 Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Manager of Data Diversity. We'd like to thank you for joining the current installment of the Monthly Data Diversity Webinar Series, Real World Data Governance with Bob Steiner. Today, Bob will discuss the new non-invasive Data Governance framework. Just a couple of points to get us started due to the large number of people that attend these sessions. You will be muted during the webinar. If you'd like to chat with us or with each other, we certainly encourage you to do so. Just click the chat icon in the upper right corner for that feature. For questions, you'll be collecting them by the Q&A in the bottom right-hand corner of your screen. Or if you'd like to tweet, we encourage you to share highlights of questions via Twitter using hashtag RWDG, Real World Data Governance. As always, we will send a follow-up email within two business days containing links to the slides, the recording of the session, and additional information requested throughout the webinar. Now, let me introduce to you our speaker for today, Bob Steiner. Bob is the President and Principal of KIK Consulting and Educational Services and the publisher of the Data Administration newsletter, T-Dan.com. Bob has been a recipient of the DAMA Professional Award for a significant and demonstrable contribution to the data management industry. Bob specializes in non-invasive data governance, data stewardship, and metadata management solutions. And with that, I will get the floor to Bob to get our webinar started today. Hello and welcome. Hello, Shannon. Hello, everybody. Glad to have you with us today. Glad you're taking time out of your busy schedule. This is a really important webinar to me. I mean, if you've attended my webinars in the past, you know that I talk a lot about non-invasive data governance, but never do I really take the time during a complete webinar to walk through an entire framework for non-invasive data governance. And that's what we're going to cover today. And there's a lot of information out there about non-invasive data governance. I'll share some direction to some of those places with you here momentarily. Before we get started, I want to share with you the upcoming webinars in the series. So in March, we'll be talking about applying data governance to agile efforts. And in April, we'll be talking about governing two different types of metadata, the data governance metadata and the master data metadata. So we'll be talking about those things in April. Look forward to having you with us then. A couple other things before we get started. As Shannon had mentioned, I focused a lot on the non-invasive data governance approach. I just wanted to direct you to where you could purchase that book, and it's also available in audio version at this point. I also wanted to let you know about two dataversity events that I'll be speaking at in the near future. One is in April, the large enterprise data world 2017 event. We'll be taking place in Atlanta, and I'll be speaking on comparing approaches to data governance. And at the data governance and information quality conference in San Diego in June, I'll be giving a tutorial presentation as well as another presentation during that event. So I hope that you will join us there. I guess last but not least, I have two other things to tell you. One is about the online publication that I published, the data administration newsletter that's produced by Dataversity. It releases content twice a month. In fact, yesterday we released a new batch of content. I hope you stop by and take a look at some of the very interesting articles. This month we talked about federated data governance, can you trust the quality of your data, and those types of things. So a lot of data management articles every month. And the last thing is the online learning plan that I produced with Dataversity that's available through the Dataversity Training Center called Non-Invasive Data Governance. So please take a look, and if you're interested in more information about non-invasive data governance, that information is out there for you. As I get started with each of the webinars, I'd like to share a couple things with you. One of them is the abstract for this specific webinar. I talk about non-invasive data governance all the time, and I summarize that basically as the practice of applying formal accountability for data, and I apply data governance to process rather than calling everything a data governance process. Like I said, I talk a lot about it. In this month's webinar I'm going to share with you a new framework that was developed recently. You might have seen bits and pieces of it over the course of the last several months. But this is the grand unveiling of the new non-invasive data governance framework. So I'm going to be discussing these things today. I'll talk about the five core components of a data governance effort. Also talk about the five different levels where we need to focus and to address data governance within our organizations. I'm going to provide a detailed explanation of each of the components, at each of the levels for the framework. And you'll see the framework in one moment where it's basically a five by five matrix that cross-references the core components of data governance with the five different levels of data governance and where it needs to be addressed in the organization. I'll provide a framework for you to use that. And then also at the end of the webinar today I'm going to talk about comparing, using the framework to compare different approaches to data governance. And if you remember in the webinar last month I spoke about different approaches to the stewardship aspect of data governance. And I'm going to use a framework that I shared during that webinar to again walk through and compare the different approaches to data governance using the framework. It makes sense to start out this webinar by getting us all on the same page in terms of the definition of the term data governance. Data governance means a lot of things to a lot of different people. I use this definition and I've been using this definition for some time. And I put some teeth behind it. I say that data governance is the execution and the enforcement of authority over the management of data. And the truth is no matter what approach you take, no matter what method you use to apply data governance in your organization, at the end of the day you want to make sure that you're able to execute and enforce authority over the management of the data, whether that's the definition of the data, the production of the data, or the usage of data across your organization. The definition that I use for data stewardship is that data stewardship is the formalization of accountability over the management of data and data-related resources. As I've talked about the non-invasive approach to stewardship, the fact is that there's already people in your organization that have accountability for data. And the non-invasive approach focuses on making certain that we formalize that level of accountability, whether a person defines data or helps them to define the data better. If they produce the data, help them to understand the impact that they have on the rest of the organization. And the no-brainer that all is the users of the data. We need to make certain that all of the people that use data that's protected or sensitive across the organization are going to make certain that all of those people understand the classification, the data handling rules associated with making sure that data is being used in the proper way in our organization. So kind of taking those two definitions, my definition of data governance and data stewardship and blending them together, it leads to the definition of non-invasive data governance, which basically is what you see in front of you is the practice of applying that formal accountability through non-invasive roles, applying data governance to process to make sure that, as I said before, the definition, production and usage of data assures the things that you want your data governance program to assure. And basically non-invasive really describes the approach or how we're going to apply data governance to the organization. We can either take a command and control approach where we're forcing people to do things and we know how people react to having things thrust upon them. In a non-invasive approach we're looking more to formalize people's accountability for the management of data and to apply data governance that way. So without further ado, and let's have a drum roll, I was actually going to have a recording of a drum roll play here, I want to share with you what I'm calling the new non-invasive data governance framework. And as I mentioned before, the framework consists of five rows and five columns. And we're going to go through each of the rows and each of the columns in a little bit of detail and I'm going to point you to where there's more information about the non-invasive data governance framework. But if it makes sense to you and if you have a printer close by, you might want to print off this piece here, this framework, and use it and refer to it throughout the webinar. I'm going to make it smaller and put it in the corner of the slides for you to reference at a later date as to what exactly it is that I'm talking about. But this is the primary look at the new non-invasive data governance framework. And what we're going to do is we're going to dissect this so that you understand exactly what I'm talking about in terms of why we need a framework like this to address what are those five core components of data governance at all the different levels of the organization that needs to be applied. So let's start by talking about the different components of a successful data governance program within your organization. So typically the first component and basically the most important component if I had to pick one of a successful data governance program is the definition of roles and responsibilities associated with your program and the authority that is given to each of those different roles. So that's the first column within the framework and we're going to talk about the roles and responsibilities as it pertains to each of those different levels of data governance that I spoke about earlier. The second core component are the processes of the organization and I'll share with you exactly what I mean by the processes that need to be governed within the organization. We'll talk about communications and how important communications is and how you communicate about data governance to your organization. So I consider that to be another core component of data governance. The metrics and how we measure the success and what the value is that we're getting from our data governance program is certainly one of the core components. I haven't seen an organization yet that says well we're just going to put data governance in place and we don't really need to understand what it's doing for the organization. So we'll talk about the different metrics that are associated with each of the different levels of a data governance program and the last component is the tools. So let's jump into a little bit further of a description of each of those five components. The first one as I mentioned being the roles and responsibilities and basically the authority associated with the roles with your data governance program. So typically the first foundational component that organizations put in place when they're defining their roles and responsibilities. And oftentimes the manner or the approach that you take to defining the roles and responsibilities in your organization are truly a predictor of the effort that's going to be required to govern data across the organization. So when we talk about roles and responsibilities in terms of noninvasive data governance they're typically expressed through something that I've shared before and I'm going to share with you again today I call it the operating model of roles and responsibilities. And if you're familiar with the pyramid diagram as I call it that defines the different levels of roles and responsibilities that focuses on each of the five different levels that I'm going to talk about in a minute. The executive level of the strategic, the tactical, the operational and the support levels of the organization. So when I share with you an operating model of roles and responsibilities that even provides more information about the data governance framework. So the roles and responsibilities is something I'm going to spend a bit of time on here in a couple of minutes and I'm going to really dissect that by each of the levels because that is so important to the success or failure of your program. Even when it comes to the tools and the communications and the processes we need to make certain that we have these roles and responsibilities well defined for our governance program in our organization. The second component is again being the processes and I consider this to be the second foundational component and I have a pet peeve that I talk about often where organizations call things their data governance processes. Well the fact is that data governance is really something that needs to be applied to processes. So a lot of your organizations may have processes that you follow and they might be quite ungoverned which means that you're not used to getting the appropriate time and the appropriate steps of the processes and so in noninvasive data governance when I talk about the processes associated with this new framework the processes need to be looked at again from all the different levels from the executive level down to the support level of your organization and there's something that I've shared in the past which I call the data governance bill of rights and the data governance bill of rights is basically the idea that the reason that we are doing data governance in the first place is that we are attempting to get the right people involved in the right process using the right data to make the right decisions and if we take that to heart that's typically what we are trying to do when we are governing processes within the organization. So I'm going to share a little bit more information with you at each of the different levels associated with the processes. The communications is a successful data governance program. A lot of organizations don't only call it communications but they call it awareness. One of the ideas or one of the focuses of a lot of successful data governance programs is to raise the level of awareness that people have. The people that define the data that produce and use the data help them to understand why the data is so important to the organization and why the data becomes the organization does. So basically communications also includes education and education needs to focus on getting people to understand the policies, the handling rules, the best practices, the standards associated with data across the organization. In the noninvasive data governance approach as I said before communications plays a vital role and in fact I consider the development of a communication plan being one of the first artifacts that you really want to focus on when you deliver your data governance program whether it's a noninvasive data governance program or another type of data governance program. Another one of the core components is the metrics and again organizations need to have a way to be able to measure the impact of data governance on the organization. Typically the group that has the responsibility for putting the metrics in place is the data governance team or that group of people in the organization that have the responsibility for not only defining and developing the program but also facilitating activities associated with data governance. In noninvasive data governance programs organizations typically measure the improvements that are associated with the processes. The processes of reporting and recording data quality issues and addressing issues, improving the way people understand how data can be used and can't be used limiting the risks involved with the data to the organization. The metrics are again one of those core components that we need to kind of dissect by each of those five different levels that I'm going to talk about here in a minute. The last of the five core components are the tools that are associated with your data governance program. The tools of data governance, the tools that you use oftentimes to deliver your data governance program basically helps you to enable the program to deliver value to the organization. It helps you to get the appropriate people involved at the appropriate time in the appropriate processes. As I mentioned before the data governance bill of rights is so important. How are we going to enable the people of the organization to succeed within these processes? Well the tools provide the business glossary and the metadata background that is necessary to have a successful data governance program. So in noninvasive data governance basically the tools are used to formalize that level of accountability I spoke about earlier to improve the knowledge that people in the organization, knowledge about the data and the rules and the processes associated with governing data in your organization. So if you think successful program always addresses and again it's the roles, it's the processes, it's the communications, it's the metrics and it's the tools. And so those are what I use basically to outline the top level of the new noninvasive data governance framework. Now down the left hand side of this new framework I list five different levels. And so there's the executive level, the strategic, the tactical, the operational and support levels. Now I've talked about that before in terms of roles and responsibilities and I'll talk a little bit more about that in a minute. But if we can address each of those five different components from each of these different levels perspectives then we can basically build all the tools and all the things that we need to deliver a successful data governance program for our organization. So let's walk through each of the levels is the level that provides the enterprise perspective. And oftentimes when we think about the executive level we think about it in terms of the people in the organization that are at the very top. And that could be the chief information officer, chief executive officer, operating officer, chief data officer, anybody at that high level of the organization is typically considered to be the executive level. Now oftentimes the executive level they meet from time to time one of the goals of the data governance program needs to make to get the data governance program into the awareness of the people at the executive level. And since they oftentimes have scheduled meetings as a steering committee for the organization we need to focus on at least some of the time getting data governance to be one of those line items of things that they discuss at these meetings and help them to understand how data governance is moving along and how it's being applied in the organization. The next level down below the executive level is the strategic level and typically there's two levels of cross business area perspective that we need to address within a data governance program. The first one being the strategic level. The strategic level of the organization typically when we think of the executive level it's typically the people that the executive level are putting responsible for running each of the business functions or business areas of the organization. So typically the strategic level of the organization is accountable to the executive level for the success of any initiatives and in this case for the success of the data governance initiative. So at the strategic level in a minute I'm going to talk about the roles and responsibilities oftentimes you've got to be accountable and that's the group that resides at the strategic level of the organization. The next level down in the framework is the tactical level and that's also a cross business area perspective or has a cross business area perspective of the organization. The people or the part of the organization that is truly tactical is not looking at data from a business area by business area perspective. They're looking at it from a cross business area perspective and oftentimes within the tactical level there's going to be the subject matter experts, the people that we go to to resolve issues around data management and around data governance in the organization. So sometimes we need to define this role and we need to identify the appropriate people to go into the role but oftentimes at the tactical level there are people that already seem to have the responsibility potentially by your organization for looking at certain aspects of the business across business areas and oftentimes these people are the authorities or the decision makers around things that get escalated to the tactical level. The operational level is the fourth level down and that's basically that business area perspective where it's operational, it's business unit by business unit within the organization. So we've looked at things from an strategic perspective, we've looked at things from a strategic perspective which again is the highest level of the cross business area perspective. We realize that we're going to have issues down at the operational level that sometimes when they start to have an impact across business areas we need to escalate those problems up to the tactical level first and then to the strategic level to get issues resolved. So the level down in the framework is the operational level and the other level in the framework that we need to talk about is the support level and oftentimes the support level is basically those people or that part of the organization that has responsibility for program management and it's basically all of the different shared services parts of the organization for example information technology or IT, the legal area, the information security area, the audit area and the compliance area. Those areas that are shared services for the organization oftentimes they become the data governance programs partners in crime when it comes to the implementation of the data governance program. So basically we talked about I took the framework, the five by five matrix that I shared with you, I walked across the top, I walked down the left hand side. Now what I'd like to do is I'd like to walk through the different components at each of the different levels and share with you what needs to be considered specifically when you're implementing a noninvasive data governance program but at the end of this webinar I'm also going to provide a blank matrix that you can look at and a blank framework so that you can pick the terminology that you want to use to describe it to your organization for each of those different core components and different five levels that we're going to talk about. So let's walk through each of the different components and the first component which I consider to be, as I mentioned before, the most important component for a successful data governance program, that's typically the roles and responsibilities, the level of authority that is given to each of the different roles and responsibilities. So it's interesting because if you look at it, it's going to be a lot of new stuff that might not already exist within the organization but the truth is that before you go and start creating new committees and new councils and giving people new titles and giving them more work, the idea of being noninvasive in the approach to governance is to look to people that already play these types of roles within your organization. So at the executive level for the roles that we're going to talk about today, I'm going to talk a little bit about those guys in a minute. At the operational level, there's the operational data steward. I'm going to talk about the data governance council and there's other names that I've heard other organizations give that group different names, but the data governance council seems to be the one that's used most often in industry today. At the tactical level, there's the operational data stewards and those people that define, produce and use data as part of their job, basically could be anybody within the organization. And lastly, I'm going to talk about the support level of roles and responsibilities in the organization and as I mentioned before, that's typically the data governance team and those people within the organization that the data governance team partners with to implement might have seen this diagram before and I share this diagram all the time. It's my operating model of roles and responsibilities and even though the first response that people have often by looking at this diagram is that it's bureaucratic and it looks like it's new and there's so much going on with this and within this diagram, that's the reason why to the outsides of the diagram, I've listed that some of these things may already exist within the organization that you could leverage to fill these roles and typically I suggest that you don't try to plug your organization into these roles and responsibilities, in fact, I suggest exactly the opposite that we take these roles and responsibilities and we overlay it over what already exists within the organization and by doing that it becomes a lot less invasive to the organization where we don't know what they do but we're giving them a role within the governance of data in the organization. So I'm going to walk through each of these different levels first because basically it describes each of the different levels that I used in the noninvasive data governance framework that I just shared with you. So let's start at the top and let's talk about the executive level of the roles and responsibilities and typically it's composed of both business and technology leadership not only for data governance but for basically all other enterprise level initiatives within the organization and oftentimes the steering committee might already exist within your organization or at least the way that I'm thinking that you would want to make up the steering committee that you may have a similar body to that within your organization and just as I said before again on the outside of the pyramid diagram it says exists next to the executive level because within your organization there might already be something that you could take advantage of and you don't need to necessarily create another group within your organization for data governance and as I mentioned earlier for when these executives have meetings it would be ideal if the data governance program align item in the discussions that take place in those executive level meetings. Typically at the executive level these people don't have day-to-day activities and data governance but they do have the ultimate accountability for making certain that they understand how data is being governed across the organization. So the executive level they're kind of hands off but we need to acknowledge who they are because as I've mentioned organizations typically it's very difficult to be successful if your executive level does not support sponsor and most importantly understand those activities that are taking place around data governance. The next level down in the operating model is the strategic level and as I mentioned it typically is called a data governance council. I've seen it called a data governance organization or even a data governance office or the term data governance office. I oftentimes use that to describe the group of people that are putting the program into place rather than this strategic level in fact I've seen for most organizations that they use the term data governance council to describe the strategic level in the organization. So the council is typically the ultimate approvers of policies and procedures. They also act as the ultimate decision maker when decisions can't be resolved at the tactical level and they get escalated up to the strategic level of the organization. At the tactical level I often talk about the tactical level as being one of the most difficult levels to fill in your operating model roles and responsibilities. As I mentioned it's the first level of attack when it comes to looking at data issues from a cross business unit perspective. So if you've got data issues that are associated with a specific business area oftentimes those problems, those issues can be resolved down at the operational level but when those data issues now start to touch on multiple business areas there's a need to escalate issues from the operational level up to the tactical level and because of that we're required to identify people in the organization that are either facilitators or decision makers or authorities around certain domains of data and if they can't be the ones or if they aren't the ones that can make the decision then ultimately that gets escalated up to that strategic level that we just talked about but the tactical level becomes one of the most important if not the most important level of the roles and responsibilities associated with data governance. At the operational level oftentimes I talk about the fact that everybody in the organization has the word of the data and I know that sounds very complex and very large to a lot of people but the fact is that if our senior management, if our leadership understands that people that have relationships to the data need to be held accountable for those relationships to the data we can identify that most of the people in the organization either define or produce or use data as part of their job and so there's certain accountabilities that come along with defining data for example, before we define data for the umpteenth time people that have the responsibility and the accountability for defining the data should know that they need to look to see what data already exists before they create another version. As I mentioned earlier the people that produce the data if we can help them to understand the impact of the data that they produce on the organization it helps them to understand what they really need to benefit the organization and the people that use the data again, I mentioned that as being a no-brainer we really need to help them to understand what data is sensitive how the data is classified what the handling rules are that are associated with the data so that they can do their job without putting the organization at risk every day. So so far I've talked about the rules in the authority column I've talked about the executive the strategic, the tactical and the operational, the one last level that we need to look at is the stuff to the left of the pyramid diagram and that's the support level and so as part of our data governance program we need to define who's going to be responsible for running the program whether that group's in a business area or in a technical area we need to or a shared service and we need to define who's going to have the responsibility to support the program and facilitate the activities of governing data in the organization the other aspect of support are those data governance partners that I mentioned earlier anybody from IT to information to security to risk management to compliance to audit to legal any of those groups that also are not necessarily business units but they're supporting shared functions within the organization what we want to do is we want to make sure that we leverage the work that's being done by those partners of ours across the organization so basically I've also shared this diagram in the past it's the common data matrix that I've used to cross reference across the organization what data what different types of data exist in what different data sources who in the organization defines produces and uses that data across the organization so basically it's a simple two-dimensional matrix that can help you to inventory who does what with data across the organization and it can also help you to identify per domain or sub domain of data where this data resides who in information technology has responsibility for that data and where in the organization that is being used or by which parts of the organization are they using that different type of data so again as I shared with you with the pyramid diagram of roles and responsibilities one of the cool things about the pyramid diagram in cooperation with this common data matrix is that I kind of color coordinate them between the two diagrams I'm going to show you a copy of that in a couple minutes here but each of these different levels are represented at least the executive strategic tactical and operational levels are represented within a common data matrix so we can formalize who's accountable for what across the organization so like I said there's a lot more to be said about the different roles and responsibilities associated with each of the different levels and I'm going to direct you to some resources to learn more about that in a couple minutes but what I want to do is I want to go through the rest of the non-invasive data governance framework so I'm going to quickly go through section five and talk about why we need to address things like processes and communications and tools and metrics at each of the different levels so typically when we talk about processes from the executive level their responsibility becomes to endorse the processes to understand how we're applying governance to the processes and to endorse and to stand behind the need to get the right people involved in the right steps of the process and at the strategic level if we consider going back and viewing the pyramid diagram there's an escalation path along the right hand side where if we can't resolve issues at the operational level they get escalated to the tactical and then to the strategic level well typically the data governance council becomes the ultimate authority and the ultimate decision maker when we can't resolve things at the tactical level people are involved in processes associated with their domains or their subject areas of data the operational folks are involved in the daily processes that need to be governed and oftentimes it's the support part of the organization that define and enforce the processes across the organization from a communications perspective it's really interesting how organizations look at this because at the executive level as the very first best practice that I talk about very often the first one is that the executive level of the organization needs to support sponsor and understand what we're doing with data governance and the criteria that I use to determine if something is best practice is is it practical and doable and are we going to be at risk if we don't achieve that best practice well 100% of the organizations that I work with use the executive level supporting sponsoring and understanding data governance as being their very first best practice and one of the things that right out of the gate when you're starting your data governance program that you want to do is to get to raise the level of awareness of your executive level so they don't only just support and sponsor that's easy to do to say I support and sponsor something or to put money towards something but the fact is really we want to gauge what level they understand the activities of governing data in the organization from the strategic level under communications we need to understand that the strategic level the data governance council is going to meet regularly so the data governance team is accountable to the data governance council to make certain that the activities of data governance are moving forward in the direction that they need to be moving so often times at the strategic level at the operating status at this tactical level we need to focus at things from the subject perspective or from a project perspective and make certain that the communications are being governed associated with each of the different subject matters of data and each of the different projects that are going on within our organization at the operational level and I often times talk about the communication plan for data governance including orientation to data governance bringing people on board data governance and also then providing them ongoing communications associated with data governance when it comes to the communications at the support level well typically we work with the people not only the team that has the responsibility for governance but for all of those partners that I mentioned before to plan and to develop and to deliver appropriate governance in different levels across the organization from a metrics perspective the way where we get our executives and executives involved is often to approve on the metrics or to approve the metrics that are brought to them so the data governance team has the responsibility to go through the data governance council to define a set of metrics that will demonstrate to the organization the value that data governance is bringing to the organization well often times it needs to be taken to the executive level for them to approve the metrics but if we don't achieve the goals that we set for ourselves in the metrics that it's up to the executive team to act on the fact that we're not achieving the goals that we are trying to achieve at the strategic level often times as I mentioned before the data governance team creates the metrics and brings those to the strategic level so that they can accept and approve the metrics and then as part of the ongoing communications with the strategic level the metrics are shared and the information about where the organization compares to those metrics and where we're demonstrating value to the organization according to those metrics are often times communicated at the strategic level but it becomes their responsibility to accept the metrics at the tactical level we want to work with the people that are the domain stewards the enterprise subject matter experts to define specific metrics associated with their domain or their subject area of data at the operational level we want to make sure that we can measure things from their daily operations meaning how much time does it take to get to the data how much do they trust the data how much time do they spend manipulating the data to make it the way that it needs to be to add value to the organization and from the support level we want to look at what it takes to really collect and report on the metrics across the organization so with the last row the last column of the framework is the tools and we also want to make certain that we're addressing the needs of each of the different levels associated with the different tools that we use within the organization so what are some of the tools that we as an organization as a data governance organization might want to provide associated with the executive level the tools or the things that are developed in conjunction with the executive level are the directives for data governance the reason why we're putting governance in place the approved charter in the organization says that the executives understand not only what we're doing but how we're going about doing it who we're going to involve how we're going to involve them and how much time we're going to expect from each of the different groups that we work with as we roll out our governance program so it becomes important for the executive level to provide those policies and those directives to the organization that data governance is important and to demonstrate their level of support sponsorship and understanding that I mentioned a few moments ago at the strategic level the tools that we want to develop the focus on the strategic level are typically those best practices associated with data governance they want to know that what we're doing is following industry standard or industry guidelines for governing data so a lot of times when organizations get started they start by defining a series of best practices and comparing their organization to those best practices so that when they define the roadmap in the action plan for data governance they're not taking a ready fire aim approach they're taking a ready aim fire approach associated with making certain that the actions of governing data follow up with each of the best practices that have been defined and approved at the strategic level at the tactical level oftentimes the tools that the data governance team can provide to the tactical level are things like the standards and the requirements and different workflows and ways to be able to document standards and requirements and workflows I know that with one of the organizations I'm working with right now who's taking more of a federated approach to data governance the data governance office has the responsibility for defining ways for parts of the organization to define their standards a consistent way a standard way for defining standards as it might be also a standard way for defining requirements for different projects and a standard way for documenting workflows associated with the activities that are taking place within each of the business areas within the organization at the operational level we want to make certain that we're addressing their tool needs as well and oftentimes those tool needs are things like the business glossary the data dictionary the metadata repository that houses all the information about the different types of tools that are being used within the organization and oftentimes those support areas the areas like the team itself and support through their shared services to data governance there's a lot of different artifacts that I've shared not only through this webinar but through other webinars things like the common data matrix the governance activity matrix that can help the different partners within the organization to understand how we're approaching implementing governance and also to share with them the information that we've collected along the way so that we can help them to improve on the way that they're already serving the organization so basically these are the two diagrams side by side that I just shared the operating model and the common data matrix and as you can see the colors are pretty closely coordinated between the two and the reason that I do that is so that if you can see yourself in the operating model or you can see yourself within the common data matrix to the overall operating model for governing data within the organization so there's color coordination between the different matrices oftentimes they're used to cross-reference the different components in the organization to the different levels certainly the operating model is broken down by the five levels so what I suggest is that you might want to consider taking the starter non-invasive data governance framework and filling it in with the things that are most appropriate to your organization so let's go back to the operating model to begin with or I'm sorry, the framework to begin with and as you can see we basically walked through each of the different components of the program across the top and we dissected them according to each of the different levels that we've defined as being important to address as part of our governance program so to start with something like this we kind of persuade you to go down a non-invasive approach to data, or head towards a non-invasive approach to data governance perhaps what you want to do is you want to use a blank version of the framework and put in for your organization what are we calling the people that exist at the at the executive level the roles that exist at the executive level versus the strategic tactical operational and support level and how are we going to handle processes or how are we going to engage the executive level of the organization the strategic tactical and so on for processes, communications metrics and tools again, it's just a framework that you could use to help you to get started defining those things that are important to your organization so the last thing that I want to talk about today is taking a look at using a model that's very similar to the framework to compare the different components across the different approaches to data governance and so typically I talk about three different approaches to data governance there's the command and control approach there's the traditional approach and there's a non-invasive approach and the basic difference between them I will show you in one second now this is the diagram that I use to cross reference the different components down the left side with the different approaches to governance across the top and as you can see here the significant differences between the different approaches when it comes to the roles and responsibilities is that in the command and control approach people are assigned into specific roles associated with governing data and the immediate feedback is that this feels like it's something it's additional to what we're already doing within the organization so it feels as though it's over and above existing work effort so people's responses to a command and control approach when you assign them into roles if they're already busy 100% of the time 120% of the time the first response will be well where am I going to find time to participate in these roles so you're assigning them something it immediately feels as though it's something it's over and above what they're presently doing in the traditional approach they're assigned into specific roles and they're identified and they're being told that they now play a specific role within the program but there's not necessarily any execution and enforcement of those roles for those people so it's typically we're going to put a program in place and our idea is that you'll follow the things that we put in place for the organization so we'll identify you into a role but we're not going to assign it to you we're not going to down your throat so to speak in the noninvasive approach when we're talking about the roles the word that I use is that we recognize people into roles which means that we recognize if people define data as part of their job or we recognize if they produce or use data as part of their job and if they do we would denote them as being an operational data steward if they have responsibility for example in a university setting somebody that kind of owns the information about the student the registrar's office that the registrar might be that person that has that tactical level of decision making authority associated with that specific domain of data so we're going to identify people that may already be called out in policy or other directives that have responsibility associated with certain buckets of data in the organization let's look at the component of processes according to each of those different approaches real quickly in the command and control approach data governance is something that's brand new to the organization we're going to define new processes in the organization and they're all going to be governed in fact we're going to call them a collective of governance processes so the first thing that people do when they look at these governance they point to governance and say that's the reason why we're doing these processes so it's really more like a command and control we're going to have governance take over each of the processes to make sure that they're being followed in the traditional approach in a lot of organizations they define what they call a data governance process that they apply to different aspects of their organization issue resolution request for access to data governance process we do neither of the two that I just mentioned instead of focusing on everything being a new process or applying a single process across the organization we take the existing processes that we have and we apply governance to those processes so again rather than calling them data governance processes which is a lot more invasive we take less of an invasive approach and we apply governance to and we continue to process what they are as far as communications is concerned the difference between the three approaches in the command and control approach people are told that you will do this and the traditional approach they're told that you should do this we can't really force you to it but you should follow those things that we've put in place in the noninvasive approach the approach is that since we're looking to formalize accountability the first time we're doing this we want to help you to do it more efficiently more effectively basically more formally across the organization from a metrics perspective oftentimes in the command and control approach the idea is that they're going to measure return on investment how much money is data governance bringing into the organization or how are we improving profitability in our organization it's very difficult to be able to link that directly with data governance or the fact that we have a governance program in place in the traditional approach to data governance typically organizations measure the quality of the data and the value of the data that is being received by the people in the organization and in noninvasive data governance we focus more on how are we advancing the ideas of governing data into the organization how are we addressing each of the different approaches and the last one I want to look at in this model of comparing the different approaches according to the components the tools aspect of it in a command and control approach you'll find that a lot of organizations purchase their tools first in a traditional and when you purchase your tools first basically you're setting a level of expectations for the organization because typically if you purchased one of the data governance tools on the market you're spending a decent amount of money for it takes a lot of resources in order to apply that to the organization but organizations that take a command and control approach purchase first in a traditional approach the first thing that organizations look to do is to leverage existing tools within the organization existing repositories, dictionaries, glossaries modeling tools, ETL tools anything that already exists that has metadata that's going to be useful to people in the organization and in the noninvasive approach the idea is to leverage what we already have and then to build and to apply what we are learning through the different things the templates and tools that we build and apply those requirements that we have for those tools to the tool that we decide to purchase for our organization. So basically in the last 50 so minutes I've discussed five things with you basically I shared with you a framework for noninvasive data governance we talked about the five core components that are components to basically pretty much every successful data governance program we talked about looking at those components from five different levels the executive strategic tactical operational and support we went through each of the blocks one by one from looking at each of the different components by each of the levels I shared with you a framework to complete the framework for your organization you can use the information that I've provided or fill in your own and lastly what I did is I used that framework to compare across the different approaches that are available when you're starting out with your noninvasive or with your data governance program. So with that I'd just like to do a quick reminder of the upcoming webinars in March we'll be talking about applying data governance to agile overall we're going to talk about governing data governance metadata and master data metadata as well. So with that I'd like to turn it over to Shannon for the Q&A. Bob thank you for another great presentation and just to answer the most commonly asked questions I will be sending a follow-up email by end of day Monday with links to the slides, the recording and of the matrices. Just so less confusing we've got a few questions coming in already if you have additional questions submit them in the Q&A in the bottom right hand corner. So Bob what are some of the data governance tools any examples that go with the framework? There's a lot of tools so there's one thing you can develop yourself internally and that would be the things like the common data matrix the operating model the governance activity matrix where we cross reference steps of an activity we do a lot of tools that are available on the market tools like Calibra and Diacu and Informatica and a lot of the major players FAP FAS have their tools associated with data governance oftentimes those tools are metadata collection tools and metadata utilization tools where we can not only build information like business glossaries and business definitions but we can also build workflows where we can engage the appropriate people at the appropriate time. So typically there's two types of tools there's the ones that we develop internally and then there's the ones that we can acquire on the market today. Alrighty and you know the framework seems to be well suited for large organizations so this particular person starting up data governance in a smaller organization to adapt to the smaller org would it make sense to combine executive and strategic into one layer than the others into a second layer? You know what that's a great question and certainly for a smaller organization these are just frameworks these are just models that you need to use to adapt to your organization. So if your organization does not have level upon level of bureaucracy then certainly you can decrease the number of levels within the operating model and the one that I've seen most organizations attempt to do is to combine that executive with that strategic level. The organizations that I've found to get the most use out of a tool like the operating model kind of keep this the tactical level will keep the strategic the tactical and the operating levels as distinct levels and don't try to join those together although I have seen some organizations try to blow up that model into nine different layers and they spent a lot of time describing to people what's the difference between level 6 and level 7. It really needs to be suited to the specific organization. So Bob I did not get what is quote-unquote new in the framework what's different from your previous framework? Well you know what the truth is that I didn't really have a previous framework. I didn't have a single diagram to use to be able to look at all the things that you need to consider in order to implement a data governance program. And so what I did was I started to document it into a document and then the image of the diagram came to me. So what it is is it's just a simplified view of the primary things that we need to focus on for how our data governance focus on and it's looking at them from each of the different perspectives that are necessary within the organization. So if you're familiar with things like the Zachman framework where he talked about who's what's when's why's where's and how's of the organization's architecture by different perspectives it's very similar to that where these are the things that we know that you're going to need to focus on and these are the levels of the organization that we know that you need to focus those components too. So it's really something that's brand new, it's not something that I've used before. And I think we have time to sneak in one more question here. How long do these data governance projects last with this framework? Ooh, that's a dangerous question. When you call something a data governance project I've got a little bit of an issue with that. So projects typically have a beginning, a middle and an end or at least a beginning and an end. And so if you're talking about the project of implementing the data governance program, actually the reason why it's called a data governance program is because it does go on forever basically. Once we've put the program into place we want to make sure that we're continually governing our data moving forward. So that's the difference between the project and the program. I suggest that you, if you're going to create a project plan for developing your program that it's going to take you a period of at least a couple months to complete each of the different aspects of the framework. And again you might not focus on all of them at once. So you might take the roles and responsibilities first and focus on those and get those strictly defined before you move on to the roles and before you move on to the processes that you're beginning to govern. And therefore you could start to use the framework right away. It doesn't take a certain period of time to implement it during your project. All right. Well, I'm afraid that's all we have time for. We're right at the top of the hour. Just a reminder to everyone I will send a follow-up email by end of day Monday with links to the slides, the recording of this session and the updated matrices. And just want to thank everyone for being so engaged in everything we do and all these great questions. And Bob thanks for another great presentation all next month. Hope everyone has a great day. Thank you very much.