from the cube studios in Palo Alto in Boston it's the cube covering empowering the autonomous enterprise brought to you by Oracle consulting hello everyone and welcome to this cube special presentation where we're covering the rebirth of Oracle consulting so this is a digital event where we're going around and identifying subject matter experts in different locations we're currently here in Chicago and I'm here with Stephanie trunzo who's the head of transformation and offerings at Oracle consulting is definitely great to see you again yeah you too so Oracle consulting you know you guys have been quiet lately where you been yeah well we were quiet because I wasn't here yet yeah make a noise yeah exactly here to make some noise so I love the way you said rebirth I think it's really accurate work while consulting has been around for quite some time but as you said maybe not high on the radar and one of the things that we're learning and one of the reasons I'm here in this transformation role is to help us transform ourselves to better match the transformation that our clients are going through so was there an internal transformation or is there an internal transformation taking place as well and then just sort of pointed to the marketplace maybe you could describe that absolutely yeah so we are undergoing our own transformation at the same time that we're helping our clients undergo their transformation and so for us what that looks like it is things like a traditional services organization which is kind of what Oracle consulting had been in the past was looking at the expertise that was necessary to drive clients business forward but delivering it in what I would call a pretty traditional way time and materials based kinds of contracting determining the skills that were necessary and and conversing with clients and feature function kinds of discussions and our transformation is now about rebuilding the organization around offerings and those offerings are things that we're doing to match the way that our clients are consuming let's say cloud technology so if you might purchase natural language processing service from a cloud platform we want to also make sure that we're matching the humans to those technology services and enabling our clients to buy from us very similar way you're also bringing in some some new blood I mean obviously Oracle a large organization a lot of DNA there but yourself you came from IBM you got people coming in from AWS you got folks from Accenture and all over the place so describe that and how that's affecting the culture of Oracle consulting there's an influx of talent that is necessary to change the way that you think and I believe that one of the reasons I myself came to join Oracle consulting was I was excited about this new adventure so when you're working in a certain style in a certain way in a certain team for some amount of time you can maybe forget to get introspective and forget to look at what's right in front of you and the changes you need to make so bringing in new talent from outside is as much a part of our transformation as the way that we're shaping our offerings is bringing in those new ideas bringing in people who have you know been there done it in other experiences so that they can infuse our thinking with some of what's going on in the market around us how would you summarize the mission of Oracle consulting the mission of Oracle consulting is extremely simple it's dead simple it's helped our clients succeed on Oracle cloud technology period of course Oracle's known as a product company is sell software products that's how you generate most of your revenue so and you've got your cloud you've got you know things like cloud a customer and you know Exadata that's really driving you got the Oracle database certainly a huge application portfolio how is Oracle consulting aligning with the products as a product company our goal is still to help our clients achieve their goals right and so consulting is looking at our Oracle products that to make sure that we are always the deepest and the best at understanding so we can help leverage that technology to its fullest capacity for our clients it's not just good enough to buy a tool you have to know how to use it right and so our objective is to align with Oracle products make sure we know what's going to be hot off the press that we're driving from our client experiences back into the product sets as well so we're informing our product development of what's really happening out with our clients implementations my last question Stephanie is how are you gonna define success when you look back you know a couple years from now what will success look like success to me will look like being the go-to for any solution that is an Oracle driven answer to our clients that Oracle consulting is driving consumption in a way that is extremely valuable to the client because in the end cloud consumption technology consumption by in and of itself is not very interesting it's when we're telling stories that are our client stories on stages because we've helped them achieve new business outcomes things that weren't possible for them before well it's great to have you thank you so much for coming on and it's good to have you at the helm sort of bring credibility to Oracle consulting and we'll be watching so thank you awesome thank you all right thank you for watching we'll be right back with our next guest [Music] you [Music]

>>Yeah, yeah, yeah, >>already. Welcome back, Cube alum Dave Volante. We're covering the transformation of Oracle Consulting. Specifically focused on really, what is what I consider a rebirth from really staff augmentation to a much more strategic partner for customers and with me to explore that a little bit of Sherry Latin back. She is the senior vice president of Cloud Key accounts at Oracle, and we're also joined by Pat McGovern. Who's the group? EVP for the North American Cloud strategy. Also Oracle folks, welcome to the Cube. Thanks for coming on. >>Thanks >>for having us. >>You're welcome. So, Sheri, you're out talking to customers a lot. Um, I'm curious as to what that conversation is like specifically as it relates to consulting. I talked about the rebirth of Oracle consulting. You? Probably not, you know, earlier, years ago, leading with staff augmentation. That's not strategic. But are you bringing Oracle consulting now into the conversation? What's that conversation like? >>Absolutely. In fact, every conversation we have relating to our cloud strategy. Oracle consultants part and parcel to that they are not staff augmentation. They're actually the digital transformation arm of what we do around cloud. So it's been really interesting to see what they've been able to do in terms of changing the narrative of what we do it Oracle from just a software company to really transform into. I thought provider >>and Chris I'm interested in Sorry, pat. I'm interested in your title group. VP Cloud strategy. Right? So gravity, obviously a fundamental part of any customer interaction. But what are you seeing? What underscores customer strategies? What are the business drivers for them right now? One of the catalysts that are driving their their technology spending decisions? >>Yeah, it's a great question, and I think a lot of it depends upon, especially in the times that we're in now depends upon the industry that they're in. But, um, most importantly, what we're seeing is right now is durability. So we want to make sure that the customers of our Oracle customers and others have an opportunity to have disaster recovery business continuity. Um, in this stage, right now, it's less about expansion per se. Unless in an industry that's uniquely positioned for that more about durability, of the overall strategy that when we look at that, your ability, we think about kind of the core missions we think about, um so the back office operations and continuity and then we think about transformational revenue generation. And so when we partner with us, yes, we want to make sure that we have both of those concepts in mind. So >>I want to ask you both. Um, you know, it was a lot of we have a lot of talk about in our community about cloud first. Um, big oracle is sort of put forth the gauntlet of Look, we're we're leading now with cloud. You both have cloud in your title. But obviously being cloud first is is more than that sharing. What if you could talk about your customers and your cloud journey and share with us and convince us that you are cloud first? >>That's a great question. And in fact, I joined Oracle about 11 months ago, was in the industry for about 25 years and enjoying simply because I believe in what Oracle is doing around this journey. We're in our second generation of cloud capabilities, and that's purposeful. And we do that because we realized that where cloud started and where we are today, are two totally different things. And so we have capabilities around security viability extensions with autonomous that other cloud providers just simply don't have built these ground up to make sure that we can run Oracle for blitz databases and applications far better than any other cloud provider. So that's super exciting time you got Oracle, and it's absolutely fascinating what our customers are going to a doctor. Apology? >>Yes, so s so pat. I wanna ask you, Ah, sort of similar question. How fundamental is, uh, you know, Cloud to organizations, strategies, and obviously everybody is a cloud strategy. But I'm specifically asking as it relates to mission critical workloads because, let's face it, that's been the hardest to move into the cloud. So when you're out talking to customers about their strategy and obviously dovetailing at the Oracle strategy, how do you align those two views? >>Yeah, so it's actually really fascinating question. So first I think I would respond in the following away. When I think about our portfolio, I don't necessarily say cloud First, I say customer first, and I really want the customer to make a decision based upon a deployment model that makes sense for that. Think of the customer whether it's a regulated industry or the public sector or, you know, any sort of compliance considerations. So Oracle's one of the very few, uh, you know, enterprise Last Mile providers that has obviously on premise capabilities as well. And so 99% of the cases that we see, with the exception of some of the sort of startup S and B five folks that are born in the cloud, we're dealing with the hybrid cloud model anyway. And so that's the kind of the first order priorities what's right for the customer. And let's make sure that we get the appropriate I'm all for that customer in terms of enterprise essentially the workloads that we have, whether it's cloud or on Prem or enterprise workloads. And those were kind of separated into two buckets, one of the core mission of the revenue generation side. And what would be mission critical sort of the back office, the oracles historically tremendous at the back office side, running finance, running operations, running supply chain, you know, doing those things that are mission critical on the core mission side. That's really where we're starting to focus now, which is getting out into the revenue generation. The mission of the entity with things like high performance. Compute on making sure that we have an ability to support our customers on both sides of those. >>You got a follow up question on strategy. You talked about hybrid. And you know the hybrid. Clearly, riel, whatever the big buzzword today is multi cloud. My question is, is multi cloud the actual strategy of customers or is it actually just an outcome of multi vendor and and shadow I t. But what if you could address that? Yeah, >>So another great question. So I think if you're on one side of the fence, you call it a strategy on maybe risk mitigation on the other side of the fence, you could say, you know, I don't When people talk about multi cloud, they tend to say, Hey, you know that one of the big names that you hear, whether it's Oracle or aws, um you know Microsoft etcetera? Uh huh. But the reality is anybody who's running those are also running, you know, hundreds of father for SAS applications. Whether the department allowed sort of that shadow, I t. I think in part you call it a strategy. In part, you'd say it's just sort of propagation of cloud capabilities that have sprung up, Do you think? Based on, you know, security integration, performance considerations as well as sort of the general expansiveness of enterprise class capabilities? You probably see if you're niche players over time and you'll see kind of the broader bets happening around enterprise class capabilities. >>So, Sheri, you're relatively new to the oracle of just under a year. But you've been around the industry, and you know that the chairman of a horrible loves technology you love speeds and feeds and shares that Oracle Open World but and, you know or was a product company. But the conversation is changing. You kind of alluded to that before. It's not just about feature function speeds and feeds. Maybe you could address that. And where does Oracle consulting fit in that equation? >>Right, So it kind of detail of what Pat was just saying around the hybrid notion. We firmly believe that every customer is gonna wanna have different options for what they do in the cloud and based on the providers. So we want. We've partnered with Microsoft. We actually can interconnect are clouds together to provide that kind of flexibility to our customers. Yeah, it is a key component of that Azure customers and talk about. I'm going to stop integration. Our partnership or consultant is the arm that does that work for us. So we are seeing them come, come about in a much different way in a way that's different, you know? And other consulting, you know, staff augmentation firms. >>Well, that Microsoft is interesting to us. Uh, actually, a lot of people in the press might have put food. It saw that and said, Wow, this is This is pretty curious both from a strategy standpoint, but it really. But I think it's premature on Oracle. So you got the Number one database. Everybody knows Oracle's got the native get this hyper cloud partner now saying, Yeah, we can run. You're kind of seamlessly. I know that's an overused word, but what is the reaction been in the customer base? That deal? >>It's phenomenal. It's infinite, especially for a lot of our retailers that are being Microsoft Cloud companies. They're seeing that they can put their Microsoft applications in the Microsoft class. They can run the Oracle databases in the Oracle Cloud and Inter Operability is tremendous and they're not any sort of service as it relates to putting, you know, using a multi cloud strategy. And for us, we're seeing that as a differentiator for us in the market. >>So what's the strategy behind that? I want you to talk about that a little bit, because, I mean, you know, it was it was an interesting chess move by Oracle you got, you know, Amazon's out there doing their thing, and there's plenty of Oracle running on on AWS. But there's a lot of head bashing going on, and then you guys partner up with Microsoft that caught a lot of people off guard. Can you help us, You know, give us a little color on the strategy behind that? >>Yeah, so I think that there's a There's a technical component of the strategy which Sherry alluded to, but I also think that there's a cultural component of the strategy and so, you know, obviously Microsoft has been around for a long time. ESX has Oracle that they have a substantial on from this friend. But as much as any other company on the Lana, probably Microsoft has this hybrid strategy just like Oracle. And so, as we look at, you know, the partner ecosystem and what makes sense the partner and how can we diversify the workloads like Microsoft is one of those companies? That's just sort of, Ah, very vertical industry focused great portfolio products. I'm slightly differentiated in terms of the space that they would buy in versus an Oracle. As you pointed out, So, uh, cultural standpoint, I think it's quite a good fit for us to find, you know, as we look at partners to find a partner like Microsoft to work with an integrated workloads. It >>was kind of a judo move for both companies in my mind, because you see a lot of companies that are predominantly on Prem, just like Oracle has been historically saying with Microsoft and basically kind of going on to hybrid, obviously they want on Prem and multi Cloud, which is okay, we're going to span multiple clouds. But both Oracle Now and Microsoft, with its hybrid strategy, as I call it, a judo move because essentially you're doing things that maybe some of the other cloud providers can't do because of your own prim present. So you're turning what may have been perceived as a disadvantage, you know, a legacy business. You know, it's funny in our business legacies of >>a >>bad word, but but it's usually as good connotations. But turning that on Prem legacy into an advantage. Cherry. Is that a reasonable premise that I'm putting forth and you having conversations with customers in that regard? >>Absolutely. Yeah, I think that's a very fair statement to make, because we do have again. I oversee the top 120 Oracle's and in that they have years and years of investment in Oracle databases in Oracle applications and for us agreeable by the capabilities to move that to your cloud. Integrate with other things such as Microsoft, you know, applications and whatnot is huge issue, and no other cloud provider can say that. So I do think that good to see that we are uniquely differentiated. >>I want to ask you about lock in because that's always the criticism of Oracle. I talked to a lot of work with customers in particular exit data. People say, Why would anybody buy exit data locks in what you by AWS and why would you buy any product. You, uh, disk drive a lock in. So So I want to ask you about that because my research shows that while there's a there's a segment of customers that are very much concerned about that, and that's a primary concern you lock in. It's actually a small percentage, maybe 10 15%. Most of the customers that I to talk to the Oracle world will say, Listen, I'm willing to risk that lock in If if If the business value overwhelms that And again I ask you, Is that is that something that is a viable conversation with your customers? Do you see the same thing? I mean, I see it as kind of a strong indication. If they kind of poo poo the lock in pieces, they look at the business value that I'm driving from my organization. I wonder if you could >>Yes. So I think value is the crux of the conversation. And if you look at sort of the legacy business, just put it that for a second. You know that what people would call legacy, uh, the US is a tremendous asset because we have 400,000 customers or so around the world. Those are folks that we're giving choice. You can run on Prem. You can run in the cloud. You can find an engineered systems or into the data box behind your firewall. You can run it as a data cloud at customer, which is behind your firewall, but leveraging Native Public Cloud services. Or you can run that same capability and exit out of service. So really again, that deployment model choice about what, folks? You how folks wanna consume their services in terms of lock in. I don't think it's so much lock in, as you point out, is value if a customer's deriving value from a given solution, especially in the cloud world, they're going to consume right, and if they're going to consume the probability and higher likelihood is that they'll expand as well. So I look it. I essentially look at consumption in the cloud world being value that's been realized, and once you have value that's been realized, it's critical conversation. I don't I don't view it is lock. In fact, there's a lot of fun, mobility and portability that can occur when you talk about hybrid cloud multi cloud environments. I view it much more is identifying the value and then executing against that value so that folks consume cloud services. >>Why, Cheri, why are customers wanting to put mission critical workloads in the cloud? Is it the same sort of cloud, agility and cost, etcetera, etcetera. I mean, why not just leave it on Prem and keep it protected and maybe spend a little bit more? What's the driver for moving mission Critical workloads? >>Well, I think it's it's dependent upon you know what? The initiatives are in the company right now. They're looking for cost reduction for top line growth, either looking for different capabilities around security that the cloud provides. The great thing about what we do is we have optimized all of our work lives but our database and our applications into our class of providing additional capabilities. But we're also seeing a lot more. So we, uh we say all the time you put us to the test, let us, you know, quantify what we would look like in the cloud with our workloads versus competitors, er and we will guarantee that will save you a lot of money. So I think that a lot of it has to do with one. It starts with potentially cost reduction, but then they start seeing additional business value driven out of and back to Oracle Consulting. What Oracle consultant provides in terms of business value in the cloud is transformative for our customers. >>Well, that this is valued to is a component of the business case that has to be risk mitigation. And, you know, if you just want to buy some object storage, you know, probably not gonna work is not going to be my first call. But if I have a mission critical set of workloads that are running on Oracle, I'm really going to think twice about migrating that, you know, somewhere else I'm either gonna leave it on, Prem, or I'm gonna look look hard that Oracle's same same approach. And we've done some research on this that the risk and cost of actually migrating to a new environment is is potentially really detrimental to companies. I wonder if you could talk about how that plays into your and customers strategies. >>Yeah, and I think, you know, is, um, reference in what? What Kerry said. So it depends on the choice of the customer, but what I would say is if a customer is driving a lot of value on premise, um, that might look something like exists ts and the cloud for D. R. So they're actually have a disaster recovery plan that's file based. I think Cloud is one of these sort of unicorn conversations. Everybody, everybody wants to have a cloud conversation. And so, making sure that that cloud of conversation in the context of the customer, um, is what's crucial for us. And so, you know, as you look at mission critical workloads, those are the workloads that we want. We want either core mission, our mission critical. It's just object storage or just something, you know, that people want to spin up and spin down. Yeah, that's interesting to Oracle, but for us, as a B two b, your B two b enterprise class, um, software company, we want to be in your core mission or in your back office, you know, helping you execute against that mission. >>So share here, going in with a stacked deck. I mean, you're not going in trying to go head to head with the hyper scale you going in saying, Look, this is our wheelhouse, and I think I'm hearing in your wheelhouse you'll take anybody on. But I wonder if you could sort of affirm that and maybe talk about how you lead in these customer conversations, >>right? Well, normally, our entry point is one. Understanding with business drivers are right. It has to be a business led recession. Really? Isn't a technology starting point right? It really is around what business problems we're trying to solve and how can we help you solve them? And because we know your environments, we know what data bases air deployed in. Other public. What is your lover? Dji to run your business? We can, I think, successfully position ourselves very, very competitively against other cloud providers. And I think that is something that resonated incredibly well with our customers and back. >>Yes, So it seems like Oracle Consulting is an important ingredient as part of that strategy, Cause again, If it was, you know, five years ago it was just stack staff augmentation. That's really not a compelling conversation to have with customers. But if you can come in with A with the mindset of strategic partner you're bringing in Deloitte, we've been talking to some of their professionals about the elevate program with with Oracle, that is, that's a nice lever that your you can take advantage of. >>Absolutely. And in fact, we've seen that that is a huge opportunity. For one, the partnership with Deloitte is incredibly strategic. We also partner with other companies like Accenture and DXC and IBM Candidly and Oracle is consulting is incredibly flexible in terms of what kind of partnerships and the line they have with our customers is really based. Yeah, >>I want to end on a growth path and maybe talk about everyone wants to weaken. Cloud Cloud is the growth business. You look at Oracle's business, you know everybody's business. This cloud is growing. Everything else is either hanging on or declining. So it's all about growth. How do you drive growth? What what is Cloud's role in terms of, you know, the growth strategy and maybe had some color to that narrative? >>Yeah, so from a from an execution standpoint, how we drive growth is we have a kind of a core part capability, its value volume, velocity burger. Those are very simplistic approach that we take in each of our line of businesses and then across each of the segments of the market size pass and I as an engineer systems as well. The values crucial If you're not, you're not selling with value and kind of positioning value at the up front part of it. You know, the customers may book, but it won't consume and don't consume. They're not going to renew. So ensuring that customers are realizing value from the process is essential. And then with volume and velocity, you know, our legacy business was much more kind of chunkier, so you could focus on big quarter ends or a big year end on. You had impending events through, you know, started compliance considerations or contract negotiations, etcetera. We have to be in a volume and velocity business in order to scale out and also the average transaction sizes. Historically, although it's growing for us, >>it >>is slightly lower than what a license on premise capability would be. As you'd expect, um, from, uh, from a product perspective, I think, you know, we were sort of a luxury of riches around the autonomous capabilities. If you haven't so that's something that's incredibly unique. Oracle. You know, the Economist database and all the economist services that we're rolling out and that Autonomous gets back to what we talked about earlier, around security, around performance, around scale, ability and all these things. Ultimately, we're positioning the capabilities of the future, but we're positioning them today. So we're a market leader in this space. You're not only is the Oracle database. As you pointed out, the market leader were market leaders here. If you found a bunch of the SAS areas, this eponymous segment of the market is crucial for us and crucial to our growth. >>Yeah, it really isn't enabling. What I've been saying. That you it's almost compulsory for Oracle to participate and compete in the cloud because it gives you that automation and that that scale. But you're talking about also setting up, you know, some future advantages of being able to take advantage of data. The combination of data ai and Cloud is the new superpower with within the industry. Sherry, I want O end on you. 11 months in an oracle. Let's say things work out great. You're here 234 years down the road. You look back. What does success look like? >>Success looks like everyone of our customers moving to the Oracle cloud and see incredible business value from that partnering with Oracle Consulting. That's what my successful curious >>guys. Thanks so much for coming on the Cube where we've been we've been tracking this transformation of Oracle consulting and one of the things that's very clear. There was Oracle's obviously serious about cloud, but also seriously about bringing in new talent and new skill sets really not only transform Oracle but help transform your customers. So thank you for your time. Really appreciate it. >>Thanks so much. >>You bet. Thank you. >>All right. Thank you. Everybody for watching. This is Dave Vellante for the Cube. We'll see you next time. >>Yeah, yeah, yeah, yeah, yeah, yeah.

(upbeat music) >> Welcome back to theCUBE everybody. This is Dave Vellante. We've been covering the transformation of Oracle Consulting and really its rebirth. And I'm here with Chris Fox, who's the Group Vice President for Enterprise Cloud Architects and Chief Technologist for the North America Tech Cloud at Oracle. Chris, thanks so much for coming on theCUBE. >> Thanks Dave, glad to be here. >> So I love this title. I mean years ago there was no such thing as a Cloud Architect, certainly there were Chief Technologists but so you are really-- Those are your peeps, is that right? >> That's right. That's right. That's really, my team and I, that's all we do. So our focus is really helping our customers take this journey from when they were on premise to really transforming with cloud. And when we think about cloud, really for us, it's a combination. It's our hybrid cloud which happens to be on premise and then of course the true public cloud like most people are familiar with. So, very exciting journey and frankly I've seen just a lot of success for our customers. >> interesting that you hear conversations like, "Oh every company is a software company" which by the way we believe. Everybody's got a some kind of SaaS offering, but it really used to be the application, heads within organizations that had a lot of the power, still do, but of course you have cloud native developers etc. And now you have this new role of Cloud Architects, they've got to align, essentially have to provide infrastructure and capabilities so that you can be agile from a development standpoint. I wonder if you can talk about that dynamic of how the roles have evolved in the last several years. >> Yeah, you know it's very interesting now because as Oracle we spend a lot of our time with those applications owners. As a leader in SaaS right now, SaaS ERP, HCM. You just start walking through the list, they're transforming their organizations. They're trying to make their lives, much more efficient, better for their employees or customers etc. On the other side of the spectrum, we have the cloud native development teams and they're looking at better ways to deploy, develop applications, roll out new features at scale, roll out new pipelines. But Dave, what I think we're seeing at Oracle though, because we're so connected with SaaS and then we're also connected with the traditional applications that have run the business for years, the legacy applications that have been servicing us for 20 years and then the cloud native developers. So what my team and I are constantly focused on now is things like digital transformation and really wiring up all three of these across. So if we think of like a customer outcome, like I want to have a package delivered to me from a retailer, that actual process flow could touch a brand new cloud native site from e-commerce. It could touch essentially, maybe a traditional application that used to be on prem that's now on the cloud and then it might even use some new SaaS application maybe for maybe a procurement process or delivery vehicle and scheduling. So what my team does, we actually connect all three. So, what I always mention to my team and all of our customers, we have to be able to service all three of those constituents and really think about process flows. So I take the cloud native developer, we help them become efficient. We take the person who's been running that traditional application and we help them become more efficient. And then we have the SaaS applications which are now rolling out new features on a quarterly basis and the whole new delivery model. But the real key is connecting all three of these into a business process flow that makes the customer's life much more efficient. >> So what you're saying is that these Cloud Architects and the sort of modern day Chief Technologists, they're multi tool players. It's not just about cloud, it's about connecting that cloud to, whether the system's on prem or other clouds. Is that right? >> It is. You know and one thing that we're seeing too Dave, is that we know it's multi cloud. So it could be Oracle's cloud, hopefully it's always Oracle's cloud, but we don't expect that. So as architects, we certainly have to take a look at what is it that we're trying to optimize? What's the outcome we're looking for? And then be able to work across these teams, and I think what makes it probably most fun and exciting, on one day in one morning, let's say, you could be talking to the cloud native developer team. Talking about Kubernetes, CI/CD pipelines, all the great technologies that help us roll out applications and features faster. Then you'll go to a traditional, maybe Oracle E-Business suite job. This is something that's been running on prem maybe for 20 years, and it's really still servicing the business. And then you have another team that maybe is rolling out a SaaS application from Oracle. And literally all three teams are connected by a process flow. So the question is, how do we optimize all three on behalf of either the customer, the employee, the supplier? And that's really the job for the Oracle Cloud Architect. Which I think, really good, that's different than the other cloud because for the most part, we actually do offer SaaS, we offer platform, we offer infrastructure and we offer the hybrid cloud on prem. So it's a common conversation. How do we optimize all these? >> So I want to get into this cloud conversation a little bit. You guys are used to this term last mover advantage. I got to ask you about it. How is being last an advantage? But let me start there. >> Yeah, that's a great question. I mean, so frankly speaking I think that-- So Oracle has been developing, what's interesting is our SaaS applications for many, many, many years, and where we began this journey is looking at SaaS. And then we started with platform. Right after that we started saying how do we augment SaaS? This OCI for us or Oracle Cloud Infrastructure Gen 2 could be considered a last mover advantage. What does that mean? We join this cloud journey later than the others but because of our heritage, of the workloads we've been running, right? We've been running enterprise scale workloads for years, the cloud itself has been phenomenal, right? It's easier to use, pay for what you use, elastic etc. These are all phenomenal features, fell. And based on our enterprise heritage it wasn't delivering resilience at scale, even for like the traditional applications we've known on prem forever. People always say, "Chris we want to get out of the data center. "We're going zero data center." And I always say, "Well, how are you going to handle that back office stuff?" Right? The stuff that's really big, it's cranky, doesn't handle just, instances dying or things going away too easily. It needs predictable performance. It needs scale. It absolutely needs security and ultimately a lot of these applications truly have relied on an Oracle database. The Oracle database has it's own specific characteristics that it needs to run really well. So we actually looked at the cloud and we said, let's take the first generation clouds, which are doing great, but let's add the features that specifically, a lot of times, the Oracle workload needed in order to run very well and in a cost effective manner. So that's what we mean when we say, last mover advantage. We said, let's take the best of the clouds that are out there today. Let's look at the workloads that, frankly Oracle runs and has been running for years, what our customers needed and then let's build those features right into this next version of the cloud, we can service the enterprise. So our goal, honestly what's interesting is, even that first discussion we had about cloud native, and legacy applications, and also the new SaaS applications, we built a cloud that handles all three use cases, at scale resiliently in a very secure manner, and I don't know of any other cloud that's handling those three use cases, all in, we'll call it the same tendency for us at Oracle. >> Let's unpack that a little bit and get into, sort of, trying to understand the strategy and I want to frame it. So you were the last really to enter the cloud market, let's sort of agree on that. >> Chris: Yup. >> And you kind of built it from the ground up. And it's just too expensive now. The CapEx required to get into cloud is just astronomical. Now, even for a SaaS company, there's no sense. If you're a new SaaS company, you're going to run it in the cloud. Somebody else's cloud. There are some SaaS companies that of course run their own data centers but they're fewer and further between. But so, and I've also said that your advantage relative to the hyper scalers is that you've got this big SaaS estate and it somewhat insulates you, actually more than somewhat. Largely insulates you from the race to the bottom. On compute and storage, cost per bit kind of thing. But my question is, why was it was it important for Oracle, and is it important for Oracle and it's customers, that it had to participate in IaaS and PaaS and SaaS? Why not just the last two layers of that? What does that give you from a strategic advantage standpoint and what does that do for your customer? >> Yeah, great question. So the number one reason why we needed to have all three was that we have so many customers to today that are in a data center. They're running a lot of our workloads on premise and they absolutely are trying to find a better way to deliver a lower cost services to their customers. And, so, we couldn't just say let's just-- everyone needs to just become net new. Everyone just needs to ditch the old and go just to brand new alone. Too hard, too expensive at times. So we said, let's give us customers the ultimate amount of choice. So, let's even go back again to that developer conversation in SaaS. If you didn't have IaaS, we couldn't help customers achieve a zero data center strategy with their traditional application. We'll call it Peoplesoft, or JD Edwards or E-Business suite or even-- there's some massive applications that are running on the Oracle cloud right now that are custom applications built on the Oracle database. What they want is they said, "Give me the lowest ASP to get predictable performance IaaS" I'll run my app's tier on this. Number two, give me a platform service for database 'cause frankly, I don't really want to run your database, like, with all the manual effort, I want someone to automate, patching, scale up and down, and all these types of features like the pilot should have given us. And then number three, I do want SaaS over time. So we spend a lot of time with our customers, really saying, "how do I take this traditional application, run it on IaaS and PaaS?" And then number two, "let's modernize it at scale." Maybe I want to start peeling off functionality and running them as cloud native services right alongside, right? That's something again, that we're doing at scale, and other people are having a hard time running these traditional workloads on prem in the cloud. The second part is they say, "You know, I've got this legacy traditional ERP. Been servicing we well or maybe a supply chain system. Ultimately I want to get out of this. How do I get to SaaS?" And we say, "Okay, here's the way to do this. First, bring into the cloud, run it on IaaS and PaaS. And then selectively, I call it cloud slicing. Take a piece of functionality and put it into SaaS." For ERP, it might be something like start with GL, a new chart of accounts in ERP SaaS. And then slowly over a number of your journey as needed, adopt the next module. So this way, I mean, I'll just say this is the fun part of as an architect, our jobs, we're helping customers move to the cloud at scale, we're helping them do it at their rate, with whatever level of change they want. And when they're ready for SaaS, we're ready for them. And I would just say the other IaaS providers, here's the challenge we're seeing Dave, is that they're getting to the cloud, they're doing a little bit of modernization, but they want PaaS, they also want to ultimately get to SaaS, and frankly, those other clouds don't offer them. So they're kind of in this we're stuck on this lift and shift. But then we want to really move and modernize and go to SaaS. And I would say that's what Oracle is doing right now for enterprises. We're really helping them move these traditional workloads to the cloud IaaS and PaaS. And then number two, they're moving to SaaS when they're ready. And even when you get to SaaS, everyone says, "You know what, leave it as as vanilla as possible, but I want to make myself differentiated." In that case, again, IaaS and PaaS, coupled alongside a SaaS environment, you can build your specific differentiation. And then you leave the ERP pristine, so it can be upgraded constantly with no impact to your specific sidebar applications. So, I would say that the best clouds in the world, I mean, I think you're going to see a lot of the others are trying to, either SaaS providers trying to grow a PaaS, or maybe some of the IaaS players are trying to add SaaS. So, I think you're going to see this blending more and more because customers are asking for the flexibility For either or all three. But I will say that-- >> How can I get PaaS and SaaS-minus. >> Absolutely, I mean, what are you doing there? You're offering choice. There's not a question in my mind that Cisco is a huge customer of ours, they have a product that is one of their SaaS applications running Tetration on the Oracle Cloud. It actually doesn't run any Oracle. It's all cloud native applications. Natively built with a number of open source components. They run just IaaS. That's it, the Tetration product, and it runs fast. The Gen 2 cloud has a great architecture underneath it, flattened fast network. By far, for us, we feel like we really gotten into the guts of IaaS and made it run more efficiently. Other customers say, "I've got a huge Oracle footprint in the data center, help me get it out." So up to the cloud that they go, and they say I don't want just IaaS because that means I'm writing all the automation, like I have to manage all the patching. And this is where for us platform services really help because we give them the automation at scale, which allows their people to do other things, that may be more impactful for the business. >> I want to ask you about, the automation piece. And you guys have made the statement that your Gen 2 cloud is fundamentally different than how other clouds work, Gen 1 clouds. And the Gen 1 clouds which are evolving, the hyper scalars are evolving, but how is Oracle's Gen 2 cloud fundamentally different? >> Yeah. I think that one of the most basic elements of the cloud itself was that for us, we had to start with the security and the network. So if you imagine that those two components really, A, could dictate speed and performance, plus doing it in a secure fashion. The two things that you'll see an awful lot about for us, is that we've embedded not only security at every level. But we've even separated off what we call, every cloud, you have a number of compute instances and then you have storage, right? In the middle, you have a network. However, to become a cloud, and to offer the elastic scale and the multiple sharing of resources, you have to have something called a control plane. What we've done is we've actually extracted the control plane out into its own separate instance of a running machine. Other clouds actually have the control plane inside of there running compute cores. Now, what does that do? Well, the fact of the matter is, we assume that the control plane and the network should be completely separate from what you run on your cloud. So if you run a virtual machine, or if you run a bare metal instance, there's no Oracle software running on it. We actually don't trust customers, and we actually tell the customers don't trust us, either. So by separating out the control plane, and all the code that runs that environment off of the running machine, you get more cores meaning like you have-- There's no Oracle tax for running this environment. It's a separate conmputer for each one, the control plane. Number two, it's more secure. We actually don't have any running code on that machine, if you had a bare metal instance. So therefore, there's no way for one machine in the cloud to infect another machine if the control plane was compromised. The second part of the network, the guys who have been building this cloud, Don Johnson, a lot of the guys came from other clouds before and they said, "yYou know the one thing we have to do is make a we call it Flattened Fast Clause Network that really is never oversubscribed." So you'll constantly see and people always ask me same question, "Dave, why is the performance faster if its the same VM shape? "Like I don't understand why it's going faster, like high performance computing." And the reason again a lot of times is the network itself is that it's just not oversubscribed. It's constantly flowing all the data, there's no such thing as congestion on the network, which can happen. The last part, we actually added 52 terabytes of local storage to every one of those compute nodes. So therefore, there's a possibility you don't even have to traverse the network to do some really serious work on the local machine. So you add these together, the idea is make the network incredibly fast, separate out the control plane and run the software and security layer separate from the entire node where all the customers work is being done. Number three, give the customers more compute, by obviously having us offload it to a separate machine. And the last thing is put local storage and everything is what's called NVMe storage. Whether it's local or remote, everything's NVMe, though the IOPS we get are really off the charts. And again, it shows up in our benchmarks. >> Yeah, so you're getting, atomic access to memory. But in your control plane, you describe that control plane that's running. Sorry to geek out everybody. But I'm kind of curious, you know. You got me started, Chris. So that's control-- >> Yeah, that's good. >> the Oracle cloud or runs. Where's it live? >> It's essentially separated from the compute node. We actually have it in between, there's a compute node that all the work is done from the customer, could be on like a Kubernetes container or VM, whatever it might be. The control plane literally is separate. And it lives right next to the actual compute node the customer is using. So it's actually embedded on a SmartNIC, it's a completely different cores. It's a different chipset, different memory structure, everything. And it does two things. It helps us control what happens up in the customers compute nodes in VMs. And it also helps us virtualize the network down as well. So it literally, the control plane is separate and distinct. It's essentially a couple SmartNICS. >> And then how does Autonomous fit into this whole architecture? I'm speaking by the way for that description, I mean, it's nuanced, but it's important. I'm sure you having this conversation with a lot of cloud architects and chief technologists, they want to know this stuff, and they want to know how it works. And then, obviously, we'll talk about what the business impact is. But talk about Autonomous and where that fit. >> Yeah, so as Larry says that there are two products that really dictate the future of Oracle and our success with our customers. Number one is ERP-SaaS. The second one is Autonomous Database. So the Autonomous Database, what we've done is really taken a look at all the runtime operations of an Oracle database. So tuning, patching, securing all these different features, and what we've done is taken the best of the Oracle database, the best of something called Exadata which we run on the cloud, which really helps a lot of our customers. And then we've wrapped it with a set of automation and security tools to help it really manage itself, tune itself, patch itself, scale up and down, independent between compute and storage. So, why that's important though, is that really our goal is to help people run the Oracle database as they have for years but with far less effort, and then even not only far less effort, hopefully, a machine plus man, out of the equation we always talk about is man plus machine is greater than man alone. So being assisted by artificial intelligence and machine learning to perform those database operations, we should provide a better service to our customers with far less costs. >> Yeah, the greatest chess player in the world is a combination of man and machine, you know that? >> You know what? It makes sense. It makes sense because, there's a number of things that we can do as humans that are just too difficult to program. And then there are other things where machines are just phenomenal, right? I mean, there's no-- Think of Google Maps, you ask it wherever you want to go. And it'll tell you in a fraction of a second, not only the best route, but based on traffic from maybe the last couple of years. right now, we don't have autonomous cars, right, that are allowed to at least drive fully autonomous yet, it's coming. But in the meantime, a human could really work through a lot of different scenarios it was hard to find a way to do that in autonomous driving. So I do believe that it's going to be a great combination. Our hope and goal is that the people who have been running Oracle databases, how can we help them do it with far less effort and maybe spend more time on what the data can do for the organization, right? Improve customer experience, etc. Versus maybe like, how do I spin up a table? One of our customers is a huge consumer. They said, "our goal is how do we reduce the time to first table?" Meaning someone in the business just came up with an idea? How do I reduce the time to first table. For some of our customers, it can take months. I mean, if you were going to put in a new server, find a place in the data center, stand up a database, make the security controls, right and etc. With the autonomous database, I could spin one up right here, for us and, and we could start using it and it would be secure, which is utmost and paramount. It would scale up and down, meaning like just based on workload, as I load data into it, it would tune itself, it would help us with the idea of running more efficiently, which means less cores, which means also less cost. And then the constant security patches that may come up because of different threats or new features. It would do that potentially on its own if you allow it. Obviously some people want to watch you know what exactly it's going to do first. Do regression testing. But it's an exciting product because I've been working with the Oracle database for about 20 years now. And to see it run in this manner, it's just phenomenal. And I think that's the thing, a lot of the database teams have seen. Pretty amazing work. >> So I love this conversation. It's hardcore computer science, architecture, engineering. But now let's end with by up leveling this. We've been talking, a lot about Oracle Consulting. So let's talk about the business impact. So you go into customers, you talk to the cloud architects, the chief technologist, you pass that test. Now you got to deliver the business impact. Where does Oracle consulting fit with regard to that, and maybe you could talk about sort of where you guys want to take this thing. >> Yeah, absolutely. I mean, so, the cloud is great set of technologies, but where Oracle consulting is really helping us deliver is in the outcome. One of the things I think that's been fantastic working with the Oracle consulting team is that cloud is new. For a lot of customers who've been running these environments for a number of years, there's always some fear and a little bit of trepidation saying, "How do I learn this new cloud?" I mean, the workloads, we're talking about deeper, like tier zero, tier one, tier two, and all the way up to Dev and Test and DR, Oracle Consulting does really, a couple of things in particular, number one, they start with the end in mind. And number two, that they start to do is they really help implement these systems. And, there's a lot of different assurances that we have that we're going to get it done on time, and better be under budget, 'cause ultimately, again, that's something that's really paramount for us. And then the third part of it a lot of it a lot of times is run books, right? We actually don't want to just live at our customers environments. We want to help them understand how to run this new system. So training and change management. A lot of times Oracle Consulting is helping with run books. We usually will, after doing it the first time, we'll sit back and let the customer do it the next few times, and essentially help them through the process. And our goal at that point is to leave, only if the customer wants us to but ultimately, our goal is to implement it, get it to go live on time, and then help the customer learn this journey to the cloud. And without them, frankly, I think these systems are sometimes too complex and difficult to do on your own, maybe the first time especially because like I say, they're closing the books, they might be running your entire supply chain. They run your entire HR system or whatever they might be. Too important to leave to chance. So they really help us with helping the customer become live and become very competent and skilled, because they can do it themselves. >> But Chris, we've covered the gamut. We're talking about, architecture, went to NVMe. We're talking about the business impact, all of your automation, run books, loved it. Loved the conversation, but to leave it right there but thanks so much for coming on theCUBE and sharing your insights, great stuff. >> Absolutely, thanks Dave, and thank you for having me on. >> All right, you're welcome. And thank you for watching everybody. This is Dave Vellante for theCUBE. We are covering the Oracle North America Consulting transformation and its rebirth in this digital event. Keep it right there. We'll be right back. (upbeat music)

>>Yeah, yeah, yeah! >>Everybody, welcome back to the special digital presentation where we are tracking the transformation of Oracle consulting. And really, it's rebirth. Aaron Millstone is back. He's the senior vice president of consulting, joined by Jeff Davis. Who's ah, principal at Deloitte. He's the chief commercial officer for Oracle at Deloitte. Gentlemen, good to see you. Welcome. >>Thank you very much. >>Thanks for having me back. >>You're welcome, guys. Jeff, let me start with you. I've got the obvious question is why would Deloitte World Class? Yes, I well known why you partnering with Oracle Consultant? >>We're really It was a perfect match. The fact that we were looking to grow our oracle practice and really new and innovative ways around Oracle's cloud technology. Uh, in discussions with the oil, coal and specifically with Aaron Millstone, we discovered that we really had complementary capabilities and very little overlapping capabilities. So it was natural for us to find a way to work together. And specifically we found that there were strategic assets we had and there were tactical assets that Oracle had the mixture of two made a really unique and compelling value proposition for the customer base >>and Aaron. I mean, we've talked about the shift from from staff augmentation to much more strategic partnering with your customers. But you're not trying to compete with the big size of there's, there's it sounds like there's not a lot of overlap there. Where do you pick up and leave off for Deloitte? You describe that? >>Sure. I mean, we're You're right, right? We're not. We're not ever going to try to compete with the Deloitte. It's not our that's not in our DNA. It's not our intention. We exist to drive Oracle's to drive success for our customers on Oracle's cloud. That's that's our mantra. That's what we focus in on. So for us, right, we're deep technologists. We're We understand our cloud. We understand how cloud works within our various product suites that we migrate to the cloud. We understand how to manage it. We understand how to build paths extensions to it, but we don't have big program management. We don't understand non oracle components that well, you know, we've got some expertise here and there. But if we need to expand, you know, on Oracle solution to coexist with a Microsoft azure solution, we can't do that without going to a partner and as we bigger and the transformation that they're gonna have to change management and big, big transformation journey capabilities. Like again, That's not That's not expertise. >>Yeah, so Jeff will come back to you. So we see a lot of these deals. Sometimes we call them Barney deals. I love you. You love me. There's a press release, and that's it. But so one of the things we look for okay is their teeth behind this. You guys have come out with what you call elevate. What is elevate? How did it get started? And I have some follow up questions. >>Yeah, well, elevate really got started when Aaron and I started to look at the assets that each of the firms possessed on the Deloitte side, as Aaron suggested, We have deep capabilities and a broad range of technologies, some of them competing technologies with Oracle at the same time. Uh, we didn't have a great deal of depth in Oracle's technical products, Oracle Cloud Infrastructure and Oracle Autonomous. Our bench was not as big as Aaron's, and Aaron also had access to your local development at a level that we didn't have access to. So we really found ourselves in a situation where we could put those two capabilities together and we could offer something to our clients and a broad range of customers. Oracle customers in the field. They had access to all of the Lloyds capabilities, which includes great project management, great change management, real skill around the strategic aspects of cloud migration. And Aaron had tools on had resource is trained and developed around the late historical technology. They'd always be a step ahead of any s I So together we felt this was really a differentiation for marketplace, right, Erin? >>Yeah, absolutely right. And if I don't think I would add to it is that if you if you look at Deloitte approaches client conversation from, ah, business value perspective, you know, the work consulting teams tends to focus conversation. It tends to approach conversations with a focus on How do you want to do the technology? Um, both are helpful. But, you know, quite frankly, as we get into the bigger information in place, we need to lead with the Lloyd model of how do we How do we drive your business value and then begin from a technologist perspective, that's when we show up. So it really has been a very logical, very complimentary match. >>So you and I have talked about, you know, data centers and building data centers and investing. It's not just it's just not a good use of capital today. There's so many other things that organizations can do. You guys have identified data center. Consolidation is, is I'll call it Ah, you know, an initiative that you're seeing customers. I wonder if you could talk about that a little bit. Is that kind of a starting point for conversations? >>Yeah, well, it's definitely starting point, right? So we call it a referred to his infrastructure led transformation, Um, and appetite. The appetite for that is certainly high. We were seeing an increased focus on um, you know what customers need to do to take not just a workload here and there. But how do they get out of the data center business full? So it's a foregone conclusion, right? Like you just said, it's not. It's not really a question of should we invest in another data center? Where should we invest in up to in their data centers? The question has changed to Let's move the cloud. How do we get there and let's move in a big way? And that's why we're seeing that dialogue across all of our customers. And we find even for Oracle, it's been a learning for us, right? We started with on Oracle workload conversation, which is, Do you want to move this work? Work loads of oracle? But you want to move that Oracle workload works. And really, what we're finding is it's a wholesale transformation of everything in the data center, too. One or more clouds, right again, often often it's a multi cloud strategy, and that's okay. And we, you know, we were having more bigger conversations. The thing that has been really interesting is these conversations have evolved, and especially as we work with our partners at Deloitte, has been that, you know, we think that the combination of our our cloud technology, the consulting services that Oracle Consulting and Deloitte can bring to bear and then Oracle's ability to finance the whole deal makes the very compelling conversations for customers because you can walk in to a CEO to a CFO and say, Look on day one, you can actually have a lower spend that what you have today in your data center and get a cop transformation underway at the same time. >>So I want to come back to that business case and member Jeff, before we do, I want to ask you. So we heard Erin, you know, talking about the catalyst. You know, that sort of infrastructure transformation. But you're in the outcomes business, right in both. The bush has been deployed especially so So what is that North Star that you're seeing with customers? You know, it's not about the tech. They're not starting there. Um, that will often tell you that's kind of the easy part. But then we see tech coming and going, and it's the It's the business process. That's the people issues lining everybody. So what are you seeing is so the outcomes. What's that conversation like with your customers? >>Yeah, well, really, this conversation starts with business leadership. Um, if you think about it, there's a strong value proposition in infrastructure renewal. It's not at the top of mind, but once you start to understand the value that's created, it does raise two ah, high priority. Now, our experiences that virtually every board is looking for the C suite toe have a cloud strategy of some kind. People recognize the value of cloud in, uh in many of our clients and many of Oracle's customers, so the boards are pressing the C suite for a cloud strategy. Among those things are the value that cloud brings, including virtually unlimited scalability. Is is being tested real time now with a lot of current events. So when you see the scalability when you know you need a cloud strategy of some kind, your business advisors impressing you, the value proposition starts well, how do we get there? And what does it take to be successful? Our perspective is that it's it's fair to believe that the cloud will reduce infrastructure. Spend significantly. It's a great opportunity for consolidation. It also adds a layer of security, resiliency and scalability that you simply couldn't do on your own. So it addresses a lot of business needs Aziz well as a number of technical needs that need to be addressed. >>So let's talk a little bit more about that business cases that generally what you're seeing, where it starts is let's take some costs right out, and then Aaron, you and I talked about maybe investing that in the future of it. But is that really the starting point for the vast majority of customers? Let's let's let's cut some costs right away and get a payback immediately. >>So I'd like to share our perspective, which is, you know, nobody spends money for the sake of spending money on technology. It's got to have meaningful business value. So the conversation starts with really renewal and a path to the cloud. But there's a natural opportunity for savings in consolidation that we take advantage. We're not simply shifting from your hardware to the cloud we're actually modernizing, which will result in significant savings. But it also gives the business something that they don't have today at a level of security and scalability and ability to run a modern technology much faster, much better. Ah, and much more scalable. >>So a lot of people might again I go back to these deals. I think of this as a sales play. One of the things we look for is there. Is there any other integration? Are you doing co engineering in this case, maybe not, co engineering But are there tools that you're developing that you're taking to market, that you're actually leveraging? Eric, can you talk about that a little bit? Convinces. That's not just the sales play. >>Yeah, sure. And Jeff alluded to some of this earlier, too, right? So we definitely each had our respective tool. Angry Deloitte's investments in tools, what was built out of data that we have seen used quite a few times now we've been investing in something we call the Oracle soar. You know, our tools are, as you'd imagine, heavily Oracle focus. It's about moving Oracle technology to Oracle Cloud out of data and some of the tools that Deloitte's invested in our focus more comprehensively on holistically, looking at everything in a data center and everything that's across data centers and start to develop a set of facts around this stuff. But in both cases, we actually looked at these things and we said, You know what? If you combine these together, we get a very comprehensive view of what exactly it is, but we're looking at with a customer so we can tell everything from the types of traffic we see in the network to the specific versions of stuff you start to identify whether there's risk associated with having things, not aster on a supporter and get a very conference of you that's based on facts. And so, you know, we took those tools. We combined them together so that we can go into a customer and give a complete end and view from both on Oracle and Delight Perspective. And quite frankly, it doesn't matter whether the Lloyd leads or whether Oracle leads. We've developed these tools together. We're going to market together. And we've even got you know, the templates you'd expect consultancies tohave, right? So when you look at business cases, we've got joint business case templates that we've created together and that we're using actively with customers and therefore then we're refining them, improving them each time we do it. But, you know, we're at a point now where our tools are combined, templates are combined, and we even at this, you know, we're even Jeff in our poll earlier yesterday actually even got a joint Ah, war room that's constantly engaging with different account teams and making sure that we structurally approach things in a consistent way so that we're driving business value and using the tools appropriately. >>You know, I think, um, migration risk is probably one of the most significant factors in a business case. I mean, many don't understand it, but those in I t. And certainly hopefully in the executive office do you understand it? It sounds like that's a part of your tooling, anyway is designed to mitigate that's significant migration risk. When you talk about that a little bit, >>yeah, so we, you know, we approach migration from, you know, we start with the conversation. I'm almost always some type of log of what? The list of applications, what versions of things running they've been maintained by some might department somewhere, right? Or the collective? It's in varying degrees of accuracy is what we find. We don't rely on that. We go in and our our tools, our combined tooling across oracle, Deloitte interrogate the systems. We come back with actual information from the actual systems themselves. And then we started the plan. And so the funny thing is, with the migration, you know, probably 80% of the effort. 90% of the effort is in the planning stages and making sure that we understand exactly what we're moving exactly. When again, we're not. We're not dealing with the edge applications. Typically, we're dealing with the mission critical applications that are supporting the heart of a supply chain or a finance operation. And you can't. You just can't afford the down time that maybe you could afford on something that might be a consumer facing or a little less mission. Critical. So, yeah, we start finding very early and interrogate aggressively with actual data. >>Jeff, can you give us a sense as to how far you're into this elevate journey? May be thinking about a couple of customers either specifically or generically gonna where you're at with them. How far along? Maybe even some examples that you feel are representative. >>Sure. Um, you know, the the relationship has been probably about six Ah, close to seven months of maturity. In that time, we've had an opportunity to work on several key clients at scale. Uh, we've worked together in collaboration with one of the nation's largest retailers in the grocery business. We've worked collaboratively in aerospace and defense and also in the hospitality industry. In these cases, what we're finding and one is each one is in the various stage of maturity. One is done, one is in midstream on one is at the early stages and current economic conditions or driving a huge pipeline. Right now, I think our challenge right now is making sure that we identify those clients that can best take a value, take advantage of our services and our joint offering to deal with that pipeline. Right now, what we're finding is that the savings are at least as we projected. In some cases, we're finding even more. What people say they have and what people say they do isn't necessarily what you find when you get in there. But almost every case we're finding that there's unused equipment, unused capacity that they currently have redundancy, low utilization of their current assets. We can go a long way and streamlining that. Plus, I can't emphasize enough that ah, these days security is a major concern and we're adding a layer of security that they could never achieve themselves with soft. >>How do you guys on how the customers wanna approach the transaction? Is it a Bixby is a T and M. Is it a situation where you participate in some of the some of the savings of the game. How does the pricing work? >>So we have Go >>ahead. Um, I'll start off by saying each deal is really custom built around what a customer really needs, what they're trying to get out of it right now. As an example, Op X is very important. So we're engineering deals in a way that helps customers deal with their financial challenges, especially around op Ex. There are other structures that we can put in place. We have the backing of Oracle Finance, so we can be very innovative on deals they could be. When value was attained. They could be milestone based. There's just, uh, I think, a wide variety I don't want to say unlimited, but a wide variety of different options that we can offer our clients in order to be able to deal with whatever financial challenge or opportunity that may be looking at >>perfect, perfect. And you want >>to add to that >>and everything looking at other than you know, the there are. There are always things that are discovered during a personal project, and so, you know, we we also we do factor and things that allow some flexibility. Right? So even if we have a fixed price deal will include a bucket of ours to deal with, you know, unanticipated changes or even innovation. It doesn't have to be, You know, contingency could be Hey, we want to go out and spend and invest some money on artificial intelligence machine learning analytics over in this space since we've already moved these applications. All right, so we're approaching it again from a very flexible standpoint, and we're just point right. We can we can custom craft. Ah, deal to match what? The clients. Best business outcome. Okay. >>Yeah, that makes sense. That client might see some adjacent opportunity that they want to pursue, and they want that to be covered in the agreement I'm gonna end. Um, if you start with you, Aaron and then Jeff go to you. How? What do you guys see? A success? What does success look like? You know, when you were, you know, just less than a year in when you're 234 let's say five years and you look back, What does success look like? >>So, to me, successful success is gonna look like we've gotten a number of these big transformation deals in play. It's in motion, naturally between our organizations, not necessarily driven entirely by Jeff and I going out and driving the organization behave the right way. It's more in our DNA. But more importantly, I think we've gone into We've gone beyond the conversation of Let's Move workloads. We've gone into conversations off. Let's really talk about how to reimagine your business on top of Oracle's cloud and have an ongoing dialogue that looks at that transformation. Once we hit that 0.345 years from now, right, that will be a wild success, Jeff. >>But really, it's been around for 135 years. This is our birthday, uh, this year and in that time, what we've learned is there's no substitute for impact and value added to our clients. In our perspective, what this would success looks like his client success find success means improved scalability of their operations, uh, securing their technology and their data at a substantially lower cost, so that they can focus on what their core businesses and focus less on technology. That success to deploy >>right guys, thanks so much. Great session We're not only witnessing the rebirth of Oracle Consulting, but there's clearly a transformation going on. And it's cultural. Gentlemen, congratulations on your partnership. And thanks so much for coming on the Cube. >>Thank you so much >>for having us. >>You're welcome. Alright, Keep right there, everybody. We're back with our next guest covering Oracle Consulting North America. This is Dave Vellante with the Cube. Thanks for watching. >>Yeah, Yeah, yeah, yeah, yeah, >>yeah.

(upbeat music) >> Everybody, welcome to this special digital presentation where we're tracking the rebirth of Oracle Consulting. And my name is Dave Vellante, and we're here with Aaron Millstone who's the senior vice president of Oracle Consulting. Aaron, thanks for coming on, good to talk to you. >> Dave, appreciate you having me and I like the introduction of a rebirth of Oracle Consulting. >> Well, it really is I mean, you know, you guys have gone from staff augmentation to being much more of a strategic partner and we're going to talk about that. But I want to start with this theme that you have about empowering the autonomous enterprise. Sounds good, you know, nice little marketing tagline. But give us what's behind that, put some meat on the bone? >> Sure, so you know, what we define as autonomous enterprise is really using artificial intelligence, using machine learning and using it to cognitively understand your actual data and processes you're using for your enterprise. And then really embedding that into everything you're doing as a company, and using it to be both drive optimization and costs, and increasing revenue. And I know that's a lot of kind of consulting speak. So, we tend to think about what we've been talking about in terms of what we call tri-modal IT. This is probably the most exciting space that I've really thought through with my team, as we build up a new consulting business, you pull it out, but this is really about pivoting away from the systems of record and the systems of interaction, and really building up the systems of intelligence capabilities that we see all enterprises needing to invest in heavily, if they're not already investing there already. >> Well, I want to talk about a couple of things there. You know, one is that notion of lowering cost or increasing revenue and you're right people say, Oh, yeah, that's consultancy people, but a good consultant digs in and starts peeling the onion. Well, how do you actually make money? You know, where are the inefficiencies in your business? And that's really what you're talking about, and that's what every business wants to know, right? That's the end game, but the how to is really what separates the good consultants from the pack. >> Right right. And we're, you know, again, we're on this journey now, we've been, you mentioned it right. I'm two years into Oracle Consulting. Myself, I spent 23 plus years at Accenture, where I was a managing director with them and part of their North American leadership team. When I came over to Oracle consulting we did, we pivoted from what you called staff augmentation business to a basic set of offerings, which were things that you recognize right migration, services of workloads to cloud or integration or security work or even, step paths for SAS augmentation that we would do, but you know, pretty basic services. We're now pivoting again into sort of two areas infrastructure and transformation, which is really our bold costs take out play, as you just said, and sort of good consultants know how to do that. And really what that is, is we're going and looking at companies that still have traditional data centers, or maybe they've got some things on clouds, and something's still in traditional data centers. And we're coming in, and we're saying there's a business case here, that looks at your total cost of ownership. And we think we can take out between 40 and 65% of your run rate costs, and that's everything from, facilities, fire suppression systems, through to the actual compute cost, through to the labor that's required to do the physical hands on activities in the data center. So, we have that sort of capability and we're pushing customers hard in that space at the moment, and then driving that into a secondary conversation system and by the way, with all these savings, you kind of have to choices. You can pocket the savings, obviously or we would propose that you go into what we're calling the autonomous enterprise space, and really building up your artificial intelligence machine learning capability with centralized capabilities, centralized data, versus letting every line of business, every department do it on their own. >> Now, the other thing a good consultant does is they make the initiative self funding, and that's a win win you keep getting paid, the customer makes money, that's a good thing. But I like the idea, you're starting with the obvious business case of cost, and I think I heard you really attacking OPPEX, labor is obviously big component of that, but it's not just labor, and then you transition if they don't pocket the gain to a gain sharing going forward to look for new revenue. Did I get that I get that right? >> Yeah, you actually got that right. And actually, what I'll tell you too, is I think the labor piece, again, you know, I came from Accenture, Accenture is big outsourcing company, big technology consulting, big strategy consulting. You know, I went in for years and did pitches on outsourcing arrangements which were fundamentally lower cost bodies running in a more effective way. What we're finding or what I'm finding with customer conversations over the last two years at Oracle has been actually I think, data centers are not, there's nothing competitively advantageous about having a data center if you're a company, there is a lot of advantageous. There's an advantage to having cloud and what we're seeing is that companies that might have outsourced their data center are just the lowest cost provider are now considering insourcing or co-sourcing as they pivot the cloud. So the funny thing is actually labor savings is not the big driver of that 40 to 65%, that plays a role of course, that's how you get to the 65%. But even go into the 40% you can get there by insourcing your labor and bringing them in house and recognizing that the speed at which you can operate on your cloud gives you a competitive advantage. >> So this requires a whole new skill set for Oracle, you mentioned, you came in from Accenture where I talked to another number of other folks in Oracle's North America Consulting Operation that came from, brand name firms, we're going to be talking to Deloitte we have and will continue. So there I know, a big part of you talk about the skills transformation that you've affected inside of Oracle Consulting. >> Sure, yeah I mean, it started when I showed up. It was primarily a staff augmentation business in our commercial space in particular, you know, if you need a DBA, here's a DBA. If you need a SAS admin, here's a SAS admin. Here's the hourly rates and quite frankly, very, very talented group of people, very talented, but focused on doing, you know, sort of nuts and bolts level work, very deep work on the Oracle technology stack, but also weren't particularly cloud certified. So we started by focusing on getting the team certified in our cloud products, invested a ton of hours, thousands and thousands of hours in training. It takes you know, we're doing something like six months investment initially to get people up and certified on multiple cloud products that Oracle is selling. And then right from there, we started putting together our basic offerings, again moved from staff augmentation to saying, look, would you like to move a workload. To move a workload is going to cost a fixed price, whatever that is 100, $200,000 move away from rate card conversations with augmentation. And we shifted the commercial contracts that had payments based on outcomes so they don't move successfully, there's no payment. And so you know that was really the focus. >> I'm going to come back to this notion of gain sharing and particularly focus on the revenue side for a moment. You mentioned a what I'll call a buzzword tri-modal IT and a buzzword because Gartner kind of with bimodal IT popularized that concept. And I think part of the problem that people had with bimodal IT was kind of had the legacy systems of record and then you had all the new cool stuff, the big data and you know now AI and systems of engagement and so forth. And everybody wanted to go to the ladder and run away from the former. But now, if I understand tri-model IT, you're talking about bringing machine intelligence to both of those spheres such that people can stay current, stay relevant and add new value to their organization. >> Yeah, that's exactly it. And we're trying to bring it to both but we're trying to make it its own sphere, independent of the other two. So, again, as we looked at this consulting evolution, I didn't come over to Oracle and Oracle is not interested in us, creating a consulting business, that's a me too consulting business that kind of looks like whatever everyone else is doing. So the goal really was okay. So if we started with sort of staff augmentation, and you know, really Oracle's legacy, a system of record stuff, we sell big back office systems, we have mission critical databases. Like it's the clunky stuff that has to work, but really at the end of the day, that's our heritage, going over to the systems of interaction which is, where the bimodal IT really came in from Gartner. That's a pretty saturated place, so again, coming from the background, I had a consulting, I looked at all the eight design agencies that were out there that were all selling digital, and we looked at the digital sales tactics going on, we're like, well, that's pretty saturated, it's not really a smart place for us to go make a lot of headway into. And so we looked and said, well really, the next layer, the next evolution of IT is this third sphere systems of intelligence. And really, since Oracle is, our heritage is mission critical and data, fundamentally, the logical step for us was to go okay, systems intelligence are powered by data, and they serve artificial intelligence as the primary consumer. So again, our thought process was you have a system of record which is process centric and really geared towards the CFO or a head of HR, you have systems of interaction, which is really geared towards the users, it's trying to make business frictionless. Those users can be consumers, they can be employees, whomever. And then systems intelligence is around artificial intelligence is the primary consumer of it. I mean really pivoting to that, and then making that something that is pervasive and structurally place across both those other two spheres, really felt like where we should be differentiating. When I brought in the talent rate that we looked to bring in, we were getting kind of affirmation that, yeah, the best talent in the market was starting to see this trend and so we kind of knew we were onto something there. >> Yeah, I mean, that makes a lot of sense, because as you as you point out, some of those new workloads, many of them are very consumer oriented, that's kind of you know, not your wheelhouse. I mean, that's your customers are, selling to consumers, but Oracle's B2B, hardcore data mission critical. But let me ask you, to that make sets, but by your cloud, you were sort of a later entrant into cloud. So where does cloud fit into this? How do you respond to when customers say, yeah, but you know, you guys were late on the cloud. >> Yeah, we are definitely late coming to cloud, like there's no two ways about it. I mean, what we've got is we have what we call a Generation 2 Cloud. And I jokingly tell customers that we have a late mover advantage. And that late mover advantage basically means that we've looked at what the first generation clouds have done. And quite frankly, they're great at what they do, they're fierce competitors, they're tough to compete with, they've got a lot of mindshare, but they fundamentally were about targeting consumers, or targeting enterprise collaboration tools, so if you want cat videos, if you want to watch humorous videos that people filmed and posted on social media, those are great clouds for that stuff. But if you want really mission critical enterprise cloud workloads, that's where we come into play. And so when you start to look at really the key differentiators in our cloud and through out, at least this is how I describe it to customers. So, we look at sort of three layers, we have an autonomous capability both on our operating system and our database. What that basically means is that we have machine learning and artificial intelligence that's driving the key, administrative activities in our cloud, we then have our Exadata platform. So Exadata for us is a secret weapon, we think that it is a differentiator in our products. And so, Exadata for those watching that doesn't know what it is, so Exadata emerged out of the Sun acquisition that Oracle did. It is purpose built hardware that is engineered for our software products, specifically our databases. And now we've taken that concept and moved it into our cloud and so customers can come in and take very intensive enterprise, mission critical workloads, run them straight in our cloud. And then, when we look at the last point, it's probably security where, again, we have total segmentation of our security layers from the customer workloads. So again, we've taken the concepts that first generation cloud providers have implemented, and they've scaled it globally. So it's really tough for them to walk back on it, it's a huge investment and we're now gone into a Generation 2 Cloud and quite frankly, I think that's what this is the frontier that everyone's racing to kind of grab. >> You know, we actually in our community, talk to a lot of Exadata customers and they get very intense, they do some really hardcore things with with Exadata. To me, the key to your cloud strategy, and specifically Exadata is you've got the same exact infrastructure, control plane, data plane, software, either on prem or in the cloud. So that's your same same narrative. But the real key, new key anyway is what autonomous, tell me if you agree with this. What autonomous gives you a scale, because as you say, you're related to cloud, you're not a hyper scalar in that sense, you're not selling just, race to the bottom infrastructure as a service. You're bringing applications and mission critical applications, so eponymous gives you the ability to scale and compete more effectively with some of those other, earlier movers. You buy that? >> Yeah, absolutely. So scaling and scaling in terms of, what has been historically human activities, when I say human activities, we're not replacing the humans, we're making some of the human activities that were highly repetitive way more efficient. So easy example I can give you is patching. Like security(mumbles) bases are very time consuming, I've talked to customers as recently as a couple weeks ago, that are three years behind on their patching. And when I look at that, it's you're like, why wouldn't you consider autonomous, they have their board of directors and their auditors are actually now demanding that they do something different about their patching problems. And they're talking about, man months, people months of trying to roll out this patching, and they're worried about breaking stuff, and they're worried about human error. Like when you look at something like autonomous, that patching would take place, pretty much instantaneous with no downtime. And we've seen it in our own cloud and our own services internally and we're able to patch, thousands and thousands of cores very, very quickly. >> So we got to wrap but I wanted to close on sort of the, I mean, again, we talked about good consultants and good consultants have continuous improvement mindset. They got a North star that they really never get through and that keeps moving because you got to keep innovating, you got to keep disrupting yourself, so maybe you could end by sort of talking about some of the things you're watching, some of the milestones you want to hit and some of that transformation that you want to keep going. How are you going to achieve that? >> Yeah, and it will skip some of it, when we hit the Deloitte segment too, but like we're definitely we've moved from, we've definitely move from the staff augmentation to basic offerings. We're now beyond that we're starting to sell the infrastructure lead transformation plays. What's exciting to me about that with our customers is, you know, Oracle's a big complex enterprise, as you'd expect with a company that has a tremendous amount of technology. We're now bringing holistic approaches to our customer say, let us help you optimize everything end to end, let's look at your data center, let's not look at a narrow slice, let's not look at just SAS admins and DBAs, we're looking at things comprehensively. So moving there has been a pretty big milestone for us to hit, we've started to get some good momentum with our customers. Our next milestone is really going to be taking that autonomous enterprise and blowing it out. We're in use case and incubation period right now with that, but again we've got some, I would argue we have the best talent in the world right now that thinks about this stuff and not just thinks about it from a pure technology standpoint, but thinks about how to actually make it effective for the business. And so once we get some of those motions going, like the use case for the autonomous enterprise that's artificial intelligence driven, it should have a continuous pace of change, and it's going to start to evolve in areas that you know, quite frankly, we can't even predict yet. But we're excited to see where it leads. >> Alright, thanks for spending some time with us. I am very excited to talk about that sort of collision course between your deep tech capabilities as Oracle as a product company and this, the Global SI, Deloitte, we're going to bring in those guys in a moment. So thanks very much for taking us through the transformation and great job, good luck. >> Thank you, appreciate it. >> All right, and thank you, everybody for watching. Keep right there, we'll be back with more coverage of Oracle's transformation. Right after the short break, you're watching the CUBE. (upbeat music)

>>Yeah, yeah, >>yeah! >>Welcome back, everybody. To this special digital event coverage, the Cube is looking into the rebirth of Oracle Consulting. Janet George is here. She's group VP Autonomous for Advanced Analytics with machine learning and artificial intelligence at Oracle. And she's joined by Grant Gibson Group VP of growth and strategy at Oracle. Folks, welcome to the Cube. Thanks so much for coming on. Great. I want to start with you because you get strategy in your title like this. Start big picture. What is the strategy with Oracle specifically as it relates to autonomous and also consulting? >>Sure. So I think you know, Oracle has a deep legacy of strength and data and, uh uh, over the company's successful history. It's evolved what that is from steps along the way. And if you look at the modern enterprise Oracle client, I think there's no denying that we've entered the age of AI, that everyone knows that artificial intelligence and machine learning are a key to their success in the business marketplace going forward. And while generally it's acknowledged that it's a transformative technology and people know that they need to take advantage of it, it's the how that's really tricky and that most enterprises, in order to really get an enterprise level, are rely on AI investment. Need to engage in projects of significant scope, and going from realizing there's an opportunity of realizing there's a threat to mobilize yourself to capitalize on it is a daunting task or certainly one that's, you know, Anybody that's got any sort of legacy of success has built in processes as building systems has built in skill sets, and making that leap to be an autonomous enterprise is challenging for companies to wrap their heads around. So as part of the rebirth of Oracle Consulting, we've developed a practice around how to both manage the technology needs for that transformation as well as the human needs as well as the data science needs. >>So there's about five or six things that I want to follow up with you there. So this is a good conversation. Ever since I've been in the industry, we were talking about a sort of start stop start stop at the Ai Winter, and now it seems to be here is almost feel like the technology never lived up to its promise. If you didn't have the horsepower compute power data may be so we're here today. It feels like we are entering a new era. Why is that? And how will the technology perform this time? >>So for AI to perform it's very remind on the data we entered the age of Ai without having the right data for AI. So you can imagine that we just launched into Ai without our data being ready to be training sex for AI. So we started with B I data or we started the data that was already historically transformed. Formatted had logical structures, physical structures. This data was sort of trapped in many different tools. And then suddenly Ai comes along and we see Take this data, our historical data we haven't tested to see if this has labels in it. This has learning capability in it. Just trust the data to AI. And that's why we saw the initial wave of ai sort of failing because it was not ready to full ai ready for the generation of Ai, if you will. >>So, to me, this is I always say, this was the contribution that Hadoop left us, right? I mean, the dupe everybody was crazy. It turned into big data. Oracle was never that nuts about it is gonna watch, Setback and wash obviously participated, but it gathered all this data created Chief Data Lakes, which people always joke turns into data swamps. But the data is often times now within organizations least present. Now it's a matter of what? What what's The next step is >>basically about Hadoop did to the world of data. Was her dupe freed data from being stuck in tools it basically brought forth. This concept of a platform and platform is very essential because as we enter the age of AI and be entered, the better wide range of data. We can't have tools handling all of the state of the data needs to scale. The data needs to move, the data needs to grow. And so we need the concept of platforms so we can be elastic for the growth of the data, right, it can be distributed. It can grow based on the growth of the data, and it can learn from that data. So that is that's the reason why Hadoop sort of brought us into the platform board, >>right? A lot of that data ended up in the cloud. I always say, You know, for years we marched to the cadence of Moore's law. That was the innovation engine in this industry and fastest, you could get a chip in, you know, you get a little advantage, and then somebody would leapfrog. Today it's got all this data you apply machine intelligence and cloud gives you scale. It gives you agility of your customers. Are they taking advantage of the new innovation cocktail? First of all, do you buy that? How do you see them taking >>advantage of? Yeah, I think part of what James mentioned makes a lot of sense is that at the beginning, when you know you're taking the existing data in an enterprise and trying to do AI to it, you often get things that look a lot like what you already knew because you're dealing with your existing data set in your existing expertise. And part of I think the leap that clients are finding success with now is getting novel data types, and you're moving from, uh, zeros and ones of structured data, too. Image language, written language, spoken language. You're capturing different data sets in ways that prior tools never could. And so the classifications that come out of it, the insights that come out of it, the business process transformation comes out of it is different than what we would have understood under the structure data format. So I think it's that combination of really being able to push massive amounts of data through a cloud product to be able to process it at scale. That is what I think is the combination that takes it to the next plateau for sure. >>So you talked about sort of. We're entering a new era Age of a AI. You know, a lot of people, you know, kind of focus on the cloud is the current era, but it really does feel like we're moving beyond that. The language that we use today, I feel like it's going to change, and you just started to touch on some of it. Sensing, you know, there are senses and you know the visualization in the the auditory. So it's It's sort of this new experience that customers are seeing a lot of this machine intelligence behind. >>I call it the autonomous and a price right. The journey to be the autonomous enterprise. And then you're on this journey to be the autonomous enterprise you need. Really? The platform that can help you be cloud is that platform which can help you get to the autonomous journey. But the autonomous journey does not end with the cloud or doesn't end with the data lake. These are just infrastructures that are basic necessary necessities for being on that on that autonomous journey. But at the end, it's about how do you train and scale at, um, very large scale training that needs to happen on this platform for AI to be successful. And if you are an autonomous and price, then you have really figured out how to tap into AI and machine learning in a way that nobody else has to derive business value, if you will. So you've got the platform, you've got the data, and now you're actually tapping into the autonomous components ai and machine learning to derive business, intelligence and business value. >>So I want to get into a little bit of Oracle's role. But to do that I want to talk a little bit more about the industry. So if you think about the way that the industry seems to be restructuring around data. Historically, industries had their own stack value chain, and if you were in in in the finance industry, you were there for life. We had your own sales channel distribution, etcetera. But today you see companies traversing industries, which has never happened before. You know, you see apple getting into content and music, and there's so many examples are buying whole foods data is sort of the enabler. There you have a lot of organizations, your customers, that are incumbents that they don't wanna get disrupted your part big party roles to help them become that autonomous and press so they don't get disrupted. I wonder if you could maybe maybe comment on How are you doing? >>Yeah, I'll comment and then grant you China, you know. So when you think about banking, for example, highly regulated industry think about RG culture. These are highly regulated industries there. It was very difficult to destruct these industries. But now you look at an Amazon, right? And what is an Amazon or any other tech giants like Apple have? They have incredible amounts of data. They understand how people use for how they want to do banking. And so they've come up with Apple cash or Amazon pay, and these things are starting to eat into the market, right? So you would have never thought and Amazon could be a competition to a banking industry just because of regulations. But they're not hindered by the regulations because they're starting at a different level. And so they become an instant threat in an instant destructive to these highly regulated industries. That's what data does, right when you use data as your DNA for your business and you are sort of born in data or you figured out how to be autonomous. If you will capture value from that data in a very significant manner, then you can get into industries that are not traditionally your own industry. It can be like the food industry can be the cloud industry, the book industry, you know, different industries. So you know that that's what I see happening with the tech giants. >>So great, there's a really interesting point that the Gina is making that you mentioned. You started off with a couple of industries that are highly regulated, the harder to disrupt use, it got disrupted, publishing got disrupted. But you've got these regulated businesses. Defense or automotive actually hasn't been truly disrupted yet. Some Tesla, maybe a harbinger. And so you've got this spectrum of disruption. But is anybody safe from disruption? >>Kind of. I don't think anyone's ever say from it. It's It's changing evolution, right? That you whether it's, you know, swapping horseshoes for cars are TV for movies or Netflix are any sort of evolution of a business You're I wouldn't coast on any of them. And I think to the earlier question around the value that we can help bring the Oracle customers is that you know, we have a rich stack of applications, and I find that the space between the applications, the data that that spans more than one of them is a ripe playground for innovations that where the data already exists inside a company. But it's trapped from both a technology and a business perspective. Uh, and that's where I think really any company can take advantage of knowing it's data better and changing itself to take advantage of what's already there. >>Yet powerful people always throw the bromide out. The data is the new oil, and we've said. No data is far more valuable because you can use it in a lot of different places. Oil you can use once and it's follow the laws of scarcity data if you can unlock it. And so a lot of the incumbents they have built a business around, whatever a factory or a process and people, a lot of the trillion are starting us that have become billionaires. You know, I'm talking about Data's at the core. They're data companies. So So it seems like a big challenge for your incumbent customers. Clients is to put data at the core, be able to break down those silos. How do they do that? >>Grading down silos is really super critical for any business. It was okay to operate in a silo, for example. You would think that, Oh, you know, I could just be payroll and expense reports and it wouldn't matter matter if I get into vendor performance management or purchasing that can operate as a silo. But any movie of finding that there are tremendous insights between vendor performance management I expensive for these things are all connected, so you can't afford to have your data sits in silos. So grading down that silo actually gives the business very good performance, right? Insights that they didn't have before. So that's one way to go. But but another phenomena happens when you start to great down the silos, you start to recognize what data you don't have to take your business to the next level, right. That awareness will not happen when you're working with existing data so that a Venice comes into form when you great the silos and you start to figure out you need to go after a different set of data to get you to a new product creation. What would that look like? New test insights or new cap ex avoidance that that data is just you have to go through the iteration to be able to figure that out. >>It becomes it becomes a business problem, right? If you got a process now where you can identify 75% of the failures and you know the value of the other 25% of failures, that becomes a simple investment. How much money am I willing to invest to knock down some portion that 25% and it changes it from simply an I t problem or expense management problem to you know, the cash problem. >>But you still need a platform that has AP eyes that allows you to bring in those data sets that you don't have access to this enable an enabler. It's not the answer. It's not the outcome in and of itself, but it enables. And >>I always say, you can't have the best toilet if you're coming, doesn't work. You know what I mean? So you have to have your plumbing. Your plumbing has to be more modern. So you have to bring in modern infrastructure distributed computing that that you cannot. There's no compromise there, right? You have to have the right equal system for you to be able to be technologically advanced on a leader in that >>table. Stakes is what you're saying. And so this notion of the autonomous enterprise I would help me here cause I get kind of autonomous and automation coming into I t I t ops. I'm interested in how you see customers taking that beyond the technology organization into the enterprise. >>Yeah, this is this is such a great question, right? This is what I've been talking about all morning. Um, I think when AI is a technology problem, the company is that at a loss AI has to be a business problem. AI has to inform the business strategy. AI has to been companies. The successful companies that have done so. 90% of my investments are going towards state. We know that and most of it going towards AI. There's data out there about this, right? And so we look at what are these? 90 90% of the company's investments. Where are these going and whose doing this right? Who's not doing this right? One of the things we're seeing as results is that the companies that are doing it right have brought data into their business strategy. They've changed their business model, right? So it's not like making a better taxi, but coming up with a bow, right? So it's not like saying Okay, I'm going to have all these. I'm going to be the drug manufacturing company. I'm gonna put drugs out there in the market forces. I'm going to do connected help, right? And so how does data serve the business model of being connected? Help rather than being a drug company selling drugs to my customers, right? It's a completely different way of looking at it. And so now you guys informing drug discovery is not helping you just put more drugs to the market. Rather, it's helping you come up with new drugs that would help the process of connected games. There's a >>lot of discussion in the press about, you know, the ethics of AI, and how far should we take? A far. Can we take it from a technology standpoint, Long road map there? But how far should we take it? Do you feel as though of public policy will take care of that? A lot of that narrative is just kind of journalists looking for, You know, the negative story. Well, that's sort itself out. How much time do you spend with your customers talking about that and is what's Oracle's role there? I mean, Facebook says, Hey, the government should figure this out. What's your point? >>I think everybody has a role. It's a joint role, and none of us could give up our responsibilities as data scientists. We have heavy responsibility in this area on. We have heavy responsibility to advise the clients on the state area. Also, the data we come from the past has to change. That is inherently biased, right? And we tend to put data signs on biased data with the one dimensional view of the data. So we have to start looking at multiple dimensions of the data. It's got to start examining. I call it a responsible AI when you just simply take one variable or start to do machine learning with that because that's not that's not right. You have to examine the data. You got to understand how much biases in the data are you training a machine learning model with the bias? Is there diversity in the models? Is their diversity in the data? These are conversations we need to have. And we absolutely need policy around this because unless our lawmakers start to understand that we need the source of the data to change. And if we look at this, if we look at the source of the data and the source of the data is inherently biased or the source of the data has only a single representation, we're never going to change that downstream. AI is not going to help us. There so that has to change upstream. That's where the policy makers come into into play. The lawmakers come into play, but at the same time as we're building models, I think we have a responsibility to say can be triangle can be built with multiple models. Can we look at the results of these models? How are these feature's ranked? Are they ranked based on biases, sex, HP II, information? Are we taking the P I information out? Are we really looking at one variable? Somebody fell to pay their bill, but they just felt they they build because they were late, right? Voices that they don't have a bank account and be classified. Them is poor and having no bank account, you know what I mean? So all of this becomes part of response >>that humans are inherently biased, and so humans or building algorithms right there. So you say that through iteration, we can stamp out, the buyers >>can stamp out, or we can confront the bias. >>Let's make it transparent, >>make transparent. So I think that even if we can have the trust to be able to have the discussion on, is this data the right data that we're doing the analysis on On start the conversation day, we start to see the change. >>We'll wait so we could make it transparent. And I'm thinking a lot of AI is black box. Is that a problem? Is the black box you know, syndrome an issue or we actually >>is not a black box. We in Oracle, we're building our data science platform with an explicit feature called Explained Ability. Off the model on how the model came up with the features what features they picked. We can rearrange the features that the model picked, citing Explain ability is very important for ordinary people. Trust ai because we can't trust even even they designed This contrast ai right to a large extent. So for us to get to that level, where we can really trust what ai speaking in terms of a modern, we need to have explain ability. And I think a lot of the companies right now are starting to make that as part of their platform. >>So that's your promise. Toe clients is that your AI will be a that's not everybody's promised. I mean, there's a lot of black box and, you know, >>there is, if you go to open source and you start downloading, you'll get a lot of black boss. The other advantage to open source is sometimes you can just modify the black box. You know they can give you access, and you could modify the black box. But if you get companies that have released to open, source it somewhat of a black box, so you have to figure out the balance between you. Don't really worry too much about the black box. If you can see that the model has done a pretty good job as compared to other models, right if I take if I triangulate the results off the algorithm and the triangulation turns out to be reasonable, the accuracy on our values and the Matrix is show reasonable results. Then I don't really have to brief one model is to bias compared to another moderate. But I worry if if there's only one dimension to it. >>Well, ultimately much too much of the data scientists to make dismay, somebody in the business side is going to ask about cause I think this is what the model says. Why is it saying that? And you know, ethical reasons aside, you're gonna want to understand why the predictions are what they are, and certainly as you're going to examine those things as you look at the factors that are causing the predictions on the outcomes, I think there's any sort of business should be asking those responsibility questions of everything they do, ai included, for sure. >>So we're entering a new era. We kind of all agree on that. So I want to just throw a few questions out, have a little fun here, so feel free to answer in any order. So when do you think machines will be able to make better diagnoses than doctors? >>I think they already are making better diagnosis. And there's so much that I found out recently that most of the very complicated cancel surgeries are done by machines doctors to standing by and making sure that the machines are doing it well, right? And so I think the machines are taking over in some aspects. I wouldn't say all aspects. And then there's the bedside manners. You really need the human doctor and you need the comfort of talking to >>a CIO inside man. Okay, when >>do you >>think that driving and owning your own vehicle is going to be the exception rather than the rule >>that I think it's so far ahead. It's going to be very, very near future, you know, because if you've ever driven in an autonomous car, you'll find that after your initial reservations, you're going to feel a lot more safer in an autonomous car because it's it's got a vision that humans don't. It's got a communication mechanism that humans don't right. It's talking to all the fleets of cars. Richardson Sense of data. It's got a richer sense of vision. It's got a richer sense of ability to react when a kid jumps in front of the car where a human will be terrified, not able to make quick decisions, the car can right. But at the same time we're going to have we're gonna have some startup problems, right? We're going to see a I miss file in certain areas, and junk insurance companies are getting gearing themselves up for that because that's just but the data is showing us that we will have tremendously decreased death rates, right? That's a pretty good start to have AI driving up costs right >>believer. Well, as you're right, there's going to be some startup issues because this car, the vehicle has to decide. Teoh kill the person who jumped in front of me. Or do I kill the driver killing? It's overstating, but those are some of the stories >>and humans you don't. You don't question the judgment system for that. >>There's no you person >>that developed right. It's treated as a one off. But I think if you look back, you look back five years where we're way. You figure the pace of innovation and the speed and the gaps that we're closing now, where we're gonna be in five years, you have to figure it's I mean, I don't I have an eight year old son. My question. If he's ever gonna drive a car, yeah, >>How about retail? Do you think retail stores largely will disappear? >>I think retail. Will there be a customer service element to retail? But it will evolve from where it's at in a very, very high stakes, right, because now, with our if I did, you know we used to be invisible as we want. We still aren't invisible as you walk into a retail store, right, Even if you spend a lot of money in in retail. And you know now with buying patterns and knowing who the customer is and your profile is out there on the Web, you know, just getting a sense of who this person is, what their intent is walking into the store and doing doing responsible ai like bringing value to that intent right, not responsible. That will gain the trust. And as people gain the trust and then verify these, you're in the location. You're nearby. You normally by the sword suits on sale, you know, bring it all together. So I think there's a lot of connective tissue work that needs to happen. But that's all coming. It's coming together, >>not the value and what the what? The proposition of the customers. If it's simply there as a place where you go and buy, pick up something, you already know what you're going to get. That story doesn't add value. But if there's something in the human expertise and the shared felt, that experience of being in the store, that's that's where you'll see retailers differentiate themselves. I >>like, yeah, yeah, yeah, >>you mentioned Apple pay before you think traditional banks will lose control of payment systems, >>They're already losing control of payment systems, right? I mean, if you look at there was no reason for the banks to create Siri like assistance. They're all over right now, right? And we started with Alexa first. So you can see the banks are trying to be a lot more customized customer service, trying to be personalized, trying to really make it connect to them in a way that you have not connected to the bank before. The way we connected to the bank is you know, you knew the person at the bank for 20 years or since when you had your first bank account, right? That's how you connect with the banks. And then you go to a different branch, and then all of a sudden you're invisible, right? Nobody knows you. Nobody knows that you were 20 years with the bank. That's changing, right? They're keeping track of which location you're going to and trying to be a more personalized. So I think ai is is a forcing function in some ways to provide more value. If anything, >>we're definitely entering a new era. The age of of AI of the autonomous enterprise folks, thanks very much for great segment. Really appreciate it. >>Yeah. Pleasure. Thank you for having us. >>All right. And thank you and keep it right there. We'll be back with our next guest right after this short break. You're watching the Cube's coverage of the rebirth of Oracle consulting right back. Yeah, yeah, yeah, yeah.

(upbeat music) >> >> Welcome back everybody to this special presentation of theCUBE where we're covering the rebirth of Oracle Consulting. It's a digital event, where we're going out, we're extracting the signal from the noise. We happen today to be in Chicago, which is obviously the center of the country, a lot of big customers here, a lot of consultants and consulting organizations here, a lot of expertise. Mike Owens is here. He is the group VP for Cloud Advisory and the General Manager of Oracle Elevate. Mike, thanks for coming on theCUBE. >> I appreciate it. Glad to be here. >> So I'm got to ask you, elevate, in your title, what is Oracle Elevate? >> Yeah, Oracle Elevate was actually announced Oracle OpenWorld last year. And it's the partnership that we really had to actually take our scale to the next level. So we actually did it with Deloitte Consulting. So the goal is to actually take the capabilities of both organizations. Deloitte really has functional capabilities and expertise, with an Oracle practice and obviously Oracle has, Oracle technical expertise. The combination the two really allows us to scale, provide sort of what I call the one plus one equals three, effort for customers. >> Now you've got a decent timeline or observation over the past several years. I think you joined three years ago, you were at some brand name companies. First of all, what attracted you to come to Oracle Consulting? >> Yeah, absolutely. So Oracle was in the point where they were doing a lot of stuff around on-prem, on-premise software, right? The old ERP type stuff, they were doing cloud, they sort of had to had this sort of transformational moment. I was asked to come in Oracle Consulting in the early days and say, "Hey, look, "we're trying to transform the organization "from on-prem consulting over to cloud consulting. "Come in and help us with this stuff "that you've worked from your prior two cloud companies, "and help us really move the organization forward "and look at things differently." So it's definitely been a journey over the last three years. I've taken it from nearly 85% of the 90% of our revenue around on-prem type of engagements, to now actually splitting the organization, being dedicated 100% on cloud, which is the huge transformation in the last three years. >> Yeah and so of course Oracle is a product company and your then CTO, Larry Ellison said, "We're going cloud first." And that happened during your tenure. You came in, I believe prior to that. What kind of effect did that have on the organization? I mean, we know from a product standpoint, but just culturally and just the mindset. >> Yeah, absolutely. It had a huge effect on the organization. They started splitting the organization to actually have be dedicated organizations, whether it's sales on product, whether it's support for product, pre sales support or our engineering and solutions architecture, and our consulting. So we've now split the organizations to primarily support those different lines of business, and what that allows us to do is actually focus that and put a lot of the stuff on cloud and moving the company a cloud first at this point. We still have a lot of organizations that do either on-prem type of work and things like that, they can't move over, that's supported, but you're going to see a larger shift of the cloud first, right? To actually move our customers and our organizations and back to what you hear a bunch of our executives talk about. We also actually use our own capabilities as well too. Whether it's AI or machine learning and the way we actually use it in our own HR systems. If I do my expense reporting, there's actually an AI bot that I can actually put stuff in there and automatically pulls it in. We actually take those capabilities and consume them ourselves because we have to believe in what we actually create as well. >> Your definition of cloud, of course, is different from the hyperscale cloud providers would say, "Hey, our cloud is hyperscale. "Put it in our cloud. "On-prem doesn't equal cloud." You guys don't buy into that obviously. Your definition is, it's the experience, wherever your data is, we're going to bring that cloud experience. Clarify that if you would. >> Yeah, I'll kind of give the Oracle version and what I've talked about for years for Oracle, or for cloud consultancy as a whole or cloud capabilities, right? So Oracle really looks at true enterprise capabilities. And it's kind of what I've been talking about for years publicly as well too. Cloud is really, when they say cloud, it's not just 100% in cloud, it's a combination that you pull from on-prem your systems and engagement. Your systems of record all get created together. Sometimes it's an ecosystem with another company, right? So the more connected we are, so cloud is really an enabler to sort of pull everything together, right? Oracle is really focused on a lot on the enterprise capabilities. Some of the other cloud providers do great on some of the systems of engagement, the smaller applications, what's sitting in someone's cell phone or hands all the time. Oracle is really around foundation of the database in data. So we start with that enterprise and come up versus creating that really snazzy application coming down to make it enterprise level. So we take at that approach. I look at cloud computing, and my definition is really different than most people and it's really around a way of doing business. And what I mean by that is, it's a business that's technology enabled specifically, right? So you have to change the way that you do business. The way that you engage with your customers, with their customers, right? The actual customer on the end line. Cloud capabilities really aren't changing your operating model, it's change the way that you organize, you govern. You can't just, if you take a great capability and move it forward, and then turn around and do it in the same way in process, that's where you lose the efficiency. If you talk about things like business case, where we see the technology itself as a standalone, will give 30% of that business case, changing the way that you operate and engage people, will actually give you the bigger benefit, right? So if you actually go forward and as we talked about a cloud transformation, not only is around changing the capabilities from the tool standpoint, it's your people and your skills and your operating model, right? So if you look at an operating model potentially has seven or eight dimensions depending on what organization you kind of talk to, right? Gartner or whatever. If you don't hit every single and understand the impacts of every portion of the operating model and make the change, you will not reap the benefits. >> And my litmus test is that experience has to be the same whether it's in your public cloud, whether it's on-prem, whether it's in a partner, multicloud, and that you guys actually came up with the notion of same, same. It took some time to actually deliver that, but do you feel like you're there now with customers that buy in and lean in? >> Yeah, absolutely. And so the concept of what I call your mess for less or picking it up and moving it over there, has no value. It could be the first step. So a cloud journey, it may give you incremental value, but it should be the first step in your journey. So if we talk about like cloud journeys, if you're going to say, no, it's the same, same, you're going to move it over there, that may give you back to the sort of the slope on the business case. That's going to give you an increment of that which should self fund then it to go okay, I'm going to take that, I'm going to decompose that. Okay, great. Now, I'm going to expand on that, I'm going to take that money to actually reinvest in automation, right? So if you move it over to infrastructure, right? Where are you going to get the automation, is really on the path's layer. All the services, the monitoring, the autonomous capabilities, all those kind of things, that's where you drive efficiency and scale. So you basically self fund with the infrastructure transformation with potentially, typical journey we see customers with right? As let's move it, let's use that funding to actually automate it, it gets more savings, we use that more for innovation. So it's kind of a continuous stream. You want to get to the point where you can actually have a continuous innovation stream. And what I mean by that is, you have a mechanism or a capability. If you look at our Gen 2 Cloud versus our Gen 1 Cloud. Gen 2 cloud actually can take advantage of all the capabilities that we have from the past layer through automation, right? And then as you do that, we actually want to have a continuous process where you constantly look for innovation and incrementally add pieces over time. It's no longer, it's a bing bing. It's just a continuous stream of innovation. >> So okay, so you've made the statement that the business case for Oracle Gen 2 Cloud is overwhelming. First of all, what really, what's the underpinning of Gen 2 Cloud? Can you give us sort of the bumper sticker on that? >> Yeah, well, the underpinning the Gen 2 Cloud is really, if you look at the Gen 1 Cloud was purely just an infrastructure layer. Gen 2 is really based on a segmenting security, which is a huge problem out in the marketplace, right Dave? So we actually have a sort of a world class way where we take this segments security outside of the actual environment itself. It's completely segmented. Which is awesome, right? But then they also, when you actually move it forward, the capability of the entire thing is built on sort of the autonomous enterprise or autonomous capabilities. Everything is sort of self healing, self funding, or no sorry, self healing and self aware that continually moves it forward. So the goal with that is, is if you have something that takes mundane tasks back to that, you have people that are no longer doing those capabilities today. So the underpinning of that, and what that allows you to do is actually take that business case, and you reduce that because you're no longer having a bunch of people do things that are no value add. Those people can actually move on to do back to the innovation and doing those higher level components. >> So the business case is really about, I mean, primarily, I would imagine about labor cost, right? IT labor costs, we're very labor intensive, we're doing stuff that doesn't necessarily add differentiation of value to the business. You're shifting that to other tasks, right? >> Yeah. So the big components are really the overall cost of the infrastructure, what it takes to maintain the infrastructure and that's broken up into kind of two components. One of it is typical power, physical location, a building, all those kinds of things. And then the people that do the automations that take care of that right? At the lower level. The third level is, as you continue to sort of process in automation going forward, the people capability that actually maintains the applications becomes easier because you can actually extend those capabilities out into the application. Then you require fewer people to actually do the typical day to day things, whether it's DBAs, et cetera, like that. So it kind of becomes a continuous stream. There's various elements of the business case, you could sort of start with just the pure infrastructure cost, and then get some of the process and automations going forward, and then actually go that even further, right? And then as organizations, as a CIO, one of the questions I always have is, where do you want to end on this? And they say, "What are you talking about?" All right? (Dave chuckles) And it's really-- >> You're never done. >> You're on a journey, you're on a transformation I go, this is the big boy, big girl conversation, right? Do you want to have an organization that actually, it stays the same from a headcount standpoint? Or are you trying to look to a partner to do the-- Where are you trying to get your operating model? What is your company trying to get you to look at, right? Because all those inflection points takes a different step in the cloud journey. So as an advisor, right? As a trusted adviser, I ask those a half a dozen or so questions, I would kind of walk your organization through on sort of a cloud strategy, and I'll pick the path that kind of works with them. And if they want to go to a managed service provider, at the end, we would actually prepare someone either bring the partner in or have an associated partner we paired it off too, but we put the right pieces in place to make sure that that business case works. >> Well, that's interesting. That's a really important point because a lot of customers would say, "I don't want to reduce headcount. "I want to, I'm starving for people. "I want to retrain people." Some companies may want to say, "Hey, okay, "I got to reduce headcount. "It's a mandate." But most at least in these boom times are saying, "I want to shift." So my point to the business case is, if you're not going to cut people, then you have to have those people be more productive. And so the example that you gave in terms of making the application developers more productive is relevant. And I want to explain this is that, for example, very simple example, I'm inferring, you're going to be able to compress the time to value, you're going to reduce, lower your breakeven, accelerate the time to positive cash flow, if you will. >> That's an example. >> Absolutely. >> Of a value component to the business and part of the business case. Do people at look is that real? >> Absolutely, that's what it is. Definitely in the business case and I want you to call it the, when you hit your rate of return, right? The more that we can compress that and I would say back to the conversation we had earlier about elevate and some of the partnerships we have with Deloitte around that, a lot of that is to actually come up with enough capabilities that we can actually take the business case and actually reduce that and have special other things we can do for our customers, we're on financing and things like that to make it easier for them, right? We have options to make customers and actually help that business case. Some of the business cases we've seen, our entire IT organization saving 30% plus. Well, if you multiply that on a large fortune 100, that may have a billion dollar budget, that's real money. >> Yeah, but and-- Okay, yes, no doubt. But then, when you translate that into the business impact, you talked about the IT impact, but if you look at the business impact now it becomes telephone numbers. And actually CFOs oftentimes just don't even believe it, but it's true. Because if you can make the entire organization just, a half a percentage point more productive and you got 100,000 employees I mean, that overwhelms actually the IT business case. >> Sure. Yeah, and that's where that back to the sort of the steps in the business case is on the business and application side is making those folks actually more productive in the business case and saving them and adding whether it's a financial services and you're getting an application out to market that actually generates revenue, right? So that's, it's sort of the trickle effect. So when I look at I definitely look at it from a IT all the way through business. I am technically a business architect that does IT pretty damn good. >> Yeah and IT enables that sort of business. >> Absolutely. >> How do you, let's talk about this notion of continuous improvement, how are people thinking about that? Because you're talking a lot about just sort of self funding, and self progressing, sort of an organic entity that you're describing. How are people thinking about that? >> Yeah, I would say they're kind of a little bit over their map, right? But I would say that the goal is what we're trying to embed back to the operating model, we want to really embed is, sort of the concept of the cloud center of excellence. And as part of that, at the end, you have to have a set of functionality of folks that's constantly looking at the applications and our services of the different cloud providers or capabilities you have across the board. Everyone's got a multicloud environment, right? How do they take those services? They're probably already paying for it anyways, and as the components get released, how can you continually put little pieces in there and do little micro releases quarterly or in sorry, weekly, every month versus a big bang twice a year, right? Those little automation pieces continually add innovation in smaller chunks. And that's really the goal of cloud computing. And as you can actually break it up. It's no longer the Big Bang Theory, right? And I love that concept. Embedding that, whether you actually have a partner, with some of the stuff that we're doing that actually embed what we call like a day two services, that that's what it is. It's to support them, but also constantly look for different ways to include capabilities that were just released to add value on an ongoing basis. You don't have to go, "Hey, great, that capability came out. "It'll be on next year's release." No, it could be next week, next month, right? >> Well, so the outcome should be dramatically lowering costs. Really accelerating your time to value. It really is what you're describing and we've been talking about in terms of the autonomous enterprise. It's really a prerequisite for scale, isn't it? >> It is, absolutely, right? And so, when we use the term autonomous enterprise, I love that because that's actually a term I've been using for a few years, even before Larry started talking about the autonomous database. I talk about that environment of constantly look at a cloud capability and everything that you can put from a machine earlier into AI under to actually, basically let it run itself. The more that you can do that, the higher the value. And you put those people off in a higher level tasks, right? That's been going on every provider for a while. Oracle just has the capabilities now within the database that takes it to the next level, right? So we still are the only organization with that. Put that on top of our Gen 2 Cloud where all that is built in, as part of it going forward, that's where we have the upper level really at the enterprise computing level, right? We can work at all types of workload, but where we are niches, is really those big enterprise workloads, because that's where we started from data enterprise. >> I don't want to make it a technology discussion but said the only organization. You mean the only technology company with that autonomous database capabilities. Is that correct? >> Mike: Yes sir, yes. >> Okay, so I know I should have sort of talk about it, but Oracle I think talks about it more forcefully. We'll dig into that and report back. Mike, thanks so much for coming on theCUBE. I really appreciate it. Good stuff. >> Thank you very much. >> And thank you for watching. We'll be right back with our next guest. You're watching theCUBE. We're here in Chicago covering the rebirth of Oracle Consulting. I'm Dave Vellante. We'll be right back. (soft music)

(upbeat music) >> Hi everybody, welcome back. You're watching theCUBE, we go out to the events we extract the signal from the noise. This is a very special digital event and we're really covering the transformation not only the industry, but the transformation of Oracle Consulting and its rebirth. Mike Owens is here Group VP of Cloud Advisory and GM of Oracle Elevate, which is a partnership that Oracle announced last Open World with Deloitte, and Don Schmidt is here, who is a Managing Director at Deloitte. Gents, good to see you, welcome. >> Good to be here Dave. >> So, Don I want to start with you. Transformation, right? Everybody talks about that, there's a lot of trends going on in the industry. What do you guys see as the big gestalt transformation that's going on? >> Yeah I think there's an inflection point right now. Everybody have been saying they want to get out their data centers. The leaves haven't really been taking place, right? They've been kind of moving in small bits. We're now at the point where large transformation at scale, of getting out of your data centers, is now here. So, we are here to try to help our clients move faster. How can we do this more effectively, cost efficiently, and get them out of these data centers so they can move on with their day to day business? >> So data centers is just not an efficient use of capital for your customers. >> No, no there's lots of ways to do this a lot faster, cheaper, and get on to innovation. Spend your money there, not on hardware, floor space, power cooling, those fun things. >> Well you guys are spending money on data centers though right? So this is a good business for you all. >> Mike: We do it on behalf of other customers though. Right? >> Yeah and that's what's happening right? My customers, they essentially want to take all this IT labor cost and shift it into R&D get them on your backs and your backs right? Is this that what you see it? You know where are we in terms of that? I mean it started ten plus years ago but it really has started to uptake right? What's driving that? What's the catalyst there? >> You know so from my perspective, I've been doing this a while. A lot of it is either organizations are driving costs or what you're also seeing is IT organizations are no longer the utility in the organization and taking the orders, you're using them to try to top line value, but to do that, they actually have to take their business and change the model of it, so they can take that money and reinvest it in what Don had talked about, investment or continuous investment. So you're starting to hit those inflection points, you know years ago a CIO would be in his job for 15, 20 years, the average tenure for a CIO is you know three to five years on average, and it's because if they're not driving innovation or driving top line growth with an organization, organizations are now starting to flip that around so you're seeing a huge inflection point, with organizations really looking for IT not to be just a back office entity anymore, to truly drive them they have to transform that back to Don's point, because that inflection point, this large data center move over is a good sort of lever to kind of get them and really use it as opportunity to transform their organization. >> And the transformations are occurring, you know within industries, but at different pace. I mean some industries have transformed radically. You think about Ride shares, and digital music and the like others are taking more time, financial services, health care, they're riskier businesses, and you know there's more government in public policy so what do you see in terms of the catalyst for transformation and is there any kind of discernible, industry variance? >> Yeah there definitely is and he's mentioned some of the more start-up kind of organizations where Cloud was right for them at the early stages. These other organizations that have built these large application stacks and have been there for years, it's scary for them to say, "Let me take this big set of equipment and applications, and move it to the Cloud." It's a big effort. Starting from scratch with start-ups, that's a little different story right? So we are kind of at a different point, there are different stages within different industries, some are faster adopters than some of the others with government regulations and some of the technologies that have to kind of catch up to be able to provide those services. >> Do people generally want to take their sort of mission-critical apps which are largely running often on Oracle infrastructure database, they want to move that into the Cloud but do they want to bring that sort of Cloud-operating model to their on-prem and maybe reduce their overall data center footprint but preserve some of that? What are you guys seeing? >> So, two different probably viewpoints. So my viewpoint is, depends on the organization, depends on the regulatory they have, and there's a lot of factors in there. But I would say, as a standard organization would take their journey, mission-critical systems are historically not the first one in there. 'Cause back to the point of changing the operating model the way you want to do business and be effective, you don't go with the crown jewels first, historically, take some other work loads learn how to work in that operating model, how you're doing things change and then you evolve some of those pieces over time. There are organizations that basically, pull the band-aid off and just go right into it, right? But a lot of large enterprises sort of that's why we talk about Cloud as a journey, right? You take this journey you have to make the journey based on what's going on back what Don had talked about the regulatory requirements in history are the right controls in place for what they need at that point. If not, okay so what's an interim step to the journey? Could you bring Cloud in those capabilities on-prem and then have some of the other stuff off-prem? So it's really situational dependent, and we actually walk a customer through and now Don's organization does the same thing. You walk them through what makes best for their journey for where they're at in the industry and what they have today and what they're trying to achieve. >> So Don Deloitte doesn't just do IT it does business transformation, right? So it's like a chicken and egg, let's say that what comes first? The chicken or the egg? The IT transformation or the business transformation? >> I don't think it's an or it's an and. So have the total conversation of where's your Cloud journey for your entire enterprise, and then decide how that's going to be played out in both in IT and in the business. How the joint conversation from an enterprise perspective. >> So let's talk a little bit about the partnership, to your very well known brands, you guys get together, so what was the sort of impetus to get together? How's it going? Give us the update on that front. >> Yeah you know so from Oracle standpoint, Oracle has been really technology focused. It was really created by technologists, right? And back to the point of what we're trying to do with the Cloud and trying to do larger transformation, those aren't some of the skills that we have. We've been bringing in some of those skills in DNA, but if you look at it as why would you try to recreate this situation? Why would you not partner with an organization who does large business transformation like Deloitte? Right? And so the impetus of that is, how do we take the technology with the business transformation, pull that together and back of the one plus one equals three for my customer, right? That's what they really want, so how do we actually scale that into really big things and get big outcomes for our customers? Our partnership is not about trying to take a bunch of customers and move a couple application work loads. Our job, what we're really charted to do is make huge transformational leaps for our customers, using the combined capabilities of the two organizations. So this it's a hug paradigm for us to kind of do this. >> And in our collaboration with the two organizations just the opposite from what Mike just said right? So Deloitte wasn't really big in big IT, right? Business led transformations kind of what Deloitte's been known for, along with our cyber practice, and so we needed the deep skills of the technical experts. >> Right, so take me through what transformation engagement looks like. They don't call you up and say, "Hey want to buy me some transformation." Right? Where does it start? Who are the stake holders? How long does it take? I mean it could be multi year, I presume and never ends maybe but you want to get to business value first, so let's shorten up the time frame. Take me through typical engagement. Typical I know in quotes. And then, how long like take me through the point at which you start to get business value. What do I got to do to get there? >> Yeah so we see two different spectrums on a transformation. And it really aligns to what are your objectives. Do you just need to get out of the data center because you're on archaic dying hardware? Or do you want to take that, take your time and make a little bit more of a transformation journey? Or do you want to play somewhere in the middle of that spectrum? But on either one of those we'll come in and we'll do a discovery conversation. We'll understand what's in your data center, understand what the age or the health of your data center is, help the customers through, business case, TCO, how fast or how slow that journey needs to be for them, crave look our wave groups of how fast and we're going to sequence those over time to get out of their data center. In parallel we're going to be doing as Mike was saying running all the operational aspects. So while we're doing that discovery, we want to start standing up their Cloud center of excellence. Getting Cloud operations into the organization is a different skill set for IT to have, right? They're going to need to retrain themselves, retool themselves in the world of Cloud. So we kind of do that in parallel and then what we want to do is when we start a project, we want to start with a little POC or small little group of safe applications that we can prove how the model works. Move those into the Cloud, and then what we want to do is we want to scale at it, its large pace, right? Get the IT savings, get the cost cuts out of the organization. >> So I cleaned out my barn this weekend and the first thing I did is I got a dumpster. So I could throw some stuff out. So, is that part of the equation like getting rid of stuff? Is that part of the assessment? You know what's not delivering value that you can live without? >> Absolutely right, so there is kind of things that are just going to not go to Cloud, right? No longer need it, it's just laying around in the side, just get rid of that and move forward. >> And earlier one you'll see there's models depends you hear there's the 6 Rs, the 7 Rs and it's really the journey to Cloud it's almost you look at your status is it going to get re-platformed, is it going to get re-hosted, is it going to get retired back to your point. And if it's had something that's an appliance, right? That's something you're not going to put out to Cloud. Okay keep that in your data center. I have something that's so old, I hope it dies in the next two years. Don't spend the money move it to Cloud, let it die over the next two years. So back to the point, you kind of take this discovery and you go, where do things fall on the spectrum? And each one actually has a destination and a lever that you're going to pull, right? And if you're going to retire things okay so out of the business case, those are status quo for the next you're going to kill it over three years, right? Re-platform re-host means different things that they're going to take, right? Whether they do just to infrastructure or take advantage of PaaS or they'll go, "I'm going to blow up the entire application who directed to Cloud native services." Right? As you go through that journey you kind of map that out for them through the discovery process, and that tells you how much value you're going to get based on what you're going to do. >> But boy, this starts to get deep I mean as you used to peel the onions. So you just described what I would think of as wave 1. And then as you keep peeling you got the applications, you got the business process, you might have, reorganizations that's really where you guys have expertise, right? >> Well combined right? 'Cause yeah we're on the organizational side of things, but yeah there's a lot of things you have to sort through, right? And that's where the combined Elevate program really synergizes itself around the tools that we have. We both have tools that will help make sure we get this right, right? Deloitte has a product called Atadata, Oracle has a product called Soar, they married together properly into this transformational journey, to make sure we get the discovery done right and we get the migrations done right as well. >> Well you also have a lot of different stake holders, than you know, let's face it P&L Managers are going to try to hold on to their P&L. So you've got to bring in the senior executives. Clearly the CIOs involved is the CFO, CSWE. Who are the stake holders that you bring together in the room to kick this thing off? >> Depends on the message and depends on the outcome right? So if it's I need to get out of my data center, my data center strategy, historically the CIO. If it's there's an overall cost reduction and I want to re-implement my cost into innovating the business, sometimes that starts the CEO, CFO levels, right? >> Dave: Sure. >> So depends on that one but it is absolutely, back to your point of, the people want to hold their P&L huggers or kind of hold the cost or whatever. And one of the things, if you're not having the right conversations with people at the right level, the analogy that I've used for years is sometimes you're talking to a turkey about thanksgiving, right? So if you're trying to actually help transform and the entity is feeling that they're impacted by that negatively, even though there's a senior direction, so working through the right levels the organization to make sure you're showing how you're enabling them, it's key it's part of this journey. Helping them understand the future and how it's valuable, 'cause otherwise you'll get people that push back, even though it's the right thing for the company. We've seen that time and time again. >> Well it's potentially a huge engagement, so do you guys have specific plays or campaigns that you know I can do to get started maybe do a little test case, any particular offerings that-- >> Mike: I think-- >> Do you want to talk about the campaigns? >> So ]s under the program of Elevate, we've got a couple of campaigns. So the biggest one we've been talking about is around the data center transformation, so that's kind of the first campaign that we're working on together. The next one is around moving JD Edwards specific applications to Oracle's Cloud. And then the third one is around our analytics offering that Deloitte has and how we're going to market through to general put that in as well. Those are our three major campaigns. >> So data center transformation we hit it pretty hard. I'm sorry the third one was Cloud-- >> Analytics. >> Sorry analytics right okay which is kind of an instate that everybody wants to get to. The JDE migration, so you've got what, situations where people have just, the systems. >> And I would say it's actually more of a JDE modernization, alright? >> Okay. >> So you have an organization, right? They may have a JDE or JD Edwards instance that's really it's older, they're maybe on version nine or something like that, they don't want to go all the way to SaaS 'cause they can't simplify the business processes. They need to do that, but they also want to take advantage of the higher level capabilities of Cloud computing, right? IOT, Mobil, et cetera right? So as a modernization, one of the things we're doing is an approach together we work with customers depending where they're going and go hey great, you can actually modernize by taking up this version of JDE through an upgrade process, but that allows you then to move it over to Oracle Cloud infrastructure, which allows you to actually tap into all those platform services, the IOT and stuff like that to take to the next level. Then you can actually do the higher level analytics that sits on top of that. So it's really a journey where the customer wants to get. There's a various kind of four major phases that we can do or entry points with the customer on the JDE modernization, we kind of work them through. So that's a skill of some of the capabilities that Deloitte has as a deep JDE, and as well as Oracle Consulting, and we actually are going to market that together, matter of fact, we're even at conferences together, talking about our approaches here and our future. >> Okay. So that'll allow you to get to a Cloud PaaS layer that'll allow you to sort of modernize that and get out of the sort of technical debt that's built up. >> Where customers are not ready to maybe move their entire data center, right? This gets them on the journey, right? That's the important pieces. We want to get them on the Cloud journey. >> In the analytics campaign, so it seems to me that a lot of companies don't have their data driven, they want to be data driven, but they're not there yet. And so, their data's in silos and so I would imagine that that's all helping them understand where the data is, breaking down, busting down those silos and then actually putting in sort of an analytics approach that drives their, drives us from data to insights. Is that fair? >> Yeah fair. Yeah it's not just doing reporting and dashboards it's actually having KPI-driven insights into their information and their data within their organizations. And so Deloitte has some pre-configured applications for HR, finance, and supply chains. >> So the existing EDW for example would be fitter into that, but then you've got agile infrastructure and processes that you're putting in place, bringing in AI and machine intelligence. That's kind of the future state that you're in. >> And it also has, they look at the particular that's one of the things we like about the other stuff that Deloitte has done. They've actually done the investment of the processes back into those particular business units that they do and actually have KPI-driven ones it prebuilt configurations that actually adds value. These are the metrics that should be driving an HR organization. Here's the metrics that should be driving finance. So rather than doing better analytics, hey help me write my report better. No, we're going to help you transform the way you should be running your business from a business financial transformation, that's why the partnership with Deloitte. So it's really changing the game of true analytics, not better BI. >> Right okay, guys, two power houses. Thanks so much for explaining in The Cube and to our audience, appreciate it. (mumbling) >> Alright, thank you everybody for watching we'll be right back with our next guest you're watching The Cube, from Chicago. We'll be right back right after the short break. (upbeat music)

>>  Welcome back to theCUBE everybody. This is a special digital presentation sponsored by Oracle Consulting. We go out to the events, we extract the signal from the noise and we're going to multiple locations to really try to understand better the rebirth of Oracle Consulting. Stephanie Trunzo is here. She is the head of transformation and offerings at Oracle consulting North America. Stephanie, good to see you. >> Yeah, good to see you. >> Okay so we talked about sort of the mission of Oracle Consulting, now let's get into it and talk about some of what the customers are seeing. There's this theme in the industry that Gartner brought up about Bimodal IT and you guys are talking about Trimodal IT, so what is that all about? >> Well, two wasn't good enough so we had to add a third. (laughs) So Bimodal IT, two speed IT, the idea there is a lot of modern enterprises are struggling with this challenge between the systems of record that they have that have to be sources of truth. They're often slow to change. There's a lot of rigger around transforming those systems of record. And then on the second side, on the Bimodal side, there are the systems of interaction or systems of engagement, they're sometimes called. And those systems are things like the applications where there's users, customers at the other end. And they need to move at the speed of business. And so the idea of Bimodal IT and what a lot of our clients are struggling with currently is how do you serve both of those needs at the same time? There's complications in the processes, the tools, and certainly in the budget. And at the same time, there's kind of looming out there, this threat almost, that if you aren't in the AI NML data driven world yet, you're going to fall behind. And so our clients are struggling with the fact that they have not yet successfully addressed Bimodal IT, but still have to figure out how to get into this AI space. So our third system, hence Trimodal IT is the systems of intelligence. And that's what we've added. >> So, to make sure I've got the Bimodal right, >> Yeah sure. >> Is that, You've got people who are handling the systems of record you said. And so they have knowledge, they've got tribal knowledge, deep expertise, which may not be widespread. Kids coming out of school don't necessarily have that same expertise. And then there's sort of the systems of engagement kind of the new fun stuff. Did customers in your sense, buy into that? Or did they try to sort of cross-pollinate, as practitioners? >> Yeah they do buy into it. But they're really still struggling with the idea of Bimodal IT without even getting into the third system yet. So they are buying into it. The challenge, it's not even really about buying into it. It's addressing the challenge, because they have to overcome this legacy stuff, that they have in their system in order to address the speed of business. >> So the third piece, obviously relates to machine intelligence, AI, NML. It seems like that type of capability would apply to both systems of record and systems of engagement. Is that how you're looking at it? >> Yes, and so the Trimodal IT concept is kind of three different systems and how they interlock and relate to one another. If you think about systems of record, the currency, so to speak, for system of record are processes. If you think about the currency for systems of interaction it's the people, it's the users, it's the humans. And the currency for the system of intelligence is data, to your point. So when you're talking about systems of intelligence, collecting and leveraging data from all three systems is going to be what fuels your system of intelligence going forward. >> And that's the common thread between all three. And it just seems to me, that is ultimately the underpinning of modernization. I wonder what your customers, how do they view, and how do you view modernization? >> So the awesome thing about being at Oracle is data is our DNA. That's where Oracle started from, that's where we still are today is data underpins everything we do, all of the technology that we build is built on the understanding that it must be data-driven. And so when we're looking at all three of those systems and you're looking at it from an Oracle perspective, data is at the heart of even systems of record. Even systems of interaction, not only the systems of intelligence. When our clients are looking at modernization, they are trying to figure out a way to kind of leapfrog this story and get the whole way to a place where they are getting intelligence and insights out of their data. They're not just unlocking it. They're not just moving workloads in a lift and shift kind of model. They're doing it, because they want to serve the ultimate outcome that they get smarter as a business. >> So data is kind of like raw material, the AI or machine intelligence allows you to take data and create insights, if you will. And then cloud gives you scale and agility and all of those things. So Cloud's again another fundamental piece of, just from an infrastructure standpoint, and I think you guys define Cloud as sort of an experience, not a place. So it includes the on prime workloads, of course. So, talk about Cloud. Customers want to go from where they are today, to some outcome, some end point. And they don't want to spend a zillion dollars. And they don't want to disrupt their business. They are going to have to make investments, clearly. How do they get from point A to point B on that Cloud journey? >> So we've built something called a Cloud evolution framework. That Cloud evolution framework has several different phases and stages. And it's intended to be a skeleton to have that conversation with clients. Are you thinking about all of the things that you need to consider to make a healthy decision that has a real road map behind it. To your point on budget, and this is part of the Trimodal IT conversation is. They're struggling, I've talked to so many CIOs who are struggling to figure out. I right now am spending, 90% of my spend is on maintenance of systems versus on innovation. So how do I shift that spending story to something that is actually going to move the needle on getting the business ahead. That's going to serve my stakeholders, who are the lines of business, in a way that is not additive to my budget. But actually a shift of the budget. So we're looking at it from a Cloud perspective, helping our clients make that monetary shift. Make the shift of the budget where they're self-financing their own innovation by getting smarter and faster on moving their workloads to the Cloud. >> That's interesting, I want to come back to that self-financing. It reminds me of Y2K where you had all these activities going on, and the boom times. And then people wanted to go through an application rationalization exercise so they could self-fund really the innovation. >> Stephanie: Right. >> And when you're in the tenth year of a boom cycle, here. I wonder if there are similar things going on. Is that where the self-funding comes in? >> That's exactly it. So, I kind of use this example as a way of helping people consume and understand this. Marie Kondo, KonMari method is a popular, she wrote a best-selling book. She's on Netflix. The premise of her concept is helping to declutter your life. And her premise is you should hold each object in your hand and say, "Does it bring me joy?" And if it does, I'm going to keep it. And if it doesn't, I'm going to thank it for it's service, and get rid of it. And so we're talking to our clients about something very similar. You said, rationalization exercise and it's precisely the same thing. We're kind of using the KonMari method, if you will, to help our clients make those determinations. What are the things that they still need? What are the things that they can de-commission? What are the things that can stay where they are? And you don't have to do anything with, because they are serving the purpose just fine. >> Yeah, we're kind of hoarders by nature, and creatures of habit, so you have all these applications that nobody's using, but you're still spending maintenance and-- >> Stephanie: Correct. >> Keeping them up and it may not be delivering, and many aren't delivering value to the organization. So you want to double down on those that do. You guys use this concept and other do as well, of the autonomous enterprise. You have the autonomous database, I wonder if we could drill into that. Get passed the buzz words. What is the autonomous enterprise and what is Oracle's fit there? >> Yeah, I think one of the big misconceptions when people here autonomous, is that they think it means without people. And that's not right. (laughs) So, autonomous means that you're helping elevate all the parts of the system to their highest value. Which means, you don't need to worry about security patches. You don't need to worry about repairing things on the database. Those kinds of autonomous things is the technology helping heal and serve itself. That doesn't mean you don't need people anymore. What it means is two things. You need the experts that can help make sure that you're optimizing the value you get out of the autonomous tooling, but it also means that the humans are now freed up to do different kinds of high value work. So, an autonomous enterprise would be one where they're really sort of self-actualized. In the sense that their technology is feeding itself. It's getting smarter, and they're getting insights out of that, so that the people in their business are as valuable as they can be, leveraging the insights from the technology. >> So I can see how that trickles into IT. No questions about it. Can the autonomous IT organization trickle into the autonomous enterprise? And I mean I know it's sort of early days, but how do you see that shaping up? >> So, these kind of transformations, I believe are fundamentally across the whole company. And this is true at Oracle as well. We have something called Oracle@Oracle. And it's about drinking our own champagne and applying our own technology in house. So it's not just in an IT organization capacity. It's across HR, Procurement, Legal, every supporting function you can imagine. So that cultural change bleeds out across the entire body of the company. And I believe fully that if you're going after something like an AI mission or an autonomous enterprise state, which is an evolution that you need to involve everyone in the company in different roles. >> So what's that future state look like? >> I think the future state looks like a place where you're not just getting incremental gains on business processes or tasks that already exist. You're fundamentally seeing shifts in the way the business runs itself, as a result of the technology learning and getting smarter. And the people who are benefiting from that technology changing the way they operate in the company as well. >> So you mentioned the sort of decluttering example before, which I love, I'm getting that book. And are there other examples that inspire you? >> There are. So there was an anecdote, a client told me this story, which is a fantastic story, kind of triggered a thought for me. Told a story about a guy who was retiring. And at his retirement dinner, he told a story that 30 years ago when he started at the company. He remembers his dad teaching him, how to use the application that he then spent his entire career building and maintaining. As I heard that story, and they jokingly said at this point, our only solution is to get him out of retirement or find his son. (laughs) I thought about that, and I thought about 23 and me. You know 23 and me? >> Yes. >> So it's a DNA testing, tells you your heritage, lineage. And we're kind of at a state now, where a lot of our enterprise clients legitimately have these systems of record applications that are generations old, human generations old. So getting into the weeds on what that looks like, I've been telling clients pretty often lately. Institutional knowledge is the enemy, right? It's the enemy of the autonomous enterprise. If you have a challenge where you keep referring to the same name (laughs). If Bob leaves, we're in big trouble. If Sally isn't here anymore, that's a trigger for you to know that that's something you need to pay attention to. Because that institutional knowledge is not getting built into your technology. >> So what do you guys do? Do you put some kind of abstraction layer around that system of record, so that it can be automated? Is that part of what you do? >> Sure. So we're looking at, there's a couple different ways you can go about it. So you can look at the systems of record as a partial move that you do over time to the Cloud. And so you have to be pretty smart about the pattern and how you do that. Moving the workloads, kind of whole, will give you a little bit of that self-financing ability to dig in deeper and start transforming them. >> Okay, Trimodal IT. We'll be watching. (laughs) All right, Stephanie, thanks so much. It was great to see you. >> Absolutely, thanks. >> And thank you for watching. You're watching theCUBE at the special digital presentation. We'll be right back after this short break. (upbeat electronic music)

>>Yeah, >>yeah, yeah. >>Hello, everyone. And welcome to this Cube special presentation where we're covering the rebirth of Oracle Consulting. So this is a digital event where we're going around and identifying subject matter experts and different locations. We're currently here in Chicago, and I'm here with Stephanie Trunzo, who's the head of transformation and offerings at Oracle Consulting. Stefanie, Great to see you again. >>Yeah, you too. >>So, Oracle Consulting. You know, you guys have been quiet lately. >>Where you Yeah, >>well, we were quiet because I wasn't here >>yet. And I think the noise. Yeah, exactly. >>Here to make some noise. So I love the way you said rebirth. I think it's really accurate work. Will. Consulting has been around for quite some time, but as you said, maybe not high on the radar and one of the things that we're learning And one of the reasons I'm here in this transformation role is to help us transform ourselves to better match the transformation that our clients are going through. So that rebirth, which kind of makes me the mother, I guess of our consulting organization here is helping match our offerings to the kind of language that our clients are now using, which is really outcome driven. >>So was there an internal transformation, or is there an internal transformation taking place as well? And then you're sort of pointed to the marketplace. Maybe you could describe that. >>Absolutely. Yeah, So we're undergoing our own transformation at the same time that we're helping our clients undergo their transformation. And so, for us what that looks like it is things like the traditional services organization, which is kind of what Oracle Consulting had been in the past, was looking at the expertise that was necessary to drive clients business forward. But delivering it in what I would call a pretty traditional way, time of materials based kinds of contracting, determining the skills that were necessary, and and conversing with clients and feature function kinds of discussions. And our transformation is now about rebuilding the organization around offerings. And those offerings are things that we're doing to match the way that our clients are consuming. Let's say cloud technology. So if you might purchase of natural language processing service from a cloud platform, we want to also make sure that we're matching the humans to those technology services and enabling our clients to buy from us in a very similar way. >>So let's drill into this a little bit, because I'm gonna explain to people. So you talked about outcome driven. It used to be sort of a T and M model, which was staff augmentation. Hey, just just keep paying us. And, you know, if we capture the flag, great. If not, well, too bad. So now you're sort of starting at the outcome, and that's kind of working back right from their >>exactly right. Okay, so you know, clients people are transforming their businesses. They have goals. Those goals are, too. Serve their own clients differently to think about how to gain efficiencies within their organization. The change management that comes with it. Maybe it's to open up new revenue streams. Those are the outcomes that they're looking to achieve. They're not looking to say I need three database administrators for four months. That's not an outcome, right? And so we're thinking about how do we better shape our language, our organizational body posture to be the kind of force that can help them accelerate their own disruptions and their own transformations instead of, as you said kind of Here's a couple people for a couple of months, but here's the outcome. We're gonna help you achieve. >>Now. You're also bringing in some new blood. I mean, obviously Oracle large organization. A lot of DNA there but yourself. You came from IBM, you got people coming in from AWS. You've got folks from Accenture and all over the place. So describe that and how that's affecting the culture of Oracle consulting. >>And again, I think it's really a miracle how much our own transformation mirrors what's going on in our clients businesses. There's an influx of talent that is necessary to change the way that you think. And I believe that one of the reasons I myself came to join Oracle Consulting was I was excited about this new adventure. So when you're working in a certain style in a certain way, in a certain team for some amount of time, you can maybe forget to get introspective and forget to look at what's right in front of you and the changes you need to make. So bringing in new talent from outside is as much a part of our transformation as the way that we're shaping our offerings is bringing in those new ideas, bringing in people who have, you know, been there, done it in other experiences so that they can infuse our thinking with some of what's going on in the market around us. >>How would you summarize the mission of Oracle Consulting? >>The mission of Oracle Consulting is extremely simple. It's dead simple. It's help our clients succeed on Oracle Cloud Technology, period. >>Okay, now, part of that success comes with partners. You talk a little about the ecosystem and how that's evolving and what your vision is, how that transforms. >>I'm a huge ecosystem proponent. I love partnerships. I think it's a really important thing to build a healthy, strong channel. And so, while we're transforming our own consulting organization, we're also looking at our partner ecosystem to find where we can identify strategic partners. So there's always multiple partners in our Oracle Channel that we work with to be able to deliver broader solutions to our clients because they may have capabilities. We don't and vice versa. But when you can find sort of the Venn diagram where your strengths and their strengths together give us a broader solution for the client those were the special ones. And so to name a couple, we have a great partnership with Deloitte. We just announced that actually, fairly recently. We also have a partnership with an logica is another one of our strategic partners. And so they are bringing to the table some stories where we don't play, and then we're able to extend that story for our clients so that we can get to those outcomes that we were talking about. >>Where do you leave off and where the partners pick up? What's the sort of swim lane, if you will? >>Yep, so it depends on every partnership is a little bit different when we are helping with what I call our cloud evolution framework and is kind of a journey of How do you get to cloud? And there's lots of different components to it. Our partners play in different parts of that cloud evolution journey. So as an example, Deloitte is, ah, fantastic example. Our partnership with Deloitte when we're helping our clients modernize, move workloads to the cloud. Deloitte can help them continue to maintain and optimize that after we finish the first wave of modernization. So that's one example with M Logical. We have a different pattern where M Logica is helping with take outs of different technologies on the front end, and then we're going to pick up and help with the innovation piece after the take out is over. >>So you really way replay that. Tell me what you're really the deep technology expertise, whereas some of your partners not only they have technology expertise but they can help with business transformations and sort of other organizational changes is that, Is that right? >>That's absolutely true. We have the deep technology experience, the Oracle expertise, but we also are able to help build and kind of umbrella plan around our cloud evolution framework and then pull in the partners to their strengths. And it also really helps us when we're in an ecosystem discussion to make sure that we're understanding how we're also benefiting the partner. There's always got to be a win win, right? So it's not just about how do we fit in and play, but that we're growing their business because by growing our partners businesses, we're growing. Overall, our Oracle story, >>because Oracle's known as a product company and still suffer products that you generate most of your revenue, so and you've got your cloud. You've got things like Cloud a customer and exit data that's really driving you got. The Oracle database is certainly a huge application portfolio. How is Oracle Consulting? Aligning with the >>products? >>Yeah, that's a great question. So as a product company, our goal is still to help our clients achieve their goals. Right? And so consulting is looking at our Oracle products that to make sure that we're always the deepest and the busted understanding so we can help leverage that technology to its fullest capacity for our clients. It's not just good enough to buy a tool. You have to know how to use it, right? And so our objective is to align with Oracle products. Make sure we know what's gonna be hot off the press that we're driving from. Our client experience is back into the product sets as well. So we're informing our product development of what's really happening out in the world with our clients implementations. >>My last question is, how are you gonna define success when you look back a couple years from now? What will success look like to you >>Yeah, that's a great question. Success to me will look like being the go to for any solution. That is an Oracle driven answer to our clients that Oracle Consulting is driving consumption in a way that is extremely valuable to the client. Because in the end, cloud consumption technology consumption brought in and of itself is not very interesting. It's when we're telling stories that our client stories on stage is because we've helped them achieve new business outcomes, things that weren't possible for them before. >>Well, it's great to have you. Thank you so much for coming on. And it's good to have you at the helm. Bring credibility to Oracle Consulting. And we'll be watching. So thank you. >>Awesome. Thank you. >>Thank you for watching. We'll be right back with our next guest right after this short break. You're watching the cube. Yeah, Yeah, yeah, yeah, yeah, yeah

from Chicago it's the cube covering Oracle transformation day 2020 not to you by Oracle consulting hello everyone and welcome to this cube special presentation where we're covering the rebirth of Oracle consulting so this is a digital event where we're going around and identifying subject matter experts in different locations we're currently here in Chicago and I'm here with Stephanie trunzo who's the head of transformation and offerings at Oracle consulting is definitely great to see you again yeah you too so Oracle consulting you know you guys have been quiet lately where you good yeah well we were quiet because I wasn't here yet okay make a noise yeah exactly here to make some noise so I love the way you said rebirth I think it's really accurate work will consulting has been around for quite some time but as you said maybe not high on the radar and one of the things that we're learning and one of the reasons I'm here in this transformation role is to help us transform ourselves to better match the transformation that our clients are going through so that rebirth which kind of makes me the the mother I guess over our consulting organization here is helping match our offerings to the kind of language that our clients are now using which is really outcome driven mm-hmm so was there an internal transformation or is there an internal transformation taking place as well and then just sort of pointed to the marketplace maybe you could describe that absolutely yeah so we are undergoing our own transformation at the same time that we're helping our clients undergo their transformation and so for us what that looks like it is things like a traditional services organization which is kind of what Oracle consulting had been in the past was looking at the expertise that was necessary to drive clients business forward but delivering it in what I would call a pretty traditional way time and materials based kinds of contracting determining the skills that were necessary in and conversing with clients and feature function kinds of discussions and our transformation is now about rebuilding the organization around offerings and those offerings are things that we're doing to match the way that our clients are consuming let's say cloud technology so if you might purchase natural language processing service from a cloud platform we want to also make sure that we're matching the humans to those technology services and enabling our clients to buy from us in a very similar way so let's drill into this a little bit because I want to explain to people so you talked about outcome driven yeah and it used to be sort of a t and M model which was staff augmentation hey just just keep paying us and you know if we capture the flag great if not well too bad so now you're sort of starting at the outcome and that's kind of working back right from there exactly right okay so you know clients people are transforming their businesses they have goals those goals are to serve their own clients differently to think about how to gain efficiencies within their organization the change management that comes with it maybe it's to open up new revenue streams those are the outcomes that they're looking to achieve they're not looking to say I need three database administrators for four months that's not an outcome right and so we're thinking about how do we better shape our language our organizational body posture to be the kind of force that can help them accelerate their own disruptions and their own transformations instead of as you said kind of here's a couple people for a couple months but here's the outcome we're gonna help you achieve now you're also bringing in some some new blood I mean obviously Oracle a large organization a lot of DNA there but yourself you came from IBM you got people coming in from AWS you got folks from Accenture and all over the place so I described that and how that's affecting the culture of Oracle consulting and again I think it's really a miracle how much our own transformation mirrors what's going on in our clients businesses there's an influx of talent that is necessary to change the way that you think and I believe that one of the reasons I myself came to join Oracle consulting was I was excited about this new adventure so when you're working in a certain style in a certain way in a certain team for some amount of time you can maybe forget to get introspective and forget to look at what's right in front of you and the changes you need to make so bringing in new talent from outside is as much a part of our transformation as the way that we're shaping our offering is bringing in those new ideas bringing in people who have you know been there done it in other experiences so that they can infuse our thinking with some of what's going on in the market around us how would you summarize the mission Oracle consulting the mission of Oracle consulting is extremely simple it's dead simple its help our clients succeed on Oracle cloud technology period ok now part of that success comes with partners absolutely talk a little bit about the ecosystem and how that's evolving and what your vision is to how that you know transforms I'm a huge ecosystem proponent I love partnerships I think it's a really important thing to build a healthy strong channel and so while we're transforming our own consulting organization we're also looking at our partner ecosystem to find where we can identify strategic partners so there's always multiple partners in our Oracle channel that we work with to be able to deliver broader solutions to our clients because they may have capabilities we don't and vice versa but when you can find sort of the Venn diagram where your strengths and their strengths together give us a broader solution for the client those are the special ones and so to name a couple we have a great partnership with Deloitte we had just announced that actually fairly recently we also have a partnership with M logica is another one of our strategic partners and so they are bringing to the table some stories where we don't play and then we're able to extend that story for our clients so that we can get to those outcomes that we were talking about where do you leave off and where do the partners pick up what's the sort of swim lane if you will yep so it depends on every partnership is a little bit different when we are helping with what I call our cloud evolution framework and is kind of a journey of how do you get to cloud and there's lots of different components to it our partners play in different parts of that cloud evolution journey so as an example Deloitte is a fantastic example our partnership with Deloitte when we're helping our clients modernize move workloads to the cloud Deloitte can help them continue to maintain and optimize that after we finish the first wave of modern is so that's one example with em Logica we have a different pattern where M logica is helping with takeouts of different technologies on the front end and then we are going to pick up and help with the innovation piece after the takeout is over so you really replay that tell me if I gotta share you're really the the tech deep technology expertise whereas some of your partners not only they have technology expertise but they can help with business transformations and sort of other organizational changes is that is that right that's absolutely true we have the deep technology experience the Oracle expertise but we also are able to help build an kind of umbrella plan around our cloud evolution framework and then pull in the partners to their strengths and it also really helps us when we're in an ecosystem discussion to make sure that we're understanding how we are also benefiting the partner there's always got to be a win-win right so it's not just about how do we fit in and play but that we're growing their business because by growing our partners businesses we're growing overall our Oracle story of course Oracle's known as a product company is sell software products that's how you generate most of your revenue so and you've got your cloud you've got you know things like cloud a customer and you know Exadata that's really driving you got the Oracle database certainly a huge application portfolio how is Oracle consulting aligning with the products yeah that's a great question so as a product company our goal is still to help our clients achieve their goals right and so consulting is looking at our Oracle products that to make sure that we are always the deepest and the best at understanding so we can help leverage that technology to its fullest capacity for our clients it's not just good enough to buy a tool you have to know how to use it right and so our objective is to align with Oracle products make sure we know what's going to be hot off the press that we're driving from our client experiences back into the product sets as well so we're informing our product development of what's really happening out in the world with our clients implementations my last question step is how are you gonna define success when you look back you know a couple years from now what will success look like to you yeah that's a great question success to me will look like being the go-to for any solution that is an Oracle driven answer to our clients that Oracle consulting is driving consumption in a way that is extremely valuable to the client because in the end cloud consumption technology consumption by in and of itself is not very interesting it's when we're telling stories that are our clients stories on stages because we've helped them achieve new business outcomes things that weren't possible for them before well it's great to have you thank you so much for coming on and it's good to have you at the helm sort of bring credibility to Oracle consulting and we'll be watching so thank you awesome thank you all right and thank you for watching we'll be right back with our next guest right after this short break you watching the cube

from Chicago it's the cube covering Oracle transformation day 2020 not to you by Oracle consulting welcome back to the queue of everybody this is a special digital presentation sponsored by Oracle consulting we go out to the events we extract the signal from the noise and we're going to multiple locations to really try to understand better the rebirth of or consulting Stephanie trunzo is here she's the head of transformation and offerings at or consulting North America Stephanie good to see you yeah good to see you okay so we talked about sort of the mission of Oracle consulting now let's get into it and talk about what some of the customers are seeing there's this you know theme in the industry the Gartner brought up about bimodal lights yeah you guys are talking about trimodal eyes yeah so what is that all about well ii wasn't good enough so we had a third so bimodal IT two-speed IT the idea there is a lot of modern enterprises are struggling with this challenge between the systems of record that they have that are have to be sources of truth they're often slow to change there's a lot of rigor around transforming those systems of record and then on the the second side on the bimodal side there are the systems of interaction or systems of engagement they're sometimes called and those systems are things like the applications where there's users customers at the other end and they need to move at the speed of business and so the idea of bimodal IT and what a lot of our clients are struggling with currently is how do you serve both of those needs at the same time there's complications in the processes the tools and certainly in the budget and at the same time there's kind of looming out there this you know threat almost that if you aren't in the a IML data-driven world yet you're going to fall behind and so our clients are struggling with the fact that they have not yet successfully addressed by modal IT but still have to figure out how to get into this AI space so our third system hence trimodal IT as the systems of intelligence and that's what we've added so should I get the bimodal right yes that you know people that are handling the the systems of record you said hmm and so they have knowledge they got you know tribal knowledge yes DJ BIA which may not be you know widespread it's not kids kids coming out of school don't necessarily have that that same expertise and then there's sort of the systems of engagement kind of the new fun stuff did customers in your sense buy into that or did they try to sort of cross pollinate as practitioners yeah they they do buy into it but they're really alright they're still struggling with the idea of bimodal IT without even getting into the third system yet and so they are buying into it the challenge I don't it's not even really about buying into it it's addressing the challenge because they have to overcome this legacy stuff that they have in their system in order to address the speed of business so the third piece obviously relates to machine intelligence AI nml it seems like that type of capability would apply to both systems of record and systems of engagement is that is that how you're looking at yes and so the trimodal IT concept is kind of three different systems and how they interlock and relate to one another if you think about systems of record the currency so to speak for systems of record or processes if you think about the currency for systems of interaction it's the people it's the users it's the humans and this is the currency for the system of intelligence is data to your point so when you're talking about systems of intelligence collecting and leveraging data from all three systems is going to be what fuels your system of intelligence going forward and that's the common thread between you know all three and it just seems to me that is ultimately the underpinning of modernization I wonder what do your customers how do they view and how do you view modernization so the awesome thing about being at Oracle is data is our DNA that's where Oracle started from that's where we still are today is data underpins everything we do all of the technology that we build is built on the understanding that it must be data driven and so when we're looking at all three of those systems and you're looking at it from an Oracle perspective data is at the heart of even system a record of even systems of interaction not only the systems of intelligence when our clients are looking at modernization they're trying to figure out a way to kind of leapfrog this story and get the whole way to a place where they're getting intelligence and insights out of their data they're not just unlocking it they're not just moving workloads and a lift and shift kind of model they're doing it because they want to serve the ultimate outcome that they get smarter as a business so data is kind of like raw material the AI or machine intelligence provides it allows you to take data and create insights if you will and then cloud gives you scale and agility and all those things so so clouds again another fundamental piece of just from an infrastructure standpoint and I think you guys define cloud as sort of an experience not a place so includes the on-prem workloads of course so talk about cloud customers want to go from where they are today to somehow become some ending point and they don't want to spend a zillion dollars and they don't want to disrupt their business they're gonna have to make investments clearly how do they get from point A to point B on that cloud journey so we've built something called a cloud evolution framework that cloud evolution framework has several different phases and stages and it's intended to be kind of a skeleton to have that conversation with clients are you thinking about all of the things you need to consider to make a healthy decision that has a real roadmap behind it to your point on budget and this is part of the trimodal IT conversation is there struggling I've talked to so many CIOs who are struggling to figure out I right now I'm spending you know 90% of my spend is on maintenance of systems versus on innovation so how do I shift that spending story to something that's actually going to move the needle on getting the business ahead that's gonna serve my stakeholders who are the lines of business in a way that is not additive to my budget but actually a shift of the budget and so we're looking at from a cloud perspective helping our clients make that monetary shift make the shift of the budget where they're self financing their own innovation by getting smarter and faster on moving their workloads to the cloud it's a - I want to come back to that self financing via y2k where you had all these activities going on in the boom times and then people wanted to go through an application rationalization exercise yes it could self fund really the innovation right and we're in a tenth year of a boom cycle here I wonder are there similar things going on is that where the self funding comes in that's exactly it so you know I kind of used this example as a way of helping people consume and understand this Marie Kondo konmari method is a popular she wrote a best-selling book she's on Netflix the premise of her concept is helping to declutter your life and her premises you should hold each object in your hand and say does it bring me joy and if it does I'm going to keep it and if it doesn't I'm gonna thank it for its service and get rid of it and so we're talking to our clients about something very similar you said rationalization exercise and it's precisely the same thing we're kind of using the konmari method if you will to help our clients make those determinations what are the things that they still need what are the things that they can decommission what are the things that can stay where they are and you don't have to do anything with because they're serving the purpose just fine yeah we're kind of hoarders by nature in creature habit so you have all these applications that nobody's using but you're still spending maintenance and correct keeping them up and and they may not be delivering and in problem any aren't delivering value for the organization so you want to double down on those that do you guys use this concept and others do as well of the autonomous enterprise you have autonomous database I wonder if we could you know drill into that get past the buzz words what is the autonomous enterprise and and what's Oracle's fit there yeah I think one of the big misconceptions when people hear autonomous is that they think it means without people and that's not right so autonomous means that you're helping elevate all the parts of the system to their highest value which means you don't need to worry about security patches you don't need to worry about repairing things on the the database those kinds of autonomous things is is the technology helping heal and serve itself that doesn't mean you don't need people anymore what it means is two things you need the experts that can help make sure that you're optimizing the value you get out of autonomous tooling but it also means that the humans are now freed up to do different kinds of high-value work so an autonomous enterprise would be one where they're really sort of self actualized in the sense that their technology is feeding itself it's getting smarter and they're getting insights out of that so that the people in their business are as valuable as they can be leveraging the insights from the technology so I can see how that trickles into IT no question about it can can the autonomous IT organization trickle into the autonomous enterprise and I mean I know it's early days but how do you see that you know shaping up so the these kinds of transformations I believe are fundamentally across the whole company and and this is true at Oracle as well we have we have something called Oracle at Oracle and it's about drinking our own champagne and applying our own technology in-house so it's not just in an IT organization capacity its across you know HR procurement legal every supporting function that you can imagine so that cultural change bleeds out across the entire body of the company and I believe fully that if you're going after something like an AI mission or an autonomous enterprise you know state which is an evolution that you need to involve everyone in the company in different roles so what's that future state look like I think the future state looks like a place where you're not just getting incremental gains on business processes or tasks that already exist you're fundamentally seeing shifts and the way the business runs itself as a result of the technology learning and getting smarter and the people who are benefiting from that technology changing the way they operate in the company as well so you mentioned the hood decluttering example yeah which I love are there other examples that inspire you there are so I there was an anecdote a client told me this story which is a fantastic story kind of triggered a thought for me a told a story about a guy who was retiring at his retirement dinner he told a story that thirty years ago when he'd started at the company he remembers his dad teaching him how to use the application that he then spent his entire career building and maintaining as I heard that story and they jokingly said at this point our only solution is to get him out of retirement or find his son I thought about that and I thought about 23andme have you know yes so it's a you know kind of DNA testing tells you your heritage lineage and we're kind of at a state now where a lot of our enterprise clients legitimately have these systems of record applications that are generations old human generations old so getting into the weeds on what that looks like I've been telling clients pretty often lately institutional knowledge is the enemy right if and it's the enemy of the autonomous enterprise if you have if you have a challenge where you keep referring to the same name you know if Bob leaves we're in big trouble if Sally isn't here anymore that's a trigger for you to know that that's something you need to pay attention to because that institutional knowledge is not getting built into your your technology so what do you guys do you put some kind of abstraction layer around that system of Records so that it can be automated does that part of sure so so we are looking at there's a couple different ways you can go about it so you can look at the systems of record as a partial move that you do over time to the cloud and so you have to be pretty smart about the pattern and how you do that moving think the workloads kind of whole will give you a little bit of that self financing ability to dig in deeper and start transforming them ok trimodal IT will be watching hey Stephanie thanks so much it's great yeah absolutely Thanks thank you for watching you watching the queue at this special digital presentation we'll be right back right after this short break

from Chicago it's the cube covering Oracle transformation day 2020 not to you by Oracle consulting welcome back everybody to this special presentation of the cube where we're covering the rebirth of Oracle consulting it's a digital event where we're going out we're extracting the signal from the noise we happen today to be in Chicago which is obviously the center of the country a lot of big customers here a lot of consultants and consulting organizations here and a lot of expertise Mike Owens is here as a group VP for cloud advisory and a general manager of Oracle elevate Mike thanks for coming on the cube I appreciate it I'm glad to be here so I could ask you elevate in your title what is Oracle elevate yeah Oracle elevate was actually announced Oracle OpenWorld last year it's the partnership that we really had to actually take her skill of the next level so we actually did it with Deloitte Consulting so the goal is to actually take the capabilities of both organizations Deloitte really has functional capabilities and expertise with an Oracle practice and obviously Oracle has Oracle technical expertise the combination the two really allows us to scale provide sort I call the one plus one equals three effort for customers now you've got a decent timeline or observation over the past several years you joined three years ago you were at some brand name companies first of all what attracted you to come to Oracle consulting yeah absolutely so Oracle was in the point where they were doing a lot of stuff around on Prem on-premise software right the old ERP type stuff they were doing cloud they sort of had to have this sort of transformational moment I was asked to come in an Oracle consulting in their early days and say hey look we're trying to transform the organization from on-prem consulting over to cloud consulting coming to help us with this stuff that you've worked from your prior to cloud companies and help us really move the organization forward and look at things differently so it's definitely been a journey over the last three years I've taken it from really 85% of the 90% of our revenue around on Prem type of engagements to now actually splitting the organization being dedicated huntersam on cloud which is just a huge transformation last three years yeah of course I work was a product company and you're you're at your then CTO Larry Ellison said we're going cloud first and that happened during your tenure you came in I'd believe prior to that what kind of effect did that have on the organization I mean we we know from a product standpoint but but just culturally and just a mindset yeah absolutely it had a huge effect in their organization they they started splitting the organization to actually have be dedicated organizations whether it's sales on product whether it's support for product pre-sales support or engineering and solutions architecture and or consulting so we've now split the organization's to primarily support those different lines of business and what that allows us to do is actually focus that and put a lot of the stuff on cloud and moving the company at cloud first at this point we still have a lot of organizations to do either on Prem type of work and things like that they can't move over that's supportive but you're gonna see a larger shift of the cloud first right to actually move our customers and our organizations and back to wheats you hear a bunch of our executives talk about we also actually use our own capabilities as well to you know whether it's a our machine learning we actually use in our own HR systems if I do my expense reporting there's actually a I bought that I can actually put stuff in there and automatically pulls it in we actually take those capabilities and consumer ourselves right because we have to believe and what we actually create as well your definition to cloud of course is different from you know the hyper scale cloud providers would say our cloud is like per scale put it in our cloud on Prem you guys don't buy into that obviously your definition is it's the experience the weather wherever your data is we're gonna bring that cloud experience clarify that if you would yeah I'll kind of give the Oracle version and what I what I've talked about for years for Oracle R for cloud consulting as a whole or cloud capabilities right so Oracle really looks at true enterprise capabilities and it's kind of what I've been talking about for years publicly as well too is cloud is really when they say cloud it's not just 100% in cloud it's a combination that you pull from on-premise systems and an engagement you know your systems of record all get created together sometimes it's an ecosystem with another company right so the more connected we are so a cloud is really an enabler to sort of pull everything together right Oracle's really focused on a lot on the enterprise capabilities some of the other cloud providers do great on some of the systems of engagement the smaller applications that that's what's sitting in someone's cell phone or hands all the time Oracle is really around foundation of the database and data so we start with that enterprise and come up versus creating that really snazzy application - coming down to make it at a prize level so we take it that approach I look at cloud computing and my definition is really different than most people it's really around it's a roundel way of doing business and what I mean by that is it's it's a business that's technology enabled specifically right so you have to change the way that you do business the way that you engage with your customers with with their customers right the actual customers on the endline cloud capabilities really are on changing your operating model it's change and change the way that you organize you govern you know you can't just if you take a great capability and move it forward and then turn around and do it in the same way in process that's where you lose the efficiency if you talk about things like business case where we see the technology itself as a standalone we'll give 30% of that business case changing the way that you operate and engage people will actually give you the bigger benefit right so if you actually go for as we talked about a cloud transformation not only is around changing the capabilities from the tools standpoint it's your people and your skills and your operating model right so if you look at an operating model potentially has seven or eight dimensions depending on what organization you kind of talk to your right Gartner or whatever right if you don't hit every single understand the impacts of everything portion of the operating model would make the change you will not reap the benefits and my limit test is that experience has to be the same whether it's in your public cloud whether it's on pram whether it's in a partner you know multi cloud and that you guys actually came up with the notion of same-same sometime to actually deliver that but but do you feel like you're you're there now with customers that yeah that buy-in and lean in yeah absolutely and so the concept of you know what I call your master alas or picking it up and moving it over there has no value it could be the first step so a cloud journey it may give you informally but it should be the first step in your journey you know so if we talk about like cloud journeys if you're gonna say you know it's the same safe you're gonna move it over there that may give you back to the sort of the slope on the business case that's going to give you a incremental that would should self fund then a go okay I'm gonna take that I'm going to decompose that okay great now I'm gonna expand on that I'm gonna take that money to actually reinvest Automation right so if you move it over to infrastructure right where you're gonna get the automation is really on the pass later all the services in the monitoring the autonomous capabilities all those kind of things that's where you drive efficiency and scale so you basically so fun with the infrastructure transformation with potentially typical journey we see customers with right as let's move it let's use that funding to actually automate it it gets more savings we use that more for innovation so it's kind of a continuous stream you want to get to the point where you can actually have a continuous innovation stream and what I mean by that is you have a mechanism or a capability if you look at our Gen 2 cloud versus our Gen 1 cloud Gen 2 cloud actually can take an inch of all the capabilities that we have from the past layer through automation right and then as you do that we actually won't have a continuous process where you constantly look for innovation and incrementally add pieces over time it's no longer it's a Big Bang it's just a continuous stream of innovation so ok so you've made the statement that the business case for Oracle gen 2 cloud is overwhelming first of all what really what's the underpinning of Gen 2 cloud can you give us throw to the bumper sticker on that yeah all the underpinning magenta to cloud is really if you look at the Gen 1 cloud was purely just an infrastructure layer Gen 2 is really based on a segmenting security which is a huge problem out in the marketplace right a so we actually have a sort of a world-class way we take a segment security outside of the actual environment itself it's completely segment which is awesome right but then they also will you actually move it forward the capability of the entire thing is built on sort of the autonomous enterprise or autonomous capabilities everything is sort of self-healing self-funding are not sorry so healing and self-aware that continually moves it forward so the goal with that is is if you have something that takes mundane tasks back to that you have people that are no longer doing those capabilities today so the underpinning of that and what that allows you do is actually take that business case and you reduce that because you're no longer having a bunch of people do things that are no value add those people can actually move on to do back to the innovation and doing those higher-level components so the so the business case is really about I mean primarily I would imagine about labor cost right IT labor cost we're very labor intensive we're doing stuff that doesn't necessarily add differentiation and value to the business you're shifting that to other tasks right yeah so the big components are really the overall cost the infrastructure what it takes to maintain the infrastructure and that's broken up into kind of two components one of it is typical power physical location of building all those kinds of things and then the people to do the automations that take care of that right at the lower level the third level is as you continue to sort of process in automation going forward the people capability that actually maintains the applications becomes easier because you can actually extend those capabilities out into the application then you require fewer people to actually do the typical day-to-day things whether it's DBAs that are like that so it kind of becomes a continuous stream there's various elements of the business case you could sort of start with just the pure infrastructure cost and then get some of the process and automations going forward and then actually go that even further right and then as organizations as a CIO one of the questions I always have is where do you want to end on this and they say well what are you talking about alright it's really I'm late ever done you're on it and you're on a journey you're on a transformation I go this is the big boy big girl conversation right do you want to have an organization that actually it stays the same from the headcount standpoint are you trying to look to a partner to do the were you trying to get our operating model what is your company trying to get you to look at right because all those inflection points takes a different step in the cloud journey so as an adviser right as a trusted adviser I asked those herbs a half a dozen or so questions I would kind of walk your organization through on sort of a cloud strategy and I'll pick the path that it kind of works with them and if they want to go to a managed service provider at the end we would actually prepare someone either bring the partner in or have a little associate a partner we've heard it off - but we put the right pieces in place to make sure that that business cake works well that's it really important point because a lot of custom customers would say I don't want to reduce headcount I want to I'm starving for people I want to retrain people you know some companies may want to say hey okay I got a reduce headcount it's a mandate but but most at least in these boom times are saying I want to ship so buy point to the business cases if you're not going to you know cut people then you have to have those people be more productive and so the example that you gave in terms of making the application developers more productive is relevant and I want to explain this is that for example very simple you're I'm inferring you're gonna be able to compress the time to value you're gonna reduce you lower your breakeven you know accelerate the time to positive cash flow if you will that's an example of a value component to the business and part of the business case the people look at that and is that absolutely that's what it is definitely the business case and one we call it the you know when you get your rate of return right the more that we can compress that and I would say back to the conversation we had earlier about elevate and some of the partnership's we have with Deloitte around that a lot of that is to actually come up with enough capabilities that we can actually take the business case and actually reduce that and have special other things we can do for our customers or on financing and things like that to make it easier for them right we have options to make customers and actually help that business case some of the business cases we've seen our entire IT organizations saving 30 plus percent well if you multiply that on a you know a large fortune 100 that may have a billion dollar budget that's real money yeah but and okay yes no doubt but then when you translate that into the business impact like you talked about the ite impact but if you look at the business impact now it becomes telephone numbers and actually CFOs often times you just don't even believe it but it's true because if you can make the entire organization just you know a half a percentage point more productive and you get a hundred thousand employees I mean that is that overwhelms actually the IT business case yeah and that's where that back to the sort of the the steps in the business case is on the business and application side is making those folks actually more productive in the business case and saving them and adding you know whether it's a financial services you're getting an application out to market that actually generates revenue right so that's it's sort of the trickle effect so when I look at I definitely look at it from a IT all the way through business I am a technically a business architect that does IT pretty damn good yeah enables that sort of business absolution how do you let's talk about this notion of you know continuous improvement how are people thinking about that because you're talking a lot about just sort of self funding and and self progressing you know sort of an organic entity that you're describing how are people thinking about that yeah and I would say they're kind of a little bit older map right but I would say that goal is what we're trying to embed back to the operating model we want to really embed is you know sort of the concept of a cloud center of excellence and as part of that at the end you have to have a set of functionality of folks that's constantly looking at the applications and/or services of the different cloud providers at capabilities you have across the board everyone's got a multi cloud environment right how do they take those services they're probably already paying for anyways and as the components get released how can you continually put little pieces in there and do little micro releases quarterly aren't sorry weekly you know every month versus a big bang twice a year right those little automation pieces continually add innovation in smaller chunks and that's really the goal of cloud computing and you know is you can actually break it up it's no longer the Big Bang Theory right and I love that concept embedding that whether you actually have a partner with some of the stuff that we're doing that actually we embed what we call like a day-to services that that's what it is is to support them but us constantly look for different ways to include capabilities that were just released to add value on an ongoing basis you don't have to go hey they're great that capability came out it'll be on next year's release no it could be next week it could be next month right well so the outcome should be you should be dramatically lowering costs really accelerating your time to value it really is what you're describing and we've been talking about in terms of the autonomous you know Enterprise it's really a prerequisite for scale isn't it it is absolutely right and so when we use the term autonomous Enterprise - I love that because that's actually the term I've been using for a few years even before Larry started talking about the autonomous database I talked about that environment of constantly look at a cloud capability and everything that you can put from a machine or into AI under basically basically let it run itself the more that you can do that the higher the value you can put those people off in a higher-level tasks right that's been going on every provider for a while Oracle just has the capabilities now within the database that takes it to the next level right so we still are the only organization with that put that on top of our gen 2 cloud where all that is built in as part of it going forward that's where we have the upper level really at the enterprise computing level right we can we can work at all types of workload but where we are niches is really those big enterprise workloads because that's where we started from data Enterprise I don't want to make it a technology discussion but you said the only organizations meaning the only technology company would that autonomous database capabilities that yes sir yes okay so I know other sort of talk about it but you know Oracle I think talks about it more forcefully will dig into that and and report back Mike thanks so much for coming on the cube really appreciate it good stuff anything thank you very much all right and thank you for watching but right back with our next guest you're watching the cube we're here in Chicago covering the rebirth of Oracle consulting I'm Dave Volante look right back

>> Announcer: From Chicago, it's theCUBE, covering Oracle Transformation Day 2020. Brought to you by Oracle Consulting. >> Welcome back, everybody, to this special digital event coverage that theCUBE is looking into the rebirth of Oracle Consulting. Janet George is here, she's a group VP, autonomous for advanced analytics with machine learning and artificial intelligence at Oracle, and she's joined by Grant Gibson, who's a group VP of growth and strategy at Oracle. Folks, welcome to theCUBE, thanks so much for coming on. >> Thank you. >> Thank you. >> Grant, I want to start with you because you've got strategy in your title. I'd like to start big-picture. What is the strategy with Oracle, specifically as it relates to autonomous, and also consulting? >> Sure, so, I think Oracle has a deep legacy of strength in data, and over the company's successful history, it's evolved what that is from steps along the way. And if you look at the modern enterprise, an Oracle client, I think there's no denying that we've entered the age of AI, that everyone knows that artificial intelligence and machine learning are a key to their success in the business marketplace going forward. And while generally it's acknowledged that it's a transformative technology, and people know that they need to take advantage of it, it's the how that's really tricky, and that most enterprises, in order to really get an enterprise-level ROI on an AI investment, need to engage in projects of significant scope. And going from realizing there's an opportunity or realizing there's a threat to mobilizing yourself to capitalize on it is a daunting task for enterprise. Certainly one that's, anybody that's got any sort of legacy of success has built-in processes, has built-in systems, has built-in skill sets, and making that leap to be an autonomous enterprise is challenging for companies to wrap their heads around. So as part of the rebirth of Oracle Consulting, we've developed a practice around how to both manage the technology needs for that transformation as well as the human needs, as well as the data science needs to it. So there's-- >> So, wow, there's about five or six things that I want to (Grant chuckles) follow up with you there, so this is a good conversation. Janet, ever since I've been in the industry, when you're talking about AI, it's sort of start-stop, start-stop. We had the AI winter, and now it seems to be here. It almost feels like the technology never lived up to its promise, 'cause we didn't have the horsepower, the compute power, it didn't have enough data, maybe. So we're here today, it feels like we are entering a new era. Why is that, and how will the technology perform this time? >> So for AI to perform, it's very reliant on the data. We entered the age of AI without having the right data for AI. So you can imagine that we just launched into AI without our data being ready to be training sets for AI. So we started with BI data, or we started with data that was already historically transformed, formatted, had logical structures, physical structures. This data was sort of trapped in many different tools, and then, suddenly, AI comes along, and we say, take this data, our historical data, we haven't tested it to see if this has labels in it, this has learning capability in it. We just thrust the data to AI. And that's why we saw the initial wave of AI sort of failing, because it was not ready for AI, ready for the generation of AI, if you will. >> So, to me, this is, I always say this was the contribution that Hadoop left us, right? I mean, Hadoop, everybody was crazy, it turned into big data. Oracle was never that nuts about it, they just kind of watched, sat back and watched, obviously participated. But it gathered all this data, it created cheap data lakes, (laughs) which people always joke, turns into data swamps. But the data is oftentimes now within organizations, at least present, right. >> Yes, yes, yes. >> Like now, it's a matter of what? What's the next step for really good value? >> Well, basically, what Hadoop did to the world of data was Hadoop freed data from being stuck in tools. It basically brought forth this concept of platform. And platform is very essential, because as we enter the age of AI and we enter the petabyte range of data, we can't have tools handling all of this data. The data needs to scale. The data needs to move. The data needs to grow. And so, we need the concept of platform so we can be elastic for the growth of the data. It can be distributed. It can grow based on the growth of the data. And it can learn from that data. So that's the reason why Hadoop sort of brought us into the platform world. And-- >> Right, and a lot of that data ended up in the cloud. I always say for years, we marched to the cadence of Moore's law. That was the innovation engine in this industry. As fast as you could get a chip in, you'd get a little advantage, and then somebody would leapfrog. Today, it's, you've got all this data, you apply machine intelligence, and cloud gives you scale, it gives you agility. Your customers, are they taking advantage of that new innovation cocktail? First of all, do you buy that, and how do you see them taking advantage of this? >> Yeah, I think part of what Janet mentioned makes a lot of sense, is that at the beginning, when you're taking the existing data in an enterprise and trying to do AI to it, you often get things that look a lot like what you already knew, because you're dealing with your existing data set and your existing expertise. And part of, I think, the leap that clients are finding success with now is getting novel data types. You're moving from the zeroes and ones of structured data to image, language, written language, spoken language. You're capturing different data sets in ways that prior tools never could, and so, the classifications that come out of it, the insights that come out of it, the business process transformation that comes out of it is different than what we would have understood under the structured data format. So I think it's that combination of really being able to push massive amounts of data through a cloud product to be able to process it at scale. That is what I think is the combination that takes it to the next plateau for sure. >> So you talked about sort of we're entering the new era, age of AI. A lot of people kind of focus on the cloud as sort of the current era, but it really does feel like we're moving beyond that. The language that we use today, I feel like, is going to change, and you just started to touch on some of it, sensing, our senses, and the visualization, and the auditory, so it's sort of this new experience that customers are seeing, and a lot of this machine intelligence behind that. >> I call it the autonomous enterprise, right? >> Okay. >> The journey to be the autonomous enterprise. And when you're on this journey to be the autonomous enterprise, you need, really, the platform that can help you be. Cloud is that platform which can help you get to the autonomous journey. But the autonomous journey does not end with the cloud, or doesn't end with the data lake. These are just infrastructures that are basic, necessary, necessities for being on that autonomous journey. But at the end, it's about, how do you train and scale very large-scale training that needs to happen on this platform for AI to be successful? And if you are an autonomous enterprise, then you have really figured out how to tap into AI and machine learning in a way that nobody else has to derive business value, if you will. So you've got the platform, you've got the data, and now you're actually tapping into the autonomous components, AI and machine learning, to derive business intelligence and business value. >> So I want to get into a little bit of Oracle's role, but to do that, I want to talk a little bit more about the industry. So if you think about the way the industry seems to be restructuring around data, historically, industries had their own stack or value chain, and if you were in the finance industry, you were there for life, you know? >> Yes. >> You had your own sales channel, distribution, et cetera. But today, you see companies traversing industries, which has never happened before. You see Apple getting into content, and music, and there's so many examples, Amazon buying Whole Foods. Data is sort of the enabler there. You have a lot of organizations, your customers, that are incumbents, that they don't want to get disrupted. A big part of your role is to help them become that autonomous enterprise so they don't get disrupted. I wonder if you could maybe comment on how you're doing. >> Yeah, I'll comment, and then, Grant, you can chime in. >> Great. >> So when you think about banking, for example, highly regulated industry, think about agriculture, these are highly regulated industries. It is very difficult to disrupt these industries. But now you're looking at Amazon, and what does an Amazon or any other tech giant like Apple have? They have incredible amounts of data. They understand how people use, or how they want to do, banking. And so, they've come up with Apple Cash, or Amazon Pay, and these things are starting to eat into the market. So you would have never thought an Amazon could be a competition to a banking industry, just because of regulations, but they are not hindered by the regulations because they're starting at a different level, and so, they become an instant threat and an instant disruptor to these highly regulated industries. That's what data does. When you use data as your DNA for your business, and you are sort of born in data, or you've figured out how to be autonomous, if you will, capture value from that data in a very significant manner, then you can get into industries that are not traditionally your own industry. It can be the food industry, it can be the cloud industry, the book industry, you know, different industries. So that's what I see happening with the tech giants. >> So, Grant, this is a really interesting point that Janet is making, that, you mentioned you started off with a couple of industries that are highly regulated and harder to disrupt. You know, music got disrupted, publishing got disrupted, but you've got these regulated businesses, defense. Automotive hasn't been truly disrupted yet, so Tesla maybe is a harbinger. And so, you've got this spectrum of disruption. But is anybody safe from disruption? >> (laughs) I don't think anyone's ever safe from it. It's change and evolution, right? Whether it's swapping horseshoes for cars, or TV for movies, or Netflix, or any sort of evolution of a business, I wouldn't coast on any of it. And I think, to your earlier question around the value that we can help bring to Oracle customers is that we have a rich stack of applications, and I find that the space between the applications, the data that spans more than one of them, is a ripe playground for innovations where the data already exists inside a company but it's trapped from both a technology and a business perspective, and that's where, I think, really, any company can take advantage of knowing its data better and changing itself to take advantage of what's already there. >> The powerful people always throw the bromide out that data is the new oil, and we've said, no, data's far more valuable, 'cause you can use it in a lot of different places. Oil, you can use once and it's all you can do. >> Yeah. >> It has to follow the laws of scarcity. Data, if you can unlock it, and so, a lot of the incumbents, they have built a business around whatever, a factory or process and people. A lot of the trillion-dollar startups, that become trillionaires, you know who I'm talking about, data's at the core, they're data companies. So it seems like a big challenge for your incumbent customers, clients, is to put data at the core, be able to break down those silos. How do they do that? >> Mm, grating down silos is really super critical for any business. If it's okay to operate in a silo, for example, you would think that, "Oh, I could just be payroll and expense reports, "and it wouldn't matter if I get into vendor "performance management or purchasing. "That can operate as a silo." But anymore, we are finding that there are tremendous insights between vendor performance management and expense reports, these things are all connected. So you can't afford to have your data sit in silos. So grating down that silo actually gives the business very good performance, insights that they didn't have before. So that's one way to go. But another phenomena happens. When you start to grate down the silos, you start to recognize what data you don't have to take your business to the next level. That awareness will not happen when you're working with existing data. So that awareness comes into form when you grate the silos and you start to figure out you need to go after a different set of data to get you to new product creation, what would that look like, new test insights, or new capex avoidance, that data is just, you have to go through the iteration to be able to figure that out. >> And then it becomes a business problem, right? If you've got a process now where you can identify 75% of the failures, and you know the value of the other 25% of the failures, it becomes a simple investment. "How much money am I willing to invest "to knock down some portion of that 25%?" And it changes it from simply an IT problem or an expense management problem to the universal cash problem. >> To a business problem. >> But you still need a platform that has APIs, that allows you to bring in-- >> Yes, yes. >> Those data sets that you don't have access to, so it's an enabler. It's not the answer, it's not the outcome, in and of itself, but it enables the outcome. >> Yeah, and-- >> I always say you can't have the best toilet if your plumbing doesn't work, you know what I mean? So you have to have your plumbing. Your plumbing has to be more modern. So you have to bring in modern infrastructure, distributed computing, that, there's no compromise there. You have to have the right ecosystem for you to be able to be technologically advanced and a leader in that space. >> But that's kind of table stakes, is what you're saying. >> Stakes. >> So this notion of the autonomous enterprise, help me here. 'Cause I get kind of autonomous and automation coming into IT, IT ops. I'm interested in how you see customers taking that beyond the technology organization into the enterprise. >> Yeah, this is such a great question. This is what I've been talking about all morning. I think when AI is a technology problem, the company is at a loss. AI has to be a business problem. AI has to inform the business strategy. When companies, the successful companies that have done, so, 90% of our investments are going towards data, we know that, and most of it going towards AI. There's data out there about this. And so, we look at, what are these 90% of the companies' investments, where are these going, and who is doing this right, and who is not doing this right? One of the things we are seeing as results is that the companies that are doing it right have brought data into their business strategy. They've changed their business model. So it's not making a better taxi, but coming up with Uber. So it's not like saying, "Okay, I'm going to be "the drug manufacturing company, "I'm going to put drugs out there in the market," versus, "I'm going to do connected health." And so, how does data serve the business model of being connected health, rather than being a drug company selling drugs to my customers? It's a completely different way of looking at it. And so now, AI's informing drug discovery. AI is not helping you just put more drugs to the market. Rather, it's helping you come up with new drugs that will help the process of connected care. >> There's a lot of discussion in the press about the ethics of AI, and how far should we take AI, and how far can we take it from a technology standpoint, (laughs) long road map, there. But how far should we take it? Do you feel as though public policy will take care of that, a lot of that narrative is just kind of journalists looking for the negative story? Will that sort itself out? How much time do you spend with your customers talking about that, and what's Oracle's role there? Facebook says, "Hey, the government should figure this out." What's your sort of point of view on that? >> I think everybody has a role, it's a joint role, and none of us can give up our responsibilities. As data scientists, we have heavy responsibility in this area, and we have heavy responsibility to advise the clients on this area also. The data we come from, the past, has to change. That is inherently biased. And we tend to put data science on biased data with a one-dimensional view of the data. So we have to start looking at multiple dimensions of the data. We've got to start examining, I call it irresponsible AI, when you just simply take one variable, we'll start to do machine learning with that, 'cause that's not right. You have to examine the data. You've got to understand how much bias is in the data. Are you training a machine learning model with the bias? Is there diversity in the models? Is there diversity in the data? These are conversations we need to have. And we absolutely need policy around this, because unless our lawmakers start to understand that we need the source of the data to change, and if we look at the source of the data, and the source of the data is inherently biased or the source of the data has only a single representation, we're never going to change that downstream. AI's not going to help us there. So that has to change upstream. That's where the policy makers come into play, the lawmakers come into play. But at the same time, as we're building models, I think we have a responsibility to say, "Can we triangulate? "Can we build with multiple models? "Can we look at the results of these models? "How are these features ranked? "Are they ranked based on biases, sex, age, PII information? "Are we taking the PII information out? "Are we really looking at one variable?" Somebody failed to pay their bill, but they just failed to pay their bill because they were late, versus that they don't have a bank account and we classify them as poor on having no bank account, you know what I mean? So all this becomes part of responsible AI. >> But humans are inherently biased, and so, if humans are building algorithms-- >> That's right, that's right. >> There is the bias. >> So you're saying that through iteration, we can stamp out the bias? Is that realistic? >> We can stamp out the bias, or we can confirm the bias. >> Or at least make it transparent. >> Make it transparent. So I think that even if we can have the trust to be able to have the discussion on, "Is this data "the right data that we are doing the analysis on?" and start the conversation there, we start to see the change. >> Well, wait, so we could make it transparent, then I'm thinking, a lot of AI is black box. Is that a problem? Is the black box syndrome an issue, or are we, how would we deal with it? >> Actually, AI is not a black box. We, in Oracle, we are building our data science platform with an explicit feature called explainability of the model, on how the model came up with the features, what features it picked. We can rearrange the features that the model picked. So I think explainability is very important for ordinary people to trust AI. Because we can't trust AI. Even data scientists can't trust AI, to a large extent. So for us to get to that level where we can really trust what AI's picking, in terms of a model, we need to have explainability. And I think a lot of the companies right now are starting to make that as part of their platform. >> So that's your promise to clients, is that your AI will not be a black box. >> Absolutely, absolutely. >> 'Cause that's not everybody's promise. >> Yes. >> I mean, there's a lot of black box in AI, as you well know. >> Yes, yes, there is. If you go to open source and you start downloading, you'll get a lot of black box. The other advantage to open source is sometimes you can just modify the black box. They can give you access and you can modify the black box. But if you get companies that have released to open source, it's somewhat of a black box, so you have to figure out the balance between. You don't really have to worry too much about the black box if you can see that the model has done a pretty good job as compared to other models. If I triangulate the results of the algorithm, and the triangulation turns out to be reasonable, the accuracy and the r values and the matrixes show reasonable results, then I don't really have to worry if one model is too biased compared to another model. But I worry if there's only one dimension to it. >> Mm-hm, well, ultimately, to much of the data scientists' dismay, somebody on the business side is going to ask about causality. >> That's right. >> "Well, this is what "the model says, why is it saying that?" >> Yeah, right. >> Yeah. >> And, ethical reasons aside, you're going to want to understand why the predictions are what they are, and certainly, as you go in to examine those things, as you look at the factors that are causing the predictions and the outcomes, I think any sort of business should be asking those responsibility questions of everything they do, AI included, for sure. >> So, we're entering a new era, we kind of all agree on that. So I just want to throw a few questions out and have a little fun here, so feel free to answer in any order. So when do you think machines will be able to make better diagnoses than doctors? >> I think they already are making better diagnoses. I mean, there's so much, like, I found out recently that most of the very complicated cancer surgeries are done by machines, doctors just standing by and making sure that the machines are doing it well. And so, I think the machines are taking over in some aspects, I wouldn't say all aspects. And then there's the bedside manners, where you (laughs) really need the human doctor, and you need the comfort of talking to the doctor. >> Smiley face, please! (Janet laughs) >> That's advanced AI, to give it a better bedside manner. >> Okay, when do you think that driving and owning your own vehicle is going to be the exception rather than the rule? >> That, I think, is so far ahead, it's going to be very, very near future, because if you've ever driven in an autonomous car, you'll find that after your initial reservations, you're going to feel a lot more safer in an autonomous car. Because it's got a vision that humans don't. It's got a communication mechanism that humans don't. It's talking to all the fleets of cars. >> It's got a richer sense of data. >> It's got a richer sense of data, it's got a richer sense of vision, it's got a richer sense of ability to (snaps) react when a kid jumps in front of the car. Where a human will be terrified and not able to make quick decisions, the car can. But at the same time, we're going to have some startup problems. We're going to see AI misfire in certain areas, and insurance companies are gearing themselves up for that, 'cause that's just, but the data's showing us that we will have tremendously decreased death rates. That's a pretty good start to have AI driving our cars. >> You're a believer, well, and you're right, there's going to be some startup issues, because this car, the vehicle has to decide, "Do I kill that person who jumped in front of me, "or do I kill the driver?" Not kill, I mean, that's overstating-- >> Yeah. >> But those are some of the startup things, and there will be others. >> And humans, you don't question the judgment system for that. >> Yes. >> There's no-- >> Dave: Right, they're yelling at humans. >> Person that developed, right. It's treated as a one-off. But I think if you look back five years, where were we? You figure, the pace of innovation and the speed and the gaps that we're closing now, where are we going to be in five years? >> Yeah. >> You have to figure it's, I have an eight-year-old son, and I question if he's ever going to drive a car. >> Yeah. >> Yeah. >> How about retail? Do you think retail stores largely will disappear? >> Oh, I think retail, there will be a customer service element to retail, but it will evolve from where it's at in a very, very high-stakes rate, because now, with RFID, you know who's, we used to be invisible as we walked, we still are invisible as you walk into a retail store, even if you spend a lot of money in retail. And now, with buying patterns and knowing who the customer is, and your profile is out there on the Web, just getting a sense of who this person is, what their intent is walking into the store, and doing responsible AI, bringing value to that intent, not irresponsibly, that will gain the trust, and as people gain the trust. And then RFIDs, you're in the location, you're nearby, you'd normally buy the suit, the suit's on sale, bring it all together. So I think there's a lot of connective tissue work that needs to happen, but that's all coming together. >> Yeah, it's about the value-add and what the proposition to the customer is. If it's simply there as a place where you go and pick out something you already know what you're going to get, that store doesn't add value, but if there's something in the human expertise, or in the shared, felt sudden experience of being in the store, that's where you'll see retailers differentiate themselves. >> I like to shop still. (laughs) >> Yeah, yeah. >> You mentioned Apple Pay before. Well, you think traditional banks will lose control of the payment systems? >> They're already losing control of payment systems. If you look at, there was no reason for the banks to create Siri-like assistants. They're all over right now. And we started with Alexa first. So you can see the banks are trying to be a lot more customized, customer service, trying to be personalized, trying to really make you connect to them in a way that you have not connected to the bank before. The way that you connected to the bank is you knew the person at the bank for 20 years, or since when you had your first bank account. That's how you connected with the banks. And then you go to a different branch, and then, all of a sudden, you're invisible. Nobody knows you, nobody knows that you were 20 years with the bank. That's changing. They're keeping track of which location you're going to, and trying to be a more personalized. So I think AI is a forcing function, in some ways, to provide more value, if anything. >> Well, we're definitely entering a new era, the age of AI, the autonomous enterprise. Folks, thanks very much for a great segment, really appreciate it. >> Yeah, our pleasure, thank you for having us. >> Thank you for having us. >> You're welcome, all right, and thank you. And keep it right there, we'll be right back with our next guest right after this short break. You're watching theCUBE's coverage of the rebirth of Oracle Consulting. We'll be right back. (upbeat electronic music)

(upbeat music) >> Reporter: From Chicago, it's The Cube. Covering Oracle transformation date 2020. Brought to you by Oracle Consulting. >> Hi everybody, welcome back. You're watching theCUBE, we go out to the events we extract the signal from the noise. This is a very special digital event and we're really covering the transformation not only the industry, but the transformation of Oracle Consulting and its rebirth. Mike Owens is here Group VP of Cloud Advisory and GM of Oracle Elevate, which is a partnership that Oracle announced last Open World with Deloitte, and Don Schmidt is here, who is a Managing Director at Deloitte. Gents, good to see you, welcome. >> Good to be here Dave. >> So, Don I want to start with you. Transformation, right? Everybody talks about that, there's a lot of trends going on in the industry. What do you guys see as the big gestalt transformation that's going on? >> Yeah I think there's an inflection point right now. Everybody have been saying they want to get out their data centers. The leaves haven't really been taking place, right? They've been kind of moving in small bits. We're now at the point where large transformation at scale, of getting out of your data centers, is now here. So, we are here to try to help our clients move faster. How can we do this more effectively, cost efficiently, and get them out of these data centers so they can move on with their day to day business? >> So data centers is just not an efficient use of capital for your customers. >> No, no there's lots of ways to do this a lot faster, cheaper, and get on to innovation. Spend your money there, not on hardware, floor space, power cooling, those fun things. >> Well you guys are spending money on data centers though right? So this is a good business for you all. >> Mike: We do it on behalf of other customers though. Right? >> Yeah and that's what's happening right? My customers, they essentially want to take all this IT labor cost and shift it into R&D get them on your backs and your backs right? Is this that what you see it? You know where are we in terms of that? I mean it started ten plus years ago but it really has started to uptake right? What's driving that? What's the catalyst there? >> You know so from my perspective, I've been doing this a while. A lot of it is either organizations are driving costs or what you're also seeing is IT organizations are no longer the utility in the organization and taking the orders, you're using them to try to top line value, but to do that, they actually have to take their business and change the model of it, so they can take that money and reinvest it in what Don had talked about, investment or continuous investment. So you're starting to hit those inflection points, you know years ago a CIO would be in his job for 15, 20 years, the average tenure for a CIO is you know three to five years on average, and it's because if they're not driving innovation or driving top line growth with an organization, organizations are now starting to flip that around so you're seeing a huge inflection point, with organizations really looking for IT not to be just a back office entity anymore, to truly drive them they have to transform that back to Don's point, because that inflection point, this large data center move over is a good sort of lever to kind of get them and really use it as opportunity to transform their organization. >> And the transformations are occurring, you know within industries, but at different pace. I mean some industries have transformed radically. You think about Ride shares, and digital music and the like others are taking more time, financial services, health care, they're riskier businesses, and you know there's more government in public policy so what do you see in terms of the catalyst for transformation and is there any kind of discernible, industry variance? >> Yeah there definitely is and he's mentioned some of the more start-up kind of organizations where Cloud was right for them at the early stages. These other organizations that have built these large application stacks and have been there for years, it's scary for them to say, "Let me take this big set of equipment and applications, and move it to the Cloud." It's a big effort. Starting from scratch with start-ups, that's a little different story right? So we are kind of at a different point, there are different stages within different industries, some are faster adopters than some of the others with government regulations and some of the technologies that have to kind of catch up to be able to provide those services. >> Do people generally want to take their sort of mission-critical apps which are largely running often on Oracle infrastructure database, they want to move that into the Cloud but do they want to bring that sort of Cloud-operating model to their on-prem and maybe reduce their overall data center footprint but preserve some of that? What are you guys seeing? >> So, two different probably viewpoints. So my viewpoint is, depends on the organization, depends on the regulatory they have, and there's a lot of factors in there. But I would say, as a standard organization would take their journey, mission-critical systems are historically not the first one in there. 'Cause back to the point of changing the operating model the way you want to do business and be effective, you don't go with the crown jewels first, historically, take some other work loads learn how to work in that operating model, how you're doing things change and then you evolve some of those pieces over time. There are organizations that basically, pull the band-aid off and just go right into it, right? But a lot of large enterprises sort of that's why we talk about Cloud as a journey, right? You take this journey you have to make the journey based on what's going on back what Don had talked about the regulatory requirements in history are the right controls in place for what they need at that point. If not, okay so what's an interim step to the journey? Could you bring Cloud in those capabilities on-prem and then have some of the other stuff off-prem? So it's really situational dependent, and we actually walk a customer through and now Don's organization does the same thing. You walk them through what makes best for their journey for where they're at in the industry and what they have today and what they're trying to achieve. >> So Don Deloitte doesn't just do IT it does business transformation, right? So it's like a chicken and egg, let's say that what comes first? The chicken or the egg? The IT transformation or the business transformation? >> I don't think it's an or it's an and. So have the total conversation of where's your Cloud journey for your entire enterprise, and then decide how that's going to be played out in both in IT and in the business. How the joint conversation from an enterprise perspective. >> So let's talk a little bit about the partnership, to your very well known brands, you guys get together, so what was the sort of impetus to get together? How's it going? Give us the update on that front. >> Yeah you know so from Oracle standpoint, Oracle has been really technology focused. It was really created by technologists, right? And back to the point of what we're trying to do with the Cloud and trying to do larger transformation, those aren't some of the skills that we have. We've been bringing in some of those skills in DNA, but if you look at it as why would you try to recreate this situation? Why would you not partner with an organization who does large business transformation like Deloitte? Right? And so the impetus of that is, how do we take the technology with the business transformation, pull that together and back of the one plus one equals three for my customer, right? That's what they really want, so how do we actually scale that into really big things and get big outcomes for our customers? Our partnership is not about trying to take a bunch of customers and move a couple application work loads. Our job, what we're really charted to do is make huge transformational leaps for our customers, using the combined capabilities of the two organizations. So this it's a hug paradigm for us to kind of do this. >> And in our collaboration with the two organizations just the opposite from what Mike just said right? So Deloitte wasn't really big in big IT, right? Business led transformations kind of what Deloitte's been known for, along with our cyber practice, and so we needed the deep skills of the technical experts. >> Right, so take me through what transformation engagement looks like. They don't call you up and say, "Hey want to buy me some transformation." Right? Where does it start? Who are the stake holders? How long does it take? I mean it could be multi year, I presume and never ends maybe but you want to get to business value first, so let's shorten up the time frame. Take me through typical engagement. Typical I know in quotes. And then, how long like take me through the point at which you start to get business value. What do I got to do to get there? >> Yeah so we see two different spectrums on a transformation. And it really aligns to what are your objectives. Do you just need to get out of the data center because you're on archaic dying hardware? Or do you want to take that, take your time and make a little bit more of a transformation journey? Or do you want to play somewhere in the middle of that spectrum? But on either one of those we'll come in and we'll do a discovery conversation. We'll understand what's in your data center, understand what the age or the health of your data center is, help the customers through, business case, TCO, how fast or how slow that journey needs to be for them, crave look our wave groups of how fast and we're going to sequence those over time to get out of their data center. In parallel we're going to be doing as Mike was saying running all the operational aspects. So while we're doing that discovery, we want to start standing up their Cloud center of excellence. Getting Cloud operations into the organization is a different skill set for IT to have, right? They're going to need to retrain themselves, retool themselves in the world of Cloud. So we kind of do that in parallel and then what we want to do is when we start a project, we want to start with a little POC or small little group of safe applications that we can prove how the model works. Move those into the Cloud, and then what we want to do is we want to scale at it, its large pace, right? Get the IT savings, get the cost cuts out of the organization. >> So I cleaned out my barn this weekend and the first thing I did is I got a dumpster. So I could throw some stuff out. So, is that part of the equation like getting rid of stuff? Is that part of the assessment? You know what's not delivering value that you can live without? >> Absolutely right, so there is kind of things that are just going to not go to Cloud, right? No longer need it, it's just laying around in the side, just get rid of that and move forward. >> And earlier one you'll see there's models depends you hear there's the 6 Rs, the 7 Rs and it's really the journey to Cloud it's almost you look at your status is it going to get re-platformed, is it going to get re-hosted, is it going to get retired back to your point. And if it's had something that's an appliance, right? That's something you're not going to put out to Cloud. Okay keep that in your data center. I have something that's so old, I hope it dies in the next two years. Don't spend the money move it to Cloud, let it die over the next two years. So back to the point, you kind of take this discovery and you go, where do things fall on the spectrum? And each one actually has a destination and a lever that you're going to pull, right? And if you're going to retire things okay so out of the business case, those are status quo for the next you're going to kill it over three years, right? Re-platform re-host means different things that they're going to take, right? Whether they do just to infrastructure or take advantage of PaaS or they'll go, "I'm going to blow up the entire application who directed to Cloud native services." Right? As you go through that journey you kind of map that out for them through the discovery process, and that tells you how much value you're going to get based on what you're going to do. >> But boy, this starts to get deep I mean as you used to peel the onions. So you just described what I would think of as wave 1. And then as you keep peeling you got the applications, you got the business process, you might have, reorganizations that's really where you guys have expertise, right? >> Well combined right? 'Cause yeah we're on the organizational side of things, but yeah there's a lot of things you have to sort through, right? And that's where the combined Elevate program really synergizes itself around the tools that we have. We both have tools that will help make sure we get this right, right? Deloitte has a product called Atadata, Oracle has a product called Soar, they married together properly into this transformational journey, to make sure we get the discovery done right and we get the migrations done right as well. >> Well you also have a lot of different stake holders, than you know, let's face it P&L Managers are going to try to hold on to their P&L. So you've got to bring in the senior executives. Clearly the CIOs involved is the CFO, CSWE. Who are the stake holders that you bring together in the room to kick this thing off? >> Depends on the message and depends on the outcome right? So if it's I need to get out of my data center, my data center strategy, historically the CIO. If it's there's an overall cost reduction and I want to re-implement my cost into innovating the business, sometimes that starts the CEO, CFO levels, right? >> Dave: Sure. >> So depends on that one but it is absolutely, back to your point of, the people want to hold their P&L huggers or kind of hold the cost or whatever. And one of the things, if you're not having the right conversations with people at the right level, the analogy that I've used for years is sometimes you're talking to a turkey about thanksgiving, right? So if you're trying to actually help transform and the entity is feeling that they're impacted by that negatively, even though there's a senior direction, so working through the right levels the organization to make sure you're showing how you're enabling them, it's key it's part of this journey. Helping them understand the future and how it's valuable, 'cause otherwise you'll get people that push back, even though it's the right thing for the company. We've seen that time and time again. >> Well it's potentially a huge engagement, so do you guys have specific plays or campaigns that you know I can do to get started maybe do a little test case, any particular offerings that-- >> Mike: I think-- >> Do you want to talk about the campaigns? >> So ]s under the program of Elevate, we've got a couple of campaigns. So the biggest one we've been talking about is around the data center transformation, so that's kind of the first campaign that we're working on together. The next one is around moving JD Edwards specific applications to Oracle's Cloud. And then the third one is around our analytics offering that Deloitte has and how we're going to market through to general put that in as well. Those are our three major campaigns. >> So data center transformation we hit it pretty hard. I'm sorry the third one was Cloud-- >> Analytics. >> Sorry analytics right okay which is kind of an instate that everybody wants to get to. The JDE migration, so you've got what, situations where people have just, the systems. >> And I would say it's actually more of a JDE modernization, alright? >> Okay. >> So you have an organization, right? They may have a JDE or JD Edwards instance that's really it's older, they're maybe on version nine or something like that, they don't want to go all the way to SaaS 'cause they can't simplify the business processes. They need to do that, but they also want to take advantage of the higher level capabilities of Cloud computing, right? IOT, Mobil, et cetera right? So as a modernization, one of the things we're doing is an approach together we work with customers depending where they're going and go hey great, you can actually modernize by taking up this version of JDE through an upgrade process, but that allows you then to move it over to Oracle Cloud infrastructure, which allows you to actually tap into all those platform services, the IOT and stuff like that to take to the next level. Then you can actually do the higher level analytics that sits on top of that. So it's really a journey where the customer wants to get. There's a various kind of four major phases that we can do or entry points with the customer on the JDE modernization, we kind of work them through. So that's a skill of some of the capabilities that Deloitte has as a deep JDE, and as well as Oracle Consulting, and we actually are going to market that together, matter of fact, we're even at conferences together, talking about our approaches here and our future. >> Okay. So that'll allow you to get to a Cloud PaaS layer that'll allow you to sort of modernize that and get out of the sort of technical debt that's built up. >> Where customers are not ready to maybe move their entire data center, right? This gets them on the journey, right? That's the important pieces. We want to get them on the Cloud journey. >> In the analytics campaign, so it seems to me that a lot of companies don't have their data driven, they want to be data driven, but they're not there yet. And so, their data's in silos and so I would imagine that that's all helping them understand where the data is, breaking down, busting down those silos and then actually putting in sort of an analytics approach that drives their, drives us from data to insights. Is that fair? >> Yeah fair. Yeah it's not just doing reporting and dashboards it's actually having KPI-driven insights into their information and their data within their organizations. And so Deloitte has some pre-configured applications for HR, finance, and supply chains. >> So the existing EDW for example would be fitter into that, but then you've got agile infrastructure and processes that you're putting in place, bringing in AI and machine intelligence. That's kind of the future state that you're in. >> And it also has, they look at the particular that's one of the things we like about the other stuff that Deloitte has done. They've actually done the investment of the processes back into those particular business units that they do and actually have KPI-driven ones it prebuilt configurations that actually adds value. These are the metrics that should be driving an HR organization. Here's the metrics that should be driving finance. So rather than doing better analytics, hey help me write my report better. No, we're going to help you transform the way you should be running your business from a business financial transformation, that's why the partnership with Deloitte. So it's really changing the game of true analytics, not better BI. >> Right okay, guys, two power houses. Thanks so much for explaining in The Cube and to our audience, appreciate it. (mumbling) >> Alright, thank you everybody for watching we'll be right back with our next guest you're watching The Cube, from Chicago. We'll be right back right after the short break. (upbeat music)

(upbeat music) >> Oracle continues to pursue a multi-mode converged database strategy. The premise of this all in one approach is to make life easier for practitioners and developers. And the most recent example is the Oracle database API for MongoDB, which was announced today. Now, Oracle, they're not the first to come out with a MongoDB compatible API, but Oracle hopes to use its autonomous database as a differentiator and further build a moat around OCI, Oracle Cloud Infrastructure. And with us to talk about Oracle's MongoDB compatible API is Gerald Venzl, who's a distinguished Product Manager at Oracle. Gerald was a guest along with Maria Colgan on the CUBE a while back, and we talked about Oracle's converge database and the kind of Swiss army knife strategy, I called it, of databases. This is dramatically different. It's an approach that we see at the opposite end of the the spectrum, for instance, from AWS, who, for example, goes after the world of developers with a different database for every use case. So, kind of picking up from there, Gerald, I wonder if you could talk about how this new MongoDB API adds to your converged model and the whole strategy there. Where does it fit? >> Yeah, thank you very much, Dave and, by the way, thanks for having me on the CUBE again. A pleasure to be here. So, essentially the MongoDB API to build the compatibility that we used with this API is a continuation of the converge database story, as you said before. Which is essentially bringing the many features of the many single purpose databases that people often like and use, together into one technology so that everybody can benefit from it. So as such, this is just a continuation that we have from so many other APIs or standards that we support. Since a long time, we already, of course to SQL because we are relational database from the get go. Also other standard like GraphQL, Sparkle, et cetera that we have. And the MongoDB API, is now essentially just the next step forward to give the developers this API that they've gotten to love and use. >> I wonder if you could talk about from the developer angle, what do they get out of it? Obviously you're appealing to the Mongo developers out there, but you've got this Mongo compatible API you're pouting the autonomous database on OCI. Why aren't they just going to use MongoDB Atlas on whatever cloud, Azure or AWS or Google Cloud platform? >> That's a very good question. We believe that the majority of developers want to just worry about their application, writing the application, and not so much about the database backend that they're using. And especially in cloud with cloud services, the reason why developers choose these services is so that they don't have to manage them. Now, autonomous database brings many topnotch advanced capabilities to database cloud services. We firmly believe that autonomous database is essentially the next generation of cloud services with all the self-driving features built in, and MongoDB developers writing applications against the MongoDB API, should not have to hold out on these capabilities either. It's like no developer likes to tune the database. No developer likes to take a downtime when they have to rescale their database to accommodate a bigger workload. And this is really where we see the benefit here, so for the developer, ideally nothing will change. You have MongoDB compatible API so they can keep on using their tools. They can build the applications the way that they do, but the benefit from the best cloud database service out there not having to worry about any of these package things anymore, that even MongoDB Atlas has a lot of shortcomings still today, as we find. >> Of cos, this is always a moving target The technology business, that's why we love it. So everybody's moving fast and investing and shaking and jiving. But, I want to ask you about, well, by the way, that's so you're hiding the underlying complexity, That's really the big takeaway there. So that's you huge for developers. But take, I was talking before about, the Amazon's approach, right tool for the right job. You got document DB, you got Microsoft with Cosmos, they compete with Mongo and they've been doing so for some time. How does Oracle's API for Mongo different from those offerings and how you going to attract their users to your JSON offering. >> So, you know, for first of all we have to kind of separate slightly document DB and AWS and Cosmos DB in Azure, they have slightly different approaches there. Document DB essentially is, a document store owned by and built by AWS, nothing different to Mongo DB, it's a head to head comparison. It's like use my document store versus the other document store. So you don't get any of the benefits of a converge database. If you ever want to do a different data model, run analytics over, etc. You still have to use the many other services that AWS provides you to. You cannot all do it into one database. Now Cosmos DB it's more in interesting because they claim to be a multi-model database. And I say claim because what we understand as multi-model database is different to what they understand as multimodel database. And also one of the reasons why we start differentiating with converge database. So what we mean is you should be able to regardless what data format you want to store in the database leverage all the functionality of the database over that data format, with no trade offs. Cosmos DB when you look at it, it essentially gives you mode of operation. When you connect as the application or the user, you have to decide at connection time, how you want, how this database should be treated. Should it be a document store? Should it be a graph store? Should it be a relational store? Once you make that choice, you are locked into that. As long as you establish that connection. So it's like, if you say, I want a document store, all you get is a document store. There's no way for you to crossly analyze with the relational data sitting in the same service. There's no for you to break these boundaries. If you ever want to add some graph data and graph analytics, you essentially have to disconnect and now treat it as a graph store. So you get multiple data models in it, but really you still get, one trick pony the moment you connect to it that you have to choose to. And that is where we see a huge differentiation again with our converge database, because we essentially say, look, one database cloud service on Oracle cloud, where it allows you to do anything, if you wish to do so. You can start as a document store if you wish to do so. If you want to write some SQL queries on top, you can do so. If you want to add some graph data, you can do so. But there's no way for you to have to rewrite your application, use different libraries and frameworks now to connect et cetera, et cetera. >> Got it. Thank you for that. Do you have any data when you talk to customers? Like I'm interested in the diversity of deployments, like for instance, how many customers are using more than one data model? Do for instance, do JSON users need support for other data types or are they happy to stay kind of in their own little sandbox? Do you have any data on that? >> So what we see from the majority of our customers, there is no such thing as one data model fits everything. So, and it's like, there again we have to differentiate the developer that builds a certain microservice, that makes happy to stay in the JSON world or relational world, or the company that's trying to derive value from the data. So it's like the relational model has not gone away since 40 years of it existence. It's still kicking strong. It's still really good at what it does. The JSON data model is really good in what it does. The graph model is really good at what it does. But all these models have been built for different purposes. Try to do graph analytics on relational or JSON data. It's like, it's really tricky, but that's why you use a graph model to begin with. Try to shield yourself from the organization of the data, how it's structured, that's really easy in the relational world, not so much when you get into a document store world. And so what we see about our customers is like as they accumulate more data, is they have many different applications to run their enterprises. The question always comes back, as we have predicted since about six, seven years now, where they say, hey, we have all this different data and different data formats. We want to bring it all together, analyze it together, get value out of the data together. We have seen a whole trend of big data emerge and disappear to answer the question and didn't quite do the trick. And we are basically now back to where we were in the early 2000's when XML databases have faded away, because everybody just allowed you to store XML in the database. >> Got it. So let's make this real for people. So maybe you could give us some examples. You got this new API from Mongo, you have your multi model database. How, take a, paint a picture of how customers are going to benefit in real world use cases. How does it kind of change the customer's world before and after if you will? >> Yeah, absolutely. So, you know the API essentially we are going to use it to accept before, you know, make the lives of the developers easier, but also of course to assist our customers with migrations from Mongo DB over to Oracle Autonomous Database. One customer that we have, for example, that would've benefited of the API several a couple of years ago, two, three years ago, it's one of the largest logistics company on the planet. They track every package that is being sent in JSON documents. So every track package is entries resembled in a JSON document, and they very early on came in with the next question of like, hey, we track all these packages and document in JSON documents. It will be really nice to know actually which packages are stuck, or anywhere where we have to intervene. It's like, can we do this? Can we analyze just how many packages get stuck, didn't get delivered on, the end of a day or whatever. And they found this struggle with this question a lot, they found this was really tricky to do back then, in that case in MongoDB. So they actually approached Oracle, they came over, they migrated over and they rewrote their applications to accommodate that. And there are happy JSON users in Oracle database, but if we were having this API already for them then they wouldn't have had to rewrite their applications or would we often see like worry about the rewriting the application later on. Usually migration use cases, we want to get kind of the migration done, get the data over be running, and then worry about everything else. So this would be one where they would've greatly benefited to shorten this migration time window. If we had already demo the Mongo API back then or this compatibility layer. >> That's a good use case. I mean, it's, one of the most prominent and painful, so anything you could do to help that is key. I remember like the early days of big data, NoSQL, of course was the big thing. There was a lot of confusion. No, people thought was none or not only SQL, which is kind of the more widely accepted interpretation today. But really, it's talking about data that's stored in a non-relational format. So, some people, again they thought that SQL was going to fade away, some people probably still believe that. And, we saw the rise of NoSQL and document databases, but if I understand it correctly, a premise for your Mongo DB API is you really see SQL as a main contributor over Mongo DB's document collections for analytics for example. Can you make, add some color here? Are you seeing, what are you seeing in terms of resurgence of SQL or the momentum in SQL? Has it ever really waned? What's your take? >> Yeah, no, it's a very good point. So I think there as well, we see to some extent history repeating itself from, this all has been tried beforehand with object databases, XML database, et cetera. But if we stay with the NoSQL databases, I think it speaks at length that every NoSQL database that as you write for the sensor you started with NoSQL, and then while actually we always meant, not only SQL, everybody has introduced a SQL like engine or interface. The last two actually join this family is MongoDB. Now they have just recently introduced a SQL compatibility for the aggregation pipelines, something where you can put in a SQL statement and that essentially will then work with aggregation pipeline. So they all acknowledge that SQL is powerful, for us this was always clear. SQL is a declarative language. Some argue it's the only true 4GL language out there. You don't have to code how to get the data, but you just ask the question and the rest is done for you. And, we think that as we, basically, has SQL ever diminished as you said before, if you look out there? SQL has always been a demand. Look at the various developer surveys, etc. The various top skills that are asked for SQL has never gone away. Everybody loves and likes and you wants to use SQL. And so, yeah, we don't think this has ever been, going away. It has maybe just been, put in the shadow by some hypes. But again, we had the same discussion in the 2000's with XML databases, with the same discussions in the 90's with object databases. And we have just frankly, all forgotten about it. >> I love when you guys come on and and let me do my thing and I can pretty much ask any question I want, because, I got to say, when Oracle starts talking about another company I know that company's doing well. So I like, I see Mongo in the marketplace and I love that you guys are calling it out and making some moves there. So here's the thing, you guys have a large install base and that can be an advantage, but it can also be a weight in your shoulder. These specialized cloud databases they don't have that legacy. So they can just kind of move freely about, less friction. Now, all the cloud database services they're going to have more and more automation. I mean, I think that's pretty clear and inevitable. And most if not all of the database vendors they're going to provide support for these kind of converged data models. However they choose to do that. They might do it through the ecosystem, like what Snowflake's trying to do, or bring it in the house themselves, like a watch maker that brings an in-house movement, if you will. But it's like death and taxes, you can't avoid it. It's got to happen. That's what customers want. So with all that being said, how do you see the capabilities that you have today with automation and converge capabilities, How do you see that, that playing out? What's, do you think it gives you enough of an advantage? And obviously it's an advantage, but is it enough of an advantage over the specialized cloud database vendors, where there's clearly a lot of momentum today? >> I mean, honestly yes, absolutely. I mean, we are with some of these databases 20 years ahead. And I give you concrete examples. It's like Oracle had transaction support asset transactions since forever. NoSQL players all said, oh, we don't need assets transactions, base transactions is fine. Yada, yada, yada. Mongo DB started introducing some transaction support. It comes with some limits, cannot be longer than 60 seconds, cannot touch more than a thousand documents as well, et cetera. They still will have to do some catching up there. I mean, it took us a while to get there, let's be honest. Glad We have been around for a long time. Same thing, now that happened with version five, is like we started some simple version of multi version concurrency control that comes along with asset transactions. The interesting part here is like, we've introduced this also an Oracle five, which was somewhere in the 80's before I even started using Oracle Database. So there's a lot of catching up to do. And then you look at the cloud services as well, there's actually certain, a lot of things that we kind of gotten take, we've kind of, we Oracle people have taken for granted and we kind of keep forgetting. For example, our elastic scale, you want to add one CPU, you add one CPU. Should you take downtime for that? Absolutely not. It's like, this is ridiculous. Why would you, you cannot take it downtime in a 24/7 backend system that runs the world. Take any of our customers. If you look at most of these cloud services or you want to reshape, you want to scale your cloud service, that's fine. It's just the VM under the covers, we just shut everything down, give you a VM with more CPU, and you boot it up again, downtown right there. So it's like, there's a lot of these things where we go like, well, we solved this frankly decades ago, that these cloud vendors will run into. And just to add one more point here, so it's like one thing that we see with all these migrations happening is exactly in that field. It's like people essentially started building on whether it's Mongo DB or other of these NoSQL databases or cloud databases. And eventually as these systems grow, as they ask more difficult questions, their use cases expand, they find shortcomings. Whether it's the scalability, whether it's the security aspects, the functionalities that we have, and this is essentially what drives them back to Oracle. And this is why we see essentially this popularity now of pendulum swimming towards our direction again, where people actually happily come over back and they come over to us, to get their workloads enterprise grade if you like. >> Well, It's true. I mean, I just reported on this recently, the momentum that you guys have in cloud because it is, 'cause you got the best mission critical database. You're all about maps. I got to tell you a quick story. I was at a vertical conference one time, I was on stage with Kurt Monash. I don't know if you know Kurt, but he knows this space really well. He's probably forgot and more about database than I'll ever know. But, and I was kind of busting his chops. He was talking about asset transactions. I'm like, well with NoSQL, who needs asset transactions, just to poke him. And he was like, "Are you out of your mind?" And, and he said, look it's everybody is going to head in this direction. It turned out, it's true. So I got to give him props for that. And so, my last question, if you had a message for, let's say there's a skeptical developer out there that's using Mongo DB and Atlas, what would you say to them? >> I would say go try it for yourself. If you don't believe us, we have an always free cloud tier out there. You just go to oracle.com/cloud/free. You sign up for an always free tier, spin up an autonomous database, go try it for yourself. See what's actually possible today. Don't just follow your trends on Hackernews and use a set study here or there. Go try it for yourself and see what's capable of >> All right, Gerald. Hey, thanks for coming into my firing line today. I really appreciate your time. >> Thank you for having me again. >> Good luck with the announcement. You're very welcome, and thank you for watching this CUBE conversation. This is Dave Vellante, We'll see you next time. (gentle music)

(bright upbeat music) >> Hi well, this is Dave Vellante. We're digging deeper into the world of database. You know, there are a lot of ways to skin a cat and different vendors take different approaches and we're reaching out to the technologists to get their perspective on the major trends that they're seeing in the market, 'cause we want to understand the different ways in which you can solve problems. So look, if you have thoughts and the technical chops on this topic, I'd love to interview you. Just ping me at at DVellante, on Twitter, a lot of ways to get ahold of me. Anyway, we recently spoke with Andrew Mendelsohn, who is Oracle's EVP and he's responsible for database server technologies. And we talked a lot about Oracle's ADW, Autonomous Data Warehouse. And we looked at the cloud database strategy that Oracle is taking and the company's plans and how they're different maybe from other solutions in the marketplace, but I wanted to dig deeper. And so today we have two members of Mendelsohn's team on The Cube, and we're going to probe a little bit. George Lumpkin, is the Vice President of Autonomous Data Warehouse. And Neil Mendelson is the VP of Modern Data Warehouse, that business for Oracle. They're both 20-year veterans of Oracle. When I reached out to Steve Savannah, who's a colleague of mine for many years, he's always telling me how great Oracle is relative to the competition. So I said, okay, come on The Cube and talk about this, give me your best people. And he said, whatever these two don't know about cloud data warehouse, it isn't worth knowing anyway. So with that said gentlemen, welcome to The Cube. Thanks so much for coming on. >> Thank you. >> Hey, glad to be here. >> So George, let's start with you. And maybe we could recap for some of the viewers who might not be familiar with the interview that I did with Andy. In your words, what exactly is an Autonomous Data Warehouse? Is this cloud native? Is it an Oracle buzzword? What is it? >> Well, I mean, Autonomous Data Warehouse is Oracle's cloud data warehouse. It's a service that built to allow business users to get more value from their data. That's what the cloud data warehouse market is. Autonomous Data Warehouse is absolutely cloud native. This is a huge misconception that people might have when they first sort of hear about something, this service because they think this is a Oracle database, right? Oracle makes databases. This is the same old database I knew from 10 years ago. And that's absolutely not true. We built a cloud native service or data warehousing built it with cloud features. You know, if your understanding of the cloud data warehouse market is based upon how you thought things look 10 years ago, like Snowflake wouldn't have even existed, right? You can't base your understanding of Oracle based upon that. We have a modern service that's highly elastic, provides cloud capabilities like online patching and it's fully autonomous. It's really built the business users so they don't need to worry about administering their database. >> So I want to come back and actually ask you some questions about that, but let me follow up and talk about some of the evolution of the ADW. And where did you start? I think it was 2018, maybe where you came from, where you are today, maybe you can take us through the technological progression and maybe the path you took to get here. >> And so 2018, was when we released the service and made generally available, but of course, you know we started much earlier than that. And this was started within my product management team, and other organization. So we really sat down with a blank sheet of paper and we said, what should the data warehouse in the cloud look like? You know, let's put aside everything that Oracle does for its on-prem customers and think about how the cloud should be different. And the first thing that we said was, well, you know, if Oracle writes the database software, and Oracle builds its own hardware, and Oracle has created its own cloud, why do we need customers to manage a database? And that's where the idea of autonomous database came from. That Oracle is managing the entire ecosystem. And therefore we built a database that we believe it's far and away the simplest to use simplest data warehouse in the market. And that's been our focus since we started with 2018. And that continues to be our focus, looking at more ways that we can make an Autonomous Data Warehouse as simpler and easier for business users to get more value out of their data. >> Awesome, one more question. And actually Neil, you might want to chime in on this as well. So just from a technical perspective, you know forget the marketing claims and all the BS. How do you compare ADW to the so-called born in the cloud data warehouses? You mentioned Snowflake, you know Redshift, is Redshift born in the cloud. Well, it was par XL but Amazon's done some good work around Redshift. I think big query is maybe probably a better example 'cause it was, you know, like Snowflake started in the cloud but how do you compare ADW to some of these other so-called born in the cloud data warehouses? >> I think part of this, you mentioned Redshift wasn't important in the cloud. It was, you know, a code base taken from a prior company that was on-premise company. So they adapted it to the cloud, right? And you know, we have done, as George said, much of the same, which is, you know, our starting point was not you know another company's code base, but our starting point was our own code base. But as George said, it's less about the starting point and it's more about where you envision the end point, right? Which is that, you know, whatever your starting point is, I think we have a fundamental different view of the endpoint. Amazon talks about how they're literally built for you know, a cloud built for developers, right? You know, builders, right? And you know Oracle wasn't first in the infrastructure business, we entered through applications business. And all of a sudden, you know we began taking on 100s of 1000s and 100s of even more customers that were SAS customers. Underneath was the database and all the infrastructure. One of the things that we took away from that was that we couldn't possibly hire enough people DBA, to manage all the infrastructure below our applications customers. So one of the things that influenced this is that, you know customers expect SAS applications to just take care of themselves, right? So we had to essentially modify the infrastructure to allow it to do so as well, right? And we're bringing that capability to those people who, you know, may or may not have an application, but their interest is, you know more of this self-service agility type of aspect. >> So it seems to me and Georgia was sort of alluding to this before. I mean, when you mentioned Snowflake a couple of times, and then Neil, something you just said, I'm going to pick up on is you've been around for a long time. And you know, when I talked to the Snowflake people, they know Oracle, a lot of them came from Oracle. They understand I think how you can't just build Oracle overnight and build in the capabilities that Oracle has and the recovery. And you talk to customers and you know you are the gold standard of, you know especially mission critical databases, so I get that. But now you just sort of hit on it, is it takes a lot of people and skill to run the database. So that's the problem that you're saying you were attacking, is that, am I getting that right? >> Right, right, so the people that you talked about who originally built Snowflake came from Oracle, but they came from Oracle more than a decade ago. So their context is over a decade old, right? In the meantime, we've been busy, you know building a economies and many other capabilities, right? Their view of Oracle is that view that was back more than 10 years ago, right? They're still adding capability. So a really good example of this illustration is Oracle as you said, it's the most capable system that's out there and has been for many years. We've been focusing on how do we simplify that and how do we use machine learning embedded within the system itself? Because core to the concept of autonomous is that inside, is this machine learning system that's continually improving, right? That's the whole notion. Where in Snowflakes case, they're still adding functionality. Last year, they added masking which you know functionality they didn't have, but when they added the capability, they added it without, you know, the ability for a business user to actually take advantage of it. There's no capability for a business user to actually find the information that needs to be masked. And then after the information is found, you require a technical person to actually implement the mask. In Oracle's case, we've had masking and those capabilities for a long time, our focus was to be able to provide a simple tool that a business user can use that doesn't need technical or security experience. Find the data that needs to be masked PII data, and then hit a button and have it masked for you. So, you know, they're still, you know, without this notion of a strategy to move toward the system to heal itself and to manage itself, they're just going to continue. As they continue to add more capability, they will in turn add more complexity. What we're trying to do is take complexity out while others are adding it in, its an ironic twist. >> It is an ironic twist. It is interesting to look at it. And I don't want to make this about Snowflake. But I mean, Hey, I like what they're doing. I like them. I know the management, they're growing like crazy and you know and the customers tell me, hey, this is really simple. And it's simple by design. I mean, to your point over time it's going to get, you know, more and more complex. I was talking to Andy, I think it was Andy. He was saying, you know, they've got the different sizes you've got to shape some, you know, they call it t-shirt sizes. And I was like, okay, I got a small, I got a medium and a large, maybe that's okay. But you guys would say, we give more granular you know, a scaling, I guess is the point there, right? I mean George, I don't know if you can comment on that. It just a different strategy. You've got a company that was founded well, I guess, 2015 versus one that was founded in 1977. So you would think the latter has, you know way more function than the former, but George, anything you'd add to this conversation? >> Yeah, I mean, I'm always amazed that there are these database systems that are perceived as cloud native and they do things like sell you database sizes by t-shirt sizes, as you described. I mean, if you look at Snowflake, it's small, medium, large extra large too extra large, but they're all factors of two. You're getting a size of your database of two, four, eight, six, 32, et cetera. Or if you look at AWS Redshift, you're buying your database by the nodes. You say, how many nodes do you want? And in both those cases, this is a cloud native. This is saying we have some hardware underneath our database and we need you, Mr. Customer, to tell us how many servers you want. That's not the way the clouds should work, right? And I think this is one of the things that we did with Autonomous Data Warehouse. We said, no, that's not how the rules should work. We still run our database on hardware, we still have nodes and servers. We should tell the customer, how many CPU's you would like for your data warehouse? You want 16? Sounds good. You want 18? Yeah, we can give you 18. We're not, you know, we're not selling these to you in bundles of eight or bundles of six or powers of two. We'll sell you what you need. That's what cloud elasticity should be. Not this idea that oh, we are a database that should be managed by IT. IT already knows about servers and nodes. Therefore it's okay if we tell people your cloud data warehouse runs on nodes. Within Oracle as Neil said, we wouldn't. The data warehouse should be used by the people who want to actually analyze their data, should be used by the business users. >> Well, and so the other piece of cloud native that has become popular, is this idea of separating compute from storage and being able to scale those two independent of each other which is pretty important, right? Because you don't want to have to pay for a chunk of compute if you don't need the storage and vice versa. Maybe you could talk about that, how you solve that problem, to the extent that you solve that problem. >> Absolutely, we do separate compute print storage with Autonomous Data Warehouse. When you come in and you say, I need 10 CPU's for my data warehouse and I need two terabytes of storage. Those are two dependent decisions that you make. So they're not tied together in any way. And, you are exactly right, Dave, this is how things should work in the cloud. You should pay for what you need, pay for what you use, not be constrained by having big sets of storage you have to use for a given amount CPU or vice versa. >> Okay, go ahead Neil, please. >> Oh, just to add on to that, you know, the other aspect that comes into play is that, you know, so your starting point is X, whatever that happens to be. Over time that changes. And we all know that workloads vary right throughout the day throughout the month, throughout the year by various events that occur maybe the close of the year, close of business at the end of the quarter, it maybe you know, holiday season for retailers and so forth. So, you know, it's not only the starting point, but how do you actually manage the growth, right? scaling up and scaling down, right? In our case, we tried, as George said, we abstracted that completely for the customer basically said check a box, which has auto scale. So, if the system is required more resources, will apply more resources. And we do so instantaneously without any downtime whatsoever, right? Because you know, again, you know, people think in terms of these systems have now become business critical. So if the business critical, you can't just shut down to expand. Imagine during the holiday season is your business is ramping up. And then all of a sudden you have to scale, right? And your system either shuts down, reboots itself, right? Or it slows down to the point that it's a crawl and all your customers get frustrated. We don't do that. You click a button, auto scale and we take care of it for you smoothing out those lumps, right? Without any technical assistance. And again, if you look at Redshift, you look at all these various systems, they require technical assistance to be able to figure out not only your initial data, but how you scale out over time. >> Interesting, okay. So all is said, you know, a lot of companies are using Azure, AWS Google for infrastructure, why would these customers not just use their database? Why would they switch to Oracle or ADW? >> Well, I think Neil will probably add something. I want to start by saying a huge number of our existing Autonomous Data Warehouse customers today are customers of AWS and Azure. They are pulling data from AWS and Azure and bringing it into an Oracle Autonomous Data Warehouse. And we built feature Joe, I focused on product managers. We feel featured for that. And so it's perfectly viable and it it's almost commonplace, that the very largest enterprises to be doing that. But then coming to the question of why would they want to do it? I don't know, Neil, you want to take that? >> Yeah, yeah, so one of the things that we've really see emerge here is you know, a data warehouse doesn't generate the transactions on itself, right? So the data has to come from somewhere, right? And you ask yourself, well, where does the data come from? Well, in a lot of cases, that data is coming from applications and increasingly SAS applications that the company has deployed. And those are, you know, HR applications, you know, CRM applications, you know ERP applications and many vertical applications. In Oracle's case, what we've done is we say, okay, well, we have the application, this transactional thing, we have the infrastructure from the economist data warehouse, why don't we just make it really, really easy? And if you're an Oracle applications customer, that's already running on the Oracle cloud, we will essentially provide you the ability to create a data warehouse from that information, right? With a clicker, with largely either with a product and service or quick start kit. You don't start from scratch, you start from where you are. And there are many cases that where you are has data, very much as George mentioned before telcos, banks, insurance companies, governments, all of the data that they want to analyze, a lot of that data guess where it's coming from, it's coming from Oracle applications. So it makes sense to be able to have both the data that's generated and the data that's being analyzed close to the same place. Because at the end of the day, the payoff pitch for any form of analysis is not coming up with an insight, oh, I realized X, Y, Z, but it's rather putting the insight directly into production. And that's where, when you have this stuff spread all over God's greener trying to go from insight into action can take months, if not years. The reason that a lot of customers are now turning to us is that they need to be much more agile and they need to be able to turn that insight into action immediately without it being a science project. >> Okay, thank you for that. So let's tick them off. Like what are the top things that customers can get from Oracle Autonomous Data Warehouse, that they couldn't get from say a Snowflake or Redshift or Big query or SQL server or something yet. I appreciate you guys' willingness to talk about the competition. Let's tick them off. What are the most important things that we should know about that they can't get elsewhere? >> So first, I mean, we already talked about a couple of what we think are really the major themes of Autonomous Data Warehouse. The services is autonomous. You don't need to worry about managing it, anyone can manage the data warehouse. The service is elastic. You can buy and pay for what you use. You know, those are just what we think of as being the general characteristics of Autonomous Data Warehouse. But you know, when you come to your question of, hey, what do we give that other vendors don't provide? And I think the one angle that Autonomous Data Warehouse does a really good job is and Neil was just discussing this, it focuses on the business problems, right? We have years and years of experience with not just database security, but data security, right? You know, every cloud vendor can say, oh we encrypt all your data, we have these compliance certifications, all of these things. And what they're saying is, we are securing your database, we are securing your database infrastructure. At Oracle of course has to do those as well. But where we go further, is we say, hey, no, no, no, no, no, we know what business users want. They want to secure their data. What kind of data am I storing? Do I have PII data? Could you detect whether there's PII data and tell me about it in case some user loaded something that I wasn't aware of? What kind of privileges did I give my users? Can you make sure that those privileges are right? And can you tell me if users were given privileges that they're not using maybe I need to take them away. These are the problems that Oracle's tackled in security over the last 20 years. It's really more about the business problem. Yeah, some other, oh, go ahead. >> Oh, I'm sorry, I got so many questions for you guys. We'll get back to that 'cause it sounds like there's a long list. (laughs) >> We have nowhere to go.(laughs) I want to pick up with George on something you said about elasticity. Is it true pay by the drink? Do you have a consumption pricing? I mean, can I dial it up and dial it down whenever I want? How does that work? >> Yes, I mean not to be too many technical details, but you say, I want 14 CPU's that's what your database runs at. You can change that default number anytime you want online, right? You can say, okay, I'm coming up on my quarter end, I'm going to raise my database 20 CPU. We just do it on the ply. We just adjust the size--- >> What about the other way? What about coming down? Can I go down to one? >> You go down, you can go down to one--- >> And you're not going to charge me for 14 if I go down to one? >> No, if you set it down to one, you get charged for one, right? >> Okay, that's good, that's good. >> In the background, you know we are also allowing levels of auto scaling. You say, if you say hey, I want to charged for 14 and Oracle, can you take care of all those scaling for me? So if a bunch of people jump on at 5:00 PM, to run some queries, 'cause the executive said, hey, I need a report by tomorrow morning. We'll take care of that for you. We'll let you go beyond 14 and only charge you for exactly what you use for those extra CPU's beyond 14. >> Okay, thank you. Go ahead, Neil. >> And maybe, if we add, you know, Andy talked about this when he was on that show with you last week, right? And you know, he talked about this concept of a converged database, but let me talk about it in the way that we see it from a business point of view, right? You know, business users are looking to, you know ask a variety of questions, right? And those questions need to be able to relate to both you know, the customer themselves, the relationship that the customer might have with others. You know, today we talk about like the social network and who are influencers within that, and then where they actually conduct business. Which is really, you know, in every case, it's on some form of increasingly on a mobile device. So in that case, you want to be able to ask questions, which is not only, you know, who should I focus on, but who are the key influencers within this community, right? That could influence others? And does that happen in a particular place in time? Meaning, you know, let's say pre COVID, it might happen at a coffee shop or somewhere else. We can answer all of those questions and more inside of the autonomous system without having to replicate the data out to one system that does graph and another system that does spatial, a third system that does this. It's like a business user. It's like, wait a minute, come on, you're trying to tell me that I need a separate system and replicate the data just be able to understand location? The answer in many cases is yes, you have to have separate, which a business person says, well, that's absurd. Can't I just do this all in one system? You can with Oracle. >> So look, I'm not trying to be the snarky journalist or analyst here but I want to keep pushing on this issue. So here we are, it's 2021. It's April. We're like a third of the way through the year. And so far, nobody has come out and said, okay, we're going to deliver Autonomous Data Warehouse just like Oracle. So I asked myself, well, why is Oracle doing this? You guys answered, you know, to reduce the labor cost. But I asked myself, is this how they're solving the problem of keeping relevant a database that spans five decades? And you guys said, no, no, this is cloud native born in the cloud, you know started essentially with a new mindset. But is this a trend that others are going to follow? You know, and if so, why haven't we seen it this idea of a self-driving databases? Why is it right now unique to Oracle? What's really going on here? >> So I think there's a really interesting thing that's happening, it's not visible outside of Oracle. It's very visible for those of us who work inside of the development organization. You know, if you look at Oracle, I can tell you bad. I mean, I think it's safe to presume Oracle has the largest database development organization on the planet, right? I mean, it was kind of the largest database or large most used database for the past two decades. And what's happened is we pivoted to building a cloud platform. We're not just building a database, we're taking all of these resources that we have with all these expertise of building database software. We were saying, we now have to build the platform to run and manage the database software in the cloud, right? And it's a little bit like, you know I think to make people relate to it a little better, there was a really good quote from Elon Musk couple of years ago, talking about Tesla. Like everyone looks at the car, right? Tesla, the car is really great. The hard part of this, is building the factory, and that's analogy holds for Oracle. What we're building is the cloud battery. And what we have transitioned is our database development organization is now building as robust a cloud as possible. So that you know, when we increase the number of databases by 10 X, we don't add 10 X, more cloud ops people to manage it. We are ramping up developer building features to automate the management of our cloud infrastructure. And with that automation, we get better ability, less errors, more security. We give benefits to our cloud data warehouse customers with it. And I think this something really important to realize, right? We build database software. We build, you know, an engineered system built for databases called exit data, and we build a cloud platform. And these are really equal tiers in what we are building and developing today in 2021 from Oracle database development organization. >> Well, you mentioned exit data, I want to shift gears here a little bit and talk about we're seeing this hybrid cloud on-premises clouds, they're finally gaining some traction. I got to give props Oracle's cloud of customers really the early to that game. I think it was the first in my view anyway, true same same vision, took you guys a little while to get there but it was the right vision. And the thing I always say about Oracle people don't understand is Oracle invest in R and D, your chairman is also the CTO. You guys are serious about technical investment so you know, that's where innovation comes from. But, and we heard during your recent earnings call, we heard some positive comments on this. So what's your take on delivering autonomous data warehouse on-prem and how do you compare with say Snowflake and AWS in that area? Snowflake, Frank Slootman, I've had him on record saying we're not going to do that halfway house. Forget it, we are always going to be in the cloud. We're never going to do an on-prem installation. AWS, we'll see to date. Yeah, I don't think you can get a Redshift for instance in outposts, but maybe that'll come. But, how do you see that emerging? What's your difference there? Maybe Neil, you could talk about that. >> Yeah, so, you know, I think, you know, customers had a lot of regulated industries, right? Still have concerns about the public cloud. And I think that when you hear statements like, you know, we're never going to do, you know, on-prem. Well, economist cloud at customer, it's not a classic on-prem solution. What it is, it's a piece of our cloud delivered in your data center. It's still the cloud software. Oracle manages it, Oracle, you know, the system itself manages itself and we take care of that responsibility so you don't have to. The differences is that we can make that available in a public cloud as well as in a private cloud, right? And there are so many use cases, you know, that you can imagine from a regulatory point of view, or just from a comfort point of view, where customers are choosing, they want the ability to decide for themselves where to place this stuff as compared to only having one option, right? And you know, you look at a lot of what's happening in the emerging world where, you know, there are a lot of places in the world that may not have, you know, really really high-speed internet connections to make, you know a public cloud feasible. Well, in that case, whether you're talking about, you know an oil rig or you're talking about something else, right? We can put that capability where it needs to be close to the operation that you're talking about, irrespective of the deployment option. >> Well, let me just follow up on that because I think it's interesting that, you know Frank Slootman said that to me, I oftentimes around AWS I say, never say never 'cause they'll surprise you, right? And I've learned that with Andy Jassy, but one of the things that seems difficult for on-prem, would be to separate that compute from storage because you have to actually physically move in resources. I think about Vertica Xeon mode. It's not quite the same, same. So, I mean, in that regard, maybe you're not the same same. And maybe that dogma makes sense for some companies. For Oracle, obviously you've got a huge on-prem state, thoughts on that. >> So, you know, clearly, you know, so typically what we'll do is that we'll provide additional hardware beyond what the customer might expect and that allows them to use the capabilities of expansion, right? We also have the ability to allow the customer to expand from their cloud of customer into the public cloud as well, of which we have a lot of those situations. So we can provide a level of elasticity, even on-premises by over provisioning the systems, well not charging the customer until they use only based on what they consume, right? Combined together with the ability for us to augment their usage in the public cloud as well, right? Where others, again are constraint, right? Because they only have a single option. >> Right, well, you've got the capital resources to do that as well which is not to be overlooked. Okay, I mean, I've blown our time here but you guys are so awesome. (laughs) I appreciate the candor. So last question and George, if you want to throw in a couple of those other tick boxes, you know the differentiators, please feel free, but for both of you, if you can leave customers with the one key point or the top key points on how Oracle Autonomous Data Warehouse can really help them improve their business in the near term, what would they be? Maybe George, you could start and then Neil you bring us home. >> Yeah, I mean, I think that, as I said before, our starting point with Autonomous Data Warehouse, is how can we build a better customer experience in the cloud? And I think, and this continues throughout 2021, and I think that the big theme here is the business users should be able to get value directly from their data warehouses. We talked a few times about how a line of business user should be able to manage their own data, should be able to load their own data warehouse, should be able to start to work with their own data, should be able to run machine learning, model of build machine learning, models against that data and all of that built in, and delivered in Autonomous Data Warehouse. And we think that this is, you know we see our customer organizations large and small, the light bulbs starting to go on how easy the services to use to and how completed it is for helping business users get value from their data. And just adding onto what George said, you know, the development organization has done a tremendous job of really simplifying this cooperation. What we also tried to do that on the business side. You know, when a customer has an on-prem situation, they're looking at moving to the cloud, whether lift and shift or modernized, they're looking at costs, they're looking at risk and they're looking at time. So one of the things we look at is how do we mitigate that? How do we mitigate the cost, the risk and the time? Well, this week, I think we announced our new cloud lift program and the cloud lift program is what Oracle will provide to its cloud engineering resources around the world is that we will do, we will take the cost, the risk and the time out of the equation and Oracle will work directly with the customer or the customer's partner of choice, maybe an Accenture or Deloitte, and we will move them, right? You know, at little or no cost, most cases there's no cost whatsoever, right? We mitigate the risk because we're taking the risk on. And we've built a lot of automated tools to make that go very quickly, right? And securely, and then finally, we do it in a very very short amount of time as compared to what you would need to do with, you know 'cause there is no Redshift on-premises. There is no Snowflake on-premises. You have to convert from what you already have to that, right? And, but the company beyond the technological barriers that George talked about were also trying to smooth the operation so that a business itself can make a decision that not only did they not need the technical people to operate it, they won't need an entire consulting contract with millions of dollars in order to actually do the movement to the cloud. >> Well, guys, I really appreciate you coming on the program and again, your candor to speak openly about you know, your approach, the competitors. And so it's great having you, really really thank you for, for your time. >> Appreciate it. >> And thank you for watching everybody. Look, if you guys want to come back, go toe to toe with these guys, say the word you're always welcome to come on The Cube. One thing for sure, Oracle are serious, when it comes to database. Thank you for watching. This is Dave Vellante. We'll see you next time. (bright music)

(upbeat music) >> On February 19th of this year, Barron's dropped an article declaring Oracle, a cloud giant and the article explained why the stock was a buy. Investors took notice and the stock ran up 18% over the next nine trading days and it peaked on March 9th, the day before Oracle announced its latest earnings. The company beat consensus earnings on both top-line and EPS last quarter, but investors, they did not like Oracle's tepid guidance and the stock pulled back. But it's still, as you can see, well above its pre-Barron's article price. What does all this mean? Is Oracle a cloud giant? What are its growth prospects? Now many parts of Oracle's business are growing including Fusion ERP, Fusion HCM, NetSuite, we're talking deep into the double digits, 20 plus percent growth. It's OnPrem legacy licensed business however, continues to decline and that moderates, the overall company growth because that OnPrem business is so large. So the overall Oracle's growing in the low single digits. Now what stands out about Oracle is it's recurring revenue model. That figure, the company says now it represents 73% of its revenue and that's going to continue to grow. Now two other things stood out on the earnings call to us. First, Oracle plans on increasing its CapEX by 50% in the coming quarter, that's a lot. Now it's still far less than AWS Google or Microsoft Spend on capital but it's a meaningful data point. Second Oracle's consumption revenue for Autonomous Database and Cloud Infrastructure, OCI or Oracle Cloud Infrastructure grew at 64% and 139% respectively and these two factors combined with the CapEX Spend suggest that the company has real momentum. I mean look, it's possible that the CapEx announcements maybe just optics in they're front loading, some spend to show the street that it's a player in cloud but I don't think so. Oracle's Safra Catz's usually pretty disciplined when it comes to it's spending. Now today on March 17th, Oracle announced updates towards Autonomous Data Warehouse and with me is David Floyer who has extensively researched Oracle over the years and today we're going to unpack the Oracle Autonomous Data Warehouse, ADW announcement. What it means to customers but we also want to dig into Oracle's strategy. We want to compare it to some other prominent database vendors specifically, AWS and Snowflake. David Floyer, Welcome back to The Cube, thanks for making some time for me. >> Thank you Vellante, great pleasure to be here. >> All right, I want to get into the news but I want to start with this idea of the autonomous database which Oracle's announcement today is building on. Oracle uses the analogy of a self-driving car. It's obviously powerful metaphor as they call it the self-driving database and my takeaway is that, this means that the system automatically provisions, it upgrades, it does all the patching for you, it tunes itself. Oracle claims that all reduces labor costs or admin costs by 90%. So I ask you, is this the right interpretation of what Oracle means by autonomous database? And is it real? >> Is that the right interpretation? It's a nice analogy. It's a test to that analogy, isn't it? I would put it as the first stage of the Autonomous Data Warehouse was to do the things that you talked about, which was the tuning, the provisioning, all of that sort of thing. The second stage is actually, I think more interesting in that what they're focusing on is making it easy to use for the end user. Eliminating the requirement for IT, staff to be there to help in the actual using of it and that is a very big step for them but an absolutely vital step because all of the competition focusing on ease of use, ease of use, ease of use and cheapness of being able to manage and deploy. But, so I think that is the really important area that Oracle has focused on and it seemed to have done so very well. >> So in your view, is this, I mean you don't really hear a lot of other companies talking about this analogy of the self-driving database, is this unique? Is it differentiable for Oracle? If so, why, or maybe you could help us understand that a little bit better. >> Well, the whole strategy is unique in its breadth. It has really brought together a whole number of things together and made it of its type the best. So it has a single, whole number of data sources and database types. So it's got a very broad range of different ways that you can look at the data and the second thing that is also excellent is it's a platform. It is fully self provisioned and its functionality is very, very broad indeed. The quality of the original SQL and the query languages, etc, is very, very good indeed and it's a better agent to do joints for example, is excellent. So all of the building blocks are there and together with it's sharing of the same data with OLTP and inference and in memory data paces as well. All together the breadth of what they have is unique and very, very powerful. >> I want to come back to this but let's get into the news a little bit and the announcement. I mean, it seems like what's new in the autonomous data warehouse piece for Oracle's new tooling around four areas that so Andy Mendelsohn, the head of this group instead of the guy who releases his baby, he talked about four things. My takeaway, faster simpler loads, simplified transforms, autonomous machine learning models which are facilitating, What do you call it? Citizen data science and then faster time to insights. So tooling to make those four things happen. What's your take and takeaways on the news? >> I think those are all correct. I would add the ease of use in terms of being able to drag and drop, the user interface has been dramatically improved. Again, I think those, strategically are actually more important that the others are all useful and good components of it but strategically, I think is more important. There's ease of use, the use of apex for example, are more important. And, >> Why are they more important strategically? >> Because they focus on the end users capability. For example, one of other things that they've started to introduce is Python together with their spatial databases, for example. That is really important that you reach out to the developer as they are and what tools they want to use. So those type of ease of use things, those types of things are respecting what the end users use. For example, they haven't come out with anything like click or Tableau. They've left that there for that marketplace for the end user to use what they like best. >> Do you mean, they're not trying to compete with those two tools. They indeed had a laundry list of stuff that they supported, Talend, Tableau, Looker, click, Informatica, IBM, I had IBM there. So their claim was, hey, we're open. But so that's smart. That's just, hey, they realized that people use these tools. >> I'm trying to exclude other people, be a platform and be an ecosystem for the end users. >> Okay, so Mendelsohn who made the announcement said that Oracle's the smartphone of databases and I think, I actually think Alison kind of used that or maybe that was us planing to have, I thought he did like the iPhone of when he announced the exit data way back when the integrated hardware and software but is that how you see it, is Oracle, the smartphone of databases? >> It is, I mean, they are trying to own the complete stack, the hardware with the exit data all the way up to the databases at the data warehouses and the OLTP databases, the inference databases. They're trying to own the complete stack from top to bottom and that's what makes autonomy process possible. You can make it autonomous when you control all of that. Take away all of the requirements for IT in the business itself. So it's democratizing the use of data warehouses. It is pushing it out to the lines of business and it's simplifying it and making it possible to push out so that they can own their own data. They can manage their own data and they do not need an IT person from headquarters to help them. >> Let's stay in this a little bit more and then I want to go into some of the competitive stuff because Mendelsohn mentioned AWS several times. One of the things that struck me, he said, hey, we're basically one API 'cause we're doing analytics in the cloud, we're doing data in the cloud, we're doing integration in the cloud and that's sort of a big part of the value proposition. He made some comparisons to Redshift. Of course, I would say, if you can't find a workload where you beat your big competitor then you shouldn't be in this business. So I take those things with a grain of salt but one of the other things that caught me is that migrating from OnPrem to Oracle, Oracle Cloud was very simple and I think he might've made some comparisons to other platforms. And this to me is important because he also brought in that Gartner data. We looked at that Gardner data when they came out with it in the operational database class, Oracle smoked everybody. They were like way ahead and the reason why I think that's important is because let's face it, the Mission Critical Workloads, when you look at what's moving into AWS, the Mission Critical Workloads, the high performance, high criticality OLTP stuff. That's not moving in droves and you've made the point often that companies with their own cloud particularly, Oracle you've mentioned this about IBM for certain, DB2 for instance, customers are going to, there should be a lower risk environment moving from OnPrem to their cloud, because you could do, I don't think you could get Oracle RAC on AWS. For example, I don't think EXIF data is running in AWS data centers and so that like component is going to facilitate migration. What's your take on all that spiel? >> I think that's absolutely right. You all crown Jewels, the most expensive and the most valuable applications, the mission-critical applications. The ones that have got to take a beating, keep on taking. So those types of applications are where Oracle really shines. They own a very large high percentage of those Mission Critical Workloads and you have the choice if you're going to AWS, for example of either migrating to Oracle on AWS and that is frankly not a good fit at all. There're a lot of constraints to running large systems on AWS, large mission critical systems. So that's not an option and then the option, of course, that AWS will push is move to a Roller, change your way of writing applications, make them tiny little pieces and stitch them all together with microservices and that's okay if you're a small organization but that has got a lot of problems in its own, right? Because then you, the user have to stitch all those pieces together and you're responsible for testing it and you're responsible for looking after it. And that as you grow becomes a bigger and bigger overhead. So AWS, in my opinion needs to have a move towards a tier-one database of it's own and it's not in that position at the moment. >> Interesting, okay. So, let's talk about the competitive landscape and the choices that customers have. As I said, Mendelssohn mentioned AWS many times, Larry on the calls often take shy, it's a compliment to me. When Larry Ellison calls you out, that means you've made it, you're doing well. We've seen it over the years, whether it's IBM or Workday or Salesforce, even though Salesforce's big Oracle customer 'cause AWS, as we know are Oracle customer as well, even though AWS tells us they've off called when you peel the onion >> Five years should be great, some of the workers >> Well, as I said, I believe they're still using Oracle in certain workloads. Way, way, we digress. So AWS though, they take a different approach and I want to push on this a little bit with database. It's got more than a dozen, I think purpose-built databases. They take this kind of right tool for the right job approach was Oracle there converging all this function into a single database. SQL JSON graph databases, machine learning, blockchain. I'd love to talk about more about blockchain if we have time but seems to me that the right tool for the right job purpose-built, very granular down to the primitives and APIs. That seems to me to be a pretty viable approach versus kind of a Swiss Army approach. How do you compare the two? >> Yes, and it is to many initial programmers who are very interested for example, in graph databases or in time series databases. They are looking for a cheap database that will do the job for a particular project and that makes, for the program or for that individual piece of work is making a very sensible way of doing it and they pay for ads on it's clear cloud dynamics. The challenge as you have more and more data and as you're building up your data warehouse in your data lakes is that you do not want to have to move data from one place to another place. So for example, if you've got a Roller,, you have to move the database and it's a pretty complicated thing to do it, to move it to Redshift. It's a five or six steps to do that and each of those costs money and each of those take time. More importantly, they take time. The Oracle approach is a single database in terms of all the pieces that obviously you have multiple databases you have different OLTP databases and data warehouse databases but as a single architecture and a single design which means that all of the work in terms of moving stuff from one place to another place is within Oracle itself. It's Oracle that's doing that work for you and as you grow, that becomes very, very important. To me, very, very important, cost saving. The overhead of all those different ones and the databases themselves originate with all as open source and they've done very well with it and then there's a large revenue stream behind the, >> The AWS, you mean? >> Yes, the original database is in AWS and they've done a lot of work in terms of making it set with the panels, etc. But if a larger organization, especially very large ones and certainly if they want to combine, for example data warehouse with the OLTP and the inference which is in my opinion, a very good thing that they should be trying to do then that is incredibly difficult to do with AWS and in my opinion, AWS has to invest enormously in to make the whole ecosystem much better. >> Okay, so innovation required there maybe is part of the TAM expansion strategy but just to sort of digress for a second. So it seems like, and by the way, there are others that are doing, they're taking this converged approach. It seems like that is a trend. I mean, you certainly see it with single store. I mean, the name sort of implies that formerly MemSQL I think Monte Zweben of splice machine is probably headed in a similar direction, embedding AI in Microsoft's, kind of interesting. It seems like Microsoft is willing to build this abstraction layer that hides that complexity of the different tooling. AWS thus far has not taken that approach and then sort of looking at Snowflake, Snowflake's got a completely different, I think Snowflake's trying to do something completely different. I don't think they're necessarily trying to take Oracle head-on. I mean, they're certainly trying to just, I guess, let's talk about this. Snowflake simplified EDW, that's clear. Zero to snowflake in 90 minutes. It's got this data cloud vision. So you sign on to this Snowflake, speaking of layers they're abstracting the complexity of the underlying cloud. That's what the data cloud vision is all about. They, talk about this Global Mesh but they've not done a good job of explaining what the heck it is. We've been pushing them on that, but we got, >> Aspiration of moment >> Well, I guess, yeah, it seems that way. And so, but conceptually, it's I think very powerful but in reality, what snowflake is doing with data sharing, a lot of reading it's probably mostly read-only and I say, mostly read-only, oh, there you go. You'll get better but it's mostly read and so you're able to share the data, it's governed. I mean, it's exactly, quite genius how they've implemented this with its simplicity. It is a caching architecture. We've talked about that, we can geek out about that. There's good, there's bad, there's ugly but generally speaking, I guess my premise here I would love your thoughts. Is snowflakes trying to do something different? It's trying to be not just another data warehouse. It's not just trying to compete with data lakes. It's trying to create this data cloud to facilitate data sharing, put data in the hands of business owners in terms of a product build, data product builders. That's a different vision than anything I've seen thus far, your thoughts. >> I agree and even more going further, being a place where people can sell data. Put it up and make it available to whoever needs it and making it so simple that it can be shared across the country and across the world. I think it's a very powerful vision indeed. The challenge they have is that the pieces at the moment are very, very easy to use but the quality in terms of the, for example, joints, I mentioned, the joints were very powerful in Oracle. They don't try and do joints. They, they say >> They being Snowflake, snowflake. Yeah, they don't even write it. They would say use another Postgres >> Yeah. >> Database to do that. >> Yeah, so then they have a long way to go. >> Complex joints anyway, maybe simple joints, yeah. >> Complex joints, so they have a long way to go in terms of the functionality of their product and also in my opinion, they sure be going to have more types of databases inside it, including OLTP and they can do that. They have obviously got a great market gap and they can do that by acquisition as well as they can >> They've started. I think, I think they support JSON, right. >> Do they support JSON? And graph, I think there's a graph database that's either coming or it's there, I can't keep all that stuff in my head but there's no reason they can't go in that direction. I mean, in speaking to the founders in Snowflake they were like, look, we're kind of new. We would focus on simple. A lot of them came from Oracle so they know all database and they know how hard it is to do things like facilitate complex joints and do complex workload management and so they said, let's just simplify, we'll put it in the cloud and it will spin up a separate data warehouse. It's a virtual data warehouse every time you want one to. So that's how they handle those things. So different philosophy but again, coming back to some of the mission critical work and some of the larger Oracle customers, they said they have a thousand autonomous database customers. I think it was autonomous database, not ADW but anyway, a few stood out AON, lift, I think Deloitte stood out and as obviously, hundreds more. So we have people who misunderstand Oracle, I think. They got a big install base. They invest in R and D and they talk about lock-in sure but the CIO that I talked to and you talked to David, they're looking for business value. I would say that 75 to 80% of them will gravitate toward business value over the fear of lock-in and I think at the end of the day, they feel like, you know what? If our business is performing, it's a better business decision, it's a better business case. >> I fully agree, they've been very difficult to do business with in the past. Everybody's in dread of the >> The audit. >> The knock on the door from the auditor. >> Right. >> And that from a purchasing point of view has been really bad experience for many, many customers. The users of the database itself are very happy indeed. I mean, you talk to them and they understand why, what they're paying for. They understand the value and in terms of availability and all of the tools for complex multi-dimensional types of applications. It's pretty well, the only game in town. It's only DB2 and SQL that had any hope of doing >> Doing Microsoft, Microsoft SQL, right. >> Okay, SQL >> Which, okay, yeah, definitely competitive for sure. DB2, no IBM look, IBM lost its dominant position in database. They kind of seeded that. Oracle had to fight hard to win it. It wasn't obvious in the 80s who was going to be the database King and all had to fight. And to me, I always tell people the difference is that the chairman of Oracle is also the CTO. They spend money on R and D and they throw off a ton of cash. I want to say something about, >> I was just going to make one extra point. The simplicity and the capability of their cloud versions of all of this is incredibly good. They are better in terms of spending what you need or what you use much better than AWS, for example or anybody else. So they have really come full circle in terms of attractiveness in a cloud environment. >> You mean charging you for what you consume. Yeah, Mendelsohn talked about that. He made a big point about the granularity, you pay for only what you need. If you need 33 CPUs or the other databases you've got to shape, if you need 33, you've got to go to 64. I know that's true for everyone. I'm not sure if that's true too for snowflake. It may be, I got to dig into that a little bit, but maybe >> Yes, Snowflake has got a front end to hiding behind. >> Right, but I didn't want to push it that a little bit because I want to go look at their pricing strategies because I still think they make you buy, I may be wrong. I thought they make you still do a one-year or two-year or three-year term. I don't know if you can just turn it off at any time. They might allow, I should hold off. I'll do some more research on that but I wanted to make a point about the audits, you mentioned audits before. A big mistake that a lot of Oracle customers have made many times and we've written about this, negotiating with Oracle, you've got to bring your best and your brightest when you negotiate with Oracle. Some of the things that people didn't pay attention to and I think they've sort of caught onto this is that Oracle's SOW is adjudicate over the MSA, a lot of legal departments and procurement department. Oh, do we have an MSA? With all, Yes, you do, okay, great and because they think the MSA, they then can run. If they have an MSA, they can rubber stamp it but the SOW really dictateS and Oracle's gotcha there and they're really smart about that. So you got to bring your best and the brightest and you've got to really negotiate hard with Oracle, you get trouble. >> Sure. >> So it is what it is but coming back to Oracle, let's sort of wrap on this. Dominant position in mission critical, we saw that from the Gartner research, especially for operational, giant customer base, there's cloud-first notion, there's investing in R and D, open, we'll put a question Mark around that but hey, they're doing some cool stuff with Michael stuff. >> Ecosystem, I put that, ecosystem they're promoting their ecosystem. >> Yeah, and look, I mean, for a lot of their customers, we've talked to many, they say, look, there's actually, a tail at the tail way, this saves us money and we don't have to migrate. >> Yeah. So interesting, so I'll give you the last word. We started sort of focusing on the announcement. So what do you want to leave us with? >> My last word is that there are platforms with a certain key application or key parts of the infrastructure, which I think can differentiate themselves from the Azures or the AWS. and Oracle owns one of those, SAP might be another one but there are certain platforms which are big enough and important enough that they will, in my opinion will succeed in that cloud strategy for this. >> Great, David, thanks so much, appreciate your insights. >> Good to be here. Thank you for watching everybody, this is Dave Vellante for The Cube. We'll see you next time. (upbeat music)

>> Narrator: From the Cube Studios in Palo Alto and Boston, it's the Cube, covering empowering the autonomous enterprise, brought to you by Oracle Consulting. >> Hi everybody, welcome back to this special digital presentation where we are tracking the transformation of Oracle Consulting. Aaron Millstone is back, he's the Senior Vice President of Oracle Consulting and he's joined by Jeff Davis whose Principal at Deloitte, he's the Chief Commercial Officer for Oracle at Deloitte. Gentlemen, good to see you, welcome. We see a lot of these deals, sometimes we call them Barney deals, you know, I love you, you love me, there's a press release and that's it. But, so one of the things we look for, okay, is there teeth behind this? Now, you guys have come up with what you call Elevate. What is Elevate, how did it get started? Then I have some follow up questions. >> Well, Elevate really got started when Aaron and I started to look at the assets that each of the firms possessed. On the Deloitte side as Aaron suggested, we have deep capabilities and a broad range of technologies. Some of them could be technologies with Oracle. At the same time, we didn't have a great deal of depth in Oracle's technical products, Oracle Cloud infrastructure and Oracle Autonomous. Our bench was not as big as Aaron's. And Aaron also had access to Oracle development at a level that we didn't have access to. So we really found ourselves in a situation where we could put those two capabilities together and we could offer something to our clients. And the broad rage of Oracle customers in the field, they had access to all of Deloitte's capabilities, which include great project management, great change management, real skill around the strategic aspects of cloud migration and Aaron had tools and had resources trained and developed around the latest Oracle technology. They'd always be a step ahead of any SI. So together we felt this was really a differentiation for the market place. >> One of the things we look for, is there any other integration? Are you doing co-engineering? In this case maybe not co-engineering, but are there tools that you're developing that you're taking to market that you're actually leveraging? Aaron, can you talk about that a little bit and convince us it's not just a sales play? >> Yeah, sure, and Jeff eluded to some of this earlier too, right. So, we definitely each had our respective tool line, right? Deloitte's investments and tools, one of them's called ATADATA, that we've seen used quite a few times now. We've invested in something we called Oracle Soar. You know, our tools are, as you'd imagine, heavily Oracle focused. It's about moving Oracle technology to Oracle cloud. ATADATA and some of the tools that Deloitte's invested in are focused more comprehensively on wholistically at looking at everything in a data center and everything that's across data centers and start to develop a set of facts around this stuff. But in both cases we actually looked at these things and we said, you know what if you combine these together, we get a very comprehensive view of what exactly it is that we're looking at with a customer. So we can tell everything from the types of traffic we see on the network, to the specific versions of stuff. We can start to identify whether there's risk associated with having things not patched or out of support, but again a very comprehensive view that's based on facts. And so, you know, we took those tools and we combined them together so that we can go in to a customer and give a complete end to end view from both an Oracle and Deloitte perspective. And quite frankly it doesn't matter whether Deloitte leads or whether Oracle leads, we've developed these tools together, we're going to market together, and we've even got, you know, the templates you'd expect consultancies to have right? So when you look at business cases, we've got joint business case templates that we've created together and that we're using actively with customers and then we're refining them and improving them each time we do it. But, you know, we're at a point now where our tools are combined, our templates are combined and we even at this, you know, we were even- Jeff and I were on a call earlier, yesterday actually, we even got a joint war room that's constantly engaging with different account teams and making sure that we structurally approach things in a consistent way so that we're driving business value and using the tools appropriately. >> Aaron you and I have talked about, you know, data centers and building data centers and investing; it's just not a good use of capital today. There are so many other things that organizations can do. You guys have identified data center consolidation as, I'll call it a you know, an initiative that you're seeing customers. I wondered if you could talk about that a little bit, is that kind of a starting point for conversations? >> Yeah, well it's definitely a starting point. So we call it and refer to it as infrastructure lead transformation and the appetite for that is certainly high. We're seeing an increased focus on you know, what do customers need to do to take not just a workload here and there, but how to they get out of the data center business hole? So it's sort of, it's a forgone conclusion. Like you just said, it's not really a question of should we invest in another data center, or should we invest in up-tooling our data centers? The question has changed to, let's move to cloud, how do we get there? And let's move in a big way. And that's, we're seeing that dialogue across all of our customers. And quite frankly, even for Oracle, it's been a learning curve for us, right? We started with an Oracle workload conversation, which is: do you want to move this Oracle workload to Oracle's cloud? Do you want to move that Oracle workload to Oracle's cloud? And really what we're finding is it's a wholesale transformation of everything in a data center to one or more clouds right? Again, often it's a multicloud strategy and that's okay. And we, you know, we're having more-bigger conversations. The thing that has been really interesting is these conversations have evolved and especially as we work with our partners at Deloitte, has been that, you know, we think that the combination of our cloud technology, the consulting services that Oracle consulting and Deloitte can bring to bear and then Oracle's ability to finance the whole deal, makes some very compelling conversations for customers cause you can walk in to a CIO, to a CFO and say look on day one, you can actually have a lower spend than what you have today in your data center, and get a cloud transformation on Deloitte at the same time. >> Let's talk a little bit more about that business case. Is that generally what you're seeing where it starts as let's take some costs right out? And then, Aaron, you and I talked about maybe investing that in the future, but is that really the starting point for the vast majority of customers? Let's cut some costs right away and get a payback immediately? >> So I'd like to share our perspective which is, you know, nobody spends money for the sake of spending money on technology. It's got to have meaningful business value. So the conversation starts with really renewal and a path to the cloud, but there's a natural opportunity for savings and consolidation that we take advantage. We're not simply shifting from your hardware to the cloud. We're actually modernizing, which will result in significant savings. But it also gives the business something that they don't have today at a level of security and scalability. An ability to run modern technology much faster, much better, and much more scalable. >> Jeff could you give us a sense as to how far you're into this elevate journey maybe thinking about a couple of customers either specifically or generically, you know, where you're at with them, how far along, maybe even some examples that you feel are representative. >> Sure, you know, the, the relationship has been probably about six, close to seven months of maturity. In that time we've had an opportunity to work on several key clients at scale. We've worked together in collaboration on one of the nation's largest retailers in the grocery business. We've worked collaboratively in aerospace and defense, And also in the hospitality industry. In these cases, what we're finding, and one is, each one is in a various stage of maturity. One is done, one is in midstream, and one is at the early stages. And current economic conditions are driving a huge pipeline right now. I think our challenge right now is making sure that we identify those clients that can best take advantage of our services and our joint offering to deal with that pipeline right now. What we're finding is that the savings are at least as we've projected, in some cases we're finding even more. What people say they have and what people say they do isn't necessarily what you find when you get in there. But almost every case, we're finding that there's unused equipment, unused capacity that they currently have, redundancy, low utilization of their current assets. We can go a long way in streamlining that, plus, I can't emphasize enough that, these days, security is a major concern. And we're adding a layer of security that they could never achieve themselves. I'll start off by saying each deal is really custom built around what a customer really needs, what they're trying to get out of it. Right now, as an example, OPEX is very important. So we're engineering deals in a way that helps customers deal with their financial challenges, especially around OPEX. There are other structures that we can put in place. We have the backing of Oracle finance, so we can be very innovative on deals. They can be when value is attained, they can be milestone based. There's just, I think, a wide variety, I don't want to say unlimited, but a wide variety of different options that we can offer our clients in order to be able to deal with whatever financial challenge or opportunity they may be looking at. >> What does success look like, you know, when you were, you know, just less than a year in. When you're two, three, four, let's say five years in and you look back, what does success look like, Aaron? >> So to me success will, success is going to look like we've gotten a number of these big transformation deals in play, it's in motion naturally between our organizations, not necessarily driven entirely by Jeff and I going out and driving the organizations to behave the right way, it's more in our DNA. But more importantly, I think we've gone into, we've gone beyond the conversation of let's move workloads and we've gone into conversations of let's really talk about how to reimagine your business on top of Oracle's cloud and have an ongoing dialogue that looks at that transformation. Once we hit that point, three, four, five years from now, that'll be a wild success in my book. >> Jeff? Final thoughts. >> Deloitte's been around for 175 years, this is our birthday, this year. And in that time what we've learned is there's no substitute for impact and value added to our clients. In our perspective, what success looks like is client's success, client's success means improved scalability of their operations, securing their technology and their data at a substantially lower cost, so that they can focus on what their core business is and focus less on technology. That's success to Deloitte. >> Great Guys thanks so much, great session. We're not only witnessing the rebirth of Oracle consulting, but there's clearly a transformation going on and it's cultural. Gentlemen, congratulations on your partnership and thanks so much for coming in theCUBE. >> Thank you so much. >> Thanks for having us.

>> Narrator: From the Cube Studios in Palo Alto and Boston, it's the Cube, covering empowering the autonomous enterprise, brought to you by Oracle Consulting. >> Hi everybody, welcome back to this special digital presentation where we are tracking the transformation of Oracle Consulting. Aaron Millstone is back, he's the Senior Vice President of Oracle Consulting and he's joined by Jeff Davis whose Principal at Deloitte, he's the Chief Commercial Officer for Oracle at Deloitte. Gentlemen, good to see you, welcome. We see a lot of these deals, sometimes we call them Barney deals, you know, I love you, you love me, there's a press release and that's it. But, so one of the things we look for, okay, is there teeth behind this? Now, you guys have come up with what you call Elevate. What is Elevate, how did it get started? Then I have some follow up questions. >> Well, Elevate really got started when Aaron and I started to look at the assets that each of the firms possessed. On the Deloitte side as Aaron suggested, we have deep capabilities and a broad range of technologies. Some of them could be technologies with Oracle. At the same time, we didn't have a great deal of depth in Oracle's technical products, Oracle Cloud infrastructure and Oracle Autonomous. Our bench was not as big as Aaron's. And Aaron also had access to Oracle development at a level that we didn't have access to. So we really found ourselves in a situation where we could put those two capabilities together and we could offer something to our clients. And the broad rage of Oracle customers in the field, they had access to all of Deloitte's capabilities, which include great project management, great change management, real skill around the strategic aspects of cloud migration and Aaron had tools and had resources trained and developed around the latest Oracle technology. They'd always be a step ahead of any SI. So together we felt this was really a differentiation for the market place. >> One of the things we look for, is there any other integration? Are you doing co-engineering? In this case maybe not co-engineering, but are there tools that you're developing that you're taking to market that you're actually leveraging? Aaron, can you talk about that a little bit and convince us it's not just a sales play? >> Yeah, sure, and Jeff eluded to some of this earlier too, right. So, we definitely each had our respective tool line, right? Deloitte's investments and tools, one of them's called ATADATA, that we've seen used quite a few times now. We've invested in something we called Oracle Soar. You know, our tools are, as you'd imagine, heavily Oracle focused. It's about moving Oracle technology to Oracle cloud. ATADATA and some of the tools that Deloitte's invested in are focused more comprehensively on wholistically at looking at everything in a data center and everything that's across data centers and start to develop a set of facts around this stuff. But in both cases we actually looked at these things and we said, you know what if you combine these together, we get a very comprehensive view of what exactly it is that we're looking at with a customer. So we can tell everything from the types of traffic we see on the network, to the specific versions of stuff. We can start to identify whether there's risk associated with having things not patched or out of support, but again a very comprehensive view that's based on facts. And so, you know, we took those tools and we combined them together so that we can go in to a customer and give a complete end to end view from both an Oracle and Deloitte perspective. And quite frankly it doesn't matter whether Deloitte leads or whether Oracle leads, we've developed these tools together, we're going to market together, and we've even got, you know, the templates you'd expect consultancies to have right? So when you look at business cases, we've got joint business case templates that we've created together and that we're using actively with customers and then we're refining them and improving them each time we do it. But, you know, we're at a point now where our tools are combined, our templates are combined and we even at this, you know, we were even- Jeff and I were on a call earlier, yesterday actually, we even got a joint war room that's constantly engaging with different account teams and making sure that we structurally approach things in a consistent way so that we're driving business value and using the tools appropriately. >> Aaron you and I have talked about, you know, data centers and building data centers and investing; it's just not a good use of capital today. There are so many other things that organizations can do. You guys have identified data center consolidation as, I'll call it a you know, an initiative that you're seeing customers. I wondered if you could talk about that a little bit, is that kind of a starting point for conversations? >> Yeah, well it's definitely a starting point. So we call it and refer to it as infrastructure lead transformation and the appetite for that is certainly high. We're seeing an increased focus on you know, what do customers need to do to take not just a workload here and there, but how to they get out of the data center business hole? So it's sort of, it's a forgone conclusion. Like you just said, it's not really a question of should we invest in another data center, or should we invest in up-tooling our data centers? The question has changed to, let's move to cloud, how do we get there? And let's move in a big way. And that's, we're seeing that dialogue across all of our customers. And quite frankly, even for Oracle, it's been a learning curve for us, right? We started with an Oracle workload conversation, which is: do you want to move this Oracle workload to Oracle's cloud? Do you want to move that Oracle workload to Oracle's cloud? And really what we're finding is it's a wholesale transformation of everything in a data center to one or more clouds right? Again, often it's a multicloud strategy and that's okay. And we, you know, we're having more-bigger conversations. The thing that has been really interesting is these conversations have evolved and especially as we work with our partners at Deloitte, has been that, you know, we think that the combination of our cloud technology, the consulting services that Oracle consulting and Deloitte can bring to bear and then Oracle's ability to finance the whole deal, makes some very compelling conversations for customers cause you can walk in to a CIO, to a CFO and say look on day one, you can actually have a lower spend than what you have today in your data center, and get a cloud transformation on Deloitte at the same time. >> Let's talk a little bit more about that business case. Is that generally what you're seeing where it starts as let's take some costs right out? And then, Aaron, you and I talked about maybe investing that in the future, but is that really the starting point for the vast majority of customers? Let's cut some costs right away and get a payback immediately? >> So I'd like to share our perspective which is, you know, nobody spends money for the sake of spending money on technology. It's got to have meaningful business value. So the conversation starts with really renewal and a path to the cloud, but there's a natural opportunity for savings and consolidation that we take advantage. We're not simply shifting from your hardware to the cloud. We're actually modernizing, which will result in significant savings. But it also gives the business something that they don't have today at a level of security and scalability. An ability to run modern technology much faster, much better, and much more scalable. >> Jeff could you give us a sense as to how far you're into this elevate journey maybe thinking about a couple of customers either specifically or generically, you know, where you're at with them, how far along, maybe even some examples that you feel are representative. >> Sure, you know, the, the relationship has been probably about six, close to seven months of maturity. In that time we've had an opportunity to work on several key clients at scale. We've worked together in collaboration on one of the nation's largest retailers in the grocery business. We've worked collaboratively in aerospace and defense, And also in the hospitality industry. In these cases, what we're finding, and one is, each one is in a various stage of maturity. One is done, one is in midstream, and one is at the early stages. And current economic conditions are driving a huge pipeline right now. I think our challenge right now is making sure that we identify those clients that can best take advantage of our services and our joint offering to deal with that pipeline right now. What we're finding is that the savings are at least as we've projected, in some cases we're finding even more. What people say they have and what people say they do isn't necessarily what you find when you get in there. But almost every case, we're finding that there's unused equipment, unused capacity that they currently have, redundancy, low utilization of their current assets. We can go a long way in streamlining that, plus, I can't emphasize enough that, these days, security is a major concern. And we're adding a layer of security that they could never achieve themselves. I'll start off by saying each deal is really custom built around what a customer really needs, what they're trying to get out of it. Right now, as an example, OPEX is very important. So we're engineering deals in a way that helps customers deal with their financial challenges, especially around OPEX. There are other structures that we can put in place. We have the backing of Oracle finance, so we can be very innovative on deals. They can be when value is attained, they can be milestone based. There's just, I think, a wide variety, I don't want to say unlimited, but a wide variety of different options that we can offer our clients in order to be able to deal with whatever financial challenge or opportunity they may be looking at. >> What does success look like, you know, when you were, you know, just less than a year in. When you're two, three, four, let's say five years in and you look back, what does success look like, Aaron? >> So to me success will, success is going to look like we've gotten a number of these big transformation deals in play, it's in motion naturally between our organizations, not necessarily driven entirely by Jeff and I going out and driving the organizations to behave the right way, it's more in our DNA. But more importantly, I think we've gone into, we've gone beyond the conversation of let's move workloads and we've gone into conversations of let's really talk about how to reimagine your business on top of Oracle's cloud and have an ongoing dialogue that looks at that transformation. Once we hit that point, three, four, five years from now, that'll be a wild success in my book. >> Jeff? Final thoughts. >> Deloitte's been around for 175 years, this is our birthday, this year. And in that time what we've learned is there's no substitute for impact and value added to our clients. In our perspective, what success looks like is client's success, client's success means improved scalability of their operations, securing their technology and their data at a substantially lower cost, so that they can focus on what their core business is and focus less on technology. That's success to Deloitte. >> Great Guys thanks so much, great session. We're not only witnessing the rebirth of Oracle consulting, but there's clearly a transformation going on and it's cultural. Gentlemen, congratulations on your partnership and thanks so much for coming in theCUBE. >> Thank you so much. >> Thanks for having us.