>>Hi everyone. And welcome to data citizens. Thank you for making the time to join me and the over 5,000 data citizens like you that are looking to become United by data. My name is Jim Cushman. I serve as the chief product officer at Collibra. I have the benefit of sharing with you, the product, vision, and strategy of Culebra. There's several sections to this presentation, and I can't wait to share them with you. The first is a story of how we're taking a business user and making it possible for him or her data, use data and gain. And if it and insight from that data, without relying on anyone in the organization to write code or do the work for them next I'll share with you how Collibra will make it possible to manage metadata at scales, into the billions of assets. And again, load this into our software without writing any code third, I will demonstrate to you the integration we have already achieved with our newest product release it's data quality that's powered by machine learning. >>Right? Finally, you're going to hear about how Colibra has become the most universally available solution in the market. Now, we all know that data is a critical asset that can make or break an organization. Yet organizations struggle to capture the power of their data and many remain afraid of how their data could be misused and or abused. We also observe that the understanding of and access to data remains in the hands of just a small few, three out of every four companies continue to struggle to use data, to drive meaningful insights, all forward looking companies, looking for an advantage, a differentiator that will set them apart from their peers and competitors. What if you could improve your organization's productivity by just 5%, even a modest 5% productivity improvement compounded over a five-year period will make your organization 28% more productive. This will leave you with an overwhelming advantage over your competition and uniting your data. >>Litter employees with data is the key to your success. And dare I say, sorry to unlock this potential for increased productivity, huge competitive advantage organizations need to enable self-service access to data for everyday to literate knowledge worker. Our ultimate goal at Cleaver has always been to enable this self-service for our customers to empower every knowledge worker to access the data they need when they need it. But with the peace of mind that your data is governed insecure. Just to imagine if you had a single integrated solution that could deliver a seamless governed, no code user experience of delivering the right data to the right person at the right time, just as simply as ordering a pair of shoes online would be quite a magic trick and one that would place you and your organization on the fast track for success. Let me introduce you to our character here. >>Cliff cliff is that business analyst. He doesn't write code. He doesn't know Julian or R or sequel, but is data literate. When cliff has presented with data of high quality and can actually help find that data of high-quality cliff knows what to do with it. Well, we're going to expose cliff to our software and see how he can find the best data to solve his problem of the day, which is customer churn. Cliff is going to go out and find this information is going to bring it back to him. And he's going to analyze it in his favorite BI reporting tool. Tableau, of course, that could be Looker, could be power BI or any other of your favorites, but let's go ahead and get started and see how cliff can do this without any help from anyone in the organization. So cliff is going to log into Cleaver and being a business user. >>The first thing he's going to do is look for a business term. He looks for customer churn rate. Now, when he brings back a churn rate, it shows him the definition of churn rate and various other things that have been attributed to it such as data domains like product and customer in order. Now, cliff says, okay, customer is really important. So let me click on that and see what makes up customer definition. Cliff will scroll through a customer and find out the various data concepts attributes that make up the definition of customer and cliff knows that customer identifier is a really important aspect to this. It helps link all the data together. And so cliff is going to want to make sure that whatever source he brings actually has customer identifier in it. And that it's of high quality cliff is also interested in things such as email address and credit activity and credit card. >>But he's now going to say, okay, what data sets actually have customer as a data domain in, and by the way, why I'm doing it, what else has product and order information? That's again, relevant to the concept of customer churn. Now, as he goes on, he can actually filter down because there's a lot of different results that could potentially come back. And again, customer identifier was very important to cliff. So cliff, further filters on customer identifier any further does it on customer churn rate as well. This results in two different datasets that are available to cliff for selection, which one to use? Well, he's first presented with some data quality information you can see for customer analytics. It has a data quality score of 76. You can see for sales data enrichment dataset. It has a data quality score of 68. Something that he can see right at the front of the box of things that he's looking for, but let's dig in deeper because the contents really matter. >>So we see again the score of 76, but we actually have the chance to find out that this is something that's actually certified. And this is something that has a check mark. And so he knows someone he trusts is actually certified. This is a dataset. You'll see that there's 91 columns that make up this data set. And rather than sifting through all of that information, cliff is going to go ahead and say, well, okay, customer identifier is very important to me. Let me search through and see if I can find what it's data quality scores very quickly. He finds that using a fuzzy search and brings back and sees, wow, that's a really high data quality score of 98. Well, what's the alternative? Well, the data set is only has 68, but how about, uh, the customer identifier and quickly, he discovers that the data quality for that is only 70. >>So all things being equal, customer analytics is the better data set for what cliff needs to achieve. But now he wants to look and say, other people have used this, what have they had to say about it? And you can see there are various reviews for different reviews from peers of his, in the organization that have given it five stars. So this is encourages cliffs, a confidence that this is great data set to use. Now cliff wants to look a little bit more detailed before he finally commits to using this dataset. Cliff has the opportunity to look at it in the broader set. What are the things can I learn about customer analytics, such as what else is it related to? Who else uses it? Where did it come from? Where does it go and what actually happens to it? And so within our graph of information, we're able to show you a diagram. >>You can see the customer analytics actually comes from the CRM cloud system. And from there you can inherit some wonderful information. We know exactly what CRM cloud is about as an overall system. It's related to other logical models. And here you're actually seeing that it's related to a policy policy about PII or personally identifiable information. This gets cliff almost the immediate knowledge that there's going to be some customer information in this PII information that he's not going to be able to see given his user role in the organization. But cliff says, Hey, that's okay. I actually don't need to see somebody's name and social security number to do my work. I can actually work with other information in the data file. That'll actually help me understand why our customers churning in, what can I actually do about it. If we dig in deeper, we can see what is personally identifiable information that actually could cause issues. >>And as we scroll down and take a little bit of a focus on what we call or what you'll see here is customer phone, because we'll show that to you a little bit later, but these show the various information that once cliff actually has it fulfilled and delivered to him, he will see that it's actually massed and or redacted from his use. Now cliff might drive in deeper and see more information. And he says, you know what? Another piece that's important to me in my analysis is something called is churned. This is basically suggesting that has a customer actually churned. It's an important flag, of course, because that's the analysis that he's performing cliff sees that the score is a mere 65. That's not exactly a great data quality score, but cliff has, is kind of in a hurry. His bosses is, has come back and said, we need to have this information so we can take action. >>So he's not going to wait around to see if they can go through some long day to quality project before he pursues, but he is going to come up and use it. The speed of thinking. He's going to create a suggestion, an issue. He's going to submit this as a work queue item that actually informs others that are responsible for the quality of data. That there's an opportunity for improvement to this dataset that is highly reviewed, but it may be, it has room for improvement as cliff is actually typing in his explanation that he'll pass along. We can also see that the data quality is made up of multiple components, such as integrity, duplication, accuracy, consistency, and conformity. Um, we see that we can submit this, uh, issue and pass it through. And this will go to somebody else who can actually work on this. >>And we'll show that to you a little bit later, but back to cliff, cliff says, okay, I'd like to, I'd like to work with this dataset. So he adds it to his data basket. And just like if he's shopping online, cliff wants that kind of ability to just say, I want to just click once and be done with it. Now it is data and there's some sensitivity about it. And again, there's an owner of this data who you need to get permission from. So cliff is going to provide information to the owner to say, here's why I need this data. And how long do I need this data for starting on a certain date and ending on a certain date and ultimately, what purpose am I going to have with this data? Now, there are other things that cliff can choose to run. This one is how do you want this day to deliver to you? >>Now, you'll see down below, there are three options. One is borrow the other's lease and others by what does that mean? Well, borrow is this idea of, I don't want to have the data that's currently in this CRM, uh, cloud database moved somewhere. I don't want it to be persistent anywhere else. I just want to borrow it very short term to use in my Tablo report and then poof be gone. Cause I don't want to create any problems in my organization. Now you also see lease. Lease is a situation where you actually do need to take possession of the data, but only for a time box period of time, you don't need it for an indefinite amount of time. And ultimately buy is your ability to take possession of the data and have it in perpetuity. So we're going to go forward with our bar use case and cliff is going to submit this and all the fun starts there. >>So cliff has actually submitted the order and the owner, Joanna is actually going to receive the request for the order. Joanna, uh, opens up her task, UCS there's work to perform. It says, oh, okay, here's this there's work for me to perform. Now, Joanna has the ability to automate this using incorporated workflow that we have in Colibra. But for this situation, she's going to manually review that. Cliff wants to borrow a specific data set for a certain period of time. And he actually wants to be using in a Tablo context. So she reviews. It makes an approval and submits it this in turn, flips it back to cliff who says, okay, what obligations did I just take on in order to work for this data? And he reviews each of these data sharing agreements that you, as an organization would set up and say, what am I, uh, what are my restrictions for using this data site? >>As cliff accepts his notices, he now has triggered the process of what we would call fulfillment or a service broker. And in this situation we're doing a virtualization, uh, access, uh, for the borrow use case. Cliff suggests Tablo is his preferred BI and reporting tool. And you can see the various options that are available from power BI Looker size on ThoughtSpot. There are others that can be added over time. And from there, cliff now will be alerted the minute this data is available to them. So now we're running out and doing a distributed query to get the information and you see it returns back for raw view. Now what's really interesting is you'll see, the customer phone has a bunch of X's in it. If you remember that's PII. So it's actually being massed. So cliff can't actually see the raw data. Now cliff also wants to look at it in a Tablo report and can see the visualization layer, but you also see an incorporation of something we call Collibra on the go. >>Not only do we bring the data to the report, but then we tell you the reader, how to interpret the report. It could be that there's someone else who wants to use the very same report that cliff helped create, but they don't understand exactly all the things that cliff went through. So now they have the ability to get a full interpretation of what was this data that was used, where did it come from? And how do I actually interpret some of the fields that I see on this report? Really a clever combination of bringing the data to you and showing you how to use it. Cliff can also see this as a registered asset within a Colibra. So the next shopper comes through might actually, instead of shopping for the dataset might actually shop for the report itself. And the report is connected with the data set he used. >>So now they have a full bill of materials to run a customer Shern report and schedule it anytime they want. So now we've turned cliff actually into a creator of data assets, and this is where intelligent, it gets more intelligence and that's really what we call data intelligence. So let's go back through that magic trick that we just did with cliff. So cliff went into the software, not knowing if the source of data that he was looking for for customer product sales was even available to him. He went in very quickly and searched and found his dataset, use facts and facets to filter down to exactly what was available. Compare to contrast the options that were there actually made an observation that there actually wasn't enough data quality around a certain thing was important to him, created an idea, or basically a suggestion for somebody to follow up on was able to put that into his shopping basket checkout and have it delivered to his front door. >>I mean, that's a bit of a magic trick, right? So, uh, cliff was successful in finding data that he wanted and having it, deliver it to him. And then in his preferred model, he was able to look at it into Tableau. All right. So let's talk about how we're going to make this vision a reality. So our first section here is about performance and scale, but it's also about codeless database registration. How did we get all that stuff into the data catalog and available for, uh, cliff to find? So allow us to introduce you to what we call the asset life cycle and some of the largest organizations in the world. They might have upwards of a billion data assets. These are columns and tables, reports, API, APIs, algorithms, et cetera. These are very high volume and quite technical and far more information than a business user like cliff might want to be engaged with those very same really large organizations may have upwards of say, 20 to 25 million that are critical data sources and data assets, things that they do need to highly curate and make available. >>But through that as a bit of a distillation, a lifecycle of different things you might want to do along that. And so we're going to share with you how you can actually automatically register these sources, deal with these very large volumes at speed and at scale, and actually make it available with just a level of information you need to govern and protect, but also make it available for opportunistic use cases, such as the one we presented with cliff. So as you recall, when cliff was actually trying to look for his dataset, he identified that the is churned, uh, data at your was of low quality. So he passed this over to Eliza, who's a data steward and she actually receives this work queue in a collaborative fashion. And she has to review, what is the request? If you recall, this was the request to improve the data quality for his churn. >>Now she needs to familiarize herself with what cliff was observing when he was doing his shopping experience. So she digs in and wants to look at the quality that he was observing and sure enough, as she goes down and it looks at his churn, she sees that it was a low 65% and now understands exactly what cliff was referring to. She says, aha, okay. I need to get help. I need to decide whether I have a data quality project to fix the data, or should I see if there's another data set in the organization that has better, uh, data for this. And so she creates a queue that can go over to one of her colleagues who really focuses on data quality. She submits this request and it goes over to, uh, her colleague, John who's really familiar with data quality. So John actually receives the request from Eliza and you'll see a task showing up in his queue. >>He opens up the request and finds out that Eliza's asking if there's another source out there that actually has good is churned, uh, data available. Now he actually knows quite a bit about the quality of information sturdiness. So he goes into the data quality console and does a quick look for a dataset that he's familiar with called customer product sales. He quickly scrolls down and finds out the one that's actually been published. That's the one he was looking for and he opens it up to find out more information. What data sets are, what columns are actually in there. And he goes down to find his churned is in fact, one of the attributes in there. It actually does have active rules that are associated with it to manage the quality. And so he says, well, let's look in more detail and find out what is the quality of this dataset? >>Oh, it's 86. This is a dramatic improvement over what we've seen before. So we can see again, it's trended quite nicely over time each day, it hasn't actually degraded in performance. So we actually responds back to realize and say, this data set, uh, is actually the data set that you want to bring in. It really will improve. And you'll see that he refers to the refined database within the CRM cloud solution. Once he actually submits this, it goes back to Eliza and she's able to continue her work. Now when Eliza actually brings this back open, she's able to very quickly go into the database registration process for her. She very quickly goes into the CRM cloud, selects the community, to which she wants to register this, uh, data set into the schemas community. And the CRM cloud is the system that she wants to load it in. >>And the refined is the database that John told her that she should bring in. After a quick description, she's able to click register. And this triggers that automatic codeless process of going out to the dataset and bringing back its metadata. Now metadata is great, but it's not the end all be all. There's a lot of other values that she really cares about as she's actually registering this dataset and synchronizing the metadata she's also then asked, would you like to bring in quality information? And so she'll go out and say, yes, of course, I want to enable the quality information from CRM refined. I also want to bring back lineage information to associate with this metadata. And I also want to select profiling and classification information. Now when she actually selects it, she can also say, how often do you want to synchronize this? This is a daily, weekly, monthly kind of update. >>That's part of the change data capture process. Again, all automated without the require of actually writing code. So she's actually run this process. Now, after this loads in, she can then open up this new registered, uh, dataset and actually look and see if it actually has achieved the problem that cliff set her out on, which was improved data quality. So looking into the data quality for the is churn capability shows her that she has fantastic quality. It's at a hundred, it's exactly what she was looking for. So she can with confidence actually, uh, suggest that it's done, but she did notice something and something that she wants to tell John, which is there's a couple of data quality checks that seem to be missing from this dataset. So again, in a collaborative fashion, she can pass that information, uh, for validity and completeness to say, you know what, check for NOLs and MPS and send that back. >>So she submits this onto John to work on. And John now has a work queue in his task force, but remember she's been working in this task forklift and because she actually has actually added a much better source for his churn information, she's going to update that test that was sent to her to notify cliff that the work has actually been done and that she actually has a really good data set in there. In fact, if you recall, it was 100% in terms of its data quality. So this will really make life a lot easier for cliff. Once he receives that data and processes, the churn report analysis next time. So let's talk about these audacious performance goals that we have in mind. Now today, we actually have really strong performance and amazing usability. Our customers continue to tell us how great our usability is, but they keep asking for more well, we've decided to present to you. >>Something you can start to bank on. This is the performance you can expect from us on the highly curated assets that are available for the business users, as well as the technical and lineage assets that are more available for the developer uses and for things that are more warehoused based, you'll see in Q1, uh, our Q2 of this year, we're making available 5 million curated assets. Now you might be out there saying, Hey, I'm already using the software and I've got over 20 million already. That's fair. We do. We have customers that are actually well over 20 million in terms of assets they're managing, but we wanted to present this to you with zero conditions, no limitations we wouldn't talk about, well, it depends, et cetera. This is without any conditions. That's what we can offer you without fail. And yes, it can go higher and higher. We're also talking about the speed with which you can ingest the data right now, we're ingesting somewhere around 50,000 to a hundred thousand records per and of course, yes, you've probably seen it go quite a bit faster, but we are assuring you that that's the case, but what's really impressive is right now, we can also, uh, help you manage 250 million technical assets and we can load it at a speed of 25 million for our, and you can see how over the next 18 months about every two quarters, we show you dramatic improvements, more than doubling of these. >>For most of them leading up to the end of 2022, we're actually handling over a billion technical lineage assets and we're loading at a hundred million per hour. That sets the mark for the industry. Earlier this year, we announced a recent acquisition Al DQ. LDQ brought to us machine learning based data quality. We're now able to introduce to you Collibra data quality, the first integrated approach to Al DQ and Culebra. We've got a demo to follow. I'm really excited to share it with you. Let's get started. So Eliza submitted a task for John to work on, remember to add checks for no and for empty. So John picks up this task very quickly and looks and sees what's what's the request. And from there says, ah, yes, we do have a quality check issue when we look at these churns. So he jumps over to the data quality console and says, I need to create a new data quality test. >>So cliff is able to go in, uh, to the solution and, uh, set up quick rules, automated rules. Uh, he could inherit rules from other things, but it starts with first identifying what is the data source that he needs to connect to, to perform this. And so he chooses the CRM refined data set that was most recently, uh, registered by Lysa. You'll see the same score of 86 was the quality score for the dataset. And you'll also see, there are four rules that are associated underneath this. Now there are various checks that, uh, that John can establish on this, but remember, this is a fairly easy request that he receives from Eliza. So he's going to go in and choose the actual field, uh, is churned. Uh, and from there identify quick rules of, uh, an empty check and that quickly sets up the rules for him. >>And also the null check equally fast. This one's established and analyzes all the data in there. And this sets up the baseline of data quality, uh, for this. Now this data, once it's captured then is periodically brought back to the catalog. So it's available to not only Eliza, but also to cliff next time he, uh, where to shop in the environment. As we look through the rules that were created through that very simple user experience, you can see the one for is empty and is no that we're set up. Now, these are various, uh, styles that can be set up either manually, or you can set them up through machine learning again, or you can inherit them. But the key is to track these, uh, rule creation in the metrics that are generated from these rules so that it can be brought back to the catalog and then used in meaningful context, by someone who's shopping and the confidence that this has neither empty nor no fields, at least most of them don't well now give a confidence as you go forward. >>And as you can see, those checks have now been entered in and you can see that it's a hundred percent quality score for the Knoll check. So with confidence now, John can actually respond back to Eliza and say, I've actually inserted them they're up and running. And, uh, you're in good status. So that was pretty amazing integration, right? And four months after our acquisition, we've already brought that level of integration between, uh, Colibra, uh, data intelligence, cloud, and data quality. Now it doesn't stop there. We have really impressive and high site set early next year. We're getting introduced a fully immersive experience where customers can work within Culebra and actually bring the data quality information all the way in as well as start to manipulate the rules and generate the machine learning rules. On top of it, all of that will be a deeply immersive experience. >>We also have something really clever coming, which we call continuous data profiling, where we bring the power of data quality all the way into the database. So it's continuously running and always making that data available for you. Now, I'd also like to share with you one of the reasons why we are the most universally available software solutions in data intelligence. We've already announced that we're available on AWS and Google cloud prior, but today we can announce to you in Q3, we're going to be, um, available on Microsoft Azure as well. Now it's not just these three cloud providers that were available on we've also become available on each of their marketplaces. So if you are buying our software, you can actually go out and achieve that same purchase from their marketplace and achieve your financial objectives as well. We're very excited about this. These are very important partners for, uh, for our, for us. >>Now, I'd also like to introduce you our system integrators, without them. There's no way we could actually achieve our objectives of growing so rapidly and dealing with the demand that you customers have had Accenture, Deloitte emphasis, and even others have been instrumental in making sure that we can serve your needs when you need them. Uh, and so it's been a big part of our growth and will be a continued part of our growth as well. And finally, I'd like to actually introduce you to our product showcases where we can go into absolute detail on many of the topics I talked about today, such as data governance with Arco or data privacy with Sergio or data quality with Brian and finally catalog with Peter. Again, I'd like to thank you all for joining us. Uh, and we really look forward to hearing your feedback. Thank you..

>>long from Las Vegas. It's the Q covering a ws re invent 2019. Brought to you by Amazon Web service is and in along with its ecosystem partners. >>Welcome back to the Cube. Here live in Las Vegas for aws reinvent I'm John for a devil on the ads, always extracting the signal from the noise. We're here for 1/7 reinvent of the eight years that they've had at what a wave. One of the biggest waves is the modernization of procurement, the modernization of business, commercial business and the rapid acceleration of public sector. We're here with the chief of public sector for AWS. Teresa Carlson, vice president publics that globally great to have you >>so great to have the Q begin this year. We appreciate you being here, >>so we're just seeing so much acceleration of modernization. Even in the commercial side, 80 talks about transformation. It's just a hard core on the public sector side. You have so many different areas transforming faster because they haven't transformed before. That's correct. This is a lot of change. What's changed the most for you in your business? >>Well, again, I'll be here 10 years this mad that A B s and my eighth reinvent, and what really changed, which was very exciting this year, is on Monday. We had 550 international government executives here from 40 countries who were talking about their modernization efforts at every level. Now again, think about that. 40 different governments, 550 executives. We had a fantastic day for them planned. It was really phenomenal because the way that these international governments or think about their budget, how much are they going to use that for maintaining? And they want to get that lesson last. Beckett for Modernization The Thin John It's a Beckett for innovation so that they continue not only modernized, but they're really looking at innovation cycles. So that's a big one. And then you heard from somewhere customers at the breakfast this morning morning from from a T. F. As part of the Department of Justice. What they're doing out. I'll call to back on firearms. They completely made you the cloud. They got rid of 20 years of technical debt thio the Veterans Administration on what they're digging for V A benefits to educational institutions like our mighty >>nose, and he had on stages Kino, Cerner, which the health care companies and what struck me about that? I think it relates to your because I want to get your reaction is that the health care is such an acute example that everyone can relate to rising costs. So cloud helping reduce costs increase the efficiencies and patient care is a triple win. The same thing happens in public sector. There's no place to hide anymore. You have a bona fide efficiencies that could come right out of the gate with cloud plus innovation. And it's happening in all the sectors within the public sector. >>So true. Well, Cerner is a great example because they won the award at V a Veteran's administration to do the whole entire medical records modernization. So you have a company on stage that's commercial as I met, commercial as they are public sector that are going into these large modernization efforts. And as you sit on these air, not easy. This takes focus and leadership and a real culture change to make these things happen. >>You know, the international expansion is impressive. We saw each other in London. We did the health care drill down at your office is, of course, a national health. And then you guys were in Bahrain, and what I deserve is it's not like these organizations. They're way behind. I mean, especially the ones that it moved to. The clouds are moving really fast. So well, >>they don't have as much technical debt internationally. It's what we see here in the U. S. So, like I was just in Africa and you know what we talked about digitizing paper. Well, there's no technology on that >>end >>there. It's kind of exciting because they can literally start from square one and get going. And there's a really hunger and the need to make that happen. So it's different for every country in terms of where they are in their cloud journey. >>So I want to ask you about some of the big deals. I'll see Jet eyes in the news, and you can't talk about it because it's in protest and little legal issues. But you have a lot of big deals that you've done. You share some color commentary on from the big deals and what it really means. >>Yeah, well, first of all, let me just say with Department of Defense, Jet are no jet. I We have a very significant business, you know, doing work at every part of different defense. Army, Navy, Air Force in the intelligence community who has a mission for d o d terminus a t o N g eight in a row on And we are not slowing down in D. O d. We had, like, 250 people at a breakfast. Are Lantian yesterday giving ideas on what they're doing and sharing best practices around the fence. So we're not slowing down in D. O d. We're really excited. We have amazing partners. They're doing mission work with us. But in terms of some really kind of fend, things have happened. We did a press announcement today with Finn Rat, the financial regulatory authority here in the U. S. That regulates markets at this is the largest financial transactions you'll ever see being processed and run on the cloud. And the program is called Cat Consolidated Audit Trail. And if you remember the flash crash and the markets kind of going crazy from 2000 day in 2008 when it started, Finneran's started on a journey to try to understand why these market events were happening, and now they have once have been called CAT, which will do more than 100 billion market points a day that will be processed on the cloud. And this is what we know of right now, and they'll be looking for indicators of nefarious behavior within the markets. And we'll look for indicators on a continuous basis. Now what? We've talked about it. We don't even know what we don't know yet because we're getting so much data, we're going to start processing and crunching coming out of all kinds of groups that they're working with, that this is an important point even for Finn rep. They're gonna be retiring technical debt that they have. So they roll out Cat. They'll be retiring other systems, like oats and other programs that they >>just say so that flash crash is really important. Consolidated, honest, because the flash crash, we'll chalk it up to a glitch in the system. Translation. We don't really know what happened. Soto have a consolidated auto trail and having the data and the capabilities, I understand it is really, really important for transparency and confidence in the >>huge and by the way, thinner has been working with us since 2014. They're one of our best partners and are prolific users of the cloud. And I will tell you it's important that we have industries like thin red regulatory authorities, that air going in and saying, Look, we couldn't possibly do what we're doing without cloud computing. >>Tell me about the technical debt because I like this conversation is that we talk about in the commercial side and developer kind of thinking. Most businesses start ups, Whatever. What is technical debt meet in public sector? Can you be specific? >>Well, it's years and years of legacy applications that never had any modernization associated with them in public sector. You know now, because you've talked about these procurement, your very best of your very savvy now public sector >>like 1995 >>not for the faint of heart, for sure that when you do procurement over the years when they would do something they wouldn't build in at new innovations or modernizations. So if you think about if you build a data center today a traditional data center, it's outdated. Tomorrow, the same thing with the procurement. By the time that they delivered on those requirements. They were outdated. So technical debt then has been built up years of on years of not modernizing, just kind of maintaining a status quo with no new insides or analytics. You couldn't add any new tooling. So that is where you see agencies like a T F. That has said, Wow, if I'm gonna if I'm gonna have a modern agency that tracks things like forensics understands the machine learning of what's happening in justice and public safety, I need to have the most modern tools. And I can't do that on an outdated system. So that's what we kind of call technical death that just maintains that system without having anything new that you're adding to >>their capabilities lag. Everything's products bad. Okay, great. Thanks for definite. I gotta ask you about something that's near and dear to our heart collaboration. If you look at the big successes in the world and within Amazon Quantum Caltex partnering on the quantum side, you've done a lot of collaboration with Cal Cal Poly for ground station Amazon Educate. You've been very collaborative in your business, and that's a continuing to be a best practice you have now new things like the cloud innovation centers. Talk about that dynamic and how collaboration has become an important part of your business model. >>What we use their own principles from Amazon. We got building things in our plan. Innovation centers. We start out piloting those two to see, Could they work? And it's really a public private partnership between eight MPs and universities, but its universities that really want to do something. And Cal Poly's a great example. Arizona State University A great example. The number one most innovative university in the US for like, four years in a row. And what we do is we go in and we do these public sector challenges. So the collaboration happens. John, between the public sector Entity, university with students and us, and what we bring to the table is technical talent, air technology and our mechanisms and processes, like they're working backwards processes, and they were like, We want you to bring your best and brightest students. Let's bring public sector in the bowl. They bring challenges there, riel that we can take on, and then they can go back and absorb, and they're pretty exciting. I today I talked about we have over 44 today that we've documented were working at Cal Poly. The one in Arizona State University is about smart cities. And then you heard We're announcing new ones. We've got two in France, one in Germany now, one that we're doing on cybersecurity with our mighty in Australia to be sitting bata rain. So you're going to see us Add a lot more of these and we're getting the results out of them. So you know we won't do if we don't like him. But right now we really like these partnerships. >>Results are looking good. What's going on with >>you? All right. And I'll tell you why. That why they're different, where we are taking on riel public sector issues and challenges that are happening, they're not kind of pie in the sky. We might get there because those are good things to do. But what we want to do is let's tackle things that are really homelessness, opioid crisis, human sex trafficking, that we're seeing things that are really in these communities and those air kind of grand. But then we're taking on areas like farming where we talked about Can we get strawberries rotting on the vine out of the field into the market before you lose billions of dollars in California. So it's things like that that were so its challenges that are quick and riel. And the thing about Cloud is you can create an application and solution and test it out very rapidly without high cost of doing that. No technical Dan, >>you mentioned Smart Cities. I just attended a session. Marty Walsh, the mayor of Boston's, got this 50 50 years smart city plan, and it's pretty impressive, but it's a heavy lift. So what do you see going on in smart cities? And you really can't do it without the cloud, which was kind of my big input cloud. Where's the data? What do you say, >>cloud? I O. T is a big part at these. All the centers that Andy talked about yesterday in his keynote and why the five G partnerships are so important. These centers, they're gonna be everywhere, and you don't even know they really exist because they could be everywhere. And if you have the five G capabilities to move those communications really fast and crypt them so you have all the security you need. This is game changing, but I'll give you an example. I'll go back to the kids for a minute at at Arizona State University, they put Io TI centers everywhere. They no traffic patterns. Have any parking slots? Airfield What Utilities of water, if they're trash bins are being filled at number of seats that are being taken up in stadiums. So it's things like that that they're really working to understand. What are the dynamics of their city and traffic flow around that smart city? And then they're adding things on for the students like Alexis skills. Where's all the activity? So you're adding all things like Alexa Abs, which go into a smart city kind of dynamic. We're not shop. Where's the best activities for about books, for about clothes? What's the pizza on sale tonight? So on and then two things like you saw today on Singapore, where they're taking data from all different elements of agencies and presenting that bad to citizen from their child as example Day one of a birth even before, where's all the service is what I do? How do I track these things? How do I navigate my city? to get all those service is the same. One can find this guy things they're not. They're really and they're actually happening. >>Seems like they're instrumented a lot of the components of the city learning from that and then deciding. Okay, where do we double down on where do we place? >>You're making it Every resilient government, a resilient town. I mean, these were the things that citizens can really help take intro Web and have a voice in doing >>threes. I want to say congratulations to your success. I know it's not for the faint of heart in the public sector of these days, a lot of blockers, a lot of politics, a lot of government lockers and the old procurement system technical debt. I mean, Windows 95 is probably still in a bunch of PCs and 50 45 fighters. 15 fighters. Oh, you've got a great job. You've been doing a great job and riding that wave. So congratulations. >>Well, I'll just say it's worth it. It is worth it. We are committed to public sector, and we really want to see everyone from our war fighters. Are citizens have the capabilities they need. So >>you know, you know that we're very passionate this year about going in the 2020 for the Cube and our audience to do a lot more tech for good programming. This'll is something that's near and dear to your heart as well. You have a chance to shape technology. >>Yes, well, today you saw we had a really amazing not for profit on stage with It's called Game Changer. And what we found with not for profits is that technology can be a game changer if they use it because it makes their mission dollars damage further. And they're an amazing father. And send a team that started game changer at. Taylor was in the hospital five years with terminal cancer, and he and his father, through these five years, kind of looked around. Look at all these Children what they need and they started. He is actually still here with us today, and now he's a young adult taking care of other young Children with cancer, using gaming technologies with their partner, twitch and eight MPs and helping analyze and understand what these young affected Children with cancer need, both that personally and academically and the tools he has He's helping really permit office and get back and it's really hard, Warren says. I was happy. My partner, Mike Level, who is my Gran's commercial sales in business, and I ran public Sector Day. We're honored to give them at a small token of our gift from A to B s to help support their efforts. >>Congratulates, We appreciate you coming on the Cube sharing the update on good luck into 2020. Great to see you 10 years at AWS day one. Still, >>it's day one. I feel like I started >>it like still, like 10 o'clock in the morning or like still a day it wasn't like >>I still wake up every day with the jump in my staff and excited about what I'm gonna do. And so I am. You know, I am really excited that we're doing and like Andy and I say we're just scratching the surface. >>You're a fighter. You are charging We love you, Great executive. You're the chief of public. Get a great job. Great, too. Follow you and ride the wave with Amazon and cover. You guys were documenting history. >>Yeah, exactly. We're in happy holidays to you all and help seeing our seventh and 20 >>so much. Okay, Cube coverage here live in Las Vegas. This is the cube coverage. Extracting the signals. Wanna shout out to eight of us? An intel for putting on the two sets without sponsorship, we wouldn't be able to support the mission of the Cube. I want to thank them. And thank you for watching with more after this short break.

>> Live from Orlando, Florida It's the Cube covering Enterprise Connect twenty nineteen brought to you by five nine. >> Welcome back to the cubes. Continuing coverage of Day one of Enterprise Connect twenty nineteen in Orlando. I'm Lisa Martin with my co host student a man. And we're excited to be joined by a first time member visitor to the cue. Bryan can the CMO at five nine. Ryan, welcome to the Q. >> Thank you. Good to be here. Thanks for having me. >> Well, thanks for having the Cuban the five nine booth context. There was a service. Tell us a little bit about first of all this event, this event is as to when they were talking about about twenty eight twenty nine years. Lots of evolution from your perspective. Today, what is enterprised connect twenty nineteen. And what opportunities This is going to provide somebody like yourself in terms of the modern marketing. >> Yeah, it's really interesting. Modern markings obviously evolved cms cr m contacts and are all part of the modern marketer. I think this show really proves out how much that modern marketing idea the spaces expanded this my first time here. It's amazing. See, all the companies, all sorts of different technologies, they're coming to market and some have been here for a while. >> One of the things I find really interesting is that you know, we're all consumers everyday way. Want to transact things on our phones, tablets, video chat, this idea of Omni Channel, where the consumer is so empowered way sort of bring these demands to the surface of whatever my problem is, if I'm trying to transact something or I'm trying to get information on mortgage a pre approval or something, I want to be ableto have a company, be able to follow my conversation regardless of channel, and then have enough data to take action on in a timely manner. Where, in your thoughts, from a modern marketing perspective, where are we in terms of maturation of like integrated Omni Channel? >> Yeah, that's a great question. I think we're finally at a mature, pointed technology where we can start to meet the demands of the consumer that salutations with consumer. Obviously, that's the dream scenario for everyone have follow me on my terms, not on the company's terms, I think five nine, we want to make sure that no matter where your customers or your prospect is that we're there to meet them on there, they're channel whether it would be >> so, Ryan, when I look around, a show like this cloud is something that has really transformed what this was. You know, I've looked at what watch? Really? From the end of the early days of companies like sales force, you've got some background there. A cz too, You know the enterprise. Is it OK? Can I trust it? Today? Cloud is here. It's not going anywhere. Major piece of the landscape when you're talking, you're customers, you know? How does that fit into the environment? You know, have they gotten over some of the, you know, kind of legacy it mindset of, you know, because I'm not sure if I'm safe to go out there, >> that is we're at a critical point right now where the contacts and her started. Out of all, a lot of the companies have built on from contact centers are starting to age out. What we're hearing from our customers is that the cloud is has never been more important. And the reason because of that is the data that they're collecting from all their different touchpoints. How do you collect it? How to use it together? How do you make it coherent and make it into a clear plan. The only way you could get the data out is to have it all in the clouds. >> So, Brian, I'm glad you brought up data because when we look at our research, data is at the center of everything. Obviously majorly important cloud. I can't have a I if it's not for the data. Exactly. I think back to you know, my first job out of college, I worked in a call centre. We talked about data being important way talked about. Oh, we're goingto have a database that's going to help you get your customer's information fast. That was back in the nineties. Yeah, it's very different today. Can you talk about how things are different today when we talk about data? How does that drive your businesses? Five nine. And your role is the CMO today. >> Yeah, well, the first thing about five nine is that we have over five billion minutes of data. Conversational data data has evolved over time. Early on, we had a lot of what we call operational data data that says how many people have flickering website how many people have viewed impressions and things of that nature five nine with really interesting is this. Things that we talked about is contextual data where your customers asking for where they want. They're literally on the phone telling you what's wrong. So that meantime, two resolutions really important. But if you start to look at that data deeper, you can start to predict what your customers are looking for from her services from your products. I think that's what's really gonna be transformational. And as a marketer, I've spent a lifetime looking at that user data and always under trying to ask the question, what our customers saying where they want behind the data. And now we're starting to look at that and marrying those two data sets together. I think that's gonna be the next evolution of data. And that's why I think at five nine, that conversational data, along with operational data as a marker that's really important with Ford. >> So one of the things that I'm interested in is you have a lot of organizations in any industry that are reactive. They want to get too proactive and eventually to predictive what some of the things that an organization, whether it's a telco or a financial services organization. How can they remove some of the barriers in the way between a contact center and those customers so that they can glean those actionable insights in a timely manner? >> Yeah, I mean, it's really about the connection between your earlier question about why the context is so important. You see all the companies here, they're starting to be more and more companies driving into this space, really looking at a I. So the two things that we've touched upon already is the power of the cloud Howard. The data part of a eye to look at all that data and make certain prediction certain conclusions from that data so that you can start to have a clear path to your customer and react faster. It's all about zero distance to your customer. >> Ryan, Can you bring us in the customer experience? I think you know, we've all had, and it put times as a consumer where you're frustrated. I can't buy stuff on the Web site. I've called, you know, interactive voice response or not my favorite thing to deal with. So, you know, if companies aren't using solutions like yours, you know what are they in danger of, >> well, your customers? Their prospects are really the heart of every business right, and part of that is, your brand is really important in those moments when they need you the most. And when they're reaching out, contact me through email as a mask were on the phone. Your brand is that could be at express, but also at its most vulnerable. And that's where the contact center your agents. That experience is crucial to the overall customer experience. You have one bad phone conversation. You have one bad SMS. Your brand is really at risk and your brand if it's at risk. So is your business, because consumers have more choice than they've ever had before. >> One of the things owned stories do you, when you're talking with customers that you say, You know, you have to look at every customer interaction as possibly your last, but also as an opportunity to delight that customer and drive an increase in customer lifetime value. Do you talk to me? Talk to customers, but you gotta look at it through both lenses. >> Yes, I mean, if you don't look at the that's the contextual data, that's the context in which you serve your customers Now five nine. Nothing's more important than the customer, and we always try to make sure the human part interaction never leaves. As technology keeps on expanding, we have to imagine we have to imagine ourselves in our customer seat. Was it like to be on that phone call? Was it like to be on that interaction? And how do you provide companies a platform to be better and better and better have the same Better, Better never best, which is this idea of always evolving. Never feel like you achieve something. Always try to get better. >> Ryan, your your your businesses Cloud based. One of the things about the cloud is usually talking about rather than just something that I install and might have maintenance on. It is something that paying for every month and every year, and therefore I need to maintain a relationship with the customer because otherwise, you know, they could just say, Well, why am I paying for this? Can you talk about the relationship you have with your customers? You know how you make sure that you're giving them, you know, not just a day one experience, but an ongoing experience that grows? >> Yeah, I think. Four five nine customer experience. We're in the customer experience business, and so it's really important. We know that our technology is only a successful is the people who adopted and use it. That's where the technology comes to life. So we want. Make sure that we only sell our product way, help you install it. We help you go through the change management, which is critical. If you don't have your agents involved and they're having a hard time adopting your technology, that means that they're focused on that and not the consumer, not your customer base. So five now we want make sure from beginning to end you are held to our high standard of customer service, which is like this five Blue Star customer service. >> Soon I talked about that and our intro. It's not just ensuring that on organization can facilitate on me ten or ensuring that the customer experience it's table stakes these days. It has to be delivered as a effectively as possible, but it's also the agents who are on the front lines were dealing with. Let's face it, oftentimes if we're calling in or we've used multiple channels. There's maybe an escalation that we're not getting the resolution that we want. So where do you guys have those conversations with? It's not just about implementing cloud technology and Tech Center as service, but it's also about the training and the enablement, an empowerment of the agents to have the data to make those decisions because they're on the front lines. >> Absolutely correct. And that's why we've renamed our platform the genius platform, because we feel that every agent should be a genius at what they're being asked to do. Way won't make them feel confident about the information at the fingertips so that they can focus on the empathy. Five Nine believes that the technology is just a part of it, as I've said before, but really, it's the combination between the change management agent, the customer, the answers and the questions. It's all those things combined. Way won't make that easy for the agent to deliver Amazing touch points for your company, >> right where that that's a great point, because when you talk about, I have automation. I have intelligent, even robotics helping in there. I need that person where I'm not gonna have that empathy. So weigh. >> See that our MPs scores. The Asian experience is critical, right? So we really focus our platform and delivering that for the agent. But the other side to is making sure you can gain the insights from these conversations and delivering it back to the business, because we feel that that's a ZAY said earlier. That's the next evolution of data. Is pulling out that contextual data and marrying it with all your different data sets >> you brought up NPS. I'm curious. Do you have any way of measuring, You know, customers that used your solution versus customers that might have been doing things the old way? Is there a bump in NPS? Is there a bump in retention of agents? How do you measure success? >> Yeah, we take both MPs for our customers, and I know our customers take MPs for their agents and their customers. And when you use five nine, those numbers obviously go up. When you start measuring something, people really, if you analyze it, it will happen. So what we see is a huge adoption of making sure that the customer empathy the customers at the focus >> so last couple questions here, Ryan. You guys had a good amount of enterprise growth and f y eighteen. In fact, they stay large growth in customers with a million in a our annual recurring revenue when your fastest growing Saigon's enterprise. You know, small, medium size businesses often have the same challenges. But I'm wondering if you're seeing any sort of early adopters from an industry perspective, financial services, health care, anything or do you see that it's fairly horizontal and organizations that have to reach that consumer? >> It's fairly horizontal. I think the definition will contact center is obviously expanding. People are really focusing on customer experience, and they're certain to realize that Contact Center is a competitive advantage. If you deliver great customary experience, you do deliver great brand loyalty, and that just means your customers will continue to come to you, trust your brand and ask for more services. And that's obviously way. All know it's easier to retain a customer, then is to find anyone. So we think that is a huge advantage, and we're seeing that across the enterprise they're sending, realized this is a huge difference when everything else is the same. Deliver great customer experience, >> right? So, Brian, let me ask the brand question. You know, CMO When people come to enterprise connector, they're reaching out to five nine. What? What is the brand promise? What do you hope people are walking away and understanding about where you fit in the landscape? >> Yeah, I think that when the key things that I want people to understand about five nine is that where about a platform about delivering relationships? It's about It's about the technology we want. Make sure you have ploughed the latest and greatest. We won't make sure features are today. But really, what's important is that service all the way through from implementation to your agents. Happiness here, customer happiness, context. There's a conflict blend technology, people and this interaction with your customers. We will make sure that each part of those are being service, not just a technology, just not a person with the whole life cycle from beginning to end. >> Well, Ryan, thanks so much for joining stew and me on the cue this afternoon and inviting us into the five nine booth and also kind of sending the contacts for the Enterprise Connect twenty nineteen event that we really appreciate your time. >> Thank you for having me. It's been great. >> Hirsute men. A man. I'm Lisa Martin, your Washington Cube lying from day one of our coverage of enterprise Connect twenty nineteen.

>> Announcer: Live from Las Vegas, it's the Cube. Covering Dell Technologies Wold 2018. Brought to you by Dell EMC and it's Ecosystem partners. >> We are back in Las Vegas. This is Dell Technologies World, the first ever Dell Technologies World. Last year was Dell EMC World, of course before that was EMC World a merge of these two giants, I'm Dave Vellante with Stu Miniman. And we're here with Howard Elias, long time Cubilum, >> Great to be back with you. >> Dave: Howard's the president of Services, Digital and IT at Dell EMC, they give you all the hard stuff. >> All the fun stuff, I would say. (Dave laughs) >> See, that's why they give you the hard stuff (Howard laughs). You look great, >> Oh thank you. >> Always done such a great job with complex integrations, you just must be a patient man (giggles). >> Well you know what, they don't call it work when you love what you do, right? >> Dave: Yeah, right. >> It's been great , I know you've heard from Michael and the whole team. It's been a great first year that we closed in February, momentum strong, customer reactions phenomenal and we're delivering and it's just a great time to be in IT. >> Stu said earlier today, when we were doing our keynote analysis, one of the things the EMC never did, it never went out and bought a big services company. You kind of grew things up from within, you kept your swim lanes, >> Howard: Yep! >> relative to your partners, that always worked well for you guys. Maybe you could talk about that a little bit-- >> And it's still working well. Look, our goal in life is to provide the strategic guidance and technology expertise around the products and the technologies and the solutions that we offer. Now, we'll certainly want to monetize those services around where it makes sense for us, But we also work with a very broad ecosystem of partners and that's very important to us. We stick to our knitting, we provide that strategic guidance, that technologies expertise. We're the experts around our technology and our solutions but it's a much broader market beyond that. And so we play very, very well, sticking to what we do well and then leveraging what our partners do well. >> So you've seen it all, I mean you and I grew up in the mainframe era when IBM was sort of the dominant position. And with Compact you saw huge awesome PC business, then you saw the internet and how that changed competition and now we're entering, it feels like, on the cloud era, forgot about that, and we're entering it feels like a new era, this digital era. >> Yeah the next big era of IT as we call it and we've seen this pendulum swing, centralized, decentralized, distributed back to the cloud, but with IOT, and censors everywhere and data being created at the edge and the core and the cloud, this really requires computing everywhere. And so you've got to have realtime data analytics at the edge whether it's the autonomous car, the robot in the factory, the healthcare systems in the hospital and so on, smart buildings, smart cities. And that needs both edge and distributed core, the ability to do those realtime or near realtime analytics. And then you'll use cloud for trend analysis, deep learning, improving the algorithm, sending that to the edge. And the opportunities there are immense and it's really awe-inspiring to us as we talk about who's the digital leader in IT, it's really our customers. They're really doing some really cool stuff. >> Yeah, we heard some of that this morning. >> Yeah, Howard it's something I remember we said when the whole trend of big data came out, we were like, Hadoop's interesting and it's useful, but it's the businesses that will be spawned off of that that will be truly important. Maybe tell us of data is at the core of it, it's always been at the core of EMC but you look at ML and AI and even Edge, it's all about that data and how does the Dell family really help customers get the value, transform with that data? >> Well here's the difference, right? Because when we were talking about data years ago and those big Hadoop clusters, it was really more about enterprise data and analyzing that enterprise data. Now it's really about those systems of engagement and systems of insight. It's all about that data being generated by our customers, our customers' customers, all the devices that are being used and it's really gaining those insights. And it's really analyzing that data that customers collect with external data and developing new patterns and insights that were just never possible before. So what we do is we help our customers frame their transformation. We talk about digital IT workforce and security and we help them think about where are they in that journey, what are the business outcomes, because is jus6t an enabler, this is really about business outcomes. And technology being business technology and business enabler, so whether it's our consulting organization to help a customer plan those journeys, our implementation business, our support business, even or manage business again, ourselves and with partners, we'll help our customers every stage of that journey. >> We often talk about the difference between the business and a digital business is the way in which a digital business uses data. So in thinking about the way in which you as a digital practitioner use data, how is that evolving, how is that changing? >> Well let's use one real example in our services business. We have an internal capability we call Support Assist. It is analyzing billions and billions of events every single day with all of our connected devices. And it's understanding the use cases how it's being used, what's working, what's not working, develop themes and semantics, and so we actually build better products and services, because of that data. Now this is a traditional call center, connected devise, break-fix business, support business, that is being completely digitized. >> A little of all from phone homes. (laughter) >> A little bit. (laughter) >> I want to ask you Howard, you've been a accomplished leader for many, many years, digital leadership. We talked earlier with Pat, CEOs are trying to figure out, how do I get digital right? How do they get digital right? Who's leading the digital charge within your customer base. >> Well, as I mentioned before, you saw it on stage with our trailblazer and innovator awards, we literally have hundreds and thousands of customers all around the world that are embracing. And what it means to really be digital is to get in with the technology practitioners, the data scientist, the people that understand what technology can do, embedded in the business, but it's getting the business, embedded in IT and technology. It's no more setting the requirements and throwing it over the wall and waiting a few months to get requirement documents back and the waterfall project in your two years later, and then the customer says, "Well that's not what I asked for." Or the markets change or the customers move. And so it's really building these balanced teams now where the business in the technology and the product owners are really getting together and saying, "What we need to do? "Let's go get it out there in the marketplace "and lets iterate, fast fail, learn quickly," that's what digital means. >> How has has Dell EMC consulting evolved, changed, in this digital era? >> Yeah, that's a great point. We've had a consulting business for a while but what we've done is focus them around our transformation journeys. We call it our three by three by one matrix. So we're focused on three specific offers in each of our IT transformation, digital transformation and workforce transformation. So three core offerings, you can IT transformation in Hybrid Cloud is an example or workforces collaboration. We of course embed security all throughout all three of those and then we have a transformation program office. So we focus down on 12 markets around the world, those three disciplines, hyper focus where we have great expertise and then we leverage our partner ecosystem beyond that. >> So that's a simpler approach than-- >> Howard: It is. >> what you need, we can we can do it. Which really was never your business anyway, but you kind of bled into that a littl&e bit. >> Yeah, well this gets back to re-examining what we're really good at. And what we wanted to focus on was that strategic guidance in technology expertise around our products and technologies, how we do that best, how we integrate into other ecosystems and then leverage the partners for the rest. >> Howard, one of the things that we heard from Alison this morning is people are bit skeptical as to how much the technology can help. I know one thing that your group helps a lot on is the career tracks. How do we move from being an admin of the silo to working closer with the business, being an architect or moving there. What are you see on your customers' journey from a career stand of point? >> That's a great point, cause one of the things we do focus on in our consulting practices, technology is necessary but woefully insufficient. You also have to transform people, process and operating model. That doesn't just mean structure, but the way that people operate within the business and within technology. And we've seen a huge increase in requirement for the transformation of people and process. This is where our education services teams come in, not just training about product and technology technology, but the accreditations, the certifications, around cloud, around data science, around what does it really mean to do analytics in an AI, ML world? And were seeing a tremendous trajectory in that. >> And the data model is changing. You maybe have a lot of backend systems around Oracle or SAP, but it doesn't necessarily tell the story of what's really happening in the field or closer to the customer. Do you discern a difference between those customers who, sorry, "get digital" and maybe those that are not as advanced in terms of the way they treat data closer to the customer? >> Well I think we're all learning. And this is really that notion of the systems of engagement because the data analytics are no longer just in the core or just at the edge, it's distributed data, and distributed data analytics and figuring out where the processing power needs to be to do the right set of analytics, for the right data set for the purposes needed at that time. And were all learning through that and it'll be different depending on the use case. >> What's your sense of let's talk about disruption a little bit. Everybody talks about it, but I'd like to put some substance behind it. It seems like every industry has its own disruption scenario. Some industries, music, certainly publishing, now taxis, hotels, have been highly disrupted. Others, banking, other financial services, insurance, healthcare, not so much disrupted yet. >> But it's coming, it's happening in different flavors at different paces, look at what FinTech's doing. Goldman Sachs getting into retail bank with Marcus, have built ground-up digital bank from the ground up. Look, every business in every industry is going to be disrupted at some level, and it's all about understanding your customer better, addressing those needs faster, learning quicker than the competition of what works for customers, what needs to change for customers and actually finding those value points even before the customers realize it themselves. And we've seen this in industry after industry and yeah, some of the big heavy infrastructure industries might take a little bit longer, but it's common to all of us. >> Wow, we agree, there is no industry that's safe, which implies that there's going to be new winners and some losers. >> And this is the opportunity for all of us, embrace! And have the courage of your conviction to go try new things. Not everything's going to work. The best hitters in baseball never bat a thousand, they don't even bat over 500, we need to do better in that business for sure, but you're not going to bat a thousand. And in fact if all you do, is if everything you did work perfectly, you're not trying enough stuff. >> Howard, we here so much about the change that's happening here, internally while change just went on. You were critically involved in all of the integration pieces. How do you help the teams inside embrace change, be aware of it, knowing that there's going to be some ups and downs, how does the cultural help? >> Well, first of all in the technology industry, we're the bastion of lots of change and disruption for many years. Other industries are going to be going through what we've been going through for decades, right? And so first of all it takes a certain kind of person to be in this business already, so they understand change is the new normal. But the more important thing we can do is have clear vision and strategy. What were trying to accomplish for our customers, we're very clear about what we measure our customer NPS, RT member MPS, our relative market performance, which then leads to our financials. We have we call Strategy Cascade, where we're very clear of our purpose which you heard Michael talk about, developing the technologies that drive human progress, our strategy to become the essential infrastructure company for today's application and the cloud-native era that we're entering, and then what are the key things were doing and what does every team member inside of our company do? And there's only two kinds of team members we have at Dell, those who serve our customers directly and those who serve, those who serve our customer. >> So Dell Technologies World, first ever? >> First-ever. >> Obviously a lot of synergies with previous Dell EMC World, EMC World at the root6 of this, Dell World brought in, but what what what should we expect here, what are the learnings, what are the things you want your customers to take away? >> Well you've seen a progression since we've come together, we refer to it as better together. It's important that we understand that we have businesses, technologies and brands. They operate at different rhythms, some of them have different business models, some of them have different ecosystems, some of our platform versus product. And so that's the reason why we got the structure we do, but our customers are better off when we're better together. And so what Dell Technologies World is meant to show is, the power of all of our capabilities. Not every customer will use everything, but those that want that full end-to-end experience, we want to learn, how we could deliver that better. >> You guys use that as a competitive advantage. >> We do. >> I mean granted, if you're a one product company and you got what's perceived as the best widget, you're going to sell some. But you guys of change the way in which you compete (giggles) the cross-selling that were seeing, obviously VMware is a huge piece of that, your security businesses, you mentioned Pivotal earlier, >> And we do it in a way that is open at every level. So it's not something that the customer, that we require them to go a certain way. Cause you think about a typical stackable hybrid cloud, PCF with PKS, on VMware Cloud foundation, running on Dell infrastructure underneath, secured by RSA and Secure Works, maybe delivered as a cloud by Virtue Stream. Those are all choices. And customers can make different choices at different levels with open interfaces and open APIs, but we do believe customers that are looking for more integrated solutions, we are better together. >> Well I think your secret is you're having fun, I mean it shows, Howard. You've gone through so many transformations, such as successful exec and have a great friend of theCube so thank you so much-- >> My pleasure, thank you. Great to see you, and thank you everybody. >> Alright, keep it right there everybody, we'll be back, with our next guest. We're live from Dell Technologies World, 2018 in Vegas. Be right back. (digital music)