 Hello and welcome, my name is Shannon Kemp and I'm the Chief Digital Officer of Data Diversity. We'd like to thank you for joining the current installment of the Monthly Data Diversity Webinar Series, Real World Data Governance with Bob Siner. Today, Bob will discuss who should own Data Governance IT or Business, sponsored today by Irwin by Quest. Just a couple of points to get us started. Due to the large number of people that attend these sessions, he will be muted during the webinar. If you'd like to chat with us or with each other, we certainly encourage you to do so. And just to note, Zoom defaults the chat to send to just the panelists, but you may absolutely switch that to network with everyone. For questions, we will be collecting them via the Q&A section. And to find the chat and the Q&A panels, you may click those icons in the bottom middle of your screen to activate those features. As always, we will send a follow-up email within two business days containing links to the slides, the recording of the session, and any additional information requested throughout the webinar. Now, let me turn it over to Danny for a brief word from our sponsor Irwin by Quest. Hi, Danny. Hello and welcome. Hey, thanks, Shannon. Thanks everyone for joining. Really excited about this chat with Rob. And I think it's a very timely topic and one that I've absolutely been involved in with our customers. So I will not take a lot of time away from that conversation. So let's get right to it. You know, from a, you know, I think this is timely for a governance perspective and really the way that I tie this into the topic is, you know, organizations are trying to democratize their data. They're trying to get data to the point of maximum impact. And that absolutely involves the business and IT. And more than ever before, we've really, really, you know, putting them in a position where they have to work more tightly together, really understand each other's perspectives and do things in a collaborative way for the betterment of the business. But at the end of the day, you know, I think there's a common goal for the governance folks, for the operational folks, for data management folks, for the business and for IT to really succeed in establishing trust in your data and establishing a culture where you can truly be data first in terms of all the decisions you make and how you move the business forward. But that, you know, isn't as easily done as, well, it probably doesn't even sound like it's easily done. But, you know, there's a couple of things that you really have to keep your mind on and that's, you know, making sure that you mitigate the risks that data can represent to the organization, whether that's, you know, safeguarding that data from a privacy compliance policy and, you know, just understanding what kind of data is really a target for those nefarious folks out there that like to play games with us with ransomware. But it's also making sure that we have a clear view of the quality of our data and making sure that that is as high and as high quality and as accurate as possible for the purposes that we're using it. And those are the risks that we see. And then on the other side of the coin, we also want to optimize those data-driven opportunities, right, and really be able to take advantage of them in a timely way and in the best way fashion using data to get there. So really, you know, it's about increasing data literacy and through that increasingly usage and the strategic usage of data across the organization. And then, of course, making sure that that data is where it needs to be in a form that it needs to be and accessible to folks when they need it. So, you know, that's where we come in with our solution and our approach of data intelligence and data intelligence is one of the three pillars that Quest brings to the table around data, data intelligence, data operations and data protection, strong capabilities and all of them. But when you look at data intelligence to me, this is sort of the umbrella that brings all of those together because you're really connecting every critical piece of data management and the governance life cycle. And it's really about getting intelligence about your data so that you can get intelligence from your data. You know, at the core of our offering in this space is something called Irwin Data Intelligence. I know it's probably, you know, fairly obvious. But and this piece of technology comes with three major components. The catalog, where we look at and get our arms around the physical landscape, then our quality solution that allows you to surface and understand the level of quality and then start to define what that quality should be and leverage its capability to move that forward, whether it's by understanding the quality scores, moving things around, understanding which source is the best. But also hooking into those back end data remediation processes that are really important in order to make sure that that data is high quality as possible. And then there's our Irwin Data Literacy component, which is really about bringing together that governance framework and making sure that people can understand their data in their context, can navigate that in from their perspective and really become a true data citizen, if you will, within the organization. And it's really about bringing everyone together, whether they're in the business or IT, to a place where they can collaborate and really sort of, you know, participate as equals in this ongoing discussion of how do we get the best enterprise data capability possible? So this is what data intelligence can do for you. And at the end of the day, it's going to enable your stewardship. It's going to allow those folks to make sure that that data is recognized, understood where it is, what it means, what it means to the business, where it came from, those things providing visibility and insights to folks so that they can understand the lineage, where did it come from, where is it impacting, what is our architecture, literacy and ideation, making people smarter about their data so that they get smarter about how they use that data and doing that in a self-service way where they're not waiting for somebody else to provide the answers that they need. They can actually go get them themselves. We talked a little bit about data quality, data compliance, making sure that you can put all of the pieces in place so that it's clear to you what data is sensitive, why it's sensitive and what specific regulatory compliance it may be associated with because that's going to guide our usage as well as the things that we do in the back end to manage that. And then, of course, leveraging all of this for automation so that you can optimize those pipelines that bring data to the business every day. So I'll just finish it off with why Quest for Data Intelligence? Well, if you're not familiar with Quest, go take a look. We've been around for a long, long time. All of the large customers that are out there and that are facing these data challenges are our customers. We have a lot of experience. We know what they're going through. We have a clear vision based on their feedback in terms of where technology needs to go to support these things. And we truly are a trusted partner. So with that, Shannon, let's get it back to you so that we can get to the meat of the discussion. Annie, thank you so much, as always, for this great presentation and for kicking us off. And thanks to Irwin for Quest for helping to sponsor these webinars and make them happen. If you have questions for Danny, feel free to submit them in the Q&A portion of your screen. He'll be joining us in the Q&A afterwards. Now, let me introduce you to the speaker for the series, Bob Sinner. Bob is the president and principal of KIK Consulting and Educational Services and the publisher of the data administration newsletter, Tdan.com. Bob specializes in non-invasive data governance, data stewardship and metadata management solutions. And with that, I'll give the floor to Bob to get his presentation started. Hello and welcome. Hi. Hi, Shannon. Hi, Danny. Hi, everybody. Thank you for taking time out of your schedule to to join us for the what I think is the last webinar for Dataversity for the year 2022. So as Danny mentioned in his very gracious introduction and when he was talking about the webinar today, this is a really important topic. Every organization that I work with, they always want to know where should data governance be placed within the organization. It should be owned by IT, should be owned by business. So we're going to do something we never did before on one of these webinars. I know you're all muted here, but just, you know, human me here for a minute. So all at once, I'd like you to answer who should own data governance? Is it IT or business? I'm guessing that a lot of you said business. There might be a few of you that have experienced data governance actually residing and operating out of IT. We're going to talk about that today. Is that right? Is that wrong? Is there an appropriate place? I actually think that the answer of the data that the business should own data governance, I think there's a piece of accuracy to that. But I also think it's a cop out of an answer, or should I say it's maybe not as strong of an answer as we really want to give because we really need to be specific as to what part of the business is the appropriate part of the organization to for the date, the function of data governance or the data governance program to reside. So before I get started, just real quickly, some of the things active, I'm actively involved in, as you know, I do this monthly webinar series. We're going to be kicking off 2023 in a grand way in January, talking about data governance trends, taking a look back at what where we've come from and where we need to go as an industry, as a discipline for organizations. I'll be speaking. I'll be actually keynoting working with a group of chief data officers at the Enterprise Data Governance Online event taking place in January. I'll be speaking at the EDW, the Enterprise Data World Digital event. I talk a lot about noninvasive data governance. I might mention it a few times in the webinar today, but I wrote a book on the subject. I've there's learning plans that are available through Data Diversity as well. I have an online publication I do consulting and in my spare time. I also am an adjunct faculty member at Carnegie Mellon University, which is right here in my hometown of Pittsburgh, Pennsylvania. So what are we going to talk about? So I really be curious. I think I am taking a glimpse at the chat and saying that most people are saying that data governance belongs in the business. But we need to define what that means. What do we mean by the business when it comes to owning data governance? We're going to talk about why some people say and there are people in the organization in the industry, in the world that will tell you that if your data governance program resides in IT, it's destined to fail. I'm not one of those people I can stop. I can talk about a lot of examples of organizations where governance has resided in IT and it's been very successful. Talk about some examples of that. Talk about considerations, things you should think about because really the best answer to the question of who should own data governance is it depends. It depends on your organization. And we'll talk a little bit more about that as we go through the webinar today. Let's start as I usually do. Let's address some definitions just to kind of be on the same page as to what we even mean by data governance, stewardship, metadata, those types of things. I word data governance very strongly. I think that at the end of the day, no matter what approach you take to data governance, whether it's command and control or noninvasive approach, you need to execute and enforce authority over data. So that's pretty much a given. I just like to word it very strongly. The stewards are the people in your organization that have a relationship to data if they're being held formally accountable for that relationship to the data. So if somebody is a steward, if they are formally accountable for how data is being defined, produced and used, they also talk a lot about metadata. And, you know, we're not going to you can read the definition that I use for metadata instead of going through that. It's it's certainly something that we need to consider. I always talk about metadata governance. We need to govern metadata the same way that we govern data. Metadata is another type of data. And if there's not people that are held formally accountable for the metadata, it's not going to govern itself. So for those of you who answered the data governance should be part of the business. Let's define what we mean by the business. Let's define what some of the alternatives are. What does it mean for somebody to own data governance? And why should even care? Why it even matters to you? So in most organizations where data governance ends out residing in the business and I'm wondering if a lot of you are, you know, represent some of these functions within the organization. Certainly risk management is a good place for data governance to reside there in the business, you know, finance is is a place where a lot of organizations supply chain operations, even marketing. But you may find that in your organization, you might have functions that look more like this and I've seen that a lot of the organizations that I work with, they have an enterprise analytics function or they have a digital transformation function or they have an existing information governance program. So and it might not be something that is IT driven. It may already reside in the business. So, you know, so yes, the item is on the left. The bullets on the left make sense traditionally for organizations. That's where data governance would reside in quote unquote the business. But when it comes to these days and where organizations are spending their money focused on getting as much as they can out of their data assets, enterprise analytics is a good place, enterprise data office. And that might reside in a part of the business that is separate from IT. And it could be that you've got IT, you've got a CIO and you've got a chief data officer or a chief data and analytics officer. Yes, but that would be an appropriate place for data governance program as well. It depends. It depends on your organization. And I'm going to draw a conclusion here at some point that, you know, where data governance resides right now in your organization might be the right place and there might you might be looking for a better place. But the fact is that you might want to in this time in this holiday time a year be thankful for the fact that somebody that there is a place for data governance to reside within your organization. So what are some of the alternatives to some of the things that we just talked about? So we talked about there being, you know, like I said, some risk, some finance. And I've seen even human resources have responsibility. Project management have responsibility. When we talk about IT, IT could mean a lot of different things as well. It could mean the traditional IT that probably a lot of you or many of your organizations have as part of that IT function. There might also be an information security function. There might be an application development function. That's where I was born and raised in the industry was developing applications. And, you know, data almost seemed to be an afterthought. Oftentimes application development, at least when I was in that part of the industry, it fell under IT. You know, regulatory reporting might be a good place for data governance. There's not a single answer. But I can tell you this. I don't believe that that because you would have it, you have to. Data governance has to be a partnership between the information technology part of the organization and everybody in the business. And we'll talk a little bit more about that as well. So what does it mean by a part of your organization owning data governance? You can have a policy in your organization that states where data governance resides, but somebody ultimately to get anything done within the organization, somebody needs to be accountable for it. So you need to have somebody who is now being held formally accountable for the data governance program. And so I think that makes sense. And probably a lot of you on the call are participating as that at least part of that part of the organization that is accountable for data governance. What does it mean to be accountable for it? Does it mean that it's written into job descriptions? I mean, there's more invasive and less invasive ways of applying accountability. So not only does owning data governance mean that somebody has to ultimately be able to report the success or the lack of success of account of data governance or governing of data that takes place in your organization. Somebody needs to run the program. And I'll talk a little bit more about that in a second. But you need to have somebody who is the administrator. In fact, the second best practice that most of the organizations that I work with use is that somebody needs to run the program. That's basically the best practice. The first one is senior leadership need to support, sponsor and understand what we're doing or we're going to be at risk. Yeah, that's true. But if we don't have somebody to run the program to administer the program. So if you have a part of the organization where the administration of your data governance program is presently taking place, you should be thankful for that. It may not be the best place. It could take a while to determine what the best place is. But if you're focusing on the administration of the program itself, like who's going to pull together the working teams? Who's going to facilitate the working teams? Who's going to report to the council? Who's going to take the message to the executive level? Somebody has to be responsible for creating the artifacts that you're going to use as part of communication. That's all administration of the program. So what does it mean to own data governance? It means having that responsibility to administer and do all those things that are necessary to have a governance program. And then I have here budget for data governance. Somebody needs data governance. And I say this quite often. It really costs the amount of time that you put into it. Certainly you need to have budget for things like tools and consultants. And there are there are costs associated with data governance. And so somebody needs to have responsibility for those purse strings and making those decisions. So one thing I suggest that you ask and feel free to use the chat room here in the webinar, who is presently accountable for your data governance program? Who is has the responsibility of administering your program? Or who has a budget? Does anybody have a budget? That could be a problem for a lot of organizations. And if you have an answer to that question for right now, you might want to even consider that that's an appropriate place because you have some of the things that you need. If you have accountability, if you have somebody, if you have a plan as to how you're going to administer data governance, if you have a budget for at least a budget could be financial, it could be your amount of time. So take a look at where your program is presently and recognize that that may be the appropriate place. If it's in I.T., do you need to move it the heck out of I.T. and move it into a business area of your organization? Maybe, maybe not. There's no simple answer to that question. But number one, be kind of happy that your program resides somewhere. And so now, why does it even matter then? Why does it matter where it comes? Because somebody has to have responsibility for coordination of all the program, all the data oriented activities of your organization. And presently, right now, if there's somebody doing that, then they're already there's some level of governance that's taking place. That, yeah, if you can tap into that knowledge, that's really important. But it matters because it's got to be situated in a place where the coordination has to come between the business, all those aspects of the business I spoke about and I.T. and all the aspects of I.T. that I spoke about. And there has to be a level of cooperation. And we need to get people to be able to communicate. If you notice the answers, you know, why it really matters. The four C's, it's always between the business and I.T. And again, it's not saying between risk management and I.T. Or or some other aspect of the business or in some aspect of I.T. It's just saying in general, there needs to be somebody who's paying attention to that or it's not going to be done. So why does it matter? It really does matter. I mean, figuring out where the best place in the organization for it. It may determine a lot of things for your organization, but it's something that we do definitely need to be considering this. So I know if there's a lot of books out there on data governance, I've written a book on noninvasive data governance. There's going to be a second book and a third book that I hope would come out soon. There's other people that have written books. There's a lot of people that give their opinion of this. And they say that if data governance is going to be in the I.T. part of the organization, that it's destined to fail. So I think it's worthwhile taking a look at who's saying that? Why are they saying it? Who are they saying to it to and really what's most important out of all these things is is it true that if data governance is in I.T., it's destined to fail. So first of all, you know, who says this? Who says that if data governance is in I.T., it's destined to fail? Well, obviously it's people that if they had had an experience of where data governance has been successful in I.T., that would certainly help. So it's people that do not know I.T. based success stories where data governance has resided in I.T. It's people that have experienced this, have experienced the failure. A lot of the times it's the people that listen to other people. You know, so if you're listening to what other people say, if you think really logically, I'm not going to suggest to you that data governance should reside in I.T., but I'm not going to also suggest to you that that your that your data governance program, if it resides in I.T., is going to fail. So I am not one of these people that are going to tell you that if your data governance program is in I.T., it's going to fail. What I will tell you is that if you're not bringing into consideration very strongly of the business, if it's not that coordination, cooperation, all those things that I mentioned between the business and the in I.T., you're not going to be successful because the people in the business have a lot of knowledge about the data. They use the data. They use the data day to day. They define they produce. They use the data. You know what, the same thing holds true for I.T. They know the data too. They know the systems they know. So why don't we just bring our knowledge together? And, you know, if it's in I.T., it's fine. If it's in business, it's fine too, as long as they're working together. So data governance in I.T. for I.T. sake. I think is going to have a somewhat difficult time getting off the ground. I think that the data governance in business without involving I.T. The same thing is true. So you've got to make certain that data governance is a partnership basically between information technology and information insights and all of them. And the business, everybody in the business that I mentioned earlier. So people who say that data governance in I.T. is destined to fail and I don't have a chance right now to read through the chat. I can see that a lot of people, if you're not looking at the chat, you might want to peek at the chat just to see what people are saying, because most people are pretty opinionated about this. And some people, I don't know if they're saying it here. They say that if it's in I.T., it's going to fail. I think a lot of that comes down to your experience. So why do they say this? So why are they saying this? Well, that's because that's what they've experienced. They've seen I.T. based success. They've never seen I.T. based success stories. They've had experience with data governance residing in I.T. where it's failed, but have they also had experience where it's resided in a part of the business? You know, again, like I said, people think very logically about this. Sometimes they think a little bit too logically about it. Be happy that you have it located somewhere. I know that doesn't answer the question of if you're looking for me to tell you that it should reside in I.T. or business, but recognize that some people will tell you that if it's in I.T., it's not the best place in the organization. And why are they saying these things? Well, because they're focusing on the audiences that are sympathetic to things about where they want data governance to end out residing. You know, and who are they saying it to? They're saying it to your leadership. They're saying it to the people high enough up in the organization to help them to understand that, well, we really don't want to have this in under I.T. We want to have this in the business or they could be saying the other thing. The bottom line is when I'm asked the question of where data governance should reside in I.T. or the business, my easiest and quickest answer to that question is yes, it just needs to reside somewhere. And you know what? Leadership needs to understand that it's not going to happen on its own. So somebody needs to be accountable for it. They just they need somebody needs to administer it. All those things that we talked about. So basically, there's a lot of people that are very willing to tell people everywhere that data governance in I.T. is destined to fail. I'm not one of those people because I've actually experienced some organizations where data governance in I.T. has not been successful and where data governance in I.T. has been successful. So is it true? You know, the people are saying that data governance in I.T. is destined to fail. No, it's not true because I'm going to give you some examples here in a minute of several organizations who have focused their data governance programs and it's been very I.T. Center. So it's not true that data governance in I.T. is destined to fail. But if you ask a lot of people and I've experienced this as well, that if it's in I.T., it may not be the best place unless there is a real strong relationship between information technology and everything that that makes up and quote unquote the business and everything that that makes up. And sometimes there's not a perfect relationship between the two. OK, let's talk about maybe how we can use data governance as a way to bring I.T. and the business together. So I think that's something that that many organizations should consider. And the best answer that a consultant will most often give you is it depends. Right. So is it true that the data governance in I.T. is going to fail? Well, I guess maybe or sometimes it's going to fail. The fact is it has to live somewhere and many organizations are focusing on something that's called shared services, even I.T. information security can be considered a shared services, a shared service in the organization. So there have been some organizations just like things like Enterprise Analytics or the Enterprise Data Office. It's there to service the entire organization. Maybe truly data governance result should reside in a shared services part of the organization and that is not necessarily specified as being I.T. or business. So I hope you weren't expecting a just a single answer. Let's answer the webinar in one word. We're going to say that in the business, I think that's really one way to look at it and I I stand behind that. I understand that it's somebody in the business. So let me give you some examples of where data governance has really been positioned in I.T. and where it's been successful. As I said before, it has to live somewhere in your organizations. Let's talk about the positives and the negatives of data governance residing in I.T. And then as the name of the webinar series, we'll talk about real world I.T. based data governance examples. So typically, you know, so there's one hurdle that we need to get over even before we talk about whether or not data governance should reside in I.T. And that's the whole concept of I.T. governance. I had a client mention to me this morning in a meeting how the new buzzword for organizations is the word governance. There's I.T. governance. There's information governance. There's data governance. There's records governance. There's information security and information access governance. There's a lot of different types of governance. So I.T. governance is a thing. But let's talk about data governance first. So data governance is has a lot to do with data prioritization. What's the most important? What's the most critical data? Where do we want? Where are we going to get the most bang for our buck if we have better definition, production and use of the data? So it's data prioritization. It's engaging the people in the organization that define produce and use the data. That's the stewards. So it's engaging the steward community. It's improving the organization's overall literacy. So how to talk about data and how to talk with data and those types of things, that's the whole life cycle management and the issue of opportunity. But there's also this thing called an I.T. governance. And some of you may have had experience with some of these things. But I.T. governance is very different from data governance. And I've even worked with organizations where we'll work there using the word governance, so we should put data governance under it. So we have actually seen the data governance function report into an I.T. governing executive board, but typically the function of I.T. governance in an organization has more to do with the overall projects, intake and prioritization of projects and what resources are going to be applied, how and who's going to manage the project and what's the budget going to be. So at least from my experience, we need we need to get over the hurdle because the term governance is being used to describe everything. And one of the things that we should be thinking about when we're thinking about where we are placing governance within the organization, we should take a look at what parts of the organization are already governing. Then they may not be using the word governance, but there's a whole lot of them and I'll share those with you in a minute. So data governance, you recognize, data governance has to live somewhere. That's pretty easy. And so if you already have a data governance, if you are to have something wrong with my wording there, but if you already have a data governance function, or if you're going to have a data governance function, it has to live somewhere. Most organizations don't hire an outside firm and an outside person to actually govern their data. And I usually suggest as one of the rules of non-invasive data governance is that there's people already governing data. There's already people defining, producing and using data. So you don't really need to hire data stewards because those people already exist within your organization. So somebody still needs to administer the program of helping people to recognize themselves as data stewards and sometimes policy can dictate where your data governance program resides that there's that sometimes data governance programs are put in place as responses to examiners or an audit has taken place within your organization. So the fact is that there's already governance that's taking place in your organization, there's already governance that's taking place in other funds or there's governance, I didn't say data governance, but there's governance that's taking place. Same thing holds true with your data that if you just go and you formalize what's already there, that is kind of the core tenet of the non-invasive approach, but, you know, we're talking about the administration of the program. But when it comes to everybody else in the organization, yeah, data governance has to have a home. But there's already people in your organization that are governing. And if you can put some formalization around that, people who use sensitive data have to protect sensitive data, people defining the data that are going on to your key performance indicators, they need to define that data clearly, especially if people are going to be expected to follow the rules and follow those KPIs. So let's talk for a moment about the positives and the negatives of data governance residing in IT. And as I mentioned before, doing data governance or putting a data governance program or governing your data with just IT and not the business is like tying one arm behind your back because there's a lot of business knowledge. But, you know, there's a lot of data knowledge that's in IT as well. So there's some positives that we should look at. There's knowledge about the systems. There's knowledge about the databases and the data models. If you're if you're still modeling your data, the budgets and the resources. So there's a lot of things that you can take as being positives when the organization is focusing your or your program is residing in IT, because there's a lot of knowledge about the data. But there's also some negatives and the negatives are that truly the business. You know, the business owns the data. The business is the one that's making the decision and producing the data. Or are they so you need to ask that in your question. But ideally, that's who you want to the systems are providing the pipelines. The business is providing the data that flows through those pipelines. So the business defines what data is necessary and it produces the data and it uses the data. I mentioned before that IT's relationship with the business, with all of the business could be strained, but it could also be positive. And one of the things that you might want to consider is just taking data governance and using data governance as a way of bringing together IT and business. It doesn't matter where it resides, it has to reside somewhere. But using that as the opportunity for the coordination, cooperation, collaboration between the IT and business. So let me give you some examples of some real world IT based data governance examples and anybody who wants to talk about these, take it offline and we can talk about them. But just some quick examples, financial institutions all over the US, Canada, all around the world, retail operations, associations, more and more associations and groups are looking to provide frameworks to their to their members, to the people that are are parts of those associations. Manufacturing, just as the example, the financial institution in the Midwest, it actually landed in IT. IT had responsibility for it. The CIO had the responsibility for that in another financial institution. It was the records management people that fell under operations. And you can see these aren't traditionally IT, they aren't traditionally business. Sometimes IT plays a key role in this. Just to give you a few more healthcare institution, the CMIO, Enterprise Analytics and a financial institution. So if you're going to specify IT or the business, be very specific around what the function is in the organization that's going to be considered to be considered to be the business, because each of the service areas of your organization, each of the functions, you know, has a name, has a specific function to say the business is just kind of like I said, it's not really a cop out, but it doesn't go into enough detail. It has to be more than just the business and it needs to be more than just IT, too. It needs to be what area in IT, because again, somebody needs to be accountable, somebody needs to administer and move the program forward. So let me share with you in the few minutes that we have before kicking them back to Shannon to see if we have questions. What are some of the considerations for answering in your organization? Let's talk about the ownership of the accountability for governance who's going to pay for it, who's going to administer it, and then talk about what levels of governance already exist in your organization. So what are the existing data functions within your organization? What are the existing governing functions? I'll list some of this. Where do those functions reside? So these are all things that you should really be considering when you are having somebody who's going to own the reins of your data governance program. Consider what the relationship between IT and business is. Consider shared services like IT, data services. I don't know too many organizations that have that, but maybe some do already. Who's going to pay for data governance? I'm listening to Danny. I love to have Irwin by Quest as a sponsor. You know, all these data catalog tools and the tools that will help you to bring more intelligence from your data. There is a cost associated with those, no doubt. But the true governance of the data is mostly people cost. So it's people finding time, engaging people formally in what they do. So data governance for itself. In fact, I've even said data governance costs the time you put into it. So it's mostly people cost. There's certainly a technology cost when it comes to catalogs and enabling people with knowledge and intelligence about the data so that they can do intelligent things with the data. And so who's going to pay for this? It's going to benefit all of your stewards. I always say that everybody in the organization is a data steward. But mostly it's who's paying for assuring that you're delivering trusted strategic data with confidence to people. And that's one of the things that you should be considering when you're answering the question of, well, who should own this? Who should be running this? Who should be administering this? And so speaking of administering, you know, administering, the ship will not captain itself. I always say the data will not govern itself. The metadata will not govern itself. Data governance as a practice in the organization. Or should I say the practice of governing data will not happen on its own. Or it probably would have already have happened, but somebody needs to administer it. So the ship won't captain in itself. Somebody needs to define your program, develop your program, deploy it. Time needs to be spent evangelizing. And I know probably a lot of you, a lot of people in the data community, just being at the the DGIQ conference last week, there's a lot of people who are evangelizing how important data is. And I know you're probably in that role where you're promoting it and you're selling it, but it takes time and these things, the artifacts that you're going to use, they're not going to materialize on their own. So somebody needs to administer the program. Somebody needs to develop the artifacts that are going to be used to promote and sell and to market and campaign the program. There's going to be somebody needs to execute and enforce authority over the management of data. My definition from the beginning of the webinar, the four C's consistency, collaboration of all of those, you know, start by recognizing who the people are who are governing your data and just kind of start with those people first. And then somebody needs to run the program. And that's really what we're talking about, who should own that? So what are some of the organizations that are all parts of your organization that are already governing? Well, information technology, they're already a governance function. They're governing data as part of IT and information security is governing data as part of information security. When I told you, one of my clients says the term governance is the buzzword. One of the things that I've been thinking about is do we need somebody to kind of corral all the different governance that's taking place within your organization, all those things that I have listed here, they're not called governance. IT is not called governance. Information security is not called governance, but they're governing. They're governing people. Even human resources is governing the human resources of the organization. So there's governance. Your organization is used to governing. So maybe one of these areas would be the appropriate place for your program to reside, maybe not, maybe it already resides there. But again, there's governance that's already taking place in your organization. So in the few minutes that we have left, just kind of a quick informal poll and we'll use the chat again. And I see that there's a lot of chat that's still coming through. But where does your data governance program presently live? And so and so it's all just let those kind of flow. And then I'll report those back to folks as part of the answers to the Q&A. If we get time to do that. And then the question is, who wants to own data governance? Is there somebody who's really stepping up and saying data governance is what we should do, what we should be responsible for it? Looking at those existing governing functions. And then I want to talk to you about a chief governance officer. Just an idea that I've had that somebody needs to corral these different governing functions within the organization. So, you know, so here we started the chat already. I can see that it's moving resources who are dedicated to data governance. They're allocated to governance. One of the things that is really important that wherever your governance program lies, recognizing that there are other functions within your organization that are governing and leveraging them and working with them and partnering with them is really important. Because if you don't do that, they're already governing your governing. Who's governing what? How are you governing it? It has to be a collaboration between you and your partner. So whether or not data governance falls in IT or it falls in the business, you should make certain that you look to see who's already governing in the organization and recognize that those people who are governing are your partners to success. And then the question always becomes, who wants to own data governance? It's like it's the hot potato. You know, does anybody else want it? And that's why I say, be thankful where it's residing right now. I know that might not be the advice that you were looking for from this webinar, but be thankful for that because, you know, somebody has taken the initiative to at least have it somewhere and then recognize what other functions. And, you know, one of the things that's most important because there are so many different parts of the organization who are governing differently is to differentiate between who's governing what and how they're governing it. And if you can be consistent and you can get people to collaborate, again, data governance is really all about building, leveraging and building partnerships. So that's what I suggest. And, you know, if there is a part of the organization that is going out of their way and they feel that data governance should reside with them, well, you should talk to them and see what, you know, how, how is it being there being any different than how it is presently within your organization? So I shared this list before, you know, you've got information technology governing IT, you've got information security governing information security and application development and governing reporting and all those types of things. You've already got governance taking place in your organization. Should your data governance function take place in that part of the organization? Probably not, but you would want to part with you. I certainly would want to partner with them. And kind of the last thing that I want to leave you with, and then I'm going to turn it back over to Shannon, is that whole concept of the chief governance officer? I don't know if it's a novel concept or I don't know if it's a stupid concept, but I'd be really curious to read your feedback or if you have any comments on that, get back to me and let me know that. Certainly somebody needs to get these different different governing functions to work together and consider what the needs of the other of different parts of the organization are and just because they're setting up governance committees in different parts of the organization, somebody's got to get coordination and collaboration between them. I haven't seen a chief governance officer yet. I'd be curious to your thoughts as to whether or not there will be a need for a governance officer. My last suggestion is that regarding your organization, wherever your governance program is right now, that's that may be good enough. And if it's in I.T., that's fine. If it's in business, it's fine. If it's in I.T., don't try to do it without business or working with business as a partner and the same thing holds true in reverse. So I'm sorry, maybe it's a cop out to the answer of the questions today. But we first talked about what is the business when it comes to owning data governance, why some people say that if data governance resides in I.T., it's going to fail, I'll give you some examples, some considerations. And the truth is that it depends. It depends on your organization as to where data governance should reside. Be happy it's residing somewhere now. Position it appropriately if you have the opportunity to do so. And with that, Shannon, I'm going to turn it back to you and see. Do we have any questions today? Thank you so much for another great presentation. And if you have questions for Bob or for Danny, feel free to submit them in the Q&A portion of your screen. And just to note, answer the most commonly asked questions, just a reminder, I will send a follow up email by end of day Monday for this webinar with links to the slides and links to the recording. So the first question here is for you, Danny, is Erwin data modeling part of the Quest Data Intelligence Platform? Or is it a separate tool? And in that case, how do they interact with each other? Oh, my goodness. That's a wonderful question. They are absolutely separate tools that work very well together. So the data modeler, you still can get your standalone data modeler. There's also the data modeler that works with a collaborative modeling repository. So it is separate from the data intelligence tool. But the data intelligence tool has something that we call a data connector. So it actually connects to the data modeling repository. And you can specify in that interaction which models you would like to go to the data catalog. And then once they're brought into the data catalog, they are then properly aligned with the metadata scan for the data source that they may represent. So so, yes, they do well and work very well together. And they end up feeding the catalog and add more curation to the catalog. But you can use data modeler either as standalone or collaboratively as a separate product. Perfect. I love it. So, Danny, in here, in relation to data governance ownership, where should the data management ownership exist? Well, it's almost the same question of who should own data governance? Who should own data management? I know a lot of organizations that are struggling between what's the definition of data management? Does data governance fall under data management or does data management fall under data governance? And to me, the data governance, as I mentioned, is really the people aspect of things, getting people to do the right thing at the right time in the right way, you know, in those types of things. So I don't know. I just think that it needs that. There's just not one place. I don't know, Danny, what do you think? Yeah, you know, I would tend to agree with you because, you know, every organization is different. All I can speak to is where I've seen some some good success and some, you know, some rapid transformation in terms of the impact of data with our customers. And it truly is where they've they've sort of brought in a chief data officer who is, you know, a peer of the chief information officer, not reporting to them because data, you know, data is not IT. Data is obviously a huge component of IT, but it is not technology. It is something different. So what I've seen in success is to have data governance, data architecture and data management as the remit of the chief data officer and then the appropriate connectivity with the other parts of the organization that are going to enable them to do that. But they've taken a one-throat-to-choke approach where data comes under one. And luckily they've funded it appropriately that, you know, so that they can make that happen. But I wouldn't say that that's a sort of a recipe for success. It really is, you know, again, down to as you say, Rob, the relationships that that are built and how those folks relate to each other, because I've also seen where taking data out, especially data management out from IT, brings in more complexity to the job of, you know, moving that forward. Who's who's is this, who's making the decision is my decision in line with your decision. So unfortunately, as with most of this, never an easy answer. But again, if you have a strong relationship builder and somebody who really can can leverage that influence, that has been something that I've seen be successful. And I don't know if I've ever seen data management per se fall under under business. I mean, data management almost at least from again, I can only speak from my experience in organizations. They have the responsibility for the data warehouse. They have responsibility for the data models and the data modeling tool. There's a data modeling piece of data management, which falls under IT. At least that's the way traditionally things have done. So I think that again, there's not a single answer to how it should be structured within your organization. Data management, I think it really makes a lot of sense for organizations to almost create a Venn diagram or something that shows data governance in one bubble and data management in another bubble. And they would they come to overlap that overlap of how data management and data governance work together would be something that's very valuable for people. That same type of tool would be the same for data governance and information security or any two functions. You define what their functions are. And then as you bring them together and you see how they overlap, that's going to depend. So if your data management group has the ability to implement your governance function, I don't think there's any problem with that. And like I said, it all depends on your organization, at least what I've seen is what's been successful. Good question now. Great question. Yeah, and. Warwick, I love your diagram there in that chat. That's amazing. Can you have a viable data governance program if you have a CDO in name only and no actual budget get dedicated to data governance? Sorry, sorry, I laugh. To have a chief data officer, if they're being held accountable for something, it's going to be the data, I would think, for the chief data officer. So if they have no budget, if they have no, do I have any suggestion to them? I'm going to ask you your response to this as well. I would say that they put together a strategy and they put together a plan and then they're going to have to do whatever the heck they have to do in order to get some budget to get some resources. And so being a chief data officer by name only, can I may put a person? A member I talked about accountability, administration. Well, it would put somebody accountable for the data of the organization. And I would take their skills and I would have them focus on creating the data strategy and then going out and marketing like heck, that data strategy to the organization, so they do have budget and they're not as chief CDO by name only. Danny, what do you think? Oh, I think you nailed it there, Rob. I'd like to know why they took the job in the first place. But, you know, I think at this point, they're not really a chief data officer. Maybe a chief data evangelist. Well, that is their opportunity right there, right? To write to set the course for the organization. And any journey starts with your first step and that may be your first step to your organization. Yeah, absolutely. And we're all salespeople at the end of the day. So, you know, if they do their job right, they will have a budget or they will have a budget that they have access to. So, yeah, interesting, interesting approach. But, you know, once you get your foot in the door, then you can start to to make all sorts of hay. So, you know, good luck to them. Very polite answers, I like it. So how would data governance work in a data mesh where each domain in an organization looks after the data relating to that domain? Oh, so I always fear it's the data mesh question that comes with a lot of the webinars that we do. You know, I don't work. I haven't worked a lot with it. So I'm not going to try to answer the question. But the one thing I do know about data mesh is that accountability is pushed out to people with new organization. And that's very much aligned with a noninvasive approach. I won't talk about, you know, I think that, yeah, you're going to need that accountability no matter where your program is housed, whether it's housed in IT or business. So I've got myself into trouble trying to answer data mesh and fabric question. Danny, you have an answer that can bail me out. I don't know if I can bill you out, but maybe I could just take the spotlight on me. Again, much like yourself, I haven't seen a lot of organizations that are, you know, operationally in a data mesh. Most of the data mesh conversations are if we were to go that way, how would you support us? So, you know, so take this answer with, you know, as many grains of salt as required. But, you know, to me, it just it screams for a federated model. Right. So, you know, there's there's some things that that really should be applied to all of the domains. And then there are some things that are very specific to the domains. And then it becomes a sort of top down bottom up and, you know, meet in the middle. So I would say that, you know, if you're going down the road of a data mesh, you you you you still have to have governance, right? If you don't, I think you you're even at more risk than if if you're not in a data mesh, because, again, that it screams Wild West to me. So or the potential for Wild West. So I would say that that a federated model where where, you know, those different owners in the different domains become part and parcel of that, you know, with a seat at the table and then those are discussions that are going to drive out. And, you know, the the upside is that that you can then start to leverage best practices between domains, especially at the point of intersection and integration. Thank you. I'm hoping I gave you some cover there. We'll see what the chat says. So here I'll let Shane and ask another question here in a second. But the federated model makes a lot of sense. And, you know, if that is and again, I guess I don't know enough about mesh to speak intelligently about it. But if you're going to follow a federated model, whether it's by domain or it's by function of an organization, you can almost expect that federated is going to be an approach that you're going to want to consider within your organization as well. I don't want to call it an approach, but the federated model where somebody is setting up the guidelines and the standards and people are being told what the standards are and they're not being told how to follow the standards just that the standards are there and then they need to be followed. Federation is really important. And if the mesh is helping you to do that, governance can piggyback on that as well. And it needs to get there. They're pushing the accountability out to the people of the organization is what governance is all about. And that's where the business really owns the data and whether or not your program resides there or not is up to you. Absolutely. Well, Bob and Danny, thank you so much. But I'm afraid that is all the time that we have for this webinar. Thanks to everybody who has attended today. It is, as Bob mentioned, the last webinar of the twenty twenty two year. I hope you all have a great holiday season. Thanks, Danny, for joining us on this webinar today. And thanks to everyone for sponsoring. Again, just a reminder, I will send a follow up email by End of Day Monday for this webinar with links to the slides, links to the recording and answers to the remaining questions that we didn't have time to get to today. So I hope you all have a great day. Happy holidays, happy new year and see you on the flip side. All right. Take care, everybody. So much, guys. Thanks, everybody. Have a good one. Take care, everybody. Bye.