 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 do-it-yourself data governance framework sponsored today by Data.World. Just a couple of points to get us started. Due to the large number of people that attend these sessions, you will be muted during the webinar. If you'd like to chat with us or with each other, we certainly encourage you to do so. And just to note, Zoom defaults the chat to send to just the panelists, but you may absolutely switch the chat to chat with each other and everyone. And for questions, we'll be collecting them by the Q&A section. Or if you'd like to tweet, we encourage you to share highlights or questions by 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 John for a brief word from our sponsor, Data.World. John, hello and welcome. Oh, you're still muted. There we go. Sorry about that. Everybody had problems finding the mute button here as soon as I started sharing. Thank you so much for the warm introduction, Shannon. My name is John Williams. I'm the Chief Product Officer and co-founder at Data.World, the only cloud-native enterprise data catalog out there. You know, we're really, really happy to be sponsoring this series. Bob does such wonderful work talking about what it takes to do data governance in the real world and how to make it a successful ongoing program. And that's something that we're very, very interested in at Data.World and very interested in figuring out how data catalogs can play a role in that. You know, when you're thinking about building a great data culture, a lot of people, you know, walk up this particular curve, right? You know, it's a maturity curve. We use a lot of Data.World. And if you're anything like me in my past, when I've run large data management practices, you know, you might find yourself really stuck in a rut, really focused on infrastructure and tools at the operations part of your maturity curve. But as you get out of that, as you've built, you know, your cloud data warehouse, as you have a great modeling and ETL strategy, maybe you're starting to think about treating data as a product. A lot of people try to climb up this and start thinking about cataloging and governance, adding true understanding around business glossaries. But instead of really opening it up and driving data democratization, they end up putting gates in front of the process. And that can be really harmful. It can really stop you from getting to this place that some of the best organizations in the world have gotten to, where their data governance programs and their collaboration, data literacy and data democratization programs are so much more. And they do so much more with them than just worry about simple compliance and risk aversion, right? A lot of this and where I think a lot of folks end up getting hung up. And this is something again, I think Bob does such a great job talking about is how do you avoid this very traditional top down model where everything flows from the top where you have these grand committees and councils with architects arguing about how things should get done requiring films, forms get filled out in triplicate. That's not a great way to run a program like this. And unfortunately, your poor data consumers are left in a, in an Oliver Twist Lake situation asking, please, sir, may I have another just trying to get their jobs done with their bosses breathing down their neck wondering why that dashboard or model isn't completed yet. And you know, a lot of this really, it comes from a very old school ivory tower approach specifically to data governance, something that has to flow from the top and becomes a chore instead of something that you do in the course of doing your normal work. We think a data.world, the data governance can be so much more. And again, I want to, I want to really thank Bob for really driving this and driving a lot of thought leadership around this around the idea that that data governance can really be about more than just risk avoidance compliance and really conform simple, consistent and effective rules of the road for doing data analytics work, just like bringing agile and scrum into your normal software engineering practices, you know, adopting some of those best practices to bring transparency and inclusion with along with great definitions of what quality work looks like and appropriate work looks like, can really accelerate your data analytics programs instead of putting a gate up in front of them, right. And for us, it's all about, you know, finding the love between your data producers and your data consumers really tightening this cycle time between the curation of data, making sure it's properly audited and governed, well documented and producing those insights that drive our business forward, right. Getting data producers and data consumers is really a lot of the crux of this problem, right, involving all those stakeholders and making sure everybody has the kind of transparency and visibility into this process that they need. This can really be unlocked if you think about your data's supply chain and if you adopt a data catalog or you adopt a couple of principles, we're huge proponents of adopting agile data governance and this idea of data ops to really to really lean into this idea of inclusivity, transparency, auditability and observability, a way to bring people into a fold without stopping them doing their work, to really and truly enable self-service. And if you do this and you decide to put a data catalog at the center of this new data ops and agile data governance practice that you're building, something that, you know, hey, we make and sell a data catalog at Data.world and that's why we're sponsoring this webinar. We think you really need to consider a data catalog to be three things. An information radiator, a front office, truly a front office. You wouldn't consider running your business without a CRM tool. Well, think about a data catalog as that information radiator for your entire data analytics practice, something that becomes the front office for your entire data governance process. A collaboration hub where data consumers and data producers can truly work together and collaborate and enable them to, you know, give them the opportunity to create these moments where they can capture knowledge and document in bite-sized chunks so you don't have to have this top-down ivory tower approach. And finally, to truly support data ops, you have to be an open ecosystem where you can easily integrate to all the tools people use so you can build the observability you need to really make this process hum. I'm going to quickly jump over here. I'm going to show you in Data.world itself, right? This is Data.world. I'm logged into one of our demo accounts. I want to show you how quick and easy it is to discover data semantically, searching on a simple concept like order in Data.world, being able to drive into a business term to really understand what's going on in this semantic search that we have. So, you know, when we drive into that, right, we can also find tables that are associated with it. Now, I talked about being an information radiator. And being an information radiator, you see we pull these full descriptions and schemas in, right? More importantly though, because we are an open ecosystem, you can pull in this data lineage information. We can even feature data quality information here to really help analyst data consumers to really understand the data that we have. Additionally, right, we want to promote collaboration. You know, we can suggest changes here as well. Or if we want to drive into this even further, we can drive into curated data sets. Data products created by data engineers specifically for consumption that bring an even greater understanding to the data analytics ecosystem to our data consumers, right? And finally, to get really into it and really accentuate this idea of being a collaboration hub, we even have the idea of data projects in Data.world where you can document and review all of the analytics that's getting done across the organization and provide folks like Data Stewards really great visibility into the work that's getting done. But more over, as people are working on data projects, we are the only data catalog that actually enables live federated query forming a data mesh of all your data data assets and then enables you to create really great normalized domain specific models to drive analytics while giving your data engineering, your data stewardship team all the visibility into how this stuff is being used. And talking about being an open ecosystem, every single one of these things ultimately ends up being an API that you can connect to and then open directly in the analytics tools that people are using today. This end to end nature of Data.world bringing you all the way from metadata management to data management, driving agile data governance to last mile data access discovery, audibility and observability is what we believe makes our data catalog unique, right? And really enables a sort of cultural shift that you're looking for in some of the real world governance ideas that Bob's talking about. So that gets me to the end of my section here. You know, don't want to be don't want to be the vendor and the sponsor talking too much and being too much for talking head because I know what you're really here for is to see Bob. Shannon, are you gonna are you introducing Bob here for us? I am. Thank you so much, John. I really appreciate it. And if you all have a scene, data.world is also going to be participating in the November demo day. Really cool stuff that they're doing if you want to check that out as well. And if you have questions for John or about data.world, feel free to submit them in the Q&A panel because John will be joining us again in the end in the Q&A portion of the webinar. So now let me introduce to you our speaker for the series, Bob Sinner. Bob is the president and principal of KIK Consulting and Educational Services and the publisher of the data administration newsletter, TDan.com. Bob specializes in non-invasive data governance, data stewardship and metadata management solutions. And with that, I'll give the floor to Bob to start his presentation and say hello and welcome. Thank you, Shannon. Thank you, John. I appreciate data.world being a sponsor of the webinar and the webinar series. Love to have you here. And I thought that the information that you shared was really helpful. So today we're going to try to do something a little bit different than what we've done in other webinars in the past. A lot of organizations, a lot of the organizations that I have the pleasure and the honor of working with are looking at creating frameworks for their data governance program. So I thought that what I would do is I would share my data governance framework and actually give you an opportunity to fill it out as we are walking through the webinar. So we've never really tried to do that before. So if you might have noticed in the chat session a little while ago, I had mentioned grab a pen and paper because you might want to start thinking about what a data governance framework looks like and we'd love to hear from you as to how this may compare to other data governance frameworks and things that you're using in your organization. So I will get to that in one minute. I just want to do a quick introduction if you don't know me. I'm obviously you're familiar with the real world data governance webinar series. It's been going on for many years. This is actually the last webinar of the summer. We've got a great fall set up in October. I'll be talking about convincing stakeholders that data governance is essential to your organization. So much time is spent and invested in getting people to understand why data governance is necessary. In fact, I can tell you now that we've got a great set of sessions for 2022 as well. So the real world data governance webinar series will continue. And I talk a lot about non-invasive data governance. And if you're interested in learning more about non-invasive data governance, I'm not going to really focus on that too much today. But there's a book that I wrote several years ago that's available through your favorite bookseller. I do a lot of work with DataVersity. They're truly a great partner to work with them all the time. I'll be speaking at an upcoming event in December, an in-person event in San Diego, California, the DGIQ or the Data Governance and Information Quality Conference. I also have a bunch of different learning plans that are available through the DataVersity Training Center, one on non-invasive data governance, one of my favorite subjects, and then one on non-invasive metadata governance because we know that the metadata won't govern itself. So we need to implement governance around the metadata as well. And then the most recent one is the one that focuses on business glossaries, data dictionaries, and data catalog. So I hope you'll take a chance or get a chance to go look and see what is available through the DataVersity Training Center. Lots of great training material. As Shannon mentioned, I'm the publisher of the Data Administration newsletter, tdan.com, published twice a month. In fact, a recent issue was just published yesterday. They're published on the first and third Wednesdays of the month. I also run a business called KIK Consulting and Educational Services. KIK are not my initials. My initials are BS. I didn't want to call myself BS Consulting. KIK stands for Knowledge as King. And then most recently I've started to fulfill a role of an adjunct faculty member here in my hometown at Carnegie Mellon University in their CDATA-O, Chief Data Officer, and their Data-Driven Leadership Program. So a little bit about me, but now I want to talk about what we're going to address today. And I hope that during that time maybe you were able to go get a pen and paper so that we can start to scratch out what might begin to look like a data governance framework for you. So the things that I want to talk about today are customizing a framework to match things that are required by your organization. You can't necessarily take a general framework and always have it fit to the requirements of your organization. So we'll talk about customizing the framework that I'm going to share to match the requirements of your organization. And typically that framework is made up of kind of the core components, which I'll talk about in a minute, six core components of a successful data governance program. And I'll talk about the different levels of the organization that need to offer their perspective when it comes to each of those components. We'll spend a little bit of time talking about how to complete the framework. And at that point, I'm going to hope that if you have a framework scratched out in front of you, that you'll be able to fill it in as we are as we are walking through the webinar. So it should make it fun. It should make it interactive. If you have questions, please submit them through the Q&A. We'll be glad to address those either during the webinar or anytime after the webinar. We'll talk about the framework to enable your program success. And we'll talk about measuring value through the framework as well. So the first thing that I want to do is I wanted to share with you the framework that I use. In fact, I created this originally as more of an academic exercise, but I'm finding that a lot of organizations are very interested in completing something like this, in customizing this to match what their specific needs are. And so it's pretty simple. It's based on, if you're familiar with the Zackman framework for enterprise architecture. You know, John Zackman created that framework. He had the different things across the top were the who's, what's, why's, where's, when's, and how's of the organization. And down the left hand side, he had all the different perspectives of the organization that had to be considered. So I kind of used John's framework to build out a framework of my own. And when I initially created this framework, there were only five columns. The one that I had forgotten was the data column. So several years back, I went and I added the data column and you'll see where that really plays into what we're trying to achieve when we're developing the framework. So I asked you to grab a pen and paper. What I would suggest is if you're interested in playing along and going along with us here, scratch out real quickly a matrix that has seven columns in it, has six rows and fill them in with the things as we go through that are relevant and really make important sense to your organization. So I'll talk about how I typically begin to fill it in and then we'll spend a little bit of time going through it to try to help you to flush out the things that are important to your organization or the different components when viewing them from the different perspectives that are down the left side of the matrix. So again, this is the matrix and I just want to quickly share with you. So I know it's kind of hard to read in the upper left. I wanted to blow that up a little bit. We'll talk a little bit about that in more detail right now, but the components are data, the roles and responsibilities associated with your program processes because we know that what are we governing? We're governing people's behavior, but we're also governing the processes, getting the right people involved at the right time in the right process using the right data. That's extremely important. I would say to a to a client to an organization that I've spoken to communications is an extremely important and valuable component to a successful governance program. And we know we can't communicate with the executive level the same way that we communicate with the operational level or the support level. So when we're creating our framework, we need to make certain that we're specifying to what messaging do we want to get to the executives? How does that differ from what we're sharing with people at the operational level? And then metrics and being able to demonstrate that your program is successful or is adding value to your organization and the tools are an important component as well. And as John talked about the data catalog, a lot of the tools that are available for your environment they address different things at the executive level, there may be a different set of tools. It might be policy, it might be guidelines, it might be standards at the tactical level. So let's talk about this. Let's walk through each of the pieces of the framework and let's think about filling it out. Now here's a completed version. I don't this, you'll get a copy of the slide deck that has this in it. Also, we will be attaching the noninvasive data governance framework white paper to this. We always seem to attach that to what we are sharing with folks who are attending the webinar. So before I jump into the creation of the framework itself, I'm sorry, I wanted to show this diagram as well. And so what I did is I took the things that were available across the top of the framework, the data roles processes and so on. And I wanted to compare what does that mean depending on the approach that you're taking to implementing governance. So if you're taking in a command and control approach, if you look along the roles row in a command and control approach, you're going to assign people into roles in a traditional field of dreams. If you build it, people will gravitate toward it approach to governance. We're going to identify people into roles. In the noninvasive approach, we're recognizing people that are already governing data and we're formalizing accountability based on people's actions and their relationship to the data that they work on. So if you look at this and again, I'm not going to spend we've actually done webinars comparing and contrasting the different approaches to data governance. But this in a nutshell kind of summarizes the key things that you might want to compare when you're talking about the components that I'm sharing within the framework today. So first, let's talk about customizing a framework to match your organizational requirements. So I don't have a whole lot more to add to this than the things that I've already talked about. If your components are different than the things that I've specified, feel free to create a column or remove one of my columns or just make it your own. That's really the key message here. You want the data governance framework to be customized to match your organization. And I like the framework. I like the structure that I'm using here because it helps you to be able to cross reference each of these components with each of these different perspectives that there are in the organization from the executive all the way down to the operational and support levels. Color coordination. No, I don't add color to it just to make it look pretty. Although it certainly helps to make it a little bit colorful. But you'll see a little bit later in the webinar where I'm going to show this next to a bunch of other tools and templates that I've shared over the years during this year and the webinar series. And you'll see that if you can be consistent in the way that you use color across your templates that people will be able to see themselves from the roles and responsibilities to the race see to the communication plan all the way to the framework. So the idea of creating colors so you can be consistent. It makes a lot of sense for organizations that are implementing tools and templates and things that they're creating themselves. And again, now use terms that make sense to you and put them in the order that makes sense to you. I had a client recently that told me that I had it wrong. I had the operational and the tactical levels reversed and in his organization referred to what I refer to now as the tactical level as the operational again, customize this to make this fit what your organization looks like. When I talk about non-invasive data governance I'm talking about looking to see what already exists in your organization and leveraging that first before you start to go and create things new or create things from scratch. I can tell you right now under the concept of non-invasive data governance your organization is governing data. The question is how formal is it? How efficient is it? How effective is it? So you want to move from that informality to that formality so that you can move from inefficiency and ineffectiveness to efficiency and effectiveness. So let's go through each of the core components first. There's the data that's the assets that are of importance to the people and within the perspectives that are down the left-hand side of the framework. The roles and responsibilities or the formal accountability oftentimes organizations have executive steering teams at the executive level. Have a data governance council or committee or advisory group at the strategic level. There's certain processes that focus on that are really important to people at different levels in the organization. The communications as I said before is a vital piece to a successful governance program. So we need to understand how are we going to educate, train, make people aware, improve their data literacy, change the culture of the organization and we need to look at communications and we need to understand that we cannot communicate with everybody in the same exact way. That's why it's important to look at communications from each of the different perspectives that I talked about. The metrics, different things are important to different people. The tools, you'll see there's a lot of different tools that we can enter into the framework as well. Just real quickly going through each of these core components. The data is really the scope of what you're looking to govern. And you hear a lot of different titles, a lot of different labels that are given to data governance. There's master data governance, big data governance, small data governance. Artificial intelligence data governance or BI data governance in most organizations really being able to be specific about what data is in scope is important to you. I don't suggest that we add these labels in front of data governance because you're going to try to, you want to be consistent in the way that you govern data across the organization. So let's call it data governance. We don't have to name it specifically to the type of data that we're governing but we need to acknowledge what that data is and we need to acknowledge what data is important to the different people and the different levels across the organization. So we may want to differentiate between what's data and what's considered information. Sometimes those words are used interchangeably. I believe that data plus metadata or data plus context gives you the information. Where are you going to find that context? You're going to find it within the data catalog tool or the metadata repository tool. Same thing holds true for record management and knowledge management. You hear a lot about information governance and those types of things. I really prefer to keep it called data governance but we need to make sure that we recognize what data is important to different people in the organization. The roles and responsibilities well this is the backbone of a data governance program. Everything that you do is going to be focused on the different roles and the way that the accountability has been set up for your organization. And oftentimes the setting up of the roles are really a key determinant in how successful your program can be. I mean it's oftentimes a big predictor of the effort that's going to take place is going to be focused on those roles that you define. And ultimately you're going to have a role at the executive level. You're going to have a role at the operational level of the data stewards. You're going to have the role of data governance partners like IT and HR and finance and other parts of the organization that are already governing but not necessarily governing data per se. Even project management would be considered a partner of data governance. That would be at the support level. We want to identify people into roles rather than assigning people into roles as I showed you that comparison matrix of the different approaches. The language that we use really matters. When you get assigned something immediately it feels like it's over and above what you're presently doing. I don't like to use the term assign. I like to use the term recognize. So we're going to recognize people for what they do and we're going to help them to govern the data better. If they define data, produce data, use data, we're going to help them. We can't just go out and say oh you're a data steward. Go start doing data steward stuff because they're not going to understand what that means. We need to explain to them what it means and where they play a significant role based on where they are within the organization. So roles and responsibilities that has to be a core component of a successful program. Processes. I'd be surprised if you would be eliminating process for being one of those columns of your framework because what are we really governing? We're governing people's behavior but we're also governing how people are getting engaged in the different steps of the processes. One of my pet peeves is this whole concept of a data governance process as if it's a singular process within the organization. My suggestion is that you're going to apply governance to process rather than renaming all of your processes as data governance and data governance processes. In fact, a process in itself that is strongly defined that people are following, that is a form of governance. It's getting the right people to do the right thing at the right time in the right way and all of those things. So steer away from the term data governance process and start figuring out what processes are really important to the people at the different levels of the organization. And you know what? You can start to fill that in to your framework itself. Communications, as I said before, it is vital. And again, I'd be surprised if you eliminate communications, eliminate changing the culture or helping to make your organization more data literate. I think you're probably going to make a mistake. So that's the fourth column of the framework. So so far, we've got data. We know it's important roles. We know it's important processes. We've got communications. Typically, when I talk about communications, I break it into three different categories of communications. So there's orientation, bringing people up to speed on the concepts of data governance, of data stewardship, of metadata management or even orientation to the data catalog. The fact that a catalog exists, what exists in that catalog. And then there's the second O of data governance communications and that's onboarding. So when we actually ask somebody to do something or get them involved in a specific govern process, there's communications that needs to go around onboarding these people to let them know what's expected of them. Also, how much of their time is going to be required? What's in it for them? What's the value that's going to come to them as well? And then the third O of data governance communications is the ongoing communications. That's oftentimes where the metrics fit in, where the status of certain projects and things go in, where there's new rules and regulations that are being entered into the mix within your organization. We need to make certain that we're communicating on an ongoing basis. So again, I think that communications is really vital as a core component of your program. And think about the fact that there's different types of communications and the three O's is a real good way to be able to look at it. Metrics, I don't think I've known, I've seen a program yet where management and leadership and everybody else who's involved in the data doesn't want to know what the data governance program is doing for your organization. So you must be able to measure the impact on your organization. Oftentimes, the metrics is part of the administration of the program itself. So the people, many of you may be the administrators of your data governance program or the leads or the managers, you know, having metrics. I'm certain that you've been asked before, you know, how are we going to measure what we are doing? How are we going to quantify what we are doing? I always suggest that we don't look for ROI from data governance itself, that we look for ROI from where we're having an impact on other heavier investments that are being made within the organization. How well is the data warehouse being used? How well do people understand the data in the data lake or that new analytical platform that you're building? Look for the ROI from data governance in those initiatives. But metrics are, without a doubt, one of the most important components when you get your program up and running, people are going to want to know what have you done for me lately? And then the last core component is the tools. So the tools are there really as an enabler to the program success. You can't buy a tool implemented or install it and all of a sudden have a data governance program. There's a lot of work that goes into getting the appropriate information into the tool, rationalizing it, making it available, getting people to understand what's available. Tools are really important, but it's not only the technology tools. Policy is a tool. Guidelines are a tool. Best practices are even a tool. So think about the fact that tools can be focused on each of the different levels of the organization. So I'm not going to spend as much time going through each of the levels of the framework itself, but now we're going to talk about that part that's highlighted in blue on your right hand side of the screen. There's the executive level and that is your senior leadership. These are not people that are day to day going to get involved in data governance. These are people that need to support sponsor and most importantly understand what data governance is doing for the organization, what it's going to take to be successful. The strategic level in your organization you may have a data governance council or something similar to a data governance council, which is typically the escalation point when things can't be resolved at more of a tactical level that goes to a strategic level. So we know that there's going to be a council and there's certain things that are important to that council or whatever you name that group, whatever you fill into that square where the strategic level meets the roles. At the tactical level this support matter of the subject matter expertise is a is probably the most important part of the data governance program where we're breaking down the silos, we're identifying who the subject matter experts are for the data. I oftentimes refer to them as data domain stewards but I had a client recently say you're really talking about subject matter experts for the data and I said, yeah, you're right. She said, okay, that's what we're going to call them. We're going to call them data subject matter experts. Oftentimes organizations refer to them as data owners. I don't really like the term owner because it implies that it's their data and they can do with it what they want when in fact the data is owned by the organization. So the tactical level is probably the most important level of all of these. Some people may disagree with that but I would also say it's the most difficult to fill. If unless you already know who you go to to resolve certain issues around certain subjects it's difficult to find the appropriate person. Those tactical people are going to be really critical, a critical piece of your successful program. The operational, the support levels, those at the operational level we've got the operational data stewards at the support level all those partners that I just talked about. So just real quickly the executive level that would typically be the C level of your organization. They could be the president's chairs, senior vice presidents and then C whatever letter you want to put in there for the C level positions within your organization. There are so many. CEO, COO. I'm seeing new ones almost every day that there's the kind of new C level positions being introduced but we need to make certain that we are able to address the needs of the executive level. At the strategic level like I said that's typically a council. There's representation of the different business the parts of the organization that sit at the strategic level. If you don't have a council please look at or you don't know what goes on in a council. We've done webinars recently on the roles on just focusing on the roles and responsibilities. So please go back to the data diversity online webinar or on demand webinars and find the roles webinar that I've done to give you more detail as to what the council looks like what they do who gets involved what the expectations are. As I said the tactical level is really probably the most important level. And this is where we break down the silos. This is where we know we've got a problem. So we're going to go to John because John knows John's always the guy that we go to. So by default John would be that subject matter expert. He might be the domain steward. He I don't like again like the idea of calling him the owner of the data because the organization owns the data. So you kind of catch my drift that tactical level is the subject matter expertise. And a lot of organizations just start by defining what their domains of data are. The subject matters of data. So we can start to identify who are the people that we go to to resolve issues around that subject area of data. The operational level I talk a lot about that. I consider that everybody in the organization is a data steward. I tell organizations that they should get over the fact that potentially everybody is a data steward. Just as an example somebody who uses data that is sensitive. They're a steward of the data. They need to know the rules. They need to follow the rules associated with how they use the data. So there's different levels of accountability that we need to formalize certainly the operational stewards in some organizations. They follow what I just stated. And everybody in the organization it makes it a little bit more complex to communicate with everybody. But when people start to recognize that they're stewarding the data that's a big win for your governance program and your stewardship program within your organization. And if you go out to tdn.com I just recently wrote an article on all the different partners of data governance. And I don't want to go into them in too much detail but IT is a partner project management regulatory and compliance security audit communications HR all of these are groups that are already governing in their own right. But they're not necessarily governing the data. We can certainly leverage what information security does but we as data governance practitioners are not looking to focus on implementing effective information security. We're going to partner with the information security part of the organization. That's just one example I want to use. So now we're going to start to use that diagram that you just sketched out and we'll start to fill in the pieces. And if we were doing this live and in person I'd love you to kind of yell out what you call the different levels of your organization what you call the names of the roles in each of the levels what you call out as the processes that are important to each of those organizations to those parts of the organization. And so oftentimes what organizations start with is they define those core components again the data the roles the processes communications metrics and tools and then the different levels of the organization. And then you begin to start analyzing the framework by component by level and you start to fill in the squares and then there's actually going to be parts in this in some of the slides that I have here real quick to give you an opportunity to sit down and write down what do we call this for that part of the organization and then we want to make certain that we can align our framework with other tools. And you know John talked about the front office the data.world tool or our data catalog tool as being the front office we'll talk a couple minutes about promoting the governance program and making the framework part of that face of your program. So if you can include that in the front office I think that makes a lot of sense. So let's start out and I hope you have a diagram like this in front of you or you can just scratch it down as we're talking here but let's think about okay what do you presently call people? Well first of all okay we're talking about data we're not going to talk about the roles first. What data is important to the executives? Where do they get that data? Do they go to dashboards? So they get regular reports. Where do those reports come from? We need to acknowledge what data is most important to the people at the executive level. Same thing with the strategic level and the tactical and the operational and the support levels. So oftentimes I find that performance metrics are things that the people at the strategic level are looking at. Oftentimes at the tactical level people are really concerned about their subject matter of data or may even be business unit specific so again you can fill in that block with what's important at the tactical level. At the operational level that's oftentimes that operational data that transactional data that the business unit functional data is what the people at the operational level are most interested in and at the support level it's information that's going to help them to govern their part of the organization even though it's not data governance we know that IT is governing IT operations. We know that security or regulations are governing those things. We want we can fill in the data block at the support level with the different types of data that these different supporting functions are most interested in. So here it is if you want to take a second I'm going to keep moving forward but think about filling in your blocks as to what data is important or where do the people go at that level to get that data that's the beginning of that's the data column of your framework. The roles level I know I've already talked about that a little bit you've got your steering level you've got your executive committee you've got your executive leadership you know you might want to fill in your role column at the executive level with with that or at the strategic level whether you call it a council or an advisory group or a committee at the tactical level if you call them data owners then feel free to fill in the yellow block in the second column over in the roles column with whatever you're calling people at that level but acknowledge that you know that you need you're going to need to have some role that addresses the data at that tactical level of the organization at the operational level oftentimes I see those people referred to as data users or data stewards operational data stewards definers producers and users of data at the support level look to see what levels of governance are already taking place in other parts of the organization I listed a whole bunch for you being IT project management regulatory um information security all of those folks are partners they're at the support level so consider you know you can make your diagram bigger if you don't have space to write in all the names of the people in the organization that are supporting data governance but fill in the blocks and again this will be a great communication tool to share with people when when they're thinking about when they're trying to visualize what's going to be important for your organization same thing with the processes what are the processes that need to be governed and then are being acknowledged at the executive level certainly um access to data certainly um you know compliance of the data compliance processes all of those types of things do the same thing that I just mentioned go down block by block and say what are the processes that are most important or most valuable to the executive level to the strategic tactical operational and support levels of your organization now once I go through the additional three columns here I'll share with you again the the framework filled in and in fact that white paper that I mentioned it goes through each of those blocks with what I have filled in it may not be appropriate for your organization but at least it may give you a start as to filling this out for your organization to think about what are the processes that are important to your to the different parts of the organization communications we know communications communications and then some more communications they're really critical to the success of the organization what do we need to communicate with the people at the executive level we don't have as much time to get in front of them as we do people at the tactical or operational or even support levels of the organization what needs to be communicated with them let's put it in some key words in that box underneath the where it says communications for the executive strategic tactical and let's really start to think about and I don't think that you can you'll necessarily have this completed by the end of the webinar but just think about even after the webinar what are the things that are important to communicate to people at the different levels of the organization that communications is not going to take place by itself people are going to have the responsibility but somebody has to have the responsibility for creating that communications for providing the communications for getting the messaging right I usually suggest to my clients that if they have people in corporate communications that you can work with they can help you to get the messaging right for each of the different levels of the organization that's what they're skilled at so by all means communications folks can be a partner of data governance to help you to make certain that you're having messaging that's going to resonate appropriately with all the different people in the different parts of the organization all right now it's your turn go and fill in the blocks of your framework as to what communications are important how is it different between the executives and the strategic and the tactical and so on as you can see you can start to fill this in and you can do it after after the webinar because I'm going to continue to move forward but again it's a great framework to be able to share with somebody to help them to know what's going to be involved with developing a successful program in your organization the metrics again different metrics may be important to different levels some people may be looking for the impact on the bottom line some people might be looking at the impact on efficiency and effectiveness within the organization again I'm not going to fill this out for you here but we want you want to think about what metrics and measurements are going to be important to the different people at the different levels of the organization and fill them into the framework again understanding that these metrics are not going to create themselves that you're going to need to spend some time creating those metrics and sharing those metrics getting them approved and then getting the data that you need in order to provide those metrics to the organization and the last column is the tools column so start to fill in you know what are the tools that are important to the executive level the policy might be important but at the strategic level there might be guidelines at the tactical level there might be standards at the operational level again like you can see just think about what tools are going to be helpful to the different people at the different levels within the organization and certainly people at the support level now they've got tools and things that they're interested in as well so I know we've only got a limited amount of time in this webinar and I probably went through things relatively quickly but I wanted to share with you again an example of what the framework looks like filled in and I oftentimes like oops before I go to that slide I oftentimes like to use the roles column and say at the executive level that's our steering committee that's our leadership at the strategic level there's a data governance council it's it is a group that may potentially preside over the activities of your governance program at the tactical level I oftentimes refer to them as data domain stewards people that are subject matter experts for certain subjects of data sometimes they're called owners again customize this and fill it in in a way that makes sense to your organization at the operational level oftentimes those people are referred to as the data stewards or the users of the data and at the support level you can see where I filled in with its program management because there's really three components to supporting of the program one is the people that have the responsibility for administering the program another one is the working teams that we create in order to solve problems and then there's the partners all the partners that I spoke about you could enter them all in there you could just put the word partners and then refer to who are the partners of your program even when you look around the the communications where it says at the executive level supporting sponsoring and understanding strategic level the status is important again fill this in so that it makes sense for your organization and I've seen organizations even use this diagram to measure how well we're doing what have we addressed so far what needs to be addressed what's going to be next kind of using a red, yellow, green even to highlight over the boxes oftentimes that really helps organizations too to flush out and fill out their framework so I mentioned earlier the color coordination I just wanted real quickly here to share with you examples of what I mean and I've talked a lot about roles and responsibilities and there's the operating model of roles and responsibilities that are on the far left there's a communication plan in the upper right where we've got the three different sections of orientation onboarding and ongoing we've got the different roles highlighted by the color at the top and bottom of each of the columns and then the things that we're going to communicate as part of the orientation onboarding and ongoing communications people should be familiar with the racy matrix which is in the bottom middle and then on the far right a tool that I talk about quite a bit is the common data matrix we don't have time to flush that out today but if you can see yourself in one part you can see yourself in the other parts or the other templates that you're using in your organization so kind of getting back to what John had talked about with the front office promote use the framework potentially as the face of your program I've seen organizations actually put the framework on the home page for data governance and give people the opportunity to click through certain things to learn more about communications at this strategic level or metrics at the operational level so you can actually use these this framework as that front that face to your program that front office as people come in to learn more about governance that's the place where people come go to become data literate let's just spend a couple minutes here talking about ways that you can use the framework it really helps to frame your entire program that's the name framework for simple explanation to people you can use this to help to orient people to data governance to bring them on board you can use this to provide status as I mentioned before with a red yellow green for the squares to let people know where you are okay we know that we need to have a steering committee we haven't met with them yet it's on the on the plans as to something that we need to address you can use your framework to enable those types of things and as I said color coordination with the other tools really helps people to see themselves in all the different components all the different templates and tools that you're creating in your environment as I said actively connect your framework to other tools communicate by level and as I said it says here request the non-invasive data governance framework white paper through my site or you can that should be attached to the email that's going to go out after this webinar and so the last thing that I want to talk about is using the program to measure your using the framework to measure your program and we're going to look at it by components and by levels all the components I'm just laying out for you some things that you can use to measure the value using the framework that I've shared with you quantify the importance of the data being governed inventory who owns the data measure the accountability when it comes to the roles how many domain stewards subject matter experts have we identified or recognized into our program how many of them are engaged what processes have been governed what communications is being set up and is taking place what metrics are we using to measure our program determine the value of the tools you can look and say okay do we have a policy at the executive level do we have a data catalog down at the strategic and tactical and operational levels so you can use the framework to measure your program and then also you can measure it based on the levels that I talked about you know gauge what level of support sponsorship and understanding there is at the executive level measure your council activity activity quantify the number of SMEs that you've recognized and that you've engaged again don't want to read through all of these but you get the idea and the idea is that you can measure the value of your of your program if you have a snapshot of everything that's involved in implementing your program so I know I went through this relatively quickly with you today again I think John very much in data.world for sponsoring the webinar you know we talked about customizing the framework the core components and levels how to go row or column by column and complete the framework using this framework to enable your program success measuring the value through your through your framework as well I hope that this was beneficial to you I've enjoyed talking about it I like this quite a bit I like to having a framework quite a bit and I'm going to toss it back to Shannon to see if we have any questions. Thank you Bob we got some questions coming in got a few minutes left so I'm going to dive in here and if you got questions for Bob or John feel free to submit them in the Q&A and any questions we don't get have time to get to I will send them over appropriately to get answers for y'all. So for a national statistics office would you consider field workers as operational or is there a need to have another level as frontline workers? That's a good question and you know I love it when I get questions that I that haven't been asked before I would consider them I would put them in the operational level at least for the time being until you find that there would be a more appropriate place for them and as I mentioned early on if you need to add a row that addresses those specific frontline workers then please feel free to do that think about if you're going to communicate with them differently than another level of operational folks then by all means add them but right off the top of my head I would say that the frontline workers are most likely going to be operational people in your organization Yeah no I mean obviously that I think that question really you know leans into Bob's framework really well and you know I expect Bob to have the answer there Thanks John All right if you have questions again feel free to submit them in the Q&A portion I'm going to I see some coming through the chat I'm trying to figure out if we can get some if I don't miss too many here so do data sewers get assigned databases or systems or data elements? I saw Sharon ask that question in the normal chat there and thank you for the question I actually just typed an answer back to you but I mean I think the where you assign data stewardship is a really great question in general it can depend a lot on your organization how you organize your data what we've seen particularly with data at all we're all clients as the most effective stewardship model is one where you have data stewards or depending on like how forward thinking you are your organization is data product owners who are really responsible for a domain of data more so than like a particular table or database or things like that so you know somebody thinking about you know the stewardship of you know what constitutes you know the customer domain and things like that and then carving out the elements and how they fit under the domain but much like with Bob's framework you can actually have multiple stewards at kind of multiple levels as well like up and down the stack depending on how how technical your organization is and also to serve where that stewardship is necessary and you know I'll throw it to you Bob there too and so the only thing that I would add to what you said John is that is and I mentioned this earlier is that I suggest to people that they shy away from using the word assign number one and so in a traditional approach people are identified in a non-invasive approach I like to use the word recognize because it has a positive connotation so if there is a person that you go to for a specific database or a specific table or a specific application then you know I don't know if they necessarily own that they steward it the definition of a steward is somebody that takes care of something for somebody else so we can recognize people instead of assigning because I don't know about you John but when I get assigned things immediately I feel like it's over and above what I'm presently doing and if the idea is to stay as least invasive as we can in the approach then we want to shy away from getting people to feel like what you're handing them is truly over and above what they're presently doing if you can leverage what they're doing it's a lot better than handing it to people as something that's brand new I love that Bobby I've never heard it like talk about it like that I didn't really think about that and that's um gosh that's that's really great you know a long time ago once very early on in my career when I first became a manager I like so many people out there you know referred to the resources on my team and I had another manager in the organization look at me and say John they're not resources like do you need a new monitor or some new computers they're people and I was like holy moly you're so right and I've never referred to a person that works for me as a resource like literally ever again and I don't think I'm ever going to use the language like assign ever again because you're right like we're trying to get people we're trying to get people to participate in a flow in a workflow and fit into their daily activities so like you know recognition is so much more positive if you want people to come along for the ride you have to be positive about it that's oh this is brilliant Bob yeah well you're not going to assign somebody to protect sense of data you're going to recognize that they use that sensitive data and you're going to teach them how to to use it so to me it's just really one of the core differences between non-invasive data governance and the other approaches is that term recognize and I have to tell you that there's other people that have had similar comments to what you just stated it's just it's really different because I don't ever want to be assigned anything you know well not I'm not never but it certainly feels like it's over and above and again we're trying to stay as least invasive as we can let's use terminology that's going to be better accepted within the organization yeah words matter man words matter I love it well that does bring us to the top of the hour here I'm afraid that is all the time that we have for today I have some questions keep them coming in and I will get those over to appropriately to get you some answers in the follow-up email and again I will send a follow-up email by end of day Monday for this presentation with links to the slides links to the recording as well as the additional things that you had asked for and you guys are fantastic I love our attendees thanks for being so engaged in everything we do you never disappoint I was worried about you all and and just love it and John thank you so much for joining us and thanks to data.world for sponsoring today and helping to make these webinars happen thank you guys thanks everybody hope you all have a great day take care everybody thanks for attending yeah thank you and our pleasure our pleasure sponsor anytime thanks guys