>>The Cube is live with three different stages here at AW S Reinvent in fabulous Las Vegas, Nevada. My name's Savannah Peterson, and I gotta tell you, even though the cube has been at AW w s reinvent for over a decade, this is my first year and wow, is it just buzzing in here? >>It's >>Busy, it's crowd, it's loud. >>So exciting to be here with you all. >>We're hearing north of 50,000 people, and I'm hearing hundreds of thousands online. >>No, it's going great. There's lots of buzz, lots of excitement this year, of course, three times a number of people, but it's fantastic. >>Everyone at the same place at the same time. Energy is just pretty special. So it's >>Fun. >>I mean, AWS is a friendly place for security companies and I'm excited to talk about that. >>Let's be here. We have a lot coming for you. We're super excited and if you think about it, it's price, performance, it's data, it's security, and it's solutions for purpose-built use cases. >>Great job. Congratulations. I love the mess. I love how you guys had the theme. I thought his keynote was great and it's great to see Amazon continue to innovate. >>My name is Savannah Peterson. We are the Cube and we are the leading source for high tech coverage.

>>Hey everyone, welcome to the Cube's coverage of AWS Reinvent 2022. Lisa Martin here with you with Subaru ier, one of our alumni who's now the CEO of Aerospike. Sabu. Great to have you on the program. Thank you for joining us. >>Great as always, to be on the cube. Luisa, good to meet you. >>So, you know, every company these days has got to be a data company, whether it's a retailer, a manufacturer, a grocer, a automotive company. But for a lot of companies, data is underutilized, yet a huge asset that is value added. Why do you think companies are struggling so much to make data a value added asset? >>Well, you know, we, we see this across the board when I talk to customers and prospects. There's a desire from the business and from it actually to leverage data to really fuel newer applications, newer services, newer business lines, if you will, for companies. I think the struggle is one, I think one the, you know, the plethora of data that is created, you know, surveys say that over the next three years data is gonna be, you know, by 2025, around 175 zetabytes, right? A hundred and zetabytes of data is gonna be created. And that's really a, a, a growth of north of 30% year over year. But the more important, and the interesting thing is the real time component of that data is actually growing at, you know, 35% cagr. And what enterprises desire is decisions that are made in real time or near real time. >>And a lot of the challenges that do exist today is that either the infrastructure that enterprises have in place was never built to actually manipulate data in real time. The second is really the ability to actually put something in place which can handle spikes yet be cost efficient if you'll, so you can build for really peak loads, but then it's very expensive to operate that particular service at normal loads. So how do you build something which actually works for you, for both you, both users, so to speak? And the last point that we see out there is even if you're able to, you know, bring all that data, you don't have the processing capability to run through that data. So as a result, most enterprises struggle with one, capturing the data, you know, making decisions from it in real time and really operating it at the cost point that they need to operate it at. >>You know, you bring up a great point with respect to real time data access. And I think one of the things that we've learned the last couple of years is that access to real time data, it's not a nice to have anymore. It's business critical for organizations in any industry. Talk about that as one of the challenges that organizations are facing. >>Yeah. When, when, when we started Aerospike, right when the company started, it started with the premise that data is gonna grow, number one, exponentially. Two, when applications open up to the internet, there's gonna be a flood of users and demands on those applications. And that was true primarily when we started the company in the ad tech vertical. So ad tech was the first vertical where there was a lot of data both on the supply side and the demand side from an inventory of ads that were available. And on the other hand, they had like microseconds or milliseconds in which they could make a decision on which ad to put in front of you and I so that we would click or engage with that particular ad. But over the last three to five years, what we've seen is as digitization has actually permeated every industry out there, the need to harness data in real time is pretty much present in every industry. >>Whether that's retail, whether that's financial services, telecommunications, e-commerce, gaming and entertainment. Every industry has a desire. One, the innovative companies, the small companies rather, are innovating at a pace and standing up new businesses to compete with the larger companies in each of these verticals. And the larger companies don't wanna be left behind. So they're standing up their own competing services or getting into new lines of business that really harness and are driven by real time data. So this compelling pressures, one, the customer exp you know, customer experience is paramount and we as customers expect answers in, you know, an instant in real time. And on the other hand, the way they make decisions is based on a large data set because you know, larger data sets actually propel better decisions. So there's competing pressures here, which essentially drive the need. One from a business perspective, two from a customer perspective to harness all of this data in real time. So that's what's driving an inces need to actually make decisions in real or near real time. >>You know, I think one of the things that's been in short supply over the last couple of years is patients we do expect as consumers, whether we're in our business lives, our personal lives that we're going to be getting, be given information and data that's relevant, it's personal to help us make those real time decisions. So having access to real time data is really business critical for organizations across any industries. Talk about some of the main capabilities that modern data applications and data platforms need to have. What are some of the key capabilities of a modern data platform that need to be delivered to meet demanding customer expectations? >>So, you know, going back to your initial question Lisa, around why is data really a high value but underutilized or underleveraged asset? One of the reasons we see is a lot of the data platforms that, you know, some of these applications were built on have been then around for a decade plus and they were never built for the needs of today, which is really driving a lot of data and driving insight in real time from a lot of data. So there are four major capabilities that we see that are essential ingredients of any modern data platform. One is really the ability to, you know, operate at unlimited scale. So what we mean by that is really the ability to scale from gigabytes to even petabytes without any degradation in performance or latency or throughput. The second is really, you know, predictable performance. So can you actually deliver predictable performance as your data size grows or your throughput grows or your concurrent user on that application of service grows? >>It's really easy to build an application that operates at low scale or low throughput or low concurrency, but performance usually starts degrading as you start scaling one of these attributes. The third thing is the ability to operate and always on globally resilient application. And that requires a, a really robust data platform that can be up on a five, nine basis globally, can support global distribution because a lot of these applications have global users. And the last point is, goes back to my first answer, which is, can you operate all of this at a cost point? Which is not prohibitive, but it makes sense from a TCO perspective. Cuz a lot of times what we see is people make choices of data platforms and as ironically their service or applications become more successful and more users join their journey, the revenue starts going up, the user base starts going up, but the cost basis starts crossing over the revenue and they're losing money on the service, ironically, as the service becomes more popular. So really unlimited scale, predictable performance always on, on a globally resilient basis and low tco. These are the four essential capabilities of any modern data platform. >>So then talk to me with those as the four main core functionalities of a modern data platform. How does aerospace deliver that? >>So we were built, as I said, from the from day one to operate at unlimited scale and deliver predictable performance. And then over the years as we work with customers, we build this incredible high availability capability which helps us deliver the always on, you know, operations. So we have customers who are, who have been on the platform 10 years with no downtime for example, right? So we are talking about an amazing continuum of high availability that we provide for customers who operate these, you know, globally resilient services. The key to our innovation here is what we call the hybrid memory architecture. So, you know, going a little bit technically deep here, essentially what we built out in our architecture is the ability on each node or each server to treat a bank of SSDs or solid state devices as essentially extended memory. So you're getting memory performance, but you're accessing these SSDs, you're not paying memory prices, but you're getting memory performance as a result of that. >>You can attach a lot more data to each node or each server in your distributed cluster. And when you kind of scale that across basically a distributed cluster you can do with aerospike, the same things at 60 to 80% lower server count and as a result 60 to 80% lower TCO compared to some of the other options that are available in the market. Then basically, as I said, that's the key kind of starting point to the innovation. We layer around capabilities like, you know, replication change, data notification, you know, synchronous and asynchronous replication. The ability to actually stretch a single cluster across multiple regions. So for example, if you're operating a global service, you can have a single aerospace cluster with one node in San Francisco, one northern New York, another one in London. And this would be basically seamlessly operating. So that, you know, this is strongly consistent. >>Very few no SQL data platforms are strongly consistent or if they are strongly consistent, they will actually suffer performance degradation. And what strongly consistent means is, you know, all your data is always available, it's guaranteed to be available, there is no data lost anytime. So in this configuration that I talked about, if the node in London goes down, your application still continues to operate, right? Your users see no kind of downtime and you know, when London comes up, it rejoins the cluster and everything is back to kind of the way it was before, you know, London left the cluster so to speak. So the op, the ability to do this globally resilient, highly available kind of model is really, really powerful. A lot of our customers actually use that kind of a scenario and we offer other deployment scenarios from a higher availability perspective. So everything starts with HMA or hybrid memory architecture and then we start building out a lot of these other capabilities around the platform. >>And then over the years, what our customers have guided us to do is as they're putting together a modern kind of data infrastructure, we don't live in a silo. So aerospace gets deployed with other technologies like streaming technologies or analytics technologies. So we built connectors into Kafka, pulsar, so that as you're ingesting data from a variety of data sources, you can ingest them at very high ingest speeds and store them persistently into Aerospike. Once the data is in Aerospike, you can actually run spark jobs across that data in a, in a multithreaded parallel fashion to get really insight from that data at really high, high throughput and high speed, >>High throughput, high speed, incredibly important, especially as today's landscape is increasingly distributed. Data centers, multiple public clouds, edge IOT devices, the workforce embracing more and more hybrid these days. How are you ex helping customers to extract more value from data while also lowering costs? Go into some customer examples cause I know you have some great ones. >>Yeah, you know, I think we have, we have built an amazing set of customers and customers actually use us for some really mission critical applications. So, you know, before I get into specific customer examples, let me talk to you about some of kind of the use cases which we see out there. We see a lot of aerospace being used in fraud detection. We see us being used in recommendations and since we use get used in customer data profiles or customer profiles, customer 360 stores, you know, multiplayer gaming and entertainment, these are kind of the repeated use case digital payments. We power most of the digital payment systems across the globe. Specific example from a, from a specific example perspective, the first one I would love to talk about is PayPal. So if you use PayPal today, then you know when you actually paying somebody your transaction is, you know, being sent through aero spike to really decide whether this is a fraudulent transaction or not. >>And when you do that, you know, you and I as a customer not gonna wait around for 10 seconds for PayPal to say yay or me, we expect, you know, the decision to be made in an instant. So we are powering that fraud detection engine at PayPal for every transaction that goes through PayPal before us, you know, PayPal was missing out on about 2% of their SLAs, which was essentially millions of dollars, which they were losing because, you know, they were letting transactions go through and taking the risk that it, it's not a fraudulent transaction with the aerospace. They can now actually get a much better sla and the data set on which they compute the fraud score has gone up by, you know, several factors. So by 30 x if you will. So not only has the data size that is powering the fraud engine actually grown up 30 x with Aerospike. Yeah. But they're actually making decisions in an instant for, you know, 99.95% of their transactions. So that's, >>And that's what we expect as consumers, right? We want to know that there's fraud detection on the swipe regardless of who we're interacting with. >>Yes. And so that's a, that's a really powerful use case and you know, it's, it's a great customer, great customer success story. The other one I would talk about is really Wayfair, right? From retail and you know, from e-commerce. So everybody knows Wayfair global leader in really, you know, online home furnishings and they use us to power their recommendations engine and you know, it's basically if you're purchasing this, people who bought this but also bought these five other things, so on and so forth, they have actually seen the card size at checkout go by up to 30% as a result of actually powering their recommendations in G by through Aerospike. And they, they were able to do this by reducing the server count by nine x. So on one ninth of the servers that were there before aerospace, they're now powering their recommendation engine and seeing card size checkout go up by 30%. Really, really powerful in terms of the business outcome and what we are able to, you know, drive at Wayfair >>Hugely powerful as a business outcome. And that's also what the consumer wants. The consumer is expecting these days to have a very personalized, relevant experience that's gonna show me if I bought this, show me something else that's related to that. We have this expectation that needs to be really fueled by technology. >>Exactly. And you know, another great example you asked about, you know, customer stories, Adobe, who doesn't know Adobe, you know, they, they're on a, they're on a mission to deliver the best customer experience that they can and they're talking about, you know, great customer 360 experience at scale and they're modernizing their entire edge compute infrastructure to support this. With Aerospike going to Aerospike, basically what they have seen is their throughput go up by 70%, their cost has been reduced by three x. So essentially doing it at one third of the cost while their annual data growth continues at, you know, about north of 30%. So not only is their data growing, they're able to actually reduce their cost to actually deliver this great customer experience by one third to one third and continue to deliver great customer 360 experience at scale. Really, really powerful example of how you deliver Customer 360 in a world which is dynamic and you know, on a dataset which is constantly growing at north, north of 30% in this case. >>Those are three great examples, PayPal, Wayfair, Adobe talking about, especially with Wayfair when you talk about increasing their cart checkout sizes, but also with Adobe increasing throughput by over 70%. I'm looking at my notes here. While data is growing at 32%, that's something that every organization has to contend with data growth is continuing to scale and scale and scale. >>Yep. I, I'll give you a fun one here. So, you know, you may not have heard about this company, it's called Dream 11 and it's a company based out of India, but it's a very, you know, it's a fun story because it's the world's largest fantasy sports platform and you know, India is a nation which is cricket crazy. So you know, when, when they have their premier league going on, you know, there's millions of users logged onto the dream alone platform building their fantasy lead teams and you know, playing on that particular platform, it has a hundred million users, a hundred million plus users on the platform, 5.5 million concurrent users and they have been growing at 30%. So they are considered a, an amazing success story in, in terms of what they have accomplished and the way they have architected their platform to operate at scale. And all of that is really powered by aerospace where think about that they are able to deliver all of this and support a hundred million users, 5.5 million concurrent users all with you know, 99 plus percent of their transactions completing in less than one millisecond. Just incredible success story. Not a brand that is you know, world renowned but at least you know from a what we see out there, it's an amazing success story of operating at scale. >>Amazing success story, huge business outcomes. Last question for you as we're almost out of time is talk a little bit about Aerospike aws, the partnership GRAVITON two better together. What are you guys doing together there? >>Great partnership. AWS has multiple layers in terms of partnerships. So you know, we engage with AWS at the executive level. They plan out, really roll out of new instances in partnership with us, making sure that, you know, those instance types work well for us. And then we just released support for Aerospike on the graviton platform and we just announced a benchmark of Aerospike running on graviton on aws. And what we see out there is with the benchmark, a 1.6 x improvement in price performance and you know, about 18% increase in throughput while maintaining a 27% reduction in cost, you know, on graviton. So this is an amazing story from a price performance perspective, performance per wat for greater energy efficiencies, which basically a lot of our customers are starting to kind of talk to us about leveraging this to further meet their sustainability target. So great story from Aero Aerospike and aws, not just from a partnership perspective on a technology and an executive level, but also in terms of what joint outcomes we are able to deliver for our customers. >>And it sounds like a great sustainability story. I wish we had more time so we would talk about this, but thank you so much for talking about the main capabilities of a modern data platform, what's needed, why, and how you guys are delivering that. We appreciate your insights and appreciate your time. >>Thank you very much. I mean, if, if folks are at reinvent next week or this week, come on and see us at our booth. We are in the data analytics pavilion. You can find us pretty easily. Would love to talk to you. >>Perfect. We'll send them there. So Ira, thank you so much for joining me on the program today. We appreciate your insights. >>Thank you Lisa. >>I'm Lisa Martin. You're watching The Cubes coverage of AWS Reinvent 2022. Thanks for watching.

>>Hey everyone. Welcome back to Las Vegas. It's the Cube live at AWS Reinvent 2022. This is our fourth day of coverage. Lisa Martin here with Paul Gillen. Paul, we started Monday night, we filmed and streamed for about three hours. We have had shammed pack days, Tuesday, Wednesday, Thursday. What's your takeaway? >>We're routed final turn as we, as we head into the home stretch. Yeah. This is as it has been since the beginning, this show with a lot of energy. I'm amazed for the fourth day of a conference, how many people are still here I am too. And how, and how active they are and how full the sessions are. Huge. Proud for the keynote this morning. You don't see that at most of the day four conferences. Everyone's on their way home. So, so people come here to learn and they're, and they're still >>Learning. They are still learning. And we're gonna help continue that learning path. We have an alumni back with us, Toron joins us, the CPO and co-founder of Dremeo. Tomer, it's great to have you back on the program. >>Yeah, thanks for, for having me here. And thanks for keeping the, the best session for the fourth day. >>Yeah, you're right. I like that. That's a good mojo to come into this interview with Tomer. So last year, last time I saw you was a year ago here in Vegas at Reinvent 21. We talked about the growth of data lakes and the data lake houses. We talked about the need for open data architectures as opposed to data warehouses. And the headline of the Silicon Angle's article on the interview we did with you was, Dremio Predicts 2022 will be the year open data architectures replace the data warehouse. We're almost done with 2022. Has that prediction come true? >>Yeah, I think, I think we're seeing almost every company out there, certainly in the enterprise, adopting data lake, data lakehouse technology, embracing open source kind of file and table formats. And, and so I think that's definitely happening. Of course, nothing goes away. So, you know, data warehouses don't go away in, in a year and actually don't go away ever. We still have mainframes around, but certainly the trends are, are all pointing in that direction. >>Describe the data lakehouse for anybody who may not be really familiar with that and, and what it's, what it really means for organizations. >>Yeah. I think you could think of the data lakehouse as the evolution of the data lake, right? And so, you know, for, for, you know, the last decade we've had kind of these two options, data lakes and data warehouses and, you know, warehouses, you know, having good SQL support, but, and good performance. But you had to spend a lot of time and effort getting data into the warehouse. You got locked into them, very, very expensive. That's a big problem now. And data lakes, you know, more open, more scalable, but had all sorts of kind of limitations. And what we've done now as an industry with the Lake House, and especially with, you know, technologies like Apache Iceberg, is we've unlocked all the capabilities of the warehouse directly on object storage like s3. So you can insert and update and delete individual records. You can do transactions, you can do all the things you could do with a, a database directly in kind of open formats without getting locked in at a much lower cost. >>But you're still dealing with semi-structured data as opposed to structured data. And there's, there's work that has to be done to get that into a usable form. That's where Drio excels. What, what has been happening in that area to, to make, I mean, is it formats like j s o that are, are enabling this to happen? How, how we advancing the cause of making semi-structured data usable? Yeah, >>Well, I think first of all, you know, I think that's all changed. I think that was maybe true for the original data lakes, but now with the Lake house, you know, our bread and butter is actually structured data. It's all, it's all tables with the schema. And, you know, you can, you know, create table insert records. You know, it's, it's, it's really everything you can do with a data warehouse you can now do in the lakehouse. Now, that's not to say that there aren't like very advanced capabilities when it comes to, you know, j s O and nested data and kind of sparse data. You know, we excel in that as well. But we're really seeing kind of the lakehouse take over the, the bread and butter data warehouse use cases. >>You mentioned open a minute ago. Talk about why it's, why open is important and the value that it can deliver for customers. >>Yeah, well, I think if you look back in time and you see all the challenges that companies have had with kind of traditional data architectures, right? The, the, the, a lot of that comes from the, the, the problems with data warehouses. The fact that they are, you know, they're very expensive. The data is, you have to ingest it into the data warehouse in order to query it. And then it's almost impossible to get off of these systems, right? It takes an enormous effort, tremendous cost to get off of them. And so you're kinda locked in and that's a big problem, right? You also, you're dependent on that one data warehouse vendor, right? You can only do things with that data that the warehouse vendor supports. And if you contrast that to data lakehouse and open architectures where the data is stored in entirely open formats. >>So things like par files and Apache iceberg tables, that means you can use any engine on that data. You can use s SQL Query Engine, you can use Spark, you can use flin. You know, there's a dozen different engines that you can use on that, both at the same time. But also in the future, if you ever wanted to try something new that comes out, some new open source innovation, some new startup, you just take it and point out the same data. So that data's now at the core, at the center of the architecture as opposed to some, you know, vendors logo. Yeah. >>Amazon seems to be bought into the Lakehouse concept. It has big announcements on day two about eliminating the ETL stage between RDS and Redshift. Do you see the cloud vendors as pushing this concept forward? >>Yeah, a hundred percent. I mean, I'm, I'm Amazon's a great, great partner of ours. We work with, you know, probably 10 different teams there. Everything from, you know, the S3 team, the, the glue team, the click site team, you know, everything in between. And, you know, their embracement of the, the, the lake house architecture, the fact that they adopted Iceberg as their primary table format. I think that's exciting as an industry. We're all coming together around standard, standard ways to represent data so that at the end of the day, companies have this benefit of being able to, you know, have their own data in their own S3 account in open formats and be able to use all these different engines without losing any of the functionality that they need, right? The ability to do all these interactions with data that maybe in the past you would have to move the data into a database or, or warehouse in order to do, you just don't have to do that anymore. Speaking >>Of functionality, talk about what's new this year with drio since we've seen you last. >>Yeah, there's a lot of, a lot of new things with, with Drio. So yeah, we now have full Apache iceberg support, you know, with DML commands, you can do inserts, updates, deletes, you know, copy into all, all that kind of stuff is now, you know, fully supported native part of the platform. We, we now offer kind of two flavors of dr. We have, you know, Dr. Cloud, which is our SaaS version fully hosted. You sign up with your Google or, you know, Azure account and, and, and you're up in, you're up and running in, in, in a minute. And then dral software, which you can self host usually in the cloud, but even, even even outside of the cloud. And then we're also very excited about this new idea of data as code. And so we've introduced a new product that's now in preview called Dr. >>Arctic. And the idea there is to bring the concepts of GI or GitHub to the world of data. So things like being able to create a branch and work in isolation. If you're a data scientist, you wanna experiment on your own without impacting other people, or you're a data engineer and you're ingesting data, you want to transform it and test it before you expose it to others. You can do that in a branch. So all these ideas that, you know, we take for granted now in the world of source code and software development, we're bringing to the world of data with Jamar. And when you think about data mesh, a lot of people talking about data mesh now and wanting to kind of take advantage of, of those concepts and ideas, you know, thinking of data as a product. Well, when you think about data as a product, we think you have to manage it like code, right? You have to, and that's why we call it data as code, right? The, all those reasons that we use things like GI have to build products, you know, if we wanna think of data as a product, we need all those capabilities also with data. You know, also the ability to go back in time. The ability to undo mistakes, to see who changed my data and when did they change that table. All of those are, are part of this, this new catalog that we've created. >>Are you talk about data as a product that's sort of intrinsic to the data mesh concept. Are you, what's your opinion of data mesh? Is the, is the world ready for that radically different approach to data ownership? >>You know, we are now in dozens of, dozens of our customers that are using drio for to implement enterprise-wide kind of data mesh solutions. And at the end of the day, I think it's just, you know, what most people would consider common sense, right? In a large organization, it is very hard for a centralized single team to understand every piece of data, to manage all the data themselves, to, you know, make sure the quality is correct to make it accessible. And so what data mesh is first and foremost about is being able to kind of federate the, or distribute the, the ownership of data, the governance of the data still has to happen, right? And so that is, I think at the heart of the data mesh, but thinking of data as kind of allowing different teams, different domains to own their own data to really manage it like a product with all the best practices that that we have with that super important. >>So we we're doing a lot with data mesh, you know, the way that cloud has multiple projects and the way that Jamar allows you to have multiple catalogs and different groups can kind of interact and share data among each other. You know, the fact that we can connect to all these different data sources, even outside your data lake, you know, with Redshift, Oracle SQL Server, you know, all the different databases that are out there and join across different databases in addition to your data lake, that that's all stuff that companies want with their data mesh. >>What are some of your favorite customer stories that where you've really helped them accelerate that data mesh and drive business value from it so that more people in the organization kind of access to data so they can really make those data driven decisions that everybody wants to make? >>I mean, there's, there's so many of them, but, you know, one of the largest tech companies in the world creating a, a data mesh where you have all the different departments in the company that, you know, they, they, they were a big data warehouse user and it kinda hit the wall, right? The costs were so high and the ability for people to kind of use it for just experimentation, to try new things out to collaborate, they couldn't do it because it was so prohibitively expensive and difficult to use. And so what they said, well, we need a platform that different people can, they can collaborate, they can ex, they can experiment with the data, they can share data with others. And so at a big organization like that, the, their ability to kind of have a centralized platform but allow different groups to manage their own data, you know, several of the largest banks in the world are, are also doing data meshes with Dr you know, one of them has over over a dozen different business units that are using, using Dremio and that ability to have thousands of people on a platform and to be able to collaborate and share among each other that, that's super important to these >>Guys. Can you contrast your approach to the market, the snowflakes? Cause they have some of those same concepts. >>Snowflake's >>A very closed system at the end of the day, right? Closed and very expensive. Right? I think they, if I remember seeing, you know, a quarter ago in, in, in one of their earnings reports that the average customer spends 70% more every year, right? Well that's not sustainable. If you think about that in a decade, that's your cost is gonna increase 200 x, most companies not gonna be able to swallow that, right? So companies need, first of all, they need more cost efficient solutions that are, you know, just more approachable, right? And the second thing is, you know, you know, we talked about the open data architecture. I think most companies now realize that the, if you want to build a platform for the future, you need to have the data and open formats and not be locked into one vendor, right? And so that's kind of another important aspect beyond that's ability to connect to all your data, even outside the lake to your different databases, no sequel databases, relational databases, and drs semantic layer where we can accelerate queries. And so typically what you have, what happens with data warehouses and other data lake query engines is that because you can't get the performance that you want, you end up creating lots and lots of copies of data. You, for every use case, you're creating a, you know, a pre-joy copy of that data, a pre aggregated version of that data. And you know, then you have to redirect all your data. >>You've got a >>Governance problem, individual things. It's expensive. It's expensive, it's hard to secure that cuz permissions don't travel with the data. So you have all sorts of problems with that, right? And so what we've done because of our semantic layer that makes it easy to kind of expose data in a logical way. And then our query acceleration technology, which we call reflections, which transparently accelerates queries and gives you subsecond response times without data copies and also without extracts into the BI tools. Cause if you start doing bi extracts or imports, again, you have lots of copies of data in the organization, all sorts of refresh problems, security problems, it's, it's a nightmare, right? And that just collapsing all those copies and having a, a simple solution where data's stored in open formats and we can give you fast access to any of that data that's very different from what you get with like a snowflake or, or any of these other >>Companies. Right. That, that's a great explanation. I wanna ask you, early this year you announced that your Dr. Cloud service would be a free forever, the basic DR. Cloud service. How has that offer gone over? What's been the uptake on that offer? >>Yeah, it, I mean it is, and thousands of people have signed up and, and it's, I think it's a great service. It's, you know, it's very, very simple. People can go on the website, try it out. We now have a test drive as well. If, if you want to get started with just some sample public sample data sets and like a tutorial, we've made that increasingly easy as well. But yeah, we continue to, you know, take that approach of, you know, making it, you know, making it easy, democratizing these kind of cloud data platforms and, and kinda lowering the barriers to >>Adoption. How, how effective has it been in driving sales of the enterprise version? >>Yeah, a lot of, a lot of, a lot of business with, you know, that, that we do like when it comes to, to selling is, you know, folks that, you know, have educated themselves, right? They've started off, they've followed some tutorials. I think generally developers, they prefer the first interaction to be with a product, not with a salesperson. And so that's, that's basically the reason we did that. >>Before we ask you the last question, I wanna just, can you give us a speak peek into the product roadmap as we enter 2023? What can you share with us that we should be paying attention to where Drum is concerned? >>Yeah. You know, actually a couple, couple days ago here at the conference, we, we had a press release with all sorts of new capabilities that we, we we just released. And there's a lot more for, for the coming year. You know, we will shortly be releasing a variety of different performance enhancements. So we'll be in the next quarter or two. We'll be, you know, probably twice as fast just in terms of rock qu speed, you know, that's in addition to our reflections and our career acceleration, you know, support for all the major clouds is coming. You know, just a lot of capabilities in Inre that make it easier and easier to use the platform. >>Awesome. Tomer, thank you so much for joining us. My last question to you is, if you had a billboard in your desired location and it was going to really just be like a mic drop about why customers should be looking at Drio, what would that billboard say? >>Well, DRIO is the easy and open data lake house and, you know, open architectures. It's just a lot, a lot better, a lot more f a lot more future proof, a lot easier and a lot just a much safer choice for the future for, for companies. And so hard to argue with those people to take a look. Exactly. That wasn't the best. That wasn't the best, you know, billboards. >>Okay. I think it's a great billboard. Awesome. And thank you so much for joining Poly Me on the program, sharing with us what's new, what some of the exciting things are that are coming down the pipe. Quite soon we're gonna be keeping our eye Ono. >>Awesome. Always happy to be here. >>Thank you. Right. For our guest and for Paul Gillin, I'm Lisa Martin. You're watching The Cube, the leader in live and emerging tech coverage.

>> Good afternoon, fellow cloud nerds and welcome back to AWS Reinvent 2022. We are live here from fabulous Las Vegas, Nevada. My name is Savannah Peterson, joined by Lisa Martin. So excited to be here Lisa, it's my first reinvent. >> Is it really? >> Yeah. >> I think it's only like my fourth or fifth. >> Only your fourth or fifth. >> Only. >> You're such a pro here. >> There's some serious veterans here in attendance that have been to all 11. >> I love that. >> Yeah. Wow, go them. I know, maybe we'll be at that level sooner. >> One day we will. >> Are you enjoying the show so far? >> Absolutely, it is. I cannot believe how many people are here. We've had 70,000 and we're only seeing what's at the foundation Expo Hall, not at the other hotel. So, I can only imagine. >> I mean, there's a world outside of this. >> Yes, and there's sunlight. There's actual sunlight outside of this room. >> Nobel idea. Well, Lisa, I'm very excited to be sitting here next to you and to welcome our fabulous guests, from TEKsystems, we have Brandon and Srini. Thank you so much for being here. How is the show going for you gentlemen so far? >> It's great. Lot of new insights and the customers are going to love what AWS is releasing in this reinvent. >> There is such a community here, and I love that vibe. It's similar to what we had at Cloud Native con in Detroit. So much collaboration going on. I assume most folks know a lot about TEKsystems who are watching, but just in case they don't, Brandon, give us the pitch. >> You bet. So full stack IT solutions firm, been in business for over 40 years, 80,000 global employees, really specializing in digital transformation, enterprise modernization services. We have partners in One Strategy, which is an an acquisition we made, but a well known premier partner in the Amazon partner ecosystem, as well as One North Interactive, who is our boutique brand, creative and digital strategy firm. So together, we really feel like we can bring full end-to-end solutions for digital and modernization initiatives. >> So, I saw some notes where TEKsystems are saying organizations need experienced AWS partners that are not afraid doing the dirty work of digital transformation, who really can advise and execute. Brandon, talk to us about how TEKsystems and AWS are working together to help customers on that journey which is nebulous of digital transformation. >> So, our real hallmark is the ability to scale. We partner with AWS in a lot of different ways. In fact, we just signed our strategic collaboration agreement. So, we're in the one percenter group in the whole partner network. >> Savanna: That's a pretty casual flex there. >> Not bad. >> I love that, top 1%, that no wonder you're wearing that partner pin so proud today. (speaking indistinctly) >> But we're working all the way on the advisory and working with their pro serve organization and then transforming that into large scale mass migration services, a lot of data modernization that Srini is an absolute expert in. I'm sure he can add some context too, but it's been a great partnership for many years now. >> In the keynote, Adam spent almost 52 minutes on data, right? So, it emphasizes how organizations are ready to take data to cloud and actually make meaningful insights and help their own customers come out of it by making meaningful decisions. So, we are glad to be part of this entire ecosystem. >> I love that you quantified how many minutes. >> I know. >> Talked about it, that was impressive. There's a little bit of data driven thinking going on here. >> I think so. >> Yeah. >> Well, we can't be at an event like this without talking about data for copious amounts of time, 52 minutes, has just used this morning. >> Right, absolutely. >> But every company these days has to be a data company. There's no choice to be successful, to thrive, to survive. I mean, even to thrive and grow, if it's a grocery store or your local gas station or what? You name it, that company has to be a data company. But the challenge of the data volume, the explosion in data is huge for organizations to really try to figure out and sift through what they have, where is all of it? How do we make sense of it? How do we act on it and get insights? That's a big challenge. How is TEKsystems helping customers tackle that challenge? >> Yeah, that's a great question because that's the whole fun of handling data. You need to ensure its meaning is first understood. So, we are not just dumping data into a storage place, but rather assign a meaningful context. In today's announcement, again, the data zone was unveiled to give meaning to data. And I think those are key concrete steps that we take to our customers as well with some good blueprints, methodical ways of approaching data and ultimately gaining business insights. >> And maybe I'll add just something real quick to that. The theme we're seeing and hearing a lot about is data monetization. So, technology companies have figured it out and used techniques to personalize things and get you ads, probably that you don't want half the time. But now all industries are really looking to do that. Looking at ways to open new revenue channels, looking at ways to drive a better customer experience, a better employee experience. We've got a ton of examples of that, Big Oil and Gas leveraging like well and machine data, coming in to be more efficient when they're pumping and moving commodities around. We work a lot in the medium entertainment space and so obviously, getting targeted ads to consumers during the right periods of TV or movies or et cetera. Especially with the advert on Netflix and all your streaming videos. So, it's been really interesting but we really see the future in leveraging data as one of your biggest corporate assets. >> Brilliant. >> So, I'm just curious on the ad thing, just real quick and I'll let you go, Lisa. So, do you still fall victim to falling for the advertising even though you know it's been strategically put there for you to consume in that moment? >> Most of the time. >> I mean, I think we all do. We're all, (indistinct), you're behind the curtain so to speak. >> The Amazon Truck shows up every day at my house, which is great, right? >> Hello again >> Same. >> But I think the power of it is you are giving the customer what they're looking for. >> That's it. >> And you know... >> Exactly. We have that expectation, we want it. >> 100%. >> We know that. >> Agree. >> We don't need to buy it. But technology has made it so easy to transact. That's like when developers started going to the cloud years ago, it was just, it was a swipe. It was so simple. Brandon, talk about the changes in cloud and cloud migration that TEKsystems has seen, particularly in the last couple of years as every company was rushing to go digital because they had to. >> So several years ago, we kind of pushed away that cloud first mentality to the side and we use more of a cloud smart kind of fashion, right? Does everything need to go to the cloud? No. Do applications, data, need to go to the cloud in a way that's modern and takes advantages of what the cloud can provide and all the new services that are being released this week and ongoing. So, the other thing we're seeing is initiatives that have traditionally been in the CTO, CIO organization aren't necessarily all that successful because we're seeing a complete misalignment between business goals and IT achievements, outcomes, et cetera. You can automate things, you can move it to the cloud, but if you didn't solve a core business problem or challenge, what'd you really do? >> Yeah, just to add on that, it's all about putting data and people together. And then how we can actually ensure the workforce is equally brought up to speed on these new technologies. That has been something that we have seen tremendous improvement in the last 24 months where customers are ready to take up new challenges and the end users are ready to learn something new and not just stick onto that status quo mindset. >> Where do you guys factor in to bringing in AWS in the customer's cloud journeys? What is that partnership like? >> We always first look for where the customer is in their cloud journey path and make sure we advise them with the right next steps. And AWS having its services across the spectrum makes it even easier for us to look at what business problem they're solving and then align it according to the process and technology so that at the end of the day, we want end user adoption. We don't want to build a fancy new gadget that no one uses. >> Just because you built it doesn't mean they'll come. And I think that's the classic engineering marketing dilemma as well as balance to healthy tension. I would say between both. You mentioned Srini, you mentioned workforce just a second ago. What sort of trends are you seeing in workforce development? >> Generally speaking, there are a lot of services now that can quantify your code for errors and then make sure that the code that you're pushing into production is well tested. So what we are trying to make sure is a healthy mix of trying to solve a business problem and asking the right questions. Like today, even in the keynote, it was all about how QuickSight, for example, has additional features now that tells why something happened. And that's the kind of mindset we want our end users to adopt. Not just restricting themselves to a reactive analytics, but rather ask the question why, why did it happen? Why did my sales go down? And I think those technologies and mindset shift is happening across the workforce. >> From a workforce development standpoint, we're seeing there's not enough workforce and the core skills of data, DevOps, standard cloud type work. So, we're actually an ATP advanced training partner, one of the few within the AWS network. So, we've developed programs like our Rising Talent Program that are allowing us to bring the workforce up to the skills that are necessary in this new world. So, it's a more build versus buy strategy because we're on talents real, though it may start to wane a little bit as we change the macroeconomic outlook in 2023, but it's still there. And we still believe that building those workforce and investing in your people is the right thing to do. >> It is, and I think there's a strong alignment there with AWS and their focus on that as well. I wanted to ask you, Brandon. >> Brandon: Absolutely. >> One of the things, so our boss, John Furrier, the co CEO of theCUBE, talked with Adam Selipsky just a week or maybe 10 days ago. He always gets an exclusive interview with the CEO of AWS before reinvent, and one of the things that Adam shared with him is that customers, CEOs and CIOs are not coming to Adam, to this head of AWS to talk about technology, they want to talk about transformation. He's talking about... >> The topic this year. >> Moving away from amorphous topic of digital transformation to business transformation. Are you seeing the same thing in your customer? >> 100%, and if you're not starting at the business level, these initiatives are going to fail. We see it all the time. Again, it's about that misalignment and there's no good answer to that. But digital, I think is amorphous to some degree. We play a lot with the One North partnership that I mentioned earlier, really focusing on that strategy element because consumer dollars are shrinking via inflation, via what we're heading into, and we have to create the best experience possible. We have to create an omnichannel experience to get our products or services to market. And if we're not looking at those as our core goals and we're looking at them as IT or technology challenges, we're not looking in the right place. >> Well, and businesses aren't going to be successful if they're looking at it in those siloed organizations. Data has to be democratizing and we've spent same data democratization for so long, but really, we're seeing that it has to be moving out into the lines of business because another thing Adam shared with John Furrier is that he sees and I'm curious what your thoughts are on this, the title of data analysts going away because everybody in different functions and different lines of business within an organization are going to have to be data analysts to some degree, to use data whether it's marketing, ops, sales, finance, are you seeing the same? >> That is true. I mean, at this point, we are all in the connected world, right? Every data point is connected in some form or shape to another data point. >> Savanna: There are many data points, just sitting here, yeah. >> Absolutely, so I think if you are strategizing, data needs to be right in the center of it. And then your business problems need to be addressed with reliable data. >> No, I mean, advertising, supply chain, marketing, they're all interconnected now, and we're looking at ways to bring a lot of that siloed data into one place so we can make use to it. It goes back to that monetization element of our data. >> That's a lot about context and situational awareness. We want what we want, when we want it, even before we knew we needed it then. I think I said that right. But you know, it's always more faster, quicker and then scaling things up. You see a lot of different customers across verticals, you have an absolutely massive team. Give us a sneak peek into 2023. What does the future hold? >> 2023 is again, to today's keynote, I'm bringing it back because it was a keynote filled with vision and limitless possibilities. And that's what we see. Right now, our customers, they are no longer scared to go and take the plunge into the cloud. And as Brandon said, it's all about being smart about those decisions. So, we are very excited that together with the partnership that we recently acquired and the services and the depth, along with the horizontal domain expertise, we can actually help customers make meaningful message out of their data points. And that keeps us really excited for next year. >> Love that, Brandon, what about you? >> I think the obvious one is DevOps and a focus on optimization, financially, security, et cetera, just for the changing times. The other one is, I still think that digital is going to continue to be a big push in 2023, namely making sure that experience is at its best, whether that's employee and combating the war on talent, keeping your people or opening new revenue streams, enhancing existing revenue streams. You got to keep working on that. >> We got to keep the people happy with the machines and the systems that we are building as we all know. But it's very nice, it's been a lot of human-centric focus and a lot of customer obsession here at the show. We know it's a big thing for you all, for Amazon, for pretty much everyone who sat here. Hopefully it is in general. Hopefully there's nobody who doesn't care about their community, we're not talking to them, if that's the case, we have a new challenge on theCUBE for the show, this year as we kind of prepped you for and can call it a bumper sticker, you can call it a 30 second sizzle reel. But this is sort of your Instagram moment, your TikTok, your thought of leadership highlight. What's the most important story coming out of the show? Srini, you've been quoting the keynotes very well, so, I'm going to you first on this one. >> I think overall, it's all about owning the change. In our TEKsystems culture, it's all about striving for excellence through serving others and owning the change. And so it makes me very excited that when we get that kind of keynote resonating the same message that we invite culturally, that's a big win-win for all the companies. >> It's all about the shared vision. A lot of people with similar vision in this room right now, in this room, like it's a room, it's a massive expo center, just to be clear, I'm sure everyone can see in the background. Brandon >> I would say partnership, continuing to enhance our strategic partnership with AWS, continuing to be our customers' partners in transformation. And bringing those two things together here has been a predominance of my time this week. And we'll continue throughout the week, but we're in it together with our customers and with AWS and looking forward to the future. >> Yeah, that's a beautiful note to end on there. Brandon, Srini, thank you both so much for being here with us. Fantastic to learn from your insights and to continue to emphasize on this theme of collaboration. We look forward to the next conversation with you. Thank all of you for tuning in wherever you happen to be hanging out and watching this fabulous live stream or the replay. We are here at AWS Reinvent 2022 in wonderful sunny Las Vegas, Nevada with Lisa Martin. My name is Savannah Peterson, we are theCUBE, the leading source for high tech coverage.

>> 10, nine, eight, (clears throat) four, three. >> Good afternoon, fellow cloud nerds and welcome back to AWS Reinvent 2022. We are live here from fabulous Las Vegas, Nevada. My name is Savannah Peterson, joined by Lisa Martin. So excited to be here Lisa, it's my first reinvent. >> Is it really? >> Yeah. >> I think it's only like my fourth or fifth. >> Only your fourth or fifth. >> Only. >> You're such a pro here. >> There's some serious veterans here in attendance that have been to all 11. >> I love that. >> Yeah. Wow, go them. I know, maybe we'll be at that level sooner. >> One day we will. >> Are you enjoying the show so far? >> Absolutely, it is. I cannot believe how many people are here. We've had 70,000 and we're only seeing what's at the foundation Expo Hall, not at the other hotel. So, I can only imagine. >> I mean, there's a world outside of this. >> Yes, and there's sunlight. There's actual sunlight outside of this room. >> Nobel idea. Well, Lisa, I'm very excited to be sitting here next to you and to welcome our fabulous guests, from TEKsystems, we have Brandon and Srini. Thank you so much for being here. How is the show going for you gentlemen so far? >> It's great. Lot of new insights and the customers are going to love what AWS is releasing in this reinvent. >> There is such a community here, and I love that vibe. It's similar to what we had at Cloud Native con in Detroit. So much collaboration going on. I assume most folks know a lot about TEKsystems who are watching, but just in case they don't, Brandon, give us the pitch. >> You bet. So full stack IT solutions firm, been in business for over 40 years, 80,000 global employees, really specializing in digital transformation, enterprise modernization services. We have partners in One Strategy, which is an an acquisition we made, but a well known premier partner in the Amazon partner ecosystem, as well as One North Interactive, who is our boutique brand, creative and digital strategy firm. So together, we really feel like we can bring full end-to-end solutions for digital and modernization initiatives. >> So, I saw some notes where TEKsystems are saying organizations need experienced AWS partners that are not afraid doing the dirty work of digital transformation, who really can advise and execute. Brandon, talk to us about how TEKsystems and AWS are working together to help customers on that journey which is nebulous of digital transformation. >> So, our real hallmark is the ability to scale. We partner with AWS in a lot of different ways. In fact, we just signed our strategic collaboration agreement. So, we're in the one percenter group in the whole partner network. >> Savanna: That's a pretty casual flex there. >> Not bad. >> I love that, top 1%, that no wonder you're wearing that partner pin so proud today. (speaking indistinctly) >> But we're working all the way on the advisory and working with their pro serve organization and then transforming that into large scale mass migration services, a lot of data modernization that Srini is an absolute expert in. I'm sure he can add some context too, but it's been a great partnership for many years now. >> In the keynote, Adam spent almost 52 minutes on data, right? So, it emphasizes how organizations are ready to take data to cloud and actually make meaningful insights and help their own customers come out of it by making meaningful decisions. So, we are glad to be part of this entire ecosystem. >> I love that you quantified how many minutes. >> I know. >> Talked about it, that was impressive. There's a little bit of data driven thinking going on here. >> I think so. >> Yeah. >> Well, we can't be at an event like this without talking about data for copious amounts of time, 52 minutes, has just used this morning. >> Right, absolutely. >> But every company these days has to be a data company. There's no choice to be successful, to thrive, to survive. I mean, even to thrive and grow, if it's a grocery store or your local gas station or what? You name it, that company has to be a data company. But the challenge of the data volume, the explosion in data is huge for organizations to really try to figure out and sift through what they have, where is all of it? How do we make sense of it? How do we act on it and get insights? That's a big challenge. How is TEKsystems helping customers tackle that challenge? >> Yeah, that's a great question because that's the whole fun of handling data. You need to ensure its meaning is first understood. So, we are not just dumping data into a storage place, but rather assign a meaningful context. In today's announcement, again, the data zone was unveiled to give meaning to data. And I think those are key concrete steps that we take to our customers as well with some good blueprints, methodical ways of approaching data and ultimately gaining business insights. >> And maybe I'll add just something real quick to that. The theme we're seeing and hearing a lot about is data monetization. So, technology companies have figured it out and used techniques to personalize things and get you ads, probably that you don't want half the time. But now all industries are really looking to do that. Looking at ways to open new revenue channels, looking at ways to drive a better customer experience, a better employee experience. We've got a ton of examples of that, Big Oil and Gas leveraging like well and machine data, coming in to be more efficient when they're pumping and moving commodities around. We work a lot in the medium entertainment space and so obviously, getting targeted ads to consumers during the right periods of TV or movies or et cetera. Especially with the advert on Netflix and all your streaming videos. So, it's been really interesting but we really see the future in leveraging data as one of your biggest corporate assets. >> Brilliant. >> So, I'm just curious on the ad thing, just real quick and I'll let you go, Lisa. So, do you still fall victim to falling for the advertising even though you know it's been strategically put there for you to consume in that moment? >> Most of the time. >> I mean, I think we all do. We're all, (indistinct), you're behind the curtain so to speak. >> The Amazon Truck shows up every day at my house, which is great, right? >> Hello again >> Same. >> But I think the power of it is you are giving the customer what they're looking for. >> That's it. >> And you know... >> Exactly. We have that expectation, we want it. >> 100%. >> We know that. >> Agree. >> We don't need to buy it. But technology has made it so easy to transact. That's like when developers started going to the cloud years ago, it was just, it was a swipe. It was so simple. Brandon, talk about the changes in cloud and cloud migration that TEKsystems has seen, particularly in the last couple of years as every company was rushing to go digital because they had to. >> So several years ago, we kind of pushed away that cloud first mentality to the side and we use more of a cloud smart kind of fashion, right? Does everything need to go to the cloud? No. Do applications, data, need to go to the cloud in a way that's modern and takes advantages of what the cloud can provide and all the new services that are being released this week and ongoing. So, the other thing we're seeing is initiatives that have traditionally been in the CTO, CIO organization aren't necessarily all that successful because we're seeing a complete misalignment between business goals and IT achievements, outcomes, et cetera. You can automate things, you can move it to the cloud, but if you didn't solve a core business problem or challenge, what'd you really do? >> Yeah, just to add on that, it's all about putting data and people together. And then how we can actually ensure the workforce is equally brought up to speed on these new technologies. That has been something that we have seen tremendous improvement in the last 24 months where customers are ready to take up new challenges and the end users are ready to learn something new and not just stick onto that status quo mindset. >> Where do you guys factor in to bringing in AWS in the customer's cloud journeys? What is that partnership like? >> We always first look for where the customer is in their cloud journey path and make sure we advise them with the right next steps. And AWS having its services across the spectrum makes it even easier for us to look at what business problem they're solving and then align it according to the process and technology so that at the end of the day, we want end user adoption. We don't want to build a fancy new gadget that no one uses. >> Just because you built it doesn't mean they'll come. And I think that's the classic engineering marketing dilemma as well as balance to healthy tension. I would say between both. You mentioned Srini, you mentioned workforce just a second ago. What sort of trends are you seeing in workforce development? >> Generally speaking, there are a lot of services now that can quantify your code for errors and then make sure that the code that you're pushing into production is well tested. So what we are trying to make sure is a healthy mix of trying to solve a business problem and asking the right questions. Like today, even in the keynote, it was all about how QuickSight, for example, has additional features now that tells why something happened. And that's the kind of mindset we want our end users to adopt. Not just restricting themselves to a reactive analytics, but rather ask the question why, why did it happen? Why did my sales go down? And I think those technologies and mindset shift is happening across the workforce. >> From a workforce development standpoint, we're seeing there's not enough workforce and the core skills of data, DevOps, standard cloud type work. So, we're actually an ATP advanced training partner, one of the few within the AWS network. So, we've developed programs like our Rising Talent Program that are allowing us to bring the workforce up to the skills that are necessary in this new world. So, it's a more build versus buy strategy because we're on talents real, though it may start to wane a little bit as we change the macroeconomic outlook in 2023, but it's still there. And we still believe that building those workforce and investing in your people is the right thing to do. >> It is, and I think there's a strong alignment there with AWS and their focus on that as well. I wanted to ask you, Brandon. >> Brandon: Absolutely. >> One of the things, so our boss, John Furrier, the co CEO of theCUBE, talked with Adam Selipsky just a week or maybe 10 days ago. He always gets an exclusive interview with the CEO of AWS before reinvent, and one of the things that Adam shared with him is that customers, CEOs and CIOs are not coming to Adam, to this head of AWS to talk about technology, they want to talk about transformation. He's talking about... >> The topic this year. >> Moving away from amorphous topic of digital transformation to business transformation. Are you seeing the same thing in your customer? >> 100%, and if you're not starting at the business level, these initiatives are going to fail. We see it all the time. Again, it's about that misalignment and there's no good answer to that. But digital, I think is amorphous to some degree. We play a lot with the One North partnership that I mentioned earlier, really focusing on that strategy element because consumer dollars are shrinking via inflation, via what we're heading into, and we have to create the best experience possible. We have to create an omnichannel experience to get our products or services to market. And if we're not looking at those as our core goals and we're looking at them as IT or technology challenges, we're not looking in the right place. >> Well, and businesses aren't going to be successful if they're looking at it in those siloed organizations. Data has to be democratizing and we've spent same data democratization for so long, but really, we're seeing that it has to be moving out into the lines of business because another thing Adam shared with John Furrier is that he sees and I'm curious what your thoughts are on this, the title of data analysts going away because everybody in different functions and different lines of business within an organization are going to have to be data analysts to some degree, to use data whether it's marketing, ops, sales, finance, are you seeing the same? >> That is true. I mean, at this point, we are all in the connected world, right? Every data point is connected in some form or shape to another data point. >> Savanna: There are many data points, just sitting here, yeah. >> Absolutely, so I think if you are strategizing, data needs to be right in the center of it. And then your business problems need to be addressed with reliable data. >> No, I mean, advertising, supply chain, marketing, they're all interconnected now, and we're looking at ways to bring a lot of that siloed data into one place so we can make use to it. It goes back to that monetization element of our data. >> That's a lot about context and situational awareness. We want what we want, when we want it, even before we knew we needed it then. I think I said that right. But you know, it's always more faster, quicker and then scaling things up. You see a lot of different customers across verticals, you have an absolutely massive team. Give us a sneak peek into 2023. What does the future hold? >> 2023 is again, to today's keynote, I'm bringing it back because it was a keynote filled with vision and limitless possibilities. And that's what we see. Right now, our customers, they are no longer scared to go and take the plunge into the cloud. And as Brandon said, it's all about being smart about those decisions. So, we are very excited that together with the partnership that we recently acquired and the services and the depth, along with the horizontal domain expertise, we can actually help customers make meaningful message out of their data points. And that keeps us really excited for next year. >> Love that, Brandon, what about you? >> I think the obvious one is DevOps and a focus on optimization, financially, security, et cetera, just for the changing times. The other one is, I still think that digital is going to continue to be a big push in 2023, namely making sure that experience is at its best, whether that's employee and combating the war on talent, keeping your people or opening new revenue streams, enhancing existing revenue streams. You got to keep working on that. >> We got to keep the people happy with the machines and the systems that we are building as we all know. But it's very nice, it's been a lot of human-centric focus and a lot of customer obsession here at the show. We know it's a big thing for you all, for Amazon, for pretty much everyone who sat here. Hopefully it is in general. Hopefully there's nobody who doesn't care about their community, we're not talking to them, if that's the case, we have a new challenge on theCUBE for the show, this year as we kind of prepped you for and can call it a bumper sticker, you can call it a 30 second sizzle reel. But this is sort of your Instagram moment, your TikTok, your thought of leadership highlight. What's the most important story coming out of the show? Srini, you've been quoting the keynotes very well, so, I'm going to you first on this one. >> I think overall, it's all about owning the change. In our TEKsystems culture, it's all about striving for excellence through serving others and owning the change. And so it makes me very excited that when we get that kind of keynote resonating the same message that we invite culturally, that's a big win-win for all the companies. >> It's all about the shared vision. A lot of people with similar vision in this room right now, in this room, like it's a room, it's a massive expo center, just to be clear, I'm sure everyone can see in the background. Brandon >> I would say partnership, continuing to enhance our strategic partnership with AWS, continuing to be our customers' partners in transformation. And bringing those two things together here has been a predominance of my time this week. And we'll continue throughout the week, but we're in it together with our customers and with AWS and looking forward to the future. >> Yeah, that's a beautiful note to end on there. Brandon, Srini, thank you both so much for being here with us. Fantastic to learn from your insights and to continue to emphasize on this theme of collaboration. We look forward to the next conversation with you. Thank all of you for tuning in wherever you happen to be hanging out and watching this fabulous live stream or the replay. We are here at AWS Reinvent 2022 in wonderful sunny Las Vegas, Nevada with Lisa Martin. My name is Savannah Peterson, we are theCUBE, the leading source for high tech coverage.

(gentle music) >> Good morning from Las Vegas. It's theCUBE live at AWS Reinvent 2022 with tons of thousands of people today. Really kicks off the event. Big keynote that I think is probably just wrapping up. Lisa Martin here with Dave Vellante. Dave, this is going to be an action packed week on theCUBE no doubt. We talked with so many different companies. Every company's a software company these days but we're also seeing a lot of companies leaving software that can help them operate more efficiently in the background. >> Yeah, well some things haven't changed at Reinvent. A lot of people here, you know, back to 2019 highs and I think we exceeded those two hour keynotes. Peter DeSantis last night talking about new Graviton instances and then Adam Selipsky doing the typical two hour keynote. But what was different he was a lot more poetic than we used to hear from Andy Jassy, right? He was talking about the universe as an analogy for data. >> I loved that. >> Talked about ocean exploration as for the security piece and then exploring into the Antarctic for, you know, better chips, you know? So yeah, I think he did a good job there. I think a lot of people might not love it but I thought it was very well done. >> I thought so too. We're having kicking off a great day of live content for you all day today. We've got Eleanor Dorfman joining us, the sales leader at Retool. Eleanor, welcome to theCUBE. It's great to have you. >> Thank you so much for having me. >> So let's talk a little bit about Retool. I was looking on your LinkedIn page. I love the tagline, build custom internal tools best. >> Eleanor: Yep. >> Talk to us a little bit about the company you recently raised, series C two. Give us the backstory. >> Yeah, so the company was founded in 2017 by two co-founders who are best friends from college. They actually set out to build a FinTech company, a payments company. And as they were building that, they needed to build a ton of custom operations software that goes with that. If you're going to be managing people's money, you need to be able to do refunds. You need to be able to look up accounts, you need to be able to detect fraud, you need to do know your customer operations. And as they were building the sort of operations software that supports the business, they realized that there were patterns to all of it and that the same components were used at and again. And had the insight that that was actually probably a better direction to go in than recreating Venmo, which was I think the original idea. And that actually this is a problem every company has because every company needs operations engineering and operations software to run their business. And so they pivoted and started building Retool which is a platform for building custom operations software or internal tools. >> Dave: Good pivot. >> In hindsight, actually probably in the moment as well, was a good pivot. >> But you know, when you talk about some of those things, refunds, fraud, you know, KYC, you know, you think of operations software, you think of it as just internal, but all those things are customer facing. >> Eleanor: Yep. >> Right so, are we seeing as sort of this new era? Is that a trend that you guys, your founders saw that hey, these internal operations can be pointed at customers to support what, a better customer service, maybe even generate revenue, subscriptions? >> I think it's a direction we're actually heading now but we're just starting to scratch the surface of that. The focus for the last five years has very much been on this operations software and sort of changing the economics of developing it and making it easy and fast to productize workflows that were previously being done in spreadsheets or hacky workarounds and make it easier for companies to prioritize those so they can run their business more efficiently. >> And where are you having your customer conversations these days? Thinking of operations software in the background, but to Dave's point, it ends up being part of the customer experience. So where are you having your customer conversations, target audience, who's that persona? >> Mainly developers. So we're working almost exclusively with developer teams who have backlogs and backlogs of internal tools requests to build that sales teams are building manual forecasts. Support teams are in 19 different tools. Their supply chain teams are using seven different spreadsheets to do demand forecasting or freight forwarding or things like that. But they've never been able to be prioritized to the top of the list because customer facing software, revenue generating software, always takes prioritization. And in this economic environment, which is challenging for many companies right now, it's important to be able to do more with less and maximize the productivity especially of high value employees like engineers and developers. >> So what would you say the biggest business outcomes are? If the developer is really the focus, productivity is the- >> Productivity. It's for both, I would say. Developer productivity and being able to maximize your sort of R and D and maximize the productivity of your engineers and take away some of the very boring parts of the job. But, so I would say developer productivity, but then also the tools and the software that they're building are very powerful for end users. So I would say efficiency and productivity across your business. >> Across the business. >> I mean historically, you know, operations is where we focused IT and code. How much of the code out there is dedicated to sort of operations versus that customer facing? >> So I think it would actually be, it's kind of surprising. We have run a few surveys on this sort of, we call them the state of engineering time, and focusing on what developers are spending their time on. And a third of all code that is being written today is actually for this internal operations software. >> Interesting. And do you guys have news at the show? Are you announcing anything interesting or? >> Yeah, so our focus historically, you sort of gave away with one of your early questions, but our focus has always been on this operations, this building web applications on building UIs on top of databases and APIs and doing that incredibly fast and being able to do it all in one place and integrate with as any data source that you need. We abstract away access authentication deployment and you build applications for your internal teams. But recently, we've launched two new products. We're actually supporting more external use cases and more customer facing use cases as well as automating CRON jobs, ETL jobs alerting with the new retail workflows product. So we're expanding the scope of operations software from web applications to also internal operations like CRON jobs and ETL jobs. >> Explain that. Explain the scourge of CRON jobs to the audience. >> Yeah, so operations software businesses run on operations software. It's interesting, zooming out, it's actually something you said earlier as well. Every company has become a software company. So when you think about software, you tend to think about here. Very cool software that people are selling. And software that you use as a consumer. But Coca-Cola for example, has hundreds of software engineers that are building tools to make the business run for forecasting, for demand gen, for their warehouse distribution and monitoring inventory. And there's two types of that. There's the applications that they build and then the operations that have to run behind that. Maybe a workflow that is detecting how many bottles of Coca-Cola are in every warehouse and sending a notification to the right person when they're out or when they, a refill is very strong, but you know when you need a refill. So it does that, it takes those tasks, those jobs that run in the background and enables you to customize them and build them very rapidly in a code first way. >> So some of the notes that you guys provided say that there's over 500 million software apps that are going to be built in the next few years alone. That's tremendous. How much of that is operation software? >> I mean I think at least a third of that, if not more. To the point where every company is being forced to maximize their resources today and operational efficiency is the way to do that. And so it can become a competitive advantage when you can take the things that humans are doing in spreadsheets with 19 open tabs and automate that. That saves hours a day. That's a significant, significant driver of efficiency and productivity for a business >> It does, and there's direct correlation to the customer experience. The use experience. >> Almost certainly. When you think about building support tooling, I was web chat, chatting on the with Gogo wifi support on my flight over here and they asked for my order number and I sent it and they looked up my account and that's a custom piece of software they were using to look up the account, create a new account for me, and restore my second wifi purchase. And so when you think about it, you're actually, even just as a consumer, interacting with this custom software on the day time. And that's because that's what companies use to have a good customer experience and have an efficient business. >> And what's the relationship with AWS? You guys started, I think you said 2017, so you obviously started in the cloud, but I'm particularly interested in from a seller perspective, what that's like. Working with Amazon, how's that affected your business? >> Yeah, I mean so we're built on AWS, so we're customers and big fans. And obviously like from a selling perspective, we have a ton of integrations with AWS so we're able to integrate directly into all the different AWS products that people are using for databases, for data warehouses, for deployment configurations, for monitoring, for security, for observability, we can basically fit into your existing AWS stack in order to make it as seamless integration with your software so that building in Retool is just as seamless as building it on your own, just much, much faster. >> So in your world, I know you wanted to but, in your world is it more analytics? is it more transactional, sort of? Is it both? >> It's all of the above. And I think what's, over Thanksgiving, I was asked a lot to explain what Retool did with people who were like, we just got our first iPhone. And so I tried to explain with an example because I have yet to stumble on the perfect metaphor. But the example I typically use is DoorDash is a customer of ours. And for about three years, and three years ago, they had a problem. They had no way of turning off delivery in certain zip codes during storms. Which as someone who has had orders canceled during a storm, it's an incredibly frustrating experience. And the way it worked is that they had operation team members manually submitting requests to engineers to say there's a storm in this zip code and an engineer would run a manual task. This didn't scale with Doordash as they were opening in new countries all over the world that have very different weather patterns. And so they looked, they had one, they were sort of confronted with a choice. They could buy a piece of software out of the box. There is not a startup that does this yet. They could build it by hand, which would mean scoping the requirements designing a UI, building authentication, building access controls, putting it into a, putting it into a sprint, assigning an engineer. This would've taken months and months. And then it would take just as long to iterate on it or they could use Retool. So they used Retool, they built this app, it saved, I think they were saying up to two years of engineering time for this one application because of how quickly it was. And since then they've built, I think 50 or 60 more automating away other tasks like that that were one out of spreadsheets or in Jira or in Slack notifications or an email saying, "Hey, could you please do this thing? There's a storm." And so now they use us for dozens and dozens of operations like that. >> A lot of automation and of course a lot of customer delight on the other end of the spectrum as you were talking about. It is frustrating when you don't get that order but it's also the company needs to be able to have the the tools in place to automate to be able to react quickly. >> Eleanor: Exactly. >> Because the consumers are, as we know, quite demanding. I wanted to ask you, I mentioned the tagline in the beginning, build custom internal tools fast. You just gave us a great example of DoorDash. Huge business outcomes they're achieving but how fast are we talking? How fast can the average developer build these internal tools? >> Well, we've been doing a fun thing at our booth where we ask people what a problem is and build a tool for them while we're there. So for something lightweight, you can build it in 10 minutes. For something a little more complex, it can take up to a few weeks depending on what the requirements are. But we all have people who will be on a call with us introducing them to our software for the first time and they'll start telling us about their problems and in the background we'll be building it and then at the end we're like, is this what you meant? And they're like, we'd like to add that to our cart. And obviously, it's a platform so you can't do that. But we've been able to build applications on a call before while people are telling us what they need. >> So fast is fast. >> I would say very fast, yeah. >> Now how do you price? >> Right now, we have a couple different plans. We actually have a motion where you can sign up on our website and get started. So we have a free plan, we've got plans for startups, and then we've got plans all the way up to the enterprise. >> Right. And that's a subscription pricing kind of thing? >> Subscription model, yes. >> So I get a subscription to the platform and then what? Is there also a consumption component? >> Exactly. So there's a consumption component as well. So there's access to the platform and then you can build as many applications as you need. Or build as many workflows. >> When you're having customer conversations with prospects, what do you define as Retool's superpowers? You're the sales leader. What are some of those key superpowers that you think really differentiate Retool? >> I do think, well, the sales team first and foremost, but that's not a fair answer. I would say that people are a bit differentiator though. We have a lot of very talented people who are have a ton of domain expertise and care a ton about the customer outcomes, which I do actually think is a little more rare than it should be. But we're one of the only products out there that's built with a developer first mindset, a varied code first mindset, built to integrate with your software development life cycle but also built with the security and robustness that enterprise companies require. So it's able to take an enterprise grade software with a developer first approach while still having a ton of agility and nimbleness which is what people are really craving as the earth keeps moving around them. So I would say that's something that really sets us apart from the field. >> And then talk about some of the what developers are saying, some of the feedback, some of the responses, and maybe even, I know we're just on day one of the show, but any feedback from the booth so far? >> We've had a few people swing by our booth and show us their Retool apps, which is incredibly cool. That's my absolute favorite thing is encountering a Retool application in the wild which happens a lot more than I would've thought, which I shouldn't say, but is incredibly rewarding. But people love it. It's the reason I joined is I'd never heard someone have a product that customers talked about the way they talk about Retool because Retool enables them to do things. For some folks who use it, it enables them to do something they previously couldn't do. So it gives them super powers in their job and to triple their impact. And then for others, it just makes things so fast. And it's a very delightful experience. It's very much built by developers, for developers. And so it's built with a developer's first mindset. And so I think it's quite fun to build in Retool. Even I can build and Retool, though not well. And then it's extremely impactful and people are able to really impact their business and delight their coworkers which I think can be really meaningful. >> Absolutely. Delighting the coworkers directly relates to delighting the customers. >> Eleanor: Exactly. >> Those customer experience, employee experience, they're like this. >> Eleanor: Exactly. >> They go hand in hand and the employee experience has to be outstanding to be able to delight those customers, to reduce churn, to increase revenue- >> Eleanor: Exactly. >> And for brand reputation. >> And it also, I think there is something as someone who is customer facing, when my coworkers and developers I work with build tools that enable me to do my job better and feel better about my own performance and my ability to impact the customer experience, it's just this incredibly virtuous cycle. >> So Retool.com is where folks can go to learn more and also try that subscription that you said was free for up to five users. >> Yes, exactly. >> All right. I guess my last question, well couple questions for you. What are some of the things that excited you that you heard from Adam Selipsky this morning? Anything from the keynote that stood out in terms of- >> Dave: Did you listen to the keynote? >> I did not. I had customer calls this morning. >> Okay, so they're bringing- >> East coast time, east coast time. >> One of the things that will excite you I think is they're connecting, making it easier to connect their databases. >> Eleanor: That would very much exciting. >> Aurora and Redshift, right? Okay. And they're making it easier to share data. I dunno if it goes across regions, but they're doing better integration. >> Amazing. >> Right? And you guys are integrating with those tools, right? Those data platforms. So that to me was a big thing for you guys. >> It is also and what a big thing Retool does is you can build a UI layer for your application on top of every single data source. And you hear, it's funny, you hear people talk about the 360 degree review of the customer so much. This is another, it's not our primary value proposition, but it is certainly another way to get there is if you have data from their desk tickets from in Redshift, you have data from Stripe, from their payments, you have data from Twilio from their text messages, you have data from DataDog where they're having your observability where you can notice analytics issues. You can actually just use Retool to build an app that sits on top of that so that you can give your support team, your sales team, your account management team, customer service team, all of the data that they need on their customers. And then you can build workflows so that you can do automated customer engagement reports. I did a Slack every week that shows what our top customers are doing with the product and that's built using all of our automation software as well. >> The integration is so important, as you just articulated, because every, you know, we say every company's a software company these days. Every company's a data company. But also, the data democratization that needs to happen to be able for lines of business so that data moves out of certain locked in functions and enables lines of business to use it. To get that visibility that you were just talking about is really going to be a competitive advantage for those that survive and thrive and grow in this market. >> It's able to, I think it's first it's visibility, but then it's action. And I think that's what Retool does very uniquely as well is it can take and unite the data from all the places, takes it out of the black box, puts it in front of the teams, and then enables them to act on it safely and securely. So not only can you see who might be fraudulent, you can flag them as fraud. Not only can you see who's actually in danger, you can click a button and send them an email and set up a meeting. You can set up an approval workflow to bring in an exec for engagement. You can update a password for someone in one place where you can see that they're having issues and not have to go somewhere else to update the password. So I think that's the key is that Retool can unlock the data visibility and then the action that you need to serve your customers. >> That's a great point. It's all about the actions, the insights that those actions can be acted upon. Last question for you. If you had a billboard that you could put any message that you want on Retool, what would it say? What's the big aha? This is why Retool is so great. >> I mean, I think the big thing about Retool is it's changing the economics of software development. It takes something that previously would've been below the line and that wouldn't get prioritized because it wasn't customer facing and makes it possible. And so I would say one of two billboards if I could be a little bit greedy, one would be Retool changed the economics of software development and one would be build operations software at the speed of thought. >> I love that. You're granted two billboards. >> Eleanor: Thank you. >> Those are both outstanding. Eleanor, it's been such a pleasure having you on the program. Thank you for talking to us about Retool. >> Eleanor: Thank you. >> Operations software and the massive impact that automating it can make for developers, businesses alike, all the way to the top line. We appreciate your insights. >> Thank you so much. >> For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live, emerging, and enterprise tech coverage. (gentle music)

>>Hey everyone. Welcome back to Las Vegas. The cube is live at the Venetian Expo Center for AWS Reinvent 2022. There are thousands and thousands and thousands of people here joining myself, Lisa Martin at Dave Valante. David, it's great to see the energy of day one alone. People are back, they're ready to be back. They're ready to hear from AWS and what it's gonna announce to. >>Yeah, all through the pandemic. Of course, we've talked about digital transformation, but the conversation is evolving beyond that to business transformation now, deeper integration of the cloud to really transform fundamental business operations and And that's a new era. >>It is a new era. It's exciting. We've got a couple of guests that we're gonna unpack that with. Anan. Beji joins us, the President Digital Business Services at HCL Tech and Prar, SVP and Global head of AWS business unit. Also from HCL Tech. Guys, welcome. Thank >>You. Thank you, >>Thank you. >>Let's talk about some of the latest trends anon. We'll start with you. What are some of the latest trends in digitalization, especially as it relates to cloud adoption? What are you hearing out in the marketplace? >>Yeah, I think you said it right. The post pandemic, every industry, every enterprise and every industry realize that for resilience, for their ability to change and adapt change and their ability to increase, you know, velocity of change so that they can move fast and keep up the expectations of their consumers, their partners, their employees, they need to have composability at the core and resilience at the core. And so, digital transformation became all about the ability to change, an ability to pivot faster. Now, it's easier said than done, right? Larger enterprises, especially as you move into complex regulated industries, you know, oil and gas, manufacturing, life sciences, healthcare, utilities, these are industries that are not easy to change. They're not adaptable to change, and yet they had to really become more adaptable. And they saw cloud as an enabler to, to all of that, right? So they started looking at every area of their business, business processes that make up their value chains and really look at how can they increase the adaptability and the ability to change these value chains so that they can engage with their customers better, their partners, better their employees better, and also build some of the composability. >>And what might mean that is that just kind of like Lego blocks, they don't have to make changes that are sweeping and big that are difficult to make, but make them in parts so that they can make them again and again. So velocity of change becomes important. Clouds become an enabler to all of this. And so if I look at the last four years, every industry, whether regulated or not b2c, B2B to C, B2B is adopting cloud for digital acceleration. >>I'm curious to what you're seeing on the front lines, given the macro headwinds. You mentioned business resilience and during the pandemic, it was a lot of CIOs told us, wow, we were, we were kind of focused on disaster recovery, but our business wasn't resilient. We were really optimizing for efficiency. And then they started to okay, build in that business resilience. But now you got the economic headwinds. Yes. People are tapping their brakes a little bit. There's some uncertainty, a longer sales cycle, even the cloud's not immune. Yeah. Even though it's still growing at 30% plus per year. What are you guys seeing in the field with the AWS partnership? How are customers, you know, dealing with some of those more strategic transformation projects? Yeah, >>Yeah. So you know, first off, one thing that's changed and is different is every industry realizes that there is no choice. They don't have a choice to not be resilient. They don't have a choice to not be adaptable. The pandemic has taught them that the markets and the macros are increasingly changing supply chains. It's changing customer behavior for their own industries. It's changing their pricing and their cost models. And for all of that, they need to continue on their digital journeys. Now, what's different though is they wanna prioritize. They wanna prioritize and do more with less. They want to adapt faster, but also make sure that they don't, they don't just try to do everything together. And so there's a lot of focus on what do we prioritize? How do we leverage cloud to move faster, you know, and cheaper in terms of our change. >>And also to decide where do we consume and where do we compose? We'll talk a little bit more about that. There are certain things that you don't want to invent yourself. You can consume from cloud providers, whether it's business features, whether it is cloud capabilities. And so it's, there is a shift from adopting cloud just for cost takeout and just for resilience, but also for composability, which means let's consume what I can consume from the cloud and really build those features faster. So squeeze the go to market time, squeeze the time to market and squeeze the price to market, right? So that's the >>Change and really driving those business outcomes. As we talked about Absolut ard, talk to us about how hcl tech and AWS are working together. How are you enabling customers to achieve what an was talking about? >>Oh, absolutely. I mean, our partnership has started almost 10 years back, but over the last one year, we have created what we call as AWS dedicated business unit to look at end to end stock from an AWS perspective. So what we see in the market as a explained is more drive from clients for optimization, driving, app modernization, driving consolidation, looking at the cost, sustainability angles, looking at the IOT angle, manufacturing platforms, the industry adoption. All this is actually igniting the way the industry would look at AWS and as well as the partnership. So from an HCL tech and AWS partnership, we're actually accelerating most of these conversations by building bespoke accelerated industry solutions. So what I mean is, for example, there is an issue with a manufacturing plant and take Covid situation, people can't get into a a manufacturing plant. So how can AWS help put it in the cloud, accelerate those conversations. So we are building those industry specific solutions so that it can be everybody from a manufacturing sector can adopt and actually go to market. As well as you can access all this applications once it is in the cloud from anywhere, any device with a scalable options. That's where our partnership is actually igniting lot of cloud conversations and playing conversations in the market. So we see a lot of traction there. Lisa, on >>That, incredibly important during the last couple of years alone. >>Absolutely. I mean, last couple of years have been groundbreaking, right? Especially with the covid, for example, Amazon Connect, we use, we used Amazon Connect to roll out, you know, call center at the cloud, right? So you don't have to walk into an office, for example. People are working in the banking sector, especially in the trading platform. They were, they were not able to get there. So, but they need to make calls. How do you do the customer service? So Amazon Connect came right at the junction, so call center in the cloud and you can access, dial the number so the customer don't feel the pain of, you know, somebody not answering. It's accessible. That's where the partnership or the HCL tech partnership and AWS comes into play because we bring the scale, the skill set capability with the services of, you know, aws, Amazon, and that forms a concrete story for the client, right? That's one such example. And you know, many such examples are in the market that we are accelerating in the, in the discussions. >>And connect is a good example. Lisa, we were talking earlier about Amazon doubling down on the primitives, but also moving up up market as well, up chain up the value chain. And it needs partners like HCL to be able to go into various industries and apply that effectively. Absolutely. And that's where business transformation comes >>In. Absolutely. Absolutely. I think some of the aspects that we are looking at is, you know, while we do most of this cloud transformation initiatives from an tech perspective, what we are doing is we are encompassing them into a story, which we call it as cloud smart, right? So we are calling it as cloud smart, which is a go-to market offering from Atcl Tech, where the client doesn't have to look at each of these services from various vendors. So it's a one stop shop, right? From strategy consulting, look, implementation, underpinned by app modernization, consolidation, and the operational. So we do that as end to end service with our offerings, which is why helping us actually accelerate conversations on the crowd. What happen is the clients are also building these capabilities more and more often. You see a lot of new services are being added to aws, so not many clients are aware of it. So it is the responsibility of system integrator like us to make them aware and bring it into a shape where the client can consume in a low cost option, in an optimized way. That's where I think it's, it's, it's working out very well for us. With the partnership of, so >>You curate those services that you know will fit the customer's business. You, you know, the ingredients that you could put together, the, the dinner. >>Absolutely. You're preparing a dish, right? So you're preparing a dish, you know where the ingredients are. So the ingredients are supplied by aws. So you need to prepare a pasta dish, right? So you, you how spicy you want to make it howland, you want to make it, you know what source you want to use. How do you bring all those elements together? That's what, you know, tech has been focusing on. >>And you use the word curation, right? Curation is really industry process down, depending on your industry, every industry, every enterprise, there are things that are differentiating them. There's a business processes that differentiate you and there are business processes that don't necessarily differentiate you but are core to you. For example, if you're a retailer, you know, you're retailing, you're merchandising, how you price your products, how you market your products, your supply chains, those differentiate you. How you run your general ledger, your accounting, your payables. HR is core to your business but doesn't differentiate you. And the choices you make in the cloud for each of these areas are different. What differentiates you? You compose what doesn't differentiate you consume because you don't want to try and compose what >>Telco Exactly. Oh my gosh. >>Our biggest examples are in Telco, right? Right. Their omnichannel marketing, you know, how they connect with their consumers, how they do their billing systems, how they do their pricing systems. Those are their differentiations and things that don't they want to consume. And that's where cloud adoption needs to come with really a curation framework. We call it the Phoenix framework, which defines what differentiates you versus not. And based on that, what are the architectural choices you make at the applications layer, the integration layer, the data layer, and the infrastructure layer all from aws and how do you make those choices? >>Talk about a customer example anon that really articulates that value. >>Yeah, I'll give you an example that sort of, everybody can relate to a very large tools company that manufactures tools that we all use at home for, you know, remodeling our houses, building stuff, building furniture. Their business post pandemic dramatically shifted in every way possible. Nobody was going anymore to Home Depot and Lowe's to buy their tools, their online business surge by 200%. Their supply chains were changing because their manufacturers originally were in China and Malaysia. They were shifting a lot of that base to Taiwan and Germany and Latin America. Their pricing model was changing. Their last mile deliveries were changing cuz they were not used to delivering you and me last mile deliveries. So every aspect of their business was changing. They hadn't thought of their business in the same way, but guess what? That business was growing, but the needs were changing and they needed to rethink every value chain in their business. >>And so they had to adopt cloud. They leverage AWS at their core to rethink every part of their business. Rebuilding their supply chain applications, modernizing their warehouse management systems, modernizing their pricing systems, modernizing their sales and marketing platforms, every aspect you can think of and all of that within 24 months. Cuz otherwise they would lose market share, you know, in any given market. And all of this, while they were, you know, delivering their day to day business, they were manufacturing the goods and they were shipping products. So that was quite a lot to achieve in 24 months. And that's not just one example is across industries, examples like that that we have. That's >>One of the best business transformation examples I think I've heard. >>Absolutely. Absolutely. And so cloud does need to start with a business transformation objective. And that's what's happening to the cloud. It's changing away from an infrastructure consolidation discussion to business task. >>Because I know you guys have a theater session tomorrow on, on continuous modern, it was experiencing cloud transformation and continuous modernization. That's the theme. Pre-cloud. It was just a, you'd, you'd live, you'd rip and replace your infrastructure and it was a big application portfolio assessment and rationalization. It was just, it just became this years long, you know, like an SAP installation. Yes. How has cloud changed that and what's, tell us more about that session and that continuous modernization. Yeah, >>So, so we are doing a John session with a client on how HCL Tech helped the client in terms of transforming the landscape and adopting cloud much faster, you know, into the ecosystem. So what we are currently doing is, so it's a continuous process. So when we talk about cloud adoption transformation, it doesn't stop there. So it, it needs to keep evolving. So what we came up with a framework for the all such clients who are on the cloud transformation part need to look at which we call it a smart waste cloud, cloud smart. Where once it is in the clouds, smart waste to cloud for cloud and in the cloud. So what happens is, when it is to cloud, what do you do? What are the accelerators? What are the frameworks? Smart waste for clouds? How do you look at the governance of it? >>Okay? Consolidation activities of it, once it is in the cloud, how do we optimize, what do you look at? Security aspects, et cetera. So the client doesn't have to go to multiple ecosystem partners to look at it. So he is looking at one such service provider who can actually encompass and give all this onto the plate in a much more granular fashion with accelerated approach. So we build accelerated solutions frameworks, which helps the client to actually pick and choose in a much lower cost, I think. And it has to be a continuous modernization for the client. So why we are calling it as a continuous modernization is we are also also creating what we call cloud foundries and factories. What happens is the client can look at not only in a transformation journey, but also futuristic when there are new services are adapted, how this transformation and factories helping them in a lower cost option and driving that a acceleration story. So we are addressing it in multiple ways. One on the transformation front, one on the TCO front, one on the AX accelerated front, one on the operational front. So all this combined into one single framework, which is what is a continuous modernization of clouded option from xgl tech. >>When you apply this framework with customers, how do you deal with technical debt? Can you avoid technical debt? Can you hide technical debt? Or is it like debt and taxes? We're always gonna have technical debt because Amazon, you know, they'll talk about, they don't ever deprecate anything. Yeah. You know, are they gonna, are we gonna see Amazon take on tech? How do you avoid that? Or at least shield the customer for that technical debt. >>So every cio, right? Key ambitions are digital cloud, TCO optimization, sustainability. So we have a framework for that. So every CIO will look at, okay, I wanna spend, but I want to be optimized. My TCO should not go up. So that's where a system integrator like us comes. We have AOP story where, which does the complete financial analysis of your cloud adoption as to what estate and what technical client already has. How can we optimize that and how can we, how can we overlay on top of that our own services to make it much more optimized solution for the client? And there are several frameworks that we have defined for the CIO organizations where the CIO can actually look at some of these elements and adopt it internally within the system. You wanna pick it from there? >>Yeah, I think, I think it's, it's, it's a great question. First of all, there's a generational shift in the last three years where nobody's doing lift and shift of traditional applications or traditional data systems to the cloud. As you said, nobody's taking their technical debt to the cloud anymore. >>Business value's not there. >>There's no business value, right? The value is really being cloud native, which means you want to continuously modernize your value chains, which means your applications, your integration, your data to leverage the cloud and continuously modernize. Now you will still make priority decisions, right? Things that really differentiate you. You will modernize them through composition things that don't, you'll rather consume them, but in both factors, you're modernizing, I use the word surround and drown enterprises are surrounding their traditional, you know, environments and drowning them over a period of time. So over the next five years, you'll see more and more irrelevant legacy because the relevance is being built in the cloud, cloud for the future. That's the way I see it. >>Speaking of, take us out here, speaking of business value and on, we're almost outta time here. If there's a billboard on 1 0 1 in Palo Alto regarding HCL tech, what's the value prop? What does it say? >>It's a simple billboard. We say we are super charging our customers, our partners, our employees. We are super charging progress. And we believe that the strength that we bring from learnings of over 200,000 professionals that work at hcl working with over half of, you know, 500 of the, the largest Fortune thousands in the world is, is really bringing those learnings that we continuously look at every day that we live with, every day across all kind of regulations, all kind of industries, in adopting new technologies, in modernizing their business strategies and achieving their business transformation goals with the velocity they want. That's kind of the supercharging progress mantra, >>Super charging progress. Love it. Guys, thank you so much for joining. David, me on the program talking about, thank you for having a conversation. Our pleasure. What's going on with HCL Tech, aws, the value that you're delivering for customers. Thank you so much for your time. Thank >>You. Thank you. Thanks. Have a great time. >>Take care for our guests. I'm Lisa Martin, he's Dave Valante. You're watching The Cube, the leader in live enterprise and emerging tech coverage.

>>Hey everyone. Welcome to Las Vegas. The Cube is here, live at the Venetian Expo Center for AWS Reinvent 2022. Amazing attendance. This is day one of our coverage. Lisa Martin here with Day Ante. David is great to see so many people back. We're gonna be talk, we've been having great conversations already. We have a wall to wall coverage for the next three and a half days. When we talk to companies, customers, every company has to be a data company. And one of the things I think we learned in the pandemic is that access to real time data and real time analytics, no longer a nice to have that is a differentiator and a competitive all >>About data. I mean, you know, I love the topic and it's, it's got so many dimensions and such texture, can't get enough of data. >>I know we have a great guest joining us. One of our alumni is back, Evan Kaplan, the CEO of Influx Data. Evan, thank you so much for joining us. Welcome back to the Cube. >>Thanks for having me. It's great to be here. So here >>We are, day one. I was telling you before we went live, we're nice and fresh hosts. Talk to us about what's new at Influxed since the last time we saw you at Reinvent. >>That's great. So first of all, we should acknowledge what's going on here. This is pretty exciting. Yeah, that does really feel like, I know there was a show last year, but this feels like the first post Covid shows a lot of energy, a lot of attention despite a difficult economy. In terms of, you know, you guys were commenting in the lead into Big data. I think, you know, if we were to talk about Big Data five, six years ago, what would we be talking about? We'd been talking about Hadoop, we were talking about Cloudera, we were talking about Hortonworks, we were talking about Big Data Lakes, data stores. I think what's happened is, is this this interesting dynamic of, let's call it if you will, the, the secularization of data in which it breaks into different fields, different, almost a taxonomy. You've got this set of search data, you've got this observability data, you've got graph data, you've got document data and what you're seeing in the market and now you have time series data. >>And what you're seeing in the market is this incredible capability by developers as well and mostly open source dynamic driving this, this incredible capability of developers to assemble data platforms that aren't unicellular, that aren't just built on Hado or Oracle or Postgres or MySQL, but in fact represent different data types. So for us, what we care about his time series, we care about anything that happens in time, where time can be the primary measurement, which if you think about it, is a huge proportion of real data. Cuz when you think about what drives ai, you think about what happened, what happened, what happened, what happened, what's going to happen. That's the functional thing. But what happened is always defined by a period, a measurement, a time. And so what's new for us is we've developed this new open source engine called IOx. And so it's basically a refresh of the whole database, a kilo database that uses Apache Arrow, par K and data fusion and turns it into a super powerful real time analytics platform. It was already pretty real time before, but it's increasingly now and it adds SQL capability and infinite cardinality. And so it handles bigger data sets, but importantly, not just bigger but faster, faster data. So that's primarily what we're talking about to show. >>So how does that affect where you can play in the marketplace? Is it, I mean, how does it affect your total available market? Your great question. Your, your customer opportunities. >>I think it's, it's really an interesting market in that you've got all of these different approaches to database. Whether you take data warehouses from Snowflake or, or arguably data bricks also. And you take these individual database companies like Mongo Influx, Neo Forge, elastic, and people like that. I think the commonality you see across the volume is, is many of 'em, if not all of them, are based on some sort of open source dynamic. So I think that is an in an untractable trend that will continue for on. But in terms of the broader, the broader database market, our total expand, total available tam, lots of these things are coming together in interesting ways. And so the, the, the wave that will ride that we wanna ride, because it's all big data and it's all increasingly fast data and it's all machine learning and AI is really around that measurement issue. That instrumentation the idea that if you're gonna build any sophisticated system, it starts with instrumentation and the journey is defined by instrumentation. So we view ourselves as that instrumentation tooling for understanding complex systems. And how, >>I have to follow quick follow up. Why did you say arguably data bricks? I mean open source ethos? >>Well, I was saying arguably data bricks cuz Spark, I mean it's a great company and it's based on Spark, but there's quite a gap between Spark and what Data Bricks is today. And in some ways data bricks from the outside looking in looks a lot like Snowflake to me looks a lot like a really sophisticated data warehouse with a lot of post-processing capabilities >>And, and with an open source less >>Than a >>Core database. Yeah. Right, right, right. Yeah, I totally agree. Okay, thank you for that >>Part that that was not arguably like they're, they're not a good company or >>No, no. They got great momentum and I'm just curious. Absolutely. You know, so, >>So talk a little bit about IOx and, and what it is enabling you guys to achieve from a competitive advantage perspective. The key differentiators give us that scoop. >>So if you think about, so our old storage engine was called tsm, also open sourced, right? And IOx is open sourced and the old storage engine was really built around this time series measurements, particularly metrics, lots of metrics and handling those at scale and making it super easy for developers to use. But, but our old data engine only supported either a custom graphical UI that you'd build yourself on top of it or a dashboarding tool like Grafana or Chronograph or things like that. With IOCs. Two or three interventions were important. One is we now support, we'll support things like Tableau, Microsoft, bi, and so you're taking that same data that was available for instrumentation and now you're using it for business intelligence also. So that became super important and it kind of answers your question about the expanded market expands the market. The second thing is, when you're dealing with time series data, you're dealing with this concept of cardinality, which is, and I don't know if you're familiar with it, but the idea that that it's a multiplication of measurements in a table. And so the more measurements you want over the more series you have, you have this really expanding exponential set that can choke a database off. And the way we've designed IIS to handle what we call infinite cardinality, where you don't even have to think about that design point of view. And then lastly, it's just query performance is dramatically better. And so it's pretty exciting. >>So the unlimited cardinality, basically you could identify relationships between data and different databases. Is that right? Between >>The same database but different measurements, different tables, yeah. Yeah. Right. Yeah, yeah. So you can handle, so you could say, I wanna look at the way, the way the noise levels are performed in this room according to 400 different locations on 25 different days, over seven months of the year. And that each one is a measurement. Each one adds to cardinality. And you can say, I wanna search on Tuesdays in December, what the noise level is at 2:21 PM and you get a very quick response. That kind of instrumentation is critical to smarter systems. How are >>You able to process that data at at, in a performance level that doesn't bring the database to its knees? What's the secret sauce behind that? >>It's AUM database. It's built on Parque and Apache Arrow. But it's, but to say it's nice to say without a much longer conversation, it's an architecture that's really built for pulling that kind of data. If you know the data is time series and you're looking for a time measurement, you already have the ability to optimize pretty dramatically. >>So it's, it's that purpose built aspect of it. It's the >>Purpose built aspect. You couldn't take Postgres and do the same >>Thing. Right? Because a lot of vendors say, oh yeah, we have time series now. Yeah. Right. So yeah. Yeah. Right. >>And they >>Do. Yeah. But >>It's not, it's not, the founding of the company came because Paul Dicks was working on Wall Street building time series databases on H base, on MyQ, on other platforms and realize every time we do it, we have to rewrite the code. We build a bunch of application logic to handle all these. We're talking about, we have customers that are adding hundreds of millions to billions of points a second. So you're talking about an ingest level. You know, you think about all those data points, you're talking about ingest level that just doesn't, you know, it just databases aren't designed for that. Right? And so it's not just us, our competitors also build good time series databases. And so the category is really emergent. Yeah, >>Sure. Talk about a favorite customer story they think really articulates the value of what Influx is doing, especially with IOx. >>Yeah, sure. And I love this, I love this story because you know, Tesla may not be in favor because of the latest Elon Musker aids, but, but, but so we've had about a four year relationship with Tesla where they built their power wall technology around recording that, seeing your device, seeing the stuff, seeing the charging on your car. It's all captured in influx databases that are reporting from power walls and mega power packs all over the world. And they report to a central place at, at, at Tesla's headquarters and it reports out to your phone and so you can see it. And what's really cool about this to me is I've got two Tesla cars and I've got a Tesla solar roof tiles. So I watch this date all the time. So it's a great customer story. And actually if you go on our website, you can see I did an hour interview with the engineer that designed the system cuz the system is super impressive and I just think it's really cool. Plus it's, you know, it's all the good green stuff that we really appreciate supporting sustainability, right? Yeah. >>Right, right. Talk about from a, what's in it for me as a customer, what you guys have done, the change to IOCs, what, what are some of the key features of it and the key values in it for customers like Tesla, like other industry customers as well? >>Well, so it's relatively new. It just arrived in our cloud product. So Tesla's not using it today. We have a first set of customers starting to use it. We, the, it's in open source. So it's a very popular project in the open source world. But the key issues are, are really the stuff that we've kind of covered here, which is that a broad SQL environment. So accessing all those SQL developers, the same people who code against Snowflake's data warehouse or data bricks or Postgres, can now can code that data against influx, open up the BI market. It's the cardinality, it's the performance. It's really an architecture. It's the next gen. We've been doing this for six years, it's the next generation of everything. We've seen how you make time series be super performing. And that's only relevant because more and more things are becoming real time as we develop smarter and smarter systems. The journey is pretty clear. You instrument the system, you, you let it run, you watch for anomalies, you correct those anomalies, you re instrument the system. You do that 4 billion times, you have a self-driving car, you do that 55 times, you have a better podcast that is, that is handling its audio better, right? So everything is on that journey of getting smarter and smarter. So >>You guys, you guys the big committers to IOCs, right? Yes. And how, talk about how you support the, develop the surrounding developer community, how you get that flywheel effect going >>First. I mean it's actually actually a really kind of, let's call it, it's more art than science. Yeah. First of all, you you, you come up with an architecture that really resonates for developers. And Paul Ds our founder, really is a developer's developer. And so he started talking about this in the community about an architecture that uses Apache Arrow Parque, which is, you know, the standard now becoming for file formats that uses Apache Arrow for directing queries and things like that and uses data fusion and said what this thing needs is a Columbia database that sits behind all of this stuff and integrates it. And he started talking about it two years ago and then he started publishing in IOCs that commits in the, in GitHub commits. And slowly, but over time in Hacker News and other, and other people go, oh yeah, this is fundamentally right. >>It addresses the problems that people have with things like click cows or plain databases or Coast and they go, okay, this is the right architecture at the right time. Not different than original influx, not different than what Elastic hit on, not different than what Confluent with Kafka hit on and their time is you build an audience of people who are committed to understanding this kind of stuff and they become committers and they become the core. Yeah. And you build out from it. And so super. And so we chose to have an MIT open source license. Yeah. It's not some secondary license competitors can use it and, and competitors can use it against us. Yeah. >>One of the things I know that Influx data talks about is the time to awesome, which I love that, but what does that mean? What is the time to Awesome. Yeah. For developer, >>It comes from that original story where, where Paul would have to write six months of application logic and stuff to build a time series based applications. And so Paul's notion was, and this was based on the original Mongo, which was very successful because it was very easy to use relative to most databases. So Paul developed this commitment, this idea that I quickly joined on, which was, hey, it should be relatively quickly for a developer to build something of import to solve a problem, it should be able to happen very quickly. So it's got a schemaless background so you don't have to know the schema beforehand. It does some things that make it really easy to feel powerful as a developer quickly. And if you think about that journey, if you feel powerful with a tool quickly, then you'll go deeper and deeper and deeper and pretty soon you're taking that tool with you wherever you go, it becomes the tool of choice as you go to that next job or you go to that next application. And so that's a fundamental way we think about it. To be honest with you, we haven't always delivered perfectly on that. It's generally in our dna. So we do pretty well, but I always feel like we can do better. >>So if you were to put a bumper sticker on one of your Teslas about influx data, what would it >>Say? By the way, I'm not rich. It just happened to be that we have two Teslas and we have for a while, we just committed to that. The, the, so ask the question again. Sorry. >>Bumper sticker on influx data. What would it say? How, how would I >>Understand it be time to Awesome. It would be that that phrase his time to Awesome. Right. >>Love that. >>Yeah, I'd love it. >>Excellent time to. Awesome. Evan, thank you so much for joining David, the >>Program. It's really fun. Great thing >>On Evan. Great to, you're on. Haven't Well, great to have you back talking about what you guys are doing and helping organizations like Tesla and others really transform their businesses, which is all about business transformation these days. We appreciate your insights. >>That's great. Thank >>You for our guest and Dave Ante. I'm Lisa Martin, you're watching The Cube, the leader in emerging and enterprise tech coverage. We'll be right back with our next guest.

>>Hello and welcome to the Cube's coverage here at AWS Reinvent 2022. This is the Executive Summit with Accenture. I'm John Furry, your host of the Cube at two great guests coming on today, really talking about the future, the role of humans. Radically human is gonna be the topic. Paul Dardy, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, global managing director of thought Leadership and Technology research. Accenture. Gentlemen, thank you for coming on the cube for this conversation around your new hit book. Radically human. >>Thanks, John. It's great to, great to be with you and great, great to be present at reinvent. >>You know, we've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're kind of in this, I call it the systems thinking, revolutions going on now where things have consequences and, and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as, as humans. And so I love the book. Very, very strong content, really. Right on point. What was the motivation for the book? And congratulations. But, you know, I noticed you got the, the structure part one and part two, This book seems to be packing a big punch. What's, what was the motivation and, and what was some of the background in, in putting the book together? >>That's a great question, John, and I'll start, and then, you know, Jim, my co-author and, and part colleague and partner on this, on the book and join in too. You know, the, if you step back from the book itself, we'd written a first book called, you know, Human Plus Machine, which talked about the, you know, focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the Human plus machine pairing. And then, you know, when we started, you know, working on the next book, Covid was, you know, it was kinda the Covid era. Covid came online as, as we were writing the book. And, but that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing, you know, once Covid hit, every company became more dependent on technology. >>Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies ba, you know, and what was different from the first, you know, research we had done around our first book. And what we found, which was super interesting, is that, is that, you know, pre pandemic, the, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of two x. And that was before the pandemic. After the pandemic. We redid the research and the gap widen into five x. And I think that's, and, and that's kind of played a lot into our book. And we talk about that in the opening of our book. And the message message there is exactly what you said is technology is not just the lifeline, you know, from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around, you know, inflation energy, supply chain crisis because of the war in Ukraine, et cetera. >>And companies need the technology more than ever. And that's what we're writing about in, in Radically Human. And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud data and ai and the metaverse that signal out is three trends that are really driving transformative change for companies. And the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are gonna set companies apart as they look to, you know, to implement this technology and transform their companies for the future. >>Jim, weigh in on this. Flipping the script, flipping the assumptions. No, >>You, you, you used a really important word there, and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as kind of a point solution. They don't think of about AI in terms of taking a systems approach. So we were trying to address that, all right, if you're gonna build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the, the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate using your talent, focusing on trust, experiences and sustainability. >>You know, I like this, I like how it reads. It's almost like a masterclass book because you kind of set the table. It's like, cuz people right now are like in the mode of, you know, what's going on around me. I'm been living through three years of covid. But coming out the other side, the world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where I am, where am I today. So I think the first part really to me hits home, like, here's the current situation and then part two is, here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or you know, society. >>Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where, you know, radically human, you know, the title came from. And you know, the, what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot and, and that, you know, the whole hypothesis, you know, or premise of the book I should say, is that the more humanlike the technology is, the more radically human or the more radical the, you know, the, the the, the human potential improvement is the more, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I, you know, talk about, you know, talked about, you know, talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. >>Just a couple examples from the ideas framework, the eye and ideas is each of the, the ideas framework is the first part of the book, The five areas to flip your Assumptions, The eye stands for intelligence. And we're talking about more, more human and less artificial in terms of the intelligence techniques, things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build, using the kind of systems thinking that Jim mentioned. And you know, things like emotional ai, common sense ai, new techniques in addition to machine the big data driven machine learning techniques which are essential to vision and solving big problems like that. So that's, that's just an example of, you know, how you bring it together and enable that human potential. >>I love the, we've been, >>We've >>Go ahead Jim. >>I was gonna say we've been used to adapting to technology, you know, and you know, contorting our fingers to keyboards and and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus. In fact, the human is in the ascended. That's one of the, one of the big ideas that we try to put out there in this book. >>You know, I love the idea of flipping the script, flicking assumptions, but, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, s for strategy, notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution really kind of interesting kind of how you guys put that together. It kind of feels like business is becoming agile and iterative and it's how it's gonna be forming. Can you guys, I mean that's my opinion, but I think, you know, observing how developers becoming much more part of, of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is kind of how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation? If you take it down to a conclusion, strategy is just what you do after you get the outcomes you need. Is that, can you, what's your reaction to that? >>Yeah, yeah, I think, I think one of the most lasting elements of the book might be that chapter on strategy in, in my opinion, because you need to think about it differently. The old, old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to, you know, to lay out with the, the essence ideas, you know, the strategy and the, the, the fun. You know, the, the subtitle that chapter is is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, That's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential world that technology plays and therefore they need to, to master technology, well, you need to think about strategy differently than because of the pace of technology innovation. >>And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really report it's about continuous strategy in all cases. Yet an example is one of the techniques we talk about forever beta, which is, you know, think about a Tesla, you know, companies that, you know, it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along, you know, the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we, we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions, you know, might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days. As Paul was saying, >>It's interesting because that's the kind of the trend you're seeing with more data, more automation. But the human plays a much critical role. And, and just as a side on the Tesla example, you know, is well documented, I think I wrote about in a post just this week that during the model three Elon wanted full automation and had to actually go off script and get to humans back in charge cuz it wasn't working properly. Now they have a balance. But that brings up the, the part two, which I like, which is, you know, this human piece of it, you know, we always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that, that second half, you know, trust, talent experiences, that's the more the person's role, either individually as part of a collective group is talent. The scarce resource now where that's the, that's the goal, that's the, the key because I mean, it all could point to that in a way, you know, skills gap kind of points to, hey, you know, humans are valuable, in fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think, you know, that's something that is not kind of nuance point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >>Yeah, it's, go ahead Jim. I was gonna say it, you know, we're, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book. You know, really zooming in on talent. I think, you know, you might think that for every, you know, a hundred dollars that you put into a technology initiative, you know, you might put 50 or 75 into reskilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw a, a economic analysis recently that pointed out that for every $1 you spend on technology, you are likely gonna need to spend about $9 on intangible human capital. That means, you know, on talent, on, on getting the best talent on reskilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >>That's a huge point. >>I think some of the elements of talent that become really critical that we, we talked about in the book are, are becoming a talent creator. We believe that the successful companies of the future are gonna be able not, not just to post, you know, post a job opening and hire, hire people in because there's not gonna be enough. And a lot of the jobs that companies are creating don't exist, you know, cause the technology changing so fast. So companies that succeed are gonna know how to create talent, bring in people, apprentices and such and, and, and, you know, shape to tail as they go. We're doing a significant amount of that in our own company. They're gonna be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what you know, employees want. And then democratizing access to technology, You know, things like, you know, Amazon's honey code is an example, you know, low code, no code development to spread, you know, development to wider pools of people. Those types of things are really critical, you know, going forward to really unlock the talent potential. And really what you end up with is, yeah, the, the human talent's important, but it's magnified to multiplied by the power of people, you know, giving them in essence superpowers in using technology in new >>Ways. I think you nailed it, That's super important. That point about the force multiplier, when you put things in combination with it's group constructs, two pizza teams, flexing, leveraging the talent. I mean, this is kind of a new configuration. You guys are nailing it there. I love that piece. And I think, you know, groups and collectives, you're gonna start to see a lot more of that. But again, with talent comes trust when you start to have these kind of, you know, ephemeral and or forming groups that are forming production systems or, or, or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously Metaverse is a pretext to the virtual world where we're gonna start to create these group experiences and create new force multipliers. How does the Metaverse play into this new radically human world and and what does it mean for the future of business? >>Yeah, I think the Metaverse is radically, you know, kind of misunderstood to use the word title, word of a, when we're not with the title of our book, you know, and we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So, you know, that that's the potential of the metaverse. And it's about, it's not just about the consumer things, it's about metaverse in the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I, I believe you know that it is, has tremendous potential. We write about that in the book and it really takes radically human to another level. >>And one way to think about this is cloud is really becoming the operating system of business. You, you have to build your enterprise around the cloud as you go forward that's gonna shape the way you do business. AI becomes the insight and intelligence in how you work, you know, in infused with, you know, the human talent and such as we said. And the metaverse then reshapes the experience layers. You have cloud AI building on top of this metaverse providing a new way to, to generate experiences for, for employees, citizens, consumers, et cetera. And that's the way it unfolds. But trust becomes more important because the, just as AI raises new questions around trust, you know, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five part framework or or five, you know, essential, you know, parts of the framework around how you establish trust as you implement these new technologies. >>Yeah, we're seeing that, you know, about three quarters of companies are really trying to figure out trust, you know, certainly with issues like the metaverse more broadly across their it, so they're, you know, they're focusing on security and privacy transparency, especially when you're talking about AI systems. Explainability. One of the, you know, the more surprising things that we learned when doing the book, when we're doing the research is that we saw that increasingly consumers and employees want systems to be informed by kind of a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, the, they're, they're actually training the system by emulating human behavior. So kind of turning the cameras on test drivers to see how they learn and then training the AI kind of using that sense of humanity cuz you know, the other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that that AI system is learning from or some really interesting innovations kind of happening in that trust space. John, >>Jim, I think you bring up a great point that's worth talking more about because you know, you're talking about how human behaviors are being put into the, the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and you know, we've been calling it super cloud, some call it multicloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's gonna happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with Chad and some video, you know, it's, it's group behavior, it's group con groups, convening, talking, getting things done, you know, debating doing things differently. And so this idea of humans informing design decisions or software with low code no code, this completely changes strategy. I mean this is a big point of the book. >>Yeah, no, I go back to, you know, one of the, the, the, the e and the ideas frameworks is expertise. And we talk about, you know, from machine learning to machine teaching, which, which is exactly that, you know, it's, you know, machine learning is, you know, maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with ai? One of the examples we give is one of the, the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to code in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create, you know, amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >>Well you, what's interesting is that I wanna to get your thoughts as we can wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in, in the enterprise of their businesses, as they look at the horizon, they see the, the future, they gotta start thinking about things like generative AI and how they can bring some of these technologies to the table where, you know, we were, we were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are, these are new things you guys are hitting on this in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge, certainly that is an opportunity. How, how do you apply all this stuff for, for business >>Now? I'll go first then Jim Canad. But the, the first thing I think starts with, with recognizing the role that technology does play and investing accordingly in it. So the right, you know, technology, talent, you know, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why, you know, the fact you're at reinvent is so important because companies are, you know, again rebuilding that, that operating system of their business in the cloud. And you need that, you know, as the foundation to go forward, to do, you know, to, to build the other, other types of capabilities. And then I think it's developing those talent systems as well. You know, do you, do you have the right the, do you have the right talent brand? Are you attacking the right, attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward and then you marry the two together and that's what, you know, gives you the radically human formula. >>Yeah. When, you know, when we were developing that first part of the book, Paul and I did quite a bit of, of research, and this was ju and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. You know, one statistic is that 70% of, there was a, there was a of companies that had never tried AI before, went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies are not, or we're not trying to do it themselves and to, you know, to necessarily, you know, build an it, a AI department. They were partnering and it's really important to, to find a partner, often a cloud partner as a way to get started, start small scale and then scale up doing experiments. So that was one of the, that was one of the key insights that we had. You don't need to do it all yourself. >>If you see the transformation of just aws, we're here at reinvent just since we've been covering the events since 2013, every year there's been kind of a thematic thing. It was, you know, startups, enterprise now builders and now, now change your company this year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and, and running a SaaS application on the cloud. People are are changing and refactoring and replatforming, categorical applications in for this new era. And you know, we're calling it super cloud super services, super apps cuz they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools or talent pools in certain ways. So this is real, something's happening here and you know, we've been talking about a lot lately, so I have to ask you guys, how does a company know if they're radical enough? Like when, what is radical? How do, how can I put a pin in that say that could take a temperature or we like radical enough what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening. How do you know if you're, you're you're pushing the envelope radical enough to, to take advantage? >>Yeah, I think one, yeah, I was gonna say one of the, one of the tests is is you know, the impact on your business. You have to start by looking at all this in the context of your business and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. Yeah. That that's still something you need to do. But now we, our focus, you know, with a lot of our customers is on how do you innovate and grow your business in the cloud? What's, what is, you know, how, how, what's the platform you know, that you're using to, you know, for your, the new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test. Whether being radical, you know, radical enough is on the one hand, is this really, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping, you know, people, your human talent with the capabilities they need to perform in very different ways? And those are the the two tests that I would give. Totally agree. >>Yeah. You know, interesting enough, we, you know, we, we love this topic and guys, again, the book is spot on. Very packs a big punch on content, but very relevant in today. And I think, you know, one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like ideas your framework and understand where they are and what's available and what's coming around the corner. They stand out in the, in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean some, you're building clouds on top of clouds or, or something's happening. You can, I think you see it like look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >>Yeah, and that's a good example and it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows the portability of being able to connect and use data across cloud environments and such is, is, is is tremendously powerful. And I think that's why, you know, you talk about companies doing things differently, that's why it's great again that you're at reinvents. If you look at the index of our book, you'll see, you'll see AWS mentioned a number of times cuz we tell a lot of cus of cus customer and company stories about how they're leveraging aws, AWS capabilities in cloud and AI to really do transformative things in your, in their business. And I, I think that's what it's, that's what it's all about. >>Yeah, and one of the things too in the book, it's great cuz it has kind of a, the systems thinking it's got really relevant information but you know, you guys have seen the, seen the movie before. I think one of the wild cards in this era is global. You know, we're global economy, you've got regions, you've got data sovereignty, you're seeing, you know, all kinds of new things, emerging thoughts on the global impact cuz you, you take your book and you overlay that to business. Like you gotta, you gotta operate all over the world as a human issue. It's a geography issue. What's your guys take on the global impact? >>Well that's, that's why the, the, you gotta think about cloud as as one technology, you know, we talked about in the book and cloud is a lot, I think a lot of people think, well clouds it's almost old news. Maybe it's been around for a while. As you said, you've been going to reinvent since 2013. You know, cloud is really just getting, you know, just getting started. And, and it's cuz the reasons you said, when you look at what you need to do around sovereign cloud capability, if you're in Europe for many companies it's about multi-cloud capabilities. You need to deploy, you know, differently in different, in different regions. And they need to, in some cases for good reason, they have hybrid, hybrid cloud, you know, capability that they, they match on their own. And then there's the edge capability which is comes into play in, in different ways. >>And, and so the architecture becomes very complex and we talk the A in and ideas is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and mod and you know, just modularity was kind of the key thing you thought about. It's more the idea of a living system, of living architecture that's, that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the, with the pace of technology advancement. >>You know, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is gonna be a big discussion as these new flipped assumptions start to generate more activity. It's gonna be very interesting to watch. Gentlemen, thank you so much for spending the time here on the queue as we break down your new book, Radically Human and how it, how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at reinvent. Thanks so much for, for sharing and congratulations on a great book. >>You know, Thanks John. And just one point I'd add is that one of the, the things we do talk about in talent is the need to reskill talent. You know, people who need to, you know, be, be relevant to the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those who need to reskilling. And the final point I mentioned is that we mentioned at the end of the book that all proceeds for the book are being donated to not NGOs and nonprofits that are focused on reskilling. Those who need a skill refresh in light of the radically human new, you know, change in technology that's happening >>Great by the book proceeds go to a great cause and it's a very relevant book if you're in the middle of this big way that's coming. This is a great book. There's a guidepost and also give you some great ideas to, to reset re flip the scripts. Refactor, re-platform. Guys, thanks for coming on and sharing, really appreciate it. Again, congratulations. >>Thanks, John. John, great discussion. >>Okay, you're watching the Cube here, covering the executive forum here at AWS Reinvent 22. I'm John Furrier, your host with aen. Thanks for watching.