Leadership Insights: Dataware

Transcript

Mike Vizard: Hello, and welcome to the latest edition of the Digital CxO Leadership Insight series. I’m your host Mike Vizard. Today we’re with Dan DeMers, who is CEO and founder of Cinchy. They make a platform that kind of helps you separate your data from the rest of your applications and not tie that data to any one application. And now we’re talking about the rise of dataware and a new report that they’ve come out with. Dan, welcome the show. Thanks for having me. Happy to be here. Right now, just about everybody’s going well, what is dataware? So maybe you might want to explain that a little bit? What’s going on behind the concept? And what’s in this report?

Dan DeMers: Sure, yeah, you actually summed it up pretty nicely at the beginning, it’s the liberation of data from individual applications. And by doing that, the world changes, things like integration become obsolete, data is at the fingertips for business users to not only see and change, but what it’s really doing is addressing the underlying root cause of all of this complexity that we’ve been chasing the symptoms for for many decades now. So it’s a really big deal, like hardware software data, where we’re very excited about the paradigm shift.

Mike Vizard: What makes it possible to do that now, because we’ve all been talking about technology level, you know, the separation of data, to a separate, isolated artifact in its own right from the applications for years, I can remember going back talking about XML was supposed to free us from all this stuff. So what’s changed? And what are the implications?

Dan DeMers: So there’s been a lot of innovations, of course, as we’ve been experimenting towards, I’d say, providing symptomatic relief. And when I say we, I mean the broader industry. So there’s a bunch of kind of forces converging – the realization of the importance of metadata and the ability to activate that metadata, the realization of the importance of federation versus centralization of something like a data model. So there’s a lot of hype and buzz around the the concept of a data mesh as an example of enabling decentralization of that. And when you start to blend and blur all these concepts and new ways of thinking together, that’s, I think, the big spark that makes dataware not only possible, but inevitable and kind of here now. And if you think about like we’ve been, from data to data warehouses to data lakes, to data lake houses, to data mesh, like all of these things, they’re essentially chasing the tail of it, they’re addressing the symptom, but it’s too late – the data is managed in silos, and you’re working around that. Really, what we’re doing is – why not fix the source problem? And then you don’t have to work around it anymore. And I think it’s taken us a whole lot of iterations across many decades to have that realization. And then the technology kind of follows that realization. So that’s kind of where we are today.

Mike Vizard: Yeah, I think one of the things that people don’t really realize is the degree to which the data is locked into the applications that they’re using. And it kind of begs the question whose data isn’t at the beginning in the first place. So then we need to have a giant sit down with ourselves and say, you know, just because we enter data in an application didn’t mean we gave up control of it. So is this as much an ownership and control issue?

Dan DeMers: Ya know, a very, very good point; the ownership of data is irrelevant if you can’t have control over that data. And as soon as data is entered into an application where that application takes away your control, not only that – it’s integrating that data with other applications, which is further degrading control. You know that’s what ails the world. Today’s people just don’t have any control over data. What information can you trust? You know, we’re in this post truth era. Are we in the pre-truth era and dataware gets us there? Right? The idea of access, not copies, collaboration, not integration, quite frankly, is the only way that any individual or organization is ever going to get control over their data. And without that, owning it is irrelevant.

Mike Vizard: A lot of organizations are struggling with their digital business transformation issues. Do you think that this data control issue is kind of at the root cause of many of those issues? Because I am spending so much time and effort trying to stitch different things together, and the data is always out of sync?

Dan DeMers: Yeah, for sure. There’s the lack of control the inability to trust that information. But there’s also the inefficiency of having to do this wacky thing we call data integration. And in my experience that easily wastes half of the IT energy and capacity of most companies on the planet and gets more expensive as we add more digital capabilities. So it is a huge tax that limits organizational agility for everyone. And by freeing that up, you’re focusing on enabling business capabilities with that exponential integration tax. And so Yeah, I actually think that, by far, this is the single largest impediment to organizational agility. And by by actually providing a path toward a solution, it’s going to be today it’s a differentiator. Tomorrow, it will be an existential requirement. If you’re not, if you have not set the speed on the journey of separating your data from your applications and having liberated data, in the future, you’ll be out of business.

Mike Vizard: How do we get to what you’re describing? Because we have so many legacy platforms out there already, we have applications that have tons of data. And we have this massive amount of infrastructure to integrate it all. But do I just draw a line in the sand and say, we’re starting over? Or can I go back and and get that data somehow or other?

Dan DeMers: Yeah, well, if you take the position of let’s draw a line in the sand and start over, you’ll probably lose your job. So I would not recommend that. But what you can do is draw a line in the sand and say, going forward, when we deliver projects, we can change how we deliver those projects to enable the gradual untangling of our data, the gradual liberation of that data. So if your next project requires you to tap into data from a mainframe, and from a SaaS platform; why integrate when you can liberate and use dataware – bring that data in, knowing it’s the last time you ever need to integrate it, because all future use cases can basically be coupled to not the application, but to the liberated dataset, right? That independence. So all future changes are built on liberated data. The only question is, how does the data become liberated? And what we recommend is the answer is doing it gradually as you deliver capabilities. So don’t create a dataware project, don’t have a dataware budget line item; literally apply it to your change projects. And that’s honestly is the only way is to make transformation. You can’t have a transformation project where they very rarely deliver any material ROI.

Mike Vizard: They say, of course, the data is the new oil, but it almost sounds like all the data is stuck in a well somewhere. And we don’t know how to get it out. So we really need to start thinking about refining the data.

Dan DeMers: Yeah. And the other thing is, the data is data; the inability to control that has consequence. But the power of having the control with a connectivity is intelligence. So I like to think that the real asset value is going to be the ability to tap into the intelligence of that connected data without the compromise of control. So I’d say that intelligence is actually the thing that is the more valuable commodity there when you hit on a sore point, because a lot of people out there, or business executives don’t always trust the data that’s in the applications, it’s often conflicting – you’re not quite sure that it was entered correctly.

Mike Vizard: So if we have this metadata approach, can we get to a point where maybe we do have more confidence in the data that we’re looking at?

Dan DeMers: Definitely. And, again, this is not an instant fix, you don’t just say we’re going to use data, where it boom, all of a sudden, all your data is high quality. But if you – I’ll use an analogy, I like to use some weird, wacky analogies. Let’s imagine you’re trying to protect a bunch of money, and you’re gonna put it in a room. But that room has 1000 doors on it, so how secure is that? Right? Like, if you contrast that to a bank vault – how many doors does a bank vault have and how secure is that one door? So that’s ultimately what you’re moving towards is having less doors, and less opportunities to lose that control. And by applying the approach, it is allowing you to basically start to close down those doors one at a time. So you’re continuously simplifying your infrastructure, you’re continuously not only avoiding new integrations, in the context of a project, but you’re preventing future integrations on that same data, right? So it’s all about the gradual, iterative process that’s going to be, and we’re kind of talking more about a methodology than a technology, right? So you kind of need both sides of it. You need the people, you need the process and you need the tools.

Mike Vizard: Who’s in charge of making this decision? Do you think it is a C-level executive sitting up top as a CEO? Is it one of these newfangled chief data officers? Or is there somebody else emerging? Who is the leader of the data evaluation program?

Dan DeMers: Well, definitely what I’m seeing is a trend toward the heightened awareness of the importance of this on the business side, right? Because you can look at this as a pure technology play, but dataware isn’t changing – just how technologists deliver technology. It’s changing how business users run their business. It’s changing how they interface with that data. So it truly cuts across. So first of all, it has to be something that has both a bottoms up and top down approach, but it is truly the the senior leaders who are deciding. I guess the consequences of these choices and the the people who ultimately benefit or pay the ultimate price is the senior business leaders. So we have seen the organizations can have champions who could be either on the business side or on the technology side who can, you know, be an internal advocate for the shift and they can have traction, but where we see that really take off is when they have that senior sponsorship. So I think, like any major shift, it has to come from the top.

Mike Vizard: Do you think organizations will have more control over their application environments, and the cost of switching ultimately will drop and we can have more competition and innovation among the different application providers because they won’t have this lock on the data? And so we won’t be forced to stay with him forever in a day.

Dan DeMers: Yeah, that lock-in is a huge problem. Every SaaS vendor that sells to the enterprise today, there’s you know, how do I make money from recurring revenue from user licenses or consumption or usage fees, but I’m also trying to get control over the data, because that’s my ultimate stickiness is I’m kinda trapped. And that means the more you use it, the more you save, but the less portability you have, the more you’re locked in. And that’s the phenomena that we find ourselves in. And the idea of, of liberating that data such that you can still have applications, but the applications are experiences on top of that data, but they’re composable. They’re pluggable which means the apps in this future need to earn their keep, right? They have to deliver the value that you bought them for. And if not, you’ll swap it out for a new one. And the idea of having a zero integration application gives you what we’ve been talking about now for a while is the idea of composability, right? Plug and play; I have one, CRM and I want to try another one, I want to run them in parallel, and then I want to come over and I don’t want to do any integration. Today, that integration barrier limits vendors ability to sell limits, the buyers ability to buy limits the time to value. It’s everybody wins when you get rid of that friction.

Mike Vizard: Some people might wonder if we’re just shifting lock-in, because they’ll say, “Well, instead of the applications, the platform becomes the lock in.” So how do I avoid that particular transition and make sure that everything is free and open forever?

Dan DeMers: Yeah, that’s a very good question. So you know, that’s one of the reasons why we have the the data collaboration alliance and are working on standards like zero copy integration. This has to be off the back of, you know, open protocols and open standards. And if you’re in the process of evaluating a data or platform, or if you’re building a dataware platform, you’re going to want to make sure that it’s as easy to get data out as it is to get data in. And I think that’s a core capability that one needs to look at. So, so far, I’ve not come across any data or platforms that are trying to trap it. In fact, they’re generally all philosophically aligned to the liberation of data. But it is something to keep an eye on. As an example, for our dataware platform, we enable it to run in any environment, running on prem, running cloud, multi-cloud provider, because you want to be able to lift and shift and move your data; you want to get data in and you want to get data out, right? And look at licensing models, you never want to be paying for usage of your own data, right? To give a business user the ability to see data or even change data. You’re paying consumption fees for using your own data which is, let’s say, a red flag. But yeah, so it is something to keep watch on for sure.

Mike Vizard: All right, folks, you heard it here. First, there’s a data revolution underway. Hey, Dan, thanks for being on the show.

Dan DeMers: Thanks for having me.

Mike Vizard: All right. Thank you for all watching this latest episode. You can find it and others on the Digital CxO website and we invite you to check them all out. And once again, we’ll see you all next time.