 Hi, I'm Peter Burris and welcome to another CUBE conversation from our wonderful studios in beautiful Palo Alto, California. Today we're going to be talking about digital transformation, more specifically the tooling that you have to establish and put in place to achieve digital transformation objectives. And to do that, we've got Actian Corporation here today. We're hit to Susos, the president and CEO of Actian. We're hit, welcome to theCUBE. Thank you Peter, I'm glad to be here. Well, we're happy to have you here because this is a really important topic, but before we get into the actual topic, give us the update on what's going on with Actian. Terrific, I'm not sure how much you know about Actian or how much you've followed it, but we've assembled over the years a series of assets that range from data management, data integration and data analytics, really targeted at the next generation of hybrid data management that really helps companies manage their digital transformation. All right, so let's jump into that digital transformation because that's where a lot of the conversation about hybrid starts. So our belief, and I want to test this with you, is that there really is a difference between a business and a digital business, and that difference is the degree to which a digital business treats data as an asset. Absolutely. And in fact, we think that digital transformation is the process by which you re-institutionalize your work, reorganize everything else to achieve the goals of using data as an asset. Does that? Absolutely, and it's not just using data as purely an asset, but it's leveraging the data that an enterprise has or has access to and the quantitative analysis of this to influence all aspects of that business's functions or processes, the way it deals with customers, where it deals with internal processes, and so on. So we think you have to be able to capture data better, you have to be able to turn that data into value, and then you have to be able to act on it. Where does Acti and Fit in that kind of virtuous cycle? So Acti and Fit's all along that chain. We've got the data management assets to allow you to manage that data effectively. We've got the integration assets to allow you to move data to the compute, to compute to the data effectively, and we've got the best high-performing tools to be able to extract insights from that data at scale and do this all on commodity hardware. So you're doing this at a price performance level that you couldn't match elsewhere. So it sounds like, but it sounds really like you're more focused on creating value out of your data. You might be doing some work at the edge and you might have some tooling, some AI tooling and whatnot. So tell us a little bit about how Actian's vision of data warehousing, data analytics, data warehousing, that whole range of capabilities is different because of what the base tooling is capable of doing. Absolutely, so the premise behind Actian is that we're going to supplement an organization's digital strategy or data management strategy. So we're not talking about having to replace stuff en masse, but we're talking about being able to supplement these things where necessary and giving organizations the flexibility to run things on premise or in the cloud, in multi-clouds giving them the flexibility to move from one cloud to the other and so on. Those capabilities, that capability to manage that data whether it's in relational systems, whether it's object-oriented systems, whether it's edge systems, to be able to extract the information from those edge systems, move that along to your central systems and then run analytics through it is what Actian does really, really well. So if I can kind of repeat that back to you. So the idea here is that we've got data in an analytics function that is now, has to be much more high performance than it used to be. That's correct. So that we can do a faster, closed loop, almost operational time set of queries from the analytics back to the transaction systems. Have I got that right? Absolutely, so if you go back a ways, the whole process was, I've got transactional systems here that are generating some information. I pull that information out into an enterprise data warehouse. I've got some things that happen with that. Some results in analytics that are driven off of those and the results may or may not make their way back into operations. Today, the business is slightly different. In this era of hyper personalization, it's no use to me to find out that you were on my website last week and you were looking at these three products and you did buy this last year. I want to understand that you're here and now and I want to understand how best we can make use of your presence on a company's website to sell you something else to give you the next best offer, to know how you're interacting with us at that point and to change the interaction that we have with you. If that's going to take place, that needs to happen while the transaction systems are currently in operation. And so the notion of this operational data warehouse is I'm generating analytics while I've got those transactions in flight. I would even say that it sounds like it's not just the transaction systems are operational, but the transaction is open so that you have, so you need a high performance data store, data manager that's capable of responding while the transactions is open to shape, guide and hyper personalize the characteristics of the transaction. Absolutely. All right, so now let's talk about the hybrid part because you mentioned that earlier. Another belief that we have is that we're going to see a lot of data moved up into the cloud but we think increasingly the cloud is going to move to the data. We're going to see the services associated to the cloud be bought down to the data. Couldn't agree more. And oh, by the way, this move to the cloud, this is not just a one time move. Most people think about movement to the cloud as a one time affair. I've got my data on premise it's going to move to the cloud. No, it's going to move from cloud to cloud. I'm going to have the ability at some point in time to want the ability to run this thing on multiple clouds. I'm not going to risk locking myself into a particular vendor. So this notion of movement of data from premise to the cloud, perhaps from the cloud back to premise and into cloud is here to stay. So the notion of creating a platform or the capability to move this data around to move my compute to that data when I need to is here to stay. It's going to be with us for a while. Well, it's one of the premises of cloud. The whole notion that data has to be made more fungible. You don't want to go to a bank where your money is contingent upon the definition of money by the bank. Absolutely. Same thing exists in cloud. So we want that degree of openness that degree of evolvability. But it also, this is what I'm testing with you is we think increasingly that businesses are going to look at their value propositions, what activities are necessary to deliver on those value propositions, where those activities are going to be extent, are going to be an operation and what data is going to be necessary to satisfactorily and successfully and with high quality perform those. So it means increasingly that the data is going to be, you're going to want to move the data closer to the activity with right performance, manageability, security and everything else in place. That's correct. Or move the compute to the data. So is that kind of the vision that Actian has because you've got this family of data managers that each can start to become associated with certain styles of transactions or, better put, certain styles of compute and work, digital work. Absolutely. Now, we take that one step further. There are people who do this today but many of the approaches that people are using are either cost prohibitive or don't work. What we've done is actually developed a set of approaches that make these approaches accessible. Today, the notion of true operational data warehousing to operational analytics has been available to really the large companies that have invested completely in extracting value from their data assets. We're bringing that value all the way down to enterprises without gigantic IT staffs and without necessarily spending an arm and a leg on some of the bespoke data management systems of yesterday. We're looking at leveraging commodity hardware to really move performance up a notch, taking your traditional Hadoop systems, transitioning those from these swamps that they were into really honest to good this operational data warehousing. So I can actually update and delete and manage these things like I would in any ordinary database. And I've done this on commodity hardware which is distributed across the enterprise. So it is, the commodity hardware allows us to place the processing wherever we want. That's correct. And now we can put the manageability of the data and creating value out of the data. That's correct. Wherever we want. So that we are not constrained by associating the data with the action wherever it needs to be? Absolutely. So as you look forward, what types of future do you anticipate for the evolving role of transaction systems, operational data stores, and digital business? I see them converging. I see that there being a convergence of these, the digital business involves the operational data stores and the transaction and transaction systems. I think you're going to see an increasing number of hybrid systems. These are systems that are good at doing both transactions and analytics out of the same systems. We've got one such one where we've embedded a very high-speed calmer engine into a traditional relational source. That allows us to do very, very rapid reporting off of existing transactional systems but get analytics out of these systems without any additional overhead. Do you anticipate that customers, I mean I do, but do you anticipate that enterprises are increasingly going to look at almost a data control plane? How does that likely to evolve and what role might acting play in that? I think you bring up a very interesting point. For the next generation of data management, there will be a data control plane. We aspire to play in that data control plane. It's not one plane yet and I don't think that the architecture of that one control plane that manages all your data assets across the company is going to come about very soon. Nor is it likely to be one control plane. For the reasons you said, you don't want to get locked in. But we've, acting does play in that control plane to allow enterprises the ability to then move their data selectively from on-premise to the cloud or between these clouds. All right, so Rohit, you're a CEO. You've been around for a long time. A lot of different places. Imagine, put yourself in the seat of another CEO at one of these large companies. What is the message that they need to bring to their senior staff and others in your organization about affecting this core transition with technology to become more data oriented, data friendly and acculturated to data utilization? I think if you're looking at, you're more than likely underestimated the value that's locked in the data that's within your enterprise, either from a customer or a competitive view or a view to improving the processes in your organization. If you task your organization with unlocking the value of these data assets and being able to respond in more real time to some of the customer or the operational requirements, I think that would go a long way. And part of parcel of that is if you've undervalued the data, you're under investing in the tooling to get value out of the data. That's correct. Rohit D'Souza is the president and CEO of Actian Conversation. Once again, Rohit, thanks for being on theCUBE and talking to us about digital transformation and Actian. Thank you very much, Peter. And once again, I'm Peter Burris and this has been another CUBE Conversation. Thanks very much for listening. Until next time.