 Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Manager of Data Diversity. We would like to thank you for joining the current installment of the Monthly Data Diversity Webinar Series, Real-World Data Governance with Bob Siner. Today, Bob will be discussing Data Governance Best Practices, sponsored today by Irwin by Quest. Just a couple of points to get us started. Due to the large number of people that attend these sessions, you will be muted during the webinar. If you would like to chat with us or with each other, we certainly encourage you to do so. And just to note, Zoom defaults the chat to send to just the panelists, but you may absolutely switch that to chat with each other. And for questions, we will be collecting them via the Q&A section. Or if you'd like to tweet, we encourage you to share highlights or questions via Twitter using hashtag RWDG. 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 additional information requested throughout the webinar. Now, let me turn it over to Danny for a brief word from our sponsor Irwin by Quest. Danny, hello and welcome. Hey, Shannon, thanks so much. It's a real pleasure to be sponsoring this. And thanks for the opportunity. As I thought, what could I add to Best Practices by Robert Seiner? There's not a lot, I think I can add to that. But maybe this will help. Taking a bit of a different tact, looking at what we've learned from our customers that we've worked with in the data governance arena in terms of critical capabilities or best practices around technology to support your data governance framework and your data governance initiative. So just a couple of quick things. Document and make sure you have the capability to document and version everything. Anything in your data world, both the physical world as well as in the entire framework that you have and want to build around that data to support the data governance. It's key that you're able to find a place for that and bring that into a centralized space so that you can then practice data governance upon it and share that out with everybody else. It's also very important because very strong in supporting the auditability of everything that you're doing with data governance, whether it's for specific compliance or any other reason that you may have. So make sure you can get that whole physical world, data stores, data models, data movement processes all the way to data consumption. Bring it into an area with all of your reference data so that you can see that and then make sure that you can then build that framework in a way that makes sense to you. So, you know, terminologies, policies, rules, but anything else that you might want to document and bring in and bring visibility to and associate with that data governance framework. Once you've done that, automate wherever possible. We hear this all the time. Make sure that, you know, what you have in that framework is always up to date and the way that you can do that and make sure that it has the highest degree of integrity is to automate those processes, whether it's bringing in the current and most up-to-date version of what's going on in the real world, whether it's taking the framework that you're building and associating that down using artificial intelligence or the automation of insights that comes from this collection, data lineage impact analysis, self-service navigation aids, you know, workflows. Make sure that's automated wherever possible. And then finally, make sure that where you do your work around data governance using that catalog and that business glossary is well connected and visible to all the other important pieces that are out there. So, you know, connect with your data modeling, make sure that your design and your standards are reflected in your governance and you can track all the way back to that. Make sure that you have connectivity with your data quality, your DevOps, your data ops, making sure that your pipelines are efficient and getting data to the people that need it when they do, you know, having that completely connected with governance is key and critical. And then, of course, you know, moving out through enterprise architecture to the wider organization, make sure that you can connect with, you know, all of the key players that are going to want to consume what you have from a data governance perspective as well as understand and assure what you're doing so that they can make that part of what they're doing. So, you know, portfolio management, transformation and innovation, risk and compliance, there's a lot of key parts of the organization that you want to get connected to and make sure that you maintain that connection to be able to collaborate effectively with them. So, you know, when you do that, you bring it all together. Really, when you look at the technology, you want it to be able to harvest everything that you have, give you the capability to curate that and bring all sorts of extended metrics and visibility and understanding context to that data, apply the governance to that data in a way that's effective and non-invasive. Activate this whole framework to be able to then start providing insights and information to all of the different stakeholders and be able to socialize that in an effective way. So, that's it from us at Irwin. If this is something that you're at a stage of looking at or want to talk about, please come and visit us at Irwin.com. We'd love to understand what you guys are doing and how we can help. With that, I'll pass it back to you, Robert. Annie, thank you so much for this great presentation and for kicking us off. And thanks so much to Irwin by Quest for sponsoring today's webinar and helping make these webinars happen. If you have any questions for Danny or about Irwin, feel free to submit them in the Q&A panel, as Danny will likewise be joining us in the Q&A portion of the webinar at the end. And now let me introduce the speaker for the series, Bob Siner. Bob is the president and principal of KIK Consulting and Educational Services and the publisher of the data administration newsletter, TDAN.com. Bob specializes in non-invasive data governance, data stewardship and metadata management solutions. And with that, I will give the floor to Bob to get his presentation started. Hello and welcome. Hi, Shannon. Hi, thank you, Danny, for the wonderful lead-in to my presentation today. Welcome, everybody. I'm really happy to have you with us today. Today, as Shannon mentioned, we're gonna talk about data governance best practices. And I often say this about my webinars, but this is a really important subject. And in fact, most of the organizations that I know that have been successful with data government, implementing effective data governance programs, start with best practices, whether they're assessing what it's gonna take to stand up a program at the beginning or whether or not they're looking at a program that already exists within their organization and looking for ways to be able to improve on the program. So this is always a good topic and I'm happy to have you with us today. And for those of you in the United States and those that celebrate Thanksgiving, I wanna wish you an early happy Thanksgiving. To next week at this time, we will all be engaging in the celebration of the holiday. So happy Thanksgiving to all of you that celebrate. A little bit before I get started here, I just wanna share some of the few things that I'm doing and involvement in the industry. As you know, because you're here, there's the monthly webinar series, Real World Data Governance. And next month I'll be talking about data governance and metadata management. So looking forward to having you there. And then we've already started to define what the series of subjects are gonna be that we're gonna address in 2022. So we hope that you'll come and join us there and there and then. I also wanna again, share information about my approach to data governance and the book that I wrote on data governance called Non-Invasive Data Governance, the path of least resistance and greatest success. You can find it at a lot of places if you're interested in learning more about non-invasive data governance. I'll be speaking at an in-person data governance, or I'm sorry, in-person data diversity conference in three weeks in San Diego, the Data Governance and Information Quality Conference, otherwise known as the DGIQ conference is taking place the second week in December. And also I've just learned that I will also be speaking at the Enterprise Data World event also in San Diego in March of 2022. If I don't see in a couple of weeks in San Diego, I certainly hope to see you in San Diego in the spring or should I say the late winter, maybe so to speak. So also available online through the Data Diversity Training Center. There's a handful or actually there's three online learning plans that are available. One is on non-invasive data governance. One is on non-invasive metadata governance. And then the most recent one is one that focuses on business glossaries, data dictionaries, and data catalogs. As Shannon mentioned, I'm the publisher of the Data Administration Newsletter, tdan.com. If you're not familiar with it, please go out, take a few minutes and take a look at it. A new issue was published yesterday. It's got free content on data articles, data columns, blogs and features. So please go out and check it out if you have not seen it yet. My primary business is my consulting and education business, KIK Consulting and Educational Services, where KIK stands for Knowledge is King. So the focus of my practice is to transfer best practice knowledge to my clients and anybody who will listen on the receiving end of the knowledge transfer. And then recently I have become an adjunct faculty member at Carnegie Mellon University here in my hometown of Pittsburgh, Pennsylvania in their Heinz College Chief Data Officer program and their data-driven leadership program, which is focused on the US Army. So what am I gonna talk about today when it comes to best practices? Boy, there are a lot of different things that you can say about best practices. In fact, I'm really gonna help to focus on what it really takes to assess your organization in comparison to the best practices that you define for your organization. So the first thing I wanna talk about is the value of performing an assessment against best practices. I'm gonna provide to you a list of best practices that I've used that I've accumulated over the years of doing many of these types of assessments for organizations. I'll help you to determine what is an appropriate best practice for your organization. So what criteria can we use to determine if a practice is a best practice for your organization? I'll talk about some steps to follow to complete an assessment. And then I'll provide a kind of a sneak preview of what might be some of the recommendations that you can expect to see after assessing your organization against best practices. And so the recommendations, they may be actions that you're already taking, but oftentimes organizations are looking for well, why are we taking these actions? So it makes sense to do an assessment prior to just jumping into what those specific actions are gonna be as you start to roll out your program or start to make improvements on your governance program. So before I get started, and I know I do this a lot in my webinars, I definitely wanna go quickly at least through the definitions that I use. Because a lot of people who may not attended these webinars in the past may not know how I define these things, but real quickly I'll go through them data governance. And I word this very strongly is the execution and enforcement of authority over the management of data and data related assets. I know, like I said, it's worded strongly, but you want to get people in your organization to sit forward and listen and question what you mean by executing and enforcing authority. Some of my clients actually temper that definition and use more of a stewardship definition as their definition for governance. But at the end of the day, no matter what approach you take, whether you take the noninvasive or a command and control or a traditional approach to governance, at the end of the day, you need to be able to execute and enforce authority over the management of the data. And that means to improve quality, to improve the protection of the data, to improve the understanding of the data. So I like to work with a very strong definition of data governance. Data stewardship is the formalization of accountability for the management of data and data related assets. I've been known to say, I don't think I actually have it plugged into this webinar, but I've been known to say that everybody in the organization potentially is a steward of the data. If they define data and or produce data and or use data as part of their job and they're being held formally accountable for how they define producer use data, they're a steward. And so oftentimes I get asked, well, what does it mean to be held formally accountable? That's something that you really need to determine within your organization. But if you think of all the people who define, produce and use data in the organization, that could be everybody. So if you want complete coverage of your organization, you need to at least consider the fact that everybody in your organization is a data steward. And I tell organizations, they really need to get over that fact. If they want to have complete coverage for the organization, everybody can be a data steward. Metadata is, I define it as data that's stored in IT tools that improves both the business and technical understanding of data and data related assets. So metadata, as Danny was talking about, this doesn't really become valuable to you until you store it somewhere and you make it available to people. So that's my definition. I know a lot of people talk about metadata as being data about data. Well, this is my definition that I use for metadata. And a steward, as I mentioned before, is a person that is held formally accountable for the actions that they take with data. And then metadata management is really that action of managing the definition, production and usage of the metadata, the way that I just defined metadata here. So let's start focusing on best practices and let's talk about what the value of performing a best practice assessment will be to your organization. So oftentimes when organizations are getting started or they're looking at revamping the things that they're presently doing, they need to be able to justify the actions that they're taking in order to govern data effectively in the organization. And if you start with an assessment, then you're pretty much assuring yourself that you're taking a ready aim fire approach rather than taking a ready fire aim approach. And you wanna have a plan, you wanna have reasons for the actions that you're taking for the recommendations that are being given out of the assessment to move your program forward. I'll talk about engaging a stakeholders, how the assessment really precedes the roadmap in the action plan. That's part of that ready aim fire approach. And then we'll talk about what types of requirements are necessary in order to conduct a data governance best practice assessment. I do a lot of assessments for organizations around the US, around the world. And typically I suggest that there's four primary staples that need to be put in place when you're starting a governance program. And it shouldn't surprise you that I believe that one of those staples is that assessment or a critical analysis. Some organizations don't like to pay for assessments anymore. So if you call it a critical analysis, there may be a better chance that they would conduct a critical analysis rather than an assessment. But then from the assessment, the recommendations feed into that roadmap and action plan. I've given a lot of webinars and presented a lot about roles and responsibilities. I won't be going into a lot of detail about roles and responsibilities, but I will share my operating model as part of this webinar. And then there's the communication plan because we realized that communications, it can't be emphasized enough within organizations. We need to communicate to people what data governance is all about, what stewardship is all about. We need to onboard people so that when they play a role, they understand what their role is and how to conduct themselves appropriately in that role. And that's all part of the communication plan. So like I said, the four staples that I typically suggest to organizations that they get started with is that assessment, that roadmap, the roles and responsibilities and the communication plan. So I mentioned that I wanna talk about justifying the actions that you're gonna take. So best practices, first of all, I think it's a very important statement to make that the best practices that I'm focusing on here are the best practices that are required to stand up an effective program in your organization. These are not best practices for day-to-day routines of defining, producing and using data. These are best practices that are really focused on taking your program, delivering and developing and delivering an appropriate governance program for your organization. So when I share the best practices with you in a couple of minutes, you'll see that they're really focused on what are the things that need to be in place in order to be successful with data governance, not just for the immediate term, but for the long term within your organization. And so what we're really doing here is so we're doing an assessment about what is it going to take to stand up an effective program, but realizing that a lot of you out there may already have existing programs in your organization. You could also use these best practices and say, well, how do we compare to these best practices? So we even know what the appropriate steps are to take to improve an existing program that we already have up and running within our organization. And so basically what you're doing is by doing an assessment, you're planning to develop a plan. Again, you're not taking a ready fire aim approach, you're taking a ready aim fire approach. And I know that from talking to a lot of organizations that they really wanna start by doing, they wanna start by governing data. And that's not always the best approach to take when you may wanna consider what are the things that we're gonna need to put in place to make certain that our activities of governing data aren't at risk at some point in the future. So instead of starting by doing, let's start by saying, where are we in comparison to what industry, what other organizations, what our organization says are best practices for us to get started. And then we can start to say, well, where's the gap between what we're doing and what the best practice says we should be doing? And so that will be helping you to develop the plan, those actions that you're going to take to move yourself closer to what you would consider as best practice for data governance within your organization. And oftentimes instead of just starting by doing, we're gonna justify the actions that we're gonna take. And it becomes an important, the assessment becomes an important artifact that you can share with the appropriate audiences in your organization. So not only do they understand what best practices are, but they understand what the present state of your organization is in comparison to the best practices, where there's gaps, where there's risk associated with gaps, of the gaps between where you are and what the assessment says. It's really an artifact that helps people again, to understand the approach that you're taking to implement an effective program for your organization. I told you I was gonna share my operating model of roles and responsibilities with you, but I'm not gonna go into this in a lot of detail with the exception of the fact that there's different types of stakeholders in data governance at different levels of your organization. There's people at the executive level that really need to know what governance is. They need to really support, sponsor, and understand the activities of data governance. And you'll see that as a best practice when I list out some best practices for you. And then there's the strategic people in your organization, oftentimes referred to as a data governance council or committee or at least the business representation at the strategic level for making certain that governance is operating properly. And then there's the tactical people in your organization. Those people who are the subject matter experts of the data, kind of the go-to people when you've got a question about data, they may in fact be the authorities on certain types of data, but the people at the tactical level are looking at data across the organization rather than just siloed within their individual business unit or business function. And the operational audiences are the people that are most concerned about the data within their business function or within their part of the organization. All of these people, you might want to engage at least some of the people from all of these different audiences when you're doing an assessment. And there's also the support audiences, which would be the people that are on your core data governance team or the different partners of governance through the organization, or even the working teams as you start to pull together stewards to help you to either resolve data issues or to address opportunities to improve the data. You need to look to see who are the most appropriate people in the organization to engage in the best practice assessment. You're not going to engage everybody. And in a lot of organizations, they may even start focusing on people that are specific to specific use cases. So what are we going to direct our program at? Is there data issues around critical data elements that we need to improve? Are there opportunities to improve the efficiency and the effectiveness of the organization when it comes to the management and the manipulation of data across the organization? You might want to consider that some of the stakeholders to engage in your best practice assessment might be some of those key people that are going to see value of the initial use case in any successive use cases that you have within your organization. So when you're conducting the assessment, take a strong look at who are the people that would probably have the best information to really help us to recognize where we are in comparison to the best practices. And when you do the assessment, as I said before, or if you're taking the ready aim fire approach, the assessment is what precedes the roadmap. Certainly you can start with a roadmap, but if you don't know, if you don't really have a target that you're shooting at or that you're aiming at, it's going to be more difficult to define those specific actions that are going to be important to your organization. So oftentimes you need to create the best practices you need to assess with the appropriate people against those best practices. Oftentimes the assessment will result in recommendations. And I'm going to share with you a series of a bunch of different recommendations that many of the organizations that I work with have followed, but then the recommendations can turn into actionable streams is what I refer to them as. And those actionable streams are the things that are going to plug into your action plan or your roadmap. So again, taking a ready aim fire approach, you want to make certain that you are directing your actions at specific things that are now recommendations of the assessment against the best practices. And so since we know that the assessments aren't going to conduct themselves, there are certain requirements. There are things that are required when you're conducting an assessment. Well, first of all, you require resources that are going to help you to define what the best practices are. And like I said, I'm going to provide you a list of 10 or 12 best practices that you may want to consider for your organization. But it also requires resources to prepare these best practices to conduct the assessment and bring the appropriate people in at the appropriate time to conduct the assessment. It requires stakeholders across the organization, like the ones that I mentioned in those different levels of your organization to participate in the assessment. It requires resources to prepare the assessment artifact. And in fact, I'm going to outline for you what would typically go into a data governance best practice as you're starting to develop something like this for your organization. So that's kind of the importance, the reason, the justification of doing a best practice assessment before you start to developing your plan and before you start operationalizing your data governance program. So the next thing I want to do is I want to share with you what some of these best practices are and how you can determine how to script and how to write the appropriate best practices for your organization. So I'm going to talk about why the best practices are important, characteristics of a productive best practice. And I'm going to share with you best practices that are selected all the time by organizations or at least the vast majority of the time by organizations I work with, but also ones that I consider to be best practices that aren't selected as often when organizations are doing their best practice assessment. So the first thing is, and I want to go back to what I said before, is that these are best practices that are associated with standing up a program or assessing an existing program so that we can make improvements to the program. And so the definition of a best practice, and I think this really makes sense when it comes to data governance best practices, they're procedures that are accepted or prescribed as being correct or most effective. And the best practices that I'm going to share with you are the ones that I have found to be most correct or at least most effective in the organizations that I've worked with. And when you're building out a roadmap and an action plan, you want to very clearly define the target not only to assess against, but to define the target of the activities that are necessary to either improve your program or stand up a new program. So again, not day-to-day best practices for defining, producing, and using data, but they're the appropriate actions that are necessary to stand up a formal program. And so a lot of organizations use the term best practice in a lot of ways. It's typically a way that organizations are preparing for the actions that they are going to take. So best practices are important in a lot of ways, especially if you are starting from scratch or assessing an existing program to define those actions that need to be taken to move your program forward. So what are some of the things that are characteristics? See, I'm kind of building up to the crescendo here of sharing the best practices with you. But I wanted to share with you what are some of the characteristics of a useful or a productive best practice. First of all, there's the two criteria that I use to determine if something is best practice. I'm going to share that with you in a second here. But we don't want the best practices to be lengthy. We want them to be memorable. We want them to be focused. So limit your verbiage. And you'll see how I've limited the verbiage on the best practices that I share with you. The other thing that I learned this over time of doing the assessments is that oftentimes you want to define your data governance best practices in the present tense. Instead of saying, we will do this or we should do this or we must do this, start with we are doing this as the best practice and then say, well, are we doing it? How well are we doing it? Where is there things that we can leverage in the organization? Where is there opportunity to improve? But I move from having them being written in future state to being more in the present tense. So we're evaluating against this as this is best practice for our organization right now. And I also suggest underline the key terms in your best practices that need to be defined. Because as you're defining best practice, you're going to find that there are key terms that people may not understand across the organization. So first thing I want to do here now is share with you six commonly used best practices that organizations assess themselves against as they are standing up their program or looking for ways to improve their program. So the first one, if I told you that that first best practice of senior leadership supporting, sponsoring, and understanding the actions of data governance, if I told you that 98% of the organizations I work with use that as a best practice, I'd be lying to you. It's 100%. Organizations realize that in order for them to be successful, their senior leadership need to support, sponsor, and most importantly, understand the actions that are being taken by data governance. So that one is used 100% of the time as the very first best practice. And if you define this as best practice, then you need to make certain that you're talking to the right people in the organization to determine how well your senior leadership support sponsor and how well they understand the actions of data governance or governing data in your organization. The second best practice is used as a best practice most of the time as well, which is that you need to have resources allocated to administering your program on a continual basis. And the reason we call it a data governance program instead of a data governance project is that projects typically have a beginning and an end. And programs are something that are gonna be with you for a long time. In fact, if you build data governance into what you do in your organization and it becomes second nature to your organization, you've won the data governance game because it's now second nature to people. They're doing it as part of their job. So you need to have resources that are allocated to administering the program. This needs to be done on a continual basis. The story I tell quite a bit is how a chief financial officer of one of the larger banks in the United States asked me, how many stewards are we going to need and how long are we going to need them for? And I kind of cracked a smile when he said that and I knew the guy quite well. And I looked at him and I said, well, how long, it all depends on how long you wanna have quality data for. Or you could say, it all depends on how long you wanna protect sensitive information. Well, that CFO actually looked at me kind of nodded his head and said, okay, I get it. This is not something that we're doing short term. We need to have the program activated forever. And we need to have people that have the responsibility for administering the program because the program's not gonna administer itself. So as a second best practice, that one's critical to most organizations and most of them use that as the second best practice as you will be at risk if you don't have anybody who is captaining the ship of data governance. Then the goals, scope, expectations and metrics that are defined and approved. That's a relatively easy best practice to assess against because either you do or you don't. I often say that some of these best practices are more binary than others. And so maybe you haven't defined what the goals of your program are, what's in scope, what the expectations are, how we're gonna measure the program. But that's a real effective best practice because what happens is if you find out that you're not really doing that or you haven't done that yet, it gives you some actions that you need to take as you start to roll out your program. So those first three, those are critical best practices and they're used very often by organizations. And that's why I marked on the slide. This is an important slide because if you're thinking about doing an assessment, you may wanna consider that these are best practices for your organization. And here I underlined the words that say, okay, we gotta define what senior leadership is. We gotta define what data governance is. When you're talking about resources and allocating them, you wanna define what those things are and on a continual basis. So I suggest if you're sharing best practices, also share those key words and provide definitions to those words that are being underlined. Some other best practices that are used a lot, the roles and responsibilities are clearly defined. We know that roles are an important aspect of a successful governance program. So we need to define clearly the roles and responsibilities for governance across the organization. Policies and guidelines as the backbone of the program, whether or not you have or need a data governance policy, that's really dependent on the organization, but you certainly wanna provide guidelines to people to help them to understand what governance is and how they can help to govern data most effectively across the organization. And the last one that I'm sharing that's most often used is that governance is being applied consistently across the organization and across all different data types, whether it's your big data, it's your master data, whether it's your metadata, your BI data, any data you wanna be consistent with the way that you're applying governance across the organization. So those six best practices are used often when organizations are beginning to assess where they are so that they can define how they're gonna get started with their program. Here are some that are not used as often, but they're still important is that the data stewards responsibilities are recognized rather than assigned or identified, I use the term recognized because it has a positive connotation that goes with it. When people are assigned things, they immediately feel like it's over and above the things that they're presently doing. So I like to use the word recognized instead of assigning people or identifying people. It just, it means that somebody who's using data that's sensitive, we're gonna help them to understand the rules associated with how they need to handle the data that is sensitive. Data governance and stewarding of the data is really part of people's everyday job. So we don't need to change their titles. We don't need to call them data stewards, but if they define data as part of their job or they produce or use data as part of their job and they're being held accountable for how they define, produce and use data, they're data stewards. It's not something that typically in organizations that follow the noninvasive approach, it's not typically something that people can opt into or opt out of. They're basically a steward based on their relationship to the data that they define, produce and use and that some additional best practices individuals that are recognized as being holding these rules that oftentimes they're evaluated based on not only their willingness to participate, their ability to participate into the obligations of the roles that are being defined for people that have those relationships to the data. And the accountability for the management of data definition, production and usage really is the responsibility of everybody in the organization. If you want to cover the entire organization, you may have the fact that everybody might be a data steward or many of the people, it's not just the few people that traditionally are assigned into steward roles, potentially everybody in the organization is a steward of the data. So let me quickly just go through two criteria that I use to determine if something is a best practice. I'll talk about why the criteria are important and how you can include them in the assessment. Well, first of all, why are criteria important? Well, because you need to be able to test the statements that you're making against whether or not, whether they fulfill the appropriate principles to be considered best practice within your organization. You need to justify why the best practices were selected again, falling down on that criteria that's gonna be on the next slide here. You need to share the criteria with people that are participating in the assessment. And you need to demonstrate that this is how we determine what was best practice for our organization. So the two criteria, and again, I listed this as being an important slide, is it's gotta be practical and doable within your organization, within your culture, within your readiness. Don't define best practices that are undoable within your organization or that aren't practical for your organization. So ask the question, is what we have defined as best practice, practical and doable within our organization, like senior leadership, supporting, sponsoring and understanding data governance. Is that practical? Are we gonna be able to do it? Certainly we can direct our attention and our communications at executives and help them to better understand the governance, what governance is. So typically those best practices that I shared with you, if you're gonna utilize them, they would have to be practical and doable given your organizational culture and your organization's readiness. The second criteria is even more important. So we know that needs to be practical and doable, but consider that the program and the activities of governing data in your organization are going to become at risk if this best practice is not achieved. If we don't have senior leadership support sponsorship and understanding of what governance is, is there a chance that governance is gonna be decreased and important at some point in time? How practical or should I say, how important is it to have somebody who is leading the charge, a data governance administrator or manager or data governance office? And what happens when you no longer have an administrator or a manager or an office? Well, immediately your program is going to be at risk. I've done assessment for organizations that didn't know where governance was gonna reside in the organization, didn't know who was gonna have the responsibility for managing the program. And I call it out as a huge risk to them that if you don't have somebody who has that responsibility immediately, your program is going to be at risk. So oftentimes I suggest that you include the criteria within the assessment document that you're building, share the best practices in the assessment, share the criteria that were used to determine if something is best practice in that document as well, specify the importance of the criteria that go along with each of the best practice. So how important is it to your organization that your senior leadership support sponsor and understand the activities of data governance? So specify the importance of the criteria and then how practical and doable is it and what are some of the actions that we're gonna need to take to help our senior leadership to become able to support sponsor and understand what it is that we're doing. And oftentimes when you share the criteria with people, it really leads into the questions that you're gonna ask to address each of the best practices. And I'm gonna share those with you in a minute as well. What typically goes into an assessment of your organization. So let's talk about that right now. Let's talk about the steps that are necessary for you to follow to complete an assessment. And we'll talk about the best practices for, what are the best practices around creating best practices? I've already shared a little bit of that with you, recognizing the appropriate stakeholders to include in the assessment. And what you can do with those best practices prior to even holding the meetings to conduct the assessment, conducting the assessment itself and then the results, what that kind of turns into when you define what the critical analysis is based on the assessment. So begin with proven industry best practices, whether you use the ones that I've just shared with you and that were noted as being important slides in this webinar, or go out and do a search and that you'll find a lot of information about best practices. I'm just gonna suggest that you focus on the best practices that are necessary to stand up an effective program within your organization. So follow the best practice criteria of is it practical and doable and is it gonna be at, are we gonna be at risk if we don't achieve these things, engage the appropriate people in the organization? And I talked about those stakeholders a minute ago and I'm gonna talk a little bit more about that in a second. Do what you need to do to prepare the people who are participating in the assessment in advance of the meetings. So they know what you're gonna be talking about, what questions you're gonna be asking them. And then don't stretch out your assessment meetings over a prolonged period of time, focus on conducting your best practice assessment meetings over a relatively short period of time. So recognize that who are the appropriate people to include in your assessment from those levels that I talked about in terms of the operating model, the executive, strategic, tactical. Now identify the people that are gonna be engaged in the initial use cases or the pilot or the proof of concept of governance in your organization. And these people could be both business and technical people because there are people in IT that are stewards of specific data in the organization. Oftentimes I hear that, we really want to focus on the business, but if we only focus on the business and we don't focus on the technical aspects of the organization, it's gonna be like we're implementing a governance program by tying one hand behind our back and recognize what people are gonna be engaged in the different roles that you associate with your governance program. So create a best practice questions and questionnaire. And in fact, I'm gonna share with you a bunch of questions that you might wanna include in the assessment meeting itself, but also within the questionnaire. So one of the first questions you might wanna ask right out of the gate when you're meeting with these stakeholders is what are some of your biggest challenges around data? What can't you do because the data is not there or you don't have confidence in the data to do it and what would you be able to do if you had the knowledge and the confidence in the data and you can get your hands on the data to be able to use it? You wanna answer the question, why each of the best practices is best practice for your organization? And then really focusing on the stakeholders, what do they see that you're already doing that you can leverage towards the best practice is why reinvent the wheel if you're already doing certain things that are gonna support the movement towards best practice and where is there opportunity to improve? And those last two questions, in fact, the ones that I've highlighted here, these are the questions that you're gonna ask people in the meetings. What are their biggest challenges around data? And hopefully it would be like opening the flood gates, they can tell you all the problems that they're having with data or what they would do with the data if they had the confidence in the data. But you might wanna consider as the person that's conducting the assessment to answer the question, why is this best practice for the organization? And then ask them, what are we already doing that we can leverage and where is there opportunity for us to improve towards the best practice? And then the questions again, now that you'll consider completing when you are completing the assessment yourself is where is there opportunity to improve towards the best practice? What's the gap between what you're doing presently, what your organization is doing presently and the best practice that you've defined? What's the risk that's associated with that gap? And what are the things, what are the steps that we can take to narrow or to eliminate the gap between what we say is best practice and how our present organization is acting towards the best practice? So those are really important questions and you might wanna consider using those when you're conducting an assessment. I know I use questions like that all the time when helping organizations to assess their present state. So conduct the best practice assessment, provide the questionnaire in advance, assemble the participants into logical groups, spend a little bit of time in the meeting, helping people to understand what data governance and data stewardship are. And typically I suggest to schedule an hour because an hour should be sufficient. That might be all the time they can give you to begin with, but you can orient them to the ideas about data governance. You can orient them to the criteria you're using for the best practices. It may give them some time to present some of the challenges that they're having, but certainly when you collect the information, when you build out the findings from your assessment, share those results with the people that have participated in the assessment so that they understand that their time wasn't wasted and the value that you got out of having discussions with them. And typically when you're creating a critical analysis, I wanted to just outline for you what the sections of a critical analysis or an assessment might look like. So it would be an executive summary, which are, well, what are the expected outcomes? What method did we use to prepare this assessment? Who participated? And then you might have a preface to the rest of the document that tells it, what's the definition we've used or selected for data governance and data stewardship? What's the purpose? What's the focused purpose of why we're putting our governance and program in place and what the best practices are? The preliminary results would include the recommendations that are going to come from it. And again, I'm gonna share with you a series of those recommendations here in a minute. And then turn those recommendations into actions that you can take in the organization and provide a notional timeline of which actions are dependent on other actions, really outline a timeline for how you're gonna take those recommendations to heart and you're actually gonna create them into actions that you can act on within your organization. You may also wanna consider including your key findings. And so what did we learn from the people that we talked to in relationship to each of the best practices that we used in the assessment? And just to share with you, typically an organization has anywhere between four to six best practices that they use. If you have more, it may be, you're gonna get repeat of information from people if you have less, you might not be doing enough. So typically organizations have between four to six best practices when they are assessing where they are and what the actions are that they need to take to implement their program. And then in the back of the document, usually there's the assessment details. What are the questions that we got to each of those best practice questions that I just shared with you? And then at the back of the document, consider having an appendix that would list out who did we meet with? When did we meet with them? What do those terms that were underlined in the best practices, what do they mean? How are we defining them within our organization? So again, the things that most people will read when they read through the assessment are gonna be that exact summary, that preface so they understand how you're defining things, what the purpose of governance is, what the best practices are, your preliminary findings. A lot of times they may even stop after they see what the recommended actions are and the streams that are necessary to implement an effective program. And then the key findings, they may get that far. Sometimes you always want to provide the detail, but oftentimes people are gonna focus on those things that I've highlighted here. So let's talk about some typical recommendations and the actions that would result from an assessment and then I'm gonna throw it back to Shannon and see if there's any questions regarding the webinar today. So I'm gonna share with you the list of typical best practice assessments, how to go about sharing the assessment results with the appropriate people and then the recommendations being used to feed the data governance action plan and roadmap. Again, taking a ready aim fire approach instead of a ready fire aim approach. So these, this is another important slide. These are recommendations that I see repeatedly being used in organizations. And the first one is to develop and deploy a data governance operating model of roles and responsibilities. Roles and responsibilities are the key. They stand behind almost everything that you do from communications to activating people as part of procedure and process from a list of accountability, who's accountable for what? Well, at what level of the organization, every organization recognizes that data governance roles and responsibilities are key. And so that needs to be a recommendation that comes out of your assessment in most organizations. I talked about the importance of data governance communications. So we need to develop an act on a governance communications and awareness plan. Again, that becomes an actionable stream within your roadmap or action plan. We need to design and deliver not only a data documentation platform for your data catalog or your metadata, but also a program platform, which helps people to become more knowledgeable about what governance and stewardship and metadata are and how we're addressing these things across the organization. So I used to say, design and deliver a program data documentation platform. And I added the word and in there because they're really two different things. There's the program documentation and then there's the data documentation, define and deliver the core components of a successful program. And oftentimes those things would be the data you're gonna focus on, the roles, the processes, the communications, the metrics, the tools. Those are things that I consider to be core components of a successful governance program. And some additional recommendations is identify, organize, place and deploy the appropriate person or people that are going to captain the ship that are going to be the data governance manager or the data governance office, design and deliver stewardship guidelines. That's an important action that organizations must take when they're implementing their program, define and deliver a set of performance metrics so you can articulate to the organization those things that are important that are gonna add value to the organization. You need to be able to measure what governance is doing for you in order to be able to sustain your program longterm. And then I always suggest not taking a big bang approach and trying to govern all your data at once, make certain that you develop actions that you're gonna focus on to incrementally roll out your program. So those are, I shared with you, and I hope this isn't gonna help you bypass the need for the assessment, but I shared with you the best practices that are used most often and the results that typically come from doing an assessment, but you may want to understand to make certain that these things are appropriate for you and for your organization. So you wanna share this with the information in this assessment with the participants, with your core team focused on governance, share it with your executive sponsors, your counsel, or make it available through your homepage for data governance within your organization. Just make certain that when you've taken the time and the effort to conduct the assessment that you're sharing it appropriately with the appropriate people across the organization. And the last thing I wanna tell you is kind of where those recommendations fit in. When you're creating an action plan, you're gonna again have an executive summary. You're gonna outline what the actionable streams and the timeline are. You're gonna define what activities need to take place to properly deploy your program, your technology infrastructure roadmap, and then detail out what each of the actions are that you need to take to deliver on each of these actionable streams. And so again, like I said, these are the ones that are highlighted in brown here are the ones that are gonna be most read by people. They wanna know what are we gonna do about governance in the organization. And so I shared with you information about the value of performing the assessment, the best practices themselves, the criteria to determine if it's appropriate as a best practice, the steps to follow to do the assessment, and then typical recommendations that come out of the assessment. And with that, I'm gonna turn it back to Shannon to see it looks like we've got a bunch of questions today. We do a lot of great questions coming in and keep them coming in. If we don't have time to get to them all, we will absolutely get them over to Bob to get the included in the follow-up email, which will also include, which we've got to all registrants by entity Monday, including the slides and the recording of this session. So diving in here for both you, how does data governance overlap with business process management? I see the lack of formal business processes leading to data management and ownership challenges. Well, I'll answer it first. And then, Danny, you're welcome to chime in. But procedures, the processes have to be formal. And you need to engage, and I talk about it oftentimes as the data governance bill of rights and the word rights is in quotes. So it's getting the right people engaged in the right process at the right time for the right reason, using the right data. And so I think that data governance overlaps significantly with business process and business process re-engineering because when you're re-engineering a process, you wanna make certain that all of those rights are being addressed. So I see significant overlap between the two. Yeah, and Rob, I don't have a ton to add to that other than we see that with our customers where data governance is hampered much in the way that was described in the question by that lack of formal management. So having visibility in both ways, the knife cuts both ways, right? You want in your business process definition, understand the governance implications, what's going on around that data and what do they need to build into that process. And then, of course, going back the other way is you're making decisions on how to govern that data and what to govern about that data. You have to understand how it's being used. And again, if there's a lack of definition on either side of those things, then you can be subject to a little bit of the Wild West. So what would be an optional number of metadata categories for the data catalog items? An optimal number? Yes. With number, and so that's a great question. And again, I wanna hear what Danny has to say about this, but it really depends on what is important to you. And there's a lot of different categories of metadata. There's data-based metadata. There's data stewardship metadata. There's data movement metadata, like the lineage. There's data understanding, the dictionary and the glossary of the terms. There is tool-based metadata. So I don't know if there's an optimal number. I wouldn't try to embrace them all at the same time, but maybe Danny, you have a better answer to that question as to what are the optimal number or categories of metadata, number of categories that you might wanna focus on when it comes to your metadata solution? Yeah, I like to keep things reasonably simple and hide the complexity behind that simplicity. So I'll stick with a Fibronacci number and go with three. Technical business, technical comma business and process metadata. But as you just stated, Rob, there's so much that goes beyond that, like in our subcategories, I guess, of those categories. So you absolutely need to know the structure of your data. You need to know the business rules. You need to know the business description or business purpose who owns it. All of that good stuff, but then as you said, how is it being used? Where is it being used? Why is it being used? All of these things are going to bring context into and help you understand the data for your consumers and how to use it, how not to use it for the people that are managing it, the things to be aware of. And then for the owners and the stewards and the folks that are in the trenches of governance, what is it that we need to put in place to have that authority and accountability, right? So a lot, but you definitely need, I think those top three categories and a view into all of them to really get a full picture. I like that number of three. You have business, technical and process. And in fact, and I just wanted to share this with folks that if they go out to tdan.com, they go out to the data administration newsletter. There are articles that I've written that have outlined different categories of metadata that you might want to consider. I've also written about what are some of the questions that the metadata in each of these categories are able to answer for people. So that's a very valuable resource. It goes beyond the three, Dan, that you just talked about, but it covers a whole bunch of different categories of metadata. Absolutely. All right. Well, that unfortunately does bring us to the top of the hour here. That is all the time you have questions, feel free again to add more questions to the Q and A. I will get those over to Bob to write up the answers to be included in the follow-up email, which will go to all registrants within the next two business days. So by end of day, Monday, with links to the slides, links to the recording of this session. And thanks to Irwin by Quest for sponsoring today's webinar. Danny, always a pleasure to have you on these webinars with us. Thanks to all of our attendees for being awesome and amazing and engaging in everything we do. Hope to see you in the next webinar. Thanks, y'all. Have a good one. Thanks, Bob. Thanks, Danny. And happy Thanksgiving, everybody. Thanks. Thank you.