 Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Officer of Data Diversity. I'd like to thank you for joining the current installment of the monthly Data Diversity webinar series, Real World Data Governance with Bob Siner. Today, Bob will discuss Build Your Own Data Governance Framework sponsored today by Alation. 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 to note, Zoom defaults the chat to send to just the panelists, but you may absolutely change that to network with everyone. For questions, we'll be collecting them by the Q&A section. And to find the chat and the Q&A panels, you may click those icons in the bottom middle of your screen to activate those features. And as always, we will send a follow-up email within two business days containing links to the slides, the recording of the session, and any additional information requested throughout the webinar. Now, let me turn it over to Susanna for a brief word from our sponsor, Alation. Susanna, hello and welcome. Hi, Shannon. Thanks for having me. I just want to make sure everybody can see my slides okay. Looks good. Perfect. Thank you so much. So my name is Susanna Barnes, and I'm the Data Intelligence Program Lead for Alation. Today, I'm going to talk a little bit about Alation's perspective on data governance. So to be successful, every company needs to use data to deliver business value. Companies need to create and foster a data-driven culture. To do that, they need a platform and program that supports their data users while still providing the data governance needed. When we talk about establishing data governance and data management, there's generally three key pillars, people, process, technology. Some of you may have already gone through the process of selecting a data catalog, and others of you may be doing that now. But in some respects, the technology piece can be the easiest part of the process. What's more challenging is understanding what comes next. We often hear customers ask, now that I have a tool, what do I do? I have a company full of data. Where do I start? How can I tell I'm delivering value? How do I measure success? How do I map out my own journey so that I'm continually building towards the next level of data maturity? To help answer these questions, Alation has developed the Active Data Governance methodology. And this is an autonomous, continuous improvement methodology guiding organizations to create a data-driven culture through data governance. Active Data Governance is a continuous process. So we represent the stages of the Active Governance on our governance wheels. The first step is to identify your initial governance group and define the vision and mission you have for your governance program. Then you really need to identify a use case that will deliver measurable business value and then use your governance program to address that use case first. Your overall program, and it may have goals to have all of your data assets monitored, curated, and classified, but you'll have to start somewhere and that initial use case is where you begin. By establishing this clear scope for your initial governance activities, you'll be able to implement your program with measurable outcomes and you'll be able to improve your processes with each new use case. So the next step is to start populating your data catalog with the data from your use case. This begins with connecting your source, ingesting technical metadata, so we're talking about the structural information, the lineage data. After that, you need to identify and empower your data stewards. Maybe you already have stewards identified, but if you don't, you can analyze the usage data ingested into your catalog and identify the top users of different data sets. And these are often ideal data stewards. So after that point, you need to really help the stewards understand the importance of creating knowledge around your data assets. And you also want to find the opportunity to recognize and encourage individuals that are already doing this work within your organization. So now you move on to the curation of your data. So this is going to be a providing documentation for the use of data sets, making sure the data is well defined, creating business glossaries and turns, basically giving people the information they need to find, understand, and trust the data that they use. On the first few steps in our wheel, focus a lot on discovery. What data do we have, who uses the data, and who understands the data? What information do people need to move from a business question to a data-driven insight? In order to foster a continued sense of trust in your data with your users, you now need to start implementing the governance policies and processes that you've defined. This ensures that users are guided to the right data for their business needs, and they can see the data is controlled and monitored. The next stage is all about engagement with your data community. The people pillar of data governance isn't just about stewards in the government's office, it's about building a data community that will contribute knowledge to your catalog. You need to teach people how to find the data they need, show them how they can verify the data's fit for their purpose, and encourage them to collaborate with peers via the catalog. Community engagement is also a great opportunity to find that next core use case for your program. Finally, we come to the final stage, monitor and measure. This is your opportunity to promote the positive business outcomes that your program has delivered. You can set up different methods to measure like curation progress, policy conformance, data quality measuring, and monitoring, whatever really works for what you need to demonstrate. This is also a great time to have a retrospective and determine what worked and what didn't work so you can make adjustments before you begin your next use case. So what does this look like applied to a data environment? Let's take a look. Your organization likely has a combination of databases, data lakes, file systems, VI systems. You need a platform that can automatically extract the physical metadata from these systems and keep it up to date. Next, you want to apply some human guided machine learning to provide suggestions for things like natural language titles for data objects and suggestions for new glass returns. Why do I specifically say human guidance? You know your data and you know your business, and as the machine learning is operating within your platform, your approval or rejection of suggestions helps that model learn and operate more tuned to your specific organizational needs and that's critical for delivering better value over time. So up to this point, we've looked at what the data is, but now we want to start looking at who's using the data and how it's being used. This is done through analysis of database query logs. This is going to identify the top users of different data sets. These are people who may be ideal steward candidates. It identifies which data objects are being used the most. This helps you find use cases and prioritize curation efforts. The logs also provide you with the broader picture of the data relationships that exist in your organization. So what joins and filters are commonly used. How is the data flowing through all your different systems? And now, you know, we have this complete picture of active governance at work. So once the technical metadata has been adjusted, the curation process can begin. You've assigned stewards to curate the data to provide the context users need to find and understand the data. Your data consumers are able to self-serve trusted data and the governance team can actively monitor data use and identify the next business opportunities tackle. So as you look at your governance program, these are just some things to consider so that your approach balances the people, processes, and technology that are the foundation for data-driven culture. And now I'll hand it back to Shannon. Dana, thank you so much. And thanks to Elation for sponsoring today's webinar and helping to make these webinars happen. And if you have any questions for Susanna, feel free to submit them in the Q&A panel as she will like what might be joining us for the Q&A portion of the webinar at the end. Now I'm going to introduce to you our speaker for the series, Bob Sinner. Bob is the president and principal of KIK Consultant and Educational Services and Bob specializes in non-invasive data governance, data stewardship, and metadata management solutions. And with that, I'll give the floor to Bob to start his presentation. Hello and welcome. Hi, Shannon. Can you hear me okay? You sound good. Hey, real good. And so number one, thank you very much to Elation. Thank you, Susanna, for a great presentation. You know, looking at the Elation Wheel of Active Data Governance, the Data Governance frameworks right in the middle of it. And that's what we're going to talk about today. In fact, this is I've been looking forward to this webinar for some time because anybody who knows me real well knows that I've been focusing a lot on the data governance framework recently. Actually, there's three main reasons why I've really been excited about doing this webinar and the timing is really perfect for it. The first one is just last month I gave a presentation on the data governance framework and non-invasive data governance framework at the EDW conference in Anaheim. And actually last December at DGIQ East, I gave a presentation on the conference, a workshop on how to complete the framework. We're going to talk about it kind of in an abbreviated fashion today. We're going to go through how to complete a framework specifically for your organization and how it can become useful as a tool for your organization. The second reason is that I'm just in the process right now building an online learning plan through Dataversities Training Center on specifically how to create and how to utilize data governance frameworks. And the third reason is I'm in the process of digitizing the framework that I'm going to share with you today. So if anybody's interested in talking to me about the digitized framework, I'll be happy to talk to you at some point after the webinar. Just to give you a little bit of an idea as to some of the things that I'm actively involved in right now. Well, first of all, there's this webinar series that has been taking place on the third Thursday of every month. So next month, on the third Thursday of the month, we're going to cover a subject that we also covered at EDW in Anaheim, how to select the right metadata to govern. There's lots of different types of metadata that we can govern as part of our data landscape or data environment. How do we go about selecting the right? And the word right is in quotes because the word right might be different, or what's right might be different for each of the different organizations. I'll be speaking at the DGIQ East Conference again this December in Washington, D.C. I talk a lot about non-invasive data governance. My first book on non-invasive data governance was published back in 2014. In the second book, the follow-up book to it, Non-Invasive Data Governance Strikes Again, was published in May of this year. There's already learning plans that are available that I have created through through Dataversely's Training Center, one on non-invasive data governance, one on non-invasive metadata governance, one on business glossaries, data dictionaries, and catalogs. And like I said, the next one is going to address how to complete a framework that can be used within your organization. The name of my consulting business is KIK Consulting and Educational Services. KIK stands for Knowledge is King. You can go to that website to see everything that you've ever wanted to know about non-invasive data governance. That is the home of non-invasive data governance. And then when I have time in my spare time, now actually I'm very engaged at Carnegie Mellon University in their Chief Data Officer Executive Education Program. So sorry to take a couple minutes to go through those things. What are we here to talk about today? First of all, I want to share with you this data governance framework that I've been using, I used initially as an educational tool, but then I had some clients that said, no, we need to utilize this. This will really help us in our journey to implement an effective data governance program. So I'm going to share with you the first thing out of the gate is the framework that then we're going to walk through and we're going to talk about how can we customize this framework to be beneficial to our organization. We'll talk about the appropriate components, the appropriate levels within the framework, and you'll see what I mean here in a minute. Then there's specific boxes, or I refer to them as bridges between the components and the levels. We need to fill those in too. And then we'll talk about leveraging your new framework to govern the data within your organization. I always like to get started just with some quick definitions that I use because my definitions may be a little bit different from some other people in the industry. Some of my definitions have a little bit more teeth behind them and make people sit forward in their chairs and ask questions about why do we need to define things this way? The definition that I have for data governance is that it's the execution and enforcement of authority over the management of data and data related assets. So execution and enforcement of authority, a lot of my clients don't, but they think that that's worded too strongly and they try to temper the definition a little bit. But at the end of the day, no matter what approach you take to data governance, you need to follow the rules. You need to execute and enforce authority over data, and you can do that in a noninvasive way. My definition of data stewardship is basically formalized accountability for data. And you've probably heard me say before that potentially everybody in your organization is a data steward if they have a relationship to the data and if they're being held formally accountable for how they're handling that relationship to the data. So if they define data, produce data, use data, if they're being held accountable for how they define produce and use data, they're stewards. It's not something you cannot into or opt out of. You're expected to follow the rules. We need to help you to follow the rules and help you to understand what the rules are. And what is a data governance framework? The main topic for today, well, it's a basic conceptual structure that you can use to outline and put together all the different pieces of an effective data governance program. So with that, I'm just going to jump right in and show you the framework. And so this is the framework. As you see it in front of you, there's core components. There's the most important things that you need to be thinking about when you're setting up your program across the top. We're going to go through those in a couple of minutes. The fact is that maybe you have different core components for your data governance program. In fact, in the workshops that I've held on the framework, I've asked people, do we need to add additional components? And I'll share with you what some of their answers have been here in a couple of minutes, that I've pretty much kept to these six core components. Again, we'll walk through them and you'll understand why I choose those as really the core components of the framework. And then I think that we need to look at each of these components from each of the different levels that we have within our organization. So in a typical organization, a typical sizable organization, you may have an executive office, an executive level, a strategic tactical, operational, and certainly a support level. So what I want the left side of the framework to represent is, what does your organization look like? And again, don't be afraid to change the terms that are being used here, change the order. I've had people tell me that, you know, that operational should be above tactical. Again, it all depends on how you define things for your organization. And then here's just a quick example of how one organization that I worked with, filled in the framework. And so if you just look at the roles column, you can see that there's roles for the executives, there's roles at the strategic and tactical and operational throughout the organization. There's metrics and tools that are important at each of these different levels. The fact is, I would suggest not taking somebody else's framework and trying to apply it specifically for your organization. I would suggest drawing out a quick map of what this framework looks like or going back and listening to this webinar again and filling out one of your own frameworks just so it represents what effectively is going to be beneficial to your organization. So I said that I was going to be digitizing the framework that I just shared with you. This is an example of a prototype of that digitized framework where it's going to make it very easy for people to be able to click through certain things and gain some of the information that people need about their data governance program and specifically about their program within their organization. Here's as an example, just the roles column being filled out in the framework. So I mentioned that before in the previous version I showed. That's a simple one. That's easy to be able to recognize what are the roles that make up your operating model and align them with each of the different levels of the organization. Another way to look at this framework would be to set it up for daily operations and reporting. And so again, I'm not here to really go through each of these boxes in detail. What I really want to do is I want to go back to the framework that I shared with you in the first place and work with you and go through each of the different components, go through each of the different levels, give you some considerations of some of the questions that you may need to answer when it comes to those bridges between the components across the top and the levels that are down the side. So what do we want to talk about next? We want to talk about customizing the data governance framework for your organization. So the first thing that we're going to do is we're going to look at those core components and I'm going to provide to you a definition of what I mean by each of those, the data, the roles, the processes and so on. And then we also need to put a definition to each of the levels that were down the left hand side of the matrix. And again, this needs to be customizable to your organization. So if the verbiage that I'm using in the example of the framework that I'm showing does not represent your organization, you should certainly consider changing it. And again, start with a blank sheet and fill in things that make sense to your organization. We'll talk a little bit about the structure and why it's built the way it is, the colors and why the colors are the way they are and how they link up with other templates and tools and things that you're using within your environment. And then the last thing just to focus on is make sure you get the terminology right. I mean, the world, according to Bob Seiner, at least in the framework that I'm sharing with you, may not match your organization at all. Or maybe it'll match it closely. Again, my suggestion is customize these frameworks. And in those workshops that I've done on the framework, the idea was to give people time throughout the workshops to complete the framework so that they could walk out of the the workshops with usable frameworks that they at least the start of a usable framework that they could take back to their organization. So let's first talk about what does it look the way that it looks? Well, I always say that if you're a consultant, you either view things in the forms of a matrix or in the form of a pyramid. Yes, I've got both of those. Certainly the the framework is a matrix. It's two dimensional, but I'm also going to talk about how there's additional dimensions that you may want to include within your framework again, depending on how you use it. And since it's two dimensional, I don't know if any of you have heard of the book Planoverse. If not, I suggest that you go take a look at it. It's about computer contact with a two dimensional world. And that's what really it's all one life is just on one plane of two dimensions. I'm going to talk about the key considerations. You know, when you're building your successful program, you know, you need to at some point in time, know what metrics are important at each level. You need to know what processes are being governed. You need to know what tools are available to these people. It's the way the framework is set up. And I've seen other frameworks that give you a lot of arrows and jump you around from box to box. This one is really meant to be a container for you to put information in that's going to benefit people within your organization. So it's really the who, what, why, where, when, and how of your organization. And, you know, it addresses really all that the core components from, you know, who needs to care, who needs to care, who cares about these things within your organization. If you complete, excuse me, the entire framework, you should be able to answer most of these questions just using the items within the framework. Again, the framework structure right now, it's a six by five matrix. When we start digging into those bridges, those pieces that connect the components in the levels, you'll see that there's multiple dimensions that we can talk about. No two organizations are exactly the same. They're in different industries that are different sizes. They have different governing styles. They have different regulatory controls and constraints. So no two organizations are the same. When I'm going to fill out the digitized version of the framework, I want to help to be able to address as many of those dimensions as I can. And you might want to consider doing that when you're filling in the matrix or filling in the framework for your organization. Also, you can connect to other templates and tools that you've developed associated with your governance program. And you can also work, do an assessment of your organization that will help you determine what are the most appropriate blocks within the framework to address. Since it's a six by five matrix, there's 30 blocks. The first question that I would have, if I'm trying to use it, is where do we start? What's the most logical? What don't we have already? What do we have that can be represented within the framework? But then start to focus on those things that are meaningful and timely to your organization. So the assessments can actually direct you to what pieces, what bridges within the framework that you should use to implement. There's other ideas about customizing your data governance framework. I use a specific set of colors. And you'll see on the next slide that those colors are in sync with other tools and templates that I've shared often within these webinars. When I talk about roles and responsibilities, I talk about the operating model of roles and responsibilities. That's a pyramid diagram that I'll share with you on the next slide. The common data matrix is probably the most requested tool from anybody that I share doing these webinars because it helps you to get your arms around your inventory of data, how it's important, what the critical data is, and how it's shared across the organization. A racy matrix is a typical matrix that organizations use to govern their processes. Typically, at the top of a racy matrix, you'll have the roles and responsibilities that align with your operating model, that align with your framework. But down the left-hand side of your racy matrix, you'll have the different steps of whatever process it is that you're governing. And you're going to say who's accountable, who's responsible, who's going to be consulted, who's going to be informed during those steps of those processes. And then the communication plan that I've done complete webinars on that help you to identify, again, the different roles and responsibilities that are aligned with the different levels of the organization. And how are we going to communicate? How are we going to orient these people on board these people and provide them ongoing communication around data governance? So the color coordination is really important because I want people to be able to see themselves not only in one of the templates that are being used. So in the middle, you've got the data governance framework. On the left-hand side, you've got that pyramid diagram that I spoke about, which is the operating model of roles and responsibilities. In the bottom left, we've got the racy matrix of the different roles across the top and the different steps of the process that's being governed down the side. If you notice, each of the colors that are associated with each of the different levels are aligned with their purpose and their use within each of these tools. So again, I'm not going to have a whole lot of time to be able to go into each of these tools themselves, but the framework, if you're creating a framework, it has to work hand in hand with the other tools that you're creating as you're defining your program. I mentioned earlier that in the bridges of the framework, you might want to provide links to other tools and templates and things that are descriptive of how your governance program is working or how it is going to work within your organization. And the last part of customizing the data governance framework is, by all means, do anything that you need to do to assure that the language that you're using in your descriptions, the language that you're using to describe the core components, the levels are appropriate. I've had organizations combine multiple levels of the organization. I've had organizations tell me that know that the operational level falls above the tactical. Again, I'm just providing the framework to be able to be used and again, make it match what you have within your organization. And like I said, use language that makes sense to your organization. And just as I mentioned in the workshop that I had done using the framework, I tell people don't be afraid to add or eliminate components or add or eliminate levels to your organization if it accurately represents what you have within your organization. All right, so now let's talk about determining those appropriate components across the top of the framework. So as you see, their data roles, processes, communications, metrics and tools, I'll share a few that other people had suggested that might want to be included within your framework. But the data is basically the assets that are being governed and the things that where you're focusing on improving the quality of the roles are the formal accountability for governance and for information quality across the organization. The processes are the things that you're applying governance to the communications. Well, that's the education, the training, the awareness, the literacy, the metrics. Again, these are the six items that I've found to be most effective in defining what is necessary to implement a strong sustainable data governance program. So let's go through each of these, just to spend a couple minutes going through each of these. So when it comes to data, actually, when I first created the framework, it was only a five by five matrix. I did not have a data column. And then I got to thinking and I got to the point where we really need to define what data is important and how people at the different levels of the organization access the data. So the data became an important added component to the framework. Again, it's evolving over time and it can evolve in whatever means it needs to evolve for your organization. So the data really defines the scope of the resources that are being governed and I put it as the very first column within the framework itself. There's a lot of confusion going on in industry about data governance, information governance, records governance. Information governance is being used primarily to summarize the governance of unstructured data. Well, data governance is mostly, at least from my experience, focusing on the structured data within the organization. The fact is there's organizations that have had records management and content management programs for different types of data of different times in their journey of their company. And so look to see what levels of governance are already taking place, what data is being governed. Data has to be included as being an important component of your data governance framework. Then the roles for the obvious reason of all those templates that I shared with you, the roles become the backbone of a successful governance program. We need to define what are the roles at the different level of the organization. Really the way people are associated into their roles, whether they're assigned into roles or identified or in a non-invasive approach recognized into roles, that plays a significant predictor of what effort is going to go into creating your program. As I said, roles are the backbone of your program and it makes sense to have roles as one of your critical components of your governance program. Processes. Well, I know that there's a lot of organizations that define things in terms of a singular data governance process. Actually, any process within itself is a form of governance because it is steps for you to handle a task. Where I suggest that we apply governance to process is that we get the right people involved at the right time and the right steps of the program. We know that we need to define process and we need to understand what processes are important at each of the different levels within the organization. Typically, there's not a single process that's being governed. It's applying governance to process is getting the right people to be engaged at the right time within that process. Communications is another important component of a successful governance program and we know that we can't communicate with all the people in the organization, all the different levels of the organization in the same way. We actually know that from experience, that the people with the different levels of the organization aren't all interested in the same things. The framework might be a good place for you to start to document what are the communications that are important at each of the different levels of the organization. How are we going to provide that communications to those people at those levels? Metrics and tools. Again, I don't want to go through these in a lot of detail. You have them written out in front of you. Metrics are important. Metrics are not the same to people at a very level. The tools aren't going to be the same. Actually, policy and strategy and standards, those are tools at different levels of the organization all the way down to the data catalog tool that Susanna talked about and the business glossary and the data dictionary. Filling in the framework with the tools that are going to be the responsibility of or going to be beneficial to the different levels of your organization will help you, just including them within your framework, will help you to get your arms around what's necessary, where do we need to address these things across our organization. And so, I did pose the question to people at the workshops that I did recently and they came back to me and said, well, maybe we need to add business value as a column. And then one of my clients just this week said, maybe we should add data culture as a column. Well, just to address data culture and the conversation that I had with her, we talked about how the culture has a lot to do with communications. It has a lot to do with processes and roles. And we determined that maybe it's not the appropriate time to add that to the framework. But again, the framework is there as a tool that can be manipulated and customized specifically for your organization in ways that will be beneficial to your program and explaining to people what's necessary and what the status is of different activities that are going on or associated with your data governance program. Let's go through the levels real quickly. If you've attended the webinars that I've done on the subject, I've done complete webinars on the roles and responsibilities associated with the data governance program. This operating model addresses all of those levels that are listed on the left-hand side. There's the executive, the strategic. There's the tactical where we're starting to look at data across business functions. There's the operational where we're looking at data most specifically within a business function. There's the support and then certainly in the administrative levels of responsibility that are important as well. So I typically align my roles and responsibilities with levels with my roles and responsibilities that I see they're common in most organizations. So just to give to provide real quick definitions of what it means to be the executive level. Again, the executive level may be different in a company that has thousands of people than a company that has hundreds of people. And so you may not even call it the executive level or the strategic level. Just have a good definition for what each of the levels are within your framework and be able to differentiate between executive and strategic and between tactical and operational. Typically where the bulk of the data governance work takes place most organizations have a data governance council at the strategic level. But a lot of the governing activities take place at the tactical and the operational level. And the way that I differentiate those is that the tactical level is really people that are looking at the data of the organization across business units as compared to the people that are operational in nature that are most often looking at specifically their function within their part of the organization. We know we need to have operational data stewards. We know we need to have subject matter experts at the tactical level as well. Again, determine what are the appropriate levels to include in your organization. Those are all the levels on the right hand side of the pyramid on the left hand side of the pyramid of the operating model. I've got the role of the administrator. In some organizations they include that under the support level of the organization. In some organizations they actually create a sixth level in their matrix for the administrative level. I don't always feel like that's necessary because the administrative person is going to be most likely the person that is completing the framework and is sharing the framework with people across the organization. When it comes to the support levels of the organization there's IT who is a partner of data governance. There's working teams. Just recognize that besides for having the executive strategic tactical and operational the support level people in the organization are going to make up a large number a large percentage of your organization. Okay, so now we spent a little bit of time going through the components at the top. We started going down the levels down the left hand side. Now what I want to do is I want to address those bridges between the components and the levels and it's basically taking a look at every component from each level's perspective. I don't know if you're familiar with a gentleman who was kind of one of my people that I looked up to when I got started in the industry, John Zachman created the Zachman framework and John would say about his framework that at some point in time you're going to need to know all this information. The same thing holds true for the data governance framework. At some point in time you're going to want to know what data is important to everybody and it's not going to be the same. It's going to be different depending on who you are and what level you are in the organization. Same thing holds true with the roles and the processes and the communications. Even the metrics are going to be different for each of the different levels so we need to consider those things as we're filling in the boxes of the framework. So the framework is a basic conceptual structure. The bridges are actually where the rubber hits the road with the application because now what we're doing is we're planning for each component at each level of the organization and we can also document what is our knowledge based, what intelligence do we have that goes behind each of the bridges and then I'll also spend some time talking about how there's more than two dimensions. There's actually several more dimensions that people should consider when they're filling in their data governance framework. So if we go row, if we go column by column, I want to just share a couple questions that you may want to consider answering as part of the completion of your data governance framework. So we're going to start with the data component and we're going to look at the data component for each level. Some of the questions that you may want to answer within your framework is what data is critical for decision making at each of these levels. The data that's critical for decision making at the executive level is going to be different than the tactical or the support levels. So you may want to go and fill in what data is critical for decision making, how do they access their data, how do they share data, what do they use data for at that level, what are the quality standards. Again, there's a lot of different questions that you can ask about each of the different components and I'm just going to go through them quickly. Again, I hope you'll go back and you'll look at the slides from this webinar and consider what these as some of the potential questions that you'll want to answer as you're completing your framework. When it comes to the roles component at each level, what are the data-related responsibilities and accountabilities? A lot of the time those will be the things that will be included in your operating model of roles and responsibilities. How should data-related communication and collaboration be facilitated? What skills or knowledge are necessary to complete each of the roles at each of the different levels of the organization? Again, at some point you're going to want to know this information. Same thing with processes. Again, a handful of questions or three questions. What are the data-related processes that are important? How did data-related decisions get made at each of the different levels? Again, these are just some ideas to help you to complete your framework in a way that's meaningful to your organization. Communications, the same thing. What are the data communication needs and requirements at each level? How should data-related information be disseminated and shared? Again, what I'm trying to do is, again, there's not one way to complete the framework. The idea is I'm trying to provide you with some questions that you might want to answer as you're filling out the bridges between the components and the levels of your organizational framework. The metrics at each level, some of the questions that you might want to ask. What are the KPIs and metrics at the tools level? Again, I'm going through these relatively quickly. I hope you'll go back and look at these slides, because I'm going to run out of time really quickly if I spend too much time on each of these categories. Again, just wanted to also give you an idea as to what the workshops that were held at Anaheim and in DC last year, we spent a lot of time. We broke into groups. We asked each other what were the questions that needed to be answered within the framework. Again, it's a different type of framework. It's not a framework that is going to show you the direction of everything that you need to do. It's there for you to complete it, to use it as a knowledge base, as a resource base, as you're building out your program. And as I mentioned, John Zachman, his enterprise architecture framework referred to as the Zachman framework. When John would give presentations at diversity events, at other events, he was known for saying the same thing over and over again during his presentations. And he said it in such a way that it really drove the point home. Or he kept saying that at some point you're going to want to know the information in each of those blocks associated with your framework. And so I'm saying the same thing with this framework, saying at some point you will want to know about every one of these data governance components from each of these different levels. And if you're not familiar with the Zachman framework, here's a picture that I got online that's available freely. It's a use of the Zachman framework for the Veterans Affairs Department. And here's another example of what John created in his framework. He had data function network people time and motivation. And he was looking at different perspectives of the organization as well. They're different from mine, but he was certainly the impetus was certainly what motivated me to put my arms around what are the important components and how should they be viewed at each level within the organization. So when I talk about there being multiple dimensions, and I shared the two dimensional diagram, the book, the plan of verse, there are many additional dimensions because organizations, no two organizations are the same. Their organizational industry may be different. And therefore they may have different regulations and different pressures coming from the industry. The size of the organization may be different, the type may be different. So the way that you fill in the matrix fill in the framework is going to be different depending on these things within your organization. When I get to the point where I'm digitizing the framework, I want to provide advice or at least some level of guidance as to, for example, how do we look at what the executive level role should be within an organization of under 200 people versus over 400 people, or of a public company versus a private company or a company that's brand new versus a company that's been established for a long time. There's a lot of different dimensions that people need to care about when they're completing the framework, when they're completing their program. There's not a one size fits all program for all organizations. And another thing I suggest to include within those bridges is links to artifacts and templates and things that you have within your organization specific to each bridge. So you can link to important documents, link to external content, to webinars, to books, to white papers that are written on the subject. Again, make the tool as useful as possible by providing links to artifacts and templates through the use of the framework itself. And the last subject I want to hit on before I turn this back over to Shannon, and we do the Q&A, is leveraging your new framework to govern data. So I have seen organizations who have used the data governance framework as the face of their program, meaning that that's something that they're providing through some type of an internet site through teams or through a SharePoint that gives people the ability to click through different aspects of the framework to get information about their program. So we'll talk about it being the face of your program, why the selection of the framework and the approach is critical, how to go about selecting it and then leveraging your framework to govern your data. So as I said, there's organizations that use the framework as a graphic and make it clickable so that people can actually click through to learn about the executive level, to learn about the data that's important to them, to learn about the tools and the policy and the standards and those types of things. So it's used as an interface for access to information about your data governance program. It's used as an interface to improve data literacy. I've seen other organizations that have highlighted certain parts of the framework that will help people across the organization, that provides artifacts that will help people to become more data literate. People use it as an interface to improve engagement with the data stewards, with the subject matter experts, with the council within the organization, and they use it as a repository for all of those artifacts. So if you remember that slide where I shared the operating model and the common data matrix and the communication plan, you can actually start to go about storing your different key artifacts and intelligence about your program within the framework itself. So why is the selection of the framework and the approach critical? Well, I'll tell you this, that the approach that you take, so typically I consider there being three approaches to governance. There's the non-invasive approach. There's the command and control top-down approach. There's the traditional field of dreams approach where I use the line, if you build it, they will come, where you build a program and you hope people will gravitate toward it. And then there's the non-invasive approach to governance. It starts with the premise of we're already governing data. There's people within our organization that already have relationships to the data. There's plenty of those people. We need to help to hold them formally accountable for what they're doing. So if we assign people new roles, which is typically the way it's done in a command and control program, or we identify people into roles, which is a traditional way of implementing governance versus we recognize people for what they do, the approach that we take out of those three approaches will impact how the program is perceived and accepted in the organization. One thing that we need to keep in mind is that people in the organization, as we're implementing our governance framework, implementing our governance program, they have day jobs. So if you go and assign them a new role, it's immediately going to feel over and above what they're presently doing. You got to understand that since they have a day job, they're going to push back if they feel like you're being invasive in how you're approaching them about data governance. The term non-invasive may be misunderstood. I've been told by somebody that by being non-invasive, it's a do nothing approach. Well, actually, it's a do everything approach. It's a do everybody approach because anybody in the organization or everybody in the organization that has a relationship to data, and if they're being held accountable for that relationship needs to help to govern the data. This is not being done by a handful of people in the organization. It's actually being done by everybody. I use the expression everybody is a data steward quite a bit. The fact is that if we're going to cover the entire organization, everybody needs to be a data steward. You will win the data governance game when you've gotten to the point where they recognize themselves as being data stewards. How do we go about selecting the appropriate approach? First of all, understand what's going to be acceptable to your organization as you're filling out your framework. Make sure it's certain that you represent your organization appropriately within the framework, that you put strong consideration into what core components you include within your framework. Consider putting significant effort towards your messaging. Make certain that if you've tried to implement governance in the past and repeatedly it hasn't worked, consider what has worked and what has not worked in the past as you go and you set your plans for moving forward. Disruption of people and process is going to be viewed as a risky proposition within any organization. The last thing I suggest is if you want to leverage your framework to govern data within your organization, start with an assessment. Don't try to govern using the entire framework at one time. Use an assessment or use some tool to help to direct you to those parts of the framework that are going to be most beneficial to you. Align your framework to your present artifacts like I did with the different tools that I shared and the templates that I shared. Use the framework to highlight where activities are critical, where activities are on time, where activities are falling behind. That's what I mean by stop lighting your bridges. Make them red, yellow, and green in order to highlight where the activities are taking place within your framework. And then use a maturity evaluation based on the results of the information that you're completing throughout your framework. So in this webinar what I did was I provided to you in a very short period of time it felt a customizable data governance framework. We talked about how to determine the most appropriate components for your framework. How to determine the most appropriate levels to match what exists within your organization. We got into some detail and I provided you with questions that you might want to consider answering as you're filling in the boxes. And then last we talked about leveraging your new framework to govern data in your organization. And with that Shannon I'm going to turn it back to you to see if we have any questions for today. Thank you so much for this great presentation. If you have questions for Bob or for Susanna feel free to put them in the Q&A portion of your screen and just to answer the most commonly asked questions. Just a reminder I will send a copy of the slides and the recording by end of day Monday. Additionally I do have a lot of these templates from Bob already that's included in the follow-up email so those will go out as well. So diving in here to what extent is it useful for an organization to have to find a full data architecture data column in Zackman framework before starting a data governance program? Well from my experience and I'd love to hear Susanna answer this as well I would say you're probably not going to have it completed before you get started. I say that you could actually use the framework to help represent some of the things that you're doing within your organization. So if you expect to have every i dotted and every t crossed before you can even get started there are some columns of the framework that I would suggest that you focus on first like for example the roles column is really going to be critical as I mentioned it's one of the backbones of a successful governance program you're going to need to know what your executive level looks like all the way down to your support level and your administrative level of roles and responsibilities so my suggestion is no don't wait don't wait until you've completed the entire framework for for data architecture or for data governance that's my thought on it. Yeah Bob I would agree with that as well I mean I think you'll be in a situation where you're waiting for perfect where in a lot of your use cases and a lot of your opportunities good enough is fine and you're going to show real value and you can you know you're going to discover information in new ways new new things that you add to your framework as you go. So have you ever had to backtrack from a data governance framework you developed and what were the ramifications? Well I'm not sure what is meant by backtrack but have I needed to make changes to it I'd say that everything is fluid I would say that your data governance framework needs to be fluid too because if things change within your organization you want the framework to accurately depict what your organization looks like and what's important to your organization. If those things change then yes I've seen organizations that have gone and backtracked in that way or maybe changed I think that you're going to be more likely to need to backtrack if you follow with the first question that was asked was about is if you go and try to fill out the entire thing because you're going to find out that as you start to really focus in on certain parts of it it may have an impact on another part of the framework and so um yeah I I've seen organizations make changes I just think it needs to be fluid in general. Very nice and what is the difference between your framework and AI governance what additional components need to be added to your framework to make AI compatible? We can't get through one webinar can we without talking about AI. It is the hottest topic yeah it is the hottest topic and so there's two actually I have a perspective on that believe it or not um AI I consider there to be two actually aspects of governance there's there's governing effective use of AI within an organization and then there's governing the data that's going to be used within the AI interface that people are going to be able to see so I think we need to do both so certainly we need to govern effective use of AI I don't know of and I actually put a chapter in the second book on non-invasive data governance about the data governance challenges associated with AI I see it as being and people will not like this I see it as being another application of data if the data is sensitive it has to be protected if the data is being used to make decisions people have to have confidence in that data whether it's through AI AI is the engine to get people access to the data so I would say the same almost the same types I hear the term AI governance and yeah so which one are we talking about are we talking about governing the effective use of AI or are we talking about governing the data governing the data I would think would having a governance program would provide great benefit towards making certain that the data that is being exposed through AI is being governed that's my thought I'd love to hear Susanna's thought too yeah I would agree with a lot of what you said Bob one thing that I wonder about is how how do these AI systems and and I you know people use the term AI very broadly but you know are we talking about our large language models in their output or are we talking about machine learning and in predictive modeling that's giving us you know kind of data points like these are different types of things and I do wonder is there a different kind of data quality that we have to start looking at how the data inputs go into these models and what the quality of that data does and how it drives different outputs is that a different perspective that we need to start taking on on how we measure quality and then also is there a different kind of accuracy that we need to put on how we measure the outputs of the models whether especially with like a large language model is it actually outputting accurate information or is it just outputting well formatted information is that a new lens of quality and monitoring that we have to start considering I agree these are all things that need to be governed as well yes love it so you know we have about four minutes left I'm going to try and slip in as many questions as we have as we can get to but keep the questions coming and Bob will answer get written answers that it will go out in the follow-up email so would the data governance oops with the data governance digital framework be sure oh yeah we're going to share that and when an organization is just starting to build out their data governance framework what is the best starting point to not get lost in the end result well I think I shared a little bit about this before is is that I would start with the roles and responsibilities first and the because those are going to be included in your communications because we're going to communicate to people differently depending on what role they're in we're going to engage them in process we're going activate them to use an elate to make to turn it into active data governance we're going to activate people depending on what their role is and what relationship they have to the data so I would start by focusing on the role column and I think that it's if you have an established governance program there's a very good chance that you have some verbiage that you can use to start filling in the framework that way and then once you recognize what the roles are within the framework I would suggest working your way left and right in the framework and go understand what data is important to each of those different groups or or roles that you've defined and then I'd also determine what processes are they engaged in that need to be governed and then I would start to work my way further over so I basically would start in column two then expand out and then work your way across the to the right that's the way that I would suggest doing it but again there's organizations that have said okay we need to focus on this specific bridge and that specific bridge again just don't try to tackle the whole thing at one time yeah I would definitely agree with that like you may have you may have to launch a governance program because you have a huge compliance risk and maybe you have to look at it through that lens first but if you have the luxury of working with people and finding out what their business needs are and format formatting it through that role process that Bob described that's a great way to start I love it well that is bringing us to the top of the hour Bob and Susanna thank you so much and thanks to all of our attendees who have been so engaged in everything that we do thank you for all the great questions again I will get Bob will write answers to the questions we didn't have time to get to in the follow-up email which will go to all registrants by end of day Monday with links to the slides links to the recording and links to some of the templates that Bob was showing today so thank you everybody and hope you all have a great day and thanks to Elation for helping to make today's webinar happen thanks everybody thanks everyone thanks Elation thanks Susanna thanks for having us