 And my name is Shannon Kemp, and I am the Executive Editor of Data Diversity. We would like to thank you for joining the current 2014 installment of the Monthly Data Diversity webinar series, Real World Data Governance with Bob Siner. Today, Bob will be discussing navigating the ocean of data governance tools. Just a couple of points to get us started due to a large number of people that attend these sessions if you will be muted during the win arm. For questions, we will 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 or questions via Twitter using hashtag R-R-W-D-G, 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 any additional information requested throughout the webinar. Now, let me introduce to you our speaker for today, Bob Siner. Bob is the President and Principal of KIK Consulting and Educational Services and the Publisher of the Data Administration Newsletter, tdata.com. Bob has been a recipient of the Damon Professional Award for significant and demonstrable contributions to the data management industry. Bob specializes in non-invasive data governance, data stewardship, and metadata management solutions. Bob will also be speaking at our upcoming Data Governance Financial Conference happening September 29th through 30th in Jersey City. And with that, I will give the floor to Bob in this webinar. Hello and welcome. Thank you very much, Shannon. Happy to be here. Happy to have everybody on board for this webinar. And good afternoon. Good morning. Good evening. Good tomorrow. Whatever time it is for you, wherever you are. I appreciate your time, taking your time out of your busy schedule to participate in this webinar. I always enjoy doing webinars on data governance tools. This is a really interesting one. And this one's going to be, you know, kind of packed with a lot of information. So I'm going to go through a lot of slides really quickly. But just to let you know, this is not a webinar specifically focused on any of the individual tools. Although I will mention some of the analysis that's been taking place in the industry around those tools and provide links to where you can learn more about these tools and other things as well. But it's not going to be to dissect any specific tool. It's going to be more about really navigating the ocean of data governance tools, as you can see in my picture on the front slide. And I thought about putting ocean liners and things like that. When you're on an ocean liner and you're on a cruise, you don't really need to navigate. But when you're looking to purchase tools that are going to help you with anything that you're doing in your environment, whether it's data warehousing, MDM, data quality, data governance, it certainly is. And it may feel like that there's an ocean of tools out there. So anything that I can provide that will help you to kind of navigate that ocean is what I want to do. Shane mentioned the webinar series and the fact that I'll be speaking at the Governments Financial Services Conference. I'm also, the weekend after that, speaking at the Enterprise Dataversity event in Chicago. So if you have interest in attending either of those, it would be great to have there. And it would be great if you would come introduce yourself to me if you are attending at those events, great events, and think it a lot out of either one or both of them if you decide to attend both, like myself. I wanted to do a real quick plug for the upcoming webinars in the series. Next month, we'll be doing data governance and metadata best practice the month after, risk and compliance, selecting the right approach. And then we're going to, forever, popular subject is big data governance, what it is, why it's necessary, is it even such a thing as big data governance or is it just the governance of big data? I'm kind of giving away where I might be coming from with that webinar. I also want to share with you a couple of things that are brand new with me. Not really shameless plugs, more like I want to share information with you that's available out there. I want to let you know I've been talking about it for a while. The final copy has gone off to the printer in September 1st deadline date. It looks like we're going to hit that date. That first book on non-invasive data governance, the path of least resistance and greatest success will be out through Amazon, through your favorite book retailer, maybe not locally, but certainly online. I wanted to also point out to you there's a lot of information about non-invasive data governance on my website and I was fortunate to have a brilliant network who redesigned the site for me and it's going through some variations right now, but please visit the IK Consulting site. It will have information about where my next speaking engagement is next webinar and there's more information about non-invasive governance. And as Shannon had mentioned and as I mentioned, the Data Governance Financial Services Conference is coming up in a couple of weeks in Jersey City, New Jersey. It is a data governance conference, again, focused specifically on the financial services industry. And then Enterprise Data Diversity, I'll be giving a couple of presentations there as well in Chicago on October 8th and 9th. So I look forward to seeing you there, hopefully we'll see you there. And so what I want to do is I want to talk today about data governance tools and the first thing I typically do is I share the abstract that I used for the webinar as the introduction slides. And so oftentimes people ask me the question, well, what exactly is a data governance tool? And data governance software vendors tell us what their tools do. There's tools that we can develop internally. Is it a traditional data dictionary or glossary? So basically the answers to those four questions you see there in reverse order are yes, yes, yes, and whatever you say it is. So a data governance tool, maybe you have a specific perspective coming into this webinar. Maybe when you leave this webinar you'll have a different perspective and you may find that some of the tools that I share with you are things that you may be able to develop internally that may serve some of the same purposes or at least get started before you venture into the ocean of data governance tools. So in this webinar I'm going to look at a bunch of different things. I'm going to look at the tools on the market, the types of tools that can be delivered internally, the pros and cons of each. And I'm going to go through some of that stuff rapidly with you. Hopefully it will make sense to you. And if you have questions, please use the bottom right-hand corner as Shannon said to ask your questions. It'll make sure that we get those questions answered. Actually the things that I'm going to talk about today are these five subjects, data governance tool requirements, tools that are available on the market, tools that can be delivered internally. I'm going to share a bunch of those with you. How to leverage tools that you already own. And then I spent a couple slides talking about how to justify the purchase of the available software that's out there on data governance and data governance tools. So that's the agenda for today. Oftentimes I will start out with a quick definition of data governance. For those of you who have not attended my webinars in the past, I figured I'd like to give you a definition, the definition that I use for data governance. Some of my clients use it. Some of them think it's worded too strongly. But it's really up to the organization to say how much teeth they have behind their definition of data governance. The data governance is the execution and enforcement of authority over the management of data and data-related resources. And no matter how you frame your definition of data governance, the truth is typically at the end of the day, the organizations want to execute and enforce authority over the management of the data. The definition that I use for stewardship is it's the formalization of accountability over the management of data-related resources. Well, if you think about it, when I talk about staying non-invasive in the process, the idea is to identify and recognize people who are already stewarding data and give them the forum, give them the instruments and the tools that are necessary to help them to govern data better. So we're not really talking about assigning people into roles. It's more, let's identify who does what with data, and let's formalize the processes that we may already have in place. In that manner, it feels non-invasive. But if we need to define all new processes, then it typically feels a little bit more invasive than that. So these are my definitions of data governance and data stewardship. Just to let you know, some of my clients don't think that the definition of data governance is worded too strongly. So they've taken it and they've kind of meshed the two definitions of governance and stewardship, and they've used the definition of formalization of behavior associated with the definition of production and usage of data, or the formalization and guidance of behavior. So it's very important when we start to look at what tools are out there on the market to help us with our data governance program that we want to have a good definition of data governance and we want to be very specific in what we hope data governance will do for our organization. And if we can define those things, it makes it a lot easier for us to come up with our requirements as to what we need out of the tools that are out in the market. The last definition I want to share with you is the one of non-invasive data governance, and that's the practice of applying formal accountability and behavior to your non-invasive roles and responsibilities to existing or new processes. And on and on, I don't need to read the definition for you. It's right there. Really, the idea is that non-invasive describes how we're applying governance to ensure that the way that we're managing data assets is non-threatening. Oftentimes, people hear the term data governance and they go running for the hills. They think that data governance needs to be off-commanding control, that it needs to be heavy-handed, that the data needs to be rolled with an iron fist. And I believe everything but those three things. I believe that we can be non-invasive in the way that we do it and the tools that we purchase to help us to implement governance in a non-invasive way certainly need to enable us to do those things, to apply formal accountability, to get them people involved at the right time in the right processes for the right reasons. So again, the goal is to be transparent, supportive, and collaborative. So enough with the definitions. Let's jump into the tools. The first thing that I had was, the first question that I had is, is the purchase of a tool considered to be invasive? Is buying a tool and by getting people to use it going to be invasive? And I would say probably not, although people may look at it as something in addition that they need to learn, but we can use the tools, whether they're developed internally or they're bought from the outside, to help us to stay non-invasive in our approach, to get the right people involved at the right time. We need to understand what expectations come when you purchase a tool. When you purchase a tool and some of the tools on the market can be expensive, some not as expensive, but when we look at the total cost of ownership and we'll pause that in a few minutes as well, we can understand that with that total cost of ownership is some level of expectations of what the tool is going to provide. So I'll talk a little bit about that. If it's data that's being governed, oftentimes I've heard other people say and I've reused the statement, is that we're really not governing data itself. Data is going to do what we call it to do. It's going to be defined the way that we define it. Really what we're governing is people's behavior associated with the data. And then the last question is, can a tool or the use of a tool help us to govern behavior? And hopefully you'll draw some conclusions on those things by the end of the webinar. So the first thing that I wanted to do is take a look at what's going on in the market. And if you're not familiar with it, or maybe you are familiar with it, Forrester Research did an analysis of the data governance tools on the market in 2014. They called it the Forrester Wave, which I think is their regular approach to helping with smart data for smart decisions. So without further ado, I kind of want to jump into seeing what did they define as what's going on in the market. And hopefully you can read the diagram in front of you. If you haven't seen this, you can certainly go and research these different tools. You can go through Forrester, as I mentioned here. They are suggesting that you go to forrester.com to download the Wave tool for more detailed product information about these tools. But certainly what they're doing is they're saying that we've got risky bets, we've got contenders, we've got strong performers, and we've got leaders. But a lot of it, a lot of the decisions that we use to base our decision of what tool makes sense to us really are based on our requirements and what we need from the tool. So I get a lot of questions about the idea that maybe a business glossary or a metadata repository would be a governance tool. Well, certainly it would be if one of the things that you're trying to do, or one of the things that you're trying to achieve is to come up with a common vocabulary of how terms are being used across the organization. So there's a lot of tools that are out there. There are more tools that are listed in this diagram here. But certainly this graphic here gives you an idea as to what are some of the leading tools on the market. And what I'm going to do is I'll provide you a little bit additional information about these tools as we move forward into that section of the webinar. So what I wanted to do is also share some of the other ideas of what's going on in the market from other people. A gentleman by the name of Rajan Shandris in Information Week Magazine not too long ago talked about there being no single solution on data governance. He said, the problem isn't that there's a shortage of products. And as you can see by the graphic on the previous page, there are certainly a bunch of products. But it's really a shortage of the clarity and vision. And as I get to the point where I walk through each of the products and show you how they market themselves as products, you'll see that the clarity and vision is all over the board. There's not industry consensus on what a data governance tool should do, although some of the vendors may tell you that their vision is the vision. And I may agree with you with some of those vendors that got a lot of really powerful tools. And if you attend either of the events that I just talked about or that Shannon talked about, there's certainly opportunity to visit the exhibits and check out some of the tools, kick the tires of some of the tools. And you'll see that there's a lot of tools that do a lot of different things for you. You just need to understand that there may not be one tool that is going to help you do everything that you want to do around governance. So in this article, Rajan said that conversations about governance have to move from wide out. Organizations are budgeting data governance activities now more than they have ever done. There are suites of data quality, data analysis and done products. And he's suggesting that data governance software tools, a lot of them look more like business semantic tools and metadata management tools. I've provided a link there as well if you want to see more about that article. There's a lot of information that Rajan shares. A couple of additional insights. A friend of mine, Sanil Sures, who has done webinars through Data Diversity and has spoken at the Data Diversity events, put it together in an article called Evaluation Criteria for Data Governance Tools. And he listed these criteria. And again, I provided a link to the article on www.InformationManagement.com. So you may be able to look at the usability of a business course, custom attributes, custom relationships, all of those things. The items that I've underlined, I'll come back to them in a few minutes here, but the approval workflows, the data policies and standards and procedures, the quality scorecards, the issue logs, the issue resolution processes, those are truly governance requirements that organizations have around their tools. And so some of the things that you may want to look at when you're evaluating tools is how do they have workflows? How do they identify or help identify people as stewards and get them actively involved? What type of means do they have for recording policies and standards and enforcing policies and standards and processes and things like that? Organizations, as they're starting to measure the effectiveness of their governance program, are also looking at data quality scorecards and issue logs and issue resolution processes. And again, I'm going to share with you in a couple of minutes some tools that you may be able to develop internally first. They're not going to help you to resolve issues in an automated way, but it is going to be a way that you can define the process, define the roles that are associated with their involvement in the process. And so again, some of the tools on the market may provide automated means for doing these things. I'm also going to share some things that you might be able to develop internally that will help you and help your governance program wherever you may be. There's another article that was written. It's more of a blog from Michelle Getz from Forrester. She talked about our data governance tools ready for the data governance, and she talked about how organizations and vendors are still really married to more data management than data governance. Again, going back to Sunil's slides, he talked about managing workflows and things like that, and that's really a little bit outside the realm of the legacy data management tools, but she states that vendors are still married to that legacy of data management, that there are no single data governance tool across all five data governance servers that they talk about, and those being MDM quality, information, lifecycle management, metadata management, and security. So some of the vendors have made significant strides in that direction. The vendors that they called out were Trillium Software and SAP as being the products that provide governance metrics, and they pointed out Coibra as being really the only integrated suite of products, and they're market tools that help with strategic stewardship and operations. So please, again, go visit that link and see what Michelle has to say about some of the tools that are on the market. She says there's no single solution, but there are data quality and MDM and metadata tools that are often tightly connected to governance that may not be being sold as governance tools. And at the end of the presentation, I'm going to run through some of the tools you may have internally in your organization already that you can use to leverage towards your data governance initiative. So identify the tools that enforce best practices. Look at tools that connect data conditions and processes to business outcomes. You know, certainly understand the vendor roadmap of what tools are out there, what strategies they're taking before you jump into purchasing a tool. And the last thing I wanted to identify as to what's going on in the market was an article from Andrew White from Gartner, and the link is there, that data quality does not equal data governance. The business users tend to say that they own process, but they really tend to own the data. And in fact, if you've heard me speak before, you know, I don't like the term ownership around data. I think that the term stewardship is more appropriate. It's being used more often in industries. Ownership implies it's my data. I can do with it what I want, just like it's my process. I can do with it what I want. Actually, the term that's being adopted in more organizations now than ever is that we have stewards of data, people that are taking care of the data for the organization, depending on the role that they have with the data that they work on. He said his conclusion was get over it, start talking about stewardship instead of ownership kind of the same way as I think of things. When someone talks about governance without any context, basically, it's vapor aware. And basically, he concludes that governance out of context is dangerous. We need to attach it to something meaningful within the organizations. So when we look to purchase tools associated with data governance, we really want to attach that to some meaningful outcome in our organization. He says that the governance of data and information needs to start to be applied first with the focus of data and information that's meaningful to the business. And there's also ways that you can start out with tools that you develop internally that may help you to take several steps down the right path of your governance program, and you may not need to go out and purchase the tool right away, but it may help you to understand better what these tools will be able to do for us and then help you to make your decision as to how these tools will enable your organization with your data governance program. So the first thing I want to talk about is tool requirements. First thing that got cut off, I don't know what that is. I don't think that ever happened to me before, but let's talk about tool requirements here for a minute. And again, I'm going to go back to Neil's article and focus on those things that he said. He talked about the usability of a business glossary. I would say that if I said 99% of my clients are looking at business glossaries and data dictionaries, I think I'd be lying to you. I think that 100% of the organizations are looking to get a better understanding of the data that they have. One of the things that drives their senior management, and maybe your senior management, is that they ask the same question to multiple people and they get multiple different answers that people feel are the appropriate and the correct answers are based on their understanding of the data, based on the data that they go to to provide their answers. Organizations are saying that the use of business glossaries are very important in helping with governance because it helps us to document a place where we have the standard definition. We have the flavors of the definition that may be used by different parts of the business. You know, come attributes and the ability to be able to extend a product to record information is important. Custom relationships between items that you're managing and being able to recognize who your stewards are, all these things are really, really important. So this may help you with your evaluation criteria of data governance tools and to go back and visit that article or go back and visit some of the earlier webinars that I have done or that have been done through Dataversy to help you to determine what your evaluation criteria are for the tools. But the ones that I underlined there, those are the ones that I hear organizations talking to most often regarding, you know, tools are available to them, what they want to use these tools for, and hopefully that list will help you as you put together your evaluation criteria for data governance tools, however you define a data governance tool, either internally or externally for your organization. Another friend of mine, Kelly O'Neill, from I believe it's First San Francisco or First San Francisco Partners, she's also been very active through Dataversy. She wrote an article about how technology enables data governance, and again, I provide a link to that and I suggest that you go out and take a look at it, but the cost of data governance is hidden in an efficient process, excessive data management activities, inability to use information. She also talked about how data governance specifically helps establish strategy objective policies that helps to effectively manage corporate data. Again, she's talking about specifying accountability and executing decision rights. That's what we need from our data governance tools is to help us specifically with these areas. She also talked about the fact that we're going to do this by creating and enforcing policies on data security and access rights. We're going to monitor and measure quality and movement. We're going to provide benefits of having implemented the MDM and so on and so forth. Again, what types of tools are available for purchase that will assist us with implementing this functionality? Again, to look at Kelly's article, I know it's a couple of years old, but I'm certain that she would love you reached out to her and had some questions to her about her experience with data governance tools and tools that are in the market. Here's a couple of things that I would suggest. I would suggest that we want to look for tools. If we're navigating the ocean of data governance tools, that we want to look for tools that will help us to assist us in formalizing accountability for the management of data. That would be through linking the stewards to the data and linking the stewards to the processes, triggering communications to the accountable parties and formalizing decision-making workflows through your organization. What I mean by formalizing those workflows is that we make certain that we get the right people involved at the right time. If we define the steps and we follow those steps in a standard or in a formal way, and we define who it is that we need to get involved in those steps and what the expectations are from their involvement in those steps, that's again what we're looking for from our data governance tools. We're looking to formalize accountability rather than, and again if you're going to stay non-invasive, we're going to formalize the accountability rather than going at people well from the way I've described it in the past and just go at them with a 2x4 and hit them over the head and change their title and change what it is that they're doing. Well, if you wonder why people push back to data governance, that's one of the reasons, because oftentimes organizations take more of a command and control or a more invasive approach rather than trying to identify who does what with the data now and make certain that they understand that they have some impact on the quality and the value of that data downstream or even upstream in the organizations. So we will look at when we're defining requirements how do these tools help us to formalize accountability. We wonder about how do these tools help us or to assist us in governing workflow, whether that's proactive or reactive workflow, whether it's building governance into a system development lifecycle methodology or an application development lifecycle methodology whether it's to define in terms of RACI or RACI as it is now with a lot of organizations where we identify who's responsible, who's accountable, who needs to be supportive, who needs to be consulted, and who needs to be informed. Also a way of being able to cross-reference, again, the methodology, the projects, the project workflows, the risk management workflows, and those types of things. We want to make certain that we can get the appropriate people involved at the appropriate time. Some tools that are on the market may help you to automate that process, may help you to be able to link to some of those people, some of those stewards that you need to be involved in the process, and it may be a way to, in an automated fashion, help you to monitor whether or not people are being involved or participating in the ways that they need to participate. So again, there's some tools that you can develop yourself that will help you down that path, but some of the tools that are on the market may actually be able to demonstrate to you how they can engage people in process through an automated fashion, using Outlook, using whatever email system or any process flow system that they have within their organization. So there's some tools to assist us in communications. If I said 99% of my clients look at data governance, look at communications, and awareness as being important, I'd be lying to you, because it's 100%. It's 100% of the organizations that recognize that data governance oftentimes requires culture change in an organization, so we need to make certain that we know specifically what it is that we need to communicate what the audience is or who the audience is that we need to communicate to and put some structure around how that communication is going to take place. So you can record and cross-reference the content and the roles, formally identify the communication topics, the audience, the content, the messages, all of those things that will help you to communicate effectively with the people in your organization that you need to communicate, whether it's at an operational level, tactical, strategic, executive level, or it's at a support level. And there's a tool that I'm going to share with you in a couple of minutes here, because this webinar is only an hour, so it can't be more than a couple of minutes here. Some tools that you can develop internally that will help you to build your communication and awareness plan, and hopefully that will take you part of the way toward the implementation of your governance program. Again, it looks like all of these words are going to be cut off, but the next thing I'd like to talk about is taking a look at what are the tools that are available on the market. And again, going back to the Forrester research, the Forrester research identified these tools as being the risky bets, contenders, strong performance, and leaders, and again, go to the Forrester site if you want to learn more of those tools. But what I've done is I've highlighted a little bit of information for you, hopefully to make it easier for you to be able to get to these tools, but there's adaptive ASG, Calibra Global ID's IBM, Informatica, and the others on the next page, and I've provided their websites there, so hopefully that'll give you some linkage to them. But the reason why I laid this out this way is that I wanted to show you how they are marketing themselves, at least their websites. So what I did was I went out to each of these websites and I saw what's the key message that they want people to get. What's the key understanding of what it is that they offer? And as you can see, the messages are all over the board. Adaptive talks about being a business glossary, metadata enterprise architecture, and IT portfolio manager ASG is cloud content and systems made. Calibra sells as being the data governance center and the tools. And I would say that out of the tools on the market that market themselves as being data governance tools, they may be a big leader in some of the things that they provide. And I know soon Neil has worked with them and some of those evaluation criteria would be rated quite high when you go and look at the Calibra tool. Global IDs is the same way, but the message that they're sharing is that they manage, integrate, govern business information, and again, globalids.com. And again, they talk to those folks about how that will help you, how governance is such a key in what Global IDs does. IBM, again, looks for a product that they had, and they talk more about the governance, data governance unified process, informatic data integration, masking quality, replication, MDM, and a bunch of other things. Other tools on the market, information builders, innovative systems, SAS, SAP, Trillium, they all market themselves differently. There's very few that market themselves specifically as being data governance tools, although some of them do. I would venture to guess that most of these tools will have a very positive impact on your governance program. Used for their purposes, but they may help you in a lot of other areas as well, but if you're looking for tools specifically to help you in the area of governance, then you may want to take a very close at those vendors that market themselves as being governance tools and ask them, why does that relate to the requirements that you lay out for them? So basically, this list of 10 or 11 or 12 vendors that I provided is a who's who of data management tool vendors. And again, some of them focus on data governance and some of them don't focus on data governance. Some of them focus on things that are either ancillary or related to data governance. So again, like I said, I wasn't going to do a deep dive on any of those individual tools. If you want to have conversations with me about those tools, I'm not certain I'm going to be a whole lot of help to you, but I'd be glad to talk to you about those. I'd be glad to hear from you as to how the tools that you're using are helping to enable your program and your organization. So let's jump into here real quickly about some of the tools that you can develop internally. I didn't initially consider this to be a tool, but I had several people that came to me and they called it something like the picture worth a thousand words tool. And it describes policy principles and dimensions. And it could be considered a tool, not necessarily an automated tool, if it's something that you can use to help share the message about what data governance is for your organization. And right down the middle of that diagram are four core principles that a lot of my clients subscribe to and a lot of organizations subscribe to, which is data must be recognized as a valued strategic asset, that we must have clearly defined accountability, that we must follow the rules from the internal and external sources, whether it's regulatory compliance rules, business rules, data sensitivity rules, and those types of things. Organizations, organizations like the federal government are not coming to us and asking us if we want to follow the rules, they're telling us that we must follow the rules. And so that's certainly one of the core principles of governance. The last one is that the quality and the application of governance itself must be done consistently across the organization. So this may be a tool per se, but it is kind of a tool that you can use to help you to communicate to people in your organization. Another one is being an operating model tool, and I'm going to run through some of these really quickly, and these will be available to you. The slide deck will be available to you if you are interested, and you shouldn't even ask that anymore. We will also send you a template that has copies of these tools, but if you have comments on them or you'd like to talk to me about them, please reach out to me, and I'll be glad to have that conversation with you. But the operating model of roles and responsibilities, every organization seems to understand that the roles and responsibilities associated with data governance are one of the backbones of a data governance initiative. Here's a tool that I use. Again, it's a graphic that can be used to help to describe what the tools are or what the roles are associated with data governance. And so the first response that a lot of organizations have when they see this tool or when they see this diagram of roles and responsibilities is, that's really bureaucratic. It's over and above. We have all those different levels when other organizations look at it and say, you know what, we've got an operational level. We've got a tactical level. We've got a strategic level. We've got an executive level that we need to leverage as part of this program. We've got a data governance team. We've IT involved, because IT houses a lot of the information about the data and the systems that we try to do governance without IT's involvement, then it's pretty much a mistake because we're not using some of the knowledge that we have as an organization. So people look at this diagram and the first response is that it looks very bureaucratic. The fact is if we take a look at what already exists, what's new, what needs to be leveraged within the organization, and we find out that we really want to focus primarily on the tactical and the strategic levels for a lot of organizations use this tool as a communication tool to their organization as to what are the roles and responsibilities that are really necessary to focus on data governance. It's a common data matrix tool. I've shot it in a lot of webinars, and if you want information about it or you want a copy, I believe Shannon will be sending that to you as well. A spreadsheet that I use, and I'm going to share it with you in a second here, that the common data matrix tool is something that you can develop yourself that assists you in inventorying what data you have, what data stores, what systems, system records, how to identify and recognize who the people are, who are stakeholders in the data. It helps to formalize accountability where people are definers, producers, and users of data. We need to inventory that. Certainly it's very difficult to manage data as an asset of an organization if we don't have data about the data, and everybody knows that's metadata, but if we don't have information that associates the people of the organization to the data, it also becomes very difficult to implement a data governance project or data governance program, I'm sorry. It helps in formalizing accountability. It helps to record cross-reference of domains and potential stakeholders. That's really important. It helps us to manage master data management categories. It helps us to identify who in the organization are stakeholders, again, from the strategic, tactical, and operational perspective. Here's a copy of a common data matrix, and I know it's kind of small, and I know it's very difficult to read on this slide. Let me at least talk to it in theory, and if you'd like a copy, there will be a version of the spreadsheet that will be used here that will be associated with the email that Shannon talked about setting out within a couple of days of the webinar. The thing that this tool sets out to do is it helps us to cross-reference the types of data that we have in the organization with the people in the organization that define, produce, and use that data. For this example, student data and student administration data may reside in these systems that I'm highlighting, and we may have people in IT that are data subject matter experts and system subject matter experts have that specific data, and there may be people in the different administrative units and functional units of the organization that define, produce, and use that data. There's a lot to be said about the common data matrix. I'd love to have that conversation with you as to how this can be used. That's not specifically the focus of this webinar, but I wanted to at least share with you that it's a pretty easy tool to implement. To a client, my clients have told me that this becomes a very valuable tool in understanding who does what with data across the organization. If we want to hold people fully accountable for what they do with the data, we need to know who they are. Again, this tool, even though it's not maybe the best automated tool in the world, it is a spreadsheet, but it does help you to get a view as to when we ask a question associated with the data, why do we get different answers depending on who we ask? Maybe it depends on what data they use or what data they go to or what data they understand or how they understand that data. This common data matrix becomes a very valuable tool in the organization's artillery that they use around implementing governance programs. Another version of that tool is something that I started years ago and this organization called it a university data matrix. That focus was on data classification. They realized that they had highly confidential, confidential, sensitive public data that all had different handling rules. They represented that on here with red for highly confidential data, yellow for sensitive data, and green for public data. They put on here whether or not these folks define, produce, or use sensitive data or public data or highly confidential data. Again, as a way of being able to cross-reference who does what with the data across the organization. Workflow templates. I talked a little bit about how Sunil talked about the importance of workflows. Workflow template tools, again, there may be something that you can develop internally, and I'm going to share a couple copies or a couple versions of those with you. Again, they assist in finding processes and workflows, records the cross-reference of process steps and governance rules, and that's really where it becomes worth its weight in gold is that we can define, once we've defined the rules, and we've identified the rules, R-O-L-E-S, not R-U-L-E-S, the rules associated with governance in our organization, we can help people to understand when they need to be involved in the process, what the outcome of their involvement in the process is. Again, using things like racy or RASC, cross-referencing methodologies and things like that. Issue resolution template tools, again, it's a workflow. The work here is issue resolution. There's other organizations that have done this for certification processes, for data that gets fed to the data warehouse or data quality processes and things like that. So here are some versions of those tools that you can develop internally. Now, this client developed this as a spreadsheet, but they made it hyperlink sensitive, and what they did was they identified the six main actions that they wanted to accomplish through data governance, resolving research information, quality issues identified and monitor risks, but these were some of the core activities. The way they set it up was so that if you clicked on one of those links to the different actions that they wanted to be able to repeat and to govern, it would become a copy of the steps that are associated with the process, the roles that are associated with the process, and they used the blocks that cross-referenced the steps and the roles to dictate or not dictate to specify who is responsible for this action, who is accountable, who needs to be supported, who should be consulted and who needs to be informed of the results of those steps. Another quick tool that I have in that vein would be a process for certifying enterprise data warehouse or enterprise data warehouse data, and here are some example steps that organizations have taken to do it. Here are the roles associated with the governance initiative and they wanted to identify, again, who's responsible, accountable, supportive, consulted, and informed. So you could take any process that you have, and a lot of those processes are already forms of governance themselves, but this way we can make certain that we associate the roles with the steps that we follow in order to actively engage in these processes. Another version I have is also the idea that I don't. So there were more versions, but I think that gives you an idea of what I'm talking about when it comes to workflow management. What we want to do, and I've spoken about this before in the past, is that I talk about something I call Data Governance Bill of Rights, and what we mean by Bill of Rights is getting the right person involved at the right time for the right reason to solve the right problem, and that's really what we're trying to do by getting our workflow management formalized and making certain that we know who we need to engage and when we need to engage them. Another tool that I want to share with you for internal use and internal development, and again, I apologize for going through some of these things quickly, but if you have questions about these, please ask them in the bottom right-hand corner or submit questions afterwards, and I'll be glad to get to those. But the last tool that I want to share is a communications matrix tool, and then I talked about how important communications is to the whole process of putting a governance program in place. We need to orient people to the fact that we have data governance, and we need to know the fact that there is a program who to reach out to if they've got issues around the data. We need to onboard people, get them to truly understand what governance is all about, what role we play, and then there's ongoing communications. So there are typically three different ways that organizations look at communications around data governance, as orientation communications, onboarding communications, and onboarding communications. Here's an example of that tool, which is down the left-hand side, and again, it's just a two-dimensional matrix, and something that you can develop yourself is that these are the different things that this organization wanted to communicate. They wanted to communicate the charter and principles, the role-based activities, their data documentation, and their metadata platform, the action plan, success metrics, alerts and triggered events, and those are the things down the left-hand side that these organizations wanted to communicate. At the top are the different parts of the organization, the different roles that they've defined as part of their operating model, and some of those can be grouped together, some of those can't be grouped together, but we know that when we communicate with our senior management, that we communicate with them differently at the executive or at the strategic level than we do with people at the operational level. We have less time, perhaps they have less time to give to us, and obviously their bandwidth is shorter, but they're covering more of a breadth of items in the organization, so we need to communicate with them a little bit differently, or maybe a lot differently than the way that we communicate with people throughout the organization. So I've talked about the Make sure it's worth a thousand words tool. I've talked about the operating model diagram tool as well. I've talked about the CUN data matrix. I've talked about the workflow management. I've talked about communication tools. All of these are different tools that can be developed internally. They can help you to formalize rules. They can help you to fly as accountability, formalize processes, formalize communications and awareness, and oftentimes when you create tools like this, they become the face of your governance program. People look to the common data matrix to understand if I'm making a change to a certain type of data, how are you and the organization going to be impacted? How are they going to be impacted? How do we need to pull into meetings? I've had clients who were working on large initiatives and they had so many fits about starting and restarting and re-restarting initiatives because they thought they could engage the appropriate people in the definition of the requirements for the project, but then they find that it's a great find as people are learning about their project, more and more people get involved, and I actually had a client come to me and say, we need to solve this problem. We need to solve the problem of not knowing who the appropriate people are to engage at the appropriate time when we're starting a major initiative like that. And so the common data matrix became a very valuable tool to them to be able to identify who in the organization was going to be impacted by this new initiative, how they were going to be impacted, at least give them the offer to bring them into the requirements setting. Certainly, at the least, give them the understanding of who does what with the data, of what tools are available internally to help them, what impact they have on the rest of the organization. So these tools that you can develop internally become very valuable to you and what does it cost for you to do it? It really costs the time that you put into it rather than the expense of purchasing one of these or the investment of investing in some of these tools that are out there on the market. And again, I'm not an a-fair to say that these tools are not necessary, these tools that you purchase. In fact, I would say that they will do a lot of great things for your organization. All I'm really trying to share is be very specific as to what you want out of those tools before you venture into the ocean and begin to navigate the evolution of data governance tools. So we'll talk for a couple of minutes here about tools that you already own in your organization and how they may be considered data governance tools. So a lot of organizations, they already have tools that are focused on data definition, data production, and data usage. So data definition tools, you may have data modeling tools, you may have a business glossary or a data dictionary tool, you may have a metadata repository tool. Wherever it is that you are currently storing information about your definition of the data, it's great to be able to share that information, to vet that through other parts of the organization. Oftentimes, the definitions that you provide in the data modeling tool don't make it any further than the data modeling tool. We need to be able to pull the data out of that tool and make it available to people in our organization so that they can see how data is being defined, the fact that we might have multiple flavors of the same number. For example, I'm doing work with a health insurance company and to ask the question, how many claims did they process? Well, that seems a very simple question to ask, but there's different types of claims they have. Again, depending on who you ask, we'll dictate the answer that you get from that person and their understanding of the data. Maybe we need to educate management that the right question to ask isn't how many claims did we process, or how many students do we enroll, or how many faculty do we have at a campus. Those things are very general questions that maybe we need to be more specific about. What type of faculty are we talking about? We're talking about full-time, part-time, sabbatical faculty. We're talking about assistant faculty. Again, we need to very much focus on the data definition and sharing that information with people in the organization. Oftentimes, by sharing the definition, what we find is that we've got things that I joke about as being cheeseburger definitions. The definition of a cheeseburger is a burger with cheese. The definition of a student address is the address of the student. It's very generic that way, and a lot of people say that those circular definitions are not appropriate. We can't really use the words associated with what we are trying to define in the definition itself. Oftentimes, we do not have data modeling tools. We do not have business glossaries. They may be old. They may be not kept up to date. They may be very cumbersome and difficult for people to get access to. But take a look at what tools you already own around data definition and recognize that maybe instead of buying a glorified business glossary tool, we could use the tools that we already have internally and use that to serve the purpose of helping to govern data definition. Data production tools. If you use ETL tools, extraction transformation load tools, or data entry forms, and we put limitations and constraints on how people add data in and how the data is produced, that's, again, a tool that we have in our artillery that we can use to help to govern data production in the organization. Data usage tools. A lot of organizations have report writers or analytical tools, and those are used sometimes to govern the use of data in reports or to help us to understand what reports are already available, and do we need to create another version of the same report to try to answer the same question. Well, we have data usage tools in our environment that we can take advantage of that have some of that metadata inherent in the tools to let people know what reports are available, how they can get access to those reports, when they're produced, what data they use, what the purpose of the report is. So we need to make certain that all three of these, that we take advantage of the data definition tools we have, the production tools and the usage tools are already in our environment. Additional tools, the data administration tools, data quality tools, data process tools. We have a metadata repository tool or a change management tool. Those would help us to administer data in our organization. Under data quality tools, the profiling tools and the issue logs under process tools or workflow management tools may not already have these in our organization. If those are some of the requirements that we want to fill by purchasing data governance tools, then we ought to be looking first and foremost at what tools do we already have in our environment, what tools can we develop ourselves that will help us, so that we can build the proper requirements and we justify the need of the purchase of an external tool or a software package to help us in our organization. So the last thing I want to talk about is really justifying the purchase of the tools. So it's one thing to say, well, we've got some of these tools that do some of these things, but we don't have tools that will do everything that we need. We really need to define what it is, what is the everything that we need in our organization when we are purchasing data governance tools. So a couple of quick points on that. Some of the questions that you might want to ask would be how do the tools that we are looking to purchase differ from tools that we already own? Where are we just going to add efficiency and effectiveness to us in our organization through the use of the tool? I mentioned earlier the whole idea, the total cost of ownership of the tool, not only the licensing itself, but the maintenance of the tool, the human resources required to learn that tool and to educate people about the organization on the tool. The level of training that's required to make this tool readily available to people in the organization. You certainly need to answer that question before we can justify that the purchase is worthwhile in our organization. What's the value and benefit we get from the tool? How will the tool help us to do things we don't presently do? And finally, how does the tool impact these things associated with data governance? And I'll talk about setting goals and having objectives and defining scope and defining best practices and roles and responsibilities, all of those things. When we justify the purchase of a tool, what we want to do is we want to take a look at how will the tool that we purchase help us or how will it impact the goal scope objectives and all the other things that we have listed here associated with our governance initiative. So basically to summarize what I've talked about, I talked a little bit about what's happening in the marketplace. I talked about developing tool requirements and I went to an external resource to see what might some of those requirements be. We looked real quickly at what some of the tools are that are available on the market. We looked again real briefly at what tools we can deliver internally, leveraging tools we already own and justifying the purchase of software in our organization. So that's what I'd like to do is turn it back over to Shannon. Shannon, you're there. Can you help me to get some of these questions answered from these kind folks? Sure, absolutely. And the first question is actually kind of in reference to your research paper that we published. Do you have a template or a tool that can help establish a gap analysis that you refer to in the research paper? I don't know if it's in the paper itself. The paper is very old. I'm not exactly sure what it was said, but again, we talked about navigating the landscape. It was the name of the white paper and please request that of dataversity. A lot of time was put into that. It was based on a questionnaire that was out there. But I don't know of any template, say, that you can use to determine what the gap is presently between what you're doing, what you need to be doing, and how those tools are going to be able to fill it. I would suggest go out to places like Garner. Go out to places like InformationAsset.com and ask those folks what their experience is as to how do we help to articulate what the gap is between what we're doing now and what we presently want to do. I hope that answers the question. If not, please reach out to me and I'll see if I can get you a better answer. Also, the templates that you mentioned in the paper are the ones you've also mentioned today, these spreadsheets and so on and so forth that everybody will be getting a copy to from this webinar. Next question, Bob, how do you view SAP's information with George? Well, to be honest with you, I have a difficult time answering questions that I don't have a whole lot of information about, but I will tell you this. I will tell you that the organizations that have used that product as part of the suite of products in implementing their tools have found varying levels of success. They are not sure exactly how they define data steward, but in the past, I've defined a data steward as being anybody in the organization that defines, produces, or uses data as part of their job, and that's different than a lot of other folks in the industry talk about when they talk about data stewards. They talk about assigning people to be stewards or having only a handful of stewards. If you go to your senior management and you ask them, do we need to hold everybody who uses data accountable for how they use data? I think they're very quickly going to tell you, yes, we need to hold everybody who uses data, and that could be everybody in the organization. Therefore, if we're going to take that to heart, we need to go out and we need to communicate to everybody in the organization that what they do has an impact on the rest of the organization, that they need to protect the data the way the data needs to be protected by the rules. Again, I don't know how they define stewardship, but if their product allows you to state basically that everybody in the organization is a data steward and we need to recognize that as such, then I would say that that could be a very valuable tool for you or for your organization. Can you give some examples of data usage tools? Data usage tools, certainly. Cognos, business objects, when business objects used to be around. Any data reporting tools would be considered to be a data usage tool. Any analytical tool that you're feeding data into to do analysis, those would all be examples of data usage tools. And the definition tools would be the modeling tools and the collection tools. Data production tools would be your ETL, but data usage, it's pretty easy. It's anything that you use to access the data to help you to make decisions. So those would be some great examples of usage tools. And also, what the next question is MDM, Master Data Management, use of the acronym can get confusing. Any ideas how to keep these straight? Yeah, it can get confusing. In fact, I was meeting with the project manager for the book that I spoke about earlier, and I used MDM in something, and he said, well, I'm assuming that you mean metadata management by that. I said, no, in that context, MDM. So it's a perfect example of how those acronyms can be confusing. But certainly, organizations that don't know what MDM is or don't know what Master Data Management is, first of all, they need to, rather than using the acronym and assume that everybody understands what it means, use the term so people can see what the terms mean. But then that may not answer questions for people. They may want to come to you and say, well, what do you mean by master data? How is master data different from other types of data in the organization? And so you should anticipate that you'll get those types of questions, especially when you use acronyms. They're going to want to know what the acronyms mean, but that may not be the total answer. They may need a further description of what those terms that you use, that you provide an acronym for, or what they mean to the organization. And what do you think is the main benefit or advantage for a DGG tool? Is it really necessary for implementing a DGG program? My first answer to that would be no. They're not absolutely necessary. Will they help you? Will they enable you to do things that you might not be able to do otherwise? For certain, that is the case. They will be able to help you. Are they absolutely necessary? No, I would suggest maybe you would want to start with some of the tools that you can develop internally. Maybe take a look at some of the tools that I shared with you or some of the other people have shared through diversity or through other channels and see what makes sense to your organization. But there's a lot of tools and templates around data quality and around data governance and around master data management that you can use without purchasing a tool. So I would say no, it's not absolutely necessary that you purchase a tool in order to implement a governance program. I would say that it is pretty necessary that you at least record those pieces of information that I shared with you and those tools you can develop internally. So tools are necessary. Purchase tools, maybe not so much. That's some great questions. Okay, I'm going to turn one more here and keep the questions coming. One of the great things about this series is we'll write out the answers to the questions and we'll get that out in the follow-up email. So the last question is, what will the data governance tool look like in 10 years? Wow. That's a great question. I'm glad you asked that question. I think they'll look better than they look now because tools are always improving. I believe that those tools will do a lot of the functionality that we talked about but take advantage of some of the existing information that we already have in our organization. It's still going to be necessary to inventory what data you have, what systems you have to take the time manually to provide definitions for the data. If the tools are going to have some of those smarts built into them, I'd say that's the direction the industry is going. If you take a look at the metadata management or the metadata repository industry, certainly that has grown. The GUI front-ends, the graphical front-ends, the ability to be able to integrate with other products, they're all there better now than they were when I first got started in metadata management a couple of years ago, say many years ago. But I see that they're going to become easier to use, they're going to be more graphically user-friendly, that they're going to integrate better. That's the direction that I see tools. So when you attend my real-world data governance webinar in five or ten years about data governance tools, let's come back to this and let's see if my expectations are actually played out in the marketplace. Hello. Thank you again for this another fabulous presentation, always so educational and just great. And thanks to all of the attendees for being so interactive and such great questions. I love it. Again, we will get a copy of the slides and a copy of the recording along with links to the matrices that Bob showed to everyone by end of day Monday. A copy of the answers to the questions that we still have outstanding. So thank you, everyone. I hope you all have a great day. And again, Bob, thanks so much for another great presentation. For all your help, Shannon, like always, and thank you, everybody. Look forward to seeing you next month on the Real-World Data Governance webinar series. Thank you.