 Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Officer at Data Diversity. We would 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 how data management and data governance overlap. Just a couple of points to get us started. Due to the large number of people that attend these sessions, you 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'll be collecting them by the Q&A section and to find the chat and the Q&A panels, you can click those icons in the bottom of your screen to activate those features. And 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 introduce to you our speaker for the series, Bob Siner. Bob is the president and principal of KIK Consulting and the 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. Hey, Shannon. Hey everybody, thank you for attending this month's webinar. Somehow, some way when Shannon and I are putting together the series of topics for the year, we come up with topics that tend to be very hot at the moment that the webinar is taking place. So this one, particularly for several of the organizations that I'm working with and several other organizations that I know about, they are struggling with trying to define the differences, the similarities between data management and data governance and where they overlap and how they can work together. So that's a great topic that somehow Shannon and I hit it right for this month for this topic. It seems like there's a lot of people that are interested in this topic. So thank you again for taking the time to be with us live or to listen to the recording of this webinar. Before I get started, I always like to spend a minute talking about some things that I have going on in my life, in my data management data governance life. And as you know, I do this webinar series on the third Thursday of every month. Next month we're going to be talking about gaining leadership support for data governance. That might be an important topic to you for your organization as well. I'm going to be speaking at several events coming up a couple of them are Dataversity Events, the DGIQ West Conference in San Diego, actually, I'm doing a full day presentation in three weeks from today. So if you're still interested in that conference if there's still room, please look for that. Also Enterprise Data World is in person in Anaheim in September I'll be speaking there. One of the issues is that just yesterday my second book was released, and it's called noninvasive data governance strikes again I'm not going to spend too much time or anytime talking about it here but if you are interested in how noninvasive data governance strikes again the first book came out in 2014. I've learned a lot of lessons I've gained a lot of perspective in the years since then. So I'm including I've included those in the new book. I also have several lesson plans learning plans available through Dataversity one on noninvasive data governance one on noninvasive metadata governance and one on business glossaries dictionaries and catalogs. My consulting business is KIK consulting and educational services. I refer to that as the home of noninvasive data governance. Shannon talked about the publication T Dan. So as I have spare time, or as I have time, I'm also an adjunct faculty member at Carnegie Mellon University here in my hometown of Pittsburgh, Pennsylvania. So what are we going to talk about today, in terms of how data management and data governance overlap Well, the first thing I want to do is I want to share with you some foundational definitions of what data management are and what data governance are. There's one single definition that's accepted across industries across organizations. So I'm going to share with you some definitions and how you might or things that you might want to consider when you're putting your definitions to what your organization means by data management data governance, how they overlap, how they don't overlap how they need to work together. Those types of things are really important. We're also going to talk about how they're the same, and how they're different. And how important it is to build a partnership between the people that have the responsibilities for data management and the people that have responsibilities for data governance and the functions of those two disciplines. And then last I'm going to talk about how how do we go about advancing the two disciplines together. And we're really going to focus on the overlap. I'll share with you a diagram. Excuse me, share with you a diagram that I put together that kind of outlines how data management and data governance overlap. So we'll get to that in a minute. First thing I'd like to do in all of these webinars is share with you just real quickly, before we do a deeper dive into the definitions, my quick definition of data governance my quick definition of data management and a couple other things. Data governance as being the execution and enforcement of authority over the management of data. A lot of my clients don't like that definition they think it's worded too strongly. But at the end of the day you need to be able to execute and enforce authority over data that is, when the government comes to you and tells you you need to comply in a certain way. They're not asking you they're telling you that you have to. So you need to execute and enforce authority where it's necessary over data and data management. I don't really have a regular definition for data management, but this is what I consider it to be a cohesive set of disciplines focused on delivering quality data and information. So you can just see by these definitions that there's going to be some overlap, at least in people's understanding as to what data governance does and what data management does. So I'm just going to share these definitions real quickly to of data stewardship and what a data steward or who a data steward is. I refer to data stewardship as being formalized accountability for data so if you use data that has to be protected. You're a steward of that data you need it's not optional, you need to protect that data. If you're defining data you're producing data as part of your job. If you're formally accountable for how you define produce and use data, I consider you to be a data steward. So that's why I say data steward is a person held formally accountable for what they do with the data to with for their relationship to the data basically. And then in terms of metadata and data documentation and those types of things. I refer to metadata as data that improves both the business and technical understanding of the data. And yes, there is such a thing as metadata governance, because as I've said in a lot of the webinars in the past, the data is not going to govern itself the metadata is not going to govern itself. Somebody has to have the responsibility for the metadata as well and those people basically are metadata stewards. So the first subject that I really want to go into some detail on today is just some kind of foundational definitions for what data management and what data governance is and I'll share with you my full definitions and dama and the data warehousing Institute and IBM there's a bunch of different definitions, and there's no single correct answer for your organization so we're going to need to also talk about. Well how do we take these definitions and how do we construct, what would be a correct or at least a proper definition for your organization. So then we'll talk about what what should your definition really depend on. And what are some of the core differences between data management data governance, because to a lot of people data management is very operational in nature, and to data governance is actually very people oriented and very behavioral in in in what it focuses on, but there certainly are. There are overlaps and they need to we need to figure out in organizations what it's going to take for these disciplines to work together. So the first thing I wanted to do was focus on some definitions of data management. And so as I said before data management is a cohesive set of disciplines focused on delivering strategic data with quality and confidence. It is if you look at the dama framework the dama wheel. It has a whole bunch of different disciplines it has a set of this disciplines that hopefully would be cohesive in nature and within your organization, but even dama has now defined it as being the development the execution, the supervision of those things plans policies programs practices, and what do they do they control protect deliver enhance the data. There is a lot in that definition from dama international. It's a great definition. It certainly needs to be dissected a little bit it could certainly be broken into pieces with each of those pieces being explained. The Gardner it glossary says that data management encompasses the practices, the architectural techniques, again a lot of want to read the complete definition to you. In fact, I have another page of definitions of data management. And it's a set of disciplines that supports the management of data. That's a cheeseburger definition by by my definition cheeseburger definition is a definition that includes the words from. So if you define a cheeseburger as a burger with cheese. And you define data management as supporting the management of data. And if I think it becomes a cheeseburger definition, and then data management is the development execution and supervision. There's a lot to each of these definitions. And so I don't know if your organization is thinking about selecting one of these or, or building your own, but at some point, especially if you have the functions of data management data governance in your organizations, you're going to need to be able to differentiate between the two. So defining a definition of data management, especially if you have a data governance function is going to be important, because people need to, or people are interested in knowing what is the difference between these two disciplines. And there's a lot of reasons for wanting to differentiate between these and the because they may be reporting to different parts of the organization they may have different functions or different. Projects that they're working on. It's important to define these things so here's just at least I shared with you five definitions of data management. And there might be something in there that you could use as you define your definition of data management for your organization. So now let's do the same thing with data governance. I always use my definition of the execution and the enforcement of authority over the over the definition production and usage of data and data assets. It's worded strongly but at the end of the day, it doesn't matter how what approach you take to data governance if you take a non invasive or a command and control, or a kind of a traditional. If you build it they will come type of an approach you need to execute and enforce authority. So I like that definition even though most organizations don't tend to gravitate toward it. If you look at the gardener it glossary it says data governance is the specification of decision rights accountability framework. Data governance Institute my good friend when Thomas data governance encompasses the people process and information technology data international the exercise of decision making authority IBM. It's a system of decision rights again there's a lot of standard standard terms that are being used across data governance and data management and not only that but they seem to share some of the same terms. So if you're wondering why there's confusion between data management and data governance. That's because we're defining them the same way, maybe we need to get away from the way that we're defining them, talk about how they work together instead of defining them using some of the same terminology. So, when I started looking at these definitions I put together this diagram. I really like the concept of action delivers outcomes because that's what when you when you're developing a program you want to have you want to take action. You need to deliver something and what are you delivering, you're delivering outcomes when it comes to your data. And then I went and looked at each of the definitions that I just shared with you. And looked at the action words that took place at the beginning of those and what it said in the middle and what it said at the end, basically try to pull out the actions, and what was being delivered and the outcomes that could be expected. And so, if you look at what I when I say the data governance is the execution and enforcement of authority over the management of data, you could almost pick from one from each of the calls. I would say that the same thing holds true maybe would pick multiple from the columns or add things to the columns that make sense to your organization. But when it comes to constructing a definition of data management and data governance, there's a lot of definitions that are out there. And I'm not going to give you one that I say you should use, because it really depends on your organization. In fact, I want to talk about what should your definition depend on. Sometimes, here's just a list of things and I hope you'll go back and look at this slide deck at some point when you're putting together your plan for data management and data governance, that it really should depend on the organizational objectives. What is your organization trying to accomplish, how regulated is your industry, how much do you need to focus on the life cycle and the different types of data. I'm going to walk through each of these things in significant detail, maybe at some point some of these subjects would be great for additional webinars in future years of the webinar series. But all of these things the organizational structure how you're going to scale a bit scale this across your organization. Are you concerned about ethics and privacy is business value important to you. All of these things are things that you might want to consider when you're starting to build your definition. So, again, thinking about the previous slide that had the three different buckets of action deliver outcomes. Make sure that your actions are aligned with the things that are important to your organization, make sure that the outcomes are important and the things that are being delivered along the way. So again, just a different way to look at the definitions of data management and data governance and maybe it would be good to have an industry standard definition or at least agree on the idea that data governance is more. It is the term operational to start and that data governance is more people and behavioral oriented but I'm getting ahead of myself let's let's talk about that a little bit as we go through the rest of the slides in the webinar. So, I have a friend that referred a good friend a friend of data diversity and Len Silverstone, who told me at one time that we shouldn't refer to it as data governance we should refer to it as people governance. Because it's really people's behavior, how they define how they produce how they use data, and how they're held accountable for it. He said, we should really call it people governance instead of data governance. I've talked to Len about it. He doesn't remember having that conversation, but I remember it pretty clearly I think it's good I think it's a good way to look at it that data governance is really the behavioral aspect of the management of data, if you want to put it that way so people governance instead of data governance and I haven't seen an organization that's used that phrase yet. I say execution and enforcement of authority, it certainly has a behavioral focus. If you're going to execute authority, you're going to enforce authority, it has to do with what people in your organization are doing. That's a very behavioral focus. And then the formalization of accountability if you remember that was the definition I shared for stewardship formalization of accountability that is very behavioral focused. But when it comes to the definitions that I shared of data management it was very operational monitoring reporting those types of things. But when we think about the technologies that are associated with data management and data governance. That's where some of the issue that's where there's some of the blend is hate to use the term but who owns the technology. If you have a data catalog tool. It's a data management tool it's also a data governance tool. So there needs to be some coordination cooperation between the groups that are doing data management and data governance, instead of the tool falling into one groups hands. It should really fall into both groups hands, and they should both be partners basically and how they work together. So that's the definition I know as I feel like I spent a lot of time just on the definition of data management the definition of data governance. I want to spend a little bit of time now talking about the function of each of these disciplines. And I think that the operational versus behavioral aspects of data management versus data governance might come a little bit more. So let's start by looking at the scope and focus. So typically, and again this is from my experience and please use the chat room, the chat board, if you've experienced things differently, or if you have some ideas as to things that you can share with people to help them to do that. So typically, and again this is from my experience and please use the chat room, the chat board, if you've experienced things differently. Or if you have some ideas as to things that you can share with people to help them to differentiate between their data management and their data governance functions, please feel free to do that. So here in my experience in data management tends to operationalize certain aspects of how data is managed or how data lives throughout its life cycle, and data management focuses a lot on on the processes and the technologies, you know, looking to make certain that there's efficient and effective ways of handling data throughout the life cycle. I've done a general description of data management, but that's really what's typically in focus, at least in some of the organizations that I've worked with in terms of what their data management programs look like. In terms of data governance. Oftentimes, and I'm not saying that data management is not strategic and organizational in its focus but data governance is maybe more strategic and organizational, and it's in its focus. Like in the Carnegie Mellon program I work in the, you know, when they start talking to CDOs and developing chief data officers and chief data analytic officers. A data strategy is the number one item data governance is the number two item on the list of things that people with that level need to consider because governance is going to be required management is going to be required. Data governance certainly has a strategic and an organizational focus. As I mentioned before it's a very much of the behavioral aspects of data management. And in the framework that I share at least for the things that need to be considered at least from a behavioral focus for data governance. There's the six core components of the data needs to be focused on the roles, the processes the communications the processes at least from a behavioral perspective, and within the organization. So now let's look at the activities of data management versus data governance. So again, data management, it tends to be the operational aspects of handling and maintaining data. And I started looking for well what are some of the terms associated with what data management does in a lot of organizations. And here is just a laundry list. They're responsible for data collection acquisition storage organization, all of these things privacy analytics maybe insights, but they're not going to do all these things on their own. The activities of data management have to do with all of these things but they can't do these things in a, in a closet by themselves, they need to work with other people. They need to depend on people behaving behaving appropriately in order for data management function to function properly. But data management has their, their, their hands full with so much of the technical and the operational aspect of handling and maintaining the data that it's oftentimes a relief to them to know that they don't also then have the responsibility of data governance, because it is something that is different. Now if we look at the activities of data governance. Again, very behavioral focused. It focuses on the framework on the policies on the stewardship we talked about stewardship earlier, the committees and the teams the standards, all of those types of things, ensuring compliance and risk management. And this data governance, the activities are looking to make certain that the data is consistent compliant responsible handling of the data and information so at least when it comes to activities. There seems to be a relatively clear differentiation between the activities of data management and data governance. And again I'd be curious as to what your thoughts are on how they're interrelated within your organization. One aspect of defining the function of each discipline has to do with the implementation of data management. So oftentimes the implementation of data management comes through the execution of processes and technologies and practices, and basically those types of things it comes down to the development and the building and the maintenance and the retention of the databases and data sources that the data warehouses the data lakes, building the platforms, you know data integration quality so all of these things seem to be key verbs or keep terms that are used. When you're defining well what does data management do what are the implementation factors, what are the things that data management focuses most of their time on. So data governance, again going back to the definition that I shared earlier, it really has more to do with the execution and enforcement of authority over the data. So again the the implementation has to do with implementing a framework, implementing a structure that might include well should include the roles and responsibilities, we've done several webinars in the years that we've been doing these webinars and we've talked about data diversity on specifically the roles and responsibilities, you know setting up policies setting up best practices, setting up standards. So, and again what are some of the things that the data governance focuses on in terms of the implementation. From my experience, it has been stewardship stewardship organizations talk about the stewardship approach to data governance. As a governor data we're going to do it through the people of the organization and how they behave associated with the actions that they take with the data. I know a lot of organizations use the term owners to define people at certain level of accountability or responsibility for a set of data. I tend to shy away from the term owner, because it, the organization typically owns the data. And that is the appropriate term because a steward by definition is somebody that takes care of something for somebody else so data governance the implementation of data governance is oftentimes done through stewardship. Recognizing who the stewards are helping them to be held accountable, you know, escalating issues and resolving issues and enforcing levels of authority over the people in the organization. And left to their own accord, people will define their own data sets over and over and over again, and you'll, you'll have silos of data and you'll have multitudes of data resources. I don't know if that sounds like your organization, but without governance, that's what happens. So, we need to implement governance we need to hold people accountable for the data we need to focus on stewardship, as well. And the next thing I want to talk about is how are data management and data governance, how are they the same. How are they different. Does it matter, why does it matter does anyone does anybody really care. I did a podcast with a good friend of mine Anthony all men, not too long ago, where we just spent an hour spent 40 minutes or so talking about, does anybody really care about the difference between data management and data governance. In fact, then we came to a conclusion that yeah people do care, especially if it's causing problems or it is presenting issues within your organization. So how are they the same well they both focus on data. They both require some level of organizational alignment, people in the organization have to have responsible responsibility for it, it needs to reside somewhere in the organization. They both tend to focus on policies. A lot of times there's information security policies sometimes their data classification policies data handling policies retention policies they're all data policies. So that's again, something that they're this they share something that they have in common. They are both require collaboration, they both require levels of accountability for for people's actions that they take with the data. You know, we can't get away from it, you know, they both involve the need for compliance and risk management as well so data management and data governance focus on the data of the organization. It's not should be surprising to us that there's a lot of similarities that in between the things that they are both trying to achieve. The thing is that we need to differentiate between what what is the function of data management and what is the function of data governance. It's not about how they're different they're they're the same in a bunch of ways I think that's understood in a lot of organizations, but how are they different. So we talked about the focus in the perspective we talked about the scope, and those things were discussed earlier, but oftentimes when organizations, when it comes to the level of abstraction, as to what do we mean by data management and data governance. Data management tends to be more concrete it tends to be more hands on in organizations. You've got data modelers you've got data integrators you've got data mappers and analysts and scientists, you know that are that a lot of times have a very close relationship to the data management function within the organization. And then there's data governance, which is there trying to ensure the consistent and responsible practices are taking place and how the data is being managed. So again, one way that they're different is just in the level of abstraction, where data management is more concrete is more hands on, and data governance is more again focused on ensuring consistent practices, and that people are being held accountable for what they're doing with the data. When it comes to roles and responsibilities they're different as well and I outlined just a couple or a handful of rule names in data management, and what some of those roles with some roles might be in a data governance program as well. We typically see data governance programs that refer to roles as data engineers or database administrators or data modelers analysts or scientists as specific roles within it within a data governance program but you do see those in a data management program. In a data governance program, you're going to have a council or a committee you're going to have subject matter experts or domain stewards domain owners in the organization you're going to have stewards, you're going to have partners. The roles are different too. And so there is oftentimes in data management data management oftentimes falls under it and under it there's it review boards and those types of things. There are there are role differences in data management versus data governance. And so I'm sure that if you think about who participates in data management activities now versus data governance activities, you probably already have different names for those folks. And the next question is, so we talked about how they're the same we talked about how they're different. And the question really becomes is does it matter, or who cares if there's a difference between data management and data governance well. The truth is why it matters is because often there's more than one of these functions within your organization. So if you have multiple functions, one that covers each, then there's going to be discussion around who does what. And at least, at least from my experience, what I've seen is that data management functions have been around a lot longer than data governance functions have been around, whether it's called data management, or something else. So data governance is more of the new kid on the block, maybe not that new because now data governance has been around for a while. But, you know, one of the things that that I hear is that, well, somebody's already doing the function that data governance is doing. And the truth is the data management has so much on its plate already that it doesn't necessarily want to or really need to duplicate the activities that data governance does. You know, it's enough of the blocking and tackling of the data of the daily operational lifecycle of the data to have to worry about the authority and the accountability and the, and the standardization and those types of things and people's You know, maybe it's time that we can differentiate that from what data management does and really define a separate data governance function for that, because the data is not going to govern itself. We know that so we need to have a function that is at least focusing on the governance of data. So data management doesn't want to duplicate what data governance does data management already has enough that they're working on to begin with. Absolutely, these two functions need to be partners, they need to work together. So if you look at the operating model and I don't really have time to go through it today, I kind of point down to where the data governance partners are wanting to make that a little bit bigger for you so you can see the operating model. There's a lot of moving parts to a data governance program. The fact is that most of these already exist within your organization, maybe not under these names they don't have to be given these names, because these are roles associated with data governance, but just wanted to show you why do people, why is it important. Well, because you may have two functions, and the question is going to come up as to who does what. So the next question is, does it matter or does it matter that we differentiate between data management and data governance. Anybody asking is, is there a question about it I know that with several of my clients right now there is definitely a question as to not only where governance should reside or what is the relationship between the data management function and the data governance function. And you know what they're looking at these things in terms of being more operational for one and being more behavioral for the other. It depends on if somebody is asking in your organization, that's going to be the time that they that differentiating between data management and data governance is going to be important. So is there a conflict is there a need for a clear definition. You know, my thinking is that that there's the chances are that at some point, the similarities and the differences are going to need to be clearly articulated by somebody. So, you know why should you care why should anybody care because they couldn't report to different parts of the organization, they could have different management. They certainly could have different budgets and have different resources that are associated now with data management and data governance plans and strategies. You know, I have the word different on there four times, you know, why should anybody care because these things are different. I think the rest of the webinar here about how to part to get these groups to partner together. I think that's really key thing is we don't want them to be different we need these groups to be communicating at the highest level that they can within the organization to have some coordination some cooperation between the groups. I told you I was going to share a diagram with you. And I wish I had more than an hour to spend on this subject but I don't. And I'm going to just focus on these things right now. Next thing we want to focus on is building a partnership between data management data governance. And if you look in the upper left hand part of the diagram it has data governance and what some of their people behavioral oriented responsibilities are, and that they're responsible for the governance of structured data on structured data, external data, all sorts of data in the organization will data management is responsible for that same data. And that's one of the biggest problems is we're governing the same data that we're managing. So now I shouldn't say it's a problem but it's, it's a point of contention in organizations and when you look at what data management does architecture the platform the metadata management platform at least quality warehousing master data a lot of those things, I would think that you would agree with me would fall under data management. And then actually when I put this diagram together. I included information security because the organization that I was working with that was those were the big three that really needed clear differentiation but the biggest point here is, look at the right hand side of each of those bubbles. They're governing they're securing they're managing the same thing. We need to focus on the middle part of this diagram, and that is the partnership between these groups. And so we're going to focus couple minutes here on the formality accountability coordinate all these things in terms of how do we build a partnership between data management and data governance. And again, I don't know what what your organization has for this but these are all considerations. When you're looking to put some format. And again, I'm not telling you that you need to do all of these things, but you should be considering when it comes to formality, having these two parts of the organization collaborate and work together and build shared goals and build integrated processes and workflows, communicate together instead of communicating independently and having cross functional training so the data management people are well aware of what's happening in data governance and that the data governance people are well aware of the activities that are taking place in data management and look to find ways to have formal joint initiatives. So if you're building a new data warehouse or data lake or analytical platform or you're integrating systems, work together, formally, put a formal plan together for how data management and data governance work together. And the second one's accountability have clearly defined responsibility roles and responsibilities as to who does what have, you know, work on policy together, you know, make certain that data management understands what stewardship is and how the stewards play a role, and how it's necessarily data management function oriented the metrics and the key performance indicators, the training and the education these are things that you might want to consider that the data management the data governance groups work together and build a partnership on these things coordination. As I said before, instead of communicating separately communicate together, even if they're in different parts of the organization, they can they need to partner together. Do shared services like a business class or a metadata management data integration data quality initiatives, all these things the development of your data governance framework should be a partnership, a coordinated effort between your data management and your data governance group. So again, these are concepts and ideas of ways that you can get your data management group and data governance group to talk to each other to work together. And there's the cooperation and establish a shared vision for what data management and data governance are doing together. Again, cross functional training, a lot of these are repeats in a joint problem solving shared metrics, create these project teams get them to work together, and look for ways to get continuous communication and feedback from people in terms of the outcomes. And remember the, the definitions the outcomes are being so important to the communications about the outcomes of data management and data governance working together. Instead of there being a question of how these two functions operate separately. The question should be how do these, how do these functions how do these disciplines complement each other. Operations, you know, align your data management practices with your data governance policies, and the other way around. Align your data governance practices with your data, data management policies, if you have data management policies is shared the catalog share in the data lifecycle management and the governance of the data and the stewarding of the data throughout the data lifecycle data quality management. Again, I don't want to read all these things to you but build a partnership between data management and data governance that is operationally based. Because if it's active parts of projects and things like that people are going to see with their own eyes, what data governance is doing and what data management is doing, and therefore we can not only share with people how they are the same, but how they're how they complement each other and the value that's coming from each of these disciplines independently. The execution find ways to work together again ways to build a partnership joint planning joint strategy development, you know cross functional project teams I think that's been on there three or four times, whereas get these folks to work together that is the way to get data management data governance to overlap, at least in the ways that they work together. Data management is extremely important to communications, all these things just make certain that you're talking that if you're in one group you're talking to the other group, and you're figuring out ways that we are going to work together. Instead of, again, constantly raising the question of what does one part of the organization do versus what the other part of the organization does. And the last, the last item around building the partnership was communications. So I mentioned a couple times earlier look for ways to be able to communicate together. I mean if you have a joint communication strategy. I'll tell you this with every organization that I work with when they get started with data governance, building a data communication strategy, or a plan is a critical component of their success. They've got to communicate effectively to the organization, even the difference between data management and data governance, but they can't communicate with the executives and the strategic level, the same way that you communicate with the tactical and the operational levels. So you need to have a plan for how you're creating that and delivering that communication. It should be a coordinated plan between data management and data governance. Collaborative training and workshops, regular stakeholder communications, all those types of things, communicate together, then people will start to view you as being complimentary, rather than being independent. So I'm going to go back to that diagram I shared with you, and then have one more section here real quickly to run through. And then I'm going to toss it back to Shannon to see if we have any questions today. My idea, at least I would hope one of the things that you would get from this webinar is that there needs to be an effort, a focused a resolute effort to get these disciplines to work together. Because they're reporting structures may be different that people may be working apart, you know when they're working together how do we start focusing on getting these people to become partners. So back to the diagram. The partnership was everything I just talked about in the last 10 minutes about the formality down through the communications. That's where these things tend to overlap. But then there's always the responsibilities the individual responsibilities of each of these groups. So let's talk about reporting structure working apart, working together and becoming partners. At least this is some of the ways that I've seen it. It established good, strong working relationships between data management and data governance functions is that they established dedicated reporting lines. So it's not really a question as to who reports to who or what function each of these groups has established those dedicated reporting lines and make sure that they're clearly stated to the organization. If they're not in the same dedicated reporting line, then account for that somehow in the way that the organizational structure is set up, because data governance should not work separately from data management. It should not work separately from data governance. If they're not both within the same function, there needs to be some level of cooperation. These groups working together executive oversight and sponsorship. It's the one of the very first best practice for most organizations that if people if your executives don't support sponsor and understand governance. Don't under support sponsor and understand the difference between data governance and data management. Then they're going to have a very hard time continuing that level of support sponsorship and understanding it create the proper committees, the metrics and the performance reporting. Advance the disciplines together through reporting on compliance and risk management and what data management has done versus what data governance does focus on continuous improvement in reporting. We need to get these folks to work apart from each other because these days, especially it used to be a lot easier when we were all in the same office and we could pull the data management team and the data governance team together. But right now we need to take advantage of virtual collaboration tools. You know, clear having clearly defined roles and responsibilities, making sure that we're educating and training people that we get good at holding remote meetings whenever necessary. It's still a very remote world, but we need to find ways for these two disciplines to work apart from each other. But at the same time we need to find ways for them to work together and that's the whole concept of partnership is again the cross functional collaboration. Getting the practices to work together and integrating the things that they're doing sharing goals and metrics communications training, all those types of things. There is an overlap between data governance and data management. We just need to focus on it we need to define those things hopefully some of these things that I've shared within the webinar today will help you to start getting some of those conversations going. So the last thing that I want to share is, you know, establish that partnership framework what does it mean for these functions to work together, develop a joint strategy or in your data management strategy or data strategy in general for your organization, or this strategy in general, differentiate between data management data governance and then define the need for both of these things, define the need for cross functional collaboration, a shared framework, all these types of things, especially do those things that you need to get the support support from one group for the other, and then support for having separate functions that focus on these things. So with that, I just want to kind of summarize the things that I've talked about in the webinar we started with the foundational definitions for data management and data governance. We went into defining what some of the functions were for each of them and I don't know if you agree or disagree with me. It's hard to see that on a webinar, as to whether or not the data management function really becomes more operational in nature, and the data management function becomes more people oriented and behavioral in nature, talked about how data management and data governance are similar, how they both focus on the data of the organization, what it takes to build a partnership between these two functions, and then advancing the two disciplines together. And with that, Shannon, I am going to kick it back to you to see if we have any questions today. Bob, thank you so much for another great presentation has been fantastic. And just a reminder and just to answer the most commonly questions that have been coming up several times. Today is 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 anything else requested throughout here. Moving into the questions Bob. What percentage of data management falls in it. What percentage of data management functions fall in it. I'd say most of them. I don't know I don't have an exact figure for you. Because it's operational because there's a lot of technology aspects to data management. It does tend to fall in it. So if I had to guess a number, I would say somewhere north of 85%. That's just the number I don't know if people are agreeing with me or disagree with me but I see the data management back in the days that I was in a data management function at a blue cross blue shield player plan here in the US a health insurance company data management did fall under it. So it just seems to be several of my clients now. Now if the question was where does data governance reside or where how many of them fall under it and answer the question completely differently. Sure. Are you waiting for me to answer that question too. You're more than welcome to be like. Exactly because I ran short this time and that's like that's okay so we have have a couple minutes. There are some people that will tell you that your data governance function if it resides in it, it will fail. I am not one of those people I have seen successful data governance functions fall under it. Is it the best place for it, probably not. If data governance is viewed as being an IT function, even by the business folks, then it's more likely that it's going to fail and you're going to have a harder time to engage people from the business function so typically it's better to fall under a chief operating officer, a chief administrative officer, a chief data officer, if you would have one or a chief financial officer. And that's how I would answer that differently if the question had been asked around data governance versus data management. Makes sense. So, how do you pitch the ROI of this. Well, if, like I said, why does why should you care, because if you do have two different functions within your organization, you should be investigating how they are complimentary and how they are different and how they can work together, and all those types of things that's what you mean by the ROI of this, you know, it's a different question again if you're asking about how do we demonstrate ROI from data management. And how do we demonstrate ROI from data governance. Yeah, again, I would answer those I'm not going to try to answer those questions right here right now unless it's another question from somebody else but the ROI of knowing how data management and data governance overlap really can work together. It's an efficiency and an effective thing, effective this thing within organizations that the organization is going to become much more efficient and effective if you have two different functions that are working together. So the ROI on that is do you want ROI from either of the two functions. Well, you're going to multiply that if you they you have them work together. All these questions Shannon that have alternative alternative questions. It's true well it's you know it's it's such an in depth topic that's such a broad topic there's there's a lot of things to dive into right. Um, yeah, you know we get that question a lot you know how do you, you know, get executive buy in and that kind of thing so. Um, yeah, because Bob, you know, can data management report to data governance office to have more working alignment. Great question. Can data management report to data governance. I'll tell you that right off the top of my head. Boy, don't hold me to this and I would say no, I would say data management shouldn't that. I guess people have asked me the question of which comes first data management or data governance, which one is the umbrella over the other. It's interesting when you look at the data framework. They call it that's a data management framework but they include data governance smack in the middle of the framework. So data governance touches every one of those disciplines at least that's the way I view the data management framework. You know, it really depends in the organization, I would say that their peers, their partners, the people that are running data management should be peers with the people that are running data governance. They should work together instead of trying to determine which one falls under the other. You know what the the true answer to the question is, you know, when I get asked should data governance reside where should data governance reside in it or in the business. I answer the question, yes, it has to reside somewhere. So within your organization right now, if data management reports to data governance or data governance reports to data management, be thankful that you have these functions, and that you have them within your organization. Is it ultimately the right place. That really depends on your organization and how well they are able to work together. So, what is your opinion when both roles data management data governance are the person doing both jobs. So there's some so there's only one. There's only one function and it is data management slash data governance. Well, they're right there you've got the building partnership don't you they're going to put part of the same part of the organization. They, you know what you've got to be where you got to put on this is the way I'll answer the question you got to put on your data management hat you've got to put on your data governance hat. So, is what you're focusing on more operational and technical and nature, or is what you're focusing on more behavioral, or if there's a blend, then you might look silly but you might be wearing two hats at one time. So we need to take in the perspective of both of these things. So, if they're if you're doing both of these recognize that some of the activities are more data management focus, and some of the activities are more data governance focus. I'm assuming that this is a common issue in organizations because not every organization is sizable enough to have multiple functions. So if you're playing both roles, at least make certain that when you're doing your data management activities that you're applying the right level of governance, or when you're doing the data governance activities, you're applying the right level of data management. I think that's probably the best way to answer that question. If you have any other questions coming in and along the time that we've got here so what suggestions or tips would you have for an organization that combines both of them, or you would just kind of we kind of went over that a little bit already so I'll throw something in about that so you know if you've already combined them again be thankful that you've got them somewhere in your organization and that somebody at least sees the importance of data management versus data governance. There's an opportunity there to share with people within your organization, how the functions of that group I don't know if it's called data management, or called data governance, how the, the functions of that group, and the things that they're doing on a daily basis are, you know, apply or adding value are leading to business outcomes for people. So yeah it is kind of the same question but a little bit different. Thank you. So in large organizations you may need to manage very different types of data in different functions does it make sense to have data management data governance of us we're still going in the reporting to the same structure of a function so it's a little bit. It's a little variation of the same question, you know, under the same structure of a function as long as reporting to the same executive. That's what I think it might be best for organizations if they both reported up into the same executive. It doesn't mean that it has to be that way it just for simplicity sake, and for education sake and for training sake and you know it, you know having it in an executive might make more sense but again if it's already set up and these functions reside under different people data governance reports up under the chief risk officer and data management reports up under the CIO. Well then we need to have that partnership at that level at the C level of the organization and work to develop a partnership between the disciplines themselves. Ideally, having them go through the same person might be a benefit to the organization. It might present its own challenges to because again now you'll have groups within the same part of the organization that are battling for the same budget. Right and well, do we give the budget to data management do we give the budget to data governance, it can cause benefits and it can cause challenges. So, but I like the idea of, you know, if it's possible. Have them report together. Very nice. So we've got about three minutes. Yeah, it is yeah and I'm kind of three minutes left and back to kind of the ROI question so labor time money economic cost of doing this versus the return so why why should they do it. Why shouldn't they do it. Why should know why do they do it. Well I will tell you that first because I focus more on data governance than I focus on data management in my career. Data governance is not going in a lot of ways data governance does not cost nearly as much as data management, in terms of the technology and the, and the building in two operations. If you consider that data governance is all about it really I always say that data governance costs you the time that you put into it. Yeah, there might be some technology. There are some things you might need to make if you don't already have tools in your environment to leverage, but it's really data governance is mostly people's time and getting people to do the right thing and getting them to understand that when I use data, there's rules associated or when I define data, there's rules associated with how I look to see if that data has been already defined somewhere else, or how I define it this time or the same thing applies to producing data. So, I think that these functions, the, especially the ROI that's going to come from them. Execute and enforce authority over your data who's going to do that. If you don't deliver a comprehensive set of disciplines associated with the operational management of your data, who's going to do that. Yes, it costs money, but it's also a conscious decision not to invest that money in these disciplines. And the organizations that consciously make the decision not to invest in these disciplines. They find that it ends up costing them more money in the long run and that Shannon is another topic for another webinar. Well, Bob, that brings us to the top of the hour. Thank you so much for this great presentation and just to let the attendees know any questions we didn't get a chance to get to. I'll get those over to Bob so we can get those in the follow up email which will go out by end of day Monday also including links to the slides and links to the recording. Bob, thank you so much and thanks all of our attendees for being so engaged in everything we do. We just love it. Thank you. Hope you all have a great day. Thank you very much, Shannon. Thanks everybody. Thank you.