ability to collaborate are incredibly important to, to drive that performance of any team of any business. >>Absolutely. >>Danielle, talk to me about your perspective and AWS as well for attracting and retaining talent. And, and, and particularly in some of those challenging roles like sales that as Stephanie said, can be known as aggressive. >>Yeah, for sure. I mean, my team is focused on the technical aspect of the field and we definitely have an uphill battle for sure. Um, two things we are focused on first and foremost is looking at early career women and that how we, how can we bring them into this role, whether in they're in support functions, uh, cl like answering the phone for support calls, et cetera, and how, how can we bring them into this organization, which is a bit more strategic, more proactive. Um, and then the other thing that as far as retention goes, you know, sometimes there will be women who they're on a team and there are no other women on that team. And, and for me, it's about building community inside of AWS and being part of, you know, we have women on solution architecture organizations. We have, uh, you know, I just personally connect people as well and to like, oh, you should meet this person. Oh, you should talk to that person. Because again, sometimes they can't see someone on their team like them and they just need to feel anchored, especially as we've all been, you know, kind of stuck at home, um, during the pandemic, just being able to make those connections with women like them has been super important and just being a, a long tenured Amazonian. Um, that's definitely one thing I'm able to, to bring to the table as well. >>That's so important and impactful and spreads across organizations in a good way. Daniel let's stick with you. Let's talk about some of the allies that you've had sponsors, mentors that have really made a difference. And I said that in past tense, but I also mean in present tense, who are some of those folks now that really inspire you? >>Yeah. I mean, I definitely would say that one of my mentors and someone who, uh, ha has been a sponsor of my career has, uh, Matt YK, who is one of our control tower GMs. He has really sponsored my career and definitely been a supporter of mine and pushed me in positive ways, which has been super helpful. And then other of my business partners, you know, Sabina Joseph, who's a cube alum as well. She definitely has been, was a fabulous partner to work with. Um, and you know, between the two of us for a period of time, we definitely felt like we could, you know, conquer the world. It's very great to go in with a, with another strong woman, um, you know, and, and get things done, um, inside of an organization like AWS. >>Absolutely. And S I've, I've agreed here several times. So Stephanie, same question for you. You talked a little bit about your kind of, one of your, uh, original early allies in the tech industry, but talk to me about allies sponsors, mentors who have, and continue to make a difference in your life. >>Yeah. And, you know, I think it's a great differentiation as well, right? Because I think that mentors teach us sponsors show us the way and allies make room for us at the table. And that is really, really key difference. I think also as women leaders, we need to make room for others at the table too, and not forget those softer skills that we bring to the table. Some of the things that Danielle mentioned as well about making those connections for others, right. And making room for them at the table. Um, some of my allies, a lot of them are men. Brian ABI was my first mentor. Uh, he actually is in the distribution, was in distribution, uh, with advent tech data no longer there. Um, Corey Hutchinson, who's now at Hashi Corp. He's also another ally of mine and remains an ally of mine, even though we're not at the same company any longer. Um, so a lot of these people transcend careers and transcend, um, um, different positions that I've held as well and make room for us. And I think that's just really critical when we're looking for allies and when allies are looking for us, >>I love how you described allies, mentors and sponsors Stephanie. And the difference. I didn't understand the difference between a mentor and a sponsor until a couple of years ago. Do you talk with some of those younger females on your team so that when they come into the organization and maybe they're fresh outta college, or maybe they've transitioned into tech so that they can also learn from you and understand the importance and the difference between the allies and the sponsors and the mentors? >>Absolutely. And I think that's really interesting because I do take, uh, an extra, uh, approach an extra time to really reach out to the women that have joined the team. One. I wanna make sure they stay right. I don't want them feeling, Hey, I'm alone here and I need to, I need to go do something else. Um, and they are located around the world, on my team. They're also different age groups, so early in career, as well as more senior people and really reaching out, making sure they know that I'm there. But also as Danielle had mentioned, connecting them to other people in the community that they can reach out to for those same opportunities and making room for them >>Make room at the table. It's so important. And it can, you never know what a massive difference and impact you can make on someone's life. And I, and I bet there's probably a lot of mentors and sponsors and allies of mine that would be surprised to know, uh, the massive influence they've had Daniel back over. Let's talk about some of the techniques that you employ, that AWS employees to make the work environment, a great place for women to really thrive and, and be retained as Stephanie was saying. Of course that's so important. >>Yeah. I mean, definitely I think that the community building, as well as we have a bit more programmatic mentorship, um, we're trying to get to the point of having a more programmatic sponsorship as well. Um, but I think just making sure that, um, you know, both everything from, uh, recruit to onboard to ever boarding that, uh, they they're the women who come into the organization, whether it's they're coming in on the software engineering side or the field side or the sales side that they feel as that they have someone, uh, working with them to help them drive their career. Those are the key things that were, I think from an organizational perspective are happening across the board. Um, for me personally, when I run my organization, I'm really trying to make sure that people feel that they can come to me at any time open door policy, make sure that they're surfacing any times in which they are feeling excluded or anything like that, any challenges, whether it be with a customer, a partner or with a colleague. Um, and then also of course, just making sure that I'm being a good sponsor, uh, to, to people on my team. Um, that is key. You can talk about it, but you have to start with yourself as well. >>That's a great point. You you've got to, to start with yourself and really reflect on that. Mm-hmm <affirmative> and look, am I, am I embodying what it is that I need? And not that I know they need that focused, thoughtful intention on that is so importants, let's talk about some of the techniques that you use that NetApp uses to make the work environment a great place for those women are marginalized, um, communities to really thrive. >>Yeah. And I appreciate it and much like Danielle, uh, and much like AWS, we have some of those more structured programs, right around sponsorship and around mentorship. Um, probably some growth there, opportunities for allies, because I think that's more of a newer concept in really an informal structure around the allies, but something that we're growing into at NetApp, um, on my team personally, I think, um, leading by example's really key. And unfortunately, a lot of the, um, life stuffs still lands on the women, whether we like it or not. Uh, I have a very, uh, active husband in our household, but I still carry when it push comes to shove it's on me. Um, and I wanna make sure that my team knows it's okay to take some time and do the things you need to do with your family. Um, I'm I show up as myself authentically and I encourage them to do the same. >>So it's okay to say, Hey, I need to take a personal day. I need to focus on some stuff that's happening in my personal life this week now, obviously to make sure your job's covered, but just allowing some of that softer vulnerability to come into the team as well, so that others, um, men and women can feel they can do the same thing. And that it's okay to say, I need to balance my life and I need to do some other things alongside. Um, so it's the formal programs, making sure people have awareness on them. Um, I think it's also softly calling people out on biases and saying, Hey, I'm not sure if you know, this landed that way, but I just wanted to make you aware. And usually the feedback is, oh my gosh, I didn't know. And could you coach me on something that I could do better next time? So all of this is driven through our NetApp formal programs, but then it's also how you manifest it on the teams that we're leading. >>Absolutely. And sometimes having that mirror to reflect into can be really eye-opening and, and allow you to, to see things in a completely different light, which is great. Um, you both talked about, um, kind of being what you, uh, can see, and, and I know both companies are upset customer obsessed in a good way. Talk to me a little bit, Danielle, go back over to you about the AWS NetApp partnership. Um, some of that maybe alignment on, on performance on obviously you guys are very well aligned, uh, in terms of that, but also it sounds like you're quite aligned on diversity and inclusion. >>Well, we definitely do. We have the best partnerships with companies in which we have these value alignments. So I think that is a positive thing, of course, but just from a, from a partnership perspective, you know, from my five now plus years of being a part of the APN, this is, you know, one of the most significant years with our launch of FSX for NetApp. Um, with that, uh, key key service, which we're making available natively on AWS. I, I can't think of a better Testament to the, to the, um, partnership than that. And that's doing incredibly well and it really resonates with our customers. And of course it started with customers and their need for NetApp. Uh, so, you know, that is a reflection, I think, of the success that we're having together. >>And Stephanie talk to, uh, about the partnership from your perspective, NetApp, AWS, what you guys are doing together, cultural alignment, but also your alignment on really bringing diversity into drive performance. >>Yeah, I think it's a, a great question. And I have to say it's just been a phenomenal year. Our relationship has, uh, started before our first party service with FSX N but definitely just, um, uh, the trajectory, um, between the two companies since the announcement about nine months ago has just taken off to a, a new level. Um, we feel like an extended part of the family. We worked together seamlessly. A lot of the people in my team often say we feel like Amazonians. Um, and we're really part of this transformation at NetApp from being that storage hardware company into being an ISV and a cloud company. And we could not do this without the partnership with AWS and without the, uh, first party service of Fs XM that we've recently released. Um, I think that those joint values that Danielle referred to are critical to our success, um, starting with customer obsession and always making sure that we are doing the right thing for the customer. >>We coach our team teams all the time on if you are doing the right thing for the customers, you cannot do anything wrong. Just always put the customer at the, in the center of your decisions. And I think that there is, um, a lot of best practice sharing and collaboration as we go through this change. And I think a lot of it is led by the diverse backgrounds that are on the team, um, female, male, um, race and so forth, and just to really, uh, have different perspectives and different experiences about how we approach this change. Um, so we definitely feel like a part of the family. Uh, we are absolutely loving, uh, working with the AWS team and our team knows that we are the right place, the right time with the right people. >>I love that last question for each of you. And I wanna stick with you Stephanie advice to your younger self, think back five years. What advice would you seen what you've accomplished and maybe the thet route that you've taken along the way, what would you advise your youngest Stephanie self. >>Uh, I would say keep being curious, right? Keep being curious, keep asking questions. And sometimes when you get a no, it's not a bad thing, it just means not right now and find out why and, and try to get feedback as to why maybe that wasn't the right opportunity for you. But, you know, just go for what you want. Continue to be curious, continue to ask questions and find a support network of people around you that wanna help you because they are there and they, they wanna see you be successful too. So never be shy about that stuff. >><laugh> absolutely. And I always say failure does not have to be an, a bad F word. A no can be the beginning of something. Amazing. Danielle, same question for you. Thinking back to when you first started in your career, what advice would you give your younger self? >>Yeah, I think the advice I'd give my younger self would be, don't be afraid to put yourself out there. Um, it's certainly, you know, coming from an engineering background, maybe you wanna stay behind the scenes, not, not do a presentation, not do a public speaking event, those types of things, but back to what the community really needs, this thing. Um, you know, I genuinely now, uh, took me a while to realize it, but I realized I needed to put myself out there in order to, um, you know, allow younger women to see what they could be. So that would be the advice I would give. Don't be afraid to put yourself out there. >>Absolutely. That advice that you both gave are, is so fantastic, so important and so applicable to everybody. Um, don't be afraid to put yourself out there, ask questions. Don't be afraid of a, no, that it's all gonna happen at some point or many points along the way. That can also be good. So thank you ladies. You inspired me. I appreciate you sharing what AWS and NetApp are doing together to strengthen diversity, to strengthen performance and the advice that you both shared for your younger selves was brilliant. Thank you. >>Thank you. >>Thank you >>For my guests. I'm Lisa Martin. You're watching the AWS partner showcase. See you next time. Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host, Lisa Martin. I've got two female rock stars joining me. Next Vero Reynolds is here engineering manager, telemetry at honeycomb, and one of our cube alumni, Danielle Ock ISV PSA director at AWS. Join us as well. Ladies. It's great to have you talking about a very important topic today. >>Thanks for having us. >>Yeah, thanks for having me. Appreciate it. >>Of course, Vera, let's go ahead and start with you. Tell me about your background and tech. You're coming up on your 10th anniversary. Happy anniversary. >>Thank you. That's right. I can't believe it's been 10 years. Um, but yeah, I started in tech in 2012. Um, I was an engineer for most of that time. Uh, and just recently as a March, switched to engineering management here at honeycomb and, um, you know, throughout my career, I was very much interested in all the things, right. And it was a big FOMO as far as trying a few different, um, companies and products. And I've done things from web development to mobile to platforms. Um, it would be apt to call me a generalist. Um, and in the more recent years I was sort of gravitating more towards developer tool space. And for me that, uh, came in the form of cloud Foundry circle CI and now honeycomb. Um, I actually had my eye on honeycomb for a while before joining, I came across a blog post by charity majors. >>Who's one of our founders and she was actually talking about management and how to pursue that and whether or not it's right, uh, for your career. And so I was like, who is this person? I really like her, uh, found the company. They were pretty small at the time. So I was sort of keeping my eye on them. And then when the time came around for me to look again, I did a little bit more digging, uh, found a lot of talks about the product. And on the one hand they really spoke to me as the solution. They talked about developers owning their coding production and answering questions about what is happening, what are your users seeing? And I felt that pain, I got what they were trying to do. And also on the other hand, every talk I saw at the time was from, uh, an amazing woman <laugh>, which I haven't seen before. Uh, so I came across charity majors again, Christine Y our other founder, and then Liz Jones, who's our principal developer advocate. And that really sealed the deal for me as far as wanting to work here. >>Yeah. Honeycomb is interesting. This is a female founded company. You're two leaders. You mentioned that you like the technology, but you were also attracted because you saw females in the leadership position. Talk to me a little bit about what that's like working for a female led organization at honeycomb. >>Yeah. You know, historically, um, we have tried not to over index on that because there was this, uh, maybe fear awareness of, um, it taking away from our legitimacy as an engineering organization, from our success as a company. Um, but I'm seeing that, uh, rhetoric shift recently because we believe that with great responsibility, uh, with great power comes great responsibility, and we're trying to be more intentional as far as using that attribute of our company. Um, so I would say that for me, it was, um, a choice between a few offers, right. And that was a selling point for sure, because again, I've never experienced it and I've really seen how much they walk that walk. Um, even me being here and me moving into management, I think were both, um, ways in which they really put a lot of trust and support in me. And so, um, I it's been a great ride. >>Excellent. Sounds like it. Before we bring Danielle in to talk about the partnership. I do wanna have you there talk to the audience a little bit about honeycomb, what technology it's delivering and what are its differentiators. >>Yeah, absolutely. Um, so honeycomb is an observability tool, uh, that enables engineers to answer questions about the code that runs in production. And, um, we work with a number of various customers. Some of them are Vanguards, slack. Hello, fresh, just to name a couple, if you're not familiar with observability tooling, it's akin to traditional application performance monitoring, but we believe that observability is succeeding APM because, uh, APM tools were built at the time of monoliths and they just weren't designed to help us answer questions about complex distributed systems that we work with today, where things can go wrong anywhere in that chain. And you can't predict what you're gonna need to ask ahead of time. So some of the ways that we are different is our ability to store and query really rich data, which we believe is the key to understanding those complex systems. >>What I mean by rich data is, um, something that has a lot of attributes. So for example, when an error happens, knowing who it happened to, which user ID, which, um, I don't know, region, they were in, um, what, what, what they were doing at the time and what was happening at the rest of your system. And our ingest engine is really fast. You can do it in as little as three seconds and we call data like this. I said, kind of rich data, contextual data. We refer it as having high ality and high dimensionality, which are big words. But at the end of the day, what that means is we can store and we can query the data. We can do it really fast. And to give you an example of how that looks for our customers, let's say you have a developer team who are using comb to understand and observe their system. >>And they get a report that a user is experiencing a slowdown or something's wrong. They can go into comb and figure out that this only happens to users who are using a particular language pack with their app. And they operated their app last week, that it only happens when they are trying to upload a file. And so it's this level of granularity and being able to zoom in and out, um, under your data that allows you to understand what's happening, especially when you have an incident going on, right. Or your really important high profile customer is telling you that something's wrong. And we can do that. Even if everything else in your other tools looks fine, right? All of your dashboards are okay. You're not actually getting paged on it, but your customers are telling you that something's wrong. Uh, and we believe that's where we shine in helping you there. >>Excellent. It sounds like that's where you really shine that real time visibility is so critical these days. Danielle, Danielle, wanna bring you into the conversation. Talk to us a little bit about the honeycomb partnership from the AWS lens. >>Yeah. So excuse me, observability is obviously a very important, uh, segment in the cloud space, very important to AWS, um, because a lot of all of our customers, uh, as they build their systems distributed, they need to be able to see where, where things are happening in the complex systems that they're building. And so honeycomb is a, is an advanced technology partner. Um, they've been working with us for quite some time and they have a, uh, their solution is listed on the marketplace. Um, definitely something that we see a lot of demand with our customers and they have many integrations, uh, which, you know, we've seen is key to success. Um, being able to work seamlessly with the rest of the services inside of the AWS platform. And I know that they've done some, some great things with people who are trying to develop games on top of AWS, uh, things in that area as well. And so, uh, very important partner in the observa observability market that we have >>Back to you, let's kind of unpack the partnership, the significance that honeycomb ha is getting from being partners with an organization as potent and pivotal as AWS. >>Yeah, absolutely. Um, I know this predates me to some extent, but I know for a long time, AWS and honeycomb has really pushed the envelope together. And, um, I think it's a beneficial relationship for both ends. There's kind of two ways of looking at it. On the one side, there is our own infrastructure. So honeycomb runs on AWS and actually one of our critical workloads that supports that fast query engine that I mentioned uses Lambda. And it does so in a pretty Orthodox way. So we've had a longstanding conversation with the AWS team as far as drawing outside those lines and kind of figuring out how to use this technology in a way that works for us and hopefully will work for other customers of theirs as well. Um, that also allows us to ask for early access for certain features when they become available. >>And then that way we can be sort of the Guinea pigs and try things out, um, in a way that migrates our system and optimizes our own performance, but also allows again, other customers of AWS to follow in that path. And then the other side of that partnership is really supporting our customers who are both honeycomb users and AWS users, because it's, as you imagine, quite a big overlap, and there are certain ways in which we can allow our customers to more easily get their data from AWS to honeycomb. So for example, last year we built a tool, um, based on the new Lambda extension capability that allowed our users who run their applications in Lambdas to get that telemetry data out of their applications and into honeycomb. And it man was win, win. >>Excellent. So I'm hearing a lot of synergies from a technology perspective, you're sticking with you, and then Danielle will bring you in, let's talk about how honeycomb supports D and I across its organization. And how is that synergistic with AWS's approach? Yeah, >>Yeah, absolutely. So I sort of alluded to that hesitancy to over index on the women led aspect of ourselves. Um, but again, a lot of things are shifting, we're growing a lot. And so we are recognizing that we need to be more intentional with our DEI initiatives, and we also notice that we can do better and we should do better. And to that, and we're doing a few things differently, um, that are pretty recent initiatives. We are partnering with organizations that help us target specific communities that are underrepresented in tech. Um, some examples would be after tech hu Latinas in tech among, um, a number of others. And another initiative is DEI head start. That's something that is an internal, um, practice that we started that includes reaching out to underrepresented applicants before any new job for honeycomb becomes live. So before we posted to LinkedIn, before it's even live on our job speech, and the idea there is to kind of balance our pipeline of applicants, which the hope is will lead to more diverse hires in the long term. >>That's a great focus there. Danielle, I know we've talked about this before, but for the audience, in terms of the context of the honeycomb partnership, the focus at AWS for D E and I is really significant, unpack that a little bit for us. >>Well, let me just bring it back to just how we think about it, um, with the companies that we work with, but also in, in terms of, you know, what we want to be able to do, excuse me, it's very important for us to, you know, build products that reflect, uh, the customers that we have. And I think, you know, working with, uh, a company like honeycomb that is looking to differentiate in a space, um, by, by bringing in, you know, the experiences of many different types of people I genuinely believe. And I'm sure Vera also believes that by having those diverse perspectives, that we're able to then build better products for our customers. Um, and you know, it's one of, one of our leadership principles, uh, is, is rooted in this. I write a lot, it asks for us to seek out diverse perspectives. Uh, and you can't really do that if everybody kind of looks the same and thinks the same and has the same background. So I think that is where our de and I, um, you know, I thought process is rooted and, you know, companies like honeycomb that give customers choice and differentiate and help them, um, to do what they need to do in their unique, um, environments is super important. So >>The, the importance of thought diversity cannot be underscored enough. It's something that is, can be pivotal to organizations. And it's very nice to hear that that's so fundamental to both companies, Barry, I wanna go back to you for a second. You, I think you mentioned this, the DEI head start program, that's an internal program at honeycomb. Can you shed a little bit of light on that? >>Yeah, that's right. And I actually am in the process of hiring a first engineer for my team. So I'm learning a lot of these things firsthand, um, and how it works is we try to make sure to pre-load our pipeline of applicants for any new job opening we have with diverse candidates to the best of our abilities, and that can involve partnering with the organizations that I mentioned or reaching out to our internal network, um, and make sure that we give those applicants a head start, so to speak. >>Excellent. I like that. Danielle, before we close, I wanna get a little bit of, of your background. We've got various background in tag, she's celebrating her 10th anniversary. Give me a, a short kind of description of the journey that you've navigated through being a female in technology. >>Yeah, thanks so much. I really appreciate, uh, being able to share this. So I started as a software engineer, uh, back actually in the late nineties, uh, during the, the first.com bubble and, uh, have, have spent quite a long time actually as an individual contributor, um, probably working in software engineering teams up through 2014 at a minimum until I joined AWS, uh, as a customer facing solutions architect. Um, I do think spending a lot of time, hands on definitely helped me with some of the imposter syndrome, um, issues that folks suffer from not to say I don't at all, but it, it certainly helped with that. And I've been leading teams at AWS since 2015. Um, so it's really been a great ride. Um, and like I said, I'm very happy to see all of our engineering teams change, uh, as far as their composition. And I'm, I'm grateful to be part of it. >>It's pretty great to be able to witness that composition change for the better last question for each of you. And we're almost out of time and Danielle, I'm gonna stick with you. What's your advice, your recommendations for women who either are thinking about getting into tech or those who may be in tech, maybe they're in individual positions and they're not sure if they should apply for that senior leadership position. What do you advise them to do? >>I mean, definitely for the individual contributors, tech tech is a great career, uh, direction, um, and you will always be able to find women like you, you have to maybe just work a little bit harder, uh, to join, have community, uh, in that. But then as a leader, um, representation is very important and we can bring more women into tech by having more leaders. So that's my, you just have to take the lead, >>Take the lead, love that there. Same question for you. What's your advice and recommendations for those maybe future female leaders in tech? >>Yeah, absolutely. Um, Danielle mentioned imposter syndrome and I think we all struggle with it from time to time, no matter how many years it's been. And I think for me, for me, the advice would be if you're starting out, don't be afraid to ask, uh, questions and don't be afraid to kind of show a little bit of ignorance because we've all been there. And I think it's on all of us to remember what it's like to not know how things work. And on the flip side of that, if you are a more senior IC or, uh, in a leadership role, also being able to model just saying, I don't know how this works and going and figuring out answers together because that was a really powerful shift for me early in my career is just to feel like I can say that I don't know something. >>I totally agree. I've been in that same situation where just ask the question because you I'm guaranteed, there's a million outta people in the room that probably has the, have the same question and because of imposter syndrome, don't wanna admit, I don't understand that. Can we back up, but I agree with you. I think that is, um, one of the best things. Raise your hand, ask a question, ladies. Thank you so much for joining me talking about honeycomb and AWS, what you're doing together from a technology perspective and the focus efforts that each company has on D E and I, we appreciate your insights. Thank you so much for having us great talking to you. My pleasure, likewise for my guests, I'm Lisa Martin. You're watching the AWS partner showcase women in check. Welcome to the AWS partner showcase I'm Lisa Martin, your host. This is season one, episode three, and this is a great episode that focuses on women in tech. I'm pleased to be joined by Danielle Shaw, the ISV PSA director at AWS, and the sponsor of this fantastic program. Danielle, it's great to see you and talk about such an important topic. >>Yes. And I will tell you, all of these interviews have just been a blast for me to do. And I feel like there has been a lot of gold that we can glean from all of the, um, stories that we heard on these interviews and good advice that I myself would not have necessarily thought of. So >>I agree. And we're gonna get to set, cuz advice is one of the, the main things that our audience is gonna hear. We have Hillary Ashton, you'll see from TETA there, Reynolds joins us from honeycomb, Stephanie Curry from NetApp and Sue Paris from Jefferson Frank. And the topics that we dig into are first and foremost, diversity equity and inclusion. That is a topic that is incredibly important to every organization. And some of the things Danielle that our audiences shared were really interesting to me. One of the things that I saw from a thematic perspective over and over was that like D Reynolds was talking about the importance of companies and hiring managers and how they need to be intentional with de and I initiatives. And that intention was a, a, a common thing that we heard. I'm curious what your thoughts are about that, that we heard about being intentional working intentionally to deliver a more holistic pool of candidates where de I is concerned. What are your, what were some of the things that stuck out to you? >>Absolutely. I think each one of us is working inside of organizations where in the last, you know, five to 10 years, there's been a, you know, a strong push in this direction, mostly because we've really seen, um, first and foremost, by being intentional, that you can change the, uh, the way your organization looks. Um, but also just that, you know, without being intentional, um, there was just a lot of, you know, outcomes and situations that maybe weren't great for, um, you know, a healthy, um, and productive environment, uh, working environment. And so, you know, a lot of these companies have made a big investments and put forth big initiatives that I think all of us are involved in. And so we're really excited to get out here and talk about it and talk about, especially as these are all partnerships that we have, how, you know, these align with our values. So >>Yeah, that, that value alignment mm-hmm <affirmative> that you bring up is another thing that we heard consistently with each of the partners, there's a cultural alignment, there's a customer obsession alignment that they have with AWS. There's a D E and I alignment that they have. And I, I think everybody also kind of agreed Stephanie Curry talked about, you know, it's really important, um, for diversity on it, on, on impacting performance, highly performant teams are teams that are more diverse. I think we heard that kind of echoed throughout the women that we talked to in >>This. Absolutely. And I absolutely, and I definitely even feel that, uh, with their studies out there that tell you that you make better products, if you have all of the right input and you're getting all many different perspectives, but not just that, but I can, I can personally see it in the performing teams, not just my team, but also, you know, the teams that I work alongside. Um, arguably some of the other business folks have done a really great job of bringing more women into their organization, bringing more underrepresented minorities. Tech is a little bit behind, but we're trying really hard to bring that forward as well to in technical roles. Um, but you can just see the difference in the outcomes. Uh, at least I personally can just in the adjacent teams of mine. >>That's awesome. We talked also quite a bit during this episode about attracting women and underrepresented, um, groups and retaining them. That retention piece is really key. What were some of the things that stuck out to you that, um, you know, some of the guests talked about in terms of retention? >>Yeah. I think especially, uh, speaking with Hillary and hearing how, uh, Teradata is thinking about different ways to make hybrid work work for everybody. I think that is definitely when I talk to women interested in joining AWS, oftentimes that might be one of the first, uh, concerns that they have. Like, am I going to be able to, you know, go pick my kid up at four o'clock at the bus, or am I going to be able to, you know, be at my kids' conf you know, conference or even just, you know, have enough work life balance that I can, um, you know, do the things that I wanna do outside of work, uh, beyond children and family. So these are all very important, um, and questions that especially women come and ask, but also, um, you know, it kind of is a, is a bellwether for, is this gonna be a company that allows me to bring my whole self to work? And then I'm also gonna be able to have that balance that I need need. So I think that was something that is, uh, changing a lot. And many people are thinking about work a lot differently. >>Absolutely. The pandemic not only changed how we think about work, you know, initially it was, do I work from home or do I live at work? And that was legitimately a challenge that all of us faced for a long time period, but we're seeing the hybrid model. We're seeing more companies be open to embracing that and allowing people to have more of that balance, which at the end of the day, it's so much better for product development for the customers, as you talked about there's, it's a win-win. >>Absolutely. And, you know, definitely the first few months of it was very hard to find that separation to be able to put up boundaries. Um, but I think at least I personally have been able to find the way to do it. And I hope that, you know, everyone is getting that space to be able to put those boundaries up to effectively have a harmonious, you know, work life where you can still be at home most of the time, but also, um, you know, have that cutoff point of the day or at least have that separate space that you can feel that you're able to separate the two. >>Yeah, absolutely. And a lot of that from a work life balance perspective leads into one of the next topics that we covered in detail with, and that's mentors and sponsors the differences between them recommendations from, uh, the women on the panel about how to combat imposter syndrome, but also how to leverage mentors and sponsors throughout your career. One of the things that, that Hillary said that I thought was fantastic, advice were mentors and sponsors are concerned is, is be selective in picking your bosses. We often see people, especially younger folks, not necessarily younger folks. I shouldn't say that that are attracted to a company it's brand maybe, and think more about that than they do the boss or bosses that can help guide them along the way. But I thought that was really poignant advice that Hillary provided something that I'm gonna take into consideration myself. >>Yeah. And I honestly hadn't thought about that, but as I reflect through my own career, I can see how I've had particular managers who have had a major impact on helping me, um, with my career. But, you know, if you don't have the ability to do that, or maybe that's not a luxury that you have, I think even if you're able to, you know, find a mentor for a period of time or, um, you know, just, just enable for you to be able to get from say a point a to point B just for a temporary period. Um, just so you can grow into your next role, have a, have a particular outcome that you wanna drive, have a particular goal in mind find that person who's been there and done that and can really help you get through. If you don't have the luxury of picking your manager mentor, who can help you get to the next step. >>Exactly. That, that I thought that advice was brilliant and something that I hadn't really considered either. We also talked with several of the women about imposter syndrome. You know, that's something that everybody, I think, regardless of gender of your background, everybody feels that at some point. So I think one of the nice things that we do in this episode is sort of identify, yes, imposter syndrome is real. This is, this is how it happened to me. This is I navigated around or got over it. I think there's some great advice there for the audience to glean as well about how to dial down the imposter syndrome that they might be feeling. >>Absolutely. And I think the key there is just acknowledging it. Um, but also just hearing all the different techniques on, on how folks have dealt with it because everybody does, um, you know, even some of the smartest, most confident men I've, I've met in, uh, industry still talk to me about how they have it and I'm shocked by it oftentimes, but, um, it is very common and hopefully we, we talk about some good techniques to, to deal with that. >>I think we do, you know, one of the things that when we were asking the, our audience, our guests about advice, what would they tell their younger selves? What would they tell young women or underrepresented groups in terms of becoming interested in stem and in tech and everybody sort of agreed on me, don't be afraid to raise your hand and ask questions. Um, show vulnerabilities, not just as the employee, but even from a leadership perspective, show that as a leader, I, I don't have all the answers. There are questions that I have. I think that goes a long way to reducing the imposter syndrome that most of us have faced at some point in our lives. And that's just, don't be afraid to ask questions. You never know, oh, how can people have the same question sitting in the room? >>Well, and also, you know, for folks who've been in industry for 20, 25 years, I think we can just say that, you know, it's a, it's a marathon, it's not a sprint and you're always going to, um, have new things to learn and you can spend, you know, back to, we talked about the zing and zagging through careers, um, where, you know, we'll have different experiences. Um, all of that kind of comes through just, you know, being curious and wanting to continue to learn. So yes, asking questions and being vulnerable and being able to say, I don't know all the answers, but I wanna learn is a key thing, uh, especially culturally at AWS, but I'm sure with all of these companies as well, >>Definitely I think it sounded like it was really ingrained in their culture. And another thing too, that we also talked about is the word, no, doesn't always mean a dead end. It can often mean not right now or may, maybe this isn't the right opportunity at this time. I think that's another important thing that the audience is gonna learn is that, you know, failure is not necessarily a bad F word. If you turn it into opportunity, no isn't necessarily the end of the road. It can be an opener to a different door. And I, I thought that was a really positive message that our guests, um, had to share with the, the audience. >>Yeah, totally. I can, I can say I had a, a mentor of mine, um, a very, uh, strong woman who told me, you know, your career is going to have lots of ebbs and flows and that's natural. And you know that when you say that, not right now, um, that's a perfect example of maybe there's an ebb where it might not be the right time for you now, but something to consider in the future. But also don't be afraid to say yes, when you can. <laugh> >>Exactly. Danielle, it's been a pleasure filming this episode with you and the great female leaders that we have on. I'm excited for the audience to be able to learn from Hillary Vera, Stephanie Sue, and you so much valuable content in here. We hope you enjoy this partner showcase season one, episode three, Danielle, thanks so much for helping >>Us with it's been a blast. I really appreciate it >>All audience. We wanna enjoy this. Enjoy the episode.

Published Date : Jul 21 2022

SUMMARY :

It's great to have you on the program talking And so as we talk about women I don't know how you do it. And I think it really, uh, improves the behaviors that we can bring, That's not something that we see very often. from the technology that we can create, which I think is fantastic. you and I have talked about this many times you bring such breadth and such a wide perspective. be able to change the numbers that you have. but what are, what do you think can be done to encourage, just the bits and bites and, and how to program, but also the value in outcomes that technology being not afraid to be vulnerable, being able to show those sides of your personality. And so I think learning is sort of a fundamental, um, uh, grounding And so I think as we look at the, And also to your other point, hold people accountable I definitely think in both technical and product roles, we definitely have some work to do. What are you seeing? and that I think is going to set us back all of us, the, the Royal us or the Royal we back, And I think, um, that that really changes I would like to think that tech can lead the way in, um, you know, coming out of the, but what advice would you give your younger self and that younger generation in terms I mean, you know, stem inside and out because you walk around And so demystifying stem as something that is around how I think picking somebody that, you know, we talk about mentors and we talk And that person can put you in the corner and not invite you to the meetings and not give you those opportunities. But luckily we have great family leaders like the two of you helping us Thank you Lisa, to see you. It's great to have you on the program talking about So let's go ahead and start with you. And if you look at it, it's really talent as a service. Danielle, talk to me a little bit about from AWS's perspective and the focus on You know, we wanna have, uh, an organization interacting with them Um, I just think that, um, you know, I I've been able to get, There's so much data out there that shows when girls start dropping up, but what are some of the trends that you are And we were talking about only 7% of the people that responded to it were women. I was watching, um, Sue, I saw that you shared on LinkedIn, the Ted talk that I think it speaks to what Susan was talking about, how, you know, I think we're approaching I think, you know, we're, we're limited with the viable pool of candidates, um, Sue, is that something that Jefferson Frank is also able to help with is, you know, I was talking about how you can't be what you can't see. And I thought I understood that, but those are the things that we need uh, on how <laugh>, you know, it used to be a, a couple years back, I would feel like sometimes And so you bring up a great point about from a diversity perspective, what is Jefferson Frank doing to, more data that we have, I mean, the, and the data takes, uh, you know, 7% is such a, you know, Danielle and I we're, And I feel like, you know, I just wanna give back, make sure I send the elevator back to but to your point to get that those numbers up, not just at AWS, but everywhere else we need, Welcome to the AWS partner showcase season one, episode three women Um, I had an ally really that reached out to me and said, Hey, you'd be great for this role. So what I wanna focus on with you is the importance of diversity for And we do find that oftentimes being, you know, field facing, if we're not reflecting Definitely it's all about outcomes, Stephanie, your perspective and NetApp's perspective on diversity And in addition to that, you know, just from building teams that you do Stephanie, that NetApp does to attract and retain women in those sales roles? And we find that, you know, you, you read the stats and I'd say in my And I, that just shocked me that I thought, you know, I, I can understand that imposter syndrome is real. Danielle, talk to me about your perspective and AWS as well for attracting and retaining I mean, my team is focused on the technical aspect of the field and we And I said that in past tense, a period of time, we definitely felt like we could, you know, conquer the world. in the tech industry, but talk to me about allies sponsors, mentors who have, And I think that's just really critical when we're looking for allies and when allies are looking I love how you described allies, mentors and sponsors Stephanie. the community that they can reach out to for those same opportunities and making room for them Let's talk about some of the techniques that you employ, that AWS employees to make Um, but I think just making sure that, um, you know, both everything is so importants, let's talk about some of the techniques that you use that NetApp take some time and do the things you need to do with your family. And that it's okay to say, I need to balance my life and I need to do Talk to me a little bit, Danielle, go back over to you about the AWS APN, this is, you know, one of the most significant years with our launch of FSX for And Stephanie talk to, uh, about the partnership from your perspective, NetApp, And I have to say it's just been a phenomenal year. And I think that there is, um, a lot of best practice sharing and collaboration as we go through And I wanna stick with you Stephanie advice to your younger And sometimes when you get a no, it's not a bad thing, And I always say failure does not have to be an, a bad F word. out there in order to, um, you know, allow younger women to I appreciate you sharing what AWS It's great to have you talking about a very important topic today. Yeah, thanks for having me. Of course, Vera, let's go ahead and start with you. Um, and in the more recent years I And on the one hand they really spoke to me as the solution. You mentioned that you like the technology, but you were also attracted because you saw uh, rhetoric shift recently because we believe that with great responsibility, I do wanna have you there talk to the audience a little bit about honeycomb, what technology And you can't predict what you're And to give you an example of how that looks for Uh, and we believe that's where we shine in helping you there. It sounds like that's where you really shine that real time visibility is so critical these days. Um, definitely something that we see a lot of demand with our customers and they have many integrations, Back to you, let's kind of unpack the partnership, the significance that Um, I know this predates me to some extent, And then that way we can be sort of the Guinea pigs and try things out, um, And how is that synergistic with AWS's approach? And so we are recognizing that we need to be more intentional with our DEI initiatives, Danielle, I know we've talked about this before, but for the audience, in terms of And I think, you know, working with, uh, a company like honeycomb that to hear that that's so fundamental to both companies, Barry, I wanna go back to you for a second. And I actually am in the process of hiring a first engineer for my Danielle, before we close, I wanna get a little bit of, of your background. And I'm, I'm grateful to be part of it. And we're almost out of time and Danielle, I'm gonna stick with you. I mean, definitely for the individual contributors, tech tech is a great career, uh, Take the lead, love that there. And on the flip side of that, if you are a more senior IC or, Danielle, it's great to see you and talk about such an important topic. And I feel like there has been a lot of gold that we can glean from all of the, And the topics that we dig the last, you know, five to 10 years, there's been a, you know, a strong push in this direction, I think everybody also kind of agreed Stephanie Curry talked about, you know, it's really important, um, Um, but you can just see the difference in the outcomes. um, you know, some of the guests talked about in terms of retention? um, you know, it kind of is a, is a bellwether for, is this gonna be a company that allows The pandemic not only changed how we think about work, you know, initially it was, And I hope that, you know, everyone is getting that space to be able to put those boundaries up I shouldn't say that that are attracted to a company it's brand maybe, Um, just so you can grow into your next role, have a, have a particular outcome I think there's some great advice there for the audience to glean on, on how folks have dealt with it because everybody does, um, you know, I think we do, you know, one of the things that when we were asking the, our audience, I think we can just say that, you know, it's a, it's a marathon, it's not a sprint and you're always going the audience is gonna learn is that, you know, failure is not necessarily a bad F word. uh, strong woman who told me, you know, your career is going to have lots of ebbs and flows and Danielle, it's been a pleasure filming this episode with you and the great female I really appreciate it Enjoy the episode.

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AWS Partner Showcase S1E3 Wrap


 

(bright music) >> Welcome to the AWS Partner Showcase. I'm Lisa Martin, your host. This is season one episode three and this is a great episode that focuses on women in tech. I'm pleased to be joined by Danielle Greshock, the ISV PSA director at AWS, and a sponsor of this fantastic program. Danielle, it's great to see you and talk about such an important topic. >> Yes, and I will tell you all of these interviews have just been a blast for me to do and I feel like there has been a lot of gold that we can glean from all of the stories that we heard on these interviews and good advice that I myself would not have necessarily thought of. >> I agree, and we're going to get to (indistinct) 'cause advice is one of the the main things that our audience is going to hear. We have Hillary Ashton, you'll see from Teradata. Vera Reynolds joins us from Honeycomb. Stephanie Curry from NetApp. And Sue Persichetti from Jefferson Frank and the topics that we dig into are, first and foremost, diversity equity and inclusion, that is a topic that is incredibly important to every organization. And some of the things, Danielle, that our audiences shared were really interesting to me. One of the things that I saw, from a thematic perspective, over and over, was that, like Vera Reynolds was talking about, the importance of companies and hiring managers and how they need to be intentional with DE&I initiatives and that intention was a common theme that we heard. I'm curious what your thoughts are about that, that we heard about being intentional, working intentionally to deliver a more holistic pool of candidates where DE&I is concerned. What were some of the things that stuck out to you? >> Absolutely, I think each one of us is working inside of organizations where, in the last five to 10 years, there's been a strong push in this direction, mostly because we've really seen, first and foremost by being intentional, that you can change the way your organization looks. But also just that without being intentional there was just a lot of outcomes and situations that maybe weren't great for a healthy and productive environment, working environment. And so a lot of these companies have made big investments and put forth big initiatives that I think all of us are involved in and so we're really excited to get out here and talk about it and talk about, especially as these are all partnerships that we have, how these align with our values. >> Yeah, that value alignment that you bring up is another theme that we heard consistently with each of the partners. There's a cultural alignment. There's a customer obsession alignment that they have with AWS. There's a DE&I alignment that they have and I think everybody also kind of agreed, Stephanie Curry talked about, it's really important for diversity on impacting performance, highly performant teams are teams that are more diverse. I think we heard that kind of echoed throughout the women that we talked to in this episode. >> Absolutely, and I definitely even feel that there are studies out there that tell you that you make better products if you have all of the right input and you're getting many different perspectives. But not just that, I can personally see it in the performing teams, not just my team, but also the teams that I work alongside. Arguably some of the other business folks have done a really great job of bringing more women into their organization, bringing more underrepresented minorities, tech is a little bit behind but we're trying really hard to bring that forward as well in technical roles. But you can just see the difference in the outcomes. At least I personally can, just in the adjacent teams of mine. >> That's awesome, we talked also quite a bit during this episode about attracting women and underrepresented groups and retaining them. That retention piece is really key. What were some of the things that stuck out to you that some of the guests talked about in terms of retention? >> Yeah, I think, especially speaking with Hillary and hearing how Teradata is thinking about different ways to make hybrid work work for everybody, I think that is definitely, when I talk to women interested in joining AWS, oftentimes that might be one of the first concerns that they have. Like, am I going to be able to go pick my kid up at four o'clock at the bus? Or, am I going to be able to be at my kid's conference? Or even just have enough work life balance that I can do the things that I want to do outside of work, beyond children and family. So these are all very important questions that especially women come and ask, but also it kind of is a bellwether for, is this going to be a company that allows me to bring my whole self to work and then I'm also going to be able to have that balance that I need. So I think that was something that is changing a lot and many people are thinking about work a lot differently. >> Absolutely, the pandemic not only changed how we think about work. You know, initially it was, do I work from home or do I live at work, and that was legitimately a challenge that all of us faced for a long time period, but we're seeing the hybrid model, we're seeing more companies be open to embracing that and allowing people to have more of that balance, which, at the end of the day, it's so much better for product development for the customers, as you talked about, it's a win-win. >> Absolutely, and definitely the first few months of it was very hard to find that separation, to be able to put up boundaries, but I think, at least I personally, have been able to find the way to do it and I hope that everyone is getting that space to be able to put those boundaries up, to effectively have a harmonious work life where you can still be at home most of the time, but also have that cutoff point of the day or at least have that separate space that you can feel that you're able to separate the two. >> Yeah absolutely, and a lot of that, from a work life balance perspective, bleeds into one of the next topics that we covered in detail and that's mentors and sponsors, the differences between them, recommendations from the women on the panel about how to combat imposter syndrome, but also how to leverage mentors and sponsors throughout your career. One of the things that Hillary said that I thought was fantastic advice, where mentors and sponsors are concerned, is be selective in picking your bosses. We often see people, especially younger folks, not necessarily younger folks, I shouldn't say that, that are attracted to a company, it's brand maybe, and think more about that than they do the boss or bosses that can help guide them along the way, but I thought that was really poignant advice that Hillary provided, something that I'm going to take into consideration myself. >> Yeah, and I honestly hadn't thought about that but as I reflect through my own career I can see how I've had particular managers who have had a major impact on helping me with my career. But if you don't have the ability to do that or maybe that's not a luxury that you have, I think even if you're able to find a mentor for a period of time or just enable for you to be able to get from, say a point A to point B, just for a temporary period, just so you can grow into your next role. Have a particular outcome that you want to drive. Have a particular goal in mind. Find that person who's been there and done that and they can really help you get through. If you don't have the luxury of picking your manager, at least be able to pick a mentor who can help you get to the next step. >> Exactly, I thought that advice was brilliant and it's something that I hadn't really considered either. We also talked with several of the women about imposter syndrome. You know that's something that everybody, I think regardless of gender, of your background, everybody feels that at some point. So I think one of the nice things that we do in this episode is sort of identify, yes, imposter syndrome is real, this is how it happened to me, this is how I navigated around or got over it. I think there's some great advice there for the audience to glean as well, about how to dial down the imposter syndrome that they might be feeling. >> Absolutely and I think the key there is just acknowledging it but also just hearing all the different techniques on how folks have dealt with it because everybody does. Even some of the smartest, most confident men I've met in industry still talk to me about how they have it and I'm shocked by it oftentimes, but it is very common and hopefully we talk about some good techniques to deal with that. >> I think we do. You know, one of the things that, when we were asking our guests about advice, what would they tell their younger selves, what would they tell young women or underrepresented groups in terms of becoming interested in STEM and in tech, and everybody sort of agreed on the, don't be afraid to raise your hand and ask questions. Show vulnerabilities, not just as the employee, but even from a leadership perspective, show that as a leader. I don't have all the answers. There are questions that I have. I think that goes a long way to reducing the imposter syndrome that most of us have faced at some point in our lives and that's just, don't be afraid to ask questions. You never know how many people have the same question sitting in the room. >> Well and also, for folks who've been in industry for 20, 25 years, I think we can just say that it's a marathon, it's not a sprint, and you're always going to have new things to learn and you can spend, back to we talked about the zigging and zagging through careers where we'll have different experiences, all of that kind of comes through just being curious and wanting to continue to learn. So yes, asking questions and being vulnerable and being able to say, "I don't know all the answers but I want to learn," is a key thing, especially culturally at AWS, but I'm sure with all of these companies as well. >> Definitely I think it sounded like it was really ingrained in their culture. And another thing too that we also talked about is the word no doesn't always mean a dead end. It can often mean, not right now, or maybe this isn't the right opportunity at this time. I think that's another important thing that the audience is going to learn is that failure is not necessarily a bad F word if you turn it into opportunity. No isn't necessarily the end of the road. It can be an opener to a different door and I thought that was a really positive message that our guests had to share with the audience. >> Yeah totally, I can say I had a mentor of mine, a very strong woman who told me, your career is going to have lots of ebbs and flows and that's natural and that when you say that, not right now, that's a perfect example of maybe there's an ebb where it might not be the right time for you now, but something to consider in the future. But also don't be afraid to say yes, when you can. >> Exactly, Danielle, it's been a pleasure filming this episode with you and the great female leaders that we have on. I'm excited for the audience to be able to learn from Hillary, Vera, Stephanie, Sue, and you. So much valuable content in here. We hope you enjoy this Partner Showcase. Season one episode three. Danielle, thank you so much for helping us. >> Thank you. Thank you, it's been a blast. I really appreciate it. >> All right, audience, we want to thank you. Enjoy the episode. (upbeat music)

Published Date : Jul 20 2022

SUMMARY :

Danielle, it's great to see you and good advice that I myself and how they need to be in the last five to 10 years, alignment that you bring up that you make better products that some of the guests talked that I can do the things that and allowing people to but also have that cutoff point of the day that are attracted to a the ability to do that and it's something that I Absolutely and I think the key there I don't have all the answers. and being able to say, that our guests had to that when you say that, and the great female I really appreciate it. Enjoy the episode.

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AWS Partner Showcase S1E3 Intro


 

(bright music) >> Everyone, it's nice to see you. Welcome to the "AWS Partner Showcase". I'm Lisa Martin, your host. This is season one, episode three, and this is a great episode that focuses on women in tech. I'm pleased to be joined by Danielle Greshock, the ISV PSA Director at AWS, and the sponsor of this fantastic program. Danielle, it's great to see you, and talk about such an important topic. >> Yes, and I will tell you all of these interviews have just been a blast for me to do, and I feel like there has been a lot of gold that we can glean from all of the stories that we heard on these interviews and good advice that I myself would not have necessarily thought of. So-- >> I agree, and we're going to get to that. 'Cause advice is one of the main things that our audience is going to hear. We have Hillary Ashton, you'll see from Teradata, Vera Reynolds joins us from Honeycomb, Stephanie Curry from NetApp and Sue Persichetti from Jefferson Frank. And the topics that we dig into are first and foremost, diversity, equity and inclusion. That is a topic that is incredibly important to every organization. And some of the things, Danielle, that our audiences shared were really interesting to me. One of the things that I saw from a thematic perspective over and over was that like Vera Reynolds was talking about the importance of companies and hiring managers and how they need to be intentional with DE&I initiatives. And that intention was a common thing that we heard. I'm curious what your thoughts are about that, that we heard about being intentional, working intentionally to deliver a more holistic pool of candidates where DE&I is concerned. What were some of the things that stuck out to you? >> Absolutely, I think each one of us is working in the inside of organizations where in the last five to 10 years there's been a strong push in this direction. Mostly because we've really seen first and foremost by being intentional, that you can change the way your organization looks. But also just that without being intentional, there was just a lot of outcomes and situations that maybe weren't great for a healthy and productive working environment. And so a lot of these companies have made big investments and put forth big initiatives that I think all of us are involved in. And so we're really excited to get out here and talk about it and talk about, especially as these are all partnerships that we have, how these align with our values. >> Yeah, that value alignment that you bring up is another thing that we heard consistently with each of the partners. There's a cultural alignment, there's a customer obsession alignment that they have with AWS, there's a DE&I alignment that they have. And I think everybody also kind of agreed. Stephanie Curry talked about it's really important for diversity on impacting performance. Highly performing teams are teams that are more diverse. I think we heard that kind of echoed throughout the women that we talked to in this episode. >> Absolutely, and I definitely even feel that there are studies out there that tell you that you make better products if you have all of the right input and you're getting many different perspectives. But not just that, but I can personally see it in the performing teams, not just my team, but also the teams that I work alongside. Arguably some of the other business folks have done a really great job of bringing more women into their organization, bringing more underrepresented minorities. Tech is a little bit behind, but we're trying really hard to bring that forward as well in technical roles. But you can just see the difference in the outcomes. At least I personally can just in the adjacent teams of mine. >> That's awesome. We talked also quite a bit during this episode about attracting women and underrepresented groups and retaining them. That retention piece is really key. What were some of the things that stuck out to you that some of the guests talked about in terms of retention? >> Yeah, I think especially speaking with Hillary and hearing how Teradata is thinking about different ways to make hybrid work work for everybody. I think that is definitely... When I talk to women interested in joining AWS, oftentimes that might be one of the first concerns that they have. Like, am I going to be able to go pick my kid up at four o'clock at the bus? Or am I going to be able to be at my kids' conference, or even just have enough work-life balance that I can do the things that I want to do outside of work beyond children and family. So these are all very important questions that especially women come and ask, but also it kind of is a bellwether for, is this going to be a company that allows me to bring my whole self to work? And then I'm also going to be able to have that balance that I need. So I think that was something that is changing a lot and many people are thinking about work a lot differently. >> Absolutely, the pandemic not only changed how we think about work. Initially it was, do I work from home or do I live at work? And that was legitimately a challenge that all of us faced for a long time period. But we're seeing the hybrid model, we're seeing more companies be open to embracing that and allowing people to have more of that balance which at the end of the day it's so much better for product development for the customers as you talked about, it's a win-win. >> Absolutely. And definitely the first few months of it was very hard to find that separation to be able to put up boundaries. But I think at least I personally have been able to find the way to do it and I hope that everyone is getting that space to be able to put those boundaries up to effectively have a harmonious work life. Where you can still be at home most of the time, but also have that cutoff point of the day or at least have that separate space that you can feel that you're able to separate the two. >> Yeah, absolutely. And a lot of that from a work-life balance perspective leads into one of the next topics that we covered in detail. And that's mentors and sponsors, the differences between them, recommendations from the women on the panel about how to combat imposter syndrome, but also how to leverage mentors and sponsors throughout your career. One of the things that Hillary said that I thought was fantastic advice where mentors and sponsors are concerned is be selective in picking your bosses. We often see people, especially younger folks, not necessarily younger folks, I shouldn't say that, that are attracted to a company, its brand maybe, and think more about that than they do the boss or bosses that can help guide them along the way. But I thought that was really poignant advice that Hillary provided, something that I'm going to take into consideration myself. >> Yeah, and I honestly hadn't thought about that, but as I reflect through my own career, I can see how I've had particular managers who have had a major impact on helping me with my career. But if you don't have the ability to do that or maybe that's not a luxury that you have, I think even if you're able to find a mentor for a period of time or just enable for you to be able to get from say a point A to point B just for a temporary period, just so you can grow into your next role, have a particular outcome that you want to drive, have a particular goal in mind. Find that person who's been there and done that and they can really help you get through if you don't have the luxury of picking your manager, at least be able to pick a mentor who can help you get to the next step. >> Exactly, I thought that advice was brilliant and something that I hadn't really considered either. We also talked with several other women about imposter syndrome. That's something that everybody, I think regardless of gender, of your background, everybody feels that at some point. So I think one of the nice things that we do in this episode is sort of identify, yes, imposter syndrome is real. This is how it happened to me, this is how I navigated around it or got over it. I think there's some great advice there for the audience to glean as well about how to dial down the imposter syndrome that they might be feeling. >> Absolutely. And I think the key there is just acknowledging it, but also just hearing all the different techniques on how folks have dealt with it, because everybody does. Even some of the smartest, most confident men I've met in industry still talk to me about how they have it. And I'm shocked by it oftentimes, but it is very common. And hopefully we talk about some good techniques to deal with that. >> I think we do. One of the things that when we were asking our guests about advice, what would they tell their younger selves, what would they tell young women or underrepresented groups in terms of becoming interested in STEM and in tech. And everybody sort of agreed on the don't be afraid to raise your hand and ask questions. Show vulnerabilities, not just as the employee, but even from a leadership perspective, show that as a leader, I don't have all the answers. There are questions that I have. I think that goes a long way to reducing the imposter syndrome that most of us have faced at some point in our lives. And that's just, don't be afraid to ask questions. You never know how many people have the same question sitting in the room. >> Well, and also for folks who've been in industry for 20, 25 years, I think we can just say that it's a marathon, it's not a sprint, and you're always going to have new things to learn. And you can spend... Back to we talked about the zigging and zagging through careers where we'll have different experiences. All of that kind of comes through just being curious and wanting to continue to learn. So yes, asking questions and being vulnerable and being able to say, I don't know all the answers but I want to learn is a key thing, especially culturally at AWS, but I'm sure with all of these companies as well. >> Definitely I think it sounded like it was really ingrained in their culture. And another thing too that we also talked about is the word, no, doesn't always mean a dead end, it can often mean, not right now or maybe this isn't the right opportunity at this time. I think that's another important thing that the audience is going to learn is that failure is not necessarily a bad F-word if you turn it into opportunity. No isn't necessarily the end of the road. It can be an opener to a different door. And I thought that was a really positive message that our guests had to share with the audience. >> Yeah, totally. I can say I had a mentor of mine, a very strong woman who told me, "Your career is going to have lots of ebbs and flows, and that's natural." And that when you say that, not right now, that's a perfect example of maybe there's an ebb where it might not be the right time for you now, but something to consider in the future. But also don't be afraid to say yes when you can. >> Exactly. Danielle, it's been a pleasure filming this episode with you and the great female leaders that we have on. I'm excited for the audience to be able to learn from Hillary, Vera, Stephanie, Sue and you. So much valuable content in here. We hope you enjoy this partner showcase season one episode three. Danielle, thanks so much for helping us with this. >> Thank you. Thank you, it's been a blast, I really appreciate it. >> All right. Audience, we want to thank you, enjoy the episode. (gentle music)

Published Date : Jul 18 2022

SUMMARY :

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Hillary Ashton, Teradata & Danielle Greshock, AWS


 

(upbeat music) >> Hey everyone. Welcome to the AWS partner showcase. This is season one, episode three. And I'm your host, Lisa Martin. I've got two great guests here with me to talk about Women in Tech. Hillary Ashton joins us, the chief product officer at Teradata, and Danielle Greshock is back with us, the ISV PSA director at AWS Ladies. It's great to have you on the program talking through such an important topic. Hillary, let's go ahead and start with you. Give us a little bit of an intro into you, your background and a little bit about Teradata. >> Yeah, absolutely. So I'm Hillary Ashton. I head up the products organization. So that's our engineering, product management, officer of the CTO team at Teradata. I've been with Teradata for just about three years and really have spent the last several decades, if I can say that in the data and analytics space. I spent time really focused on the value of analytics at scale, and I'm super excited to be here at Teradata. I'm also a mom of two teenage boys. And so as we talk about women in tech, I think there's lots of different dimensions and angles of that. At Teradata we are partnered very deeply with AWS and happy to talk a little bit more about that throughout this discussion as well. >> Excellent. A busy mom of two teen boys. My goodness. I don't know how you do it. Let's now look at Teradata's views of diversity, equity and inclusion. It's a topic that's important to everyone but give us a snapshot into some of the initiatives that Teradata has there. >> Yeah, I have to say, I am super proud to be working at Teradata. We have gone through a series of transformations but I think it starts with culture and we are deeply committed to diversity, equity and inclusion. It's really more than just a statement here. It's just how we live our lives. And we use data to back that up. In fact, we were named one of the world's most ethical companies for the 13th year in a row. And all of our executive leadership team has taken an oath around DE&I, that's available on LinkedIn as well. So in fact, our leadership team reporting into the CEO is just about 50/50 men and women which is the first time I've worked in a company where that has been the case. And I think as individuals, we can probably appreciate what a huge difference that makes in terms of not just being a representative, but truly being on a diverse and equitable team. And I think it really improves the behaviors that we can bring to our office. >> There's so much value in that. It's I impressive to see about a 50/50 at the leadership level. That's not something that we see very often. Tell me how you, Hillary, how did you get into tech? Were you an engineering person by computer science or did you have more of a zigzaggy path to where you are now? >> I'm going to pick door number two and say more zigzaggy. I started off thinking that, I started off as a political science major or a government major and I was probably destined to go into the law field but actually took a summer course at Harvard, I did not go to Harvard, but I took a summer course there and learned a lot about multimedia and some programming. And that really set me on a trajectory of how data and analytics can truly provide value and outcomes to our customers. And I have been living that life ever since I graduated from college. So I was very excited and privileged in my early career to work in a company where I found after my first year that I was managing kids, people who had graduated from Harvard Business School and from MIT Sloan School. And that was super crazy 'cause I did not go to either of those schools but I sort of have always had a natural knack for how do you take technology and the really cool things that technology can do, but because I'm not a programmer by training, I'm really focused on the value that I'm able to help organizations really extract value from the technology that we can create, which I think is fantastic. >> I think there's so much value in having a zigzag path into tech. You bring... Danielle, you and I have talked about this many times, you bring such breadth and such a wide perspective that really is such a value add to teams. Danielle, talk to us from AWS's perspective about what can be done to encourage more young women to get, and underrepresented groups as well to get into STEM and stay. >> Yeah, and this is definitely a challenge as we're trying to grow our organization and kind of shift the numbers. And the reality is, especially with the more senior folks in our organization, unless you bring folks with a zigzag path, the likelihood is you won't be able to change the numbers that you have. But for me, it's really been about looking at that, the folks who are just graduating college, maybe in other roles where they are adjacent to technology and to try to spark their interest and show that, yes, they can do it because oftentimes it's really about believing in themselves and realizing that we need folks with all sorts of different perspectives to kind of come in to be able to help really provide both products and services and solutions for all types of people inside of technology which requires all sorts of perspectives. >> Yeah, the diverse perspectives. There's so much value and there's a lot of data that demonstrates how much value, revenue impact organizations can make by having diversity especially at the leadership level. Hillary, let's go back to you. We talked about your career path. You talked about some of the importance of the focus on DE&I at Teradata, but what do you think can be done to encourage, sorry, to recruit more young women and under represented groups into tech, any carrots there that you think are really important that we need to be dangling more of? >> Yeah, absolutely. And I'll build on what Danielle just said. I think the bringing in diverse understandings of customer outcomes, I mean, we've really moved from technology for technology's sake. And I know AWS and Entirety have had a lot of conversations on how do we drive customer outcomes that are differentiated in the market and really being customer-centric. And technology is wonderful. You can do wonderful things with it. You can do not so wonderful things with it as well but unless you're really focused on the outcomes and what customers are seeking technology is not hugely valuable. And so I think bringing in people who understand voice of customer, who understand those outcomes and those are not necessarily the folks who are PhD in mathematics or statistics, those can be people who understand a day in the life of a data scientist or a day in the life of a citizen data scientist. And so really working to bridge the high impact technology with the practical kind of usability, usefulness of data and analytics in our cases, I think is something that we need more of in tech and sort of demystifying tech and freeing technology so that everybody can use it and having a really wide range of people who understand not just the bits and bites and and how to program, but also the value and outcomes that technology through data and analytics can drive. >> Yeah. You know, we often talk about the hard skills but the soft skills are equally, if not more important that even just being curious, being willing to ask questions being not afraid to be vulnerable, being able to show those sides of your personality. I think those are important for young women and underrepresented groups to understand that those are just as important as some of the harder technical skills that can be taught. >> That's right. >> What do you think about from a bias perspective, Hillary, what have you seen in the tech industry and how do you think we can leverage culture as you talked about to help dial down some of the biases that are going on? >> Yeah. I mean, I think first of all, and there's some interesting data out there that says that 90% of the population, which includes a lot of women have some inherent bias in their day to day behaviors when it comes to women in particular. But I'm sure that that is true across all kinds of of diverse and underrepresented folks in the world. And so I think acknowledging that we have bias and actually really learning what that can look like, how that can show up, we might be sitting here and thinking, oh, of course I don't have any bias. And then you realize that as you learn more about different types of bias that actually you do need to kind of account for that and change behaviors. And so I think learning is sort of a fundamental grounding for all of us to really know what bias looks like, know how it shows up in each of us, if we're leaders, know how it shows up in our teams and make sure that we are constantly getting better. We're not going to be perfect anytime soon, but I think being on a path to improvement to overcoming bias is really critical. And part of that is really starting the dialogue, having the conversations, holding ourselves and each other accountable when things aren't going in a copesthetic way, and being able to talk openly about that felt like maybe there was some bias in that interaction and how do we make good on that? How do we change our behavior fundamentally. Of course, data and analytics can have some bias in it as well. And so I think as we look at the technology aspect of bias, looking at at ethical AI I think is a really important additional area. And I'm sure we could spend another 20 minutes talking about that, but I would be remiss if I didn't talk more about sort of the bias and the opportunity to overcome bias in data and analytics as well. >> Yeah. The opportunity to overcome it is definitely there, you bring up a couple of really good points, Hillary. It starts with awareness. We need to be aware that there are inherent biases in data in thought. And also to your other point, hold people accountable, ourselves, our teammates that's critical to being able to dial that back down. Danielle, I want to get your perspective on your view of women in leadership roles. Do you think that we have good representation or we still have work to do in there? >> I definitely think in both technical and product roles we definitely have some work to do. And when I think about our partnership with Teradata, part of the reason why it's so important is, Teradata solution is really the brains of a lot of companies, what they differentiate on, how they figure out insights into their business. And it's all about the product itself and the data, and the same is true at AWS. And we really could do some work to have some more women in these technical roles as well as in the product, shaping the products, just for all the reasons that we just kind of talked about over the last 10 minutes in order to move bias out of our solutions and also to just build better products and have better outcomes for customers. So I think there's a bit of work to do still. >> I agree. There's definitely a bit of work to do and it's all about delivering those better outcomes for customers at the end of the day. We need to figure out what the right ways are of doing that and working together in a community. We've had obviously a lot had changed in the last couple of years. Hillary, what have you seen in terms of the impact that the pandemic has had on this status of women in tech? Has it been a pro, is silver lining, the opposite? What are you seeing? >> Yeah, I mean, certainly there's data out there that tells us factually that it has been very difficult for women during COVID-19. Women have dropped out of the workforce for a wide range of reasons. And that I think is going to set us back all of us, the Royal us or the Royal we back years and years. And it's very unfortunate because I think we're at a time when we're making great progress and now to see COVID setting us back in such a powerful way I think there's work to be done to understand how do we bring people back into the workforce? How do we do that understanding work life balance better, understanding virtual and remote working better. I think in the technology sector we've really embraced hybrid virtual work and are empowering people to bring their whole selves to work. And I think if anything, these Zoom calls have, both for the men and the women on my team. In fact, I would say much more so for the men on my team, we're seeing more kids in the background, more kind of split childcare duties, more ability to start talking about other responsibilities that maybe they had, especially in the early days of COVID where maybe day cares were shut down and maybe a parent was sick. And so we saw quite a lot of people bringing their whole selves to the office which I think was really wonderful. Even our CEO saw some of that. And I think that that really changes the dialogue. It changes it to maybe scheduling meetings at a time when people can do it after daycare drop off and really allowing that both for men and for women, makes it better for women overall. So I would like to think that this hybrid working environment and that this whole view into somebody's life that COVID has really provided for, probably for white collar workers, if I'm being honest for people who are at a better point of privilege, they don't necessarily have to go into the office every day. I would like to think that tech can lead the way in coming out of the old COVID, I don't know if we have a new COVID coming, but the old COVID and really leading the way for women and for people to transform how we do work, leveraging data and analytics but also overcoming some of the disparities that exist for women in particular in the workforce. >> Yeah, I think there's, like we say, there's a lot of opportunity there and I like your point of hopefully tech can be that guiding light that shows us this can be done. We're all humans at the end of the day. And ultimately, if we're able to have some sort of work life balance, everything benefits. Our work, we're more productive, higher performing teams impacts customers. There's so much value that can be gleaned from that hybrid model and embracing for humans. We need to be able to work when we can. We've learned that you don't have to be in an office 24/7 commuting crazy hours, flying all around the world. We can get a lot of things done in ways that fit people's lives rather than taking command over it. I want to get your advice, Hillary, if you were to talk to your younger self, what would be some of the key pieces of advice you would say? And Danielle and I have talked about this before, and sometimes we would both agree on like, ask more questions, don't be afraid to raise your hand, but what advice would you give your younger self and that younger generation in terms of being inspired to get into tech? >> Oh, inspired in being in tech. I think looking at technology as, in some ways I feel like we do a disservice to inclusion when we talk about STEM, 'cause I think stem can be kind of daunting, it can be a little scary for people, for younger people. When I go and talk to folks at schools, I think STEM is like, oh, all the super smart kids are over there. They're all, like maybe they're all men. And so it's a little intimidating. And STEM is actually, especially for people joining the workforce today, it's actually how you've been living your life since you were born. I mean, you know STEM inside and out because you walk around with a phone and you know how to get your internet working and like that is technology fundamentally. And so demystifying STEM as something that is around how we actually make our our lives useful and how we can change outcomes through technology, I think is maybe a different lens to put on it. And there's absolutely, for hard scientists, there's absolutely a great place in the world for folks who want to pursue that, and men and women can do that. So I don't want to be setting the wrong expectations but I think STEM is very holistic in the change that's happening globally for us today across economies, across global warming, across all kinds of impactful issues. And so I think everybody who's interested in some of that world change can participate in STEM. It just may be through a different lens than how we classically talk about STEM. So I think there's great opportunity to demystify STEM. I think also what I would tell my younger self is choose your bosses wisely. And that sounds really funny. That sounds like inside out almost but I think choose the person that you're going to work for in your first five to seven years. And it might be more than one person, but be selective. Maybe be a little less selective about the exact company or the exact title. I think picking somebody that, we talk about mentors and we talk about sponsors and those are important, but the person you're going to spend in your early career, a lot of your day with, who's going to influence a lot of the outcomes for you. That is the person that you, I think want to be more selective about because that person can set you up for success and give you opportunities and set you on course to be a standout or that person can hold you back and that person can put you in the corner and not invite you to the meetings and not give you those opportunities. And so we're in an economy today where you actually can be a little bit picky about who you go and work for. And I would encourage my younger self, I just lucked out actually, but I think that my first boss really set me up for success, gave me a lot of feedback and coaching. And some of it was really hard to hear but it really set me up for the path that I've been on ever since. So that would be my advice. >> I love that advice. It's brilliant. And I think it, choose your bosses wisely, isn't something that we primarily think about. I think a lot of people think about the big name companies that they want to go after and put on a resume, but you bring up a great point. And Danielle and I have talked about this with other guests about mentors and sponsors. I think that is brilliant advice, and also more work to do to demystify STEM. But luckily we have great female leaders like the two of you helping us to do that. Ladies, I want to thank you so much for joining me on the program today and talking through what you're seeing in DE&I, what your companies are doing and the opportunities that we have to move the needle. Appreciate your time. >> Thank you so much. Great to see you, Danielle. Thank you, Lisa. >> Nice to see you. >> My pleasure. For my guests, I'm Lisa Martin. You're watching the AWS partner showcase season one, episode three. (upbeat music)

Published Date : Jul 18 2022

SUMMARY :

It's great to have you if I can say that in the into some of the initiatives And I think it really to where you are now? and the really cool things I think there's so much value and kind of shift the numbers. that we need to be dangling more of? and and how to program, as some of the harder technical and the opportunity to overcome bias And also to your other point, and the same is true at AWS. that the pandemic has had on and for people to And Danielle and I have and that person can put you in and the opportunities that Great to see you, Danielle. (upbeat music)

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theCUBE on Supercloud | AWS Summit New York 2022


 

welcome back to thecube's live coverage coming to you from the big apple in new york city we're talking all things aws summit but right now i've got two powerhouses you know them you love them john furrier dave vellante going to be talking about super cloud guys we've been talking a lot about this there's a big event coming up on the cube august 9th and i gotta start dave with you because we talk about it pretty much in every interview where it's relevant why super cloud yeah so john furrier years ago started a tradition lisa prior to aws which was to lay down the expectation for our audiences what they should be looking for at aws reinvent okay john when did that start 2012 2013. actually 2013 was our first but 2015 was the first time when we get access to andy jassy who wasn't doing any briefings and we realized that the whole industry started looking at amazon web services as a structural forcing function of massive change uh some say inflection point we were saying complete redefinition so you wrote the trillion dollar baby yeah right which actually turns into probably multi-trillion dollars we got it right on that one surprisingly it was pretty obvious so every year since then john has published the seminal article prior to reinvent so this year we were talking we're coming out of the isolation economy and john hedwig also also adam silevski was the new ceo so we had a one-on-one with adam that's right and then that's where the convergence between andy jassy and adam celebski kicked in which is essentially those guys work together even though they he went off and boomerang back in as they say in aws but what's interesting was is that adam zluski's point of view piggyback jassy but he had a different twist yeah some so you know low you know people who didn't have really a lot of thought into it said oh he's copying microsoft moving up the stack we're like no no no no no something structural is happening again and so john wrote the piece and he started sharing it we're collaborating he said hey dave take a take a look add your perspectives and then jerry chen had just written castles in the cloud and he talked about sub-markets and we were sort of noodling and one of the other things was in 2018 2019 around that time at aws re invent there was this friction between like snowflake and aws because redshift separated compute from storage which was snowflake's whole thing now fast forward to 2021 after we're leaving you know the covert economy by the way everyone was complaining they are asking jassy are you competing with your ecosystem the classic right trope and then in in remember jason used to use cloudera as the example i would like to maybe pick a better example snowflake became that example and what the transition was it went from hey we're kind of competitive for sure there's a lot of examples but it went from we're competitive they're stealing our stuff to you know what we're making so much money building on top of aws specifically but also the clouds and cross clouds so we said there's something new happening in the ecosystem and then just it popped up this term super cloud came up to connote a layer that floats above the hyperscale capex not is it's not pass it's not sas it's the combination of the of those things on top of a new digital infrastructure and we chose the term super cloud we liked it better than multi-cloud because multiplayer at least one other point too i think four or five years earlier dave and i across not just aws reinvent all of our other events we were speculating that there might be a tier two cloud service provider models and we've talked with intel about this and others just kind of like evaluating it staring at it and we met by tier two like maybe competing against amazon but what happened was it wasn't a tier two cloud it was a super cloud built on the capex of aws which means initially was a company didn't have to build aws to be like aws and everybody wanted to be like aws so we saw the emergence of the smart companies saying hey let's refactor our business model in the category or industry scope and to dominate with cloud scale and they did it that then continued that was the premise of chen's post which was kind of rift on the cube initially which is you can have a moat in a castle in the cloud and have a competitive advantage and a sustainable differentiation model and that's exactly what's happening and then you introduce the edge and hybrid you now have a cloud operating model that that super cloud extends as a substrate across all environments so it's not multi-cloud which sounds broken and like put it distance jointed joint barriers hybrid cloud which is the hybrid operating model at scale and you don't have to be amazon to take advantage of all the value creation since they took care of the capex now they win too on the other side because because they're selling ec2 and storage and ml and ai and this is new and this is information that people don't might not know about internally at aws there was a debate dave okay i heard this from sources do we go all in and compete and just own the whole category or open the ecosystem and coexist with [ __ ] why do we have these other companies or snowflake and guess what the decision was let's make it open ecosystem and let's have our own offerings as well and let the winner take off smart because they can't hire enough people and we just had aws and snowflake on the cube a few weeks ago talking about the partnership the co-op petition the value in it but what's been driving it is the voice of the customer but i want to ask you paint the picture for the audience of the critical key components of super cloud what are those yeah so i think first and foremost super cloud as john was saying it's not multi-cloud chuck whitten had a great phrase at dell tech world he said multi-cloud by default right versus multi-cloud by design and multi-cloud has been by default it's been this sort of i run in aws and i run my stack in azure or i run my stack in gcp and it works or i wrap my stack in a container and host it in the cloud that's what multi-cloud has been so the first sort of concept is it's a layer that that abstracts the underlying complexity of all the clouds all the primitives uh it takes advantage of maybe graviton or microsoft tooling hides all that and builds new value on top of that the other piece of of super cloud is it's ecosystem driven really interesting story you just told because literally amazon can't hire everybody right so they have to rely on the ecosystem for feature acceleration so it's it also includes a path layer a super pass layer we call it because you need to develop applications that are specific to the problem that the super cloud is solving so it's not a generic path like openshift it's specific to whether it's snowflake or [ __ ] or aviatrix so that developers can actually build on top of and not have to worry about that underlying and also there's some people that are criticizing um what we're doing in a good way because we want to have an open concept sure but here's the thing that a lot of people don't understand they're criticizing or trying to kind of shoot holes in our new structural change that we're identifying to comparing it to old that's like saying mainframe and mini computers it's like saying well the mainframe does it this way therefore there's no way that's going to be legitimate so the old thinking dave is from people that have no real foresight in the new model right and so they don't really get it right so what i'm saying is that we look at structural change structural change is structural change it either happens or it doesn't so what we're observing is the fact that a snowflake didn't design their solution to be multi-cloud they did it all on aws and then said hey why would we why are we going to stop there let's go to azure because microsoft's got a boatload of customers because they have a vertically stacking integration for their install base so if i'm snowflake why wouldn't i be on azure and the same for gcp and the same for other things so this idea that you can get the value of an amp what amazon did leverage and all that value without paying for it up front is a huge dynamic and that's not just saying oh that's cloud that's saying i have a cloud-like scale cloud-like value proposition which which will look like an ecosystem so to me the acid test is if i build on top of say [ __ ] or say snowflake or super cloud by default i'm either a category leader i own the data at scale or i'm sharing data at scale and i have an ecosystem people are building on top of me so that's a platform so that's really difficult so what's happening is these ecosystem partners are taking advantage as john said of all the hyperscale capex and they're building out their version of a distributed global system and then the other attribute of super cloud is it's got metadata management capability in other words it knows if i'm optimizing for latency where in the super cloud to get the data or how to protect privacy or sovereignty or how many copies to make to have the proper data protection or where the air gap should be for ransomware so these are examples of very specific purpose-built super clouds that are filling gaps that the hyperscalers aren't going after what's a good example of a specific super cloud that you think really articulates what you guys are talking about i think there are a lot of them i think snowflake is a really good example i think vmware is building a multi-cloud management system i think aviatrix and virtual you know private cloud networking and for high performance networking i think to a certain extent what oracle is doing with azure is is is definitely looks like a super cloud i think what capital one is doing by building on to taking their own tools and and and moving that to snowflake now that they're not cross-cloud yet but i predict that they will be of i think uh what veeam is doing in data protection uh dell what they showed at dell tech world with project alpine these are all early examples of super well here's an indicator here's how you look at the example so to me if you're just lifting and shifting that was the first gen cloud that's not changing the business model so i think the number one thing to look at is is the company whether they're in a vertical like insurance or fintech or financial are they refactoring their spend not as an i.t cost but as a refactoring of their business model yes like what snowflake did dave or they say okay i'm gonna change how i operate not change my business model per se or not my business identity if i'm gonna provide financial services i don't have to spend capex it's operating expenses i get the capex leverage i redefine i get the data at scale and now i become a service provider to everybody else because scale will determine the power law of who wins in the verticals and in the industry so we believe that snowflake is a data warehouse in the cloud they call it a data cloud now i don't think snowflake would like that dave i call them a data warehouse no a super data cloud but but so the other key here is you know the old saying that andreessen came up with i guess with every company's a software company well what does that mean it means every company software company every company is going digital well how are they going to do that they're going to do that by taking their business their data their tooling their proprietary you know moat and moving that to the cloud so they can compete at scale every company should be if they're not thinking about doing a super cloud well walmart i think i think andreessen's wrong i think i would revise and say that andreessen and the brain trust at andreas and horowitz is that that's no longer irrelevant every company isn't a software company the software industry is called open source everybody is an open source company and every company will be at super cloud that survives yeah to me to me if you're not looking at super cloud as a strategy to get value and refactor your business model take advantage of what you're paying it for but you're paying now in a new way you're building out value so that's you're either going to be a super cloud or get services from a super cloud so if you're not it's like the old joke dave if you're at the table and you don't know who the sucker is it's probably you right so if you're looking at the marketplace you're saying if i'm not a super cloud i'm probably gonna have to work with one because they're gonna have the data they're gonna have the insights they're gonna have the scale they're going to have the castle in the cloud and they will be called a super cloud so in customer conversations helping customers identify workloads to move to the cloud what are the ideal workloads and services to run in super cloud so i honestly think virtually any workload could be a candidate and i think that it's really the business that they're in that's going to define the workload i'll say what i mean so there's certain businesses where low latency high performance transactions are going to matter that's you know kind of the oracle's business there's certain businesses like snowflake where data sharing is the objective how do i share data in a governed way in a secure way in any location across the world that i can monetize so that's their objective you take a data protection company like veeam their objective is to protect data so they have very specific objectives that ultimately dictate what the workload looks like couchbase is another one they they in my opinion are doing some of the most interesting things at the edge because this is where when you when you really push companies in the cloud including the hyperscalers when they get out to the far edge it starts to get a little squishy couchbase actually is developing capabilities to do that and that's to me that's the big wild card john i think you described it accurately the cloud is expanding you've got public clouds no longer just remote services you're including on-prem and now expanding out to the near edge and the deep what do you call it deep edge or far edge lower sousa called the tiny edge right deep edge well i mean look at look at amazon's outpost announcement to me hp e is opportunity dell has opportunities the hardware box guys companies they have an opportunity to be that gear to be an outpost to be their own output they get better stacks they have better gear they just got to run cloud on it yeah right that's an edge node right so so that's that would be part of the super cloud so this is where i think people that are looking at the old models like operating systems or systems mindsets from the 80s they look they're not understanding the new architecture what i would say to them is yeah i hear what you're saying but the structural change is the nodes on the network distributed computing if you will is going to run hybrid cloud all the way across the fact that it's multiple clouds is just coincidence on who's got the best capex value that people build on for their super cloud capability so why wouldn't i be on azure if microsoft's going to give me all their customers that are running office 365 and teams great if i want to be on amazon's kind of sweet which is their ecosystem why wouldn't i want to tap into that so again you can patch it all together in the super cloud so i think the future will be distributed computing cloud architecture end to end and and we felt that was different from multi-cloud you know if you want to call it multi-cloud 2.0 that's fine but you know frankly you know sometimes we get criticized for not defining it tightly enough but we continue to evolve that definition i've never really seen a great definition from multi-cloud i think multi-cloud by default was the definition i run in multiple clouds you know it works in azure it's not a strategy it's a broken name it's a symptom right it's a symptom of multi-vendor is really what multi-cloud has been and so we felt like it was a new term of examples look what we're talking about snowflake data bricks databricks another good one these are these are examples goldman sachs and we felt like the term immediately connotes something bigger something that sits above the clouds and is part of a digital platform you know the people poo poo the metaverse because it's really you know not well defined but every 15 or 20 years this industry goes through dave let me ask you a question so uh lisa you too if i'm in the insurance vertical uh and i'm a i'm an insurance company i have competitors my customers can go there and and do business with that company and you know and they all know that they go to the same conferences but in that sector now you have new dynamics your i.t spend isn't going to keep the lights on and make your apps work your back-end systems and your mobile app to get your whatever now it's like i have cloud scale so what if i refactored my business model become a super cloud and become the major primary service provider to all the competitors and the people that are the the the channel partners of the of the ecosystem that means that company could change the category totally okay and become the dominant category leader literally in two three years if i'm geico okay i i got business in the cloud because i got the app and i'm doing transactions on geico but with all the data that they're collecting there's adjacent businesses that they can get into maybe they're in the safety business maybe they can sell data to governments maybe they can inform logistics and highway you know patterns roll up all the people that don't have the same scale they have and service them with that data and they get subscription revenue and they can build on top of the geico super insurance cloud right yes it's it's unlimited opportunity that's why it's but the multi-trillion dollar baby so talk to us you've done an amazing job of talking which i know you would of why super cloud what it is the critical components the key workloads great examples talk to us in our last few minutes about the event the cube on super cloud august 9th what's the audience going to who are they going to hear from what are they going to learn yeah so august 9th live out of our palo alto studio we're going to have a program that's going to run from 9 a.m to 1 p.m and we're going to have a number of industry luminaries in there uh kit colbert from from vmware is going to talk about you know their strategy uh benoit de javille uh from snowflake is going to is going to be there of g written house of sky-high security um i i i don't want to give it away but i think steve mullaney is going to come on adrian uh cockroft is coming on the panel keith townsend sanjeev mohan will be on so we'll be running that live and also we'll be bringing in pre-recorded interviews that we'll have prior to the show that will run post the live event it's really a pilot virtual event we want to do a physical event we're thinking but the pilot is to bring our trusted friends together they're credible that have industry experience to try to understand the scope of what we're talking about and open it up and help flesh out the definition make it an open model where we can it's not just our opinion we're observing identifying the structural changes but bringing in smart people our smart friends and companies are saying yeah we get behind this because it has it has legs for a reason so we're gonna zoom out and let people participate and let the conversation and the community drive the content and that is super important to the cube as you know dave but i think that's what's going on lisa is that it's a pilot if it has legs we'll do a physical event certainly we're getting phones to bring it off the hook for sponsors so we don't want to go and go all in on sponsorships right now because it's not about money making it's about getting that super cloud clarity around to help companies yeah we want to evolve the concept and and bring in outside perspectives well the community is one of the best places to do that absolutely organic it's an organic community where i mean people want to find out what's going on with the best practices of how to transform a business and right now digital transformation is not just getting digitized it's taking advantage of the technology to leapfrog the competition so all the successful people we talked to at least have the same common theme i'm changing my game but not changing my game to the customer i'm just going to do it differently better faster cheaper more efficient and have higher margins and beat the competition that's the company doesn't want to beat the competition go to thecube.net if you're not all they're all ready to register for the cube on supercloud august 9th 9am pacific you won't want to miss it for john furrier and dave vellante i'm lisa martin we're all coming at you from new york city at aws summit 22. i'll be right back with our next guest [Music] you

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Javier de la Torre, Carto | AWS Startup Showcase S2 E2


 

(upbeat music) >> Hello, and welcome to theCUBE's presentation of the a AWS startup showcase, data as code is the theme. This is season two episode two of the ongoing series covering the exciting startups from the AWS ecosystem and we talk about data analytics. I'm your old John Furrier with the cube, and we have Javier De La Torre. who's the founder and chief strategy officer of Carto, which is doing some amazing innovation around geographic information systems or GIS. Javier welcome to the cube for this showcase. >> Thank you. Thank you for having me. >> So, you know, one of the things that you guys are bringing to the table is spatial analytic data that now moves into spatial relations, which is, you know, we know about geofencing. You're seeing more data coming from satellites, ground stations, you name it. Things are coming into the market from a data perspective, that's across the board and geo's one of them GIS systems. This is what you guys are doing in the rise of SQL in particular with spatial. This is a huge new benefit to the world. Can you take a minute to explain what Carto's doing and what spatial SQL is? >> Sure. Yeah. So like you said, like data, obviously we know is growing very fast and as you know now, being leveraged by many organizations in many different ways. There's one part of data, one dimension that is location. We like to say that everything happens somewhere. So therefore everything can be analyzed and understood based on the location. So we like to put an example, if all your neighbors get an alarm in their homes, the likelihood that you will get an alarm increases, right? So that's obvious we are all affected by our surroundings. What is spatial analytics, this type of analytics does is try to uncover those spacial relations so that you can model, you can predict where something is going to happen, or, you know, like, or optimize it, you know, like where else you want it to happen, right? So that's at the core of it. Now, this is something that as an industry has been done for many years, like the GIS or geographic information systems have existed for a long time. But now, and this is what Carto really brings to the table. We're looking at really the marketizing it, so that it's in the hands of any analyst, our vision is that you need to go five years, to a geography school to be able to do this type of spatial analysis. And the way that we want to make that happen is what we call with the rise of a spatial SQL. We add these capabilities around spatial analytics based on the language that is very, very popular for a analysts, which is SQL. So what we do is enables you to do this spatial analysis on top of the well known and well used SQL methods. >> It's interesting the cloud native and the cloud scale wave and now data as code has shown that the old school, the old guard, the old way of doing things, you mentioned data warehousing, okay, as one. BI tools in particular have always been limited. And the scope of the limitation was the environment was different. You have to have domain expertise, rich knowledge of the syntax. Usually it's for an application developer, not for like real time and building it into the CICD pipeline, or just from a workflow standpoint, making it available. The so-called democratization, this is where this connects. And so I got to ask you, what are you most excited about in the innovations at Carto? Can you share some of the things that people might know about or might not know about that's happening at Carto, that takes advantage of this cloud native wave because companies are now on this bandwagon. >> Yeah, no, it is. And cloud native analytics is probably the most disruptive kind of like trend that we've seen over the few years, in our particular space on the spatial it has tremendous effects on the way that we provide our service. So I'd like to kind of highlight four main reasons why cloud analytics, cloud native is super important to us. So the first one is obviously is a scalability, the working with the sizes of data that we work now in terms of location was just not possible or before. So for someone that is performing now analysis on autonomous car, or you're like that has any sensorized GPS on a device and is collecting hundreds of billions of points. If you want to do analysis on that type of data, cloud native allows you to do that in a scalable way, but it also is very cost effective. That is something that you'll see very quickly when your data grows a lot, which is that this computing storage separation, the idea that is store your data at cloud prices, but then use them with these data warehouses that we work in this private, makes for a very, very cost effective solution. But then, you know, there is other two, obviously one of them being SQL and spatial SQL that like means we like to say that SQL is becoming the lingua franca for analytics. So it's used by many products that you can connect through the usage of SQL, but I think like you coming towards why I think it's even more interesting it's like, in the cloud the concept like we all are serving, we are all living in the same infrastructure enables us that we can distribute a spatial data sets to a customer that they can join it on their database on SQL without having to move the data from one another, like in the case of Redshift or Amazon Redshift car connects and you using something called a spectrum, we can connect live to data that is stored on S3. And I think that is going to disrupt a lot the way that we think about data distributions and how cost effective it is. I think, it has a lot of your like potential on it. And in that sense what Carto is providing on top of it in the format of formats like parquet, which is a very popular with big data format. We adding geo parquet, we are specializing this big data technology for doing the spatial analysis. And that to me it is very exciting because it's putting some of the best tools at the hands of doing the space analytics for something that we're not able to do before. So to me, this is one area that I'm very, very excited. >> Well, I want to back up for a second. So you mentioned parquet and the standards around that format. And also you mentioned Redshift, so let me get this right. So you just saying that you can connect into Redshift. So I'm a customer and I have Redshift I'm using, I got my S3, I'm using Redshift for analysis. You're saying you can plug right into Redshift. >> Yes. And this is a very, very, very important part because what Carto does is leverage Redshift computing infrastructure to essentially kind of like do all the analysis. So what we do is we bring a spatial analysis where the data is, where Redshift is versus in the past, what we will do is take the data where the analysis was and that sense, it's at the core of cloud native. >> Okay. This is really where I see the exciting shift where data as code now becomes a reality is that you bring the... It redefines architecture, the script is flipped. The architecture has been redefined. You're making the data move to the environments that needs to move when it has to, if it doesn't have to move you bring compute to it. So you're seeing new kinds of use cases. So I have to ask you on the use cases and examples for Carto AWS customers with spatial analytics, what are some of the examples on how your clients are using cloud native spatial analytics or Carto? >> Yeah. So one, for example, that we've seen a lot, on the AWS ecosystem, obviously because of its suites and its position. We work together with another service in the AWS ecosystem called Amazon Location. So that actually provides you access to maps and SDKs for navigation. So it means that you are like a company that is delivering food or any other goods in the city. We have like hundreds or thousands of drivers around the city moving, doing all these deliveries. And each of these drivers they have an app and they're collecting actively their location, their position, right? So you get all the data and then it gets stored on something like a Redshift data cluster on S3 as well. There's different architectures in there, but now you essentially have like a full log of the activity that is happening on the ground from your business. So what Carto does on top of that data is you connect your data into Carto. And now you can do analysis, for example, for finding out where you user may be placed, another distribution center, you know, for optimizing your delivering routes, or like if you're in the restaurant business where you might want to have a new dark kitchen, right? So all this type of analysis based on, since I know where you're doing your operations, I can post analyze the data and then provide you a different way that you can think about solving your operation. So that's an example of a great use case that we're seeing right now. >> Talk to me about about the traditional BI tools out there, because you mentioned earlier, they lack the specific capabilities. You guys bring that to the table. What about the scalability limitations? Can you talk about where that is? Is there limitations there, obviously, if they don't have the capabilities, you can't scale that's one, but you know, as you start plugging into Redshift, scale and performance matters, what's the issue there? Can you unpack that a little bit real quick? >> Yeah. It goes back to the particulars of the spacial data, location data, like in the use case, like I was describing you very quickly are going to end up with really a lot of your like terabytes, if not petabytes of data very quickly, if you're start aggregating all this data, because it gets created by sensors. So volumes in our world kind of tends to grow a lot now. So when you work with BI tools, there's two things that you have to take in consideration. BI tools are great for seeing things like for example, if all you want to see is where your customers are, a BI tool is great. Seeing, creating a map and seeing your customers. That's totally in the world of BI. But if you want to understand why your customers are there, or where else could they be, you're going to need to perform what we call a spatial analysis. You're going to have to create a spatial model. You're going to have to, and for that BI tools will not give you that that's one side, the other it talks about the volumes that I was describing. Most of these BI tools can handle certain aggregations. Like, for example, if you are reading, if you're connecting your, let's say 10 billion data set to a BI tool, the BI tool will do some aggregations because you cannot display 10,000 rows on a BI tool and that's okay, you get aggregations and that works. But when it comes to a map, you cannot aggregate the data on the map. You actually want to see all the data on the map, and that's what Carto provides you. It allows you to make maps that sees all the data, not just aggregated by county or aggregated by other kind of like area, you see all your data on the map. >> You know, what's interesting is that location based service has been around for a long time. You know, when mobile started even hitting the scene, you saw it get better mashups, Google Maps, all this Google API mashups, things like that. You know, developers are used to it, but they could never get to the promised land on the big data side, because they just didn't have the compute. But now you add in geofencing, geo information, you now have access to this new edge like data, right? So I have to ask you on the mobile side, are you guys working with any 5G or edge providers? Because I can almost imagine that the spatial equation gets more complicated and more data full when you start blowing out edge data, like with 5G, you got more, more things happening at the edge. It's only going to fill in more data points. Can you share that's how that use case is going with mobile, mobile carriers or 5G? >> Yeah, that's totally, yeah. It's totally the case. Well, first, even before, you know, like we are there, we actually helping a lot of telcos on actually planning the 5G deployment. Where do you place your antennas is a very, very important topic when you're like talking about 5G. Because you know, like 5G networks require a lot of density. So it's a lot about like, okay, where do I start deploying my infrastructure to ensure the customers like meet, like have the best service and the places where I want to kind of like go first So like... >> You mean like the RF maps, like understanding how RF propagates. >> Well, that's one signal, but the other is like, imagine that your telco is more interested on, you know, let's say on a certain kind of like consumer profile, like young people that are using the one type of service. Well, we know where these demographics kind of lives. So you might want to start kind of like deploying your 5G in those areas, right. Versus if you go to more commercial and more kind of like residential areas, there might be other demographics. So that's one part around market analysis. Then the second part is once these 5G networks are in place, you're right. I mean, one of the premises that kind of like these news technologies give us is because the network is much smarter. You can have all these edge cases, there's much more location data that can be collected. So what we see now is a rise on the amount of what we call telemetry. That for example, the IOT space can make around location. And that's now enabled because of 5G. So I think 5G is going to be one of those trends that are going to make like more and more data coming into, I mean, more location, data available for analysis. >> So how does that, I mean, this is a great conversation because everyone can realize they're at a stadium and they see multiple bars but they can't get bandwidth. So they got a back haul problem or not enough signal. Everyone knows when they're driving their car, they know they can relate to the consumer side of it. So I get how the spatial data grows. What's the impact to Carto and specifically the cloud, because if you have more data coming in, you need the actionable insight. So I can see the use case, oh, put the antenna here. That's an actionable business decision, more content, more revenue, more happy customers, but where else is the impact to you guys and the spatial piece of it? >> Yeah. Well, I mean like there's many, many factors, right? So one of them, for example, on the telco, one of the things where we realize impact is that it gives the visibility to the operator, for example, around the quality of service. Like, okay, are my customers getting the quality of services where I want? Or like you said, like if there sitting outside a concert the quality of service in one particular area is dropping very fast. So the idea of like being able to now in real time, kind of like detect location issues, like I'm having an issue in this place. That means that then now I can act, I can drive up bandwidth, put more capacity et cetera right. So I think the biggest impact that we are seeing we are going to see on the upcoming years is that like more and more use cases going towards real time. So where, like before it was like, well, now that it has happened, I'm going to analyze it. I'm going to look at, you know, like how I could do better next time towards a more of like an industry where Carto ourselves, we are embedded in more real time type of, you know, like analytics where it's okay, if this happens, then do that, right. So it's going to be more personalized at the level that like in the code environment, it has to be art of a full kind of like pipeline kind of like type of analysis. That's already programmatically prepared to act on real time. >> That's great and it's a good segue. My next question, as more and more companies adopt cloud native analytics, what trends are you seeing out of the key to watch? Obviously you're seeing more developers coming on site, on the scene, open sources growing, what's the big cloud native analytics trends for Carto and geographic information. >> Yeah. So I think you know like the, we were talking before the cloud native now is unstoppable, but one of the things that we are seeing that is still needs to be developed and we are seeing progress is around a standardization, for example, around like data sets that are provided by different providers. What I mean with that is like, you as an organization, you're going to be responsible for your data like that you create on your cloud, right. On S3, or, you know and then you going to have a competing engine, like Redshift and you're going to have all that set up, but then you also going to have to think about like, okay, how do I ingest data from third party providers that are important for my analysis? So for example, Carto provides a lot of demographics, human mobility. we aggregate and clean up and prepare lot of spacial data so that we can then enrich your business. So for us, how we deliver that into your cloud native solution is a very important factor. And we haven't seen yet enough standardization around that. And that's one of the things, what we are pushing, you know, with the concept of geo Parquet of standardizing that body. That's one, then there is another, this is more what I like to say that you know, we are helping companies figure out their own geographies. What we mean by that is like most companies, when they start thinking about like how they interact, on the space, on the location, some of them will work like by zip codes and other by cities, they organize their operations based on a geography in a way, or technically what we call a geographic support system. Well, nowadays, like the most advance companies are defining their geographies in a continuous spectrum in what we call global grid system or spatial indexes that allows them to understand the business, not just as a set of regions, but as a continuous space. And that is now possible because of the technologies that we are introducing around spatial indexes at the cloud native infrastructure. And it provides a great a way to match data with resources and operate at scale. To me those two trends are going to be like very, very important because of the capabilities that cloud native brings to our spatial industry. >> So it changes the operation. So it's data as ops, data as code, is data ops, like infrastructures code means cloud DevOps. So I got to ask you because that's cool. Spatial index is a whole another way to think of it, rather than you go hyper local, super local, you get local zones for AWS and regions. Things are getting down to the granular levels I see that. So I have to ask you, what does data as code mean to you and what does it mean to Carto? Because you're kind of teasing at this new way because it's redefining the operation, the data operations, data engineering. So data as code is real. What does that mean to you? >> No, I think we already seeing it happening to me and to Carto what I will describe data as code is when an organization has moved from doing an analysis after the fact, like where they're like post kind of like analysis in a way to where they're actually kind of like putting analytics on their operational cycle. So then they need to really code it. They need to make these analysis, put them and insert them into the architecture bus, if you want to say of the organization. So if I get a customer, happens to be in this location, I'm going to trigger that and then this is going to do that. Or if this happens, I'm need to open up. And this is where if an organization is going to react in more real time, and we know that organizations need to drive in that direction, the only way that they can make that happen is if they operationalize analytics on their daily operations. And that can only happen with data as code. >> Yeah. And that's interesting. Look at ML ops, AI ops, people talk about that. This is data, so developers meets operations, that's the cloud, data meets code that's operations, that's data business. >> You got it. And add to that, the spacial with Carto and we go it. >> Yeah, because every piece of data now is important. And the spatial's key real quick before we close out, what is the index thing? Explain the benefit real quick of a spatial index. >> Yes. So the spatial index is well everybody can understand how we organize societies politically, right? Our countries, you have like states and then you have like counties and you have all these different kind, what we call administrative boundaries, right? That's a way that we organize information too, right? A spatial index is when you divide the world, not in administrative boundaries, but you actually make a grid. Imagine that you just essentially make a grid of the world. right? And you make that grid so that in every cell you can then split it into, let's say for example, four more cells. So you now have like an organization. You split the world in a grid that you can have multiple resolutions think like Google maps when you see the entire world, but you can zoom in and you end up seeing, you know, like one particular place, so that's one thing. So what a spatial indexes allows you is to technically put, you know like your location, not based coordinate, but actually on one grid place on an index. And we use that then later to correlate, let's say your data with someone else data, as we can use what we call this spatial indexes to do joints very, very fast and we can do a lot of operations with it. So it is a new way to do spatial computing based on this type of indexes, but for more than anything for an organization, what spatial index allows is that you don't need to work on zip codes or in boundaries on artificial boundaries. I mean, your customer doesn't change because he goes from this place to the road, to the other side of the road, this is the same place. It's an arbitrary in location. It's a spatial index break out all of that. You're like you break with your zip codes, you break. And you essentially have a continuous geography, that actually is a much closer look up to the reality. >> It's like the forest and the trees and the bark of the tree. (Javier laughing) You can see everything. >> That's it, you can get a look at everything. >> Javi, great to have you on. In real quick closing give a quick plug for the company, summarize what you do, what you're looking into, how many people you got, when you're hiring, what's the key goals for the company? >> Yeah, sure. So Carto is a company, now we are around 200 people. Our vision is that spatial analytics is something that every organization should do. So we really try to enable organizations with the best data and analysis around spatial. And we do all that cloud native on top of your data warehouse. So what we are really in enabling these organizations is to take that cloud native approach that they're already embracing it also to spatial analysis. >> Javi, founder, chief strategy officer for Carto. Great to have you on data as code, all data's real, all data has impact, operational impact with data is the new big trend. Thanks for coming on and sharing the company story and all your key innovations. Thank you. >> Thanks to you. >> Okay. This is the startup showcase. Data as code, season two episode two of the ongoing series. Every episode will explore new topics and new exciting companies pioneering this next cloud native wave of innovation. I'm John Furrier, your host of theCUBE. Thanks for watching. (upbeat music)

Published Date : Apr 26 2022

SUMMARY :

data as code is the theme. Thank you for having me. one of the things that you guys the likelihood that you will shown that the old school, products that you can connect So you just saying that you like do all the analysis. So I have to ask you on the use cases So it means that you are like a company You guys bring that to the table. So when you work with BI tools, So I have to ask you on the mobile side, and the places where I want You mean like the RF maps, on the amount of what we call telemetry. So I can see the use case, I'm going to look at, you know, out of the key to watch? that you create on your cloud, right. So I got to ask you because that's cool. and to Carto what I will operations, that's the cloud, And add to that, the spacial And the spatial's key real is to technically put, you and the bark of the tree. That's it, you can Javi, great to have you on. is to take that cloud native approach Great to have you on data and new exciting companies pioneering

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Javier de la Torre, Carto | CUBE Conversation


 

>>Hey everyone. Welcome to this cube conversation featuring Carto I'm Lisa Martin. And today we're excited to be joined by Javier Delatorre, the founder and chief strategy officer at Carto. We're going to be talking about how Carto is bringing cloud native spatial analysis to the cloud with AWS. How do you are great to have you on the program? Talk to us about cartel. What do you guys do? >>Great. So, uh, part two is a location intelligence platform, but we really use some neighboring organizations to work with location data on the AWS cloud. So essentially enabling organizations to analyze what do they, what should they open new stores? Whereas today probably the new internet, in essence, understanding the locations. I mentioned just helping them to figure out where to do things >>From Carter's perspective. Talk to me about why spatial analysis, location data is important. What power does it give to businesses in any industry? >>Right. I mean, we like to say that everything happens somewhere, right? So we understand that, you know, like the physical world is a very important dimension. So understanding where things happens and the relation within space is a pretty fundamental dimension when it comes to another. I like to put examples of, um, before your neighbors, uh, install alarms in their phones, the likelihood that you will get an alarm is also versus quite a lot. So that's eight years old, says that we are influenced by things that happens around us. And if you can model and understand those spacial relations, you can then look to optimize or predict what is going to happen based on where things are happening. And this is something that we've seen a lot, for example, with the pandemic, but now we're seeing, you know, like many organizations utilizing it for yeah. For finding out where they can find new customers, stores, like say, where did they deploy the new infrastructure? Everything that the ANZ has a spatial component. And that's what is spatial analytics and location intelligence allows you to do? >>Give me some examples of spatial data. And the first thing that pops into my mind is GPS. But I know that there's a lot more than that. >>Uh, GPS has been one of the most important types of data for, so since you know, the inability of GPS and, and with mobile and different sensors are staring at it, we've seen an incredible amount of location data coming into place, but you're right. There's many other types of location data that people tend not to be so aware. I'd say any company that is handling customers, you know, they're likely going to have their addresses. So we have the address of the customer. You have a location already, we'll have, we'll call that the process of geocoding. We transform an address that coordinates, right? But you also have the same, you know, with bees, you have the same, uh, with many different sip codes, it's many different ways that you can represent location. And once you identify those, uh, location bits in your data, then you can start thinking about what type of analysis you can do with them. So it is, like I said, like in many, many places, but definitely the, the rise of, uh, GPS and sensors have been very dramatic. Now we see in also like acute stream of location data coming, for example, from satellites, you know, with all these constellations of satellites, capturing daily images on from earlier, that is also giving us a lot of contextual information. But so it is, you know, mobile phones, when you connect to cell towers, there's many different businesses that are now kind of giving us location data. >>So you alluded to that earlier, a lot more businesses are using location data in their strategies. Talk to me about the acceleration that you seen of that in the last couple of years alone. >>Yeah. So I think one thing that we see in, you know, like massively on the industry obviously is these companies are going through the digital transformation. They are applying analytics to bigger and bigger areas of their, of their, of their business, right. And in a way to showcase, to kind of came as while the last time I mentioned that a lot of organizations started to look at, and over the last few years, we've seen that change in a lot. We've seen it within the many more organized spaces. Now making the questions around where things happens, how does actually matter to my business. So this is celebration, you know, has the sensitive men that many more people are now starting to look at, not only seeing things on a map, like, you know, where my customers are, where my warehouses are, my logistics supply chain, where is it located? >>Now, we're starting to see many more organizations looking at questions about how can I predict where something is going to happen, or how can I optimize my business process so that, um, you know, I, I try to reduce the number of kilometers that I have to drive miles. So, um, I guess it's a mix of the need for sustainability optimizing the business process. And the fact that more and more organizations are starting to do much more deep transformation that now location data has become a much more interesting aspect for many more organizations. So I think all these things together has to make in a way that perfect storm. And now we've seen a lot of the men too, um, for companies that want to go will be John seeing things in a map to understanding why things happen in those spaces. And that's, I think that like, again, a multitude of drivers, you know, that is supposed to in this industry. >>Can you talk about some of the key use cases and maybe some of the vertical industries where you've really seen this takeoff in the last couple of years? >>Yes. And I think he's just in a way, one of the most interesting factors of our industry traditional industries have been on the area around security in the public sector was very much on the military and the, in the, in the, uh, intelligence ecosystem. But now we've seen tremendous adoption on industries like retail, right, where they are lying now consolidating what is their, what is their physical presence? Where do they open stores? You know, like, uh, food chains, what do they open restaurants? And it's a much more analytical process now towards making businesses because, and that involves the usage of location intelligence and space analytics. We do touch one, but we still also like tremendous increase in usage on things like telcos telecommunication. Now with all the deployment of 5g networks, fiber optics, most of those operators require a very good understanding of where you should apply your networks, which, which areas you want to go start first tablet, smart CapEx car, like a strategy. >>So that's telco, I would say it's also has been a tremendous increase. Um, the public secretary is obviously very important, you know, especially, you know, with a lot of the, in a way we all got to master or do you know why geography matters? You know, how to understand your location. Um, and the last one that I would say that it's also connected very much with climate change, transportation and logistics are very, very important factor now. So understanding what is the best strategies for last mile delivery, how to organize your warehouses to better meet your needs. Those are the places that now we're seeing really growing really fast. >>So tremendous amount of use cases, a lot of opportunity there for optimization. How have companies traditionally analyze spatial data and why does that need to change? >>Yeah, so, um, I mean, to a certain extent, I would like to say that there's not been, um, that much use of location data. And that I think is one of the most exciting parts that for many organizations, this is the first time that they're looking at location as a, as a need. I mentioned that they need to understand. So there were, there were several organizations doing already a spatial analytics, but right now it's really, we really see in the expansion of our industry and you're not catching up in, in major, uh, major companies. So those are not like more advanced, you know, we'll have used so-called the traditional GIS systems. GIS is a, is a type of software. That's been existing for many years, but it's only the second used by a very small needs of analysts. You have to go almost four years to school, you know, to become a GIS expert and then do GIS analyst. >>This is right now trending dramatically. And I think, you know, Carter's part of that, uh, transition to necessity, making best patient analysis and GIS part of just the generic general analytics. And I think this is one of the most exciting times that we have, because we've seen the demo by station of his face. And it takes now to imagine why there are, so now we've seen, you know, like analysts that, you know, used to be just to know how to make a map. So things are not with a map, you know, where, where something was happening. Now we starting to see them making much more interesting plastics. So I'm like, okay, if it happens here, where else could they be happened? Right. So that's what I, right now, they, the, the, the huge statements, I'd say, I'd say like many organizations is the first time they go into jail. People like me for being very passionate about the possibilities of really improving processes. I mean, this is super, super exciting time. >>I can definitely feel your passion here through zoom, or talk to me a little bit about how cartel and AWS are helping organizations to embrace the democratization of spatial data and really unlock its super powers. >>Yeah. Well, I mean, obviously, you know, that AWS as the leader on the cloud, in a way that has fundamentally changed the way that we think about like analytics, right? So, um, not only the clouds provide us with the scalability, scalability, affordable the scale of anything. So that's one of the things that, you know, has been incredibly, um, transformative in our industry, uh, with AWS. Now we can do analysis at the scale that wasn't possible before. So that's, that's, that's one thing. So for us, you know, what we've embarked with AWS is rethinking how we can do a spatial analytics in the cloud. We're calling it car to cloud native is providing a full cloud native approach towards performing the spatial analytics, traditional GIS. And for us to utilize this game, even as huge amount of scalability, we use services like Retsef the now with their server last capabilities, we like a, an organization have their data already on that data warehouse on breaths test and using Kartra space. >>now they can do a special ethics directly on the warehouse. This is one of the biggest characteristics of cartel made by being the first cloud data platform. Every computing that we do actually gets pushed down to the warehouse. So the customer is already using the computing engine that they're already, they've been using it for many other things they're paying for already. And they give us scalability. Uh, also very cost-effectiveness this storage competed in separation that the rest of service provides. It makes it very competitive from a call like a cost perspective, and then also is very convenient. So it means that you can use just traditional sequel that are many analysts, know how to use it within the tools that they've been using for many. So I think the participation is essential to read safe, and then also with incorporating the Amazon location services. So we can talk to, and it certainly provides a cloud native it's scalable, affordable, efficient, and much more easy to use solution to performance, space analytics that anything that has been done before. >>It's a tremendous amount of opportunity. It sounds like we're just scratching the surface, but really interesting things that cartoon was doing and how you're enabling organizations in every industry to accelerate the use of spatial data. Javier, thank you so much for joining me on the program today. Fascinating information and best of luck to you. >>Thank you very much >>For Javier Delatorre I'm Lisa Martin. You're watching the cubes stay right here for more coverage of the hybrid tech event world.

Published Date : Mar 23 2022

SUMMARY :

How do you are great to have you on the program? I mentioned just helping them to figure out where to do things Talk to me about why spatial analysis, location data is So we understand that, you know, like the physical world is a very important dimension. And the first thing that pops into my mind is GPS. Uh, GPS has been one of the most important types of data for, so since you know, Talk to me about the acceleration that you seen of that in you know, has the sensitive men that many more people are now starting to look at, not only seeing things a multitude of drivers, you know, that is supposed to in this industry. a very good understanding of where you should apply your networks, Um, the public secretary is obviously very important, you know, especially, So tremendous amount of use cases, a lot of opportunity there for optimization. So those are not like more advanced, you know, we'll have used so-called the traditional GIS So things are not with a map, you know, where, where something was happening. and AWS are helping organizations to embrace the democratization of spatial data and So that's one of the things that, you know, So it means that you can use just traditional sequel that are many analysts, know how to use it Javier, thank you so much for joining me on the program today. of the hybrid tech event world.

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Narelle Bailey, Sandy Carter & Kristen Mirabella | Unstoppable Domains Partner Showcase


 

>>Hi, everyone. Welcome to the cube and unstoppable domain, special showcase women of web three or well, three I'm super excited for this season. We have three great guests, Sandy Carter, the SVP and channel chief of unstoppable domains. Noel Bailey managing director for the entertainment, AKA disco leper. That's her handle NFT handle. We'll talk more about that. And Kristen Mirabella, Bella director of business development, Gemini all in the web three world here for women of web three. Welcome to the show. So what a great announcement, Sandy? What is the wow three women of web three. And why did you announce it on stumbled domains? Web three. >>Awesome. Well, thanks John. So today we are so excited to announce unstoppable women of web three. And one of the things that we noticed ourselves plus 60 plus companies is that we need more diversity in the web three space. So our mission is to make web three more accessible for everyone to help women with that first step and be very action oriented. So we're going to launch education, networking and events as we move forward. And we're real excited to start today, March 8th, we've got a 24 hour Twitter space. We have a YouTube live. We're going to be auction and off some NFTs to donate to girls in tech, a not-for-profit who is also going to launch a mentoring platform for women in web three. We'll also be announcing a hundred inspirational women's and Webster, and I can take up the entire time talking about all we have in store to make web three accessible to everyone. >>That's awesome. We're going to unpack that lot of things to talk about there. I'm really looking forward to it, neural, your, you got a great story here. What are the lazy lions and, and the queen so to speak and what are you guys doing? And tell us about your handle. >>That's a lot of questions there. John, why don't we start with that? So, I mean, I started my NFT journey about six months ago only, and I got really lucky in entering into the space for the lazy lions to start with and the Kings and existing Queens that were kind of in that space to begin were incredibly welcoming. I literally like, I love being the person in the room that asked the dumb question, because if I, if I can ask it, then, you know, there's, there's a hundred other people there that aren't asking that question. And so when I stepped into the, you know, the pride space with Twitter and discord, getting to know the lazy lions before I even got into my first project, they were incredibly welcoming. Like any question that I asked they had an answer for. And so, you know, why we're kind of wondering with unstoppable and supporting that? >>Well, one, once we, once through that space, I got introduced to queen Sandy as well. You know, she's part of the pride and, and one of the lazy lions and again, yeah, it's that whole symbiotic relationship where you've got, you know, Kings and Queens, men and women kind of in the pride, but it's not just about men and women either. It's the diversity aspect where it's people from all different cultures, backgrounds all around the world. And so, you know, getting in and learning and growing together in this brand new space that we're all part of creating. And then Unstoppables a huge part of that with the gateway to allowing people to kind of get into it, to begin. So it just all makes sense. We're going to expense. >>Okay, we're going to unpack that in a minute, but Kristen w what's going on with Gemini and web three, what's going on in the ecosystem there? How are you supporting the women of web three initiative? >>Really excited. Gemini is an exchange and custodian. We offer access to cryptocurrencies. We are your access points. We're the access point for women who are trying to embrace their own financial freedom and build their own story, be economically empowered and interacting with web three in a way that's going to be increasingly necessary. As, as this continues to build, Gemini is really excited to be able to provide a platform for education for anyone and especially women who are looking to build their knowledge base around what's happening in cryptocurrency. How can they interact with it? How can they make really good financial decisions as they look to interact with networks, you know, within defy, what tokens do they want to be able to, you know, purchase, move off of a centralized platform like Geminis. We are very regulated. We're very secure as an access point to be able to interact with cryptocurrencies and use crypto to interact with this ecosystem that's growing. You can, you know, as a woman decide on a really good idea on how you want to embrace that financial freedom of interacting with the protocol that might unlock your potential to be more financially independent, make really good decisions about the future of what your, your family might need economically, you know, in Gemini as an access point for that, as far as crypto and other digital assets go is where we were really proud that we can power that network. >>So we have to chip and I got the lazy lions. You have the unstoppable, all three of you guys are in the middle of all the action and it's super game-changing. It's also a cultural shift. You seeing a lot of young, the young generation, as well as senior experienced people coming in, certainly technologists are coming in, business leaders are coming in and it just feels like a whole nother cultural shift. So we have to ask you, what are you guys most excited for in this roadmap for women of web three what's on your mind? What do you guys see? What's the vision? >>Well, I'll start first. You know, one of the things that I'm really excited about is getting women to experience web three, not just book learning, but really get in there and interact and play with it. So for example, John, there is a game called de-central land. They sell land. And what they're going to help us do is to build a virtual women of web three headquarters inside of the game. And as women go there, they're going to experience, you know, logging in, they're going to experience crypto, like Kristin does talked about they'll experience. NFT is like disco, just talked about. And so it won't just be book smart. They'll be able to get in there and do and see and play, which I think is the best way to learn about web three. >>For me, I'd say, I mean, honestly, I'm most excited about getting it started. There's been so much work kind of going into this to begin with. And, and this space is, is also new and constantly growing and kind of evolving, changing as we go because we're pioneers kind of in this space, really. Like we all have web three. And so getting it started and it continues to grow and evolve from there, which is, you know, a lot to do with kind of community driven initiatives what's happening in the market and the space at the time as well. So super get it started, build it. And it keeps growing from there. >>Christine, what's your vision to what, how do you see this evolving what's what do you hope for and what are some of the things you're excited about? >>I couldn't agree more. What I think is really exciting is that again, if you're looking to learn about this, you know, Sandy you're so right, you're not gonna learn about really how to unlock the potential of this ecosystem by reading about it. You have to get in there, find crypto, come to Geminis platform, open an account, understand what it means to buy cryptocurrency, buy Bitcoin, understand what you're comfortable with. Use resources like our crypto pedia, to understand the differences between tokens, the differences between layers. Why would you buy this token and transfer it off of the platform where you're looking to interact with three, maybe you're looking at these web three applications and you want to understand what generating income through one of these looks like you really got to start with the basics, but start here, purchase something, move it off. You know, test it, use little, little amounts. >>You don't have to buy a full Bitcoin. I think that that's a common misconception with people who are really starting to get interested in the space, especially as they start to learn about cryptocurrency, buy a tiny piece, you know, you don't need to sell the farm, move it off the platform, learn a little bit about how you can interact, build a community around yourself. There are a lot of women who are learning how to do this and through NFTs and through other interests that you might naturally have, you can really embrace the technology and understand what it can do for you. >>You know, you, you mentioned that in the early days of Bitcoin, even a theory of giving it away was a big part of that kind of early days of community. And Earl, you mentioned the word pride as part of the lazy lions community is a big part of this. Sandy, you know, this you've seen communities develop over the years, this new kind of community dynamic is a network effect, but it's also people centric. It's also about reputation. So it's about being open and collaborative. I mean, it sounds like a bunch of cliches jammed together, but this is kind of the world we're in for web three. Can you guys share your thoughts on that and get a reaction to that? >>Yeah. And I just wanted to jump on kind of what Kristin was mentioning there as well. You know, like, and Sandy, like get in there, get started, like have a little taste, have a little of this watch learn and then kind of tying into your community aspect there, ask the questions, get into, and you know, the two, the couple of main spaces, there are discord and Twitter, which, and again, I signed up my Twitter account in 2014 and I pretty much didn't touch it, like from 2015 kind of onwards, like now learning and getting in and growing with this space, that's kind of where the mediums are to start with with that. So yeah. Get in and get started and, and ask the questions on the way >>Sandy, you see Twitter and discord as the primary. >>Yeah. Yeah. There's so many this guy, right. Because you know, I'm on, I'm now on telegram. I'm on disbarred, I'm on Twitter, I'm on signal. I just got invited to signal groups. So this is one of the areas that we need to work on for web three. I think all of us would agree is just that interface. Part of the reason that we're launching this is because it is hard today, right? Web three is hard. And so there's multiple communications channels, you know, and that's why we love, you know, partners like Jim and I, who are making it easier and lazy lions who are setting up these communities. You know, when you buy in it of T you're really not, I guess you are buying the NFT for value, but you're also buying into the community disco. And I have been meeting actually every Saturday night for a while now with the rest of the Queens, planning out women of web three, Kristin and Jim and I, and I have been meeting together it's about the people and the networking and the tribe that you're part of as well. You really nailed it on the community piece. >>You know, ever since we started talking about it unstoppable, I got to say, I've been wanting to get the cube and FTS going because it is a community dynamic, but it's also this got practical usage of is there's data behind it. There's actually real use cases. Can you guys share your thoughts on how you see the use cases being applied specifically to the world, but also to, to women of web three to Wasn't go first. >>Yeah. We're also polite. We're all quite polite. And do you want to go first? You're one of our partners, we'll let you start us off. >>Sorry. I didn't want to and want to jump in there and they want to get started a real applications of, of what this looks like. I think goes back to an idea I had at the top of the call as there's clarity, as that continues to emerge as web three continues to build. And we understand what this really means. I think many would say that there's, you know, lack of clarity around what web three means. Maybe there are some platforms that are slightly more centralized than others. If we think of what web three in general represents, you know, it's this idea of decentralization empowering you through ownership of your data, empowering you through the ability to do things in a decentralized way, but you're not able to do on web two. And I think the real application of transition of where we are today into what this becomes is, you know, I think we keep nailing it on the head. >>You really have to get out there and practice. You have to understand what this transition means for you and what does it mean for what you're trying to achieve? So if my personal stance is, is really solid in where, you know, your financial future is rooted. And if we're talking about cryptocurrency in your ability to interact with these networks, like we've been saying, you have to practice, you have to understand and learn what you're getting yourself into. But I also think there's this element of being okay with making mistakes, but you are talking about your financial future. You're talking about something that's there really high stakes around making mistakes means starting with really good partners. You can start with platforms like Gemini. You can start with platforms like unstoppable domains and know that the foundation has been laid for you to be able to test these grounds. >>I think that what this becomes and what is really important here is knowing that there are going to be a few centralized points that are your access to this web of three, to this broader ecosystem. But being able to trust that these platforms have security in mind. So the security first mindset that empowers you to then go be in charge of data, privacy, being able to take charge of really what your interaction with the rest of this world means. And being, being able to trust that the foundational layer that you're entering that world through is one that can be trusted. I think that as we look at the real world application of this finding that right starting point is really important. >>Yeah. And I w I would just add John to, to what Kristen just said. There are also B2B use cases here. So we want to make sure that, you know, there's a lot of consumer work, but there's also B to B as well. So, you know, imagine you're in decentral land or you're in sandbox a game. If you're a retailer or in a consumer business, you can place your products or your portfolio inside of that game, there is now decentralized finance that's out there. How does that play a role in your company and the way that you're financing for your company? Not just for yourself, like Kristin mentioned, but also for your company. And then dowels, of course, fractional ownership of different things. We're seeing, you know, funding change. SPACs turning into dowels, all of this. If you look at our 24 hour Twitter space, I'm S I can't wait. I think I'm going to actually do a 24 hour bins for myself because >>That's a college come on. We gotta do. >>Right. I know this guy will be with me. Right. And just that last time I did, that was new. Yeah. >>Well, super exciting. I mean, wow, wow. Three could be a doubt. I mean, the vision here is really amazing. I am so impressed. I think this is a great thing because it could go anywhere. What do you guys see at Dow in the future merging communities and merging tribes together? How do you guys have you guys talked about that? What's the, what's the thought process there? >>We actually did talk about doing a Dow. We decided to kick off first and get everybody up to speed on what it was before we jumped into a doubt, which I think is pretty advanced and sophisticated. And so, you know, part of what we also see is if you look at part of the membership, you'll see women of blockchain, women of data BFF. I mean, all these women's groups coming together to unite as long with, along with a lot of major companies, web to companies, Google Deloitte I'll chair, with the who's, who of web three, you've got Gemini, you've got, you know, consensus, you've got blockchain.com. So, you know, I love this because we are coming together for a movement, not for individual companies, but to have an impact on the industry to really educate women. And John, I forgot one of the really cool things we're also announcing today is our first 100 inspirational women of web three. In fact, disco helped me come up with the name of that, because we do want to highlight as examples, all of these great women that are in the space so that we each can reach back and pull others forward. >>Okay, now we've got to get into the, the disco leopard, let's put the lower third up there so we can see it. And the name that's tell us about the story here. And what does it mean to you? Take us through the thought process, the experience and how you envision this unfolding. Cause it's an NFT. You have one it's >>Yeah, totally. I guess. I mean, starting with, so the disco leopard kind of piece to it as well, like in this new space, in the, in the web space, first of all, you get to like, come up with your own identity. So I got to pick this go leopard, like if he doesn't want to be a disco leopard. And so even just coming up with the journey of like, what is your identity with that? And then, you know, you go through that path of being doxed, meaning being revealed, people kind of know who you are or not, or keeping it, you know, kind of a name on the side, that's all. Okay. Like it's all part of that whole decentralized space, which is super exciting. So just so you know, like the disco leper feeds, you know, optimist glass, half full, you know, pessimist, glass, half empty. And then the third piece to that was disco leopard equals. Awesome. And that's where I saw it. And I'm like, that's me a hundred percent. I'm >>Trying to get your lower third, had your name next to it, >>But that's okay. I'm all right with that. I don't mind. So, you know, getting, getting into that to start with, and then, you know, when we were talking about partners and coming into this safe space as well, and yeah, absolutely kind of technology based partners infrastructure to make sure that we're, we're safe and we've got a smooth gateway kind of coming in, but I'm also gonna put communities into partnerships as well, because there are so many NFT projects, you know, defy gaming projects, et cetera, finding your people, finding the community that resonates with you and it's different for everyone. And that's a beautiful thing, but you get to kind of find like-minded people and join them. >>You know, I've been thinking this for about a long, long time, and I thought I was just weird, but now that it's happening, you guys are in the middle of it. The, your identity is so important now, and you could have a community and tribe to belong to, but yet traverse other tribes and move around. This is kind of the whole prospect of unstoppable, right? So Sandy, this is like a great future. You can be protected in a trusted tribe or community, and then still move around to others and engage. It's almost like a packet moving around a network. It's really about people too, on the internet. This is a total complete game changer. It wasn't really, it's not really possible prior to this. >>Yeah. I mean, if you look at all the members, you can move from a metaverse, you can move into gaming, you can go into defy, we've got NFT communities. And, and I love, you know, like you said, traversing, those communities, like we're going to do an auction and we've had donated NFTs. So disco and lazy lions, the queen of lazy lions are donating a lazy lion. Crypto chicks are gonna donate something. If you don't know what these are, these are all NFT communities that have their own identities as well. We have Deadheads NILAH and the long neck ladies, which is started by a 13 year old girl, who's going to talk on one of our Twitter spaces about how she had 13 earned millions of dollars and became times first artist in residence. So there's just, I mean, there's so much potential here and just look at all these amazing women on the screen. You know, I think web three, the face of web three is female. >>That's awesome. Any final thoughts for you guys and, and the session here, it's amazing. First of all, I'm so excited to, to have this conversation and be included and be included into the group here. Thank you for having me closing thoughts on women of web three, how people can get involved, what you guys aspire to be, what are some of the goals can take us through that? >>I guess for me looking at, you kind of asked the question of, you know, what we're most excited about with what's coming up with the international women's day. And, and, you know, what's beyond that. I'm really excited about what unstoppable are doing in introducing the gateway from web two to web three, because that whole 24, the, the events that we have coming on today is, you know, information, education, openness, how to use it, but what's coming beyond there. And it is that transition from web to, and how to, how do we even, like, I'm about to learn that as well. And as I said, I've been in that, in this NMT journey for six months learning thus far, but what does it look like to get into a web three experience and the web page and that design and look and feel so that next step of learning and getting into it. And again, anyone that's kind of being involved in this conversation now you'll be the first people stepping into that space as web three really comes to life. And it is the new web. Very exciting, >>Great. >>I couldn't agree more neural. What I think excites us the most is the level of interest and the level of engagement that we're seeing an unprecedented levels. These and what's coming next is that you're going to see more and more women and more, more people as part of these communities, as we've talked about wanting to learn, wanting to engage and wanting to be part of this and numbers that we really haven't even seen still yet. We've just scratched the surface. And what I want to ask everyone to do is not to wait not to wait until you feel like you're behind. Take action. Now go to our crypto pedia page, open an account at Gemini, start to interact with cryptocurrencies, understand what it means to take, you know, a crypto or digital asset off of a platform and interact with some of these networks, understand what it means to own, and then empty look at unstoppable domains and understand how you can start to dip your toe in. We really want to empower everyone with the knowledge of what you can do here, and we couldn't be more excited about the future >>Also Sandy final word. >>Yes. So I'm excited about a new world where diversity helps shape the next movement. You know, we've seen web one and web two shaped by, you know, homogeneous groups. And what I'm looking forward to is the future, because we know that innovation is driven by diversity of thought. And so for me, I'm really excited about today international women's day, where we're launching all these educational sessions, you know, Kristen mentioned don't wait, get involved, disco, you know, talked a lot about the potential of going from web two to web three. We hope to see tons of women learning from the web to world. And then I just have to say, I mean, if we could get this across in the virtual world, we're then going to also host an in real life I R L event at south by Southwest. So I'm real excited to be back in person to John so that I can actually give my, my fellow colleagues hugs as well. >>I can't wait to be in person. Thank you so much for coming on this. A great program today is international women's day, but every day is women of web three day. Thanks for sharing great insight. I'm looking forward to more conversations and seeing what happens and participating in any way that I can. And thanks for having me and including me in the conversation. Thank you. Thank you. Okay. This is the cubes conversations here in the showcase women of web three. I'm John for your host. Thanks for watching.

Published Date : Mar 8 2022

SUMMARY :

And Kristen Mirabella, Bella director of business development, Gemini all in the web three world here for women of And one of the things that we noticed ourselves plus 60 and the queen so to speak and what are you guys doing? And so when I stepped into the, you know, the pride space with Twitter and discord, getting to know the lazy lions And so, you know, getting in and learning and growing together you know, within defy, what tokens do they want to be able to, you know, You have the unstoppable, all three of you guys are in the middle And as women go there, they're going to experience, you know, logging in, they're going to experience crypto, evolve from there, which is, you know, a lot to do with kind of community driven initiatives what's happening in the to learn about this, you know, Sandy you're so right, you're not gonna learn you know, you don't need to sell the farm, move it off the platform, learn a little bit about how you can interact, And Earl, you mentioned the word pride as part of the lazy lions community and you know, the two, the couple of main spaces, there are discord and Twitter, which, and again, And so there's multiple communications channels, you know, Can you guys share your thoughts on how you see the And do you want to go first? I think many would say that there's, you know, lack of clarity around what web three means. But I also think there's this element of being okay with making mistakes, but you are talking about your financial that empowers you to then go be in charge of data, privacy, being able to take charge So, you know, imagine you're in decentral land or you're in sandbox a game. We gotta do. I know this guy will be with me. How do you guys have you guys talked about that? And so, you know, part of what we also see is if you look at part of the membership, Take us through the thought process, the experience and how you envision this unfolding. like the disco leper feeds, you know, optimist glass, half full, you know, pessimist, you know, getting, getting into that to start with, and then, you know, when we were talking about partners and coming into this safe space you guys are in the middle of it. And, and I love, you know, like you said, traversing, those communities, like we're going on women of web three, how people can get involved, what you guys aspire I guess for me looking at, you kind of asked the question of, to take, you know, a crypto or digital asset off of a platform and interact get involved, disco, you know, talked a lot about the potential This is the cubes conversations here in the showcase women of web three.

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IBM, The Next 3 Years of Life Sciences Innovation


 

>>Welcome to this exclusive discussion. IBM, the next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond. My name is Dave Volante from the Cuban today, we're going to take a deep dive into some of the most important trends impacting the life sciences industry in the next 60 minutes. Yeah, of course. We're going to hear how IBM is utilizing Watson and some really important in life impacting ways, but we'll also bring in real world perspectives from industry and the independent analyst view to better understand how technology and data are changing the nature of precision medicine. Now, the pandemic has created a new reality for everyone, but especially for life sciences companies, one where digital transformation is no longer an option, but a necessity. Now the upside is the events of the past 22 months have presented an accelerated opportunity for innovation technology and real world data are coming together and being applied to support life science, industry trends and improve drug discovery, clinical development, and treatment commercialization throughout the product life cycle cycle. Now I'd like to introduce our esteemed panel. Let me first introduce Lorraine Marshawn, who is general manager of life sciences at IBM Watson health. Lorraine leads the organization dedicated to improving clinical development research, showing greater treatment value in getting treatments to patients faster with differentiated solutions. Welcome Lorraine. Great to see you. >>Dr. Namita LeMay is the research vice-president of IDC, where she leads the life sciences R and D strategy and technology program, which provides research based advisory and consulting services as well as market analysis. The loan to meta thanks for joining us today. And our third panelist is Greg Cunningham. Who's the director of the RWE center of excellence at Eli Lilly and company. Welcome, Greg, you guys are doing some great work. Thanks for being here. Thanks >>Dave. >>Now today's panelists are very passionate about their work. If you'd like to ask them a question, please add it to the chat box located near the bottom of your screen, and we'll do our best to answer them all at the end of the panel. Let's get started. Okay, Greg, and then Lorraine and meta feel free to chime in after one of the game-changers that you're seeing, which are advancing precision medicine. And how do you see this evolving in 2022 and into the next decade? >>I'll give my answer from a life science research perspective. The game changer I see in advancing precision medicine is moving from doing research using kind of a single gene mutation or kind of a single to look at to doing this research using combinations of genes and the potential that this brings is to bring better drug targets forward, but also get the best product to a patient faster. Um, I can give, uh, an example how I see it playing out in the last decade. Non-oncology real-world evidence. We've seen an evolution in precision medicine as we've built out the patient record. Um, as we've done that, uh, the marketplace has evolved rapidly, uh, with, particularly for electronic medical record data and genomic data. And we were pretty happy to get our hands on electronic medical record data in the early days. And then later the genetic test results were combined with this data and we could do research looking at a single mutation leading to better patient outcomes. But I think where we're going to evolve in 2022 and beyond is with genetic testing, growing and oncology, providing us more data about that patient. More genes to look at, uh, researchers can look at groups of genes to analyze, to look at that complex combination of gene mutations. And I think it'll open the door for things like using artificial intelligence to help researchers plow through the complex number of permutations. When you think about all those genes you can look at in combination, right? Lorraine yes. Data and machine intelligence coming together, anything you would add. >>Yeah. Thank you very much. Well, I think that Greg's response really sets us up nicely, particularly when we think about the ability to utilize real-world data in the farm industry across a number of use cases from discovery to development to commercial, and, you know, in particular, I think with real world data and the comments that Greg just made about clinical EMR data linked with genetic or genomic data, a real area of interest in one that, uh, Watson health in particular is focused on the idea of being able to create a data exchange so that we can bring together claims clinical EMR data, genomics data, increasingly wearables and data directly from patients in order to create a digital health record that we like to call an intelligent patient health record that basically gives us the digital equivalent of a real life patient. And these can be used in use cases in randomized controlled clinical trials for synthetic control arms or natural history. They can be used in order to track patients' response to drugs and look at outcomes after they've been on various therapies as, as Greg is speaking to. And so I think that, you know, the promise of data and technology, the AI that we can apply on that is really helping us advance, getting therapies to market faster, with better information, lower sample sizes, and just a much more efficient way to do drug development and to track and monitor outcomes in patients. >>Great. Thank you for that now to meta, when I joined IDC many, many years ago, I really didn't know much about the industry that I was covering, but it's great to see you as a former practitioner now bringing in your views. What do you see as the big game-changers? >>So, um, I would, I would agree with what both Lorraine and Greg said. Um, but one thing that I'd just like to call out is that, you know, everyone's talking about big data, the volume of data is growing. It's growing exponentially actually about, I think 30% of data that exists today is healthcare data. And it's growing at a rate of 36%. That's huge, but then it's not just about the big, it's also about the broad, I think, um, you know, I think great points that, uh, Lorraine and Greg brought out that it's, it's not just specifically genomic data, it's multi omic data. And it's also about things like medical history, social determinants of health, behavioral data. Um, and why, because when you're talking about precision medicine and we know that we moved away from the, the terminology of personalized to position, because you want to talk about disease stratification and you can, it's really about convergence. >>Um, if you look at a recent JAMA paper in 2021, only 1% of EHS actually included genomic data. So you really need to have that ability to look at data holistically and IDC prediction is seeing that investments in AI to fuel in silico, silicone drug discovery will double by 20, 24, but how are you actually going to integrate all the different types of data? Just look at, for example, diabetes, you're on type two diabetes, 40 to 70% of it is genetically inherited and you have over 500 different, uh, genetic low side, which could be involved in playing into causing diabetes. So the earlier strategy, when you are looking at, you know, genetic risk scoring was really single trait. Now it's transitioning to multi rate. And when you say multi trade, you really need to get that integrated view that converging for you to, to be able to drive a precision medicine strategy. So to me, it's a very interesting contrast on one side, you're really trying to make it specific and focused towards an individual. And on the other side, you really have to go wider and bigger as well. >>Uh, great. I mean, the technology is enabling that convergence and the conditions are almost mandating it. Let's talk about some more about data that the data exchange and building an intelligent health record, as it relates to precision medicine, how will the interoperability of real-world data, you know, create that more cohesive picture for the, for the patient maybe Greg, you want to start, or anybody else wants to chime in? >>I think, um, the, the exciting thing from, from my perspective is the potential to gain access to data. You may be weren't aware of an exchange in implies that, uh, some kind of cataloging, so I can see, uh, maybe things that might, I just had no idea and, uh, bringing my own data and maybe linking data. These are concepts that I think are starting to take off in our field, but it, it really opens up those avenues to when you, you were talking about data, the robustness and richness volume isn't, uh, the only thing is Namita said, I think really getting to a rich high-quality data and, and an exchange offers a far bigger, uh, range for all of us to, to use, to get our work done. >>Yeah. And I think, um, just to chime, chime into that, uh, response from Greg, you know, what we hear increasingly, and it's pretty pervasive across the industry right now, because this ability to create an exchange or the intelligent, uh, patient health record, these are new ideas, you know, they're still rather nascent and it always is the operating model. Uh, that, that is the, uh, the difficult challenge here. And certainly that is the case. So we do have data in various silos. Uh, they're in patient claims, they're in electronic medical records, they might be in labs, images, genetic files on your smartphone. And so one of the challenges with this interoperability is being able to tap into these various sources of data, trying to identify quality data, as Greg has said, and the meta is underscoring as well. Uh, we've gotta be able to get to the depth of data that's really meaningful to us, but then we have to have technology that allows us to pull this data together. >>First of all, it has to be de-identified because of security and patient related needs. And then we've gotta be able to link it so that you can create that likeness in terms of the record, it has to be what we call cleaned or curated so that you get the noise and all the missing this out of it, that's a big step. And then it needs to be enriched, which means that the various components that are going to be meaningful, you know, again, are brought together so that you can create that cohort of patients, that individual patient record that now is useful in so many instances across farm, again, from development, all the way through commercial. So the idea of this exchange is to enable that exact process that I just described to have a, a place, a platform where various entities can bring their data in order to have it linked and integrated and cleaned and enriched so that they get something that is a package like a data package that they can actually use. >>And it's easy to plug into their, into their studies or into their use cases. And I think a really important component of this is that it's gotta be a place where various third parties can feel comfortable bringing their data together in order to match it with other third parties. That is a, a real value, uh, that the industry is increasingly saying would be important to them is, is the ability to bring in those third-party data sets and be able to link them and create these, these various data products. So that's really the idea of the data exchange is that you can benefit from accessing data, as Greg mentioned in catalogs that maybe are across these various silos so that you can do the kind of work that you need. And that we take a lot of the hard work out of it. I like to give an example. >>We spoke with one of our clients at one of the large pharma companies. And, uh, I think he expressed it very well. He said, what I'd like to do is have like a complete dataset of lupus. Lupus is an autoimmune condition. And I've just like to have like the quintessential lupus dataset that I can use to run any number of use cases across it. You know, whether it's looking at my phase one trial, whether it's selecting patients and enriching for later stage trials, whether it's understanding patient responses to different therapies as I designed my studies. And so, you know, this idea of adding in therapeutic area indication, specific data sets and being able to create that for the industry in the meta mentioned, being able to do that, for example, in diabetes, that's how pharma clients need to have their needs met is through taking the hard workout, bringing the data together, having it very therapeutically enriched so that they can use it very easily. >>Thank you for that detail and the meta. I mean, you can't do this with humans at scale in technology of all the things that Lorraine was talking about, the enrichment, the provenance, the quality, and of course, it's got to be governed. You've got to protect the privacy privacy humans just can't do all that at massive scale. Can it really tech that's where technology comes in? Doesn't it and automation. >>Absolutely. >>I, couldn't more, I think the biggest, you know, whether you talk about precision medicine or you talk about decentralized trials, I think there's been a lot of hype around these terms, but what is really important to remember is technology is the game changer and bringing all that data together is really going to be the key enabler. So multimodal data integration, looking at things like security or federated learning, or also when you're talking about leveraging AI, you're not talking about things like bias or other aspects around that are, are critical components that need to be addressed. I think the industry is, uh, it's partly, still trying to figure out the right use cases. So it's one part is getting together the data, but also getting together the right data. Um, I think data interoperability is going to be the absolute game changer for enabling this. Uh, but yes, um, absolutely. I can, I can really couldn't agree more with what Lorraine just said, that it's bringing all those different aspects of data together to really drive that precision medicine strategy. >>Excellent. Hey Greg, let's talk about protocols decentralized clinical trials. You know, they're not new to life silences, but, but the adoption of DCTs is of course sped up due to the pandemic we've had to make trade-offs obviously, and the risk is clearly worth it, but you're going to continue to be a primary approach as we enter 2022. What are the opportunities that you see to improve? How DCTs are designed and executed? >>I see a couple opportunities to improve in this area. The first is, uh, back to technology. The infrastructure around clinical trials has, has evolved over the years. Uh, but now you're talking about moving away from kind of site focus to the patient focus. Uh, so with that, you have to build out a new set of tools that would help. So for example, one would be novel trial, recruitment, and screening, you know, how do you, how do you find patients and how do you screen them to see if are they, are they really a fit for, for this protocol? Another example, uh, very important documents that we have to get is, uh, you know, the e-consent that someone's says, yes, I'm, well, I understand this study and I'm willing to do it, have to do that in a more remote way than, than we've done in the past. >>Um, the exciting area, I think, is the use of, uh, eco, uh, E-Pro where we capture data from the patient using apps, devices, sensors. And I think all of these capabilities will bring a new way of, of getting data faster, uh, in, in this kind of model. But the exciting thing from, uh, our perspective at Lily is it's going to bring more data about the patient from the patient, not just from the healthcare provider side, it's going to bring real data from these apps, devices and sensors. The second thing I think is using real-world data to identify patients, to also improve protocols. We run scenarios today, looking at what's the impact. If you change a cut point on a, a lab or a biomarker to see how that would affect, uh, potential enrollment of patients. So it, it definitely the real-world data can be used to, to make decisions, you know, how you improve these protocols. >>But the thing that we've been at the challenge we've been after that this probably offers the biggest is using real-world data to identify patients as we move away from large academic centers that we've used for years as our sites. Um, you can maybe get more patients who are from the rural areas of our countries or not near these large, uh, uh, academic centers. And we think it'll bring a little more diversity to the population, uh, who who's, uh, eligible, but also we have their data, so we can see if they really fit the criteria and the probability they are a fit for the trial is much higher than >>Right. Lorraine. I mean, your clients must be really pushing you to help them improve DCTs what are you seeing in the field? >>Yes, in fact, we just attended the inaugural meeting of the de-central trials research Alliance in, uh, in Boston about two weeks ago where, uh, all of the industry came together, pharma companies, uh, consulting vendors, just everyone who's been in this industry working to help define de-central trials and, um, think through what its potential is. Think through various models in order to enable it, because again, a nascent concept that I think COVID has spurred into action. Um, but it is important to take a look at the definition of DCT. I think there are those entities that describe it as accessing data directly from the patient. I think that is a component of it, but I think it's much broader than that. To me, it's about really looking at workflows and processes of bringing data in from various remote locations and enabling the whole ecosystem to work much more effectively along the data continuum. >>So a DCT is all around being able to make a site more effective, whether it's being able to administer a tele visit or the way that they're getting data into the electronic data captures. So I think we have to take a look at the, the workflows and the operating models for enabling de-central trials and a lot of what we're doing with our own technology. Greg mentioned the idea of electronic consent of being able to do electronic patient reported outcomes, other collection of data directly from the patient wearables tele-health. So these are all data acquisition, methodologies, and technologies that, that we are enabling in order to get the best of the data into the electronic data capture system. So edit can be put together and processed and submitted to the FDA for regulatory use for clinical trial type submission. So we're working on that. I think the other thing that's happening is the ability to be much more flexible and be able to have more cloud-based storage allows you to be much more inter-operable to allow API APIs in order to bring in the various types of data. >>So we're really looking at technology that can make us much more fluid and flexible and accommodating to all the ways that people live and work and manage their health, because we have to reflect that in the way we collect those data types. So that's a lot of what we're, what we're focused on. And in talking with our clients, we spend also a lot of time trying to understand along the, let's say de-central clinical trials continuum, you know, w where are they? And I know Namita is going to talk a little bit about research that they've done in terms of that adoption curve, but because COVID sort of forced us into being able to collect data in more remote fashion in order to allow some of these clinical trials to continue during COVID when a lot of them had to stop. What we want to make sure is that we understand and can codify some of those best practices and that we can help our clients enable that because the worst thing that would happen would be to have made some of that progress in that direction. >>But then when COVID is over to go back to the old ways of doing things and not bring some of those best practices forward, and we actually hear from some of our clients in the pharma industry, that they worry about that as well, because we don't yet have a system for operationalizing a de-central trial. And so we really have to think about the protocol it's designed, the indication, the types of patients, what makes sense to decentralize, what makes sense to still continue to collect data in a more traditional fashion. So we're spending a lot of time advising and consulting with our patients, as well as, I mean, with our clients, as well as CRS, um, on what the best model is in terms of their, their portfolio of studies. And I think that's a really important aspect of trying to accelerate the adoption is making sure that what we're doing is fit for purpose, just because you can use technology doesn't mean you should, it really still does require human beings to think about the problem and solve them in a very practical way. >>Great, thank you for that. Lorraine. I want to pick up on some things that Lorraine was just saying. And then back to what Greg was saying about, uh, uh, DCTs becoming more patient centric, you had a prediction or IDC, did I presume your fingerprints were on it? Uh, that by 20 25, 70 5% of trials will be patient-centric decentralized clinical trials, 90% will be hybrid. So maybe you could help us understand that relationship and what types of innovations are going to be needed to support that evolution of DCT. >>Thanks, Dave. Yeah. Um, you know, sorry, I, I certainly believe that, uh, you know, uh, Lorraine was pointing out of bringing up a very important point. It's about being able to continue what you have learned in over the past two years, I feel this, you know, it was not really a digital revolution. It was an attitude. The revolution that this industry underwent, um, technology existed just as clinical trials exist as drugs exist, but there was a proof of concept that technology works that this model is working. So I think that what, for example, telehealth, um, did for, for healthcare, you know, transition from, from care, anywhere care, anytime, anywhere, and even becoming predictive. That's what the decentralized clinical trials model is doing for clinical trials today. Great points again, that you have to really look at where it's being applied. You just can't randomly apply it across clinical trials. >>And this is where the industry is maturing the complexity. Um, you know, some people think decentralized trials are very simple. You just go and implement these centralized clinical trials, but it's not that simple as it it's being able to define, which are the right technologies for that specific, um, therapeutic area for that specific phase of the study. It's being also a very important point is bringing in the patient's voice into the process. Hey, I had my first telehealth visit sometime last year and I was absolutely thrilled about it. I said, no time wasted. I mean, everything's done in half an hour, but not all patients want that. Some want to consider going back and you, again, need to customize your de-centralized trials model to, to the, to the type of patient population, the demographics that you're dealing with. So there are multiple factors. Um, also stepping back, you know, Lorraine mentioned they're consulting with, uh, with their clients, advising them. >>And I think a lot of, um, a lot of companies are still evolving in their maturity in DCTs though. There's a lot of boys about it. Not everyone is very mature in it. So it's, I think it, one thing everyone's kind of agreeing with is yes, we want to do it, but it's really about how do we go about it? How do we make this a flexible and scalable modern model? How do we integrate the patient's voice into the process? What are the KPIs that we define the key performance indicators that we define? Do we have a playbook to implement this model to make it a scalable model? And, you know, finally, I think what organizations really need to look at is kind of developing a de-centralized mature maturity scoring model, so that I assess where I am today and use that playbook to define, how am I going to move down the line to me reach the next level of maturity. Those were some of my thoughts. Right? >>Excellent. And now remember you, if you have any questions, use the chat box below to submit those questions. We have some questions coming in from the audience. >>At one point to that, I think one common thread between the earlier discussion around precision medicine and around decentralized trials really is data interoperability. It is going to be a big game changer to, to enable both of these pieces. Sorry. Thanks, Dave. >>Yeah. Thank you. Yeah. So again, put your questions in the chat box. I'm actually going to go to one of the questions from the audience. I get some other questions as well, but when you think about all the new data types that are coming in from social media, omics wearables. So the question is with greater access to these new types of data, what trends are you seeing from pharma device as far as developing capabilities to effectively manage and analyze these novel data types? Is there anything that you guys are seeing, um, that you can share in terms of best practice or advice >>I'll offer up? One thing, I think the interoperability isn't quite there today. So, so what's that mean you can take some of those data sources. You mentioned, uh, some Omix data with, uh, some health claims data and it's the, we spend too much time and in our space putting data to gather the behind the scenes, I think the stat is 80% of the time is assembling the data 20% analyzing. And we've had conversations here at Lilly about how do we get to 80% of the time is doing analysis. And it really requires us to think, take a step back and think about when you create a, uh, a health record, you really have to be, have the same plugins so that, you know, data can be put together very easily, like Lorraine mentioned earlier. And that comes back to investing in as an industry and standards so that, you know, you have some of data standard, we all can agree upon. And then those plugs get a lot easier and we can spend our time figuring out how to make, uh, people's lives better with healthcare analysis versus putting data together, which is not a lot of fun behind the scenes. >>Other thoughts on, um, on, on how to take advantage of sort of novel data coming from things like devices in the nose that you guys are seeing. >>I could jump in there on your end. Did you want to go ahead? Okay. So, uh, I mean, I think there's huge value that's being seen, uh, in leveraging those multiple data types. I think one area you're seeing is the growth of prescription digital therapeutics and, um, using those to support, uh, you know, things like behavioral health issues and a lot of other critical conditions it's really taking you again, it is interlinking real-world data cause it's really taking you to the patient's home. Um, and it's, it's, there's a lot of patients in the city out here cause you can really monitor the patient real-time um, without the patient having coming, you know, coming and doing a site visit once in say four weeks or six weeks. So, um, I, and, uh, for example, uh, suicidal behavior and just to take an example, if you can predict well in advance, based on those behavioral parameters, that this is likely to trigger that, uh, the value of it is enormous. Um, again, I think, uh, Greg made a valid point about the industry still trying to deal with resolving the data interoperability issue. And there are so many players that are coming in the industry right now. There are really few that have the maturity and the capability to address these challenges and provide intelligence solutions. >>Yeah. Maybe I'll just, uh, go ahead and, uh, and chime into Nikita's last comment there. I think that's what we're seeing as well. And it's very common, you know, from an innovation standpoint that you have, uh, a nascent industry or a nascent innovation sort of situation that we have right now where it's very fragmented. You have a lot of small players, you have some larger entrenched players that have the capability, um, to help to solve the interoperability challenge, the standards challenge. I mean, I think IBM Watson health is certainly one of the entities that has that ability and is taking a stand in the industry, uh, in order to, to help lead in that way. Others are too. And, uh, but with, with all of the small companies that are trying to find interesting and creative ways to gather that data, it does create a very fragmented, uh, type of environment and ecosystem that we're in. >>And I think as we mature, as we do come forward with the KPIs, the operating models, um, because you know, the devil's in the detail in terms of the operating models, it's really exciting to talk these trends and think about the future state. But as Greg pointed out, if you're spending 80% of your time just under the hood, you know, trying to get the engine, all the spark plugs to line up, um, that's, that's just hard grunt work that has to be done. So I think that's where we need to be focused. And I think bringing all the data in from these disparate tools, you know, that's fine, we need, uh, a platform or the API APIs that can enable that. But I think as we, as we progress, we'll see more consolidation, uh, more standards coming into play, solving the interoperability types of challenges. >>And, um, so I think that's where we should, we should focus on what it's going to take and in three years to really codify this and make it, so it's a, it's a well hum humming machine. And, you know, I do know having also been in pharma that, uh, there's a very pilot oriented approach to this thing, which I think is really healthy. I think large pharma companies tend to place a lot of bets with different programs on different tools and technologies, to some extent to see what's gonna stick and, you know, kind of with an innovation mindset. And I think that's good. I think that's kind of part of the process of figuring out what is going to work and, and helping us when we get to that point of consolidating our model and the technologies going forward. So I think all of the efforts today are definitely driving us to something that feels much more codified in the next three to five years. >>Excellent. We have another question from the audience it's sort of related to the theme of this discussion, given the FDA's recent guidance on using claims and electronic health records, data to support regulatory decision-making what advancements do you think we can expect with regards to regulatory use of real-world data in the coming years? It's kind of a two-parter so maybe you guys can collaborate on this one. What role that, and then what role do you think industry plays in influencing innovation within the regulatory space? >>All right. Well, it looks like you've stumped the panel there. Uh, Dave, >>It's okay to take some time to think about it, right? You want me to repeat it? You guys, >>I, you know, I I'm sure that the group is going to chime into this. I, so the FDA has issued a guidance. Um, it's just, it's, it's exactly that the FDA issues guidances and says that, you know, it's aware and supportive of the fact that we need to be using real-world data. We need to create the interoperability, the standards, the ways to make sure that we can include it in regulatory submissions and the like, um, and, and I sort of think about it akin to the critical path initiative, probably, I don't know, 10 or 12 years ago in pharma, uh, when the FDA also embrace this idea of the critical path and being able to allow more in silico modeling of clinical trial, design and development. And it really took the industry a good 10 years, um, you know, before they were able to actually adopt and apply and take that sort of guidance or openness from the FDA and actually apply it in a way that started to influence the way clinical trials were designed or the in silico modeling. >>So I think the second part of the question is really important because while I think the FDA is saying, yes, we recognize it's important. Uh, we want to be able to encourage and support it. You know, when you look for example, at synthetic control arms, right? The use of real-world data in regulatory submissions over the last five or six years, all of the use cases have been in oncology. I think there've been about maybe somewhere between eight to 10 submissions. And I think only one actually was a successful submission, uh, in all those situations, the real-world data arm of that oncology trial that synthetic control arm was actually rejected by the FDA because of lack of completeness or, you know, equalness in terms of the data. So the FDA is not going to tell us how to do this. So I think the second part of the question, which is what's the role of industry, it's absolutely on industry in order to figure out exactly what we're talking about, how do we figure out the interoperability, how do we apply the standards? >>How do we ensure good quality data? How do we enrich it and create the cohort that is going to be equivalent to the patient in the real world, uh, in the end that would otherwise be in the clinical trial and how do we create something that the FDA can agree with? And we'll certainly we'll want to work with the FDA in order to figure out this model. And I think companies are already doing that, but I think that the onus is going to be on industry in order to figure out how you actually operationalize this and make it real. >>Excellent. Thank you. Um, question on what's the most common misconception that clinical research stakeholders with sites or participants, et cetera might have about DCTs? >>Um, I could jump in there. Right. So, sure. So, um, I think in terms of misconceptions, um, I think the communist misconceptions that sites are going away forever, which I do not think is really happening today. Then the second, second part of it is that, um, I think also the perspective that patients are potentially neglected because they're moving away. So we'll pay when I, when I, what I mean by that neglected, perhaps it was not the appropriate term, but the fact that, uh, will patients will, will, will patient engagement continue, will retention be strong since the patients are not interacting in person with the investigator quite as much. Um, so site retention and patient retention or engagement from both perspectives, I think remains a concern. Um, but actually if you look at, uh, look at, uh, assessments that have been done, I think patients are more than happy. >>Majority of the patients have been really happy about, about the new model. And in fact, sites are, seem to increase, have increased investments in technology by 50% to support this kind of a model. So, and the last thing is that, you know, decentralized trials is a great model and it can be applied to every possible clinical trial. And in another couple of weeks, the whole industry will be implementing only decentralized trials. I think we are far away from that. It's just not something that you would implement across every trial. And we discussed that already. So you have to find the right use cases for that. So I think those were some of the key misconceptions I'd say in the industry right now. Yeah. >>Yeah. And I would add that the misconception I hear the most about is, uh, the, the similar to what Namita said about the sites and healthcare professionals, not being involved to the level that they are today. Uh, when I mentioned earlier in our conversation about being excited about capturing more data, uh, from the patient that was always in context of, in addition to, you know, healthcare professional opinion, because I think both of them bring that enrichment and a broader perspective of that patient experience, whatever disease they're faced with. So I, I think some people think is just an all internet trial with just someone, uh, putting out there their own perspective. And, and it's, it's a combination of both to, to deliver a robust data set. >>Yeah. Maybe I'll just comment on, it reminds me of probably 10 or 15 years ago, maybe even more when, um, really remote monitoring was enabled, right? So you didn't have to have the study coordinator traveled to the investigative site in order to check the temperature of the freezer and make sure that patient records were being completed appropriately because they could have a remote visit and they could, they could send the data in a via electronic data and do the monitoring visit, you know, in real time, just the way we're having this kind of communication here. And there was just so much fear that you were going to replace or supplant the personal relationship between the sites between the study coordinators that you were going to, you know, have to supplant the role of the monitor, which was always a very important role in clinical trials. >>And I think people that really want to do embrace the technology and the advantages that it provided quickly saw that what it allowed was the monitor to do higher value work, you know, instead of going in and checking the temperature on a freezer, when they did have their visit, they were able to sit and have a quality discussion for example, about how patient recruitment was going or what was coming up in terms of the consent. And so it created a much more high touch, high quality type of interaction between the monitor and the investigative site. And I think we should be looking for the same advantages from DCT. We shouldn't fear it. We shouldn't think that it's going to supplant the site or the investigator or the relationship. It's our job to figure out where the technology fits and clinical sciences always got to be high touch combined with high-tech, but the high touch has to lead. And so getting that balance right? And so that's going to happen here as well. We will figure out other high value work, meaningful work for the site staff to do while they let the technology take care of the lower quality work, if you will, or the lower value work, >>That's not an, or it's an, and, and you're talking about the higher value work. And it, it leads me to something that Greg said earlier about the 80, 20, 80% is assembly. 20% is actually doing the analysis and that's not unique to, to, to life sciences, but, but sort of question is it's an organizational question in terms of how we think about data and how we approach data in the future. So Bamyan historically big data in life sciences in any industry really is required highly centralized and specialized teams to do things that the rain was talking about, the enrichment, the provenance, the data quality, the governance, the PR highly hyper specialized teams to do that. And they serve different constituencies. You know, not necessarily with that, with, with context, they're just kind of data people. Um, so they have responsibility for doing all those things. Greg, for instance, within literally, are you seeing a move to, to, to democratize data access? We've talked about data interoperability, part of that state of sharing, um, that kind of breaks that centralized hold, or is that just too far in the future? It's too risky in this industry? >>Uh, it's actually happening now. Uh, it's a great point. We, we try to classify what people can do. And, uh, the example would be you give someone who's less analytically qualified, uh, give them a dashboard, let them interact with the data, let them better understand, uh, what, what we're seeing out in the real world. Uh, there's a middle user, someone who you could give them, they can do some analysis with the tool. And the nice thing with that is you have some guardrails around that and you keep them in their lane, but it allows them to do some of their work without having to go ask those centralized experts that, that you mentioned their precious resources. And that's the third group is those, uh, highly analytical folks that can, can really deliver, uh, just value beyond. But when they're doing all those other things, uh, it really hinders them from doing what we've been talking about is the high value stuff. So we've, we've kind of split into those. We look at people using data in one of those three lanes and it, and it has helped I think, uh, us better not try to make a one fit solution for, for how we deliver data and analytic tools for people. Right. >>Okay. I mean, DCT hot topic with the, the, the audience here. Another question, um, what capabilities do sponsors and CRS need to develop in-house to pivot toward DCT? >>Should I jump in here? Yeah, I mean, um, I think, you know, when, when we speak about DCTs and when I speak with, uh, folks around in the industry, I, it takes me back to the days of risk-based monitoring. When it was first being implemented, it was a huge organizational change from the conventional monitoring models to centralize monitoring and risk-based monitoring, it needs a mental reset. It needs as Lorraine had pointed out a little while ago, restructuring workflows, re redefining processes. And I think that is one big piece. That is, I think the first piece, when, you know, when you're implementing a new model, I think organizational change management is a big piece of it because you are disturbing existing structures, existing methods. So getting that buy-in across the organization towards the new model, seeing what the value add in it. And where do you personally fit into that story? >>How do your workflows change, or how was your role impacted? I think without that this industry will struggle. So I see organizations, I think, first trying to work on that piece to build that in. And then of course, I also want to step back for the second to the, uh, to the point that you brought out about data democratization. And I think Greg Greg gave an excellent point, uh, input about how it's happening in the industry. But I would also say that the data democratization really empowerment of, of, of the stakeholders also includes the sites, the investigators. So what is the level of access to data that you know, that they have now, and is it, uh, as well as patients? So see increasingly more and more companies trying to provide access to patients finally, it's their data. So why shouldn't they have some insights to it, right. So access to patients and, uh, you know, the 80, 20 part of it. Uh, yes, he's absolutely right that, uh, we want to see that flip from, uh, 20%, um, you know, focusing on, on actually integrating the data 80% of analytics, but the real future will be coming in when actually the 20 and 18 has gone. And you actually have analysts the insights out on a silver platter. That's kind of wishful thinking, some of the industries is getting there in small pieces, but yeah, then that's just why I should, why we share >>Great points. >>And I think that we're, we're there in terms that like, I really appreciate the point around democratizing the data and giving the patient access ownership and control over their own data. I mean, you know, we see the health portals that are now available for patients to view their own records, images, and labs, and claims and EMR. We have blockchain technology, which is really critical here in terms of the patient, being able to pull all of their own data together, you know, in the blockchain and immutable record that they can own and control if they want to use that to transact clinical trial types of opportunities based on their data, they can, or other real world scenarios. But if they want to just manage their own data because they're traveling and if they're in a risky health situation, they've got their own record of their health, their health history, uh, which can avoid, you know, medical errors occurring. So, you know, even going beyond life sciences, I think this idea of democratizing data is just good for health. It's just good for people. And we definitely have the technology that can make it a reality. Now >>You're here. We have just about 10 minutes left and now of course, now all the questions are rolling in like crazy from the crowd. Would it be curious to know if there would be any comments from the panel on cost comparison analysis between traditional clinical trials in DCTs and how could the outcome effect the implementation of DCTs any sort of high-level framework you can share? >>I would say these are still early days to, to drive that analysis because I think many companies are, um, are still in the early stages of implementation. They've done a couple of trials. The other part of it that's important to keep in mind is, um, is for organizations it's, they're at a stage of, uh, of being on the learning curve. So when you're, you're calculating the cost efficiencies, if ideally you should have had two stakeholders involved, you could have potentially 20 stakeholders involved because everyone's trying to learn the process and see how it's going to be implemented. So, um, I don't think, and the third part of it, I think is organizations are still defining their KPIs. How do you measure it? What do you measure? So, um, and even still plugging in the pieces of technology that they need to fit in, who are they partnering with? >>What are the pieces of technology they're implementing? So I don't think there is a clear cut as answered at this stage. I think as you scale this model, the efficiencies will be seen. It's like any new technology or any new solution that's implemented in the first stages. It's always a little more complex and in fact sometimes costs extra. But as, as you start scaling it, as you establish your workflows, as you streamline it, the cost efficiencies will start becoming evident. That's why the industry is moving there. And I think that's how it turned out on the long run. >>Yeah. Just make it maybe out a comment. If you don't mind, the clinical trials are, have traditionally been costed are budgeted is on a per patient basis. And so, you know, based on the difficulty of the therapeutic area to recruit a rare oncology or neuromuscular disease, there's an average that it costs in order to find that patient and then execute the various procedures throughout the clinical trial on that patient. And so the difficulty of reaching the patient and then the complexity of the trial has led to what we might call a per patient stipend, which is just the metric that we use to sort of figure out what the average cost of a trial will be. So I think to point, we're going to have to see where the ability to adjust workflows, get to patients faster, collect data more easily in order to make the burden on the site, less onerous. I think once we start to see that work eases up because of technology, then I think we'll start to see those cost equations change. But I think right now the system isn't designed in order to really measure the economic benefit of de-central models. And I think we're going to have to sort of figure out what that looks like as we go along and since it's patient oriented right now, we'll have to say, well, you know, how does that work, ease up? And to those costs actually come down and then >>Just scale, it's going to be more, more clear as the media was saying, next question from the audiences, it's kind of a best fit question. You all have touched on this, but let me just ask it is what examples in which, in which phases suit DCT in its current form, be it fully DCT or hybrid models, none of our horses for courses question. >>Well, I think it's kind of, uh, it's, it's it's has its efficiencies, obviously on the later phases, then the absolute early phase trials, those are not the ideal models for DCTs I would say so. And again, the logic is also the fact that, you know, when you're, you're going into the later phase trials, the volume of number of patients is increasing considerably to the point that Lorraine brought up about access to the patients about patient selection. The fact, I think what one should look at is really the advantages that it brings in, in terms of, you know, patient access in terms of patient diversity, which is a big piece that, um, the cities are enabling. So, um, if you, if, if you, if you look at the spectrum of, of these advantages and, and just to step back for a moment, if you, if you're looking at costs, like you're looking at things like remote site monitoring, um, is, is a big, big plus, right? >>I mean, uh, site monitoring alone accounts for around a third of the trial costs. So there are so many pieces that fall in together. The challenge actually that comes when you're in defining DCTs and there are, as Rick pointed out multiple definitions of DCTs that are existing, uh, you know, in the industry right now, whether you're talking of what Detroit is doing, or you're talking about acro or Citi or others. But the point is it's a continuum, it's a continuum of different pieces that have been woven together. And so how do you decide which pieces you're plugging in and how does that impact the total cost or the solution that you're implementing? >>Great, thank you. Last question we have in the audience, excuse me. What changes have you seen? Are there others that you can share from the FDA EU APAC, regulators and supporting DCTs precision medicine for approval processes, anything you guys would highlight that we should be aware of? >>Um, I could quickly just add that. I think, um, I'm just publishing a report on de-centralized clinical trials should be published shortly, uh, perspective on that. But I would say that right now, um, there, there was a, in the FDA agenda, there was a plan for a decentralized clinical trials guidance, as far as I'm aware, one has not yet been published. There have been significant guidances that have been published both by email and by, uh, the FDA that, um, you know, around the implementation of clinical trials during the COVID pandemic, which incorporate various technology pieces, which support the DCD model. Um, but I, and again, I think one of the reasons why it's not easy to publish a well-defined guidance on that is because there are so many moving pieces in it. I think it's the Danish, uh, regulatory agency, which has per se published a guidance and revised it as well on decentralized clinical trials. >>Right. Okay. Uh, we're pretty much out of time, but I, I wonder Lorraine, if you could give us some, some final thoughts and bring us home things that we should be watching or how you see the future. >>Well, I think first of all, let me, let me thank the panel. Uh, we really appreciate Greg from Lily and the meta from IDC bringing their perspectives to this conversation. And, uh, I hope that the audience has enjoyed the, uh, the discussion that we've had around the future state of real world data as, as well as DCT. And I think, you know, some of the themes that we've talked about, number one, I think we have a vision and I think we have the right strategies in terms of the future promise of real-world data in any number of different applications. We certainly have talked about the promise of DCT to be more efficient, to get us closer to the patient. I think that what we have to focus on is how we come together as an industry to really work through these very vexing operational issues, because those are always the things that hang us up and whether it's clinical research or whether it's later stage, uh, applications of data. >>We, the healthcare system is still very fragmented, particularly in the us. Um, it's still very, state-based, uh, you know, different states can have different kinds of, uh, of, of cultures and geographic, uh, delineations. And so I think that, you know, figuring out a way that we can sort of harmonize and bring all of the data together, bring some of the models together. I think that's what you need to look to us to do both industry consulting organizations, such as IBM Watson health. And we are, you know, through DTRA and, and other, uh, consortia and different bodies. I think we're all identifying what the challenges are in terms of making this a reality and working systematically on those. >>It's always a pleasure to work with such great panelists. Thank you, Lorraine Marshawn, Dr. Namita LeMay, and Greg Cunningham really appreciate your participation today and your insights. The next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond has been brought to you by IBM in the cube. You're a global leader in high tech coverage. And while this discussion has concluded, the conversation continues. So please take a moment to answer a few questions about today's panel on behalf of the entire IBM life sciences team and the cube decks for your time and your feedback. And we'll see you next time.

Published Date : Dec 7 2021

SUMMARY :

and the independent analyst view to better understand how technology and data are changing The loan to meta thanks for joining us today. And how do you see this evolving the potential that this brings is to bring better drug targets forward, And so I think that, you know, the promise of data the industry that I was covering, but it's great to see you as a former practitioner now bringing in your Um, but one thing that I'd just like to call out is that, you know, And on the other side, you really have to go wider and bigger as well. for the patient maybe Greg, you want to start, or anybody else wants to chime in? from my perspective is the potential to gain access to uh, patient health record, these are new ideas, you know, they're still rather nascent and of the record, it has to be what we call cleaned or curated so that you get is, is the ability to bring in those third-party data sets and be able to link them and create And so, you know, this idea of adding in therapeutic I mean, you can't do this with humans at scale in technology I, couldn't more, I think the biggest, you know, whether What are the opportunities that you see to improve? uh, very important documents that we have to get is, uh, you know, the e-consent that someone's the patient from the patient, not just from the healthcare provider side, it's going to bring real to the population, uh, who who's, uh, eligible, you to help them improve DCTs what are you seeing in the field? Um, but it is important to take and submitted to the FDA for regulatory use for clinical trial type And I know Namita is going to talk a little bit about research that they've done the adoption is making sure that what we're doing is fit for purpose, just because you can use And then back to what Greg was saying about, uh, uh, DCTs becoming more patient centric, It's about being able to continue what you have learned in over the past two years, Um, you know, some people think decentralized trials are very simple. And I think a lot of, um, a lot of companies are still evolving in their maturity in We have some questions coming in from the audience. It is going to be a big game changer to, to enable both of these pieces. to these new types of data, what trends are you seeing from pharma device have the same plugins so that, you know, data can be put together very easily, coming from things like devices in the nose that you guys are seeing. and just to take an example, if you can predict well in advance, based on those behavioral And it's very common, you know, the operating models, um, because you know, the devil's in the detail in terms of the operating models, to some extent to see what's gonna stick and, you know, kind of with an innovation mindset. records, data to support regulatory decision-making what advancements do you think we can expect Uh, Dave, And it really took the industry a good 10 years, um, you know, before they I think there've been about maybe somewhere between eight to 10 submissions. onus is going to be on industry in order to figure out how you actually operationalize that clinical research stakeholders with sites or participants, Um, but actually if you look at, uh, look at, uh, It's just not something that you would implement across you know, healthcare professional opinion, because I think both of them bring that enrichment and do the monitoring visit, you know, in real time, just the way we're having this kind of communication to do higher value work, you know, instead of going in and checking the the data quality, the governance, the PR highly hyper specialized teams to do that. And the nice thing with that is you have some guardrails around that and you keep them in in-house to pivot toward DCT? That is, I think the first piece, when, you know, when you're implementing a new model, to patients and, uh, you know, the 80, 20 part of it. I mean, you know, we see the health portals that We have just about 10 minutes left and now of course, now all the questions are rolling in like crazy from learn the process and see how it's going to be implemented. I think as you scale this model, the efficiencies will be seen. And so, you know, based on the difficulty of the therapeutic Just scale, it's going to be more, more clear as the media was saying, next question from the audiences, the logic is also the fact that, you know, when you're, you're going into the later phase trials, uh, you know, in the industry right now, whether you're talking of what Detroit is doing, Are there others that you can share from the FDA EU APAC, regulators and supporting you know, around the implementation of clinical trials during the COVID pandemic, which incorporate various if you could give us some, some final thoughts and bring us home things that we should be watching or how you see And I think, you know, some of the themes that we've talked about, number one, And so I think that, you know, figuring out a way that we can sort of harmonize and and beyond has been brought to you by IBM in the cube.

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Madhav Mekala, Pepsi | Couchbase ConnectONLINE 2021


 

>> I've got Madhav Mekala here with me, commerce architect at PepsiCo Madhav welcome to the program. >> Thank you Lisa. >> So we're going to be talking about the solution that you implemented that helped with the global supply chain. So let's talk first about your role, commerce architect. Help me understand that a little bit better. >> So Frito-Lay PepsiCo is pretty big. It's a conglomerate of multiple product lines. So I worked for Frito-Lay, which is basically all the salty snacks and then we have a Quaker products as well in our portfolio. So I oversee all the architecture for all the commercial IoT solutions in the FNA portfolio. >> Got it all the commercial lines. So we all know the last 18 months major challenges with the global supply chain component shortages, we've seen a huge increase in the cost of raw materials, limited labor, but you guys actually started to tackle this challenge before the pandemic happened. So talk to me about the catalyst that PepsiCo, what you saw to modernize field service and supply chain application. >> Yeah, so we have a pretty old system that our field force, our frontline users are using. So we have a world-class supply chain system where we go into the stores and place orders and deliver products throughout the U.S. And then we penetrate, I think, more than 95% of the households with our products. So we need to have a robust supply chain as well as a good frontline sales application, to be able to manage the orders, and be able to deliver the products, right? So the system that we have is almost 20 year old system running on a very outdated technology. We've been trying to replace that for a while now. And finally, we started this early last year to completely replace the solution with a brand new IPhone based app. And then that gives our frontline the ability to go place orders, do deliveries to retail execution in the store like check-in check-out, bill displays. There are so much functionality that our RSRs or frontline users do in the stores and this app enables them to do much more efficiently. >> And we're going to break into that, but you mentioned you had a 20 year old technology. Talk to me about some of the challenges that that likely presented to those frontline workers. >> Yeah. I mean, there are multiple challenges for one, we cannot enable new business models. So business wants to come up with new ideas for, to be able to implement in the field, but with our system being so old, it's so hard to implement anything on that one. And then even the physical device is not scaling. We had a lot of memory issues, so it's time for it to kind of retire, but also the technology we use the 3G technology is retiring pretty soon at the next year. So we were definitely need to move to a new solution. And this is one of the must things we have to do right away. So that's where we started the project and we are in pilot phase right now. >> What would have been some of those negative consequences, had you not undertaken the effort? I imagine from a competitive perspective, knowing how much competition is out there, what would some of those challenges have been if this had persisted? >> Yeah, so one is the stability of the application, right? So the frontline users have to spend more time because the app is not stable, the current one. So that reduces the efficiency of our Salesforce. Right? And then on the other hand, we also not able to put new features or new business models enable new business models on top of the existing ones. So we are losing out on some of them because of our outdated system. So that's one thing we want to solve with the new one. >> So this is really critical to really evolve PepsiCo's business at, at its baseline, right? >> That's true. Yeah. It is very critical application that we are building and this will enable us to do a lot more things in future. And we can come up with new ideas, including like virtual reality or connecting to multiple systems. There are so many new ideas that we want to enable once we have this in place. >> Awesome. Talk to me about why Couchbase and then tell us more about, you started to talk a little bit about the solution, but let's go ahead and dig in and unpack the actual solution that you implemented. >> Yeah. So this is, eh, we call it an ERP and a mobile device because it has so much functionality as a company Frito-Lay, we have been over a hundred years in this business, right? We have so many optimized process that we have that kind of led to some digility in the system because we want to do in a particular way, because that's the best way to do it as part of our business process. So what we're trying to do here is take that business process and also provide an app that will enhance it and then connect to more, more systems. So that's what we are trying to do here. And then on top of that one, we will replace all the existing peripherals that we use with the new technology, like Bluetooth and all so that, they are much more faster and they slot more productive for our frontline force. >> Sounds like a lot of sales folks are going to to be a lot more productive. Talk to me about where Couchbase is as an integral component to this new system. >> Yeah. So one of the key requirements for this app is offline mode. What that means is one of our other salesforce who go from our system from our DC to other stores, should be able to run the whole day without any major disruption, even if they're not connected, let's say because when they go into big stores, typically there's no connection there all metal boxes. So the cellular reception is not there, but most of our work that we do from our frontline is within the store. So it has to be a full offline where we have to have all the data within the device and we should be able to place orders, create inventory that records or adjust inventory, and then create invoices. All the majority of the things that we do are in the store and they should be able to do without the connection. So that's where we explored multiple options and kind of zeroed in on Couchbase where we bring all the data into Couchbase database on the device and then sync it when there is connection, but there's no connection, we still have all the data on the device and we can go do all of our duties in the stores without any issues, even if it is not connected. >> So the sales folks can be in the stores with their mobile device, doing all the transactions that they need to do with the stores, regardless of if there's connectivity. Talk to me about what happens when they get back to connectivity in that and the Couchbase database sync. >> Yeah. And the other big thing we want is instant connect. I mean, when there's connectivity, we want instant sync with the backend, right? If there's new data that comes, we need that in the device. At the same time, if I place an order, I want to send it back immediately to our backend systems so that our fulfillment starts for those. So that's very critical when we have a lot of cutoff times for our orders. So we need order as soon as we've placed to be going into the backend systems. So what happens when it gets connected, as soon as the sales folks come out of the store or when, within the story they could connectivity the Couchbased technology that we are using using the sync gateway immediately syncs the data back and forth if there's any new data that's available. So that is key for us in this particular app. >> So our transactions happening in real time or near real time. >> Yeah. So the data flow happens in real time when there's connectivity, but when it is not connected still, it doesn't have any issue with the actual transactions with the RSR that can go complete anything that. >> Got it. Okay. So there's no impediment there. In fact, it's a productivity enhancer. It sounds like for all of those sales folks out on the frontline. Tell us so millions of documents go through the system, tens of billions of dollars. Talk to me about the volume of data and the actual monetary value that's traversing the system. >> Yeah. It's huge, again, this is kind of the lifeline of the company. The sales are always the life of any company, right? So most of the sales for Frito-Lay goes through our system and we're talking anywhere between hundreds of thousands of documents that flow through back and forth between the Couch between the device and the server. So there's a lot of master data that comes like products price from customers, all that information that comes from the backend to the device and all the orders inventory and everything that gets created on the device gets flown sync back to the server. So yeah, I mean, it's, it's a very complex system. And also from the volume perspective, it's huge. So we had to build a massive infrastructure on the backend to be able to handle all this. One of the key feature is again, we have this massive data that we need to sync to the devices, but each device should only get the portion of the data that they want because a particular Salesforce only goes to a small set of 20 stores, let's say. So the data that we sync to that device is only for those 20 stores. So that's the key here. So Couchbase allows us to do that. The Couchbase sync, where we can subset the data into different portions and only send the data that is relevant for a particular device. >> So then from a, from a latency perspective, it must be pretty low latency, pretty fast to be able to get this data back to the device and to the sales person that is in the middle of a transaction. >> Yes. I mean, it's pretty, the sink is very fast. The Couchbase sync, especially user's web sockets. And we do continuous replicators where if I complete an order, the next instant it's on the server. So it's, it's we observed the speeds improved a lot. So the technology that we are using uses syncs for a long, long time compared to Couchbase, and that's another productivity gain for our Salesforce. >> What were some of the differentials? You mentioned some of the technology requirements that PepsiCo had in rearchitecting, the infrastructure, but what were some of the key technology differentiators that really made Couchbase stand out as the obvious choice? >> Yeah, so we, when we started this project, we all know the sink is the key for this whole project, because we thought the data going back and forth, we cannot really build a robust offline app. So we looked at multiple options, other providers that are doing the sync. And we also looked at building our own sink, in-house using APIs, but then we did lots of performance testing across all the options that we had at that time. And then Couchbase came above all of them pretty handily. So obviously we can coach base takes care of the sync, and then we can focus on our business process. So we can go build all the business process and not worry about how to build the syncing engine. And then that is itself a big effort. So that's what Couchbase provided us saying a instant sync engine. And then we were able to focus more on our, the app applicants, the frontline application, the sensor application. >> And those business processes. Let's talk about some of the business outcomes. We've mentioned a few already in our conversation, increased in productivity, the sales forces increased in that as well. But I imagine there's a lot of benefits for the end-user customer in terms of being able to get the transactions completed faster. What are some of those positive business outcomes that PepsiCo is seeing as a result of implementing Couchbase? >> Yeah. So you hit on a couple of them that the sync times are definitely a big factor where that will directly give more time for the sales folks to go either go to most stores, or even if they go to the existing stores, they can do more, spend more time with the customer merchandising and making sure everything is correct. So that's one, also the new app users connect with a lot of new peripherals that are not available on the previous platform. Also, the, our folks are very enthusiastic about using a new app, right? So it's like coming into the 21st century for them using such an old lab for a long time. So a lot of things that they see, they can see the images of the bags while ordering, which was not a feature earlier. Some of them are small, but they make a huge impact on our users. So, yeah, I mean, and then this is just a start that we are doing. And then once we are able to completely implement this one, we have a lot more going into, in future. I was just talking about, we can do virtual reality or show them how to sell using virtual reality. We can show a display to a store manager saying, 'Hey, I want to put a display here. And this is how it looks,' they can show it on the phone directly, than just explaining and showing some paper images. So there's a lot of possibilities. >> A lot of improvements to the customer experience. It sounds like, it sounds like adoption is quite high for your folks who are used to 20 year old technology, probably being very excited that they have a modern app. But talk to me a little bit about the appetite of the organization to continue modernizing the application infrastructure and presuming going from older technology to that 21st century, like you talked about. >> Yeah. So in other parts, we are already modernized some of these. So we have been on the journey for the last four, five years building multiple digital platforms. So one of the examples I can give is when COVID hit, there's a lot of disruption for everybody, for the consumers, so they are not able to find the products in the stores, a lot people are afraid to go to the stores to even buy products. So we reacted very quickly and opened a consumer website called snacks.com, which Pepsi never sold it to consumer directly. We always go through our stores, but the first time we open the consumer channel and Couchbase powered some of it for the backend purpose. So this is not a mobile app, it's just a desktop app, but we already have been on the digital transmission journey, even before we quickly turn into COVID for the snacks.com. And similarly, we are, doing this for our retail execution, portion of it using this project. So, and then we'll be continuing to do this going forward to enable a lot of functionality for I mean, for all of our sales, as well as supply chain and other systems, so that we can be more efficient. We can be more elastic saying if there is more demand, our backend should be able to handle all that, which was not the case before. So now we've built a state of the art backend system on cloud. So there's a lot of transmission, digital transmission going on within PepsiCo. And I'm really proud to be part of this project so that we took this to the next level. And then this is just a start. We can do a lot more. >> Right? This is just the beginning. That sounds like a great transformation for a historied company that we all, everybody knows PepsiCo and all of its products. But it sounds like when the pandemic hit, you had the infrastructure in place to be able to pivot quickly to launch that direct to consumer, which of course consumers, patience has been quite thin in the last year and a half. Talk to me a little bit about the impact to the overall organization as a result of being able to, to get more direct with those consumers. >> Yeah. So till now, again, we are the business model is we sell to the stores and then go customer. So we'd never get a direct sense of what consumer liking is. I mean, we get through some surveys and stuff, but we don't have a direct channel to the consumer, which this particular project enabled us snacks.com. So we know the consumer behavior, how they buying patterns, browsing patterns, which ones they like and including with geography and all so we learned a lot from the consumer behavior point of view for the project. And then we kept on enhancing. So one new thing we introduced was called Multipack where the consumers can come and pick, make their own Multipacks basically. They can say, okay, I need these many of this particular product, this particular product and make their Multipack and we ship them the customized Multipack. And it was, such a huge hit that we are not able to even fulfill them so much demand was there for that one, so we had to revamp and then get back. And now it's a huge thing on all the snacks.com platform. So all of this is possible because we had a digital platform underneath that supports this kind of innovation. So the new business models are just coming to life in within weeks or even few months and that's what we will be trying to do with the new platform that we're building for this app as well, where we'll bring in lot of new business models on top of we have already. >> Excellent, a lot of transformation it sounds like at PepsiCo in the last couple of years, I love the customization, that personalization route that you're going and I think that's going to be a huge hit for consumers. And as you said, there's a lot of demand , Madhav thank you for joining me today, talking about how you are modernizing the field service and supply chain application, the impact it's making for end users for your customers and for the sales folks. We appreciate your time. >> Thank you so much Lisa. >> From McCalla. I'm Lisa Martin. You're watching this Cube conversation.

Published Date : Oct 26 2021

SUMMARY :

I've got Madhav Mekala here with me, about the solution that you So I oversee all the architecture So talk to me about the So the system that we have Talk to me about some of the So we were definitely need So that reduces the efficiency that we are building and the actual solution that you implemented. that we have that kind of led to some Talk to me about where Couchbase is as an the device and we can go do So the sales folks can be in the stores So we need order as soon as So our transactions the actual transactions with data and the actual monetary So the data that we sync to that device that is in the middle of a transaction. So the technology that we are other providers that are doing the sync. of benefits for the end-user So that's one, also the new app users about the appetite of the but the first time we the impact to the overall So the new business models in the last couple of years,

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Protect Against Ransomware & Accelerate Your Business with HPE's Cloud Operational Experience


 

>>Okay, okay, we're back, you're watching the cubes, continuous coverage of HBs Green Lake announcement. One of the things that we said on the Cuban. We first saw Green Lake was let's watch the pace at which H P E delivers new servants is what's that cadence like? Because that's a real signal as to the extent that the company's leading into the cloud and today we're covering that continued expansion. We're here with Tom Black, who was the general manager of HPC storage and Omar assad, who's the storage platform lead for cloud data services at Hewlett Packard Enterprise gentlemen welcome. It's good to see you. >>Thanks Dave. Thanks for having us today. Good to see you. >>Happy to be here. Dave. >>So obviously a lot has changed globally, but when you think of things like cyber threats, ransomware, uh, the acceleration of business transformation, uh, these are new things, a lot of it is unknown a lot of it was forced upon us tom what are you guys doing to address these trends? How are you helping customers? >>Sure, thanks for the question. So if you think back to what we launched in early May, kind of the initial cloud transformation of what was our traditional storage business. Um, we really focused on one key theme. Very customer and customer driven theme that the cloud operational model has one and that customers want that operational model, whether they're operating their workload in the cloud or whether they're operating that workload in their own facility or Nicolo kind of the same thing. So that was kind of our true north and that's what we launched out of the gate in May. But we did allude in May to the fact that we would have an ongoing series of new services coming out on the uh H B Green Lake edge to cloud platform. And just really excited today to be talking about somewhat that expansion looks like um we will continue uh through this month and through the quarters ahead to really add more and more services in that vein of focusing on bringing that true cloud services model to our customer. So we're really excited today to unveil kind of, we've entered the data protection as a service market with HP Green Lake. So this is really our expansion into a very top of mind topic and set of problems and solutions or headaches and aspirins, to quote an old friend um that Ceos faces, they think about how to manage data through its life cycle in their organization. >>When I talked to see IOS during the pandemic. Not that we're out yet, but really in the throes of it and asked them about things like business resilience that they said, you know, we really had to rethink our disaster recovery strategy. It was it was sort of geared toward a fire or a hurricane and we we just didn't even imagine this type of disaster if you will. So we really needed to rethink it. So when I, I see your disaster recovery as a service and capabilities like that. Is that the Xarelto acquisition? >>Yes. Dave thanks you. So we're super happy to have the Xarelto team now as part of our family. Um, just a brilliant team, a well respected technology, uh, kind of a blue chips at our customers and partners that really appreciate what zero has to offer. Um, as we looked at the data protection as a service market, one of the hardest problems is really in that disaster recovery space, I think Omar's gonna talk a little bit more about today. Um, but sort of really does bring the leading industry, what's called continuous data protection um, capability into our green lake platform. Um, we've just recently closed the acquisition and we're working on kind of integration plan as we speak now that we can actually talk to each other post close. Um, but you'll uh, you'll continue to see, you know, some really exciting milestones each and every quarter as we march forward with certain now as part of the family. >>So we all talk about how data is, is so important. We certainly learned during the pandemic that that if you weren't a digital business, you were out of business and a digital business is a data business. So things like backup data protection as a service become increasingly critical. I know you have some capabilities there maybe you could share with us. >>Absolutely. So you know, one of the things that we noticed was as we took the storage business through its transformation and we started can work you know, with the launch of the electron 90 and the six K platform. We really really brought the cloud operational model to our customers. So one of the things that you know, feedback that was coming loud and clear to us is that as we look at the storage portfolio where we look at file block and object, which are now being transformed into a cloud operational experience, data protection, disaster recovery coming back into business after a disaster snapshot management. All of those capabilities, we still have to rely on our partner technologies in order to do that now. It's not bad that we have great partners in the data protection world, but what we're really focused on is that cloud operational model and cloud operational experience and to and as tom mentioned through the data management life cycle. So as a result of that, we talked to a lot of our customers, we talked to a bunch of partners and one of the things that was coming back was that yes, there are many data protection backup offerings on the market. But that true as a service experience that is completely integrated to the services experience of the storage that the customers is experiencing that is not there. So what we looked at was especially to the largest ecosystem, which is the VM ware ecosystems. So we're launching data protection as a service or backup as a service for our VM ware customers offered from data services, cloud console as a SAAS portal. 100% SAs service, nothing to install. No media servers, no application servers, no catalog servers, no backup targets, no patching, no expansion, no capacity planning. None of that is needed. All that's needed is sign on click. Give your V center credentials and off you go, that's it. That is it three clicks and you're in business. So currently, you know, in our, in our analysis we offer five x faster recovery from any of the competitive offerings that there there there are 3.5 better de doop ratios. But for our customers is as simple as this. VM is protected as this many dollars per gig per month. That's it. No backup target, no media server, no catalogs are nothing nothing to manage total Turkey off of the portal. So that's the cadence of services that if you promise and this is one of the first ones when it comes to data management that is coming out into the open. >>So you may have just answered this question, but I want to pose it and get you maybe just summarize it because tom was talking earlier about the customer mandate for cloud in a cloud operational model. So I want you to explain to the audience how you're making that real >>actually can I start that one should be the test was monday morning. Getting ready for this chat with you Dave they got me on console and I'm not kidding three clicks, I got back up and running off the lab VM ware instance so I'll pass it off to you the real answer. But if I could do it three clicks >>as well as a convenience of this service, even tom can be your back, you might be able to do with this. Uh again, you know, a very important question the when you, when you look at the cloud operational model as you abstracts the hardware and and take the management model up into a SAS service, it gives our customers that access to that continuous delivery access that we have. We're going to continue to make the service medal better in the cloud model and automatically customers get the value of it without even reinstalling or going through a patch cycle or an upgrade cycle. But as we get into this cloud operational model, one of the things that was missing was uh if you if you if you if you start to talk about applications, how our application workloads going to be deployed, how are they going to be protected and how are they going to be expanded? So what we did was we, we expanded our info site offerings by merging them into the data services, cloud console and we're releasing a new service called app insects. It is going to be available to our customers at the end of the month. Uh It is, nothing has to change. They don't have to install any sort of agents or or host modifications, nothing like that. If their customers of electra nimble primary boxes and they're using info site and data services, cloud console, they will automatically get app insights. What Athens sites does is it really teases apart all that data that we have been collecting within foresight and now with the acquisition of HPV cloud physics, we're merging them together and relating the operational stacked top to bottom. So discovering all the way from your application usage, network usage, storage, use it. IOP usage VM values cross, collaborating them and presenting that to a customer from an app or an outcome perspective all in the data services, cloud console. So what this does for our customers is it really really transforms not only their operational experience but also buying experience. Because if you remember in one of the earlier releases of data services cloud console we released this application called, you know, intelligent intent based provisioning in which you just describe your workload and we go ahead and we provision that app insights and info site, feed that information directly into that and cloud physics generates and results and displays those analytics back to us to your partner of record and to the H. B. So we can all come together on a common data driven discussion point with our customers to continue to make their journey better >>tom where's all the boxes, traditional storage is changing. I've actually been waiting for this day for a long, long time. We've certainly seen glimpses of it from the cloud players, but they don't have, you know, super rich portfolio storage portfolio. They're growing now, but this is a really good strong example of a company with a large storage portfolio. That's, I mean I haven't heard the word three power once today. Right. And so what that says to me, that's an indication that you're thinking like a cloud player, can you maybe talk >>to that? Sure. Yeah, we're just tremendously excited about this transformation and really the reception we've got in the market from analysts, from partners, from customers because you're right, you haven't heard us talk about a box at all today. It's really about a block service, a file on the object service, a backup and recovery service, disaster recovery service. That that's that is the the language, if you will of the business problems of our customers not, do they need to pick this widget or that widget. And how many apps can I get here and there? And which did the h a cage protection scheme be that, is that, is our job to manage underneath are true North, which is the cloud operational model. And so that's going to be really how we we've set our course and how we will uh kind of deliver products solutions offers into the market underneath that umbrella, Ultimately, um getting our customers wherever their data is Dave to be able to interact at that service level instead of at that infrastructure box >>level, you've got my attention wherever the data. So that's the north star here is this is, you know, you're not done today obviously, but you've got a vision to bring that to the cloud across clouds on prem out to the edge. That's the abstraction layer that you're gonna build, your hiding all that complexity. That's correct. And that's cloud. The definition of cloud is changing. >>Yeah, >>it's no longer started, it's no longer a remote set of services. Somewhere up in the cloud. It's expanding on prem hybrid across clouds edge >>everywhere. You're exactly right. Dave it is, cloud is more about the experience and the outcome. It gives a customer than actually where the compute or storage is. We've chosen to take a very customer an agnostic position of whether it's, you know, data in your premise, data in your cloud. We're going to help you manage that data and deliver, you know, that data to workloads and analytics, uh, wherever the, wherever the compute needs to be, where the data needs to be. Again, technologies like Xarelto giving instability and move data across clouds from facilities and clouds back and forth. So it's a really exciting new day for HP. Green Lake were just so super happy to bring these technologies out and really continue to follow on the course of doing what we said, we would do >>the new mindset starts there, I guess it's obviously knew certainly new technologies, uh, you're talking about machine intelligence is a metadata challenge. Absolutely. Big time, you know, long term that North Star that we talked about and applying that machine intelligence, all the experience that you gather data that you're gathering is, I think ultimately how customers want you to solve this problem >>in the middle of info site data services, cloud console and the instrumentation that is already shipping on our appliances, both in edge appliances and the data center appliances were collecting more than a trillion data points over the period of a quarter. Right at the end of the day. So it's harnessing that at the back end to cross relate and then using the cloud physics accusation. What we're doing is we can now simulate these things on behalf of our customers into the future timeline. So at the end of the day, it's really about listening to the customer and what outcomes that they want to achieve with their data storage is there we provide excellent persistence layers where customers can store their data safely. But at the end of the day it's customers choice, They can store their data out of the edge in compute servers, commodity servers, X 86 servers, they can have their data in the data center which they are privately owned or their data can be in a service provider or it can be in a hyper secular. The infrastructure of the persistence layer is independent from the data services. Cloud console data services. Cloud console provides our customers with a SAS based industry leading metadata rich management experience, which then allows you to draw conclusions. So services like cloud physics services like uh enforce it, provide the analytics and richness of the metadata, backup and recovery service allows us to index our customers data and add a rich metadata to that and then combine that with xylitol, which is our disaster recovery as a service offering. Going to start over here. That gives the customer a very simple slider as to where they want their protection levels to be, they want their protection to be instant or they want their protection to be lazy eight hours window. But the thing is at the end of the day, it's about choice without managing the complexities of the hardware >>underneath because programmable completely right I come in, what I'm hearing is file object blocks of your multi protocol. I got a full stack so data data reduction, my snaps might replicate whatever whatever I need it in there as a service. I can I can access latency sensitive storage if I need to or I can push it out to cheaper stores. I could push it out to the cloud, presumably I could someday I air gap it uh and it's all done as infrastructure as code and then different protection levels where I see this going. It really gets exciting is you're now a data company and you're bringing ai machine intelligence and driving data products, data services for your customers who are going to monetize that at their end of the value >>chain. That's right. That's right. And safely insecurity. Keeping in mind that was their toes technology. We can give you, you know, small second recovery points to protect against ransomware. So all of that operational elegance, all those insights and intelligence to help you build a more agile, um you know, workloads centric organization, but then to do it safely and securely against ransomware, that's kind of the storm, if you will. That's brewing. And we're just really excited to be at the eye of it. >>I'm excited to. This is uh I've been waiting for this day for a long time and we're not talking about envy, Emmy and Atomic Rights and I love that stuff by the way and I'm sure it's all under the covers, but that's not what drives business value guys. Thanks so much for coming on the Cuban. David. >>Thanks for having us. It's been great. Thank you. >>All right. We're seeing a transformation all through the stack and keep it right there. This is Dave Volonte for the Cuban. Our coverage of HBs Green Lake announcements right back mm mhm

Published Date : Sep 28 2021

SUMMARY :

One of the things that we said Good to see you. Happy to be here. So that was kind of our true north and that's what we launched out of the gate in May. Is that the Xarelto acquisition? market, one of the hardest problems is really in that disaster recovery space, I think Omar's gonna talk a little bit that if you weren't a digital business, you were out of business and a digital business is a data business. So one of the things that you know, So I want you to explain to the audience how you're making that real actually can I start that one should be the test was monday morning. one of the things that was missing was uh if you if you if you if you start to talk about but they don't have, you know, super rich portfolio storage portfolio. And so that's going to be really how we we've set our course and how So that's the north star here is this is, It's expanding on prem hybrid across clouds edge We're going to help you manage that data and deliver, you know, that machine intelligence, all the experience that you gather data that you're gathering is, So at the end of the day, it's really about listening to the customer and what outcomes that I could push it out to the cloud, presumably I could someday I air gap it uh against ransomware, that's kind of the storm, if you will. Emmy and Atomic Rights and I love that stuff by the way and I'm sure it's all under the covers, Thanks for having us. This is Dave Volonte for the Cuban.

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Fernando Castillo, CloudHesive & Luis Munoz, Universidad de Los Lagos | AWS PS Awards 2021


 

(upbeat music) >> Hello and welcome to today's session of the 2021 AWS Global Public Sector Partner Awards Program. This session's award is going to be profiling the Most Customer Obsessed Mission-based Win in the education domain. I'm your host, Donald Klein, with theCUBE. And today we are joined by Fernando Castillo. He's the Business Development Manager at CloudHesive, and then also Luis Muñoz, who's the Information Director at the Unibersidad de Los Lagos. >> Okay, everyone. Welcome to today's session. All right. Fernando, thanks for taking some time out and joining us today. Wanted to start with you and wanted to hear a little bit of background about CloudHesive. Obviously, you're a company that had won an award last year, but you're back on this year, again. Want you give us some a little bit of the story of CloudHesive, and what kind of services you provide? (speaking in foreign language) >> Translator: Thank you very much, Donald. Yes, CloudHesive is a managed consulting service provider in the cloud. We are AWS Partner and since 2014 we have been providing solutions focusing on security, trustability, and scalability in the cloud. Accompany companies to their main objective, which is reducing operational costs and increasing their productivity as they move forward in the adaption of cloud services. >> Very good. Okay. And then Luis, I'm going to turn to you now, want you talk to us a little bit about your role there at the Unibersidad de Los Lagos, and how you started this project? (speaking in foreign language) >> Translator: Good afternoon. I belong to the academic department of the engineering department at the University of Los Lagos and the director of the IT of this school. For several years, for about five years, we've been analyzing the deployment of these automation at universities of Chile. Since it's not a common item in the country, we've done several benchmarking worldwide, especially in Spain, Mexico, Columbia, and places where it's more developed. And eventually, we have to take some demos that allowed us to make some decisions. This topic was not going to be considered in 2020, but it happened because of a political situation, social political in Chile in 2019. So we have to move forward the process, but we had already made a global analysis and this was one of the reasons why we have to get closer to AWS Partners and this allowed us to move this process forward within the university. >> Okay. Very good. All right. Well then, what I'm going to do now is I'm going to come back to you, Fernando, and I want you to talk a little bit about the overall goal of what you were trying to help the university with. (speaking in foreign language) >> Translator: Well, within the main objectives we had in the project was to have a platform that would support a concurrent load of thousands of students, especially in University of Los Lagos. They had requested to have around 15,000 students and the main complication or the main challenge was to keep a virtual attendance, which is now known as learning management system, but also having the possibility of having video classes in two days, something similar to what we are doing today, but with 50 or up to 100 students. This was one of the main objectives of the project. >> Okay, understood. So the goal is here to deploy this platform and open source platform and make it available for about 15,000 students. Okay. Now coming back to you, Luis, there was a time constraint here, correct? You needed to get the system going very quickly. Maybe you could explain why you needed to accelerate this program so quickly. (speaking in foreign language) >> Translator: Well, literally, the pandemic conditions in the country started to be more evident and more severe since the first week of March in 2020. And so we have to make the decision, the double-sided decision of choosing an infrastructure that we could not buy at that time, given the emergency, logistic emergency of the pandemic at the server's room and to keep a stable platform for that number of users, student and professors of university. So we started conversations to make this scale up and move everything to the cloud. This was the first decision. So we decided to use Amazon and with CloudHesive, we were able to organize the academics charter in the same platform. So as to move no longer than three weeks so that we could give classes, online classes with the students while we were learning this new normal, which was virtual distance education. This was very difficult of every morning, afternoon, and evening of work, but this allowed us not to fall behind in the first semester of the educational needs of the students. With this modality, we have around 5% more students that we used to last year in 2020, in March 2020. And this allowed us to have a more visible structure for those who were questioning this new modality and we were applied to take this new modality in the end. >> Okay. So because of the pandemic, you had to accelerate the deployment of this learning management system very quickly. And you had to learn how to manage the system at the same time that you were deploying it. Okay. Understood. So a lot of challenges there. All right. So then maybe coming back to you, Fernando. Wanted you talk about your role and how CloudHesive helped with this sort of this very rapid deployment of this LMS system. (speaking in foreign language) >> Translator: Well, talking about the challenges and how we were able to get to the objective, within the plan, deployment and development have to accompany the University of Los Lagos not only with the use of the platform, but also how to change management. One of the biggest challenges was to do a security audit, the deployment of scalable infrastructures. And one of the main topics was, one of the main challenges for CloudHesive that we can now talk about and obtained objective was to do the tests from the point of view of scalability and security getting into 15,000 students, concurrent students, stimulating the workload of the university, keeping 99.5 availability of the platform. Going back to the challenges, it's not only the scalability and stability. Nowadays, the University of Los Lagos platform can continue to grow, as Luis mentioned, without the need to look for new resources. But with our implementation, deployment and development, we already have a scalable resource as they increase the number of professors and students to their university. >> Okay. Understood, understood. Now, maybe talk a little bit just to continue with that point. Maybe talk for a minute about how you leverage the AWS platform in order to be able to accelerate this project. What aspects of your partnership with AWS enabled you to deploy the system so quickly? (speaking in foreign language) >> Translator: Well, talking about that, we based on a referential architecture of AWS, which is an open source middle platform, and within these competencies and within things, they belong to the education. We also have the problems, the presence of (indistinct), which allows us to deploy new solution and new integrations. So this allowed us as the team to, within weeks, to develop new features that would allow us to deal with each of the requirements of the universities, specifically. So within the first week, the University of Los Lagos had the connectivity with the academic sector. On the second week, they had the infrastructure to support out two-way videos. And on the third week, they already had the platform completely deployed with all the security safeguards that we already have in all of our products and services. So having worked hand-in-hand with AWS allowed us to have success in time with this platform. >> Wow. So that's fantastic. You were able to deploy this entire system from the connection with the academics to the video infrastructure to actually getting all the security implementations in place. You were able to do that in a three week cycle, is that correct? >> Yeah, that's correct. >> Fantastic. Okay. So Luis, coming back to you then, so working with CloudHesive as a partner to help deploy the platform on AWS gave you fantastic speed and agility to get the system working. Maybe talk a little bit now about the challenges of getting students and educators to adapt the system, and what kind of successes you had? (speaking in foreign language) >> Translator: First of all, they have to, we need to need to know the geography, the landscape of the university. The geography is very varied. We have mountains and lakes and so forth, and connectivity concepts are very difficult in this area. In addition, University of Los Lagos has the characteristic of receiving students from very poor sectors within the region. So this means that more than 80% have a free education, as there are few universities that exist in the country. So one of the technological challenges was for these students to receive the mechanisms and technology to have the connectivity they needed. After that, we had a very big training plan with the deployment company, CloudHesive, with the permissions, and eventually together, we were able to go beyond students and professors. And I remember we had 50% students and professors logged in to the platform, and nowadays, we have 100% students and professors logged in having classes in the platform. But most importantly, nowadays, we have an analytical control because of an integration with CloudHesive, with certain tools that allow us to gather data in real time. And we can do a follow-up of the student that is closer actually from the previous situation when we didn't have this technology. If the student is not logged in, we can reach them directly or indirectly to know, what is happening with his meeting, which is the kind of support, academic, social or economic support that they need. Before, it was harder to get this. So we have a communion between technology and social services that we can provide as a university. And of course, the adaptability of CloudHesive in as much as most of the requirements that we needed. So as to have a good response, they've been very providing, they provided a very robust service in this terms. >> Fantastic. So you were able to reach 100% percent of your target audience very quickly. Is that correct? Great. >> Yes. >> And maybe just to kind of follow up one more. Just talk a little bit about the future of your program. Now that you've worked so hard to establish the system and to connect your students and your teachers and to optimize the system, what is your plan to use it going forward? Are you looking to expand it? What would you say are your goals? (speaking in foreign language) >> Translator: First of all, for better or for worse, this modality came here to stay. The pandemic may end, but it generated opportunities that nationwide, it moved forward at least seven or eight times faster, these kinds of possibilities. So it's hard to use or waste this opportunity with the face-to-face classes. The university nowadays, thanks to the platform and the work done by CloudHesive and AWS, the university won ministry projects from the Ministry of Education in the country, have a strengthening plans for other kinds of services that were not incorporated before, like the idea of virtual library, research work, academic development work, of training and cultural transformation as well. But eventually, they are happening in this virtually environments. And the university won this possibility through the ministry, bridging the gap between the academic sector and the students. And in order to elaborate a little bit more from the previous question, we did a survey last year and ended not long ago. And most professors said that 80%, more than 80% said that the virtual environment was considered as good or very good. So we have a very good assessment in order to participate in this project that were won by the university and they are nowadays being applied. So this generates development in the academic sector, in research, in library, in content creation, global communication, working together with other universities with work postgraduate courses and other universities without the need of getting out of home. So this is a very competitive advantage that we didn't have before. And since 2020, we were able to develop. >> Fantastic. Well, congratulations on a really well put together program. And I'm excited to hear that you've won an award in your country and that you're planning to expand the system more broadly. I think that's a fantastic success story. So maybe just to wrap this up here with you Fernando, why don't you talk a little bit about, so obviously, you guys were very critical in helping this system be deployed very quickly, but very securely at the same time. How do you see your role going forward in enabling these types of situations, this distance learning type formats? (speaking in foreign language) >> Translator: Well, just as Luis said, taking this project with the University of Los Lagos, this showed the importance of looking at technological advances and to improve the universities and research centers and how to focus on innovation and bringing the future education down. For us, the data generated in this virtual interactions are very valuable and having a clear perspective, so as to organize this data for, to make more effective decisions that allow us to act in real time. This is what we are focusing on right now. So as to keep, I mean, prove, and being able to provide new tools, the research centers and universities to operate quickly, safely, and cost effectively. >> Okay, fantastic. So really, the real lesson learned here is by working with a partner like yourself, you were able take an open source learning management system and then deploy it very quickly, manage it, and then secure it in a way that allowed the university then to do their work. So I think that's a really great end-to-end delivery story. So I think, maybe if you want to make one last comment, Fernando, about your role in any kind of future expansion for this type of work. (speaking in foreign language) >> Translator: Yes, of course. I would like to thank Amazon and University of Los Lagos, of course for giving us the chance to work together and develop this project successfully. And answering your question, I would like to say that this is a good incentive to build more robust solutions, as long as we have our focus on our clients, when working and as a final comment, I would just would like to thank you and hope to see you again with a new project. >> Okay, well, congratulations to you both on winning this award. And for CloudHesive, this is your second year in a row of winning a Public Sector Award. So with that, I'm going to sign off today and I'm going to thank you both for attending. Today, we've had Fernando Castillo, the Business Development Manager from CloudHesive and then Luis Muñoz, the Information Director at the Uniberisdad de Los Lagos, and thank you both for attending. This is Donald Klein for theCUBE, until next time. (bright music)

Published Date : Jun 30 2021

SUMMARY :

of the 2021 AWS Global Public of the story of CloudHesive, and scalability in the cloud. at the Unibersidad de Los Lagos, and the director of the IT of this school. help the university with. in the project was to have a So the goal is here to emergency of the pandemic at the same time that One of the biggest challenges the AWS platform in order to be able of the universities, specifically. from the connection with the academics and agility to get the system working. in as much as most of the able to reach 100% percent and to optimize the system, and the work done by CloudHesive and AWS, So maybe just to wrap this and bringing the future education down. that allowed the university then and hope to see you and I'm going to thank

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Sandy Carter, AWS | CUBE Conversation, February 2021


 

(upbeat music) >> Hello and welcome to this Cube conversation. I'm John Furrier, your host of theCube here in Palo Alto, California. We're here in 2021 as we get through the pandemic and vaccine on the horizon all around the world. It's great to welcome Sandy Carter, Vice President of Partners and Programs with Amazon Web Services. Sandy, great to see you. I wanted to check in with you for a couple of reasons. One is just get a take on the landscape of the marketplace as well as you've got some always good programs going on. You're in the middle of all the action. Great to see you. >> Nice to see you too, John. Thanks for having me. >> So one of the things that's come out of this COVID and as we get ready to come out of the pandemic you starting to see some patterns emerging, and that is cloud and cloud-native technologies and SAS and the new platforming and refactoring using cloud has created an opportunity for companies. Your partner group within public sector and beyond is just completely exploding and value creation. Changing the world's society is now accelerated. We've covered that in the past, certainly in detail last year at re:Invent. Now more than ever it's more important. You're doing some pretty cutting things. What's your update here for us? >> Well, John, we're really excited because you know the heartbeat of countries of the United States globally are small and medium businesses. So today we're really excited to launch Think Big for Small Business. It's a program that helps accelerate public sector serving small and diverse partners. So you know that these small and medium businesses are just the engine for inclusive growth and strategy. We talked about some stats today, but according to the World Bank, smaller medium business accounts for 98% of all companies, they contribute a 50% of the GDP, two-thirds of the employment opportunities, and the fastest growing areas are in minority owned businesses, women, black owned, brown owned, veteran owned, aborigine, ethnic minorities who are just vital to the economic role. And so today this program enables us as AWS to support this partner group to overcome the challenges that they're seeing today in their business with some benefits specifically targeted for them from AWS. >> Can I ask you what was the driver behind this? Obviously, we're seeing the pandemic and you can't look at on the TV or in the news without seeing the impact that small businesses had. So I can almost imagine that might be some motivation, but what is some of the conversations that you're having? Why this program? Why think Big for Small Business pilot experience that you're launch? >> Well, it's really interesting. The COVID obviously plays a role here because COVID hit small and medium businesses harder, but we also, you know, part of Amazon is working backwards from the customers. So we collected feedback from small businesses on their experience in working with us. They all want to work with us. And essentially they told us that they need a little bit more help, a little bit more push around programmatic benefits. So we listened to them to see what was happening. In addition, AWS grew up with a startup community. That's how we grew up. And so we wanted to also reflect our heritage and our commitment to these partners who represent such a heartbeat of many different economies. That was really the main driver. And today we had, John, one of our follow the sun. So we're doing sessions in Latin America, Canada, the US, APJ, Europe. And if you had heard these partners today it was just such a great story of how we were able to help them and help them grow. >> One of the cultural changes that we've been reporting on SiliconANGLE, you're seeing it all over the world is the shift in who's adopting, who's starting businesses. And you're seeing, you mentioned minority owned businesses but it goes beyond that. Now you have complete diverse set entrepreneurial activity. And cloud has generated this democratization wave. You starting to see businesses highly accelerated. I mean, more than ever, I've never seen in the entrepreneurial equation the ability to start, get started and get to success, get to some measurable MVP, minimal viable product, and then ultimately to success faster than ever before. This has opened up the doors to anyone to be an entrepreneur. And so this brings up the conversation of equality in entrepreneurship. I know this is close to your heart. Share your thoughts on this big trend. >> Yeah, and that's why this program it's not just a great I think achievement for AWS, but it's very personal to the entire public sector team. If you look at entrepreneurs like, Lisa Burnett, she's the President and Managing Director of DLZP. They are a female owned minority owned business from Texas. And as you listen to her story about equity, she has this amazing business, migrating Oracle workloads over to AWS, but as she started growing she needed help understanding a little bit more about what AWS could bring to the table, how we could help her, what go to market strategies we could bring, and so that equalizer was this program. She was part of our pilot. We also had John Wieler on. He is the Vice President of Biz Dev from IMT out of Canada. And he is focused on government for Canada. And as a small business, he said today something that was so impactful, he goes, "Amazon never asked me if I'm a small business. They now treat me like I'm big. I feel like I'm one of the big guys and that enables me grow even bigger." And we also talked today to Juan Pablo De Rosa. He's the CEO of Technogi. And it's a small business in Mexico. And what do they do? They do migrations. They just migrate legacy workloads over. And again, back to that equality point you made, how cool was it that here's this company in Mexico, and they're doing all these migrations and we can help them even be more successful and to drive more jobs in the region. It's a very equalizing program and something that we're very proud of. >> You know what I love about your job and I love talking to you about this (Sandy laughs) because it's so much fun. You have a global perspective. It's not just United States. There's a global perspective. This event you're having this morning that you kicked off with is not just in the US, it's a follow the sun kind of a community. You got quite the global community developing there, Sandy. Can you share some insight behind the curtain, behind AWS, how this is developing? How you're handling it? What you're doing to nurture and grow that community that really wants to engage with you because you are making them feel big because (laughs) that's what cloud does. It makes them punch above their weight class and innovate. >> Yeah, that's very correct. >> This is the core thesis of Amazon. So you've got a community developing, how are you handling it? How are you building it? How are you nurturing it? What are your thoughts? >> You know what, John? You're so insightful because that's actually the goal of this program. We want to help these partners. We want to help them grow. But our ultimate goal is to build that small and medium business community that is based on AWS. In fact, at re:Invent this year, we were able to talk about MST which is based out of Malaysia, as well as cloud prime based out of Korea. And just by talking about it, those two CEOs reached out to each other from Korea and Malaysia and started talking. And then we today introduced folks from Mexico, and Canada, and the US, and Bulgaria. And so, we really pride ourselves on facilitating that community. Our dream here, our vision here is that we would build that small business community to be much more scalable but starting out by making those connections, having that mentoring that will be built in together, doing community meetings that advisory meetings together. We piloted this program in 2020. We already have 37 partners. And they told me as I met with them, they already feel like this small and medium business community or family. Family was the word they used, I think, moving forward. So you nailed it. That's the goal here is to create that community where people can share their thoughts and mentor each other. >> And it's on the ground floor too. It's just beginning. I think it's going to be so much larger. And to piggyback off that I want to also point out and highlight and get your reaction to is the success that you've been having and Amazon Web Services in general but mainly in the public sector side with the public private partnership. You're seeing this theme emerge really been a big way. I've been enclose to it and hosting and being interviewing a lot of folks at that, your customers whether it's cybersecurity in space, the Mars partnership that you guys just got on Mars with partnerships. So it's a global and interstellar soon to be huge everywhere. But this is a big discussion because as from cybersecurity, geopolitical to space, you have this partnership with public private because you can't do it alone. The public markets, the public sector cannot do it alone. And it pretty much everyone's agreeing to that. So this dynamic of public sector and partnering private public is a pretty big deal. Unpack that for us real quickly. >> Yeah, it really is a big deal. And in fact, we've worked with several companies. I'll just use one sector. Public Safety and Disaster Response. We just announced the competency at re:Invent for our tech partners. And what we found is that when communities are facing a disaster, it really is government or the public sector plus the private sector. We had many solutions where citizens are providing data that helps the government manage a disaster or manage or help in a public safety scenario to things like simple things you would think, but in one country they were looking at bicycle routes and discovered that certain bicycle routes there were more crashes. And so one of our partners decided to have the community provide the data. And so as they were collecting that data, putting in the data lake in AWS, the community or the private sector was providing the data that enabled the application, our Public Sector Partner application to identify places where bicycle accidents happen most often. And I love the story, John, because the CEO of the partner told me that they measured their results in terms of ELO, I'm sorry, ROL, Return on Lives not ROI, because they save so many lives just from that simple application. >> Yeah, and the data's all there. You just saw on the news, Tiger Woods got into a car accident and survived. And as it turns out to your point that's a curve in the road where a lot of accidents happen. And if that data was available that could have been telegraphed right into the car itself and slow down, kind of like almost a prevention. So he just an example of just all the innovation possibilities that are abound out there. >> And that's why we love our small businesses and startups too, John. They are driving that innovation. The startups are driving that innovation and we're able to then open access to that innovation to governments, agencies, healthcare providers, space. You mentioned Mars. One of our partners MAXR helped them with the robotics. So it's just a really cool experience where you can open up that innovation, help create new jobs through these small businesses and help them be successful. There's really nothing, nothing better. >> Can I ask you- >> Small, small is beautiful. >> Can I asked you a personal question on this been Mars thing? >> Yeah. >> What's it like at Amazon Web Services now because that was such a cool mission. I saw Teresa Carlson, had a post on the internet and LinkedIn as well as her blog post. You had posted a picture of me and you had thumbs were taking an old picture from in real life. Space is cool, Mars in particular, everyone's fixated on it. Pretty big accomplishment. What's it like at Amazon? People high five in each other pretty giddy, what's happening? >> Oh yeah. The thing about Amazon is people come here to change the world. That's what we want to do. We want to have an impact on history. We want to help make history. And we do it all on behalf of our customers. We're innovating on behalf of our customers. And so, I think we get excited when our customers are successful, when our partners are successful, which is why I'm so excited right now, John, because we did that session this morning, and as I listened to Juan Pablo Dela Rosa, and just all the partners, Lisa, John, and just to hear them say, "You helped us," that's what makes us giddy. And that's what makes us excited. So it could be something as big as Mars. We went to Mars but it's also doing something for small businesses as well. It runs the spectrum that really drives us and fuels that energy. And of course, we've got great leadership as you know, because you get to talk to Andy. Andy is such a great leader. He motivates and he inspires us as well to do more on behalf of our customer. >> Yeah, you guys are very customer focused and innovative which is really the kind of the secret sauce. I love the fact that small medium sized business can also be part of the solutions. And I truly believe that, and why I wanted us to promote and amplify what you're working on today is because the small medium size enterprise and business is the heart of the recovery on a global scale. So important and having the resources to do that, and doing it easily and consuming the cloud so that they can apply the value. It's going to change lives. I think the thing that people aren't really talking much about right now, is that the small medium size businesses will be the road to recovery. >> I agree with you. And I love this program because it does promote diversity, something that Amazon is very much focused on. It's global, so it has that global reach and it supports small business, and therefore the recovery that you talked about. So it is I think an amazing emphasis on all the things that really matter now. During COVID, John, we learned about what really matters, and this program focuses on those things and helping others. >> Well, great to see you. I know you're super busy. Thanks for coming on and sharing the update, and certainly talking about the small mid size business program. I'm sure you're busy getting ready to give the awards out to the winners this year. Looking forward to seeing that come up soon. >> Great. Thank you, John. And don't forget if you are a small and medium business partner 'cause this program is specifically for partners, check out Think Big for Small Business. >> Think Big for Small Business. Sandy Carter, here on theCube, sharing our insight, of course all the updates from the worldwide public sector partner program, doing great things. I'm John Furrier for theCube. Thanks for watching. (upbeat music)

Published Date : Feb 25 2021

SUMMARY :

One is just get a take on the Nice to see you too, John. and the new platforming and the fastest growing areas and you can't look at on the TV and our commitment to these partners the ability to start, and so that equalizer was this program. and I love talking to you about this This is the core thesis and Canada, and the US, and Bulgaria. And it's on the ground floor too. And I love the story, John, Yeah, and the data's all there. They are driving that innovation. a post on the internet and just all the partners, Lisa, John, is that the small medium size businesses And I love this program and sharing the update, And don't forget if you are a small of course all the updates

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Andy Jassy Becoming the new CEO of Amazon: theCUBE Analysis


 

>> Narrator: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> As you know by now, Jeff Bezos, CEO of Amazon, is stepping aside from his CEO role and AWS CEO, Andy Jassy, is being promoted to head all of Amazon. Bezos, of course, is going to remain executive chairman. Now, 15 years ago, next month, Amazon launched it's simple storage service, which was the first modern cloud offering. And the man who wrote the business plan for AWS, was Andy Jassy, and he's navigated the meteoric rise and disruption that has seen AWS grow into a $45 billion company that draws off the vast majority of Amazon's operating profits. No one in the media has covered Jassy more intimately and closely than John Furrier, the founder of SiliconANGLE. And John joins us today to help us understand on theCUBE this move and what we can expect from Jassy in his new role, and importantly what it means for AWS. John, thanks for taking the time to speak with us. >> Hey, great day. Great to see you as always, we've done a lot of interviews together over the years and we're on our 11th year with theCUBE and SiliconANGLE. But I got to be excited too, that we're simulcasters on Clubhouse, which is kind of cool. Love Clubhouse but not since the, in December. It's awesome. It's like Cube radio. It's like, so this is a Cube talk. So we opened up a Clubhouse room while we're filming this. We'll do more live hits in studio and syndicate the Clubhouse and then take questions after. This is a huge digital transformation moment. I'm part of the digital transformation club on Clubhouse which has almost 5,000 followers at the moment and also has like 500 members. So if you're not on Clubhouse, yet, if you have an iPhone go check it out and join the digital transformation club. Android users you'll have to wait until that app is done but it's really a great club. And Jeremiah Owyang is also doing a lot of stuff on digital transformation. >> Or you can just buy an iPhone and get in. >> Yeah, that's what people are doing. I can see all the influences are on there but to me, the digital transformation, it's always been kind of a cliche, the consumerization of IT, information technology. This has been the boring world of the enterprise over the past, 20 years ago. Enterprise right now is super hot because there's no distinction between enterprise and society. And that's clearly the, because of the rise of cloud computing and the rise of Amazon Web Services which was a side project at AWS, at Amazon that Andy Jassy did. And it wasn't really pleasant at the beginning. It was failed. It failed a lot and it wasn't as successful as people thought in the early days. And I have a lot of stories with Andy that he told me a lot of the inside baseball and we'll share that here today. But we started covering Amazon since the beginning. I was as an entrepreneur. I used it when it came out and a huge fan of them as a company because they just got a superior product and they have always had been but it was very misunderstood from the beginning. And now everyone's calling it the most important thing. And Andy now is becoming Andy Jassy, the most important executive in the world. >> So let's get it to the, I mean, look at, you said to me over holidays, you thought this might have something like this could happen. And you said, Jassy is probably in line to get this. So, tell us, what can you tell us about Jassy? Why is he qualified for this job? What do you think he brings to the table? >> Well, the thing that I know about Amazon everyone's been following the Amazon news is, Jeff Bezos has a lot of personal turmoil. They had his marriage fail. They had some issues with the smear campaigns and all this stuff going on, the run-ins with Donald Trump, he bought the Washington post. He's got a lot of other endeavors outside of Amazon cause he's the second richest man in the world competing with Elon Musk at Space X versus Blue Origin. So the guy's a billionaire. So Amazon is his baby and he's been running it as best he could. He's got an executive team committee they called the S team. He's been grooming people in the company and that's just been his mode. And the rise of AWS and the business performance that we've been documenting on SiliconANGLE and theCUBE, it's just been absolutely changing the game on Amazon as a company. So clearly Amazon Web Services become a driving force of the new Amazon that's emerging. And obviously they've got all their retail business and they got the gaming challenges and they got the studios and the other diversified stuff. So Jassy is just, he's just one of those guys. He's just been an Amazonian from day one. He came out of Harvard business school, drove across the country, very similar story to Jeff Bezos. He did that in 1997 and him and Jeff had been collaborating and Jeff tapped him to be his shadow, they call it, which is basically technical assistance and an heir apparent and groomed him. And then that's how it is. Jassy is not a climber as they call it in corporate America. He's not a person who is looking for a political gain. He's not a territory taker, but he's a micromanager. He loves details and he likes to create customer value. And that's his focus. So he's not a grandstander. In fact, he's been very low profile. Early days when we started meeting with him, he wouldn't meet with press regularly because they weren't writing the right stories. And everyone is, he didn't know he was misunderstood. So that's classic Amazon. >> So, he gave us the time, I think it was 2014 or 15 and he told us a story back then, John, you might want to share it as to how AWS got started. Why, what was the main spring Amazon's tech wasn't working that great? And Bezos said to Jassy, going to go figure out why and maybe explain how AWS was born. >> Yeah, we had, in fact, we were the first ones to get access to do his first public profile. If you go to the Google and search Andy Jassy, the trillion dollar baby, we had a post, we put out the story of AWS, Andy Jassy's trillion dollar baby. This was in early, this was January 2015, six years ago. And, we back then, we posited that this would be a trillion dollar total addressable market. Okay, people thought we were crazy but we wrote a story and he gave us a very intimate access. We did a full drill down on him and the person, the story of Amazon and that laid out essentially the beginning of the rise of AWS and Andy Jassy. So that's a good story to check out but really the key here is, is that he's always been relentless and competitive on creating value in what they call raising the bar outside Amazon. That's a term that they use. They also have another leadership principle called working backwards, which is like, go to the customer and work backwards from the customer in a very Steve Job's kind of way. And that's been kind of Jobs mentality as well at Apple that made them successful work backwards from the customer and make things easier. And that was Apple. Amazon, their philosophy was work backwards from the customer and Jassy specifically would say it many times and eliminate the undifferentiated heavy lifting. That was a key principle of what they were doing. So that was a key thesis of their entire business model. And that's the Amazonian way. Faster, cheaper, ship it faster, make it less expensive and higher value. While when you apply the Amazon shipping concept to cloud computing, it was completely disrupted. They were shipping code and services faster and that became their innovation strategy. More announcements every year, they out announced their competition by huge margin. They introduced new services faster and they're less expensive some say, but in the aggregate, they make more money but that's kind of a key thing. >> Well, when you, I was been listening to the TV today and there was a debate on whether or not, this support tends that they'll actually split the company into two. To me, I think it's just the opposite. I think it's less likely. I mean, if you think about Amazon getting into grocery or healthcare, eventually financial services or other industries and the IOT opportunity to me, what they do, John, is they bring in together the cloud, data and AI and they go attack these new industries. I would think Jassy of all people would want to keep this thing together now whether or not the government allows them to do that. But what are your thoughts? I mean, you've asked Andy this before in your personal interviews about splitting the company. What are your thoughts? >> Well, Jon Fortt at CNBC always asked the same question every year. It's almost like the standard question. I kind of laugh and I ask it now too because I liked Jon Fortt. I think he's an awesome dude. And I'll, it's just a tongue in cheek, Jassy. He won't answer the question. Amazon, Bezos and Jassy have one thing in common. They're really good at not answering questions. So if you ask the same question. They'll just say, nothing's ever, never say never, that's his classic answer to everything. Never say never. And he's always said that to you. (chuckles) Some say, he's, flip-flopped on things but he's really customer driven. For example, he said at one point, no one should ever build a data center. Okay, that was a principle. And then they come out and they have now a hybrid strategy. And I called them out on that and said, hey, what, are you flip-flopping? You said at some point, no one should have a data center. He's like, well, we looked at it differently and what we meant was is that, it should all be cloud native. Okay. So that's kind of revision, but he's cool with that. He says, hey, we'll revise based on what customers are doing. VMware working with Amazon that no one ever thought that would happen. Okay. So, VMware has some techies, Raghu, for instance, over there, super top notch. He worked with Jassy, directly in his team Sanjay Poonen when they went to business school together, they cut a deal. And now Amazon essentially saved VMware, in my opinion. And Pat Gelsinger drove that deal. Now, Pat Gelsinger, CEO, Intel, and Pat told me that directly in candid conversation off theCUBE, he said, hey, we have to make a decision either we're going to be in cloud or we're not going to be in cloud, we will partner. And I'll see, he was Intel. He understood the Intel inside mentality. So that's good for VMware. So Jassy does these kinds of deals. He's not afraid he's got a good stomach for business and a relentless competitor. >> So, how do you think as you mentioned Jassy is a micromanager. He gets deep into the technology. Anybody who's seen his two hour, three hour keynotes. No, he has a really fine grasp of the technology across the entire stack. How do you think John, he will approach things like antitrust, the big tech lash of the unionization of the workforce at Amazon? How do you think Jassy will approach that? >> Well, I think one of the things that emerges Jassy, first of all, he's a huge sports fan. And many people don't know that but he's also progressive person. He's very progressive politically. He's been on the record and off the record saying things like, obviously, literacy has been big on, he's been on basically unrepresented minorities, pushing for that, and certainly cloud computing in tech, women in tech, he's been a big proponent. He's been a big supporter of Teresa Carlson. Who's been rising star at Amazon. People don't know who Teresa Carlson is and they should check out her. She's become one of the biggest leaders inside Amazon she's turned around public sector from the beginning. She ran that business, she's a global star. He's been a great leader and he's been getting, forget he's a micromanager, he's on top of the details. I mean, the word is, and nothing gets approved without Andy, Andy seeing it. But he's been progressive. He's been an Amazon original as they call it internally. He's progressive, he's got the business acumen but he's perfect for this pragmatic conversation that needs to happen. And again, because he's so technically strong having a CEO that's that proficient is going to give Amazon an advantage when they have to go in and change how DC works, for instance, or how the government geopolitical landscape works, because Amazon is now a global company with regions all over the place. So, I think he's pragmatic, he's open to listening and changing. I think that's a huge quality >> Well, when you think of this, just to set the context here for those who may not know, I mean, Amazon started as I said back in 2006 in March with simple storage service that later that year they announced EC2 which is their compute platform. And that was the majority of their business, is still a very large portion of their business but Amazon, our estimates are that in 2020, Amazon did 45 billion, 45.4 billion in revenue. That's actually an Amazon reported number. And just to give you a context, Azure about 26 billion GCP, Google about 6 billion. So you're talking about an industry that Amazon created. That's now $78 billion and Amazon at 45 billion. John they're growing at 30% annually. So it's just a massive growth engine. And then another story Jassy told us, is they, he and Jeff and the team talked early on about whether or not they should just sort of do an experiment, do a little POC, dip their toe in and they decided to go for it. Let's go big or go home as Michael Dell has said to us many times, I mean, pretty astounding. >> Yeah. One of the things about Jassy that people should know about, I think there's some compelling relative to the newest ascension to the CEO of Amazon, is that he's not afraid to do new things. For instance, I'll give you an example. The Amazon Web Services re-invent their annual conference grew to being thousands and thousands of people. And they would have a traditional after party. They called a replay, they'd have a band like every tech conference and their conference became so big that essentially, it was like setting up a live concert. So they were spending millions of dollars to set up basically a one night concert and they'd bring in great, great artists. So he said, hey, what's been all this cash? Why don't we just have a festival? So they did a thing called Intersect. They got LA involved from creatives and they basically built a weekend festival in the back end of re-invent. This was when real life was, before COVID and they turned into an opportunity because that's the way they think. They like to look at the resources, hey, we're already all in on this, why don't we just keep it for the weekend and charge some tickets and have a good time. He's not afraid to take chances on the product side. He'll go in and take a chance on a new market. That comes from directly from Bezos. They try stuff. They don't mind failing but they put a tight leash on measurement. They work backwards from the customer and they are not afraid to take chances. So, that's going to board well for him as he tries to figure out how Amazon navigates the contention on the political side when they get challenged for their dominance. And I think he's going to have to apply that pragmatic experimentation to new business models. >> So John I want you to take on AWS. I mean, despite the large numbers, I talked about 30% growth, Azure is growing at over 50% a year, GCP at 83%. So despite the large numbers and big growth the growth rates are slowing. Everybody knows that, we've reported it extensively. So the incoming CEO of Amazon Web Services has a TAM expansion challenge. And at some point they've got to decide, okay, how do we keep this growth engine? So, do you have any thoughts as to who might be the next CEO and what are some of their challenges as you see it? >> Well, Amazon is a real product centric company. So it's going to be very interesting to see who they go with here. Obviously they've been grooming a lot of people. There's been some turnover. You had some really strong executives recently leave, Jeff Wilkes, who was the CEO of the retail business. He retired a couple of months ago, formerly announced I think recently, he was probably in line. You had Mike Clayville, is now the chief revenue officer of Stripe. He ran all commercial business, Teresa Carlson stepped up to his role as well as running public sector. Again, she got more power. You have Matt Garman who ran the EC2 business, Stanford grad, great guy, super strong on the product side. He's now running all commercial sales and marketing. And he's also on the, was on Bezos' S team, that's the executive kind of team. Peter DeSantis is also on that S team. He runs all infrastructure. He took over for James Hamilton, who was the genius behind all the data center work that they've done and all the chip design stuff that they've innovated on. So there's so much technical innovation going on. I think you still going to see a leadership probably come from, I would say Matt Garman, in my opinion is the lead dog at this point, he's the lead horse. You could have an outside person come in depending upon how, who might be available. And that would probably come from an Andy Jassy network because he's a real fierce competitor but he's also a loyalist and he likes trust. So if someone comes in from the outside, it's going to be someone maybe he trusts. And then the other wildcards are like Teresa Carlson. Like I said, she is a great woman in tech who's done amazing work. I've profiled her many times. We've interviewed her many times. She took that public sector business with Amazon and changed the game completely. Outside the Jedi contract, she was in competitive for, had the big Trump showdown with the Jedi, with the department of defense. Had the CIA cloud. Amazon set the standard on public sector and that's directly the result of Teresa Carlson. But she's in the field, she's not a product person, she's kind of running that group. So Amazon has that product field kind of structure. So we'll see how they handle that. But those are the top three I think are going to be in line. >> So the obvious question that people always ask and it is a big change like this is, okay, in this case, what is Jassy going to bring in? And what's going to change? Maybe the flip side question is somewhat more interesting. What's not going to change in your view? Jassy has been there since nearly the beginning. What are some of the fundamental tenets that he's, that are fossilized, that won't change, do you think? >> I think he's, I think what's not going to change is Amazon, is going to continue to grow and develop their platform business and enable more SaaS players. That's a little bit different than what Microsoft's doing. They're more SaaS oriented, Office 365 is becoming their biggest application in terms of revenue on Microsoft side. So Amazon is going to still have to compete and enable more ecosystem partners. I think what's not going to change is that Bezos is still going to be in charge because executive chairman is just a code word for "not an active CEO." So in the corporate governance world when you have an executive chairman, that's essentially the person still in charge. And so he'll be in charge, will still be the boss of Andy Jassy and Jassy will be running all of Amazon. So I think that's going to be a little bit the same, but Jassy is going to be more in charge. I think you'll see a team change over, whether you're going to see some new management come in, Andy's management team will expand, I think Amazon will stay the same, Amazon Web Services. >> So John, last night, I was just making some notes about notable transitions in the history of the tech business, Gerstner to Palmisano, Gates to Ballmer, and then Ballmer to Nadella. One that you were close to, David Packard to John Young and then John Young to Lew Platt at the old company. Ellison to Safra and Mark, Jobs to Cook. We talked about Larry Page to Sundar Pichai. So how do you see this? And you've talked to, I remember when you interviewed John Chambers, he said, there is no rite of passage, East coast mini-computer companies, Edson de Castro, Ken Olsen, An Wang. These were executives who wouldn't let go. So it's of interesting to juxtapose that with the modern day executive. How do you see this fitting in to some of those epic transitions that I just mentioned? >> I think a lot of people are surprised at Jeff Bezos', even stepping down. I think he's just been such the face of Amazon. I think some of the poll numbers that people are doing on Twitter, people don't think it's going to make a big difference because he's kind of been that, leader hand on the wheel, but it's been its own ship now, kind of. And so depending on who's at the helm, it will be different. I think the Amazon choice of Andy wasn't obvious. And I think a lot of people were asking the question who was Andy Jassy and that's why we're doing this. And we're going to be doing more features on the Andy Jassy. We got a tons, tons of content that we've we've had shipped, original content with them. We'll share more of those key soundbites and who he is. I think a lot of people scratching their head like, why Andy Jassy? It's not obvious to the outsiders who don't know cloud computing. If you're in the competing business, in the digital transformation side, everyone knows about Amazon Web Services. Has been the most successful company, in my opinion, since I could remember at many levels just the way they've completely dominated the business and how they change others to be dominant. So, I mean, they've made Microsoft change, it made Google change and even then he's a leader that accepts conversations. Other companies, their CEOs hide behind their PR wall and they don't talk to people. They won't come on Clubhouse. They won't talk to the press. They hide behind their PR and they feed them, the media. Jassy is not afraid to talk to reporters. He's not afraid to talk to people, but he doesn't like people who don't know what they're talking about. So he doesn't suffer fools. So, you got to have your shit together to talk to Jassy. That's really the way it is. And that's, and he'll give you mind share, like he'll answer any question except for the ones that are too tough for him to answer. Like, are you, is facial recognition bad or good? Are you going to spin out AWS? I mean these are the hard questions and he's got a great team. He's got Jay Carney, former Obama press secretary working for him. He's been a great leader. So I'm really bullish on, is a good choice. >> We're going to jump into the Clubhouse here and open it up shortly. John, the last question for you is competition. Amazon as a company and even Jassy specifically I always talk about how they don't really focus on the competition, they focus on the customer but we know that just observing these folks Bezos is very competitive individual. Jassy, I mean, you know him better than I, very competitive individual. So, and he's, Jassy has been known to call out Oracle. Of course it was in response to Larry Ellison's jabs at Amazon regarding database. But, but how do you see that? Do you see that changing at all? I mean, will Amazon get more publicly competitive or they stick to their knitting, you think? >> You know this is going to sound kind of a weird analogy. And I know there's a lot of hero worshiping on Elon Musk but Elon Musk and Andy Jassy have a lot of similarities in the sense of their brilliance. They got both a brilliant people, different kinds of backgrounds. Obviously, they're running different things. They both are builders, right? If you were listening to Elon Musk on Clubhouse the other night, what was really striking was not only the magic of how it was all orchestrated and what he did and how he interviewed Robin Hood. He basically is about building stuff. And he was asked questions like, what advice do you give startups? He's like, if you need advice you shouldn't be doing startups. That's the kind of mentality that Jassy has, which is, it's not easy. It's not for the faint of heart, but Elon Musk is a builder. Jassy builds, he likes to build stuff, right? And so you look at all the things that he's done with AWS, it's been about enabling people to be successful with the tools that they need, adding more services, creating things that are lower price point. If you're an entrepreneur and you're over the age of 30, you know about AWS because you know what, it's cheaper to start a business on Amazon Web Services than buying servers and everyone knows that. If you're under the age of 25, you might not know 50 grand to a hundred thousand just to start something. Today you get your credit card down, you're up and running and you can get Clubhouses up and running all day long. So the next Clubhouse will be on Amazon or a cloud technology. And that's because of Andy Jassy right? So this is a significant executive and he continue, will bring that mindset of building. So, I think the digital transformation, we're in the digital engine club, we're going to see a complete revolution of a new generation. And I think having a new leader like Andy Jassy will enable in my opinion next generation talent, whether that's media and technology convergence, media technology and art convergence and the fact that he digs music, he digs sports, he digs tech, he digs media, it's going to be very interesting to see, I think he's well-poised to be, and he's soft-spoken, he doesn't want the glamorous press. He doesn't want the puff pieces. He just wants to do what he does and he puts his game do the talking. >> Talking about advice at startups. Just a quick aside. I remember, John, you and I when we were interviewing Scott McNealy former CEO of Sun Microsystems. And you asked him advice for startups. He said, move out of California. It's kind of tongue in cheek. I heard this morning that there's a proposal to tax the multi-billionaires of 1% annually not just the one-time tax. And so Jeff Bezos of course, has a ranch in Texas, no tax there, but places all over. >> You see I don't know. >> But I don't see Amazon leaving Seattle anytime soon, nor Jassy. >> Jeremiah Owyang did a Clubhouse on California. And the basic sentiment is that, it's California is not going away. I mean, come on. People got to just get real. I think it's a fad. Yeah. This has benefits with remote working, no doubt, but people will stay here in California, the network affects beautiful. I think Silicon Valley is going to continue to be relevant. It's just going to syndicate differently. And I think other hubs like Seattle and around the world will be integrated through remote work and I think it's going to be much more of a democratizing effect, not a win lose. So that to me is a huge shift. And look at Amazon, look at Amazon and Microsoft. It's the cloud cities, so people call Seattle. You've got Google down here and they're making waves but still, all good stuff. >> Well John, thanks so much. Let's let's wrap and let's jump into the Clubhouse and hear from others. Thanks so much for coming on, back on theCUBE. And many times we, you and I've done this really. It was a pleasure having you. Thanks for your perspectives. And thank you for watching everybody, this is Dave Vellante for theCUBE. We'll see you next time. (soft ambient music)

Published Date : Feb 4 2021

SUMMARY :

leaders all around the world. the time to speak with us. and syndicate the Clubhouse Or you can just buy I can see all the influences are on there So let's get it to and the other diversified stuff. And Bezos said to Jassy, And that's the Amazonian way. and the IOT opportunity And he's always said that to you. of the technology across the entire stack. I mean, the word is, And just to give you a context, and they are not afraid to take chances. I mean, despite the large numbers, and that's directly the So the obvious question So in the corporate governance world So it's of interesting to juxtapose that and how they change others to be dominant. on the competition, over the age of 30, you know about AWS not just the one-time tax. But I don't see Amazon leaving and I think it's going to be much more into the Clubhouse and hear from others.

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Zhamak Dehghani, ThoughtWorks | theCUBE on Cloud 2021


 

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle in 2000 >>nine. Hal Varian, Google's chief economist, said that statisticians would be the sexiest job in the coming decade. The modern big data movement >>really >>took off later in the following year. After the Second Hadoop World, which was hosted by Claudette Cloudera in New York City. Jeff Ham Abakar famously declared to me and John further in the Cube that the best minds of his generation, we're trying to figure out how to get people to click on ads. And he said that sucks. The industry was abuzz with the realization that data was the new competitive weapon. Hadoop was heralded as the new data management paradigm. Now, what actually transpired Over the next 10 years on Lee, a small handful of companies could really master the complexities of big data and attract the data science talent really necessary to realize massive returns as well. Back then, Cloud was in the early stages of its adoption. When you think about it at the beginning of the last decade and as the years passed, Maurin Mawr data got moved to the cloud and the number of data sources absolutely exploded. Experimentation accelerated, as did the pace of change. Complexity just overwhelmed big data infrastructures and data teams, leading to a continuous stream of incremental technical improvements designed to try and keep pace things like data Lakes, data hubs, new open source projects, new tools which piled on even Mawr complexity. And as we reported, we believe what's needed is a comm pleat bit flip and how we approach data architectures. Our next guest is Jean Marc de Connie, who is the director of emerging technologies That thought works. John Mark is a software engineer, architect, thought leader and adviser to some of the world's most prominent enterprises. She's, in my view, one of the foremost advocates for rethinking and changing the way we create and manage data architectures. Favoring a decentralized over monolithic structure and elevating domain knowledge is a primary criterion. And how we organize so called big data teams and platforms. Chamakh. Welcome to the Cube. It's a pleasure to have you on the program. >>Hi, David. This wonderful to be here. >>Well, okay, so >>you're >>pretty outspoken about the need for a paradigm shift in how we manage our data and our platforms that scale. Why do you feel we need such a radical change? What's your thoughts there? >>Well, I think if you just look back over the last decades you gave us, you know, a summary of what happened since 2000 and 10. But if even if we go before then what we have done over the last few decades is basically repeating and, as you mentioned, incrementally improving how we've managed data based on a certain assumptions around. As you mentioned, centralization data has to be in one place so we can get value from it. But if you look at the parallel movement off our industry in general since the birth of Internet, we are actually moving towards decentralization. If we think today, like if this move data side, if he said the only way Web would work the only way we get access to you know various applications on the Web pages is to centralize it. We would laugh at that idea, but for some reason we don't. We don't question that when it comes to data, right? So I think it's time to embrace the complexity that comes with the growth of number of sources, the proliferation of sources and consumptions models, you know, embrace the distribution of sources of data that they're not just within one part of organization. They're not just within even bounds of organization there beyond the bounds of organization. And then look back and say Okay, if that's the trend off our industry in general, Um, given the fabric of computation and data that we put in, you know globally in place, then how the architecture and technology and organizational structure incentives need to move to embrace that complexity. And to me, that requires a paradigm shift, a full stack from how we organize our organizations, how we organize our teams, how we, you know, put a technology in place, um, to to look at it from a decentralized angle. >>Okay, so let's let's unpack that a little bit. I mean, you've spoken about and written that today's big architecture and you basically just mentioned that it's flawed, So I wanna bring up. I love your diagrams of a simple diagram, guys, if you could bring up ah, figure one. So on the left here we're adjusting data from the operational systems and other enterprise data sets and, of course, external data. We cleanse it, you know, you've gotta do the do the quality thing and then serve them up to the business. So So what's wrong with that picture that we just described and give granted? It's a simplified form. >>Yeah, quite a few things. So, yeah, I would flip the question may be back to you or the audience if we said that. You know, there are so many sources off the data on the Actually, the data comes from systems and from teams that are very diverse in terms off domains. Right? Domain. If if you just think about, I don't know retail, Uh, the the E Commerce versus Order Management versus customer This is a very diverse domains. The data comes from many different diverse domains. And then we expect to put them under the control off a centralized team, a centralized system. And I know that centralization. Probably if you zoom out, it's centralized. If you zoom in it z compartmentalized based on functions that we can talk about that and we assume that the centralized model will be served, you know, getting that data, making sense of it, cleansing and transforming it then to satisfy in need of very diverse set of consumers without really understanding the domains, because the teams responsible for it or not close to the source of the data. So there is a bit of it, um, cognitive gap and domain understanding Gap, um, you know, without really understanding of how the data is going to be used, I've talked to numerous. When we came to this, I came up with the idea. I talked to a lot of data teams globally just to see, you know, what are the pain points? How are they doing it? And one thing that was evident in all of those conversations that they actually didn't know after they built these pipelines and put the data in whether the data warehouse tables or like, they didn't know how the data was being used. But yet the responsible for making the data available for these diverse set of these cases, So s centralized system. A monolithic system often is a bottleneck. So what you find is, a lot of the teams are struggling with satisfying the needs of the consumers, the struggling with really understanding the data. The domain knowledge is lost there is a los off understanding and kind of in that in that transformation. Often, you know, we end up training machine learning models on data that is not really representative off the reality off the business. And then we put them to production and they don't work because the semantic and the same tax off the data gets lost within that translation. So we're struggling with finding people thio, you know, to manage a centralized system because there's still the technology is fairly, in my opinion, fairly low level and exposes the users of those technologies. I said, Let's say warehouse a lot off, you know, complexity. So in summary, I think it's a bottleneck is not gonna, you know, satisfy the pace of change, of pace, of innovation and the pace of, you know, availability of sources. Um, it's disconnected and fragmented, even though the centralizes disconnected and fragmented from where the data comes from and where the data gets used on is managed by, you know, a team off hyper specialized people that you know, they're struggling to understand the actual value of the data, the actual format of the data, so it's not gonna get us where our aspirations and ambitions need to be. >>Yes. So the big data platform is essentially I think you call it, uh, context agnostic. And so is data becomes, you know, more important, our lives. You've got all these new data sources, you know, injected into the system. Experimentation as we said it with the cloud becomes much, much easier. So one of the blockers that you've started, you just mentioned it is you've got these hyper specialized roles the data engineer, the quality engineer, data scientists and and the It's illusory. I mean, it's like an illusion. These guys air, they seemingly they're independent and in scale independently. But I think you've made the point that in fact, they can't that a change in the data source has an effect across the entire data lifecycle entire data pipeline. So maybe you could maybe you could add some color to why that's problematic for some of the organizations that you work with and maybe give some examples. >>Yeah, absolutely so in fact, that initially the hypothesis around that image came from a Siris of requests that we received from our both large scale and progressive clients and progressive in terms of their investment in data architectures. So this is where clients that they were there were larger scale. They had divers and reached out of domains. Some of them were big technology tech companies. Some of them were retail companies, big health care companies. So they had that diversity off the data and the number off. You know, the sources of the domains they had invested for quite a few years in, you know, generations. If they had multi generations of proprietary data warehouses on print that they were moving to cloud, they had moved to the barriers, you know, revisions of the Hadoop clusters and they were moving to the cloud. And they the challenges that they were facing were simply there were not like, if I want to just, like, you know, simplifying in one phrase, they were not getting value from the data that they were collecting. There were continuously struggling Thio shift the culture because there was so much friction between all of these three phases of both consumption of the data and transformation and making it available consumption from sources and then providing it and serving it to the consumer. So that whole process was full of friction. Everybody was unhappy. So its bottom line is that you're collecting all this data. There is delay. There is lack of trust in the data itself because the data is not representative of the reality has gone through a transformation. But people that didn't understand really what the data was got delayed on bond. So there is no trust. It's hard to get to the data. It's hard to create. Ultimately, it's hard to create value from the data, and people are working really hard and under a lot of pressure. But it's still, you know, struggling. So we often you know, our solutions like we are. You know, Technologies will often pointed to technology. So we go. Okay, This this version of you know, some some proprietary data warehouse we're using is not the right thing. We should go to the cloud, and that certainly will solve our problems. Right? Or warehouse wasn't a good one. Let's make a deal Lake version. So instead of you know, extracting and then transforming and loading into the little bits. And that transformation is that, you know, heavy process, because you fundamentally made an assumption using warehouses that if I transform this data into this multi dimensional, perfectly designed schema that then everybody can run whatever choir they want that's gonna solve. You know everybody's problem, but in reality it doesn't because you you are delayed and there is no universal model that serves everybody's need. Everybody that needs the divers data scientists necessarily don't don't like the perfectly modeled data. They're looking for both signals and the noise. So then, you know, we've We've just gone from, uh, et elles to let's say now to Lake, which is okay, let's move the transformation to the to the last mile. Let's just get load the data into, uh into the object stores into semi structured files and get the data. Scientists use it, but they're still struggling because the problems that we mentioned eso then with the solution. What is the solution? Well, next generation data platform, let's put it on the cloud, and we sell clients that actually had gone through, you know, a year or multiple years of migration to the cloud. But with it was great. 18 months I've seen, you know, nine months migrations of the warehouse versus two year migrations of the various data sources to the clubhouse. But ultimately, the result is the same on satisfy frustrated data users, data providers, um, you know, with lack of ability to innovate quickly on relevant data and have have have an experience that they deserve toe have have a delightful experience off discovering and exploring data that they trust. And all of that was still a missed so something something else more fundamentally needed to change than just the technology. >>So then the linchpin to your scenario is this notion of context and you you pointed out you made the other observation that look, we've made our operational systems context aware. But our data platforms are not on bond like CRM system sales guys very comfortable with what's in the CRM system. They own the data. So let's talk about the answer that you and your colleagues are proposing. You're essentially flipping the architecture whereby those domain knowledge workers, the builders, if you will, of data products or data services there now, first class citizens in the data flow and they're injecting by design domain knowledge into the system. So So I wanna put up another one of your charts. Guys, bring up the figure to their, um it talks about, you know, convergence. You showed data distributed domain, dream and architecture. Er this self serve platform design and this notion of product thinking. So maybe you could explain why this approach is is so desirable, in your view, >>sure. The motivation and inspiration for the approach came from studying what has happened over the last few decades in operational systems. We had a very similar problem prior to micro services with monolithic systems, monolithic systems where you know the bottleneck. Um, the changes we needed to make was always, you know, our fellow Noto, how the architecture was centralized and we found a nice nation. I'm not saying this is the perfect way of decoupling a monolith, but it's a way that currently where we are in our journey to become data driven, um is a nice place to be, um, which is distribution or decomposition off your system as well as organization. I think when we whenever we talk about systems, we've got to talk about people and teams that's responsible for managing those systems. So the decomposition off the systems and the teams on the data around domains because that's how today we are decoupling our business, right? We're decoupling our businesses around domains, and that's a that's a good thing and that What does that do really for us? What it does? Is it localizes change to the bounded context of fact business. It creates clear boundary and interfaces and contracts between the rest of the universe of the organization on that particular team, so removes the friction that often we have for both managing the change and both serving data or capability. So it's the first principle of data meshes. Let's decouple this world off analytical data the same to mirror the same way we have to couple their systems and teams and business why data is any different. And the moment you do that, So you, the moment you bring the ownership to people who understands the data best, then you get questions that well, how is that any different from silence that's connected databases that we have today and nobody can get to the data? So then the rest of the principles is really to address all of the challenges that comes with this first principle of decomposition around domain Context on the second principle is well, we have to expect a certain level off quality and accountability and responsibility for the teams that provide the data. So let's bring product thinking and treating data as a product to the data that these teams now, um share and let's put accountability around. And we need a new set of incentives and metrics for domain teams to share the data. We need to have a new set off kind of quality metrics that define what it means for the data to be a product. And we can go through that conversation perhaps later eso then the second principle is okay. The teams now that are responsible, the domain teams responsible for the analytical data need to provide that data with a certain level of quality and assurance. Let's call that a product and bring products thinking to that. And then the next question you get asked off by C. E. O s or city or the people who build the infrastructure and, you know, spend the money. They said, Well, it's actually quite complex to manage big data, and now we're We want everybody, every independent team to manage the full stack of, you know, storage and computation and pipelines and, you know, access, control and all of that. And that's well, we have solved that problem in operational world. And that requires really a new level of platform thinking toe provide infrastructure and tooling to the domain teams to now be able to manage and serve their big data. And that I think that requires reimagining the world of our tooling and technology. But for now, let's just assume that we need a new level of abstraction to hide away ton of complexity that unnecessarily people get exposed to and that that's the third principle of creating Selves of infrastructure, um, to allow autonomous teams to build their domains. But then the last pillar, the last you know, fundamental pillar is okay. Once you distributed problem into a smaller problems that you found yourself with another set of problems, which is how I'm gonna connect this data, how I'm gonna you know, that the insights happens and emerges from the interconnection of the data domains right? It does not necessarily locked into one domain. So the concerns around interoperability and standardization and getting value as a result of composition and interconnection of these domains requires a new approach to governance. And we have to think about governance very differently based on a Federated model and based on a computational model. Like once we have this powerful self serve platform, we can computational e automate a lot of governance decisions. Um, that security decisions and policy decisions that applies to you know, this fabric of mesh not just a single domain or not in a centralized. Also, really. As you mentioned that the most important component of the emissions distribution of ownership and distribution of architecture and data the rest of them is to solve all the problems that come with that. >>So very powerful guys. We actually have a picture of what Jamaat just described. Bring up, bring up figure three, if you would tell me it. Essentially, you're advocating for the pushing of the pipeline and all its various functions into the lines of business and abstracting that complexity of the underlying infrastructure, which you kind of show here in this figure, data infrastructure is a platform down below. And you know what I love about this Jama is it to me, it underscores the data is not the new oil because I could put oil in my car I can put in my house, but I can't put the same court in both places. But I think you call it polyglot data, which is really different forms, batch or whatever. But the same data data doesn't follow the laws of scarcity. I can use the same data for many, many uses, and that's what this sort of graphic shows. And then you brought in the really important, you know, sticking problem, which is that you know the governance which is now not a command and control. It's it's Federated governance. So maybe you could add some thoughts on that. >>Sure, absolutely. It's one of those I think I keep referring to data much as a paradigm shift. And it's not just to make it sound ground and, you know, like, kind of ground and exciting or in court. And it's really because I want to point out, we need to question every moment when we make a decision around how we're going to design security or governance or modeling off the data, we need to reflect and go back and say, um, I applying some of my cognitive biases around how I have worked for the last 40 years, I have seen it work. Or do I do I really need to question. And we do need to question the way we have applied governance. I think at the end of the day, the rule of the data governance and objective remains the same. I mean, we all want quality data accessible to a diverse set of users. And these users now have different personas, like David, Personal data, analyst data, scientists, data application, Um, you know, user, very diverse personal. So at the end of the day, we want quality data accessible to them, um, trustworthy in in an easy consumable way. Um, however, how we get there looks very different in as you mentioned that the governance model in the old world has been very commander control, very centralized. Um, you know, they were responsible for quality. They were responsible for certification off the data, you know, applying making sure the data complies. But also such regulations Make sure you know, data gets discovered and made available in the world of the data mesh. Really. The job of the data governance as a function becomes finding that equilibrium between what decisions need to be um, you know, made and enforced globally. And what decisions need to be made locally so that we can have an interoperable measure. If data sets that can move fast and can change fast like it's really about instead of hardest, you know, kind of putting the putting those systems in a straitjacket of being constant and don't change, embrace, change and continuous change of landscape because that's that's just the reality we can't escape. So the role of governance really the governance model called Federated and Computational. And by that I mean, um, every domain needs to have a representative in the governance team. So the role of the data or domain data product owner who really were understand the data that domain really well but also wears that hacks of a product owner. It is an important role that had has to have a representation in the governance. So it's a federation off domains coming together, plus the SMEs and people have, you know, subject matter. Experts who understands the regulations in that environmental understands the data security concerns, but instead off trying to enforce and do this as a central team. They make decisions as what need to be standardized, what need to be enforced. And let's push that into that computational E and in an automated fashion into the into the camp platform itself. For example, instead of trying to do that, you know, be part of the data quality pipeline and inject ourselves as people in that process, let's actually, as a group, define what constitutes quality, like, how do we measure quality? And then let's automate that and let Z codify that into the platform so that every native products will have a C I City pipeline on as part of that pipeline. Those quality metrics gets validated and every day to product needs to publish those SLOC or service level objectives. So you know, whatever we choose as a measure of quality, maybe it's the, you know, the integrity of the data, the delay in the data, the liveliness of it, whatever the are the decisions that you're making, let's codify that. So it's, um, it's really, um, the role of the governance. The objectives of the governance team tried to satisfies the same, but how they do it. It is very, very different. I wrote a new article recently trying to explain the logical architecture that would emerge from applying these principles. And I put a kind of light table to compare and contrast the roll off the You know how we do governance today versus how we will do it differently to just give people a flavor of what does it mean to embrace the centralization? And what does it mean to embrace change and continuous change? Eso hopefully that that that could be helpful. >>Yes, very so many questions I haven't but the point you make it to data quality. Sometimes I feel like quality is the end game. Where is the end game? Should be how fast you could go from idea to monetization with the data service. What happens again? You sort of address this, but what happens to the underlying infrastructure? I mean, spinning a PC to S and S three buckets and my pie torches and tensor flows. And where does that that lives in the business? And who's responsible for that? >>Yeah, that's I'm glad you're asking this question. Maybe because, um, I truly believe we need to re imagine that world. I think there are many pieces that we can use Aziz utilities on foundational pieces, but I but I can see for myself a 5 to 7 year roadmap of building this new tooling. I think, in terms of the ownership, the question around ownership, if that would remains with the platform team, but and perhaps the domain agnostic, technology focused team right that there are providing instead of products themselves. And but the products are the users off those products are data product developers, right? Data domain teams that now have really high expectations in terms of low friction in terms of lead time to create a new data product. Eso We need a new set off tooling, and I think with the language needs to shift from, You know, I need a storage buckets. So I need a storage account. So I need a cluster to run my, you know, spark jobs, too. Here's the declaration of my data products. This is where the data for it will come from. This is the data that I want to serve. These are the policies that I need toe apply in terms of perhaps encryption or access control. Um, go make it happen. Platform, go provision, Everything that I mean so that as a data product developer. All I can focus on is the data itself, representation of semantic and representation of the syntax. And make sure that data meets the quality that I have that I have to assure and it's available. The rest of provisioning of everything that sits underneath will have to get taken care of by the platform. And that's what I mean by requires a re imagination and in fact, Andi, there will be a data platform team, the data platform teams that we set up for our clients. In fact, themselves have a favorite of complexity. Internally, they divide into multiple teams multiple planes, eso there would be a plane, as in a group of capabilities that satisfied that data product developer experience, there would be a set of capabilities that deal with those need a greatly underlying utilities. I call it at this point, utilities, because to me that the level of abstraction of the platform is to go higher than where it is. So what we call platform today are a set of utilities will be continuing to using will be continuing to using object storage, will continue using relation of databases and so on so there will be a plane and a group of people responsible for that. There will be a group of people responsible for capabilities that you know enable the mesh level functionality, for example, be able to correlate and connects. And query data from multiple knows. That's a measure level capability to be able to discover and explore the measure data products as a measure of capability. So it would be set of teams as part of platforms with a strong again platform product thinking embedded and product ownership embedded into that. To satisfy the experience of this now business oriented domain data team teams s way have a lot of work to do. >>I could go on. Unfortunately, we're out of time. But I guess my first I want to tell people there's two pieces that you put out so far. One is, uh, how to move beyond a monolithic data lake to a distributed data mesh. You guys should read that in a data mesh principles and logical architectures kind of part two. I guess my last question in the very limited time we have is our organization is ready for this. >>E think the desire is there I've bean overwhelmed with number off large and medium and small and private and public governments and federal, you know, organizations that reached out to us globally. I mean, it's not This is this is a global movement and I'm humbled by the response of the industry. I think they're the desire is there. The pains are really people acknowledge that something needs to change. Here s so that's the first step. I think that awareness isa spreading organizations. They're more and more becoming aware. In fact, many technology providers are reach out to us asking what you know, what shall we do? Because our clients are asking us, You know, people are already asking We need the data vision. We need the tooling to support. It s oh, that awareness is there In terms of the first step of being ready, However, the ingredients of a successful transformation requires top down and bottom up support. So it requires, you know, support from Chief Data Analytics officers or above the most successful clients that we have with data. Make sure the ones that you know the CEOs have made a statement that, you know, we want to change the experience of every single customer using data and we're going to do, we're going to commit to this. So the investment and support, you know, exists from top to all layers. The engineers are excited that maybe perhaps the traditional data teams are open to change. So there are a lot of ingredients. Substance to transformation is to come together. Um, are we really ready for it? I think I think the pioneers, perhaps the innovators. If you think about that innovation, careful. My doctors, probably pioneers and innovators and leaders. Doctors are making making move towards it. And hopefully, as the technology becomes more available, organizations that are less or in, you know, engineering oriented, they don't have the capability in house today, but they can buy it. They would come next. Maybe those are not the ones who aren't quite ready for it because the technology is not readily available. Requires, you know, internal investment today. >>I think you're right on. I think the leaders are gonna lead in hard, and they're gonna show us the path over the next several years. And I think the the end of this decade is gonna be defined a lot differently than the beginning. Jammeh. Thanks so much for coming in. The Cuban. Participate in the >>program. Pleasure head. >>Alright, Keep it right. Everybody went back right after this short break.

Published Date : Jan 22 2021

SUMMARY :

cloud brought to you by silicon angle in 2000 The modern big data movement It's a pleasure to have you on the program. This wonderful to be here. pretty outspoken about the need for a paradigm shift in how we manage our data and our platforms the only way we get access to you know various applications on the Web pages is to So on the left here we're adjusting data from the operational lot of data teams globally just to see, you know, what are the pain points? that's problematic for some of the organizations that you work with and maybe give some examples. And that transformation is that, you know, heavy process, because you fundamentally So let's talk about the answer that you and your colleagues are proposing. the changes we needed to make was always, you know, our fellow Noto, how the architecture was centralized And then you brought in the really important, you know, sticking problem, which is that you know the governance which So at the end of the day, we want quality data accessible to them, um, Where is the end game? And make sure that data meets the quality that I I guess my last question in the very limited time we have is our organization is ready So the investment and support, you know, Participate in the Alright, Keep it right.

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Shawn Bice, AWS | AWS re:Invent 2020


 

>>from around the globe. It's the Cube with digital coverage of aws reinvent 2024 sponsored by Intel and AWS. Yeah. >>Welcome back here to our coverage here on the Cube of AWS reinvent 2020. It's now pleasure. Welcome. Sean. Vice to the program was the vice president of databases at AWS and Sean. Good day to you. How you doing, sir? >>I'm doing great. Thank you for having me. >>You bet. You bet. Thanks for carving out time. I know it was a very a busy couple of weeks for the A. W s team on DSO certainly was kicked off key notes today. We heard right away that there's some fairly significant announcements that I know certainly affect your world at AWS. Tell us a little bit about those announcements, and then we'll do a little deeper divers. You you go through >>sure, you know. And he made three big announcements this morning as it relates to databases, one of whom was around Aurora serverless V two on. Do you could just think of that as, uh um, no infrastructure whatsoever to manage and Aurora server list that can scale for, you know, from zero to hundreds of thousands of transactions in a fraction of a second, literally with no infrastructure to manage. So it's a really easy way to build applications in the cloud. Eso excited about that? Another big announcement WAAS related to a lot of our customers today are really they're using the right tool for the right job. In other words, they're not trying toe GM all of their data into one database management systems. They're breaking app down into smaller parts. They pick the right tool for the right job. And with that context, we announce glue elastic views, which just allows you to very easily write a sequel. Query most. There's a lot of developers that understand sequel. So if I could easily write a sequel query to reach out to the source databases and then materialize, um, that data into a different target, Um, that's a really simple way toe. Build new customer experiences and make the most of the databases you have. Aan den. The third big announcement remained today was called Babble Eso Babel. Babel Fish is really a a compatibility or a sequel server compatibility layer on Aurora post grass. So if you have ah sequel server application. You've been trying to migrate it to post grass, and you've been wishing for an easier way to get that done. Babel Fish allows you to take your T sequel or your Microsoft sequel server application connected to post grass. Using your same client drivers with little to no code change eso That's a big deal for those that are trying to migrate from commercial systems to open source. And then finally, we didn't stop there as we thought about Babel, Um, and talked to a lot of customers about it. We actually are open sourcing the technology, so it will be available later in 21. All the development will be done open transparently hosted on get hub and licensed under Apache 20 so those that's kind of one lap around the track, if you will, of the big announcements from today How big >>the open source announcement to me. I mean, that's fairly significant that that you're opening up this new opportunity thio the entire community, um, that you're willing to open it up, and I'm sure you're gonna have you know, I mean, this is this is gonna be I would imagine Ah, very popular destination for a lot of folks. >>Yeah, I think so, too. You know, I'm I'm personally, I'm a believer that every customer can use data to build a foundation for future innovation. And to me, a lot of things start and end with data. As we know, data really is a foundational component of at a swell A systems and, you know, and you know, what we found is not every customer can plan for every contingency that happens. But what they can do is build a strong foundation. So, you know, and with a strong foundation, you really stand the best chance to overcome whatever that next unexpected thing is or innovate new ways. And with that is a backdrop. We think this open source piece is a big deal. Why? I'll tell you, you know, it's just us right now. But if I told you the story behind the story, I have met so many customers over the last few years that you know, John, if you and I were sitting down with them, it kind of sounds like this. You sit down, you talk to somebody and they'll say things like, Hey, I've built, you know, we've built years and years and years of application development against sequel server. We really don't like the punitive commercial licensing and, you know, we're trying to get over Thio open source, but we need an easier way and, you know, and we thought about that long and hard and, you know, we came up with the team, came up with a wonderful solution for this, But to tell you the truth, as we were building Babel fish and talking to customers, what became really clear with the community enterprises in I S V s and s eyes is they all basically said, Hey, if there was a way where we could go and extend this, um for, you know, like it could be Boy, if this thing supported to more features, that would be awesome. But if it was open source, that would be even better, because then we could we could take things under our own control so that that's what truly motivated this decision to go open source and based on conversations we've had in the decisions we made, we actually think it's it's really big. It's really big for everybody who has been trying to move off of commercial systems and over toe open source. You. >>Let's talk about transforming your kind of your database mindset in general right now from a client's perspective, especially for somebody who was considering, you know, substantial moves, you know, a major reconfigurations off their processes. What's the process that you go through with them to evaluate their needs, to evaluate their capabilities, to evaluate their storage? All that, you know, that comes into play here and help them to get thio kind of the end of the rainbow >>because it z absolutely, you know, so it really depends on who you're talking Thio and no, at this stage of the game, the clouds been around now for 10, 14 years. I think it is something in that range, you know? So a lot of the early cloud adopters, you know, they've been here and they've been building in a certain way. Um and you know, you and I know early cloud adopters by way of watching streaming media, ordering rideshare, taking a selfie, you know, and you know, we have these great application experiences and we expect them to work all the time at Super Low. Leighton See, they should always be available. So you know, the single biggest thing we learned from Early Cloud builders was there's no such thing as one size football. There's one thing doesn't fit anything at all. Um, that's kind of the way data was, you know, 20 years ago. But today, if you take the learning from these early cloud builders, the journey that we go on with, let's say a mid to late stage cloud a doctor. We're all excited on, you know, sort of. If they can start now today, where Early Cloud Wilders have done a bunch of pioneering, they get excited. So So what happens is, um, there's usually to kind of conversations. One is how do we you know, we've got all these databases that we self managed on premise. How do we bring those into the cloud? And then how do we stop doing undifferentiated heavy lifting? In other words, what they're saying is, we don't want to do patching and back up and monitoring that Z instead, our precious resources should be working on innovations for the business. So in that context, you and I would end up talking to somebody about moving to fully managed services like an already s, for example, um and then the other conversation we have with customers is is the one about breaking free, which is hey, a burn on commercial. I wanna move for open source. And in that context, there are a lot of customers today that they'll move to the cloud. And then and then when they get there as a first step, their second step is to is to migrate over toe open source. And then that third piece is folks that are trying to build for the cloud, these modern APS. And in that context, they follow the playbook of these early cloud builders, which is what you take this big app. You break it into smaller parts and then they pick the right tool for the right job. So that's that's kind of the conversation that we go through there. And finally, what I would say is, most customers say that they'll say to me, What do you mean by picking the right tool for the right job? And the mindset is very different than the one that we all grew up in from 20 years ago. 20 years ago, you just bought a database platform. And then whatever the business was trying to do, you you you would try to support that access pattern on on that database choice. But today, the new world that we live in, it really is. Let's start with the business use case first, understand the access pattern and then pick the best optimized database storage for that. So that's that's kind of how those conversations go. >>You've got what, 15, 14, 15 different data based instruments, you know, like in your tool chest? Um, how how is that evolution occurred? Um because I'm sure, you know one, but got another big at another big at another, looking at different capabilities, different needs. So I mean, >>kind of walked me >>through that a little bit and how you've gotten to the point that you've got 15 >>Tonto eso. So one of the things that you know I'd start off with here, like the question is, Well, if there's 15 today, is there gonna be 100 tomorrow? The real answer is, I don't know, you know, And but what I do know is there's really a handful of categories around data models and access patterns that if you will kind of fill out the portfolio if you will. Um, the first one is around relation. Also, relational databases have been around for a long time. It has a certain set of characteristics that people have come to appreciate and understand and, you know, and we provide a set of services that provide fully managed relational services. Let it be for things like Oracle or sequel, server or open source, like Maria DB or my sequel or Post Press and even Aurora, which provides commercial grade performance availability and scale it about 1/10 the cost of commercial. So you know, there's a handful of different services in that context. But there's new services in this key value. And think of a key value access pattern along the lines of you. Imagine. We order you order a ride share and you're trying to track a vehicle every second. So on your phone you can see it moving across your phone. And now imagine if you were building that at our a million people going to do that all at the same time or 10. So in that kind of access pattern, a product like dynamodb is excellent because It's designed for basically unlimited scale, really high throughput. So developer doesn't have toe really worry about a million people. 10 million people are one. This thing can just scale inevitably. Yeah, it's just not an issue. And, you know, I'll give you one other example like, um, in Neptune, which is a graph database. So you and I would know graph databases by way of seeing a product recommendation, for example, Um, and you know, grab the beauty of a graph databases. It's optimized for highly connected data. In other words, as a developer, I can what I can do with a few lines of code and a graph database because it's optimized for all these different relationships. I might try to do that in a different system that I might write 1500 lines of codes and because it was never designed for something like highly connect the data like graph. So that's kind of the evolution of how things there's just these different categories that have to do with access patterns and data models. And our strategy is simple. In each category, we wanna have the very best AP is available for our customers. Let's >>talk about security here for a moment because you have, you know, these just these tremendous reservoirs now, right that you've built up in capabilities got, you know, new data centers going up every day. It seems like around around the country and around the world, security or securing data nevermore important on dnep ver mawr, I guess on the radar of the bad actors to at the same time because of the value of that data. So just if you would paint the picture in terms of security awareness three encryption devices that you're now deploying the stuff that's keeping you up at night, I would think probably falls into this category a little bit. Eso Let's just take it on security and the level of concern. And then what you at a w s are doing about that? >>Yeah. So, you know, when I talked to customers, I always remind people security is a shared responsibility on De So Amazon's piece of that is the infrastructure that we build the processes that we have, you know, from how people you know can enter a building toe, what they can do in an environment. The auditing to the encryption systems that rebuild. Um, there's there's three infrastructure responsibility, which, you know, we think about every second of every day. Um, Andi, it's, you know, yes, it's one of those things that keeps you up at night. But you have to kind of have this level of paranoia, if you will. There's bad actors everywhere. And, you know, that mindset is kind of, you know, kind of helps you stay focused on Ben. There's the customers responsibility to in in terms of how they think about security. So, you know, um and what that means is, uh, you know, best practices around how they how they integrate identity and access management into their solution. Um, you know how they use how they rotate encryption keys, how they apply encryption and all the safeguards that you would expect the customer do so together, you know, we work with our customers to ensure that our systems are are secure. Um, and the only other thing that I would add to this is that, you know, kind of in the old world. And I keep bringing up the old world because security in the old world was sort of one of those things. Like if you go back 20 years ago. You know, security sometimes is one of those things that you think about a little bit later in the cycle. And I've met a lot of customers that tryto bolt on security and it never works. It's just hard to just bolt it into an app. But the really nice thing about thes fully managed services in the cloud they have security built right in. So security, performance and availability is built right into these fully managed A p I s eso customer doesn't have to think about Well, how do I add this capability onto it? You know, in some sense, it could be a simple is turning a feature on or something like encryption being turned on by default, and they don't have to do anything. So, you know, there it's just a completely different world that we live in today, and we try to improve it every second of every day. >>Well, Sean, it's nice to know that you're experiencing the paranoia for all your customers. That Zaveri very gracious yesterday There. Hey, thanks for the time. I appreciate it. I know you're very busy the next couple of weeks with the number of leadership sessions and intermediate sessions as well with AWS reinvent. So thanks again for carving a little bit of time for us here today on the Cube. >>You bet, John. Thank you. I really appreciate it. >>Take care.

Published Date : Dec 2 2020

SUMMARY :

It's the Cube with digital coverage How you doing, sir? Thank you for having me. You you go through Aurora server list that can scale for, you know, from zero to hundreds of thousands the open source announcement to me. but we need an easier way and, you know, and we thought about that long you know, substantial moves, you know, a major reconfigurations off their processes. So a lot of the early cloud adopters, you know, based instruments, you know, like in your tool chest? So one of the things that you the stuff that's keeping you up at night, that we build the processes that we have, you know, from how people you know can Hey, thanks for the time. I really appreciate it.

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