Drill to Detail - Drill to Detail Ep.70 'Oracle Analytics, Luke Skywalker and the Remarkable Return of Enterprise Analytics' featuring Special Guest Bruno Aziza

Episode Date: July 8, 2019

Mark Rittman is joined by Bruno Aziza, Group Vice President, AI, Data Analytics & Cloud at Oracle to talk about the recently-updated product roadmap for Oracle Analytics, Oracle BI in the marketplace, recent acquisitions in the analytics marketplace and the recent Oracle Analytics Summit at Skywalker Ranch, California.Oracle Analytics SummitOracle Analytics Summit RecapOracle Analytics for Applications: Oracle Analytics Summit Product TourOracle Analytics: Honing 18+ products down to a single brand

So hello and welcome to another episode of Drill to Detail and I'm your host Mark Rittman. I'm joined today by Bruno Aziza, someone who I'm sure our listeners from the world of Oracle Analytics will be aware of, from his role as Group Vice President, AI, Data Analytics and Cloud at Oracle, and from his social media profile photo with Big Data Nerd on his T-shirt. So welcome to the show, Bruno, and why don't you introduce yourself properly to the audience and let us know who you are. Well, thanks for having me on your show, Mark. I'm excited to be here and share with your community. So I think I'm probably connected to a lot of folks that watch this show because I have been in the data and analytics space my entire career. Business Objects that many folks probably know there. I was there when we acquired companies like Crystal Decisions and Crystal Reports. That was a fun ride. From Business Objects, I moved up to Seattle where I followed my boss who was asked to

start Microsoft Business Intelligence. And I worked there for, I want to say, about seven years. And after those seven years, we worked on products that many people will know, Power Pivot, Power BI, Performance Point Server, all these products came out of that team. It was a great experience. It allowed me to go out back to the world of startups that I had been in before Business Objects and helped launch uh three companies uh scicents being one of them uh alpine data labs which was bought by tipco

and then finally at scale and i joined uh oracle here um a few months ago uh to uh head up the uh the team on uh data analytics so what what do you what's your general kind of i suppose remit really at oracle at the moment? So what my team looks at, there's a lot of functions under it. We're in the product team. So, you know, our number one job is to build a product that people can use and, of course, innovate with data. That's the number one charter. There's a few other things as well that, you know, and I call them the three Cs.

The first one is context. We spend a lot of work with customers and particularly analysts and folks like you in the community to really we have lots and lots of options for doing data analytics. And so bringing the context of what the world wants us to build for is important. So I've got a team focused on that. The second one is, and I talked a little bit about it, is customers. We are a customer first group. And so we do a lot of work to initiate contact with customers, help them innovate at scale. And so that's really important for us. And then you talked about events, but events for us are not marketing events.

They are community events. So what we are building is a strong community of folks that, you know, they feel like they have the tools. We've released Udemy training that's available for free. We've got 10,000 people that got trained over the last three months. And basically enabling the community to self-serve to the right tools, meet with each other. We realized that we are only going to be successful when they can connect and we're not in the room. And so that's what my teams do, context, customers, and community. Of course, a lot more around product strategy and so forth but that's really based in the first in the first bullet here where i talked about context building

the right product and the right roadmap for our customers for anybody just maybe first of all for anybody that that is new to oracle analytics or only knew it from a kind of long time ago maybe just give us a very kind of i suppose high, high level overview of what Oracle Analytics is, and then we'll dig into the roadmap after that. Absolutely. So, you know, one of the first things that I did when I joined the company is I called our top customers. And by top customers, I don't mean customers from a revenue standpoint. We looked at the list of customers and picked them across industries and use cases and so forth. And the first thing that they wanted is they wanted clarity on our design centers, where we were building the product and why, and they wanted transparency. And so that's the first thing that we did is we put our roadmap in.

You know, it's interesting. I've been traveling to meet these customers. And when I announced that the roadmap was available at a last customer event, people stood up and I got a standing ovation, which was great, but also a little sad because it's something that I wish we'd had before then. And so overall, what Oracle Analytics is trying to solve

is a few things. I mean, first of all, recognizing our competitive advantage. We're at the intersection of the data and the application world, right? That's our competitive advantage. We're not trying to replicate what you already see from the, you know, the other vendors in the magic quadrant,

which the majority of them are desktop and download types of companies. You know, they've built great franchises with end-user driven applications. And sometimes it worked well because it spread access to the data. And sometimes it worked terribly wrong because it put the wrong data in the wrong hands. And so because we have this understanding of what it means to scale data in a secure manner, enterprise data, we do as much as we can to take advantage of what's called the autonomous data warehouse. So Oracle Analytics takes advantage of the processing power database in the cloud.

It's built for the cloud first, which is a little different from the other vendors that have been in the space for the last 20 years. And it also focuses on what we call continuous analysis and augmented analysis, which is this idea that analytics should be everywhere in your workflows. So if you're in CRM, HCM, ERP, Walker Analytics is powering the analysis of these workflows, popping insights when you might need them the most, et cetera, et cetera. And then finally, the third pillar that's a focus of us is on augmentation uh in augmentation i know we'll talk a little bit about more about later but it's this idea of how do we infuse artificial intelligence to make decisions and more importantly make actions occur faster than they were in the past okay okay so let's go through some of the roadmap then and

there was three i noticed there were three kind of And there were three, I suppose, pillars of what you were doing there. There was self-service, there was governed and augmented. And let's go through it in maybe that order. So self-service, I know from my experience of Oracle Analytics that a lot of effort went into data visualization and generally making the product, I suppose, you know, competitive in that market that was being maybe dominated by Tableau and so on. What's the direction you're going with self-service and what are you trying to achieve with that? And again, how are you differentiating that from every other, you know, point and click vendor out there? So, you know, self-service is

the second era of analytics. And in addition to the roadmap, what I'd love to point people to is we have what I call a context grid, which basically compares our capabilities to some of the top vendors in the space, according to Gartner. We've added videos as well, so you can see specifically what we mean by self-service. But if you think about the beauty about self-service is it enabled a lot of people to get access to data and start working with them quickly. What we're trying to do there is, one, with a center of gravity around the cloud, it makes it a lot easier for you to get access to analytical capabilities without having to deploy any software, asking for access or any of that. So on the self-service side, we're not focusing on making more beautiful dashboards or visual or anything like that. We're focusing on how do we make self-service frictionless

and secure, which is really, really hard. There are some vendors out there that do it well, but in general, the legacy of the self-service era has been that it just hits a wall after a while where you know and this is a an industry stat uh 35 percent of your employees only use analytics and so it's it's a little bit of a shame after over 30 years of an industry that's been focused on trying to deploy analytics to people um and is is failing for about 65% of them. Where we see is the competitive advantage here for Oracle is this idea that analytics should be pointed to line of business.

They should be pointed to manager, regular people that don't necessarily have the time to train themselves on building a dashboard. So what we're doing, and we'll talk about in the augmentation pillar we're doing as much as we can in order to give them the self-service capabilities they're used to you know in traditional bi tools they've seen in the past but also making it easy for them to get access secure access quickly with a cloud first pillar in everything that we build okay okay so so a traditional strength of oracle analytics oracle bi i mean i wrote a book on it at one point was was on the kind of governed side the the kind of the rpd the repository and so on and i mean i mean just you know as a kind of observation it's it's

not been quite so front and center i don't think in the in the in the i suppose in the way the product's been positioned and marketed recently but but there's a lot of value in that. What's your view on the governance side? And where's that going? And where's the, I suppose, what's the next step in things like the repository in Oracle Analytics? So there's a lot of things in that area. And as you pointed, we have a competitive advantage there because we, you know, for 42 years we've been in this market. We are the leader in

in data management for analytics and so everybody knew about that so i think i think the first area is this idea of being able to have an architecture that scales and is massively secured so that's really hard if you have best of breed deployments of multiple tools that don't integrate with each other. We don't have that issue because we have a very broad offer. The second piece that we're doing is how can you be open and govern at the same time? And so having developer and platform extensibility is an important piece that we're working on. We have a huge network of partners that are developing to extend the capabilities of Oracle Analytics, for instance.

We are also building prepackaged models. So if you're an Oracle, let's say HCM or ERP or Oracle NetSuite customer, you're able to now right off the bat get pre-built analytical data models that are highly secure, highly connected to the source of truth. customer, you're able to now right off the bat get pre-built analytical data models that are highly secure, highly connected to the source of truth. That's, as I was saying earlier, I think it's a competitive advantage for us because if

you think about it, we're number one in database, number one in applications, and we're going to build on that foundation. So governance is not just security and policies, but it's integration with the rest of the ecosystem. Okay. What about augmented analytics? I mean, British people are quite cynical. And I think one of the things that there's a lot of hype around AI and something that I've always been looking for is what does this actually mean? What does augmented mean? And what does it mean in almost like tangible terms to people that's right so i think you're right there's a lot of hype there and i think the hype is around oh my gosh the machine's going to replace people and i'm going to lose my job and so uh that's not what we're focused on what we're focused on is uh inserting areas inserting artificial intelligence in places that are either not useful for humans to waste their time on.

So for instance, a typical example, data augmentation, data enrichment, data cleaning, all these areas, we have now algorithms embedded in Oracle and Linux that just basically, once you load the data, we can obfuscate it, we could complement it, we can enrich it, we can clean it, and all of that happens automatically. For instance, if you give us a file with social security numbers, we can enrich it, we can clean it, and all of that happens automatically. For instance, if you give us a file with social security numbers, we're going to secure it right away. If you give us a file with a city, we're going to automatically give you a zip code, country, et cetera, et cetera. So that's the first level that's fairly, it sounds fairly basic,

but it turns out it takes about 70% of the analyst's time to clean and prepare data. So we're trying to get rid of that piece by augmenting with the intelligence that we have, particularly coming from this heritage of being the number one database company. The second piece is in the creation of the dashboard. So there's this thing we call the empty canvas syndrome, ECS. I don't know if you've experienced this yourself, Mark, but typically any BI tool has this problem. You've created a great data environment. You've cleaned the data, and now you're looking at an empty canvas.

The canvas is looking at you, and you don't know what you need to do next. So we have this functionality called Explain, which basically allows you to right click on any dimension or measure inside your model, and it will auto generate dashboards for you. And that's the power of augmented right there, is that now an average person that maybe does not necessarily understand the meaning behind the data is going to be suggested.

Hey, here's the data you should be putting together. Here are some of the visuals. And so you then pick and choose, and then it just constructs your dashboard for you. The whole point here is that if you look at the data analysis pipeline, where are the points of leverage where a machine can do it so much better than a human and more so that we can clear time for humans to do things like judgments um adding gray area where you know it's not binary and or sharing the insights and collaborating and so forth that's really what we're focusing on so auto suggestion intelligence uh embedded in the data process is important. There's another piece of augmentation that I think is particularly unique is we, I think, maybe more than other vendors, recognize that the next interface into analysis is not going to be your keyboard.

It's going to be your voice. It's going to be your mobile phone. So, for instance, we are the only vendor today that supports 27 plus languages for talking to your data. So I could be speaking in French to my database using Oracle Analytics and the data might be in English. It will return the results in a French dashboard. Now, you can imagine why we have that functionality because with half a billion customers across the the world you know we have a lot of multinationals but i i think that's where it's going it's where it's going is the machine has to adapt to the human and in the past 30 years we've we've asked humans to adapt

to the machine and so we're i think we're at a tipping point here and and i think walk was particularly strong advantage there because of our lineage in data and understanding how data is applied. So would you say that Oracle Analytics is where you'd want it to be in the market at the moment? I mean, is it getting the exposure you want? Is it getting the kind of the, I suppose, the recognition and so on? What's your view on its position in people's minds and its position in the market at the moment? Is it where you want it to be? No, it's not getting the recognition that it should get. And, you know, this has been kind of the story of my career. I think every company I've worked at has been an amazing technology vendor that, you know, at the beginning when we started, did not really have the recognition that it deserved. I mean, if I remember the early days of Business Objects,

if some of you listeners remember products like Webby or Enterprise 6 and so forth, I was working during those days, and we were in a good position. We weren't in a leadership position all the way up until the space consolidated and the company sold to SAP for $6 billion. So that was a journey, and a lot of it was really listening to the customers and building something they wanted when i was at microsoft was the same and it took us about seven years to go from you know being developed across three different departments uh to being a brand and a team with a line roadmap uh going after this very

specific market and i think oracle think Oracle is in a much better position than the other vendors that worked out when I began because not only do we have the technology assets, the database and the applications, and we're leaders there, we also made choices four years ago that were a little different than the rest of the market. You know, building for the cloud, building for voice and mobile. Four years ago, that wasn't obvious because the entire analytics market was about a download

and desktop. It really wasn't about mobile. There was probably one vendor back then talking about mobile, but it was really authoring on mobile something that you could see on the web. You know, you look at the mobile Oahu Analytics application and it's completely different from the other offers. And so I think, yeah, I think, you know, you're looking at us now. We're at the beginning of this journey because we've built for cloud. We're going to be able to out-innovate a lot of the vendors that are making their migration to the cloud and subscription at the moment uh so yeah you know talk to me in in uh two to three years and and we'll see if this bet has

has worked out but um i'd say we've got pretty good odds okay and you mentioned cloud there i guess cloud is is you know i can say i can say it's not work for oracle but maybe a kind of blessing and a curse sometimes in that you know you I think it's a lot of appeal to people who are Oracle customers using Oracle Cloud. But, you know, maybe I suppose something I've noticed is less and less non-Oracle customers using Oracle Analytics. You know, again, is that something that you plan to address, hope to address? Is it maybe an unfair thing? But what's the plan to get OAC to appeal to more than just the Oracle market? Oh, absolutely.

So, you know, and we have lots of customers that are not traditional wall-to-wall Oracle customers using Oracle Analytics. And I think that's just the nature of the market. Of course, you know, we're best in class on our applications, on our database. And I think you would expect us to do that because we take care of our customers the non-local customers they're in fact this for local customers as well the reality of the market today is your data is everywhere your data is on premise your data is on your whole cloud it's on all the other guys's clouds I mean I think you saw our partnership with Microsoft is an indication that you know we have a very hybrid world and by hybrid I mean, I think you saw our partnership with Microsoft as an indication that, you know, we have a very hybrid world. And by hybrid, I mean on-prem and cloud.

I mean multi-on-prem and multi-cloud at the same time. And so our goal with Oracle Analytics is to be completely oblivious to all of that. You know, we have customers that have only on-prem data using Oracle Cloud in the cloud. And, you know, Oracle applications, two different systems that are industry data that they're farming out from outside their internal walls. So I think the reality is that you have to be in an open hybrid world. Otherwise, you know, you can't serve your customers. So that's definitely our approach to the market.

We are not closed off to the Oracle world. We're very open. You look at the connectors that we have. We have connectors to a lot of databases that are not Oracle databases direct. There was an acquisition a while ago at Sparkline Data that you guys made. Is that something you're aware of? You work with those guys at all? I was kind of wondering what was happening with that at all.

So there's a lot of acquisitions. There's a lot of market acquisitions that are not Oracle. And we've had certainly our share of acquisitions. I mean, if you start from Siebel and DECA and datascience.com and so forth, all these are part of the Oracle Analytics family. I mean, I think that's what's interesting for a customer today is that you really have two options, right? You either go off and pick the individual vendors and you stitch them together, or you realize that the market is actually changing. If you look at the first three phases of business intelligence have been,

first is highly centralized and business objects was part of that where IT would build the universes and centralize access to the end so forth and that was disrupted by companies like Tableau and Microsoft and Clickdeck that you know said no you got to get information out to the business users. And now we're starting to see, well, in this third phase is what I call the battles of the ecosystem, where now customers are changing their buying habits and they're buying very broadly. They're buying from people that have cloud assets, application assets, database assets, analytics assets and so our job is to make sure that one we're highly integrated we provide the best experience with our stack but we're also open so we can provide uh continuity of service across anybody else's stack um and and uh you know that's that's not easy but that's that's the strategic intent today okay so so moving on a little bit i mean there's been a lot of news

recently uh about acquisitions you know there's been a lot of news uh recently uh about acquisitions you know there's been various acquisitions been made uh i think look have been bought by by google cloud and tableau by salesforce and and i guess the question to you would be do you think i mean i think a certain something that's quite comes out in those acquisitions is i suppose uh analytics uh is moving more back towards the enterprise maybe, or certainly these enterprise vendors that are buying these analytics tools and presumably therefore going to give them enterprise features and sell them to enterprise customers. Do you think what we're seeing here is a bit of a kind of refocus really

on enterprise analytics and away from, as you called it, kind of download and desktop tools? I don't know that it's focused on enterprise analytics. I think it's very good news for the space because you have now companies that were not necessarily involved with data analytics that are finally realizing that data management and data analytics is important to their customers.

We've been doing that for 42 years. So I would say, you you know welcome to the party i would i would say now you know i'm not in the strategy group of these companies so i can't tell you kind of what they're thinking how they're thinking they're going to go to market and so forth but you could i anticipate that they're going to have a fair uh a set of challenges but i i welcome that because i think it continues um to communicate what we've been saying for years, which is, look, data analytics and analytics is the bread and butter of any company. If you think about the most important assets of any company today, the first asset is your people and the second asset is your data. And if you don't know how to keep the best performers, and if you don't know how to

enable them with the right analytics so they can innovate, they'll leave and you could have the best products on earth. You won't be able to compete and win. So I'm not surprised, of course, but I'm a little biased because this is where I invested my entire career, right? I have only worked in data analytics. And so I'm excited to see these developments, and I'm looking forward to seeing them in the marketplace. Okay. Another trend that's been going on in the market, an area I've been involved in quite recently,

is this kind of, I suppose, modular, modern BI stack kind of movement with a lot of open-source tools and the idea that actually it's almost the antithesis of what you're doing at Oracle, where to kind of plug things together, integrate them yourselves, because these days things do integrate together better. I mean, is this something – I see this as being a different type of tool for a different type of use case and customer. But you must be aware of these things. Any kind of thoughts from you on open source BI, modular BI, that sort of thing? Yeah, I think, you know, there has been proliferation of, you know, that sort of thing? Yeah, I think there has been proliferation of dashboard companies,

and there's certainly a lot of open source ways to build your own dashboards, even inside organizations. We talk on a daily basis to organizations that have built their own toolkit, and they're building their own dashboards and so forth. And what I would say there is that as long as it's a focused effort for a team inside an organization, or maybe it's addressing a particular use case that the current industry options are unable to address, I think that's a viable scenario. I would be worried, though, if you were hoping to build a new paradigm there, because after 30 years of experience, I think the story

really is about integration across multiple stacks. I mean, if I think about what we are building, we're building augmentation. So machines can help humans in the places where humans waste their time and are not really happy about that. We talked about a few. Integration, and by integration, I don't mean closed. I actually mean the opposite. By integration, we mean open. customers or maybe there's a small startup that has built particularly clever way of visualizing certain things or maybe transforming particular set of data we have an sdk that allows us to bring that into the bigger platform because integrating the process of analysis is actually fairly complex way so you can't really solve it with a beautiful dashboard and then the third

aspect is collaborative um a simple example is and, people might not know a lot about that, is being able to integrate the analysis process throughout a Slack conversation or a chatbot conversation and so forth. And so any technology that's open and can integrate with that, we will absolutely embrace it because we're trying to advance the agenda of analytics across augmentation, integration, and collaboration. So for sure, lots of options out there. It is becoming increasingly easy to build your own first dashboard using open source tools. But like I said, I think the industry is past that.

I think the industry is past build me a beautiful dashboard. We know what that looks like. The problem has been and continues to be what happens under that. Something we talked about earlier on, I talked about the RPD, the repository, and I suppose the semantic model within Oracle Analytics. And, in fact, Looker recently was acquired, and I think one of the features that I think is a key feature of theirs is their lightweight semantic model. And yet the conversations you've been having with customers,

what are customers telling you that they want out of, I suppose, a business model in analytics and about that kind of, I suppose, that kind of modeled layer there where they want something that helps them understand the data in there, makes it more easy to understand and kind of make sense of it really. What do customers say to you about that so there there are a few things that people want i think the first one is how do i deal with the complexity of different data types different databases and unification of all that so you know having an open way to connect and understand the diversity of data on-prem and cloud, different types, is requirement number one. Requirement number two is how can augmented intelligence or augmented technology enable me to automate the creation of these models? Because I think what's happened, and I mean, it's true of a lot of vendors today, is that the definition of data model is a very IT-centric function.

And because it's a very IT-centric function, there's a few things that unfortunately get in the way. One is it takes time to describe it. It takes time to maintain it. And then once you have it, it might not be described in a way that actually makes sense to the business user. And so the automation, the creation, and the make it business friendly is another one. The third thing that we see, and this is due to the proliferation of analytics inside an organization, you take any organization and they have five different BI tools, and therefore they have five different business models for looking at reality is how can you bring all of those together in one centralized self-service and secure matter? How can you put a stamp on this is the sanctioned model and so forth?

And that's certainly something we understand very well and that not many vendors can do. In fact, the majority of developer-driven data modeling or even business-driven modeling creates this problem in spade and they don't have the tools to actually bring it back to one model that makes sense for the organization.

I mean, this is the typical you know one version of the truth problem but i think um that hasn't been solved um and so we're focused on that because of course you know in any organization um we have that we have the the analytics departments trying to use our stack in concert with you know the five or six different other tools and they're asking to rationalize and so we help them do that okay and on a sort of i suppose a related topic um another strength of of our collapse i'm sorry oracle analytics in the past has been the kind of packaged applications the you know the vertical apps the the you know the apps things like sort of um i suppose financial analytics and so on um i mean to my mind there's

a bit of a contradiction there customers want it to be you know instantly available and to be able to kind of effectively but they also want it to be ins ultimately customizable as well and you know i wonder what's the strategy around around the packaged applications from you guys how do you reconcile those two contradictory things and how do you i suppose in a way how do you i suppose leverage your application space your analytics tools and so on to give people something that's kind of i suppose fast time to value but it's still useful to them yeah so this is an excellent question because you're right that the ideal is to is to have both and and we have two offers for it that enable people to go from one offer to the next. And the two offers are based on the same thing.

So I'll kind of explain. The first one is the product everybody knows, which is the Oracle Analytics Cloud. It is built for the cloud first. It's what you would expect of a self-service, governed, augmented analytics application. It's for the business analyst, and you don't need to install anything and it has all of it for a business user. So that's one. And that's not bound to an application. It's a horizontal application, if you will, that you can use for standardized dashboards. You can use them on top of the applications as well. But once you do that, you have to understand the data in that

application. So you have to model on top of it in order to build your analytical application, if you will. That's offer number one. It's called AllQuantilex Cloud. That offer is also available on-prem or in regulated industries or when you have multi-cloud hybrid environments. It's called AllQuantilex Server. And it enables people to get started with the full-fledged functionality of Oracle Analytics, but deploying it in your own environment so you can move to the cloud at your own pace. So that's offer one. Think about it as it's a horizontal solution.

The second solution that we have built on the Oracle Analytics Cloud platform, if you will, is called Oracle Analytics for Applications. Now, Oracle Analytics for Applications has everything that Oracle Analytics Cloud has. But on top of that, it has pre-built business model powered by the autonomous data warehouse. So what does that mean? That means that if you're an ERP customer, we have, so if you're an ERP customer, and you buy all Coinlytics for applications, what will instantly happen is we have created a business of visuals and metrics and KPIs straight out of your ERP.

Where does it store it? It stores it into the autonomous data warehouse. So then you can go in and using Oracle Analytics further customize the application. So you have two paths, if you will, that are based on the same infrastructure. One is a completely free flow and build your own dashboards and build your own model the other one is a little bit more automated but it also uses the familiarity of the oracle and next stack that you already know so you can further work on it as you'd like so we're trying to give people the ability to have their cake and eat it if you will

with these two offers does that make sense am i answering your question yeah that's good yeah so so the other thing the other thing that i couldn't help noticing you're organizing soon is of fact is actually run now is the the auric analytics summit so what was that and and what was the what was the purpose of that and maybe kind of give us some of the news that happened there as well sure so there's a few things that happen. And again, it goes back to what we started the call with, which is, you know, we're a customer first organization. And so the first thing I talked about was, you know, people wanted to get transparency and a sense of direction what we're building, what we're building for. We give them the roadmap available online and we keep updating that so you know what we're doing. They also wanted to understand the context. How do we

compare with the other tools they're evaluating? We have a set of resources on that. We're also giving context on the types of products that they might have had and what they want to upgrade to and so forth. So we've got a lot more guidance now available online. The third thing people wanted us to do was create a moment in time where they can connect with the rest of the community. As I was saying earlier, we've got lots and lots of customers across the world, and they might not know each other well. And so we thought that the best way to kind of do this is to bring them all together in

one location, the Skywalker Ranch north of San Francisco, to connect across a whole day of best practices. In that event, there's only 15 minutes of us talking. So if you can imagine an entire day of content with an Oracle event and all we did is talk for 15 minutes. After that, it was customer presentations, customer demos, partners coming in and sharing their commitment to the community. Because the idea is that what we want to do is after this event we want people to

just connect with each other and share and then communicate back to the community what they've done. We also announced our new packaging and pricing and I'll let you go to the press release on that. It's really quite differentiated and I think make a lot of people very happy about how we're listening to their requirements and how we are evolving the Oracle Analytics story and products and package so they can be effective day one with our product. Fantastic. So, I mean, just to kind of round up then then how would somebody go and get uh how would they get experience with this everybody how would they go and maybe sort of play around with oac or generally sort of find out more about the things you've been talking about

absolutely so there is uh three easy ways here the first way is that you can get all analytics desktop for free just go and google i could give you the url if you'd like mark but it's fairly easy to google and you can you can just download that and then get a taste of what it's like if you don't want to do it through a cloud trial which you could do as well the second thing you should do is go to udemy.com and search for oracle analytics we have two courses that are entirely free that are available for you to just get your first uh taste of uh or analytics the course is based on the desktop product by design so there's really no friction no barrier uh for you to um to access like i said you know

if you go and see the stats of the folks over the last three months, we have trained over 10,000 people on this. It's a very popular course and I think people have been wanting for us to do that and it's brand new. And again, we keep updating that and there'll be new courses coming out for the rest of the year. And then the third thing is join the community. So if you go to LinkedIn and you type in Oracle Analytics, we have a fairly large LinkedIn group where we share customer videos and best practices.

So an example of such a program is a program that we just created called Destination Insights. And Destination Insights is a weekly web series where I sit down for six to ten minutes with a customer, and we talk through their journey. Again, entirely free, available on YouTube, not a marketing video, right? It's purely an interview of one of your peers, and they go through their do's and don'ts and the tribulations, if you will, of your journey. And it's highly entertaining but also it's connected with our goal which is we want people in the community to connect with each other

we don't have to be in the room because you the customer is the innovation and so we build the product and get the honor to serve you and so every program that i built is around that that's great well bruno it's been fantastic speaking to you and uh you know hopefully i we hear a lot more about you and what you're doing with Oracle Analytics. And yeah, it's great to have a great advocate for the product there. So yeah, thank you very much. And yeah, take care. Thank you very much for having me, Mark. you you Thank you.