Tim Gasper [00:00:00] Hello, everyone. Welcome. It's time for Catalog& Cocktails, your honest, no- BS, non- salesy conversation about enterprise data management with tasty beverages in hand. I'm Tim Gasper, longtime product guy, customer guy at Data. World, joined by Juan.
Juan Sequeda [00:00:16] Hey, Tim. How are you doing? I'm Juan Sequeda, Principal Scientist at Data. World, and as always, it is a pleasure to take a break middle of the week, end of the day, and discuss data. And today, we have a slight change of plans last minute. We were supposed to have our guest, Samia Rahman today, who is the Director of Enterprise Data Strategy and Governance at CGEN. However, there was a last- minute change of conflict. She can't make it right now, but look, this is the live show, honest, no- BS. So the show must go on and we'll look forward to having Samia back and we'll reschedule it. So, looking forward. But the thing here is that the topic, we're going to have this discussion around data governance, data stewardship and AI. And actually, what will be interesting is that Tim and I have not prepared for this because we were supposed to have a guest and we actually just prepared for it in the last two, three minutes. So it'll be interesting to get our take and then have Samia on this and then we can compare our takes afterwards and we'll have the audience go listen to the differences and stuff.
Tim Gasper [00:01:21] Yeah. And every once in a while, we do these where it's you and me chatting and we find some areas of alignment and then there's some cases where we disagree and that's great. We love it.
Juan Sequeda [00:01:30] And actually, so we've done these, what we've called before these rant sessions, but they've always been prerecorded because we've been on the road or whatever. But this is the first time we do this live rant session. So honestly, if anybody's listening to us live right now, we'll bring this up. Just comment anything.
Tim Gasper [00:01:44] Yeah, we're keeping a close eye on the comments and the chat here. So please jump in, ask questions, guide the conversation. We're watching.
Juan Sequeda [00:01:53] But we are still drinking something. So what are you drinking, Tim?
Tim Gasper [00:01:55] So I am drinking actually a little cocktail of my own making here, which is strawberry, vanilla, and some bourbon whiskey. It's sort of a little bit of a cocktail combination.
Juan Sequeda [00:02:09] Strawberry? And I'm in Chicago right now. I found this business center here at the hotel and I really wanted a beer and they have nice a Oktoberfest, Goose Island, and this is perfectly refreshing right now even though I'm in this business center and I only see four walls. But anyways, cheers. Cheers, cheers, cheers.
Tim Gasper [00:02:31] Cheers, Juan.
Juan Sequeda [00:02:31] Cheers to we're going to have a controversial discussion about data stewardship. All right.
Tim Gasper [00:02:35] I'm excited that you're drinking some Oktoberfest beer to accompany it.
Juan Sequeda [00:02:42] Who wants to go first?
Tim Gasper [00:02:44] Well, why don't we start by talking a little bit about what Samia was thinking of bringing up. So the topic was around data stewardship, data governance, and how things are evolving, how things are changing. And where things started off was around this idea of the data steward and this idea of nowadays, you hear more about things like data product managers, whether you're embracing things like data mesh or you're not, do we need to change the way that we're thinking about things? The traditional view of governance was much more around defensive data governance, data stewardship. Can you just get away with only having data product managers as we go forward?
Juan Sequeda [00:03:31] Okay. So one of the things... So let's be my bold, honest position right now. Let's just imagine we can take the stewardship role out and the product management, all this stuff because data product management, these products, this is something that's coming from the whole data mesh and that has the governance pillar. So we have governance. What if we could start from scratch? It's a clean slate. The analogy, not analogy, I was thinking about, there's a top- down bottoms- up situation that I'm seeing right now. One is that from the bottoms- up, we're like, " Well, we need the steward to know what data we have and make sure that we have great descriptions and what's PII for all the stuff that we have and blah, blah." Okay, so you're like, " Let's go make sure we understand the current lay of the land that we have." But from the top, it's like I don't really care about what we have; I care about what we need, and what we need is what is the problem we're trying go solve? So we're seeing these two things separately and I'm like, " This shouldn't be separate things. I think there should be one." And I think sharing a little bit of the notes from what I was talking with Samia before is if you have data stewards in the organizations, you should upskill them and turn them into data product managers. And if you don't have a stewardship program, don't have one. Don't start it. Actually just start with the data product management. And so I don't want to speak for Samia. I believe that was her point, but actually, I'm going to make that point right now. Let's just stop with the data stewardship and the data product. There's just this one thing, I don't know what name we want to give it, and actually, a lot of other topics of conversations we've had before is even we need to be rebranding data governance and call it data enablement or something. So I think all that work needs to be done. I think we just need to reframe it just to get people excited because an honest, no- BS thing here is I don't think people go to school are saying, " I want to become a data steward when I grow up," or honestly, how many people are just super excited? The word data stewardship kind of already sounds boring, so how do we make this exciting and what does this change? So anyways, I'll shut up for now. You go.
Tim Gasper [00:05:55] No, I think this is an interesting discussion point around... Let's back up a little bit. What is a data steward and what are they supposed to be doing? It's like, well, the data steward role was mostly born out of the current conception of data governance that you need people who take on some of the responsibility around data quality, around data security, around more effectively communicating about the meaning of and the usage of the data. And it is a little bit more traditionally defined as a little bit more of a library- oriented function to make sure that the data is properly organized, properly categorized, and properly taken care of. And if you're a financial institution, you have some even more rigid responsibilities. Broader organizations tend to have some looser responsibilities. There's sort of this role around data stewards that has existed for a while now. I think it especially got accentuated during the late 2000s. SOX compliance and things like that really accelerated things around data stewardship. But it is a little more reactive. It is a little bit more coverage- oriented and it's a little more maintenance and documentation- oriented. If that's going away, and I'm a big proponent of data product managers and what they could do, more of a focus on value, building data products, building analytics products, coming from a software background especially, it resonates very strongly with me. But then who is doing the stewardship? Similar to DevOps being, " Hey, all the engineers are going to be able to manage the infrastructure," are we shifting to a world where stewardship is fading away, data product management is coming to the fore, and really it's everyone's responsibility around data quality, it's everyone's responsibility around data documentation?
Juan Sequeda [00:08:06] Yes, because everybody needs to eat their vegetables. The reason why we want to document and know where all our data is and stuff because for regulation and so forth. Now, why is it only just one part of the order or just a handful of people need to go do that while everybody else goes, let's say, " Go have fun with the data"? It's like no, I think everybody should have some responsibility around that. I think that's it. There's a paradigm shift that needs to happen around this because as you're saying, the whole traditional governance and stewardship is something that comes from the regulations, especially again, the 2008 stuff is one of the... The BCBS U39. So I think something needs to change because we don't live anymore in this world where it's all about the fear of regulations. Now, here's the thing: the vendors will always want to go with the governance because you need governance, you need compliance, and they're always going to be selling you fear and that's always a" easy way" to go sell you something. But on the other hand, the data product is all about business value and the analytics you can derive from it. AI, you're using all this generative AI stuff. This is again, not just for... You're not using that to manage your fear and stuff. You want to go generate new value. So I think this is the change. And I would actually characterize stewardship, even the words, and I'm picky here on the words because yeah, words matter and that's just kind of the image that you get, and you get annoyed, " Oh, the governance team, the compliance or the stewardship," so forth, we need to change that. And I think it's more of a... Maybe the work is still the same, it's just kind of like the style that's being presented, how we're marketing ourselves around this, that's the stuff that needs to change. But anyway, you're smiling, you go.
Tim Gasper [00:09:59] I think this is interesting just because, well, I think some more traditional organizations are always going to want to have data stewards because it's what they're used to and there's sort of a defensive posture around it. I can imagine, if anybody who's listening to this who's more in the financial industry, you may think, " Data steward's going away? Yeah, that's not happening anytime soon." But as we go forward, maybe those responsibilities are really established and there's maybe lowercase D, lowercase S data stewardship that is a key set of responsibilities. But I do think that this idea that data product management is going to become more the center, more the focus makes a lot of sense and it especially starts making more sense as you think about how much data tools and analytics tools are democratizing and how much just the chaos requires more of a product management mindset to build the right repeatable things. And then secondly, as AI is becoming more of a trend, I think Jon Cooke in our episode last week made a really good point that even a particular application around ChatGPT or an LLM, that might actually be a data product, and you should think of it as such, and more and more of these data products are actually going to be maybe a conversational agent and things like that and that requires a different kind of a perspective, less of a stewardship perspective and more of a data product perspective.
Juan Sequeda [00:11:29] I think we are and I'll acknowledge I'm picking a lot on this whole data stewardship right now, but if we zoom out, it goes to the umbrella of data governance. But at the end of the day, why are we doing this? The business value, three things. How are we making money, how are we saving money, and how are we mitigating risk? I think those are the three things that we think about. That's what should always be the focus. So if people are like, " Well, you don't have the seat at the table. I don't get all the resources I need," because you're not being able to communicate what is the value that you're producing. And I think having that governance and stewardship just separately, then they will... If they're doing it successfully, they shouldn't have an issue because they can say, " We're focusing on mitigating risk." But then you look at the strategic objectives of an organization, it's not probably equally 30%, 30%, 30% or something. Yeah, we need to manage and mitigate risk, but we probably want to just do the minimum stuff. And let's be honest, you're talking about those large financial companies, they probably have in their budgets the fines that they're going to go pay for stuff anyways. Are they actually incentivized to go do... They're incentivized to do the minimal stuff that needs to be done and they know if something's bad's going to happen and they have to go pay a fine whatever, they'll have already the cost of how to go deal with those fines and how to do the PR, all those things. So this is why my point is that we just need to have a paradigm shift about the way we think about this. And I also wonder, here's another honest, no- BS take, is this a generational thing? People who were thinking about stewardship and governance in the mid- 2000s and the 2000s, they're still in the leadership roles. That was 15 years ago. What's the next generation going to think?
Tim Gasper [00:13:27] Well, the next generation wants to keep reinventing the wheel.
Juan Sequeda [00:13:31] Well, that's true.
Tim Gasper [00:13:35] I do think things are actually changing though. And I do think that this idea of focusing on value, the offensive use cases around data, not just the defensive use cases is important. But I guess one thing that I worry about is amongst all this excitement around data product management, we also can't forget data stewardship. It is an important responsibility.
Juan Sequeda [00:14:02] I'm not saying that we can't forget it. Now, is it a person? I just think that the work just gets involved in different... It gets spread around. Now, the issue there is who's responsible for those types of tasks.
Tim Gasper [00:14:18] Well, yeah, do data product managers do stewardship?
Juan Sequeda [00:14:21] I would think so.
Tim Gasper [00:14:23] Okay.
Juan Sequeda [00:14:23] You don't seem convinced.
Tim Gasper [00:14:27] No, I guess it depends on the data product manager. I think this is maybe what we're grappling with as an industry is that I think sometimes we hijack these terms a little bit.
Juan Sequeda [00:14:39] Yeah, we do.
Tim Gasper [00:14:40] Yeah. Data product manager, maybe in the strictest sense, is there is literally a product manager who works with a data team and is creating these data assets. But I think maybe what we're arguing for a little bit here is a broadening of that concept a little bit, that it'd be better to have a data product manager that takes on data stewardship responsibilities than to have a data steward maybe who isn't really equipped to do the data product management side. And so maybe this is an opportunity to say, " Hey, let's hire..." Going back to the original point, if we could bring on data product managers and maybe that's the future, they're covering some of the stewardship responsibilities and if you have stewards, evolving them to think about value in the production of data products, maybe that's a better approach.
Juan Sequeda [00:15:29] All right. Well, Tim, you're a customer guy. What are the best practices that you see? So things that you see that are like, " Okay, this is working"; things that you see that, " this is not working"; and what are the ideas that you say, " we haven't even tried this, but we should try this other thing out because I think it could work but we haven't tried it out"?
Tim Gasper [00:15:54] Yeah. Well, I think across our customers, but in the space in general, stewardship is pretty common. Everyone's trying to define data stewards. Not a lot of organizations are hiring data stewards. Most folks are giving the hat to people, they're SMEs that are in different domains and things like that, and their names get identified, they get stuck on a spreadsheet, and now you're the data steward because you showed up on that spreadsheet. I think that's a little bit more the common thread of what's happening right now. And everyone is excited about data products. Everyone's talking about marketplace. We've got to build this marketplace internally. We've got to put our data products in there. People are seeing data marketplace and data products as being a little bit separate and a little more of a curated experience versus sort of a broader catalog or a broader governance platform, even though a lot of times it's the same tool. But what we are not seeing across our customers, with some exceptions, there are some exceptions, Indeed, for example, is one of our customers and they're more advanced in this, but what we're not seeing across our customer base is a strong data product management kind of approach. They're talking about data products, but they're not talking about data product management.
Juan Sequeda [00:17:19] It's still early on the data product manager. People are enamored with it and talking about it and stuff, but they don't actually know how to do it.
Tim Gasper [00:17:30] Yeah, there's work to be done and folks want to know, what's the right way to do that?
Juan Sequeda [00:17:37] How do people end up becoming a data steward?
Tim Gasper [00:17:42] I don't know. Is there anybody listening who was like, " I went to college and when I graduated I was like, 'I want to be a data steward,' and then got hired into a data steward"? I know that even within our customer base, we do have some people who are literally professional data stewards, but it's also combined with understanding in that industry, at minimum, a deep understanding in the industry and the use cases and often also deep understanding of the data.
Juan Sequeda [00:18:12] Let's talk about that understanding thing for a moment. I've worked in the past with people who either had the title data steward or they're doing the job of data steward is because they actually understand the data, and the reason they understand the data is because they understand the business, they understand the people, they understand who's asking for this question and why it's important. And so typically, it's been people who've been around the organization for a while. And these are folks who I'd actually say that they enjoy their job, they're very successful at their job because they actually care. They care about the organization, they care about the business, they care about the problems they're trying to go solve, and they actually know that data can actually help and they know what data and they realize the value of the data and the data is not dirty, whatever, it's not going to help us. So there is this empathy about just the organization itself, and I think that's a characteristic that I've seen. And so I wonder how much of truly successful data stewardship and data products is really about you actually care about the problem that you're solving and it's not just another job. I don't know. It's hard to inaudible-
Tim Gasper [00:19:34] I think caring is part of it. Caring is definitely part of it. But another part of it is also the dreaded P- word, process. It's about putting process in place that lets you have predictability around the quality of the metadata and the quality of the information that you have. For example, one of our customers, they've built stewardship directly into the data analytics workflow. So as they're building dashboards, they're actually making sure that as part of that process that they're doing the stewardship and the documentation and the quality as part of that build process. So maybe to some degree, they're doing data product management. They're not necessarily calling it that. It's stewardship in the data analytics workflow.
Juan Sequeda [00:20:24] If you have a process and it's a repeatable process that people are going through it, it's probably a sign that you're doing some sort of... Well, you're managing something now, so you're probably on the route of doing data product management.
Tim Gasper [00:20:43]Mm-hmm.
Juan Sequeda [00:20:43] Okay. Now, another topic to tie into this is how AI is changing things and I think there's two ways. It's like what does data governance, data steward, data product management mean with respect to AI? And also, how is AI affecting the jobs or the work of data steward, data governance, data product management, all that stuff? I don't know. What are your thoughts?
Tim Gasper [00:21:11] Well, I think one big thing, and maybe this feeds into the whole, " Well, maybe stewardship isn't really a job as much anymore. Maybe it's more of a set of responsibilities and maybe the data product manager is more the job now," is because of AI, we're able to shift a lot of manual tasks to more automated tasks. And so a lot of what traditional steward work is thought of as things like, " Well, I need to create the data dictionary for something or I need to help with the classification rules and things like that." Right?
Juan Sequeda [00:21:45] That should be automated though. That is automated.
Tim Gasper [00:21:47] A lot of that is automated now. And so that's starting to become... It's a job that was very unscalable is starting to become a lot more scalable now.
Juan Sequeda [00:21:57] Just quickly, GPT and all these large language models you think they'll generate all these descriptions for you, sufficient to the point that you're like, " Yeah, this is okay, I can go with it or I can build off that," so that's one. And by the way, you're only sending metadata stuff to these things, so people will have a concern, but others won't, and so it shouldn't be that big of a concern. That's one. Second, detecting PII and PHI, all this stuff that you would have to have these machine learning models that look at the data, honestly, just experiments that I've been doing, you just send the metadata, the tables and the columns and that stuff, and it tells you, " This could probably happen," and guess what? It's probably right without even looking at it. So it's like you can get so much of this stuff already" for free." So I think this is truly accelerated. I tell every, right now, everybody in governance cataloging, " You need to be using these large language model technologies, these generative AI because it is amazing, the productivity lift that you do." Now, this may be a concern too. It's like, " Well, that's the job I'm supposed to be doing." Well, guess what? No, not really because that thing's already doing it for you. Again, the AI is not taking your job away. Somebody who knows how to use the AI is taking your job away. This is a clear example of that. That's how I see AI now" affecting" a little bit the steward, these jobs, but we just need to accelerate because that is the boring work that we don't want to go do. It gets 80% of the work done. Perfect.
Tim Gasper [00:23:34] Yeah, yep. Are there certain use cases that you're seeing just in terms of data governance and stewardship that are being addressed by AI better? And then are there use cases that you're like, " It's not there yet"?
Juan Sequeda [00:23:58] I would say everything I have tested for, all types of governance, cataloging tasks, it's already doing better than I would've imagined, so I think it's just going to start using it. Now, is it magic? No. If it gets 80% of the work done, if it gets 50%, if it gets 20%, it's already better. I think that's already a win on that stuff.
Tim Gasper [00:24:23] Well, by the way, that's a little bit of a paradigm shift because I do think sometimes people think of automation as like, well, it has to get 100% right.
Juan Sequeda [00:24:29] This is the thing, and I think that's the mindset we have to get out of. " Oh, look, it didn't generate the right thing." That's fine. It generated it correctly 80% of the time, 50% of the time, so it already saved you money. Now you only need to revise things. Perfect. Now become a better analytical reviser of things and not the one who's doing all this manual stuff. So I think that's the shift that's happening and people get uncomfortable about it, but yeah, that's where the world is going. So one thing that I've been experimenting, and it works great because it's a science and also an art, is think about data modeling. I can. Here is my database schema or create an ontology, a semantic layer or whatever, the target model, whatever you want of what this represents, and then actually create the relationship. Is it going to be perfect? No, because what does perfect mean? Modeling is going to be always a science and an art there, and that's maybe not how you're going define it in your organization, but it's going to take you to the next... It's going to accelerate that. That is something that it's inevitable. So actually, I think architects, enterprise architects, data modelers and stuff, that job is... A lot of that work is going to get automated. That's the one I see. Now, not fully. I'm not saying that... The people who do that job need to be focusing so much more on connecting that to the end users, to the business, understanding that because you're going to get something out and it's not going to be perfect, it's not going to be correct. The model it's going to generate is going to be usable, but not probably for the thing you need to go do, but to make it from what you've got to make it usable, that gap just got so small right now, and I think that means that you can go do more things faster. People are going to be asking, " Can you add this data? Can you add this? Do we need to extend this?" It's like, yes, we can now do more of this stuff faster. That's the focus there should be.
Tim Gasper [00:26:48] This conversation triggers something for me. Is all this automation and growth around AI technology shifting the ratio between IT and business? For example, I think in general, there's a certain amount of IT. I'm using that as a generic term to represent the technical people that are having to support the broader line, the line of business, the people who are really... If you're a bank, there are people who are cashing checks and stuff like that. There are people who have to do the work, and even a lot of that's getting automated, but that aside, the people in the line of business. Is the ratio shifting now? Because going back to the architect, maybe the architect normally needs to take a week and go build out the schema, build out the concept diagram, build out the network diagram, whatever. Now, you just say, " Okay, here's the data I'm going to use. Here's the concepts we're trying to do," and boom, it's done in a minute.
Juan Sequeda [00:27:52] I expect that now in hours. Honestly, there's no excuse. Before, we had a bunch of bank tellers. We still have bank tellers, not as many because we have ATMs. By the way, just a quick thing, I always want to say an ATM machine, but I forget. I remind myself-
Tim Gasper [00:28:11] The M is machine, right?
Juan Sequeda [00:28:20]The M is machine. So yeah, this is the stuff that's going to change.
Tim Gasper [00:28:20] Architects aren't going away.
Juan Sequeda [00:28:22] They're not going to go away. They're just going to spend their time on doing more of the, I would consider this the fun stuff. And let's tie it back to what we were talking before about caring. Like, oh, you have to go take that model that you did and connect it to the business because you should care about the business.
Tim Gasper [00:28:41] Empathy and curiosity.
Juan Sequeda [00:28:43] Now also, we have to go see that the organizations, companies need to also care about their employees. This is a two- way street here. I always remind, remember, organizations, companies, they are just human endeavors. They're a group of people who get together because they want to accomplish a goal together, and we live in a capitalist world, want to make money. That's it. But at the end, this is a human endeavor. So humans, people, we're all part of this.
Tim Gasper [00:29:14] We're in the center. Are there any other, obviously AI is a big trend, is there anything else around stewardship and governance that it makes sense to call out as some megatrends that are changing here? One I'll call out is the regulatory environment.
Juan Sequeda [00:29:34] Oh, I'm waiting to touch that one.
Tim Gasper [00:29:36] Right? I mean, obviously we've got some things that have been around for a long time, GDPR, CCPA.
Juan Sequeda [00:29:42] Now we're going to have more regulations. There's the AI Act, all these acts-
Tim Gasper [00:29:45] And we're going to have new AI regulations. There's the one in Europe that is getting pretty close to being rolled out. But also, it's not just the enforcement of these, it's the fractured nature of so many regulations. For example, one of our customers at Data. World is grappling with the Colorado Privacy Act, CPA, and needing to figure out how to make sure that they comply with that. That's just one state. There are 50 states. There's a Massachusetts privacy law. Do you know there's a New York City privacy law, just for the City of New York that they passed? So everyone wants to do business with New York City. Then they've got to think about this privacy law. So there's these things that make it extremely fractured, and that's probably not going away anytime soon. And so not only do we have to act in compliance with these different diverse environments, but it's too much for any one person to really handle. So it actually ties back to our AI conversation, that AI has to help us here or else we're just going to lose our minds.
Juan Sequeda [00:31:03] And I'll tie this back to our data product management and the stewardship is that who's responsible? I'm creating data products that are going to be used for analytics, for that stuff, so who's responsible? Who should know about all these acts and be responsible, be accountable that this data product, the data in this product actually follows all the guidelines and the regulations for these things? Who's accountable for that? Does data steward who's in a central org or whatever, the team that created that data product? This is the stuff where we need to start thinking-
Tim Gasper [00:31:44] Some of these are pretty severe fines and things like that. Maybe it's delegated or things like that, but really, the CEO is accountable.
Juan Sequeda [00:31:59] But then you're like, okay, so if we're going to deliver data products and it's going to have people data or whatever that's going to be used internally, who needs to learn what these acts are? Who needs to be able to go and map them back to the data? And I think these are the things that we need to start thinking about. Again, does only one central org go do this or everybody gets educated just because it's like, " You've got to eat your vegetables, you've got to do this stuff, you just have to go do this"? We all have to go through security training. I think this is something where there's a shared responsibility and I think this is the evolution because eventually that's how we're going to go scale too. We can't just always relegate things and say, " Well, there's that stewardship governance org. We're going to do it." Because otherwise, if they want to go do their job, they just stop things. " I'll just stop. No, no, no." And then it just takes too much time and then we don't go so-
Tim Gasper [00:33:01] That's true. That's true. Everybody goes through security training, right? I'm sure everybody's starting to go through AI training now. " Turn off your chat history with OpenAI."
Juan Sequeda [00:33:12] How many people actually realize that?
Tim Gasper [00:33:16] Yeah. If your chat history is on, everybody, did you know that OpenAI is able to train off of everything that you're saying?
Juan Sequeda [00:33:25] Yeah, that's true. So if you're using it-
Tim Gasper [00:33:27] Yeah, that actually is true. We're not actually pretending when we say that.
Juan Sequeda [00:33:31] That's true. Tim, this is a reminder. This episode, here's a reminder of how we used to do things many years ago, three years ago.
Tim Gasper [00:33:42] Yeah. For those of you that know, over three years ago, we would get together on a Zoom and we'd have our tasty beverages in hand and-
Juan Sequeda [00:33:54] And people would join.
Tim Gasper [00:33:55] ... we wouldjust be ranting.
Juan Sequeda [00:33:56] People would join the Zoom.
Tim Gasper [00:33:58] People would join.
Juan Sequeda [00:33:59] We would have probably, I don't know, between 10 and 40 people join the Zoom. They were all cameras off and muted. And we would talk for 30 minutes and then we would stop the recording and then we would just keep chatting with anybody else in the Zoom for another 30 minutes. And then this is evolved. Anyways, this is cool to do this again. It's been a long time.
Tim Gasper [00:34:28] Yeah, it is. It is.
Juan Sequeda [00:34:28] Time, it's been a pleasure talking with you.
Tim Gasper [00:34:28] We love our guests. Our guests are always fun, but it's always fun to have a little rant and debate as well.
Juan Sequeda [00:34:30] Yeah, it's been a pleasure doing the podcast with you on our fourth year. And what's your plan? Are we just going to keep doing this and we just keep having fun and...
Tim Gasper [00:34:42] Let's just keep doing it. And for those who are listening, let us know what you want to hear more about.
Juan Sequeda [00:34:49] Who do you want to hear, guests?
Tim Gasper [00:34:51] Who you want to hear.
Juan Sequeda [00:34:52] And if you want to be a guest too, just reach out to us. We're open. We want to be very diverse on all aspects about the show and everybody who we have on the topics and people and where they're coming from. So yeah, just reach out. What's your final takeaway?
Tim Gasper [00:35:12] My final takeaway is data stewardship is important. It's not going away, but it's evolving because we need to focus on value, bringing value to the organization. And this idea around the data product manager, it's very interesting because it's more around how do we build repeatable value around our data? So I'm excited about that. I think this focus on data products is really important and valuable, and it's going to change how stewardship and data governance works as we go forward. So that's my biggest takeaway. What about you?
Juan Sequeda [00:35:46] I agree with your takeaway, and actually, I don't think... We didn't disagree on anything. Well, I mean was being a little-
Tim Gasper [00:35:55] You were a little aggressive on stewardship.
Juan Sequeda [00:35:57] Yeah.
Tim Gasper [00:36:04] I like data stewards.
Juan Sequeda [00:36:06] I can imagine. I'm imagining a world where the words data steward and data governance are not the center anymore, but we have other words that we use that people get excited about and we all care. That's what I'm closing with.
Tim Gasper [00:36:28] I think that's fair. I think we can get there.
Juan Sequeda [00:36:31] I do think, I do think. We truly can be there.
Tim Gasper [00:36:33] Yeah, between-
Juan Sequeda [00:36:34] It's not like, " Oh, it's over there. Let's go there." No, no, we're already doing it. It goes back to-
Tim Gasper [00:36:42] I think we can see the future. I think data security doesn't go away. There's data security and compliance, and then there's data enablement, which I think is the term we prefer, and there's data product management. And I think between those three parts of the triangle here, you have a pretty nice coverage. You never even have to say data governance if you don't want to.
Juan Sequeda [00:37:02] Exactly. Cheers to not saying, " Data governance." No, I'm just kidding.
Tim Gasper [00:37:10] I'm going to say it five times right after this. I'm going to be like, " All right, so that data governance use case." Anyways, it's really hard. Words are hard, right? We get steeped in them. They don't go away easily. Anyway, Juan, to many more wonderful episodes together.
Juan Sequeda [00:37:29] And care about your business and care about more of your data. Cheers.
Tim Gasper [00:37:32] Yep. Cheers.
