 And here we go. Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Manager of Data Diversity. I hope everyone is staying well and safe out there and 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 be discussing the stewardship approach to 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. Just click the chat icon in the bottom middle of your screen for that feature. For questions, we will be collecting them via the Q&A in the bottom right hand corner of your screen. Or if you'd like to tweet, we encourage you to share our questions via Twitter using hashtag RWDG. And if you'd like to engage more with Bob and continue the conversations after the webinar, you can go to thedativersitycommunity at community.dativersity.net. As always, we will send a follow-up email within two business days containing links to the slides, the recording of the session, and additional information requested throughout the webinar. Now, let me introduce to you our speaker for this series, Bob Siner. Bob is the president and principal of KIK Consulting Educational Services and the publisher of the data administration newsletter, T-Dan.com. Bob has been a recipient of the DAMA Professional Award for demonstrable and significant contributions to the data management industry. He specializes in non-invasive data governance, data stewardship, and metadata management solutions. And with that, I will give the floor to Bob to get today's webinar started. Hello and welcome. Hi, Shannon. Hi, everybody. Good morning, good afternoon, good evening, depending on where you are in the world. I hope you're having a great day and I'm going to echo what Shannon said. I hope everybody's staying safe, staying healthy, and it's great to have you with us today. This is one of my favorite subjects. I love to talk about data stewards. I certainly have some opinions about how stewardship can work within organizations. And it really, as data stewardship lies at the core of developing and implementing a data governance program, I always say the data can't govern itself, the metadata can't govern itself. You need stewards to, in order to make that happen within your organization. So again, hope you're having a great day, everybody. I want to start out the presentation by just sharing a couple of things that I typically start the sessions with, a couple of ways that I'm involved. And as Shannon said, I love to be on the data diversity community. I'll go there after the session. And if you've got additional questions, please address them to me or to everybody there. I want to let you know about the real world data governance series. Obviously, you know about this webinar, but I do it on a monthly basis to third Thursday every month, right at this hour. And next month, I will be talking about data governance and policy management. I talk a lot about noninvasive data governance. And if you're interested in learning more about noninvasive data governance, you can certainly go and find a book by the same name. I call it the path of least resistance and greatest success. I will be speaking at a couple of data diversity events that are coming up shortly. One will be Enterprise Data World in Chicago in October. And I'll also be speaking at the data governance and information quality conference in Washington, D.C. in December. I provide a couple online learning plans through the Data Diversity Training Center as well. One on noninvasive data governance, another one on noninvasive metadata governance. As Shannon mentioned, I have been the publisher of the data administration newsletter now for more than 22 years. I guess it's like 23 years now. And so it's a free publication online. If you're not familiar with it, please go out and take a look at it. Like I said, if there's no cost, there's articles that are updated, columns, blogs, features that are updated all the time. In fact, it's always updated the day before my webinar. So it's updated twice a month. So please go take a look at it if you get a chance. And last but not least, KIK Consulting and Educational Services. KIK stands for Knowledge is King. So the focus of what I do with my clients and the people that I work with is knowledge transfer. And that's somewhat what I'm trying to do in the webinar today is transfer some knowledge to you. So you might perhaps look at data stewardship through an alternative like an alternative approach to the kind of data stewardship that a lot of people talk about. So very interested in hearing your feedback on that. The things that I'm going to share with you today are, first of all, we're going to talk about something that I say all the time, that everybody in the organization is a data steward. I'll talk a little bit about that, why I say that, why that's important, why that will actually provide the coverage of your organization that is really required in this digital age. I'll talk about the stewards and how they impact the complexity of your program. So how you define your stewards, you know, what is that? What's the impact that's going to have on your organization? We'll talk about leveraging people's existing data responsibility and formalizing it so that they really recognize themselves as being data stewards. I'll talk about engaging stewards based on those relationships to the data. And finally, I will talk about how to follow a stewardship approach to data governance. That's really the topic for today. Before I get started, I want to share with you a couple of definitions that I share a lot and especially the second definition that you see on the screen in front of you. That is very relevant for today's webinar. Well, they're both very relevant. But now I say that data governance is the execution and enforcement of authority over the management of data and data related assets. And the idea is that at the end of the day, no matter what approach you take to data governance, and I'll share a couple of different approaches to governance and stewardship with you in the webinar today. The end result needs to be the execution and enforcement of authority. You need to be able to make tough decisions when decisions need to be made. You need to be able to follow the rules and the legislation and regulations and you need to protect sensitive data and get people involved in improving the definition, the production and the usage of the data. So that's my definition of data governance. I know it's worded strongly, but it is what it is. And it certainly makes people sit forward in their chair and ask questions about, well, what do you mean by wording it that strongly? The definition that's really most important for today is data stewardship. And I talk about data stewardship as the formalization of accountability for over the management of data and data related assets. And when people want to know, you know, who are the data stewards? Well, I say the stewards can be anybody in the organization if they have a relationship to the data, meaning that if they define and or produce and or use data as part of their job and this is perhaps the most important part of it, if they're being held formally accountable for that relationship to the data, they're data stewards. They don't have to be called data stewards. They don't have to be put through data steward training. They don't need to, like I said, have the title of data steward. But they do need to recognize that if they're being held accountable for that relationship, they are a data steward. It's not something that people can opt in or opt out of. So I find that that definition of data stewardship being the formalization of accountability is really important, really relevant to today's conference. The my definition of noninvasive data governance, since I mentioned it earlier, earlier is the application of that formal accountability and behavior. And we're going to use noninvasive roles and responsibilities. I'll be speaking at Enterprise Data World about a complete set of data governance roles and responsibilities. And we're going to apply governance to existing and or new processes in the organization to make sure that we're defining, producing and using the data properly to assure whatever it is you're trying to assure with data governance, whether it's regulatory compliance, security, privacy, any of those things. Actually, the goal of being noninvasive is to be transparent, supportive and collaborative and noninvasive really describes how we're applying governance to the organization. So I'll talk a little bit about command and control approach or the traditional approach, what that means for data governance. And then we'll kind of compare and contrast that to the noninvasive approach today as it relates to the stewardship approach to data governance. So the first thing I want to jump into is why do I say that everybody in the organization is a data steward? So I want to explain that to you. And I'll even tell you that there's some people that have been quite combative and have really questioned how that can even possibly be true. But I'll talk about that in a minute as well. I actually say everybody's a data steward. It's the most logical way to look at data stewards. I'll talk about the differences between that's assigning, identifying and recognizing people as stewards. And again, the key words that I mentioned in the definition were that if we're going to hold people formally accountable for that relationship to the data, they're a data steward. They can't say, no, I'm not a data steward. They are a data steward because they're now being held formally accountable for what they do with the data. And the truth is that if you're going to do it this way, it's really the only way that you're going to cover the entire organization. So I've been known to say that everybody is a data steward. Get over it. I know that doesn't necessarily sound very nice or politically correct. But the fact is we need to start recognizing that potentially everybody in the organization is a data steward. So let's start by talking about how this is really the most logical way to look at data stewards and data stewardship. So the truth is, and I hear this from people all the time, well, people have day jobs, if you're going to make them a data steward, they're already busy 120 percent of the time, 150 percent of the time. They have day jobs. They're not called data stewards, at least that's not typically their title. And we need to recognize that. But the fact is a lot of what they're doing as part of their day jobs is defining, producing and using data. And if we recognize that and recognize which data they define, produce and use, then we can kind of build it into their jobs. We're not handing this to somebody as a brand new responsibility. It's actually part of their job. And the example that I use most often is if you use data and if you're being held formally accountable for using data, and certainly everybody in the organization has to be accountable for how they protect sensitive information. They're data stewards. They don't need to be called data stewards. They don't need that title. And as I said before, people can't opt out of being a data steward. If they use sensitive data, we're not going to. And I'm going to point to the left side of my room here. You guys on the left in this webinar, you're using sensitive data and we're going to hold you formally accountable. But you folks on the right, you're using the sensitive data. We're not going to hold you formally accountable. That's not going to fly within most organizations. So basically you're a data usage steward. If you're using data that's sensitive. If you're using data at all, we should supply those people with the the rules as to how to use the data, the classification of the data, the quality of the data. And my mind that basically anybody who uses data and that's being held accountable for that is a data steward. So we need to get past that fact. So data stewards don't necessarily need to be taught to be data stewards. And I'm going to provide with you my eight rules for what makes a data steward at the end of the session today. So I hope you'll hold on for that. And in my honest opinion, humble opinion, data steward certification is a load of bunk. And I'm not sure data stewards need to be told how to do their job, but maybe related to the data they need to be told a little bit about how to do their job, certainly be shared by the handling rules for data that's sensitive. I was doing a presentation on a boat in Sweden where somebody stopped me in the middle of a presentation and said to me, if everybody is a data steward, then nobody is a data steward. And I'm sorry, I just don't agree with that. In fact, I very much disagree with that statement. If you are using, producing, defying, producing or using data and you're being held formally accountable, you are a data steward. And we may not call you that, but you need to understand it. What we as data governance practitioners can do is share with people the proper way to define data. And I'll get into that in a little bit as well. You know, we don't want to use cheeseburger definitions and those types of things. I'll explain a little bit more of what I mean by that in a little bit here. But you know what, there's a big difference in how we go about recognizing or figuring out who the data stewards are in our organization. And so people use the term they assign people to be data stewards. They identify people as being data stewards. They recognize people as being data stewards. And actually, those three things, those three actions that we use to determine who our data stewards are, they align perfectly with the three approaches that I typically talk about when it comes to data governance. So there's the command and control approach where people are assigned as data stewards and they're told they're being assigned as data stewards. And the fact is that whenever you're assigned anything, it feels like it's over and above what you're already doing. The common is you will do this versus the traditional approach to data governance, which is I always kind of compare it to the movie The Field of Greens. If you build it, they will come or if you build it, he will come. And so we're going to build a data governance program and we're going to hope that people in the organization gravitate toward it. So instead of you will do this, it's you should do this. In a non-invasive approach to data governance, we're looking to formalize accountability. We're not necessarily looking to give people additional accountability. So the tagline there is you're already doing this. And if we can recognize what people are already doing with data, that's going to help them to recognize themselves as data stewards. And that's really key here is that we get people to recognize that they are stewards of the data if they have a relationship to the data. So those three approaches, command and control, traditional, non-invasive, that goes from most invasive to least invasive. And the idea of data governance, at least from the approach that I take, is that we will formalize what you are already doing. People need to recognize that if they use sensitive data, they're going to need to understand how to protect that data, how to use it properly and such. So there is a difference between the and there is a big meaning to the words that we use. And if we say that we're assigning somebody something, make sure that they recognize or that they understand that it's not really over and above what they're presently doing. They're already using the data, we're just going to help them. And so the key word, as I mentioned in my definition of what a steward is, is the term held formally accountable. Well, people are already informally accountable. That left side of the room versus the right side of the room thing that I just talked about, the right side of the room, you guys over there, guys and gals over there are formally or are accountable, maybe not formally. And if we can formalize that accountability, we're taking a great step forward to recognize that potentially everybody in the organization that defines, produces and uses data is a data steward. I had a client recently who decided that at that operational level of the roles and responsibilities, they were going to talk about it as being everybody in the organization. All staff are basically the data stewards. So so they're recognizing that again, anybody in the organization, if they're held formally accountable, can be a data steward or should be a data steward. And some organizations look to include this as part of people's job descriptions. And that's more invasive than less invasive, for sure. But really part of people's job descriptions is that they need to follow procedure. And if we're going to formalize that and get them to recognize themselves as stewards, that takes us a great way towards getting people to understand that they are stewards of the data and there are rules to be followed, a good friend of mine, Len Silverstone. Len Silverstone, he's been a guest on my webinars in the past. He came to me years ago and said, well, it's really not data governance. It's people governance. We're getting people to behave appropriately. So if you think about it again, that kind of comes back to the whole idea of the stewards. If we can get them to recognize that there is appropriate behavior for them and that could come to data quality and protection and all the things that we do data governance for, they are stewards of the data. And it's really people governance is what we're doing more than data governance. Now, we can evaluate people on how they perform. And as long as there's consequences in your organization, there are certainly consequences for people that are using data and using it incorrectly or not protecting it appropriately. So we're going to hold people formally accountable for what they do with the data. And I mentioned it earlier that this is really the only way that I can think of. Please share with me if you feel differently. But it's the only way that I can think of that. We're going to cover the entire organization. So it's difficult to assign the stewardship responsibility to everybody in the organization that has that relationship. It's better to recognize those people. Help them to recognize themselves as being data stewards. And if we're going to follow this traditional approach of if you build it, they will come. It's wishful thinking that people will all gravitate towards being data stewards. You know, we want them to recognize themselves as such. And we want to recognize them, which has a positive connotation to it, that they're being recognized for something that they do. And complete coverage requires basically that everybody is a data steward. Again, left side, right side of the room, we want to make sure that everybody that uses data that is sensitive and has a relationship to the data is a steward of the data. It is really the only way to have complete coverage of the organization. But at the same time, it also adds some complexities to how we plan for data stewardship within our data governance program. And some of the things that it really requires a lot of is that we're communicating effectively with people that we're socializing with them. Why data stewards in the organization? Why they are stewards and what it means to be a steward and how they have an impact on the rest of the organization. So it's really truly the way I see it. It's the only way to cover the entire organization is to make sure that people recognize themselves as data stewards and that we as the practitioners assist them in that level of knowledge. And so my last subject here under why everybody is a data steward, well, because they are and I always say that we need to get over it. So get over it and move on. Well, if we recognize and if we adopt that concept, we are truly getting people who are already defining, producing and using data as part of their job to recognize that they are stewards of the data. And as we move or as we're already in up to our knees, at least, maybe up to our shoulders in the digital era, it really requires that everybody in the organization is being healthfully accountable for the data. Complete coverage requires everybody. You know, what are the alternatives to have five data stewards, 10, 100? It really this whole thought of everybody being a data steward alters the way that a lot of people think about stewards. And but we need to make certain that we plan our program as such to do that massive communications, to do that massive socialization to people within the organization to help them to recognize that they are stewards. So the next subject is the stewards impact on the complexity of the program, which is just what I was just speaking about. Is there a right number of stewards in the organization that need to be that we need to have? Is it a dozen? Is it more than a dozen? Is it is it everybody? But is there really a right number of data stewards in the organization? So we'll talk about that. We'll talk about the count and complexity. How do we deal with all of these people? How do we hold the people accountable? And really, it's the appropriate approach for most organizations to take and think about it for the organizations that are global and have people all around the world, we need to do a good job of communicating to those people that pretty much everybody can be a data steward. Now, that doesn't mean that there aren't different levels of stewards within the organization. There are certainly subject matter experts. There are, I guess, some organizations call them chief data stewards. We want to recognize that there's different levels of stewards in the organization. So is there a specific count of data stewards that's appropriate or is perfect for your organization? The answer to that question is no. How many people are in your organization that define, produce, and or use data as part of their job? I had a CFO of one of the biggest banks in the United States ask me, how many data stewards do we need and how long do we need them for? And, you know, I knew him pretty well and I could kind of joke back to him. But I asked him, how long do you want to have quality data for? And he looked at me kind of winked and said, I get what you mean. OK, we always want to have data stewards. We always want to have data governance. It's not a project that is a beginning and end. It's something that has to be in place all the time in order for it to be successful. And as I mentioned before, there are different levels of data stewards. Typically, they're operational data stewards and tactical data stewards. Operational are people that are working within a specific business unit that define, produce and use data within their business unit. But then there's the next level where we start to look at the data across business units, across divisions and lines of business. And those are more tactical stewards. I oftentimes refer to those people as data domain stewards. And so we need to recognize again as such and I'm not going to go into detail on this in this webinar, but there's different levels of stewards. There are people that have that cross business unit responsibility for the data, and that's not easy to find. Maybe you already have subject matter experts, but those folks that are making decisions for data across the organization, they're tactical versus the operational stewards. And as I mentioned before, everybody that uses sensitive data must protect it. So again, that kind of goes back to anybody that there's a lot of people in your organization potentially that use customer information, that have access to PII or personal health information or intellectual property. Even any of the data that you classify as being sensitive, anybody who uses that data needs to understand how to use it. If we are going to go with the idea that everybody is a data steward. This is the way to cover the entire organization. So more stewards, the more stewards we have. And again, potentially everybody, it requires effective planning. It requires effective communication. It requires additional time. So if you're looking to staff your office or you only have one person and it's part time who's running your data governance program, it's going to be very difficult for that one person to engage with everybody across the organization, especially if you've got people at many locations and it just makes certain that you have the appropriate resources to communicate effectively with people across the organization. So basically having more stewards requires more time. And we're not going to like flip a switch and all of a sudden have data governance and data stewardship turned on for the entire organization. We need to do this incrementally. So the incremental development of your program and the delivery is a key. You may define your your roles and responsibilities, but you don't know if they're working for you until you get to the point where you actually start using them in a proof of concept or a pilot situation. So it's great to have them on paper. But then again, you don't know if that's going to work very well for you and what the impact it's going to have on planning and delivery until you actually start to deliver this to the organization. So how do we deal with all these people in the organization that are data stewards? Well, first thing we need to do is we need to sell it as being appropriate for our organization and necessary. People need to understand that. And I'm talking about the people and all the people in the senior leadership of your organization specifically, they need to support, sponsor and understand this, they need to understand that this is really the appropriate way. Ask them if the right side of the room that uses sensitive data doesn't have to protect the data and they'll laugh at you. I mean, the fact is that there are the people are data stewards, no matter what we call them, no matter how they're titled, they're data stewards. So performing or providing forums to engage the masses become really important as well. The data diversity community is an excellent place for people to go to engage with other people that are trying to solve this same type of problem. I'm not saying that you have to create a data diversity community within your organization, but create centers of excellence, centers of interest around certain subject matters, get people to chime in, get people to participate as sharing ideas as to what's good and what's working for them, what's not working for them, where there are opportunities that we can address through data governance and data stewardship. And another way to deal with all the data stewards is to provide that effective face for data governance and stewardship. And what I mean by that is providing a website or providing a place that people can go to become educated. So if it's an internet site or a SharePoint site or you have it in OneNote or you're just doing massive repeated communications, you want data governance to have a face. I've had organizations that have created the name of the company.com slash data governance and people could go into their internet site and learn all about what it means, how they can help to recognize themselves as being a data steward and what that means. Another way to deal with all the data stewards is to provide an effective feedback loop so that when they've got an issue or they've got a question, they they're not just talking to the air. They're talking to somebody who is going to listen to them. And again, that requires some level of resources to get feedback from all of these people that are data stewards in the organization. And it will require some effective coordination. If there's a business rule that changes or a regulatory rule that changes, we need to make certain that we've now coordinated to the point that we can communicate to everybody in the organization what that rule changes and how that impacts them and their job. And as I mentioned before, the holding people accountable is critical. Now, we need management to support and understand that this is required, that people need to be held formally accountable, plan to hold people accountable, you know, formally build it into people's jobs or get them to recognize that it's part of their job. And I've been known to say that data, if data governance is a game, you win the game when you get to the point where people are not even thinking that they're data stewards and that there's data governance. It just becomes built into their job. And that's really what it requires. If you want data governance to become so commonplace rather than, oh, we're doing this because the data governance people told us, that's when you win the game is by doing that, by setting it up so that people recognize themselves as data stewards and typically those people that are running the program or administering the program, they lead, they guide, they provide direction and they provide standards and ways of doing thing and repeatable processes. The people that act on those things are the stewards. And again, recognizing that there's a lot of people that can be data stewards, we need to make certain that part of our governance program is set up to communicate that information effectively with people. So we want to build on the existing culture of the organization. We want to leverage wherever possible rather than trying to assign people things. You know, we want to take advantage of the relationships we have and the common data matrix, which is a tool that I share oftentimes with people. You know, it helps us to recognize where data is being defined, produced and used across the organization. And if we do that inventory and we know what that inventory is and we keep it up to date, that goes a great way, a great distance towards helping to communicate with your management that I want these people or data stewards, we need to let them know their data stewards and help them in their job. So again, the big differences in those three approaches of command and control versus traditional and non-invasive is the first word of what follows after the names of those approaches, the assigning of stewards versus the identifying of stewards versus the recognizing of stewards. And if you're going to take a non-invasive approach, please consider that recognizing people as stewards for what they already do and their relationship to the data, if we're going to hold them formally accountable for that, we're recognizing people as data stewards. And that way they don't feel like it's over and above the existing things that they have to do in their job. So let's talk about how to leverage existing data responsibility. So if we recognize that there's already people in the organization that do data definition, they're creating applications, systems, they're bringing data into the organization and they want to make certain that people understand that data and understand how to use it. There are people that have the responsibility for data definition and data production and data usage. So one of the things that we need to do is recognize who these people are. So is a DBA a data steward? Well, I'm not saying that the only data stewards are in the business area. That's what a lot of people think. But there are people that are defining data within IT or with who are business analysts who ride that liaison line between the business and IT. But if we know who those people are, let's give them some context as to what makes up a good definition for the data so that they can make certain that they are that they're not providing. Don't quick, you know, misunderstood definitions of the data. So let's formalize how data definition takes place, how the production and the usage takes place and let's celebrate that level of accountability for the relationship so that people all understand how that relationship is important to what they do. So let's first focus on the data definition. And you see my cheeseburger picture, it's not a great cheeseburger picture, but there's a circle with a red line through it. We don't want cheeseburger definitions. We don't want to define a student account number as an account number for a student or a or a hospitality code to be a code for hospitality. We want to provide better definition. And so what that means is that we want to be able to share people what a good definition looks like and how that compares to the quote unquote cheeseburger definitions that a lot of our old databases and old data models contain. We want to make sure that we apply this this definition to the metadata that's in the glossaries, dictionaries and catalogs that you're creating to help people to recognize who's accountable, who's not accountable, who's defining, producing and using the data across the organization. And at some point, somebody has the responsibility to say, well, this term customer number is called customer ID over there. And it's called account number over there without any reference to customer. We want to make sure that we have people in the organization that are documenting those aliases. I talk a lot about glossaries, dictionaries and catalogs. And one of the things that we need to build into those are those connections, the conceptual, the logical, the physical aliases for what we call things. That's where the glossaries and the dictionaries add the most value. And as I said before, avoid the cheeseburger definitions because they're not necessarily going to answer the questions that people have about this data. And make certain that we're leveraging what the definitions that are provided by the vendors, but again, make sure that the definitions follow the needs that you have when it comes to formal production. Well, the production of the data could happen at the point of entry. It could happen at the point of acquisition and bringing new data into the organization. It can be when you're taking pieces of data and creating other pieces of data from them. So there's a lot of data production. It's not just the front end people that are entering the data. Make sure that people understand that this data that's being produced has to follow the quality dimensions that are being shared and evaluate people's steward performance based on how they're producing the data. I know that organizations that have key punch people who are entering data, they evaluate those people on the amount of data that they're able to enter, the quality of the data that they're able to enter. And they actually use those two things when they're evaluating people. Let's evaluate the data stewards based on how well they're producing the data and producing it for the best use within the organization. And the data usage responsibilities, that's kind of a no brainer of it all. Educate people, educate stewards on the rules for the data, whether that's the protection of sensitive data or it includes PII, PHI, IP. Make sure that people understand how the data can be used, how it can't be used. And that might even include ethical use guidelines. You know, we're not supposed to combine these two things or these three or these 10 things when we're producing data, there may be ethical guidelines. And you know what, they're not going to create themselves either. Somebody needs to document and communicate what the appropriate usage of the data was. I mentioned celebrate accountability for data relationship. We need to educate the stewards a lot. We need to reward them where it's appropriate. Gamify is a term that I hear used quite a bit and that's to make it fun, make it interesting to people, have competition between parts of your organization as to who's defining their data more thoroughly, more accurately. You know, promote the idea that there are stewards and that there's effective stewardship across the organization and by all means measure that accountability result for the data. That is the best way to take advantage of who the stewards are and to to achieve data governance through the stewards that we are recognizing across the organization and understand, get people to understand the importance of their relationship to data, appreciate the relationships or the key to the data, acknowledge that the data definition stewards are defining the data and help them to do a better job, distinguish the data production stewards because they're bringing data into the organization. They're entering new data, help them to recognize that they play an important role. Oftentimes, the production of the data depends very heavily on the definition of the data and then the usage of the data depends on both of those things, the definition and the production of the data. So make the stewards accountable where they live, help them to understand that we're not handing them lots of additional things and being a data steward should not necessarily make their life more difficult. It should make their life easier, but it's only made easier if we can help to share with them what it means for them to be stewards and really help them where they live, which I mean by that is where are they working? What part of the organization are they in? These days, everybody's working from home while protecting sensitive data from home is still the same. Well, you have to follow the same rules as if everybody's on site at the same location or at multiple locations, people need to be held accountable for the data, where they live and what they're doing. So let's talk about engaged, engaging these stewards based on their relationship to data and we'll talk about engaging the definers, the producers and the users. And as I mentioned this before, it's very important for people to recognize themselves as being data stewards and whatever we can do to help them to recognize themselves as data stewards is a significant step forward for our program. And we want to make sure that we're demonstrating value to the stewards when we have better definition of the data, when people know what that data means and they know where else that data can be found and the differences between definitions, that really demonstrates value to the data stewards. Leadership really hates when people ask questions and all of a sudden they get different answers depending on who they ask because they have different understanding of the data or they're going after similar data, but it's different because it's in different locations. So we want to engage the data definers. Those are the people that are recording the data definition. We want to recognize in detail the aliases. Like I said, those connections between pieces of data, it's not going to happen on its own. We need somebody that has the responsibility for doing that. Compare the definitions, rationalize them, make sure that things are called the appropriate things. And I know that a lot of the databases and systems have limitations on the sizes of the fields, but that doesn't mean that there's limitation on the logical names that we use for those data elements or even the conceptual names that we use within the business glossaries. Make sure that we're comparing the definitions and we're rationalizing the data to make sure that we know that this piece of data is the same as that, but it's different than that one, even though it's called the same thing. We need to have that understanding because a lot of our organizations grow through acquisition. We acquire systems that have different data or should we say have a lot of the same data, but it's called something else. And it's being defined a little bit differently. And the data definers need to make certain that they document the rules associated with how the data can be used. That's key. We've got to engage people that are defining data as being data stewards. We don't have to call them data stewards, but the fact is they are stewards. They have responsibility for the definition. Same thing that holds true for the data producers. We need to make certain that when data is being produced, whether that's through calculations or derivations or mapping, that they understand how important it is to document those rules and make certain people understand. Well, we've got this data from combining these three fields or from doing this calculation or derivation and mapping the data across the organization becomes more important as we keep adding more and more different sources of data in the organization, record the source of the acquired data, validate the data at the point of production, putting edit checks into software. I guess I've always heard that more people in the world were born on 010101 than any other date. And that's not the case. They weren't actually more people that were born on January 1st, 1901 or 2001. The fact is that was the default and people go through and they just pick the default rather than having to really think about the data that's being entered to educate the producers about how the data is defined and used and evaluate them on all the quality dimensions that are associated with the data, the accessibility, the completeness, the accuracy, the timeliness, all of the quality dimensions that organizations use or the dimensions that organizations use to determine if data is high quality. And again, the data users are kind of the no-brainer of it all. That's where a lot of people focus, provide awareness of the data rules, educate them on how the data is classified. And if it's classified a certain way, you need to encrypt that data when you send it or you need to dispose of it when you're done with it. There are handling rules that people need to know, train them on how long data should be kept around, how we get rid of data and assure them that they know when there's changes to the way that people use data or even get data stewards to share how they've used the data and what the effect is on the way that the data is recognized for use across the organization. Provide that feedback loop. Hey, I used this piece of data and that piece of data and I was able to increase the sales in my part of the organization by X percentage. Get people to share that information. Data users can be more than just protecting the data. They can share from the analytical capabilities and the data science capabilities what it means to be users of the data and how they can add value to the rest of the organization. I've said this many times so far about getting the stewards to self recognize and get them, provide them with the details of what it means to be a data steward. Oh, I do that. So I guess I'm a data steward. Well, nobody's called me that. The fact is you don't have to be called a data steward to be a data steward to get stewards to provide their data relationship. So if you're going to build out a model of knowing who defines, produces and uses data across the organization, capture that information somewhere, the common data matrix is a great place for that. The data catalog is a great place for that. But it really helps to formalize. If I go back to the definition that I used for metadata earlier on, it's data that's recorded. It's information about the data. It's the people aspect of the data. And so the information about the stewards and the data that they steward or the data that they define, produce and use is metadata. And it's not going to govern itself. Somebody needs to collect that information and keep that information up to date. So recording the steward metadata, make that information available to people. And by all means, make being a data steward a good thing. Don't make it a scary thing. Don't make it think they're OK, we're going to slow down what you do by making you a data steward. No, no, no, that's not the intention at all. We want data making people data stewards or helping them to recognize themselves as data stewards to be a good thing, to be a positive. For people to recognize that, hey, I steward that data and that I have some responsibility for making certain that data is as effective as possible for the organization, demonstrate value to the stewards, improve the efficiency and the effectiveness in their work. Oftentimes I talk about how the informality of holding people accountable accountable for the data leads to inefficiency and ineffectiveness. So we want to formalize that accountability. We want to formalize efficiency and effectiveness. And we want to help people to make better decisions from the data. And that's going to be based on the information that we collect about the data, reduce the time that people spend massaging the data. You hear about the 80-20 rule a lot. Now we want to make certain that people understand the data and know what data is there and available to them and improve their knowledge on how to get access to the data. So the last subject that I want to approach with you today is how to follow the stewardship approach. So I mentioned a little bit earlier about the different approaches to governance and we'll talk about recording the stewards and I'll share with you a tool to be able to do that, sharing the steward information. So people across the organization have that information and they know who to go to when they have a question or they know who they're going to impact when they make a change to the data. And then the last thing I'm going to talk about today is again how everybody in the organization potentially is a data steward and that we need to get past that fact. So when I talk about the approaches to governance, I always talk about the command and control approach. You will do this. The traditional approach of you should do this and the noninvasive approach, which is you're already doing this. And the fact is that some organizations don't take strictly one of those approaches. They create hybrid models of that. I'm going to share with you my data governance framework and a tool that I've developed on top of that can help us to understand the differences in the approaches to data governance. So here, if you've seen my framework, and I'll share that with you more in a minute, this is a kind of a similar model that I use for my framework, but this is a way to compare those different approaches. So if you look across the top, you've got command and control, you've got traditional, you've got the noninvasive approach. And I want to relate those things to the different levels or the different components, should I say, of a successful data governance program. I talk about data being a component, the roles, the processes, communications, the metrics and the tools in my framework. And the one thing is that the things that I want to highlight for you here are if you look at the roles and you compare the differences in the approaches, there's the difference between assigning people into rules, identifying them into roles, recognizing them and just formalizing their accountability and then the communications, I think I mentioned before, instead of you will do this or you should do this, you're already doing this. So we want to help you to do it more, more effectively for the organization. This is the framework that I share a lot with organizations and you'll see the components across the top and you'll see the different levels of the organization down the side. And what I want to focus on and here's a version of the framework that's now filled in with information that you look at the executive approach and the executive's perspective of data and the strategic perspective of processes. Now, this isn't going to be perfect and the same for everybody, but that empty model is one that you could fill in as it's appropriate for you and your parts of the organization. And the part that I wanted to highlight here is the roles column, because we all know that there's an executive role, strategic role, tactical, operational and support roles to our data governance program. I challenge you to say that there's other roles or different types of roles within the organization, but pretty much every one of them falls under one of those categories and that's kind of the traditional approach that people look at the organization from the executive down to the support parts of the organization, but not even just looking at the roles. Let's look specifically at the where the operational roles, the operational level kind of cross exists with the roles themselves. And you'll see that that's where the operational data stewards are. That's where the users of the data are. And they have a relationship to a lot of different things within the organization. They relate when it comes to processes and communications and metrics. They relate because they're going to be working with the tactical stewards. They're going to be reporting the information to this strategic level. And then you're going to get your guidance from your executive level. So consider using this model, this framework to help you to really define what you need to put in place in order to have a successful governance program. I'm not going to spend a lot of time on the common data matrix. I will describe it very quickly to you here. We're not we don't have the time to go through it. I've done webinars in the past on how to create tools within your organization. But this tool is the one that is requested the most often from this webinar, from my book, from the presentations I give at the university events that people want to know they want to template for how can we start to inventory and identify who's responsible for the data? Who's accountable for the data across the organization? If you work your way left to right, well, first of all, there's a color key in the upper left hand corner that has the data governance council, the council alternate, coordinators, domain stewards, all the way down to the operational data stewards and working from left to right, you've got a domain of data. The example here is the customer data. You've got some domains of data, the customer demographic data. And you know what? The customer demographic data, as we work our way complete, continue to move to the right, you'll see that customer demographic data could reside in multiple systems, the ERP system, the master data management in your enterprise data warehouse. And you know what? There's people in it that have responsibility for that data. So you can use the common data matrix to document even the partners from IT that are really knowledgeable about specific data within specific systems. And then as we continue to move to the right, we've got all the different business areas and functions within the business units and even represent shadow IT in one of those columns. We could put an X in the block or we could put people's names in the block. This says that, OK, well, in this part of the organization, they use this specific data from this specific system. I'm telling you, you're going to want to know that information when you're moving forward with your data governance program. It's going to be the kind of the core, the backbone of taking your roles and responsibilities and making it visual to people. So I call it the data inventory and accountability matrix. I've been calling it the common data matrix for a long time. These are tools that you can build yourself to help get people to understand that the reason why when I ask a question, I get a multiple answers is because people are going to get the data from different places. And we can point back to the fact that the documentation of the data is not complete the way that it needs to be. So if you want more information about the common data matrix, I know that we share it with the webinar. So when Shannon sends her email after the webinar is over, there will be links to being able to access the common data matrix or reach out to me and I'll be glad to send you a copy as well. But we want to share this steward information. We want to recognize that the stewards are basically the backbone of the program. We want to make the steward information available widely across the organization. Make sure that we're not just collecting a snapshot and that we're doing change management for the data for the metadata that the steward metadata that we're talking about here and use the metadata that we that we fill in to grow data governance. I always talk about the data governance bill of rights, getting the right people at the right time, using the right data to do the right thing. Across our organization, that's really what data governance is all about. It's all about those bill of rights. And I think that's also a link that Shannon shares with the email is that there's a bill of rights that I've kind of drawn up as a bill of as it like the traditional bill of rights, but traditional the focus of the bill of rights for people across the organization. So I know I mentioned this earlier and it's kind of a repeat of that earlier slide, people are already informally accountable. It's part of people's job description to follow procedures. We want to make sure that we're doing all these things and recognize that there are consequences for not behaving properly and not following the rules associated with the data. So the last thing that I have to share with you before I turn this over to Shannon to see if there's any questions that are coming in from today's webinar are my eight roles for becoming a data steward. And here I say a data steward can be anybody in the organization. It can actually be everybody in the organization if they're being held formally accountable for their relationship to the data. And being a data steward is not necessarily a title. It may be for some of your organizations, but it really describes a relationship to people that people have to the data. And it's not necessarily a position. People don't have to be hired in to be data stewards. They're basically data stewards based on their relationship to the data. They don't need to have the title of data steward in order to be a data steward. And oftentimes they don't have to be told how to do their job. Well, I guess they do have to be told how to protect the sensitive information. But I don't necessarily, but they should be taught to do that already when they join the organization. I don't like the idea of public or industry data steward certification. I know other people might disagree with me. But if we can help people to recognize themselves as data stewards, that's a big step forward in our organization. And typically there's more than one data steward. We don't have Bob Steiner. He's not the customer data steward and nobody else is the steward of that data. Now, if you use that data, you're a data steward. And basically, if you're going to train your stewards in the organization, it should focus on that formalization of the accountability. So I know I went through a lot in a very short period of time, but this is what I covered in today's session. Why everybody is a data steward, how the number of stewards and how you define their stewardship impacts the complexity of your program, how to leverage the responsibility that people already have for the data and engaging those stewards based on their relationship to the data. And finally, I talked about how to follow a stewardship approach. And with that, I will turn it back to you, Shannon, to see if we have any questions today from the webinar. Bob, thank you so much for another fantastic presentation. And just to answer the most commonly asked questions that we receive, you will indeed get a copy of Bob's matricy as he was talking about as well as links to the slides and links to the recording. I will be sending that out by end of day Tuesday, typically by end of day Monday, but it is a US holiday on Monday. So by end of day Tuesday, I'll be sending that out to all registrants. Diving in here then, Bob, what would you do if the data steward is in another business line than the data owner? We have some problems with line of command. OK, so one thing and I don't know how everybody feels about this, but I don't really like the term data owner. I know that a lot of organizations use data owner, process owner, system owner, but they don't really own these things. The organizations own them. So people are data stewards. They're not just in the same business unit as the data owner, the quote unquote data owner, the person that owns that data, owns that system. So what would I do about it? They're not necessarily accountable to the data owner. They're accountable to the organization. So kind of eliminate that from your way of thinking that they're not doing this for the data owner, they're doing this for the organization. And so a data owner of sensitive information is not the only person that you're taking care of this data for. That's a definition kind of a dictionary definition of stewardship is somebody who takes care of something for somebody else. And somebody else in this situation is the organization. They're not necessarily they don't need to be in the same line of command as the owner. They're really doing this for the organization and they should be considered as such. And is the data owner then not accountable? No, no, no, the data the data owner is definitely accountable. Again, I don't like the term, but if you call them data owners, they're accountable for making sure that the data is defined in such a way that people understand it and understand how it can be used. They're also responsible for defining the rules associated with the data. If they truly quote unquote own the data, they're going to make sure that that data is classified appropriately, that people that access that data know the rules. So the data owner without a doubt is accountable, but they're kind of more of that tactical level than the operational people. So there's not a hierarchy of the operational data stewards reporting to the data owners. They're again, they're accountable to the entire organization. But the people at the tactical level need to make certain that the data is well documented in the glossary, in the dictionary, in the data catalog, in the metadata repository, even in the common data matrix that I shared. So what if the organization is not doing data definitions or data modeling? How to recognize what is not there? Well, I just ask yourself a question. Are there definitions for the data? You know what, at some point when the data was being, was when the systems were being developed or even when the systems were being acquired, somebody was responsible for the data, for defining the data that's going to go into that system or defining the data that we need in the system when we go out and acquire a system. So it may not be somewhere where everybody can get access to it. It may be in a spreadsheet or in a Word document or in a SharePoint site, like the things I mentioned before, or it may not exist at all. It's not going to, it's not going, the definitions are not going to be produced on their cell by themselves. If there's not somebody who's held formally accountable for capturing the definitions, unless you already have them and they're just being done as part of business, you can't expect those definitions to exist. It requires that we have a steward for the definition of the data. And that's why I talked about earlier, the data definition stewards are a key role in data governance because they are where it starts. The production of the data oftentimes depends on good definition of the data. If we don't have good definition of the data, how can we expect that the production of the data is going to be of high quality? We need that solid definition in order to be successful with quality production and then quality use of the data. I agree that ideally everyone is and should be recognized as a data steward. However, as a leader of our data governance program, I can't work with everyone at once. Could I identify people from business units to be quote unquote champions for their group? Oh, without a doubt, that's a great question. So going back to the common data matrix, I had a role of a data steward coordinator and if you noticed that that role was associated with each column, so a functional area or a business unit. And by all means, you're right that one person or just a few people that are running your program cannot be expected to communicate with everybody across the organization, especially if your organization is huge. So you want to have coordinators and it's not necessarily in their title or it's part of their job and it could be even an administrative person within that part of the organization that when there's a change to a business role, we communicate it to the coordinator and the coordinator then communicates it out to everybody. No, we cannot expect the administrator or the data governance lead or the data governance manager to communicate with everybody. There needs to be somebody there who is going to assist you in that communication. So that was a great question. I am very glad you asked that. I find data stewards are quite often very literate about data they use, but not so literate about data governance around their data. How do you change culture to recognize the importance of becoming more literate about good data governance practices? Well, you know what? We need to share them with them. It has to be a big part of the role of the administrator or the lead or the manager or the office that is putting governance. We can't expect them to become more literate without somebody kind of leading the path, leading the way for them. So how can we get to expect them to become more literate about data governance in general? Well, somebody needs to share the concepts with them. Get them familiar with not only the concepts, but how we're going about it. And again, as I mentioned this many times during the webinar, get people to recognize themselves as data stewards and get them to understand how they relate to the overall governance of the data in the organization. It is the best way to move forward, at least in my opinion, it's the best way to move forward with a data governance program that embraces the entire organization. Well, Bob, thank you so much. That does bring us to the top of the hour. Again, just a reminder, I will send a follow up email by end of day Tuesday for this webinar again, Monday is the US holiday. So by end of day Tuesday, with links to the slides, the recording and the matrices that Bob mentioned. Also, if you have additional questions, I'll get all the questions that we didn't get answered today over to Bob to include a write up of answers for those unanswered questions. Thanks, everybody. Hope you all have a great day. Stay safe out there and enjoy. Thanks, Bob. Take care, everybody. Thanks for being here today.