 Hello and welcome, my name is Shannon Kemp and I'm the Chief Digital Officer of 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 Sinner. Today, Bob will discuss the data stewardship method of data governance. 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 it to just the panelists, absolutely switch that to network with everyone. For questions, we'll be collecting them by the Q&A panel and to find the chat and the Q&A panels, you may click those icons found in the bottom of your screen to activate those features. And as always, we will send a follow-up email within the next two business days by end of day Monday for this webinar with links to the slides and links to the recording from anything else requested throughout the webinar. And Bob, you can share now. And now let me introduce to you our speaker for the series, Bob Sinner. Bob is the president and principal of KIK Consulting and Educational Services. And what's the publisher of the data administration newsletter, tdan.com, Bob specializes in non-invasive data governance, data stewardship, and metadata management solutions. And as you may have noticed, I said was because we've got an announcement, Bob. We do have an announcement and the announcement has been made all week and it's great to share this with this audience as well. I don't know. I know that we talk about the data administration newsletter tdan.com quite a bit and it's actually in my lengthy career, it's been one of my proudest accomplishments to have the publication for the last 26 plus years. But I'm also thinking that it's time to kind of turn over the reins to somebody else and let them run the daily operations and kind of own the data administration newsletter. And that perfect partner to do that with is dataversity. So the big announcement is not just mine, I think it's also a big announcement from dataversity as well. Dataversity will be the ones that will be responsible for the operations and they own the tdan.com website. And I'm really proud of that. And I'm going to continue to work with you and with dataversy and provide content and things like that. So I think that most of it will be seamless to people, but that's a big announcement. I'm so excited, Bob, and yeah, it is a big announcement. We're excited to be to, we've got some big shoes to fill, but we're excited to take on the challenge. Well, it's a little bit old. It was a little bit, it is a little bit older than 26 years. And my younger daughter is a little bit older than 26 years too. And I feel like I'm getting up a child. But no, I'm looking forward to it. I think it's going to be a good thing forever. I was going to joke and say it's older than me, but that's not true. I just wish it were. We won't go into that. OK, well, let's let's get started with the webinar. I'm really looking forward to this subject. This is a subject that kind of I touch on almost within every subject within every webinar that I do. There's always a data stewardship angle or a it's part of the subject matter. And so one of the things that you might notice that's a little bit different about I call it the data stewardship method. I call it the noninvasive data governance approach. When I talk about noninvasive data governance, an approach is more of a philosophy. And I compare to the noninvasive approach to the command and control and the traditional approach, the data stewardship method is really more of a tactic. And I think you'll see that in the things I'm going to talk about in today's webinar, because it's going to talk to you about how to recognize who the stewards are, how to engage the stewards, how to get the stewards to work together and those types of things. So just want to take a quick second. You'll notice TNAN is not on this page anymore, but it will pop up from time to time for sure. And you can certainly continue to register for the webinars through TNAN.com as well. But I just came back from Enterprise Data World in Anaheim, and that was a phenomenal event. And I certainly recommend it to people in the future. I will also be speaking at the DGIQ East Conference in Washington, DC in early December. If you know about noninvasive data governance, you may or may not know about the second noninvasive data governance book called Noninvasive Data Governance Strikes Again. It was published in May of this year. So check it out. It's just lessons learned in perspective gains since implementing the, since I've been implementing the noninvasive approach for the last 10 to 12 years. And also there's online learning plans that are available through data diversity on noninvasive data governance, noninvasive metadata governance, business glossaries, dictionaries, catalogs, and there's also going to be a new one that you will be seeing sometime in the hopefully near future. KIK Consulting is my business. That is the home of noninvasive data governance. So if you want to learn more, please go there. And in my spare time, I am also a faculty member at Carnegie Mellon University here in my hometown of Pittsburgh, Pennsylvania in their Chief Data Officer Certificate Program. So what are we going to talk about today? And like I said, I really love this subject because data stewards, I mean, you're not going to have a noninvasive data governance program and you're not going to have a traditional data governance program if you don't recognize who your stewards are or activate your stewards and get them as part of the program. So I think that these subjects of where data stewards kind of fit into an organization's customized operating model, specifically designed for what your organization's program is going to look like. The stewards play a big role in that. And I'm going to talk about that a little bit. We'll talk about ways to determine who your stewards are. And you notice and you've probably heard me say before that everybody is a data steward. So potentially everybody in your organization is a data steward. We need to figure out how to help them to recognize themselves as data stewards. So we're going to talk about ways to determine who your stewards are, how to get the stewards to interact with each other, with the business, with the technology areas, leveraging stewards to become data literate. It was a big subject at the conference this week in Anaheim. Data literacy was mentioned in almost every one of the sessions and then engaging the students, the data stewards to improve the status quo. So let's kind of jump into these subjects and hopefully you'll see how it's really a method to determine who your stewards are and to get them activated. I always start my webinars by sharing my definitions of data governance and data stewardship and they're a little bit different than what you'll hear from most people in the industry. The data governance definition is worded very strongly, the execution and enforcement of authority. I say no matter what approach you take to data governance, at the end of the day, you need to execute and enforce authority in order to change the status quo, in order to improve the quality, improve the risk management over your data. And then my definition of data stewardship is that it's really the formalization of accountability for what people do with data. So if people define data and they're help formally accountable for how they define data or how they produce or how they use data, it's not something that people need to opt into or opt out of. You're a data steward, if you are a person that has a relationship to the data that you're being held formally accountable for. So I think those are really important because we're talking about the data stewardship method of data governance. So I wanted to just start with some context as to how I define those two terms. So the first thing we're going to talk about is where do data stewards fit into an operating model, into your set of roles and responsibilities for data governance. We need to realize that there's more than one level of steward. And so I will share with you where they fit into the operating model. I have several rules, rules for becoming a data steward. I talk all the time about how everybody is a data steward, because most people define and or produce and or use data as part of their job. And if they're being held accountable, well, that's going to give you more stewards than just assigning a few people to be data stewards. And then we're going to talk about formalizing accountability versus assigning a people accountability. Chances are there's already some accountability there. It might not be formal. It's a lot better accepted than being assigned something of being assigned what feels like new accountability. So this is an example of an operating model. And we've given webinars, diversity as part of this series have had specific webinars that dissected this operating model. We're not going to do that today, but it's really important to consider the idea that there's different levels within the organization that need to be represented within the your roles and responsibilities for data governance. We know there's an executive level. We know there's a strategic level. Then I'm going to talk about the tactical and the operational level. Then there's other moving parts as well. There's the administration of the program, I.T. and what I.T.'s role is in project management and those types of things and then the development of working teams. You know, like I said, I could talk the whole session on that, but we're going to focus on these two bottom layers first. And so there's operational data stewards, at least typically. That's how I find it in organizations that are doing things with data within their specific business function. And if they're held accountable for what they're doing with the data within their business functions, they're stewards. They may not recognize themselves as stewards, but they're stewards. They're operational stewards because the things that they're concerned most about are those things that pertain to their specific business function. And then there's another level of stewards where we stop just looking at data or they stop just looking at data specifically within their business function. You can see in the middle of the operating model that I call that the tactical layer. I think it's pretty tactical, but it's really cross business function. So we've got these people day to day that are defining, producing and using data. And then we have people within the organization that might be subject matter experts. I've referred to them as data domain stewards. If you see the escalation arrow along the right hand side of the pyramid, if we can't solve a problem, or if a problem is larger than just within a specific business function, we need to know who those domain stewards are, those subject matter experts stewards are. And that's who we're going to take the issues to for the escalation. So just to kind of restate that, you know, if you've got the operational stewards at the bottom of the pyramid that I use and I talk about defining, producing and using is really being the only three actions people can take with data. So you've got people that are doing those actions, again, holding them accountable for what they do, they become stewards. They can't really say, no, I'm not a domain steward or a subject matter expert or a definer or a user of data when they actually are. And then there's the tactical level. Like I said, data domain stewards, some organizations have said data subject matter experts. So let's call them the data sneeze. But then there's also business process stewards and something that's really kind of occurred to me fairly recently is the concept of the business data steward and the technical data stewards. And you've got business process stewards as I listed before. I had a client recently that decided that they were just going to call the people business stewards instead of even business data stewards because they were the people that were knowledgeable about both the process and the data, and they were truly the stewards of the business. So again, just to keep in mind, there are more than one level of layer of stewards within the organization. There's typically operational and then there's more tactical and subject matter expert stewards within the organization. So I have, like I said before, I have a bunch of rules associated with becoming a data steward. Maybe I have too many rules, but I'm going to go through them real quickly with you and just describe to you why I stated these are the rules for becoming a data steward. So first of all, I said already that basically anybody or everybody in the organization can be a data steward if they're being held accountable for what they're doing with the data. And that's why I say data stewardship describes a relationship and it's not typically a position, although there's a lot of organizations that tend to hire people in even to be data stewards. Typically a data steward, a person that becomes a data steward has been hired into your organization to do another job. And that other job has them defining, producing and using data. And therefore they become data stewards. You know, we don't have to go tag everybody. If everybody in the organization is a data steward, we don't need to tag them all on the shoulder and give them the title of data steward. And typically their job is their job. Their job is not data per se. So data steward doesn't really need to be told how to do their job. But in some ways, I guess they do when it pertains to the data itself. So I don't really like the idea of public or industry data steward certification. I don't I put here it's a load of bunk, but it's I don't think it's necessarily valuable because you're not teaching data stewards how to do their job. But you may be able to train them a little bit in how they can work better with the data, what the rules are with the data, how they can find the data they need. Another rule is more than one data steward exists for each type of data. There might be five people that are defining the same data, hopefully the same way and maybe different ways. There's certainly going to be more users of the data than just one person who would be a steward. So more than one data steward exists for each data type and data steward training in general should focus on formalizing accountability. So that kind of goes with the idea of being noninvasive. We don't want to hand people more work or at least we don't want them to get the impression that we're handing them more work than they they presently have. So again, these are rules for becoming a data steward. There's articles about this on the TDAN.com website. If you're interested in learning more, I kind of go into each of these and describe them a little bit more. So if you've attended the webinar series before, I know you've heard me say everybody is a data steward. And then I say you should get over it. Again, another TDAN article that I wrote, everybody is a data steward. Get over it. I only mean the words get over it in the kindest and the most polite, politest sense. I'm not. I don't want to sound rude, but organizations need to get past the idea that there's just certain people that we're going to assign to be data stores. We need, if we're going to cover the entire organization, we need to keep in mind that potentially everybody in the organization who has a relationship to data that's being held accountable is a data steward. And if you think that you can cover the entire organization by just handpicking who your data stewards are, I think you're going to find yourself in a bit of a bind because in order to truly manage risk within your organization, just using one example, people need to know the rules associated with how they can share data. And if there's intellectual property or there's personal information, how that information can be shared or can't be shared, every one of those people that use that data need to protect it and they're being held accountable for it, they're data stewards, basically. So there's a difference also between saying, you know what, in most senses, you're right, you're already a data steward because you're using sensitive information and that sensitive information needs to be protected. So if you start with the premise of just formalizing existing levels of accountability versus assigning additional levels of accountability, think about it in terms of being on the receiving end of that accountability. Which would you rather have? Would you have rather be assigned something which feels new or would you like to formalize based on what your actions are already with data? So being assigned anything basically feels over and above what you're presently doing. And if you start with a premise that people are already accountable, I think in most cases, people that use information that's sensitive are made aware that the data is classified a certain way and that there's handling rules associated with it. So start with that premise of they're already accountable but help to formalize that and make certain that the things that they're doing follow the rules that need to be followed for that data. And accountability is basically based on the actions people take with data. So I always say we just need to recognize people for what they do rather than assigning them more things to do. You know, so people are the stewards are basically people within the organization that are being held accountable for what they're doing with data, but they can use help. They need to be directed, guided, assisted in how they steward data. And oftentimes that's going to come from inside the organization rather than coming from outside the organization. So the next subject that we really wanted to address in terms of the stewardship method of data governance is that we need to figure out how to determine who our data stewards are. And the first thing we need to recognize really is that there are those three approaches to data governance. And this is going to have potentially the biggest impact on your stewardship and your governance success within your organization. How you go about determining who your stewards are will have a big impact on whether or not you're going to be successful. There's really three ways to be able to get a steward to be a data steward. They can be assigned, which I said is sounds very command and control. It's over and above when I'm assigned anything. I know it feels that way. Just identifying people as data stewards, recognizing versus recognizing people for what they do. There's a positive connotation that comes with recognizing somebody for some actions that they're already taken, even if those actions are with a data. So basically three approaches to data governance, the command and control. That's the one where we're assigning people to be data stewards. Typically, there's only a limited finite number of people who are data stewards versus the idea that potentially everybody is a data steward. And then there's the traditional approach to data governance, which I liken to the movie Field of Dreams, which one of the key lines in that movie was if you build it they will come, that's how people oftentimes build data governance programs. They build it and they hope people are going to gravitate towards the program. We're going to identify people as stewards. It's not as invasive as assigning people to be data stewards, but it also might not be as effective as well. And then the third approach is the noninvasive approach that I talk about quite a bit, which is we're going to recognize people as stewards for what they do. But if you go back to the definitions that I shared earlier in the webinar, the outcome, no matter which approach you take, whether it's command and control or traditional or noninvasive, you need to be able to execute and enforce authority over data. And there's rules that need to be followed when the government comes to you with some regulations. They're not asking you to do it. You need to do it. You need to execute and enforce authority over the data to assure the government that you're following their regulations, just as one example. And so what we're going to do is we're going to formalize accountability for how people define, produce and use data. And just to kind of rub the point back in is I really believe that if you it may add some complexity to your program, but you need to consider that potentially everybody is a data steward. Now, you're not going to deal with each of them individually, but certainly in groups or in categories within your organization. That would be something that you would might want to consider if you believe what I'm saying is that everybody is a data steward. We need to get over that. And what I mentioned before, it really is one of the biggest determinations in your organization to and it will have the biggest impact on whether your programs of stewardship and governance are successful. How are people going to accept being assigned as data stewards? How are they going to accept it? So maybe they won't want to be assigned or they might ask questions of, well, I'm already busy one hundred and fifty percent of the time and you're assigning me to be a data steward. What does that mean? Does that mean that I'm going to now be busy two hundred percent of the time or or the the identified? So how will people accept being just identified? OK, you're a data steward. We've identified you versus recognized. And the idea of recognized, again, is they're doing something that we're going to help them to do better for the organization. Another thing that people think about when you're determining who your stewards are is how people will define the role of data owner. We talked about this a lot at at EWW this week, that the term data owner is so so used within organizations. And do we need to change their language from owner to steward? There's a lot of understanding presently in organizations about what it means to be a data owner. But think about that as well. It's going to have a big impact if you call people data owners, help them to understand that truly the organization owns the data. They're not there. They're truly taking care of the data for the organization. If you look in the dictionary, that's what a definition of a steward is somebody who takes care of something for somebody else. So you got to think about how stewards are going to represent the entire organization. How are people going to respond to being told you already do this? You know, maybe it's something that's going to be less threatening to them, less invasive to the things that they do. That's why I like the idea of recognizing instead of assigning or identifying people as data stewards. And most organizations, they think of data stewardship. They think of it as being over and above what people are presently doing. So let's just go through each of these real quickly, assigning people to be data stewards. In most organizations, I know that I work with these days, people are being asked to do more with less resources. So and because of that, people are busier. They're they're spending much more time. They are having a hard time getting all their work done and those types of things. So people are already being asked to do more with less in their jobs. And if you assign them to be data stewards, think about put yourself in their shoes. Think about how they're going to feel about that. And, you know, these new positions, you know, if you're going to assign people to be data stewards and it's actually going to be a position within your organization. Well, not too many organizations are creating new positions right now. It's there's more of a trend to the to the to the reverse of that, where positions are being eliminated. And people are having difficulties finding people to fill positions, people don't want more work. You know, if you assign people to be data stewards, you might be setting yourself up for disaster or failure, at least. Because again, people don't want to be assigned. And now we're going to talk about the difference between this and identifying stewards and then recognizing, again, I referred to the the traditional approach as being the field of dreams and that you hope people are going to navigate toward navigate towards that role of the steward. It's not as invasive as being assigned, but it still feels like it's over and above. And a lot of stewards say, well, I'll be a data steward as time permits me to be a data steward. Well, that's not really good enough because if you're using sensitive information, again, just as an example, in your job and you use it every day, it's not as time permits. It's you need to know that there are rules that need to be held that you're held accountable for following. So identifying people as stewards also might not result in what you're looking for within your organization. And so that's why I talk a lot from the noninvasive approach about recognizing people as data stewards, recognize who's already defining data as part of their job. Who's creating data warehouse? Who's creating the integration strategies when you're upgrading your ERP system or something like that? People are defining new data or putting better definition to data all the time. So if we can formalize and help those people to do it in a way that's going to be beneficial to the organization, we're not going to be giving them things that they don't already have. We're basically formalizing and helping them to do a better job of already defining the data. If they're producing them, again, I don't want to go through each of these, you know, but if they're producing or using data, the same thing holds true. If they're already producing data, we can help them to produce data better. If they're already using data, we can help people to use the data better. And then my suggestion is if you go back and look at the recording of this webinar, refer to those rules for becoming a data steward. People are already doing this stuff. If we can help them to do it better, it's not going to be as threatening to them. It's going to be more noninvasive in that sense. And focus on the positives. Focus on the ideas of there's a positive nature that comes from being recognized for something. So, again, those are really the three. You can assign people, you can identify, you can recognize. If there's other ways to go about it, share them in the chat and see what other people in the session are saying. But those are really the basic three that I've seen and I've witnessed in my career. So now let's talk about how data stewards need to interact. And I shared the operating model when it talked about there's operational level stewards, tactical level stewards, and we need to focus on what the things are. How do those people interact? What are they doing? What are their opportunities to interact with other data stewards for the benefit of the organization? I'm going to talk about that in terms of tactical interactions as well. The business interaction. So data stewards, oftentimes, at least at the beginning for organizations, can be fairly technical people. Getting them to work with the business might need to have some education and some literacy on what are the best ways to tell stories about data and with data within the organization. And then there's the technical interactions. How the stewards that you're recognizing or assigning into the role, how they interact is really key to your program success. So let's go through each of these. From an operational interaction, oftentimes these describe some of the things that people in their job are doing day in, day out. They're profiling data or they're monitoring data or they're determining what the quality is of the data and finding ways to improve the quality of data. They're collaborating or at least they're working on documentation. At least they should be. And if you want to engage them, get them to work together. Don't give the delivery of a data dictionary to one person, make it a team effort. Get the people who define the data, again, data stewards, get them to collaborate and work together. Some of the operational interactions also include getting together to define issues, to resolve issues, to escalate issues to the appropriate person within the organization. Other operational interactions are those things that I mentioned, data quality improvement initiatives. Oftentimes they're very homegrown within an organization. They recognize that some of the data is not of the level of quality there needs to be. So the stewards at the operational level primarily interact to help to resolve those data quality problems. And then data access and permissioning. And these are people that are operational within the business units that are requesting access to data and needing to be granted permission to access the data. These are basically how the operational stewards interact with people throughout the organization. Now let's bump it up a level within the operating model and talk about the tactical interactions. So oftentimes those tactical level, if you remember what I talked about with the pyramid diagram, is they're looking at data across business units. And one of the things that I know you know is that, you know, what drives management nuts is that they ask a question and they get different answers. And it's all, the different answers are based on the different data and different understanding. And so getting the people at that tactical level, that subject matter level to work together, to interact, to create additional education and awareness around data, to collaborate on data definitions and standards. As I mentioned before, if you're having operational people focusing on data dictionaries, more often you're gonna have the subject matter experts focusing on the business glossary and the definitions of the terms within the organization. Other tactical interactions include supporting the data quality initiatives, promoting data privacy and security, facilitating communication and feedback within the organization. Again, these are the subject matter experts. If we create communities of domain stewards or even create communities around just domains of data, that's playing more into the tactical interactions of the stewards. So again, just another way to get data stewards to interact at all the different levels of the organization. And then let's talk about things in terms of business interactions and technical interactions. If a data steward is in the business, they oftentimes need help communicating well with the technical people. And the same thing holds true in reverse. Somebody in the technical environment, I know when I got started, I was a programmer and I needed to learn how to relate to the business, learn how to understand the business and those types of things. So the business interactions are, understanding what the business needs are and the objectives are, aligning the things that they're doing around the management of data in general more than even just the stewardship or the governance of data, but aligning the data management activities with the business goals of the organization. Other business interactions would include providing data insights and recommendations based on their knowledge of the data to the business folks to help them to see an improvement in the quality and the value of the data that they're using. Facilitating data access and collaboration. Again, stewards, if you can get the stewards to interact with people at the business level, if they're in the business, that's great, but getting them to interact with other people within the business is always a benefit. And then there's the technical interactions. Getting the business stewards to be able to work with the technology folks, get them to understand the landscape, actually collaborate on the architecture and the design, implementing the quality checks, all of these things that are very technical in nature, oftentimes organizations define these things as being more data management oriented than being data governance oriented. The data stewards, the business data stewards, the business people who are responsible, who are defining, producing and using data, they need to also be able to talk the tech language. There's gotta be collaboration between the technical folks and the business folks. It's an age old problem that still it needs to be addressed within many organizations. And then there's the interaction between these folks. Engaging in cross-functional collaboration, acting as advisors and educators for each other, all of these different activities, what we as data governance practitioners need to do is get people, activate the stewards. Recognize the stewards, do all the things that I talked about in the method a little bit earlier in the webinar, but we need to get them active. If they are active and they don't even see it as being different from what their normal job is, you've won the data governance game when the data stewards actually are just regular people within your organization that are now knowledgeable about how their relationship to the data has an impact on the organization. All right, so let's talk about that subject that I said was so popular this week at Enterprise Data World about data literacy. So first we're gonna talk about data literacy and why it's important. One of the things that I'm hearing talked about more and more when it comes to data literacy is the difference between having a data literate organization and having individuals within the organization that are data literate. And there's actually differences in the definitions of what those things are. They're all pushing in the same direction, but I wanna just kind of point out what some of those differences are and then talk about the relationship between data literacy and stewardship and the relationship between data literacy and data governance. So everybody has a definition of data literacy. Everybody has a definition of data governance. This is the definition that I use for data literacy. And it's just a little bit different than you'll see from a lot of people. And I say the ability to understand, interpret and communicate about and with data effectively. So it's not just understanding, interpreting, communicating with data effectively. It's actually having the ability to be able to communicate about the data. And when I talk about about the data, what I mean is articulating the effort that's gonna be required to improve these things that we're referring to as data management and data governance. We've got to talk about, there's a poor quality problem. We need to talk about what's gonna be necessary in order to resolve that problem. And so talking about the data, that's important, at least to me, that's an important piece of data literacy. And then the one that most people talk about is being able to communicate with the data. And again, recognizing the power of the data itself and how you can use that data to make decisions and share results. So data literacy is basically something that's really important to the data stewards. If the data stewards are engaged and they're looking for ways to improve a lot of different things. Again, don't wanna go through each of these things, but if you can get to the point where the stewards recognize themselves as being data stewards, again, not changing their titles, but they're stewards of the data based on the fact that they work with data and they need to know the rules. These are the things that we can, if we can convince them that these are the things that we're trying to help to improve in what they do, it's going to go a great way towards leveraging your stewards in your organization to become more data literate. So that's just a kind of compare and contrast individual data literacy with organizational data literacy. And it makes sense that this pertains to the specific individuals within an organization. And so different parts of the organization can focus on getting their staff better skilled. So focus on building the data skills of employees or people who are working in one part of the organization, use it to evaluate job performance. And if they become more literate and they can work with the data and they can talk about the data and with the data, if they find ways that you can measure that within the organization, it basically makes them better decision makers in their role. So there is an individual level of data literacy, but then there's also more of an organizational data literacy level as well. And that obviously requires more attention. It requires more of an effort if we want to put together a program that's gonna help to increase the level of literacy within the entire organization. So this extends beyond the individual. It really encompasses the collective organization and helping them to talk about data, helping them to talk with data and those types of things. It really has a broader impact on the entire organization. There are a lot of organizations that start smaller and start in specific groups and improve their literacy and then go on to the next group and improve their literacy. And then there's organizations that are taking an enterprise approach to data literacy. It requires a communication plan. It requires working with people who are skilled in getting the appropriate messaging out to people within the organization. So again, there's different, I don't know if you view them the same or differently, but I think it's worth calling out that we can increase the data literacy of both individuals and of the organization. There are similar efforts, but one is tremendously more involved and that is trying to get the entire organization to become data literate. So let's talk a minute about data literacy and data stewardship. One of the things that you can do to help stewards to become more data literate is to invest in training and educational programs for these folks. Task these individuals who are now recognized as data stewards with certain things that are gonna add value to the organization. Some of those things might be creating clear policies and creating clear documentation around the data. Now, basically stewards can play a pivotal role, a regular everyday role in improving and maintaining the quality of the data and monitoring it, help them to understand how their experience doing those things can play into how they most effectively use the data, how they most effectively define the data and produce the data as well. So just keep in mind that there's a relationship between data literacy and data stewardship, just like there's a relationship between data literacy and data governance. I could tell you many organizations that their data governance programs have had the responsibility for data literacy. Sometimes that works out. I know just implementing a formal data governance program itself takes a lot of work. Oftentimes it may be partners within the organization. If you recall the operating model, one of the sets of roles on the left hand side were data governance partners. Partner with the communication folks. Establish and like I said here, establish and maintain clear definitions of data, clear onboarding of your executives and your strategic level and all of your stewards within your organization. Data literacy is, it is not going away. It is going to be part of data governance at least related to data governance within most organizations moving forward. And so the last thing that I wanna talk to you about is engaging data stewards to improve the status quo. I think most people understand what the status quo is but I asked my app over here just to describe what the status quo means. And the status quo means the way things are being done presently. That's the status quo. So we wanna engage the stewards to improve the definition of the data, the production of the data. We wanna engage stewards in the escalation and the decision making around the data when it's appropriate, especially the subject matter experts. And it basically boils down to this is the stewardship method of data governance. Again, it's a tactic to engage stewards and get them working, getting them working in the positive direction for your data governance program. So I just wanna have a couple of more slides left. I wanna talk about data definition stewards. If we recognize that there are people in the organization that are defining data and they're using what I've referred to in the past as cheeseburger definitions. They're not really putting good business definition to the data. So what's a cheeseburger definition? It's a burger with cheese. What's a student account number? It's an account number for a student. It doesn't tell us much more than just the name of the field itself. But if we can engage stewards and help them to improve on the existing levels of definitions we have within our organization, we're gonna improve clarity and consistency. There's gonna be a higher level of data quality assurance. The data integration efforts, especially if the data is well-defined and the ability to interoperate between systems is going to improve as well. Based on a cheeseburger definition versus based on a valid, well-described definition of the data, it's going to improve the lightliness that you're gonna be successful or successful more quickly with your data integration and interoperability efforts within the organization. And compliance and data governance, again, these are ways that you can engage the data stewards in making certain that they know the rules, that they're following the rules, that they're sharing the rules. So we can help them, we can engage with them by helping them to understand compliance and data governance better and then getting them involved in the documentation and the cataloging of the data. Again, one of the outcomes of data governance programs that have been around for a while is that they have improved data documentation. And I even mentioned this in a session at EW this week that data documentation is another, just another term I use for metadata. If you, the metadata will not govern itself, I've said that before too, we need to engage data definition stewards in improving the data documentation and cataloging the data. Because I recognize that most data governance teams just don't have people sitting around looking for things to do if we can engage our stewards to improve the status quo by doing these things, it's going to be a great move forward for our program. The data production stewards, you know, they get them worried. And those again, those are just people that are producing data as part of their job, but they're also being held accountable for how they're producing the data. So get them involved, engage them in the quality control and focusing on making certain that the data is timely and that it's following standards. All of these things are necessary. Again, just another way since I've broken them into definition production and usage stewards, these are ways to engage these different types of stewards to change things that aren't going to change by themselves. And that's what I really mean by improving the status quo. This is the way things are. This is status quo, basically. If we want that to improve, we need to take action in order to get that to improve. And then last is the data usage stewards. So in surely adherence to the policies, you know, people who use the data, in most cases, they're probably already accountable somehow, some way for how they're using the data. But if they don't know the rules and they haven't been described to people to expect them to follow rules that they are not well versed in, it's a big risk for organizations. So we need to make certain that we're helping these people that use the data, we're engaging with them so that they protect the sensitive data they identify, know how to identify and to rectify data quality issues. We need, that's part of the data stewardship method of data governance is to engage your data usage stewards. That's actually where many organizations start when it comes to risk management and compliance and regulatory privacy, protection, data protection, those types of things is where I see a lot of organizations are focusing their data governance programs. You've got to engage your data usage stewards in order to be successful in that. If you engage your stewards in escalation, they can make certain the problems are documented, they can escalate issues to the appropriate people, they can do all these things, assess and mitigate risk. We need to get the stewards engaged when they need to get engaged in the escalation. And typically if you recall again back to the operating model, going from the operating level to the operational level to the tactical level, you got to know who the right people are to get engaged and those are most likely going to be your tactical level data stewards. So engage your data stewards, the role of the data stewards in escalation. And again, that's going to be another way that you're going to be able to improve the status quo by leveraging the people in your steward positions. So the last slide that I have before I summarize this up is I'm thinking that I have a lot of sayings that I use like the data will not govern itself and everybody is a data steward. But I think that there's one that I'm leading to almost. I say data will not govern itself, metadata will govern itself, your program's not going to run itself. I say everybody's a data steward. But really data stewardship is all about the people within your organization. So maybe the new statement is data governance by the people for the people. I don't know if that's one's going to as catchy as everybody is a data steward or the data will not govern itself. But again, it's something that may result from following this method of recognizing and engaging your data stewards. So what have I been talking about? Well, we started out by talking about where stewards fit within your roles and responsibilities for your governance program. We talked about ways to determine who the people are and to record who those people are. So other people know who to go to when they have a question about the data. We talked about how data stewards interact at all the different levels, mostly the operational tactical, but there's business and technical interactions as well. We talked about leveraging data stewards to become data literate, and then basically engaging these people that we're recognizing into these roles to improve on the status quo. And I talked about different ways to improve on the status quo. And with that, Shannon, I think we're up to the point where maybe we can take some questions. Bob, thank you so much for another great presentation. And just a reminder and to answer the most commonly asked questions, I will send a follow-up email by end of day Monday for this webinar with links to the slides, links to the recording, along with anything else requested. And diving in here, Bob, we've got some great questions coming up. So on the subject of determining who the stewards are, how about the stewards accountable for enterprise definitions, enterprise business and data quality rules, approving enterprise logical models, et cetera. It seems to me that very few people naturally assume these enterprise-wide roles that span across the boundaries of their department. In this case, isn't it best to assign that role to willing, skilled and credible volunteers, grant them the appropriate enterprise-wide decision-making authority and recognize them for their work? That's a great question. This is a really good question. It's a long question. Well, I think what we... It's hard to answer that question the same for everybody, but we do need to involve the skilled people because they're gonna be the ones that are gonna be asking the right questions in order to be able to put the architecture together to model the data appropriately. I know back from the days that I was a data modeler, it was all about getting to know the business and being able to represent the business through the data model. You're not gonna ask the business to model their data. So I think they do need to be engaged. And in fact, again, trying to just... If you envision the operating model that I had shared, your partners, you could partner with those technical people and those people that know the architecture. So I say, you need to use those people. Yes, they should be involved. Are they the decision-makers as to what the outcome should look like? If they're doing that without working with the business, that doesn't make a lot of sense. So I think it's gonna be a partnership between those people that really have the skills and the knowledge to do those things that you mentioned in your question and the business people that know the data and use the data and define it and produce it every day. Well, that was a long answer for a long question. I love it, that's great. So how do we quote-a-quote formalize data stores without assigning them the responsibility? Well, you think about the folks down the hall from you who use sensitive data and do they know the rules associated with protecting that data for how to share that data? I mean, so you want to, you don't need to assign them, if you recognize that they're doing things that need to be controlled, excuse me, you can formalize it by helping them to know the rules and to make sure that they're following the rules. So you don't have, they don't have to be assigned to do something that they're already doing. They're already using sensitive data. They already are expected to follow the rules associated with protecting sensitive data. What data governance does is it helps, it formalizes that, it formalizes the fact that they know the rules that they're being expected to follow. Perfect, so Bob, just wondering if there are any examples or case studies of implementing noninvasive data governance in healthcare organizations? Oh, I don't know if there's ones that have been written up, but if somebody wants to talk to me about it, I don't focus specifically on healthcare, but I can talk to you about organizations that have taken, have built consortiums of people within their organization, basically stewards, tactical and operational stewards. I mean, there are case studies of organizations following the noninvasive approach. And the idea, again, of noninvasive, it's really very practical. It starts with the premise of you're already governing your data. And you know what, within healthcare institutions, there is already a lot of existing levels of accountability for data. So anybody who, in any healthcare organization or any, like I said, I don't know of any that have been documented, but I'd be glad to talk to the question asker about that. There's a lot of accountability already. Healthcare institutions like this idea because people are already very busy. And if we're gonna give them additional work, it's they push back. And that's almost any industry, but specifically within healthcare. Maybe I need to put together a book of case studies. Ooh, that would be awesome. I could present some of those at EDW, maybe. That would be amazing. I love that. I love that idea a lot. But you just finished publishing one, so why not start the next one? Okay. So, Bob, I love this next question, because we get this a lot, how to get funded, who pays for data governance and realistically who is willing to pay? And I wish, well, it's that guy over there. I'm pointing to, no. It's not the same answer for every organization. It has to be funded, but to be honest with you, in my experience, tool aside, but the tool and maybe consultant aside, data governance programs don't have to cost a lot of money. They, I mean, actually you need to have somebody to execute and run the program and administrator of the program. And that might cost some money, but it needs to, how does anything get done with it? In the organization without it being funded, find a chief sponsor or somebody who believes that there's improvements that can be made in the data, but tell them that we don't need to throw a lot of money at this because we are already governing. We're governing informally because it's informal, it's inefficient, ineffective. Don't go ask for a ton of money unless you really know what you want to use it for. And that might be to request a tool to request working with consultants or something like that to improve your efficiency in getting your program up and running. So in many organizations, I see it being the finance part of the organization and that's oftentimes the executive sponsor, but I've also seen it be the chief operating officer. And then if there's a chief data officer, it comes out from under their funding. So there's not a single answer, but again, this is a great opportunity in the chat for you to be able to put, choose your executive sponsor or people could share who they are because again, there's not a single answer. It really depends on your organization. Thank you. And we've got time for a few more questions here. We've got about six minutes left. So Bob, I often get asked what data governance policies we have. Can you share some examples of data governance policies that data stores are often expected to have processes for? Well, the thing is that they often do not fall under the categories of data governance policies. They're data policies. There's data protection policies, data privacy policies, data sharing policies, there's the operational data policies and those types of things. So the idea of having a data governance policy where I've seen organizations be effective in implementing data governance policies, the policies are more to stand up the program itself to find the different levels of requirements, the different levels of the organization that are gonna be impacted and how they're being impacted. All of those other policies that I talked about privacy and regulatory policy and those types of things, they're data governance policies, but you really need to recognize, well, if somebody's using data that falls under this policy, they should know about it because otherwise to think that they're gonna know what the policy is without ever being educated on it is not gonna work out well in most cases. So I'd say don't focus on the data governance policy and we've done webinars Shannon, I think in the past on data governance policies themselves and I'm not a huge fan of them. The fact is that there's a lot of other policies that aren't any policy is a governance policy is what I look at. You don't have to call it a data governance policy because then people are gonna point at data governance and say, oh, we're following this policy because data governance is telling us we have to. Well, no, maybe it's a data privacy policy or a data sharing policy that even without a data governance program, the policy would still be there and you should still be expected to follow it. Alrighty, so how difficult would it be then to implement data stewardship in an organization that has not historically formally dealt with data governance? Well, if you start with the premise, instead of going around assigning people to be data stewards, look around you, look and see who is making, go to your meeting, your next agile meeting and bringing together all the thought leaders or the business area leaders from different parts of the organization and look to see who are the people within the organization that know the data, that define the data, that produce the data, that use the data and start to document who they are and then incrementally go out to them and start working with them to get them to recognize that they're data stewards. So you don't formally have a data governance program but I will tell you this, that if you're company and I'm just gonna throw a number out here, your company's been around for 20 years, there's been some level of governance to get you to 20 years. The only problem is it's informal. So go look around you, that would be my best advice I think is just look around you and start recognizing those people and helping them to recognize themselves as stewards of the data. All right and a few more questions here. I'm just trying to sneak in just one more. We've got about three minutes. I would like to better understand your vision of data stewardship. Let's take for example, organizational department hierarchy. Do you consider defining the codes for departments, teams, the responsibility of data steward or the responsibility of the data owner or data curator? Well, I don't typically use the role owner or curator but when you're talking about codes, I'm assuming you're talking, that the question is based on reference data and those types of things. So values for a specific type. That's why I'm understanding codes to be. It actually should be all those people working together because you're gonna get good ideas from the curators and you're gonna get good ideas from the owners and you're gonna get reality from the stewards of themselves because they are the ones that are actively defining, producing and using the data or at least producing and using the data on a regular basis. So I would, again, I would start there and I think that's the way to build something like that out. Perfect, okay. And I'm gonna slip in one more question, rapid fire Bob. Okay. Healthcare data is defined by an international standard or see, it's actually a comment by HL7 org and an SI. So. And so there are standards in a lot of different industries. That's a great example of a standard in an industry. And if you want to be able to interact and interoperate with those, that people are gonna expect that you're following those standards. So those standards are not going to govern themselves either that it's gonna require people that are going to actually get involved in that. So it's a great comment. Look to your industry. I'm sure there's somebody in your organization that knows what the policies and the rules are associated with the data that your organization works with. Absolutely. Well, Bob, thank you so much for another great presentation and thanks to all of our attendees for being so engaged in everything that we do. I'm afraid that is all the time that we have scheduled for this webinar. I will get the remaining questions over to Bob and we'll get those answers included in the follow up email, which will go out by end of day Monday for this webinar with links to slides, links to the recording. Thanks Bob. There are more questions. There are more questions. I love it, always more questions. It's great. Yeah. Yeah, it's perfect. And again, Bob, we're so honored to be, to filling your shoes or attempting to fill your shoes in the publication of the data administration newsletter. I will be helping you along the way. So I'm looking forward to it. Thank you everybody. Appreciate it. Thank you. Have a great day. Bye.