 Well, thank you, Gary. Well, you know, reasonable people can debate when the so-called big data era started. But for me, it was in the fall of 2010 when I was sleepwalking through this conference in Dallas. And the conference was focused on data being a liability. And the whole conversation was about how do you mitigate the risks of things like work and process and smoking gun emails. I got a call from my business partner, John Furrier who said to me, get to New York and come and see the future of data. We're doing theCUBE at Hadoop World tomorrow. I subsequently, I canceled about a dozen meetings that I had scheduled for the week. And with only one exception, every one of the folks I was scheduled to meet said, what's a dupe? Well, I flew through an ice storm across country. I got to the New York Hilton around 3 a.m. And I met John in the dark bar, if any of you remember that little facility. And I caught a little shut eye. And then the next day, I met some of the most interesting people in tech during that time. They were thinking a lot differently than we were used to. They looked at data through a prism of value. And they were finding new ways to do things like deal with fraud. They were building out social networks. They were finding novel marketing vectors and identifying new investment strategies. The other thing they were doing is they were taking these little tiny bits of code and bringing it to really large sets of data. And they were doing things that I hadn't really heard of, like no schema on right. And they were transforming their organizations by looking at data, not as a liability but as a monetization opportunity. And that opened my eyes. And theCUBE, like a lot of others, bet its business on data. Now, over the past decade, customers have built up infrastructure and have been accommodating a lot of different use cases. Things like offloading ETL, data protection, mining data, analyzing data, visualizing. And as you know, you no doubt realize, this was at a time when the cloud was really kind of nascent. And it was really about startups and experimentation. But today, we've evolved from the wild west of 2010. And many of these customers, they're leveraging the cloud for of course ease of use and flexibility it brings, but also they're finding out it brings complexity and risk. I want to tell you a quick story. Recently, I was interviewing a CIO in theCUBE and he said to me, if you just shove all your workloads into the cloud, you might get some benefit but you're also going to miss the forest or the trees. You have to change your operating model and expand your mind as to what is cloud and create a cloud-like experience that spans your on-premises workloads, multiple public clouds, and even the edge. And you have to reimagine your business and the possibilities that this new architecture, this new platform can bring. So we're going to talk about some of this today in a little bit more detail and specifically how we can better navigate the data storm and what's the role of hybrid cloud. I'm really excited to have two great guests. Manish Desar is the managing director and the North America lead for analytics and artificial intelligence at Accenture. And Anupam Singh is the chief customer officer for Cloudera. Gentlemen, welcome to theCUBE. Great to see you. Hi there, good to see you again. All right, guys. Anupam, you and Manish, you heard my little monologue up front. Anupam, I'll start with you. What would you, anything you'd add, amend, emphasize, you know, share a quick story. Yeah, Dave, thank you for that introduction. It takes me back to the days when I was an article employee and went to this 14 people meetup. Just a couple of pizzas talking about this thing called Hadoop. I'm just amazed to see that today, we are now at 2,000 customers who are using petabytes of data to make extremely critical decisions. Reminds me of the fact that this week, a lot of our customers are busy thinking about elections and what effect it would have on their data pipeline. Will it be more data? Will it be more stressful? So totally agree with you and also agree that Cloudera is almost still in early days and times about the culture of IT on how to use the cloud. And I'm sure we'll talk about that today in greater detail. Yeah, most definitely. Manish, I wonder if we could, we could get your perspective on this. I mean, back when Anupam was at Oracle, you'd shove a bunch of data, maybe you'd attach a big honking disk drive, you'd buy some Oracle licenses, it was a Unix box, everything went into this God box. And then things changed quite dramatically, which was awesome, but also complex. And you guys have been there from the beginning. What's your perspective on all this? Yeah, it's been fascinating just to watch the market and the technology evolve. And I think the urgency to innovate is really just getting started. We're seeing companies drive growth from 20% in cloud today to 80% cloud in the next few years. And I think the emergence of capabilities like hybrid cloud, we're going to offer a lot of flexibility for companies who have the ability to keep some data in a private setting but be able to share the rest of the data in a public setting. I think we're just starting to scratch the surface of it. So let's talk a little bit about what is a hybrid cloud. Anupama, I wonder if you could take this one and at least start with you. And then Manish will come back to you to get the customer perspective as well. I mean, it's a lot of things to a lot of people, but what is it? Why do we need it? What's the value? Yeah, I could think poetic about Kubernetes and containers, et cetera, but given that we talk to customers a lot, all three of us, from the customer's perspective, hybrid cloud is a lot about collaboration and ease of procurement. A lot of our customers, whether they're in healthcare, banking, or telco are being asked to make the data available to regulatory authorities, to subsidiaries outside of their geography. When you need that data to be available in other settings, taking it from on-prem and making it available in public cloud enables extreme collaboration, extreme shared data experience, if you will, inside the company. So we think about hybrid like that. Manish, anything you'd add? How are your customers thinking about it? I mean, in a very simple way, it's a structure that we're allowing mixed computing storage and service environments that's made up on-prem structures, private cloud structures and public cloud structures. We're often calling it a multi-cloud or mixed cloud. And I think the really big advantage is this model of cloud computing is enabling our clients to gain the benefit of public cloud setting while maintaining their own private cloud or sensitive and mission-critical and highly regulated computing services. That's also allowing our clients and organizations to leverage the pay as you go model, which is really quite impressive and attractive to them because then they can scale their investments according to it. Clients can combine one or more public cloud providers together in a private cloud and a multi-cloud platform. The cloud can operate independently of each other, communicate over an encrypted connection. This dynamic solution offers a lot of flexibility and scalability, which I think is really important for our clients. So, Minesh, I wonder if we can stay there. How do your customers decide? How do you help them decide what the right mix is? What the equilibrium is? How much should be in on-prem? How much should be in public or across clouds or eventually, well, the edge, I guess, decide for us? But how do you go through the, what are the decision points there? Yeah, I think that's a great question, Dave. I would say there's several factors to consider when developing a cloud strategy that's the right strategy for you. Some of the factors that come to my mind when contemplating it, one would be security. Are there data sets that are highly sensitive that you don't want leaving the premise versus data sets that need to be in a more shareable solution? Another factor I'd consider is speed and flexibility. Is there a need to stand up and stand down capabilities based on the seasonality of the business or some short-term demands? Is there a need to add and remove scale from the infrastructure and that quick pivot and that quick reaction is another factor they should consider? The third one I'd probably put out there is cost. Large data sets and large computing capacities often much more scalable and cost-effective in a cloud infrastructure so there's lots of advantages to think through there. And maybe lastly, I'd share, is the native services. A lot of the cloud providers enable a set of native services for ingestion, for processing, for modeling, for machine learning that organizations can really take advantage of. I would say if you're contemplating your strategy right now, my coaching would be get help. It's a team sport. So definitely leverage your partners and think through the pros and cons of the strategy. Establish a primary hyperscaler. I think that's gonna be super key. And maximize your value to optimizing the workload, the data placement and really scaling the run and operations. And lastly, maybe they move quickly, right? Each day that you wait, you're incurring technical debt in your legacy environment that's gonna increase the cost and barrier to entry when moving to the new cloud hybrid show. Thank you for that, Anupama. I wonder if we could talk a little bit about the business impact. I mean, in the early days of big data, yes, it was a heavy lift, but it was really transformative. When you go to hybrid cloud, is it really about governance and compliance and security and getting the right mix in terms of latency? Are there other business impacts that are potentially as transformative as we saw in the early days? What are your thoughts on that? Absolutely. It's the other business impact that are interesting. You know, Dave, let's say you're in the line of business and I come to you and say, oh, there's cost, there's all these other security governance benefits. It doesn't ring the bell for you. But if I say, Dave, you used to wait 32 weeks, 32 weeks to procure hardware and install software, but I can give you the same thing in 30 minutes. It's literally that transformative, right? Even on-prem, if I use cloud-native technology, I can give something today within days versus weeks. So we have banks, we have a bank in Ohio that would take 32 weeks to rack up a 42 node server. Yes, it's very powerful. You have 42 nodes on it, 42 things stacked on it, but still it's taking too much time. So when you get cloud-native technologies in your data center, you start behaving like the cloud and you're responsive to the business. The responsiveness is very important. That's a great point. I mean, in fact, you know, there's always this debate about is a cloud, you know, public cloud, is it more expensive? Is it more expensive the rent than it is to own? And you get debates back and forth based on your perspective. But I think at the end of the day, what Anupam, you just talked about, it may oftentimes could dwarf any cost factors if you can actually move that fast. Now cost is always a consideration, but I want to talk about the migration path if we can, Manish. How should customers think about migrating to the cloud? Migration's an evil word. How should they think about migrating to the cloud? What's the strategy there? Where should they start? No, I think you should start with kind of a use case in mind. I think you should start with a particular data set in mind as well. I think starting with what you're really seeking to achieve from a business value perspective is always the right lens in my mind. This is the decade of time technology and cloud to the business value, right? So if you start with, I'm seeking to make a dramatic upsell or dramatic change to my top line or bottom line, start with a use case in mind and migrate the data sets and elements that are relevant to that use case, relevant to that value lever, relevant to that unlock that you're trying to create. That I think is the way to prioritize it. Most of our clients are going to have tons and tons of data in their legacy environment. I don't think the right way to start is to start with a strategy that's going to be focused on migrating all of that. I think the strategy is start with the prioritized items that are tied to the specific value of the use case you're seeking to drive and focus your transformation and your migration on that. So guys, I've been around a long time in this business and I've been an observer for a while and back in the mainframe days, we used to have a joke called CTAM when we talk about moving data, it was called the Chevy Truck Access Method. So I want to ask you on the problem, how do you move the data? It's like an Einstein saying, right? Move as much data as you need to, but no more. So what's going on in that front? What's happening with data movement? And do you have to make changes to the applications when you move data to the cloud? So there's two design patterns, but I love your Chevy story because when you have a 30-petabyte system and you tell the customer, hey, just make a copy of the data and everything will be fine, that will take you one and a half years to make the copies aligned with each other. Instead, what we have seen is the biggest magic is workload analysis. You analyze the workload, you analyze the behavior of the users and say, so let's say Dave runs dashboards that are very complicated and Manish waits for compute when Dave is running his dashboards. If you're able to gather that information, you can actually take some of the noise out of the system. So it takes selected sets of hot data and you move it to public cloud, process it in public cloud, maybe even bring it back. Sounds like sound friction, but the good news is you don't need a Chevy to take all that data into public cloud. It's a small amount of data. So that's one reason. The other pattern that we have seen is, let's say Manish needs something, is a data scientist and he needs some really specific type of GPUs that are only available in the cloud. So you pull the data set out that Manish needs so that he can get the new silicon, the new libraries in the cloud. Those are the two patterns that if you have a new type of compute requirement, you go to public cloud, or if you have a really noisy tenant, you take the hot data out into public cloud and process it there. Does that make sense? Yeah, it does. And it sort of sets up this notion. I was sort of describing up front that the cloud is not just the public cloud. It's the spans on-prem and multi-cloud and even the edge. And it seems to me that you've got a metadata opportunity, I'll call it, and a challenge as well. I mean, there's got to be a lot of R&D going on right now. You hear people talking about cloud native and I wonder on upon if you could stay on that. I mean, what's your sense as to how, what the journey is going to look like? I mean, we're not going to get there overnight. People have laid out a vision of this sort of expanding cloud and I'm saying it's a metadata opportunity but the system has to know what workload to put where, based on a lot of those factors that you guys were talking about, the governance, the laws of the land, the latency issues, the cost issues, how is the industry on upon sort of approaching this problem and solving this problem? I think the biggest thing is to reflect all your security governance across every cloud as well as on-prem. So let's say a particular user named Manish cannot access financial data, revenue data. It's important that that data as it goes around the cloud, if it gets copied from on-prem to the cloud, it should carry that quality with it. A big danger is you copy it into some object storage and you're absolutely right there. Metadata is the goal there. If you copy that data into an object storage and you lose all metadata, you lose all security, you lose all authorization. So we have invested heavily in something called shared data experience, which reflects policies from on-prem all the way to the cloud and back. So we've seen customers needing to invest in that but some customers rent whole hog on the cloud and they realize that putting data just in these buckets of object storage, you lose all the metadata and then you're exposing yourself to some breach and security issues. Manish, I wonder if we could talk about, thank you for that on the pump. Manish, I wonder if we could talk about, imagine a project, okay? Wherever I am in my journey, maybe you can pick your sort of sweet spot in the market today. What's the fat middle, if you will? What does a project look like when I'm migrating to the cloud? I mean, what are some of the, who are the stakeholders? What are some of the out of scope, maybe expectations that I better be thinking about? What's kind of timeframe? How should I tackle this? So it's not like a big giant expensive. Can I take it in pieces? What's the state of the art of a project look like today? Yeah, lots of thoughts come to mind, Dave, when you ask that question. There's lots to pack. As far as who the buyer is and what the project is for, this is out migration is directly relevant to every officer in the C-suite in my mind. It's very relevant for the CIO and CTO. Obviously it's going to be their infrastructure of the future and certainly something that they're going to need to migrate to. It's very important for the CFO as well. These things require a significant migration and a significant investment from enterprises to kind of position there. And it's very relevant all the way up to the CEO. Because if you get it right, the truly the power it unlocks is illuminates parts of your business that allow you to capture more value, capture a higher share of wallet, allows you to pivot. A lot of our clients right now are making a pivot from going from a products organization to an Azure service organization and really using the capability of the cloud to make that pivot happen. So it's really relevant kind of across the C-suite. As far as what a typical program looks like, I always coach my clients just like I said to start with a value case in mind. So typically what I'll ask them to do is kind of prioritize their top three or five use cases that they really want to drive and then we'll land a project team that will help them make that migration and really stay allowed data and analytics on the cloud that are focused on those use cases. Great, thank you for that. I'm glad you mentioned the shift in the mindset from product to Azure service. We're seeing that across the board now. Even infrastructure players are jumping on the bandwagon and borrowing some sort of best practices from the SaaS vendors. And I wanted to ask you guys about, I mean as you move to the cloud, one of the other things that strikes me is that you actually get greater scale but there's a broader ecosystem as well. So we're kind of moving from a product-centric world and with SaaS we've got this sort of platform-centric and now it seems like ecosystems are really where the innovation is coming from. I wonder if you guys could comment on that maybe Anupam you could start. Yeah, many of our customers as I said are all about sharing data with more and more lines of businesses. So whenever we talk to our CXO partners, our CIO partners, they are being asked to open up the big data system to more tenants. The fear is of course, if you add more tenants to a system it could get, the operational SLA might get violated. So I think that's a very important part as more and more collaboration across the company, more and more collaboration across industry. So we have customers who create sandboxes. These are healthcare customers who create sandbox environments for other pharma companies to come in and look at clinical trial data. In that case, you need to be able to create these fenced environments that can be run in public cloud but with the same security that you expect out. Yeah, thank you. Minish, this is your wheelhouse as Accenture. You guys are one of the top two or three or four organizations in the world in terms of dealing with complexity. You've got deep industry expertise and it seems like some of these ecosystems as Anupam was just sort of describing in a form around industries, whether it's healthcare, government, financial services and the like. But maybe your thoughts on the power of ecosystems versus the power of many versus the resources of one. Yeah, listen, I always talk about this is a team sport, right? And it's not about doing it alone. It's about developing these ecosystem partners and really leveraging the power of that collective group. And I've encouraged my clients to start thinking about, the key thing you want to think about is how you migrate to becoming a data-driven enterprise. And in order for you to get there, you're going to need ecosystem partners to go along the journey with you to help you drive that innovation. You're going to need to adopt a pervasive mindset to data and democratization of that data everywhere in your enterprise. And you're going to need to refocus your decision-making based on that data, right? So I think partner ecosystem partnerships are here to stay. I think what we're going to see, Dave, is at the beginning of the maturity cycle, you're going to see the ecosystem expand with lots of different players and technologies kind of focused on industry. And then I think you'll get to a point where it starts to mature and starts to consolidate as ecosystem partners start to join together through acquisitions and mergers and things like that. So I think ecosystem is just starting to change. I think the key message that I would get to our clients is take advantage of that. There's too much complexity for any one person to kind of navigate through on your own. It's a team sport. So take advantage of all the partnerships you can create. Well, Manisha, one of the things you just said that it kind of reminds me, you said data-driven organizations. And if you look at the pre-COVID narrative around digital transformation, certainly there was a lot of digital transformation going on, but there was a lot of complacency too. I talked to a lot of folks at companies that say, you know, we're doing pretty well. Our bank's kicking butt right now. We're making a ton of money. Well, you know, all that stuff, that's kind of not on my watch. I'll be retired before then. And then it was the old, if it ain't broke, don't fix it. And then COVID breaks everything. And now if you're not digital, you're out of business. And so on upon, we'll start with you. I mean, to build a data-driven culture, what does that mean? That means putting data at the center of your organization, as opposed to around and stovepipes. And this, again, we talked about this. It sort of started before even, or the early parts of the last decade. And so it seems that there's cultural aspects. There's obviously technology, but there's skillsets. There's processes. You've got a data lifecycle and a data, what I sometimes call a data pipeline, meaning an end-to-end cycle. And organizations are having to rethink really, putting data at the core. What are you seeing specifically as it relates to this notion of data-driven organization and data culture? What's working? You have three favorite stories. And your 100% digital transformation has been hyper-accelerated with COVID, right? So our telco customers, for example, Manish had some technical problems with bandwidth just 10 minutes ago. Most likely he's going to call his ISP. The ISP will most likely load up a dashboard in his zip code. And the reason it gives me stress, this entire story is because most likely it's running on a big data system that has to collect data every 15 minutes and make it available. Because you'll have a very angry Manish on the other end if you can't explain when is the internet coming back? Right? So as you said, this has accelerated our telco providers, our telco customers' ability to ingest data because they have to get it in 15-minute increments, not in 24-hour increments. So that's one. On the banking sector, what we have seen is uncertainty has created more needs for data. So next week is going to be very uncertain. All of us know elections are upcoming. We have customers who are preparing for that by additional variable capacity, elastic capacity, so that if investment bankers start running hundreds and thousands of reports, they better be ready. So it's changing the culture at a very fundamental level, right? And my last story is healthcare. You're running clinical trials, but everybody wants access to the data. Your partners, the government wants access to the data, manufacturers wants access to the data. So again, you have to accelerate digital transformation on how do you share very sensitive, private healthcare data without violating any policy. But you have to do it quick. That's what code is talking about. Thank you for that. Well, I want to come back to hybrid clocks. I know a lot of people in the audience are want to learn more about that. And they have a mandate really to go to cloud, generally about hybrid specifically. So Manisha, I wonder if you could share with us, maybe there's some challenges there. What's the dark side of hybrid? What should people be thinking about that they don't want to venture into this way. They want to go that way. What are some of the challenges that you're seeing with customers and how are they mitigating them? Yeah, Dave, it's a great question. I think there's a few items that I would coach my clients to prioritize and really get right when thinking about making the migration happen. First of all, I would say integration. Between your private and public components, that can be complex. It can be challenging. It can be complicated based on the data itself, the organizational structure of the company, the number of touches and authors we have on that data and several other factors. So I think it's really important to get this integration right with some clear accountabilities, build automation where you can and really establish some consistent governance that allows you to maintain these assets. The second one, I would say is security. When it comes to hybrid cloud management, any transfers of data need to handle the strict set of policies and procedures, especially in industries where that's really relevant like healthcare and financial services. But using these policies in a way that's consistent across your environment and really well understood with anyone who's touching your environment is really important. And the third I would say is cost management. All the executives that I talk about have to have a cost management angle to it. Cloud migration provides ample opportunities for cost reduction. However, many migration projects can go over budget when all the costs are factors in, right? So your the cloud vendors, you've got to be mindful of kind of the charges on accessing premise applications and scaling costs that maybe need to be budgeted for and where possible anticipated and really planned for. Excellent. So Anupama, I wonder if we could go a little deeper on, we talked a little bit about this, but kind of what you put where, which workloads. What are you seeing? I mean, how are people making the choice? Are they saying, okay, this cloud is good for analytics. This cloud is good. Well, I'm a customer of their software. So I'm going to use this cloud or this one is the best infrastructure and they got most of the most features. How are people deciding really what to put where? Or is it, hey, I don't want to be locked into one cloud. I want to spread my risk around. What are you seeing specifically? I think the biggest thing is just to echo what Manish said is business comes in and has a complaint. So most projects that we see on digital transformation and on public cloud adoption is because business is complaining about something. It's not for architectural goodness. It is not for just innovation for innovation, say. So the biggest thing that we see is what we call noisy neighbors. A lot of dashboards, you know, because business has become so intense, click, click, click. You're actually putting a lot of load on the system. So isolating noisy neighbors into a cloud is one of the biggest patterns that we have seen. You take the noisiest tenant on your cluster, noisiest workload and you take them to public cloud. The other one is data scientists. They want new libraries. They want to work with GPUs. And to your point, Dave, that's where you select a particular cloud. Let's say there's a particular type of silicon that is available only in that cloud. That GPU is available only in that cloud. Or that particular artificial intelligence library is available only in a particular cloud. That's when customers say, hey, Mr. Data Scientist, why don't you go to this cloud while the main workload might still be running on there? That's the two patterns that we assume. Great, thank you. And I wonder if we can end on a little bit of looking to the future and maybe how this is all going to evolve over the next several years. I mean, I like to look at a spectrum, at a journey. It's not going to all come at once. I do think the edge is part of that. But it feels like today we've got, you know, multi-clouds are loosely coupled in a hybrid is also loosely coupled, but we're moving very quickly to a much more integrated. I think when you should talk about integration, where you've got state, you've got the control plane, you've got the data plane, and all this stuff is really becoming native to the respective clouds and even bring that on-prem and you've got now hybrid applications and much, much tighter integration and build this build out of this massively distributed, maybe going from like a hyper-converged to hyper-distributed, again, including the edge. So I wonder, Manish, we can start with you. How are your customers thinking about the future? How are they thinking about, you know, making sure that they're not going down a path where they're going to incur a lot of technical debt. I know there's sort of infrastructure as code and containers and that seems necessary and insufficient. There's a lot of talk about, well, maybe we start with a functions-based or a serverless architecture. There's some bets that have to be made to make sure that you can future-proof yourself. What are you recommending there, Manish? Yeah, listen, I think we're just getting started on this journey. And like I said, it's really exciting time and I think there's a lot of evolution in front of us that we're going to see. You know, I think, for example, I think we're going to see hybrid technologies evolve from public and private thinking to dedicated and shared thinking instead. And I think we're going to see advances in capabilities around automation and computer federation and evolution of consumption models of that data. But I think we've got a lot of kind of technology modifications and enhancements ahead of us. As far as companies and how they future-proof themselves, I would offer the following. First of all, I think it's a time for action, right? So I would encourage all my clients to take action now. Every day spent in legacy adds to the technical debt that you're going to incur and it increases your barrier to entry. The second one would be move with agility and flexibility. That's the underlying value of hybrid cloud structures. So organizations really need to learn how to operate in that way and take advantage of that agility and that flexibility. We talked about creating partnerships and ecosystems. I think that's going to be really important. Gathering partners and thought leaders to help you navigate through that complexity. And lastly, I would say monetizing your data, keeping a value-led approach to how you viewed your data assets and force a function where each decision in your enterprise is tied to the value that it creates and is backed by the data that supports it. And I think if you get those things right, the technology and the infrastructure will serve. Excellent. Anupam, why don't you bring us home? I mean, you've got a unique combination of technical acumen and business knowledge. How do you see this evolving over the next three to five years? Oh, thank you, dude. So technically speaking, adoption of containers is going to steadily make sure that you're not aware even of what cloud you're running on that day. So the multi-cloud will not be a requirement even. It will just be obviated when you have that abstraction there. Culturally, it's going to be a bigger challenge. So I would echo what Manish had thought today, especially on the cultural side. It is great that you don't have to procure hardware anymore, but that also means that many of us don't know what a cloud bill is going to be next month. It is a very scary feeling for your TIO, I'm your CFO that you don't know how much you're going to spend next month, but it's next year, right? So you have to be agile in your financial planning as much you have to be agile in your technical planning. And finally, I think you hit on it. Ecosystems are what makes data great. And so you have to start from day one, that if I am going on this cloud solution, is that data shareable? Am I able to create an ecosystem around that data? Because without that, it's just somebody running a report may or may not have value to the business. That's awesome, guys. Thanks so much for a great conversation. We're out of time. And I want to wish everybody a terrific event. Let me now hand it back to Vanita. She's going to take you through the rest of the day. This is Dave Vellante for theCUBE. Thanks.