 Welcome, my name is Shannon Kemp and I'm the executive editor 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 Siner. Today, Bob will discuss do-it-yourself and purchase data governance tools, just a couple of points to get us started due to the large number of people that attend these sessions. He 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 for that feature. As always, we'll 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 Siner. Bob is the president and principal of KIK Consulting and Educational Services, and the publisher of the data administration newsletter. Bob is the president and principal of KIK Consulting and Educational Services, and the publisher of the data administration newsletter. Bob has been a recipient of the Damer 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. And with that, I will give the floor to Bob to get today's webinar started. Hello and welcome. Hi, Shannon. Hi, everybody. Thank you, everybody. I really appreciate you taking time out of your schedule to attend this webinar. I don't know if you heard while Shannon was talking, my phone started going off. We're having weather alerts here in Pittsburgh, so hopefully we'll make it through this stormy Thursday afternoon and share a little bit of information with you about real-world data governance, about do-it-yourself and purchased data governance tools. This is one of my favorite webinars, and we do one of these types of webinars from time to time, every year, every year or so, and it seems to be a lot of requests for information regarding the types of tools that I'm talking about, the criteria that are used to evaluate tools and things like that. So I'm looking forward to sharing a lot of information with you today, and please, if you have any questions, like Shannon said, please ask them through the Q&A or through the chat. We look forward to hearing from you. Before we get started today, I wanted to share a little bit of information about next month's webinar. So the next month installment of the real-world data governance series. In July, we'll be talking about data steward definition and other data governance roles, and data steward definition is, again, another one of those really popular, very interesting subjects that are associated with data governance. A lot of organizations look at defining their stewards differently, and I certainly have a specific approach that I use, and I'm looking forward to sharing that with you next month. In the real-world data governance webinar. A couple other quick items of note before we get started, as I usually do before the session. I wanted to share information with you about my book, Non-Invasive Data Governance, The Path of Least Resistance and Greatest Success, available through all of your greatest booksellers, and please take a look at that if you're interested in learning more about non-invasive data governance. I can be reached through KIK Consulting at kikconsulting.com, which is the home of non-invasive data governance. Also, a quick note about a data-versity event with DevTech International that's coming up in a couple of weeks. I'll be in sunny, hopefully sunny, San Diego, California. Speaking at the Data Governance and Information Quality Conference, I'll be giving two presentations. One is a tutorial on how to assess an existing data governance program. So if your program's been around for a while and you want to know whether or not it's really doing for you what you want it to do, please come to the conference and attend that tutorial. It should be quite interesting. Also, I will be doing another session on data governance privacy in the Internet of Things. So I hope you can make it out to California, and you can attend my sessions while you're out there as well. And last but not least, as Shannon also mentioned, I'm the publisher of the Data Administration Newsletter. If you're not familiar with it, well, you should be familiar with it. Please go out online to tdan.com. It's a monthly publication that really focuses on all the most important issues of the day around data governance and data administration. So the June issue is out there, and we're working on the July issue. If you're interested in publishing, please let me know. Always looking for great content to share with people. So without further ado, we're going to move into the subject for today, which is do-it-yourself and purchase data governance tools. And most organizations and most people that are practitioners of the data governance field, the data governance discipline know that the different tools that are available in the industry, and either the ones that we're going to create ourselves or the ones that we're going to go out and purchase, are really enablers to having a successful data governance program. And the information that's stored in these tools, which is metadata, it's data about data, it's data about the people associated with the data, it's truly metadata. The metadata really becomes the backbone of successful data governance programs. So a lot of organizations are looking or are challenged with the question of do we build our own tools and kind of do it ourselves, or do we put the investment into purchasing tools that are available on the market? So what I'm going to do is share with you today several criteria and several considerations for whether or not you think you should build or develop some of your own tools or whether we should look at some of the tools that are available out there on the market. And there's more of those that are available seemingly every day, every month, certainly every year. So we'll talk about what are some of the considerations we should, what are the things that we should consider in regards to whether or not we should build our own data governance tools or we should purchase tools. So there's really both ways to look at it. There's value from building them yourselves and there's value from acquiring the tools that are available on the market. So this month we're going to talk about smart choices when it comes to selecting or developing tools. I'm going to share with you as I often do during my webinars several templates and tools that I use that I've used in successful data governance implementations around the country and around the world and as a special treat for you today, I've got a new tool that I've never shared before about data governance frameworks and it's basically a do-it-yourself data governance framework that you can fill in to really put your arms around what's necessary to put a successful data governance program into place. So if you're a newbie to data governance, it's great because I've got a lot of ideas to share with you regarding new tools and new ways to look at things and if you're an experienced practitioner, I hope you'll find that some of the things that I share with you along the way here in this hour will benefit you as well. So the items that we're going to talk about in the webinar today are really how to answer that question of whether we should build our own data governance tools or whether we should go out and buy tools that are available on the market. So we're going to talk about considerations for both of those decisions. We'll talk about criteria for evaluating the tools that are on the market. So if you're deciding that you are going to put out an RFP or you're going to be taking a look at the available tools, I want to share with you several criteria from a data governance perspective and then also from a metadata management perspective that should help you to develop and to deliver a sound RFP to the vendors of the different data governance tools that are on the market today. I'm going to share with you several of those tools and I said during that session, during that piece of the session today, I'm going to share with you that new framework tool that I hope you will find of interest to you. We'll talk about the complementary nature of do-it-yourself and purchase tools, the cost and the benefits of purchasing data governance tools and using some of these do-it-yourself tools. And last but not least, we're also going to address what are some of the main tools that are on the market, who are the vendors that you might want to look at if you are moving forward with a data governance tool in your environment. So as I said, the first thing that I really wanted to talk about today was really what are the things that we should consider when we are faced with that decision of whether or not we should build our own data governance tools or whether we should buy tools available on the market. And so I list out seven different things that I think that we should consider even before we make the decision as to whether we're not going to build or buy a tool for our data governance program. The very first item on the list is one that a lot of organizations just don't seem to spend enough time on or focus enough on. And that is developing the requirements and doing the planning that is necessary for acquiring a tool that we're going to bring into our environment. And typically when we're developing tools and we're developing them ourselves, we can be very specific as to what we are expecting out of those tools. But when we look out on the market, a lot of the tools have very broad capabilities that cover a lot of different areas. We want to make certain that as we're getting started that we define a very solid set of requirements and we plan for what is going to be necessary in order for us to implement these tools, whether we buy or whether we build them ourselves. Oftentimes what I suggest, actually all the time what I suggest is to first take a look at the tools that we have already available within our environment. Now we might already have data modeling tools, we have database tools, we have data movement tools, quality tools and analytical tools. Now there are capabilities that are in these tools that we may not be leveraging already. Now we might want to take a look at first before we even go out and make that decision as to whether or not we're going to build or buy a data governance tool. We also want to look at what's the timing of the decision as to whether or not we're going to build or buy. We certainly don't want to start out the development of our data governance program to make that decision whether or not we're going to build our internal tools or we're going to go out and buy tools. So oftentimes the decision to build versus buy has to come after we've taken the time to put together solid requirements to do the planning that's necessary for moving forward with a tool in our environment. We also need to look at the resources that are required and specifically if we're going to develop our own tool how substantial do we want that tool to be? Are we going to need developers? Are we going to host it somewhere? What are all the things that we need to be concerned about when we're developing tools and compare those to when, if we go out and buy a tool, what are some of the resources that are going to be required in order for us to be successful with that tool? I'll share what some of those resource requirements are for the build versus buy decision in a little bit as we go forward with this webinar here. We also want to talk about something that is very important to a lot of organizations and that's the total cost of ownership of these tools. It's not necessarily just the price of the software. It might be the price of the hardware and the price of the support that we need through different parts of our organization. The resources that are going to be required to populate the tools because as I've stated before you can't purchase a data governance tool and implement it and therefore have a data governance program. The strength of these tools is in the way that you can choose the information that is captured within the tool. So there's a lot of work that goes into collecting that information and validating that information before we can even load it into a tool. So the total cost of ownership is not just the software. It's not just the hardware. It's not just the maintenance but it's all the other resources that are required and the cost of those resources not only to evaluate tools that are on the market but also to acquire the tools to get training on the tools and learn how to use them and then educate other people in our organization. The total cost of ownership goes way beyond just those things that most people think of the cost of acquiring a tool. So when we're looking at building versus buying a data governance tool we also got to look at what level of funding do we have? What type of approval are we going to need to move forward with acquiring these types of tools for our environment? Currently funding is an issue and what's the process going to be to get the approval to move forward with either the development or the purchase of a tool? Certainly the process that you go through to gain approval of a tool to purchase for your environment might be a lengthy procedure and a lot of organizations they have IT governance procedures and portfolio management procedures whereas when a new acquisition is planned for it takes time for those things to be flushed out all the way through to getting the approval of acquiring those tools for the market and then there's the consideration of what's the tool evaluation process going to be like itself. As I mentioned earlier I'm going to share with you some criteria that you might want to consider when you are looking at the tools that are available on the market from a data governance perspective and also from a metadata management perspective. So the first thing I'd like to do is let's take a look at some of the considerations for building a data governance tool for your environment. So the first thing, just like I go back to the considerations for the decision of build versus buy, the first thing we need to know is what do you need the tool to do for you? Are you looking for a business glossary or a data dictionary tool? Are you looking for a workflow management? Are you looking for a lineage and impact analysis tool? Or are you just looking to know who the stewards are in different parts of the organization and the types of data that they not only have access to but have some level of accountability for as they define and produce and use data as part of their job? So the first thing that we ought to do when we're thinking about building a tool is really kind of jot down some notice to what we think we need the tool to do for us. And I suggest to share that information with other people in your environment to see what would they like to see out of a data governance tool, whether it's one that you build or one that you buy, what do you need the tool to do for you? And then when it comes to the tools themselves and developing the tools, do you even have the skills to design and then to develop and then to implement and maintain a new piece of software that you've developed yourself within your organization? Or will some of the tools and templates that I'm going to share with you a little bit later on, are those going to suffice? Will you be able to give people access to those types of tools? So we've got to think about the skills that are necessary to even build a tool. And if we don't have the skills that are necessary to build a tool, then we might want to kind of jump right in to looking at the tools that are available for us on the market and what they can do with what our requirements are. Certainly when it comes to building data governance tools, and there's the common data matrix, which is a typical tool that I share during a lot of my webinars in this series, how much time does it take for you to deliver the tool? If you're going to need to design, develop, implement and maintain that tool, you've got to look at the time that's necessary for you to build the tool. It might be quicker for you to go out and acquire a tool and implement it so the amount of time to deliver is certainly a consideration for when you're thinking about building a data governance tool for your environment. Another thing that we should consider when we're building data governance tools is who's going to use the tool? Are we developing the tool just for a small group of people within the organization? Or is it something a little bit larger than that, which might be your department? Or are you truly trying to create a tool that is going to be an enterprise tool that's going to be able to be used by people not only where you're located but in other locations for your organization, whether it's nationally or internationally, globally. You know, whatever the use of the tool, when you're making that decision of whether you're going to build or buy, think about the scalability of the tool that you build. Will you have the ability to move beyond just a small group of users to a department to the enterprise users of the tools? So that's certainly a handful or almost a handful of considerations for building a data governance tool. Let's talk about some additional considerations for building the data governance tool. And so the first thing is that we need to have ideas as to what we're going to want the tool to do for us. And, you know, we can look at other tools and templates and things that are available on the market. If you stay tuned for the rest of the webinar here, I will share with you several tools that I found to be very successful when used well and used for the right reasons within an organization. And some of the tools may require, you know, it's just a database of information that we're trying to collect, like our business glossary might just be a database of terms and their definitions, or it might be a spreadsheet or it might be an application. Now, again, we want to consider what is going to need to be the breadth of the tool when we're developing it. Do we need a database of spreadsheet? Do we need an application bill? And then once we've developed this tool, you know, who is going to educate people in the organization about the tool? Who's going to educate them to let them know or even just increase their level of awareness that there is a tool available for them that does some of the tasks or at least enables some of the tasks of a successful data governance program? And we've got to consider the training that's going to be necessary. We've got to consider the support that will be necessary if we are building a data governance tool rather than going out on the market and looking at tools that are available to us that way. So that's a bunch of considerations for building a data governance tool. Let's talk about some of those considerations for buying a data governance tool. And if you notice, the very first consideration is the same as that I used for the building of the tool. First of all, we need to know what the tool needs to do for us. So we need to have a sound set of business requirements, technical requirements for our data governance and or our metadata tool in our environment. And once we've created these sets of requirements, and I'm going to share, like I said before, I'm going to share with you some of the criteria that I use when I'm assisting clients to evaluate tools that are on the market. But once we have those requirements defined, we need to match them to the capabilities of the tools that are available on the market. And not only that, not only do we need to define our requirements for right now, but we should be anticipating what our future requirements are going to be. If this tool becomes accepted into the organization, what are the other things that we may ask for that tool to do for us? So there are a lot of organizations that will select tools that are excellent business glossaries and excellent data dictionary tools, but at some point, they also want to load in the legacy data and link the legacy data to their existing and their present-day data and make certain that people can do the impact analysis. Maybe that's a future requirement for you, but it's not something that you need right out of the gate. As you are thinking about buying a data governance tool, you want to not only think about your requirements for the day, but also think about future requirements and anticipate what future requirements might be. Other things that you need to consider are funding to acquire the tool, resources to manage the tool. I talked about a few of those in the first slide about the build versus buy decision. The total cost of ownership of a tool that you buy is certainly going to be more expensive than just the cost of the license and the cost of the renewal of the license and the cost of the hardware and the software that's required to maintain that tool. Some additional considerations for buying a data governance tool is, again, look at the process that you have to go through in your organization and anticipate what questions are going to be asked and what people are going to be looking for as far as return on investment regarding those tools. But as I mentioned earlier, a lot of organizations have this IT governance process where they are very, very careful as to how they are spending their money and what tools are going to be selected and added to their environment. So we should know before we go into the whole process of buying a data governance tool, what is the process that we're going to have to go through in order to get a tool at this size and at this magnitude approved within our organization. Now, we also need to look at what level of support are we going to need from the rest of the organization, from a hardware support, from a database management support, from a technical support and help desk, and things like that. We have to include those in our considerations when we are thinking about buying data governance tools. And then just as I mentioned with tools that you develop yourself, we need to consider what level of education is going to be required, not only for those people that are going to manage the running of that tool and the loading of information to that tool and the making available of information from that tool, but we also then need to consider what the training is going to be necessary for people outside of the specific practitioners that have responsibility for the tool. What's the training look like? How much is that going to cost? Do we need to send people away? Can we train the trainer type environment? And what level of support is going to be required for that tool? So there's lots of considerations for building and buying tools. I also want to spend a little bit of time today talking with you about what are some of the tool evaluation criteria that I have grown accustomed to using over the years, and I want to look at it from two perspectives. One is the data governance criteria perspective, and then the other one is the metadata management perspective. And just to give you a little bit of background, when I got started in the industry, I was a data administration consultant for a large health insurance company, and one of my responsibilities was to bring in a metadata management tool. And so I learned by implementing a mainframe-based repository tool, what were some of the criteria and things that I needed, and had I known about them earlier, I would have used them better in the selection of the tool. But if I can share with you a list of different types of criteria to consider when we're buying tools or we're looking at tools on the market for both data governance and metadata management, hopefully it'll give you a checklist of things to look at when you're in that process, or maybe you're already in that process, and hopefully it will be a benefit to you. So let's start out by talking about data governance requirements and capabilities that we might be looking for from tools that are available on the market. The one that I hear people talking about the most, or most often, is the business glossary capabilities. And there's, excuse me, there's a lot of darn good tools out there for building business glossaries. So you want to know how well the tools and the vendors that you're looking at address the business glossary capabilities, how easy they are to use, how easy they are to train people on, you know, in those types of things. But when it comes to business glossaries and data dictionaries and technical metadata, you want to know what these tools can do for you. How can they be linked together? How can this information be made available in a coherent way to people of your organization so that they have a better understanding of the data in your organization? You want to ask the question about how easy is it for us to customize the tools? We don't like the labels that you use. So for example, you don't like the term steward, and you want to call them custodian, or you don't like the name owner, and you want to call them steward. Now how easy is it for us to be able to customize the tool so that it matches the requirements that we have within our organization? Some additional requirements and capabilities. You might want to take a look at how do they apply data stewards and data owners to data across the organization. You know, as an example, one tool that an organization that I was working with recently was using was only allowed to link one person as a data steward to each specific type of data. And to me, I found that to be almost unusable and the fact that there's a lot of people in the organization that have a relationship to the data, that have some level of stewarding accountability for that data. We want to make sure that we have a many, many relationship there in how we can assign or how we can recognize or identify responsibility and link that to the data within the tool. We want to make sure that we have the ability to be able to be able to customize roles that workflow management is a big part of applying data governance to process. And you want to make sure that you can manage that process and get the appropriate people involved at the appropriate time. So workflow management is an important requirement and capability that we need for these data governance tools to have. Some more data governance requirements and capabilities. Perhaps your organization is very policy based, has data standards, data quality standards and those things that they want to store in a centralized location. Well, you may want to know if the data governance tool has that capability to kind of be that policy and standard repository. If you can also keep information like your business rules and your master data rules in a repository where people can link those to the different types of data that people can understand, specifically the rules associated not only with the use of the data, but rules associated with defining and producing the data as well. Many of these tools on the market also give you the ability to load information about different domains or different subject matters of data. Or even when it comes to reference data, being able to say, okay, for this specific field, these are the appropriate values for that field. Anything that is not in this list of allowable values might be considered to be poor quality data. So we want to make sure that the data governance tools have the ability to be able to track domains and list allowable values as most metadata repository tools have the ability to do that. One of your requirements for your data governance tool might be to be able to collect source to target mappings. And so it might be important for you to pull in information from your ETL tools and your data movement tools. And you might want to ask yourself a question as to how are people going to use this information? For example, if we're using our data governance program really to improve the understanding of data in our data warehouse and people are going to want to know where that data came from, well then certainly we want to not only be able to load the data base, the aspects of the data base from the sourcing system but also from the target system as well, do you need to manually map those or can you pull that information in from your Informatica or your data stages or all those other data movement tools that are available? Are you going to want to use your tool, your data governance tool to do impact analysis? Again, just another capability that you want the vendors to be able to show you that if we make a change to a specific term or if we make a change to a specific field, what all is going to be impacted by that change? Again, that might be a requirement for your purchase of a data governance tool. And last but not least, I've got five more requirements and capabilities for why you're looking at your data governance tools is does the data governance tool give you the ability to provide metrics on how well your data governance program is doing for your organization? Several of the tools I've seen provide pretty cool dashboards of information that not only state how many issues have been uncovered but how many issues have been resolved and the cost-saving from resolving those issues. Now, there's a lot of different data governance metrics that you may want to be able to share with people through your data governance tool. Is that a requirement? Well, if it is, then you want to ask the vendors that are out there, what do they do for you in regards to sharing metrics and their overall level of metrics capability? You know, we want to be able to extend the artifacts and the relationships between the different types of data that are stored in the tool. You know, our data governance tool may need to be a data issue and really emphasize the resolution process. You might want data profiling capabilities. We might want to be able to help other aspects of the organization, including people like in your internal audit areas, your legal areas. So there's a list of, I'd say, I think there were 15 different capabilities or requirements that you might want to consider when you're looking at different tools that are available on the market. But that's only one aspect of the tool because we know that these data governance tools often sit on top of metadata repositories and metadata tools. So I'd like to share with you a couple handfuls, should I say, of metadata requirements and capabilities that you might want to look at when you're evaluating metadata tools for your environment. Because, again, there's a relationship between the data governance and the metadata tools are pretty solid. You need to be able to do a lot of the same things with the metadata regarding data governance as you would need to do with any other metadata in your environment. You want to know about the meta models and how is the metadata represented within the tools and how often the vendors put out software releases and what's required in order to update their releases. You want to make sure that the tools are extensible so you don't just have to use the information that's available to you out of the box. You might have additional entities and things that you want to collect information about, and you might want to relate them to things within the organization. So extensibility would be one of the first questions that I would ask when looking at the metadata tool vendors. Being able to define self-defined loads and loading things into the repository associated with the data governance or metadata tool. You want to know how roles are represented within the tool. You want to know how well you can integrate your metadata tool into the different processes that are going to use those tools in your environment. Some additional metadata requirements you might want to consider asking the vendors or putting into your request for proposals. How do you handle change control? How do you handle versioning of things? When we know that in our organization we may have two things that are called the same thing, but there's actually just different versions of them and they actually have completely different meanings. We need to be able to version things, not only from kind of a test and development and production perspective, but also from a system of record perspective and just something that's used as a departmental application. We want to be able to note that within our tools themselves as well. We want to know how the metadata tools will enable us from communications, from end user requirements. Again, we talked a little bit about training and education and resource requirements. We need to know what's typical for the implementation of these metadata tools within these organizations' environments. So one of the best ways to find out how well your criteria match up with the vendor is to talk to some of their existing customers. Find out what their experience is with the resources that are necessary to install and maintain the product. What type of training and education they use and how it was beneficial to them. So a lot of information is not only available from the vendors themselves and the white papers and their websites, but it makes sense to talk to other people who have used these tools before you go out and invest in the amount of money that it takes to invest in some of these tools. All right, as I said earlier, I want to share with you several tools that you can create yourself. And that's one of the things that I get asked the most for out of these webinars and during my presentations is people want to see copies of these templates. As Shannon mentioned earlier, we are very glad to send out copies of these templates and links to these templates after the webinar is over. I'm curious to hear from you as to whether or not you've used any of these tools and what value they've added to your organization. But kind of before I get started with that, I want to introduce this first tool. So this is the first, for those of you that have been regular attendees of this webinar series, and I hope that's a lot of you, but I'm always happy to have new people on the webinars as well. I share these tools often. The first tool I want to share with you today is something that I call Data Governance Framework. And I just wanted to kind of give you a backed-off view of that so you can see what all is involved, but I also wanted to give you a little bit larger version of that so you can actually read what's in the diagram. And if you take a look at this Data Governance Framework, it's not that dissimilar from some of the other frameworks that you've seen on the market. But as John Zachman would say about the Zachman framework, at some point in time, you're going to want to know how you're handling every single block that is at the intersection of every row and every column. So when I talk about roles and responsibilities, oftentimes I talk about it from the perspectives of the executive roles, strategic, tactical, operational, and support roles. And if you notice, those are the things that I have listed down the left-hand side of this signer noninvasive framework for Data Governance Implementation. So we want to think about things in the way it works in our organization. So a lot of organizations are set up to kind of operate this way. There's not an executive level, a strategic level that might be your counsel, tactical people who are your domain stewards or subject matter experts, operational and support folks. And then I have different components of the Data Governance Program listed across the top. And we want to consider every one of those components for every one of those levels that we just talked about, the executive down to the support levels. So, for example, with the roles, at the executive level, a lot of organizations will have a steering committee. But at the strategic level, they'll have a Data Governance Counsel who has decision-making authority. At the tactical level, we may have these data domain stewards or these owners who might have subject matter level authority. At the operational level, have data stewards or operational data stewards or definers, producers, and users of data that just have daily accountability based on their specific activities. And at the support level, the Data Governance Lead and the work groups and the people that are partnering with your Data Governance Team across your organization, typically they have functional authority around the areas that they are specifically responsible for. So that's just kind of one way of walking through this tool and saying that, okay, for roles, we nearly need roles at each of these levels. We know that we are going to involve these different levels of our organization in the different processes that we define. We know that we're going to need to communicate with each of these levels effectively and we're going to need to be able to provide metrics, what role these different levels play in the metrics that we're defining. And then when it comes to the tools, the tools of the organization, what types of tools can we expect from each of these different levels and how might we get them involved in the development of these tools? So I know this is pretty kind of small on the screen in front of you, just to blow it up a little bit further, just to kind of give you an idea as to what I'm talking about. Now we have the components across the top and we have them well defined up in that upper blue block in the upper left-hand corner of the framework. And then we have the different levels that I talked about. So if you're interested in talking to me about data governance implementation, I think that if you start to fill in each of the different blocks that are at the intersection of each of the rows and each of the columns, it might be very beneficial to you to be able to explain to people how we're putting data governance in place and how we are moving forward in our organization with our data governance program. The second tool I want to share with you is the operating model of roles and responsibilities I've shared it before. Again, it kind of aligns with what you saw in the framework that you've got the operational, tactical, strategic, executive and support roles. And I could spend a whole session talking just about this operating model of roles and responsibilities. My suggestion to you is don't try to plug your organization into that model. Try to take the model and overlay it over your organization. Another view of the data governance operating model kind of has a time component thrown in which on the project of defining the program is starting the emphasis is on the executive level but when it comes to the delivery of the program the emphasis is really at the operational level. So again, it has the time component but it really is the same tribal and pyramid diagram that I shared on the slide before. The common data matrix is the place for you just to record who does what with data across the organization. It's a two-dimensional matrix that has the types of data down the left-hand side and the different parts of the organization across the top. And by using this tool we can identify who in the organization defines, produces and uses the different domains of data in different applications that are maintained by our information technology group across the organization. Again, this diagram is relatively small print specifically what I'm talking about. So you've got the council represented on here, you've got the alternate, the steward coordinator, the domain steward, the operational steward and then we've got information about specific data that we're governing and where that data resides in the organization. I used to present the common data matrix very early on in the presentation but I gave and what I found was a lot of people stopped paying attention to me and started to complete the information of the data matrix. At some point in time you're going to want to know who does what with the data across the organization. A governance activity matrix is basically a two-dimensional matrix where we're taking the steps of a procedure or a process down the left-hand side and the roles and responsibilities that have been defined as part of your operating model across the top and we're stating what is the responsibility for each of these different roles during each different step of a specific process. Again, it takes the guesswork out of who does what and when and it really formalizes the activities that are associated with the processes that are being governed within your organization and here's kind of a blown-up version of at least a piece of that where you can see down the left-hand side use my marker here, down the left-hand side you've got the different steps and across the top you have the different roles associated with your program. Now we can be very specific as to who does what during each step of the process that is being governed. Another example of that is this tool which I've shared before. Some organizations identify specific sets of tasks that they want to govern and that they want to apply accountability for in this tool it was simple enough to be able to click on the items and up on your screen would come the list of the steps that are necessary to complete that task. Again, with the different roles associated with your program, if you're familiar with RACI or RASCII and who's responsible, who's accountable, who's consulted with, who's informed during each step of a specific process. I have one more of these to share with you which is an example based on daily issue resolution which again, down the left-hand side demonstrates the steps that are necessary for data issue resolution and across the top we've got the different roles associated with our program. If you'll notice one of the neat things when you go from tool to tool within the different tools that I've shared with you in this webinar, there's color coordination between the different templates. So where you see yourself as a data governance counsel in pink or purple at the top and you see the enterprise data stewards or the owners as being the yellow, if you go back through, see if I can do this here, if you go back through some of the tools you'll notice that we use the same colors to represent these individuals in the different models and different tools that are being used as part of your tool base or your template base when you're implementing governance in your organization. One more tool that I wanted to share with you on the data governance framework that I shared with you, communications was a big aspect, was certainly one of the components and most people that I've talked to recognize that communications and awareness are extremely important subjects when it comes to implementing your data governance program. Organizations struggle a little bit with the definition of their data governance communication plan if we identify the items that we want to communicate down the left and we identify the groups that we need to communicate with across the top, we can be very specific as to how we communicate a specific thing to that specific group. We know that we can't communicate with the executive team the same way that we communicate with the everyday operational stewards in our organization. So to truly put a communication plan in place really requires that we know that we have onboarding level communications and ongoing communications. If we identify the core types of things that we need to communicate and we identify the audiences to which we need to communicate them with then the information that goes into each of these blocks could be the how's, the when's, the why's, the where's that those communications take place. So we know that we need a communication plan this is a template to help you to set up your communication plan and a little bit bigger picture of a section of that where again you can see down the left-hand side we've got orientation communication we've got onboarding communication ongoing communication and we've got a lot of information that we need to share with people as part of our data governance program this will help us to identify the things that are necessary in order to act on that communication plan for our organization. So the truth is with two organizations you're going to find a combination of tools that you can create yourself and I just shared with you several that would not only help you to formalize accountability and to inventory the data in your organization and put together a communication plan and clearly define your roles and responsibilities so certainly you can have tools like that in your environment but I'm sure that in most environments data modeling tools maybe even some metadata tools data visualization tools and reporting tools the fact is that it is an inevitable reality that you're going to have both of these tools so you've got to look at ways that we can use these tools together how they're complementary to each other how we can match whether or not we're going to use our do-it-yourself tools or the tools that we have acquired or that we already own with the requirements that we have for data governance we have to consider the portability of the metadata back and forth between tools which is always an issue because vendors typically have certain ways that they like to see metadata as it's being entered into the tool and in your do-it-yourself tools I'm not sure how the metadata is going to be maintained where it's going to be maintained whether it's in a database or a spreadsheet you can match your tools with your requirements and that you have the ability to be portable with your metadata from one tool to the other a little bit more on the complementary nature of purchase tools and do-it-yourself tools is how are people going to access this information are they going to access it through the purchase tools are they going to access it through front-ends that you apply we need to consider that when we're looking at how these tools are going to complement each other the information and the training one of the suggestions that I have for you is to limit the number of tools or maybe have some tools working behind the scenes and only express that you have certain tools to people within your organization because you could really bog them down with where do they go to get specific information ideally you're going to create a warehouse for your metadata a centralized place where people can go and get access to the information and then the other last thing regarding the complementary nature of the tools is it would be really great if we could take the metadata that we've collected within our do-it-yourself tools and make that information available through the purchase tools so a lot of those tools have hooks into being able to use metadata from the outside and certainly we want to look at that because again if we want to give people kind of a centralized location to go through for the information of the metadata into that tool or at least access that metadata through the tool so one of the last things to talk about is weighing the costs and the benefits of purchasing versus building your data governance tools you know certainly there are costs associated with developing your requirements there's costs associated with gaining the approval of the tool there's the tool cost itself and then there's the licensing and the renewal fees associated with tool cost there's resource maintenance, hardware education and training costs associated with any tool that you use within your environment so you want to weigh the costs associated with the tool in a way then with the benefits associated with the tool and what are some of the benefits that we can gain from implementing not only internal tools that we've developed ourselves but tools from the outside understanding of the data in the organization through the glossary through the dictionary through the business metadata that we're collecting we can certainly improve the quality of the tool quality of the data should I say by defining standards and putting those standards into the tool and getting people the ability to access those standards and know what is quality data versus what is poor quality data you know there's the protection benefits of defining handling rules associated with your data and getting that information out to the people that are using the data in the organization so it's again a way of it's a benefit of your do-it-yourself or your purchase tool is to take those rules associated with handling data off the shelf and get those into the hands of the end users there's data management benefits there's workflow audit legal benefits there's a lot of different benefits associated with implementing tools ideally as I stated earlier in the webinar today you want to know what your requirements are going in before you go and develop a tool or you purchase a tool for your environment so last but not least because I get a lot of requests from this for this information from people who want to know my experience with tools and what tools they should be looking at there's a whole bunch of different types of tools that are out there on the market and that diagram on the right side of the page is how a lot of organizations that I work with look at their metadata they look at it kind of from a semantic layer a vocabulary layer to a dictionary layer to a technical metadata layer so there's a lot of tools in the market that are used to collect that information to have that type of structure there's data governance and stewardship tools metadata, glossary, dictionary workflow management tools that are most likely already in your environment that might help you to collect this information or where you might already have some of this information collected and that would be your data modeling tool your ETL or movement tool reporting big data security change management tools you've got a lot of tools in your environment we need to understand how we can match our existing tool set with the requirements that we've defined as we are going about putting together to enable our program and so that diagram on the previous page kind of flushed out a little bit further is what a lot of organizations are looking for when it comes to implementing their data governance tools and their metadata tools they want to have business terminology that's linked at the semantic layer that's linked to standard names and business metadata which is linked to the technical metadata so if that's one of the things that you're looking to do take a look at the tools that are available and see which ones will help you to be able to enable your governance program to successfully govern data that way and this page it may be important to some of you may not be important to some of you but I wanted to share with you a list of the vendors that I seem to come in contact with the most and the names of their products I don't push any specific individual product what I suggest is take a look at the products that are on the market and see which ones will best satisfy the requirements that you have for governing and managing metadata in your environment I'd be glad to talk to you about my experience in looking at tools so that's something that you'd like to talk about please reach out and we can talk about that as well there's a lot of information that's out there about the tools on the market there's a lot of analyst reports from the Gardner Group to the Forrester Group Aberdeen, Mackenzie Bain and even searchdatamanagement.com there's a lot of evaluations of tools on the market that you can look to see what do other people think of these tools and how do they stack up to what you can already produce yourself within your organization so with that being said I'd like to turn it over to Shannon for questions and answers real quickly these are the things that we addressed are on the screen for you right now next month we'll be talking about data sewer definition and other data governance rules Shannon do we have any questions today? There's lots of comments that have been coming in but no questions yet for any questions that you have for Bob's minimum the bottom right hand corner in the Q&A of course the most common question that we always receive are people asking if they will receive a copy of the slides in the presentation so for this webinar I will be sending out a follow-up email to all registrants by end of day Monday with links to the slides the recording and all the matrices in today's webinar do you have access to that? Other than that people are being pretty quiet today Bob Oh here we go It's a stormy Thursday at least it is here What considerations do companies normally give toward internet or internal audits? Well a lot of us now use as an example an organization I worked with recently that is focusing on protecting their data as really being one of the key results that they are looking for out of their data governance program and in order to do that they define handling rules for different types of data that must be protected PII, personal information health information, intellectual property in the long run in order for these programs to pass the mustard of the organizations that are under regulatory control you have to have audits assistance so whatever you are going to report to people as being governed and your data being governed it has to be auditable so I'm finding more and more either organizations are looking at auditors as not being their friends or as being their friends more and more organizations are involving audit in the data governance function to make certain that the data is protected substantially for that organization Love it and there is quite a bit of chatter going on about total cost of ownership thanks for bringing that up and do you have what's your perspective on what you are seeing in the usage of cloud versus on premise by tools? That's a great question you know what with one company I worked with recently they were very adamant about the fact that they wanted to store all their metadata locally because they realized that if the metadata was in the cloud at risk so there are some organizations that are very adamant about storing not only their data but storing their metadata where they can have complete protection but that being said I've had several conversations with vendors even this week which are moving to more of a cloud based environment so I'm seeing it being available more and more but I still see that there are some organizations that it may be just a little bit uncomfortable doing this type of information and porting it up to the cloud Do you know any good SharePoint templates for data governance? What I would do is I would go to a data university conference and I would talk to people about how they are using SharePoint to support them I don't know of any sets of templates although I'm sure you can take some of the tools that I provided today some of the do-it-yourself tools and create templates in SharePoint and directly point you to my suggestion is talk to people who are using SharePoint as their tools to get started and learn from them Love it Is there a percentage of time that a company should expect to spend on data governance and master data management? If you follow the non-invasive approach I always say that data governance should really potentially only cost you the time that you put into it by governing data informally and efficiently and effectively and by formalizing it we don't necessarily have to go out and spend a lot of money but then again, time is money as well so I would suggest when organizations are getting started not to throw a whole lot of money at their data governance efforts when it comes to master data management it's a little bit different because oftentimes the master data management I'm not talking about the governance to master data but the master data environment itself it's typically a pretty large expenditure for some of the tools of the trade for master data management but again not for necessarily the data governance or the governing of the data associated with the master data management effort Sure and I think we have time for at least one more question here and just let everybody know keep your questions coming in if we don't have time to get to all of them today I'll give you some answers to those questions and I will likewise get those out in the follow-up email so the next question coming in is there a metadata model standard we should consider to allow the metadata in different tools to be integrated more easily I don't know if there's a meta model standard but the meta models which for those of you who don't know what a meta model is it's actually a data model so it's how the data is represented in the tools if you're not able to get the metadata out of the tools directly you may be looking at some point in trying to get to that metadata indirectly I'm sorry you might be looking at getting to that metadata directly from the database that that metadata is stored rather than through the tool so there are data model books as somebody just mentioned there's a book by David Marco on universal metadata models but the fact is that most organizations are vendors of products create their own meta models that stand behind their product and the best way that the data is represented within their tools so the meta data models that Dave provides are good but you might want to take a look at those first before you compare them to the actuals that are provided by the metadata and data governance tool vendors well I'm afraid that is all the time that we have for today there are a couple more great questions coming in and again I'll get those to Bob so feel free to keep typing some more up if you have them and I will, as a reminder I will get a follow up email by end of day Monday with links to the slides the answers to questions we didn't have time to get to today the links to the recording and links to the matrices all the great matrices that are presented in in Bob's webinars so Bob thank you again for having for another great presentation and thanks to our attendees as always for being so experienced and so engaged in everything that we do we really appreciate it and we will see you next month hopefully we talk about data stewards thank you very much Shannon like always thank you have a great day everyone thank you everybody