 To 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, TDAM.com. Bob has been a recipient of the Dama 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 introduce the webinar and today's panelists. Welcome. Thank you very much, Shannon. It's always a pleasure working with you. Thank you very much for taking time out of your schedules to attend this session. This session is kind of a change-up for us. A little bit different than a lot of the webinar sessions that we've done in the past. In the past, it's been primarily or actually solely me speaking during the webinar session. But this time, as Shannon had mentioned, I have an esteemed setup panelists, people that I have close relationships with as far as their involvement in the data governance industry. It's kind of a vast kind of a different type of group. But I think that they will be able to provide you with a lot of information and actually compare the way that they've developed their solutions for data governance. And so in order to get started with what I'd like to do is just talk real briefly here about the upcoming webinars in June on the 19th, which is actually a special Wednesday date for this event. And briefly, as you know, it's the third Thursday of the month at 2 o'clock. Well, we're going to do the third Wednesday of that month because that will coincide with the Data Governance and Information Quality Conference that had a Data Diversity event and a DevTech International event that will be taking place in San Diego. So what we're going to do, I'll be speaking on that Thursday. So that Wednesday, what we're going to do is we're going to pull some of the thought leaders from the event into OpenR. And again, that will be a little bit different as well. But it's good to get a wide perspective from different individuals. The one in general will be Governance for Master Data. And to get more information about any and all of these things, you can go to DataDiversity.net and look for a conference or look for the winners and everything that is out there for you. As quickly as I usually do in the introductions to the winners, I kind of go through the abstracts that I used to hopefully attract your attention to this event. And so we know that governance programs, there's really no two that are exactly like everyone has nuances in the things that I talk about in the abstract. But it's extremely beneficial to hear from people who are doing it and let them share their experiences with you. So that's going to be the focus of this month's webinar. In this webinar, I selected, as I mentioned, three participants that I think will provide some great insight in the questions that I've put together before them. And the idea here is hopefully that you'll have questions for them or you'll have questions for me to give to them or they'll have questions for each other. And I'd like to make this kind of a lovely discussion in the next hour. So what we're going to do is introduce the panelists. Then we're going to talk about topic one, which if you'll notice, the three topics that I selected are very closely related to the real-world data governance webinars. The one that I just gave was on data storage, the one before that was on metadata and data governance. And the one that will be in July will be about master data. So I wanted to kind of touch on some of these subjects early on. And then we're going to summarize the stuff that we've talked about and proceed with the Q&A. So without further ado, what I'd like to do is introduce to you the panelists. I want to read everything that's on their slide, but I will give you the opportunity to look through that so you understand who they are. I also want to relate my relationship with them. Dan and I work together at PNC Bank here in Pittsburgh, which is my hometown. And Dan has been a practitioner of data governance for years. He actually spoke at the Enterprise Data World conference last week or two weeks ago. And Dan is doing really well in the data governance world. I think that he'll provide some great insight to you. The second one is Pablo Revolti. Pablo and I have been friends for many, many years. Pablo works for the Church of Jesus Christ with Latter-day Saints. Pablo was just the winner of the 2013 Data Governance Best Practice Award, of which I was participating in the judging of that. So when I go way back, he's got a lot of history in data governance and information governance as well. And the panelists, you all know her. You all love her. My friend for a long time is Gwen Thomas of the Data Governance Institute. But Gwen actually has a change that she's made in her career. I'm not sure if you're aware of that yet. And she told me what the title was that she was going to be holding at her new organization. But Gwen, could you give the title and the name of the organization real quickly just to bring people up to date as to where you are? Certainly. I've gone in-house and I'm working with the Interfinational Finance Corporation, IFC, part of the World Bank Group. I'm a senior operations officer working the Information Quality and Governance Group. So I'm really excited about that. I've had a friendship for many years. We used to work for the same consulting company together. We started talking about data governance together many years before it even became a regular known topic. I've selected Gwen because she's a practitioner now. But she has a lot of insight into what different organizations have done. And I think she'll bring a different perspective from Pablo and from Dan. So with that, what I'd like to do is proceed. So I'm a little bit orderly here in the way that I've put things together. I'm going to throw the question out there. And then I'm going to go in the order that's displayed on the slide. So with the first question, we're going to get to Dan first. Dan, please spend five minutes or so answering it. And then we're going to go to Gwen and then to Pablo, and then we'll bring it round to discussion and then move on to the next question. So Dan and I know from working with you that there's always an adventure within your organization. And a lot of organizations have different approaches in how they either identify or assign or recognize people as data stewards. So with PNFank, a large financial organization, can you share with us how you went about doing that? Sure. Yeah, you're absolutely right. It's been a great adventure over the last five years since we started our work with you. And that has to do with what probably everybody on the call is experiencing is that this is still a relatively new space, this concept of data governance, data stewardship, et cetera. So when you're reaching out to people in your organization whose calendars are already full and blessing them with a new additional title and asking them to come to meetings and interact with a glossary tool or whatever, you get a lot of frightened looks, scared looks, why me kind of things. So the important thing that I've found over the years in getting those right, the subject matter experts engaged perfectly is you have to have a solid foundation in your data governance program. And specifically, a central piece of our governance program is in this glossary. And so to have a good taxonomy for the glossary that's off with what is the scope of your program? Are you just applying this to one of the portfolios that you manage in your company? Is it enterprise or are you trying to cover all the portfolios and identify what the data domains are that you want to govern? Are you going to govern customer data? Are you going to govern product data? Are you going to govern risk data? Whatever you have, we have that established taxonomy and buy-in from the executives that that's the content, at least with a high priority that needs to be governed this year or in the next three years, once your data domain is established, that gives you the beginnings of the ability to then reach out to the subject matter experts in those fields. And you want to go to them with very tactical requests. You don't want to walk in with some high-level sort of, you know, discussion that you're going to steward data, you're going to be responsible for. You don't want to give them real nuts and bolts. If you get back to your desk, here's what is being asked of you. We're asking you to go to the business glossary application or go to these, you know, data sets and help us identify what the high priority terms are to be defined or whatever. So, again, in short, it starts with a good, well-defined taxonomy, a very clear purpose for your data governance program, exactly what you're going to be asking them for. In the way of time and interaction, again, with your governance tools and your processes and things like that. And with those things well-defined, then anybody you talk to in the organization in those spaces will know that the people will offer them up. I'll just start off with saying, again, that's part of the challenge is identifying the right people. And I know, Bob, with your anonymous data governance approach, a lot of that has to do with working with those people to get what you do out of them without really impacting them or taking them out of their day job. Appreciate your saying that. And that's exactly right. I mean, when we talked about who a data steward was and what data stewards do in the last webinar, and it was a pretty hot topic. You know, the idea is doing kind of exactly what you're doing is you're identifying the people who already know the data or you're identifying the people who know the people who know the data and you're having a good answer to the questions that they're going to have about, well, what does this mean to my job? So that's an extremely important part. And thus, I think it was a good question to ask. So thank you again. Anything else that you wanted to share on that or should I move on to Gwen? With Bob. All right. So the same thing. And I know you've worked in a lot of different organizations. So you can probably share at least several. I know we've only got a minute and a lot of time here, but I'll share with us some examples of how the organizations that you've worked with and the organization that you're working with now identify who your stewards are and what work you do. So the model that Dan described is very familiar to me. And it sounds like you're being very successful with it, Dan. What I've observed, however, are that there are four very distinct models for data governance. One is the idea for data stewardship in association with data governance. The first model is where the data stewards are those who touch the data. They have responsibilities for data activities. And so these people who may be individual contributors in an organization or specialist in part of the data flow, with their names stewards, their responsibilities are particularly to ensure that certain standards and rules and controls are actually applied into the work. And so they may be responsible only for their span of work or for a group around them. So this model of lower-level stewardship, sometimes with a lower K-S, I've seen that in organizations that are information factories where these people, the jobs may be business analysts or information analysts. Now, at the other end of the extreme, I've seen quite a few organizations where their stewards are very, very senior people in the organization. And their responsibility is to do, issue, escalation, resolution, set direction, argue through the management aspects of a new governance rule. Whose budget will it go through? Resources will be used. What project are we going to piggyback over? So these are extremely senior people. Now, I actually got called in one place where they had assembled this sort of a group, and then they had handed out dictionary terms from a dictionary to them and said, go off and create some definitions for this. Obviously, the people in those roles thought that that was not a good use of their time, and the program was troubled from the start because of that. Another model for lower-level stewardship, and that's the one that is in place here at IFC. Arts are intermediaries. They are evangelists. They are embedded within the organization. And the goal is to utilize and communicate out to the organization, new standards or issues or concerns from a decentralized governance group and also to be eyes and ears on the ground of a governance group to collect issues and bring them back, as well as trying to spread the world about good governance and stewardship practices, the C-1 Help 1 model. And the full model that I've seen, and this is, I've seen it many times. At first it surprised me, and then I finally got it. It is, especially in large complex organizations, is to not even use stewardship term. And when I saw it, I asked, what do you mean you're not having stewardship? They said, no, no, you got me wrong. We have stewardship responsibilities, but we're not naming anyone a day to do it. And I said, why? I said, well, because we are so dispersed that we don't have time for the arguing over status, whether it be a high level role or a low level role. We don't have room for it. We're more concerned about the accountabilities, so we just assign data accountabilities. The next case I heard this rationale that we don't name data stewards, it was because they had some history and the term had been reasoned for them. The next time I heard the rationale that we don't have data stewards, it was because of confusion. So many people came from organizations previously that used stewards in different roles. Some were top level stewards. Some were lower level stewards that they thought it would just add too much confusion. And then at an extremely large, complex tip of the pyramid organization I was at, they tried to use the term because their governance was not down in the trenches touching the data, but it was serving more as a management alignment tool. And they tried to leave it to each line of business, each different group, to determine the terminology that made sense for them in their data management trench. So some of them may have used the term steward and some not, but as they were using this distributed model of governance, they limited the confusion that might take place if one group on the West Coast had data stewards that were highly knowledgeable and influential deciders whereas another group in the West may have data entry folks being designated data stewards. So my experience here is that as soon as you start having a discussion with someone about their stewardship program or what they envisioned for you, you should probably level set on which vision of stewardship is being discussed. How confusing, Bob? Let me jump in. Okay, I'm Pablo. Thank you, Pablo. Yes, no problem. So in our organization, we probably follow what you represented when as the third model. Our data stewards are mostly, almost all of them in the business units. The church is a very large complex organization. We have lots of very independent departments. So in our organization, there's something a little different that I haven't seen very often. I have seen it in some other large government organizations or organizations that have this type of silo environment. The main function of the data stewards in practice has been to control and authorize who has access to the data under their stewardship. We have a little process that we follow to identify the data stewards. So for example, as soon as we identify a new domain of data that is not assigned to a particular data steward, we talk with several of the stakeholders in that department around the people that normally use the information and try to identify who would be the data steward. Who is the person that knows most about the data that is always interested in the data and so on. And then we interview several candidates. Okay, sometimes most of the time, most people point directly to someone and they go from there. And then we talk with those candidates. We see who would be best in their personality position. We like someone that has some managerial or a director level position and then propose that assignment to the managing director of the department. Then we give them training on the different aspects of data stewardship, the areas of sharing data, data quality, definition of data terms, and information security. And then they go on and start performing their work. Okay, that's what they do, what we do in our organization. I'm sorry guys, I had my phone on mute actually when Glenn came to an end and what I was going to say was he really supported the things that I said in the webinar last month. It really depends on the organization. There's not just a single way to be able to identify who the stewards are or even what the stewards do within the organization. So when I was concerned when I added you to the panel, not in a bad way but in a good way, the fact that I know that you bring a wealth of information about this can ensure examples of what several organizations are doing. So to be able to provide four models was really a great answer. We just got to be careful because we're going to run out of time here. I know we're going to have the hours going to be filled up before you know it. But again, I just want to tell people if you've got questions for Dan, Gwen, and Pablo about stewards, if you can just send them in the Q&A section down at the bottom right of the screen. We're going to hopefully save some time at the end of the session so we're going to go through those questions. So again, I hope that that was helpful to all of you out there in listener land or in participant land as far as just hearing from different organizations different options that you can have. And the idea is to pick the one that fits best into your organization. And I would think that the panelists would probably agree with that. Now, I know that a couple of different people mentioned the idea of metadata management. And I know Dan, it's something that's really new to Dan. Dan's been answering this question third, however. But the idea, and I get questions all the time about the business glossary, about the data dictionary, about the metadata management. So we're going to start, Gwen, with you if you could also, again, from your wealth of experience talk about how you handle metadata that's associated with the metadata that's associated with the governance program. And how metadata is that that is associated with the governance program? I'm going to be a more brief this time. You know, there's a core set. We all need to know who are stewards and sometimes referred to as business metadata. I don't know what activities are worth undertaking. Interestingly, while this is considered business metadata, I consider it the master data of a governance program who has people and places and things and locations that we use to run our operations. The other thing we've been there is technical metadata and data about the data definitions and such. And there's logistic data. So it is, you have a broad solutions for what you can manage. And frankly, I have seen every one of those options put in play. I've seen them implemented in metadata repositories. I've seen them most frequently managed through web portals or cell spreadsheets. And I have not had the privilege of working with an organization that uses one of the new governance tools yet, but I'm excited to hear from anyone who has because it's time that we cobbler's children get some proper shoes, I would say. I agree with you, and I'm kind of in the same boat as you are, Gwen, that I have, there's several companies that have been looking at some of the newer tools on the market and there's, you know, certainly from a repository perspective, a lot of organizations or at least some organizations have pretty solid metadata programs. And I disagree with me if I'm wrong, but in organizations, the type of metadata that you talked about, Gwen, is the data that relates the who to the data and who has accountability. And I think that's where the industry is kind of going. Are you feeling the same way? Ben. Hi. So who has accountability and another set that just came up in discussions today is to what level data survived and have we certified at a feed level, at a field level, and what does that certification mean? And others who are responsible for management reporting or financial reporting need to know exactly how well they can trust each and every data that goes, feeds into their metrics. So that is one aspect of governance that they look at, they're looking at the governance of the data itself, the who aspects are more about the people, the human side of data governance. And that's important as we know from getting the right people, and I talked about it in other webinars, to get the right people involved at the right time for the right reason to make the right decision and most often leads to the right results. So with that in mind, let's move it over to Pablo. Pablo, I know we've talked about the artifacts and things that are being governed within the OES Church. Do you want to share with us what metadata you manage and how you go about managing it? Yes, so the answer to the question of how do we handle the metadata associated with the data governance program, the answer is not very well, okay? I'm pretty sincere here. Frankly, one of the problems that we have is that, you know how Wen mentioned that in some organizations, data stored has a bad taste and a bad rep, okay? In our organization, the word metadata has a bad rep, okay? So it's one word that I cannot use. Nevertheless, what we do is we are creating a data sharing portal where we have our glossary of terms and we have there the capability of storing a definition and I always try to say that it should be not a database definition, you know, not what is in the comments column of the database but actually a business definition and those are really, really hard to come by, okay? It's worse than trying to extract wisdom teeth from people to get a good definition out. We also have there the opportunity to classify the terms in terms of confidentiality and privacy and also designate who is the data store. So we group the business terms into domains and then assign these domains to a department and a data store. So that is the metadata that we are governing. The grouping of business terms into domains assign the business terms to a data store, classify the business terms for confidentiality and privacy and then trying to come up with good business definitions and the other one is that last one. All right. The other one is the classification. It's also hard to actually many times commit people to a decision even if it's a simple decision, okay? That's when people are shy to find out the decision on these things. Can you clarify what you mean by classification? Are you talking about classification into domains? Are you talking about classification as far as highly confidential, sensitive, public? Yes. So we have two classifications. One is the confidentiality classification whether it's public, internal use, confidential or highly confidential data or can then the privacy classification whether it's not privacy-related, be-related or PI under regulation or very highly sensitive on privacy. Okay. Where do you store most of the metadata? So we have this application that we are creating called Data Sharing Portal. Okay. So the kind of data sharing agreement is very big to the LDS Charter's solution, right? So this application, that is one of the things. The first one is to be the glossary, the data glossary for the organization. Okay. And that is where we do the metadata management and the classification of these terms and then also helps us to control the sharing of the data. Okay. I will let that slide. The definitions were easier to do but in my experience, it has been. So if someone else knows how to do them better, actually that would probably be a really good topic for a webinar is how do we get business definitions out of business people? Okay. So this is going to be our pocket and maybe that will be something that we'll address in the future. Okay. Can I do a quick follow-up? No, that's not a big deal. Okay. Go ahead, Blaine. We just got to leave Dan some time. Okay. Great. Well, I think just that as Pablo said that metadata is a difficult word to say there, but we've seen that a lot as is documentation or definitions writing. No strategic leader needs to spend money on those. But if you rebrand all of that work as transparency into our information, they all jump on board immediately. Because after all, metadata is just a tactic. Documentation is a tactic. The created dictionary is a tactic. Strictly, what they want is transparency. Now that I turn it over to Dan. Dan, did you have to sell the governance metadata into your organization? I know that you were using a couple of different tools. You're still using some pretty well-known tools. Was transparency part of how you sold the need for it or how did you go about doing it? Yeah. Well, fortunately for me, my experience in trying to sell the metadata governance and everything was all from my previous organizations. When I joined PNC five years ago, it was the people that were before me, the people that hired me had already sold the indicators on the need for data governance and metadata. So after a long time of trying to be the salesman, it was clipped because then I joined the data governance manager here responsible for metadata. The sales job was already done. Now it was time to execute. It was a whole new challenge. So that was in 2008. Our first order of business in that sort of fledgling warehousing business intelligence group was to select a metadata repository. And we did, we selected Informatica's metadata manager, which we'll use today for our technical metadata and essentially point that tool to our Oracle databases, even our OBIE environment, et cetera. And we're using it for transparency, the data lineage, the abilities to be able to trace data from reports back through the warehouse layers to their sources, et cetera. Again, we still do that today. We made a fundamental addition to that in 2010 when we decided to get our manager on our business metadata. And so this is where we bought in and implemented a business metadata repository or a business glossary. And that's what we use adaptive for today. And so with adaptive, we have a business glossary where we've established the roles of data consumers that propose terms and definitions into owning catalogs which have data owners associated with them, donors assigned those newly proposed terms out to data stewards, the subject matter experts. The data stewards then do kind of the heavy lifting on the definitions to get the appropriate stakeholders around the organization to weigh in on what these terms and definitions should look like in fact to the data owner for final approval. The tool includes a workflow capability. So these are email notifications that go to the data owners and data stewards that this content has been proposed for their catalogs, et cetera. The part I'll say then what we also did with that implementation very soon after getting adaptive up and running is we've linked the business metadata repository with the technical metadata repository. So you can get sort of a 360 degree view from a business term which in some cases can be kind of a high level topic like customer number or something like that. You can see that it has an enterprise definition. It has an enterprise data owner associated with it. And then you can actually link from that term into the technical metadata to see exactly what database fields are involved in delivering that data. And from there you flip into the metadata manager world where you have all the stability and all the other technical metadata attributes associated with it. I know that metadata has always been a big part of the kind of the building block of which governance was rolled out. I just want to throw this kind of follow-up question out to the three of you quickly. And so why don't we start then with you? I mean, the search and the people who you identify as being involved in the governance activities, what's their responsibility for the metadata? Sir, last part again, what's the response? No, the kind of follow-up question to that was, how do you involve the stewards or how are the stewards involved in the metadata management and keeping the tools up-to-date and active and approving things and stuff? My response on that is short, so I'll throw it out there. I mean, for us, again, with our business and glossary application, it's their interface. It's, you know, when data consumers, and that's anybody throughout the organization, they can compose those terms by selecting, you know, what data domain that term should belong to, at least what they think. These are all notifications that show up, you know, in the data owner's inbox. So they have that work queue. They assign it out to data stewards. Again, my comments earlier is just, it's very tactical. When we're adding, you know, new data owners and data stewards, we can be very direct as to what we're looking for from them, the content that they're responsible for, and then it's a living repository. So, you know, anybody can look at, you know, the set of terms in the risk catalog or in the finance catalog and see who's responsible for those, how much understanding workflows there are, how many have been, you know, set in and approved, et cetera. Okay. All right, yeah, and Pablo, I mean, I know you don't use the M word, but how do you get the stewards, how active are the stewards in managing the metadata as well? I don't know. No problems on me. I'm sorry. Okay, there we go. Sorry. Yeah, that has been a problem for us, actually. You know, sometimes we can engage them, and one of the trouble that we have is that if the people that know the definition of the business terms, they know it in their heads, okay? And they believe that that information is widespread when in reality it is not, okay? Or it is shared actually in the organization. But to get it out of people's heads into a written definition, that has been actually a big challenge. So I actually want to see and to know how to do that better. Okay, anybody out there who has any suggestions? Maybe even Gwen can answer that. Gwen, just in a quick minute or so, maybe you can respond to the relationship between the stewards and the metadata? Sure. You know, I would be repeating what the other guy said, but what I'm hearing from here is that it's evidence that most of our programs are still doing remedial work because if we were starting for a new development or developing new data, then at some point in a project, the data is absolutely defined. It goes through this process. So we're trying to deconstruct our datasets and retrofit the definitions. So I certainly look forward to a period when we get caught up and we can move to better practices. Meanwhile, anyone out there who has tips for extracting this kind of information, that's highly valuable, be able to let us all know. That would be great. And if you even send it to me in an email or to Shannon in an email, it'll get to me and we can share tips like that in the follow-up email. So thanks. I think that those were great answers to the question. I've got to move on to the third and final question for this. So the question is we're going to start with Pablo, then we're going to go to Dan and Gwen. We're going to ask you to kind of wrap up this question. But Pablo, is master data something that's important to your program or is your program important to master data? Are you using the term master data and are you, you know, are there specific subjects of master data that you have already governed? Yes. So master data is actually extremely important in our program. Master data has actually gained in reputation because of that. We developed an MDM solution in-house that was quite inexpensive. And on the governance side, our team helped the master data program by doing the marketing really with the data stores about the advantages of putting information in an MDM repository. So over the years, we have been able to put basically different types of data sets. So the reference data sets that we have are languages. For us, the list of languages is extremely important because we translate materials in languages and we have to keep track of what is the content that is produced in the different materials. Geopolitical locations, all the list of countries, regions, localities, also that is one data set that is extremely important and governed through the master data repository. Also because we are a multinational organization, we have the list of currencies and exchange rates that are from the MDM. So those are the reference data sets. The master data sets that are more in turn to the organization are all the organizations and the leaders of the organizations. For example, the churches, the bishops, the ecclesiastical leaders of the church. All we have in the MDM are now the employees information, the reporting hierarchy, and all the physical facilities where are the churches, temples, seminaries, and so on. So this information is now shared with these different data sets. We are sharing them with over 95, 97 different applications that receive feeds of the data daily, and we deliver this information over 400 different endpoints. And the information is refreshed from the sources daily into all these other consumers. So that has been a big goal. The relationship between MDM and governance is really that we are kind of the main marketers of MDM, both for the data stewards, the vision of the data, and for the requesters that receive the information. The things that you described, that's exactly... Of course, the vast nature of your governance program and the different parts of the world that are infected and where you're getting data from, certainly going into the best practice award winner this year. So I like your answer. I think it was very helpful. Hopefully people got a lot out of it. Dan, I want to kind of switch over to you real quickly. Do you use the term master data? What does it mean to your organization? What's the relationship between the master data and the data governance program? Sure. I can probably get you some time back on this one, Bob. We do use the term master data. Although there have been a few attempts, we don't have a funded master data management program as of yet. There's been some time and energy spent in looking at the different solutions from like the IEMs and informatics and things like that. We don't have an MDM program today. We do have in our metadata world and our data governance world along the lines of master data, things like product hierarchies and starting toward an enterprise product hierarchy where everybody can have the same understanding, the same roles and relationships among all of the products and things. If we're successful in doing that this year, I would consider that a step forward in this MDM space, but no fully funded program today at PNC. Okay. And the truth is in the organizations that I've worked with, some of them are doing master data management, some of the organizations are doing master data management and not even calling it MDM and they're not looking for specific tool sets to solve their problems for them. But what they are trying to do is you see it everywhere that data governance and the term master data are connected at the hip. And so wherever you hear data governance talked about, you also see MDM. Whenever you see MDM, you see data governance. Gwen, can you share with us maybe some of your experience with different organizations real quickly about, you know, which ones have you seen governance focused on master data? Have you seen it be successful when it has not? You know, share your insights with us, please. Sure. Wherever the concept of master data management has been sold, there's a really good chance that you're going to also see governance in place because it is an acknowledged truth now, maybe not the first few years of master data management that a stable set requires governance. However, MDM is unsold in two situations and environments that in with their data architectures are just not supporting the business. They have spaghetti code. They have embedded terms throughout their systems that are just creating all kinds of problems. We've found that MDM has seen a master data management effort the way the vendors would, the toolers might present it, is the master data implement apps. And in the financial industry, it's usually called reference. Master data is just grouped into ref data as the broader term. Correct me if you have a different perspective of that. But in some environments, we have reference data as code sets and master data as being the values of our people, our places, our customers, et cetera. But in the last three years especially, I've seen a really interesting situation and it's one of the things that made this current job so attractive to me. And that is a school coming to terms with the idea of master and reference data management as being the key to findability of information that relates to business competition, your effectiveness, your efficiency. Those terms that may be labeled as reference data, the data values that might be labeled as master data are the very same terms that are used in queries if we're doing search or structured data. In search terms, if we're moving it through web or unstructured content, as tags that can apply to document management, content management, record management, those that end up in taxonomies or the facets if we're using a faceted approach to search or new semantic technologies, they tend to be the values that are applied to the different levels of hierarchies or customer hierarchies. They're the terms that are used over and over and over again in reports, their titles, their headings, the key fields that appear in them. So the trend that I'm seeing now is to take a very broad, holistic approach to examining how these same sets of controlled vocabularies are applied across traditional data management and governance and these other related fields. I'm just going to have a ball this year looking at strategy for how to pull all of that together in very large, complex organizations. Any of you that have already done this work in maybe smaller organizations or less complex ones, please reach out to me. I would love to share stories and I think this is another topic for another discussion. I think it's a great topic for discussion and it's really good to hear you talking as a practitioner and say, hey, have you done this before? Please let us know and share your ideas with us. One of the ideas of having this type of forum for the webinar is to get people talking about things, to get people to share ideas, and it's a great channel to be able to do that. So we've had a lot of people signed up for this webinar and a lot of people on the session right now that hopefully they're getting a lot of good information out of it and maybe what I'll do is I'm going to hit on each of the three panelists to see if they provide some insight to some of the other questions that we're going to get to. So let's start getting to some of the questions that have come from Poole in attendance here. Let's start with one and we're not sure how great I'm using the Q&A area because I'm getting partial questions and things like that, but one that we can read and it's not really related to the subjects of stewards and metadata and master data. I guess it's more related to the topic of governance in general, but let's start with Pablo. Pablo, do you feel that data governance is different when you're dealing with big data? We don't have a lot of experience. So we are not getting too much into the big data realm yet. And so there will be fine, for example, data stores for some of what would be considered big data sets yet. Okay, we try to focus on those data sets that are requested or shared around the organization. And we are not getting too much of that yet, but I suspect that the same principles that we develop and apply for data governance of the structured data would apply for what would be considered big data or content and structure data sets. If you are following a principles approach to governance, I think that it would be very applicable. Any experience with big data? Have you looked at big data, the relationship to governance? Honestly, I'm still waiting to see whether big data is just one of those newer buzzwords to fill out a lot of books and products and things. But I know that there's more to it. I mean massive amounts of data that traditional database technologies have trouble managing. But I did respond to this question in the chat as well as some others. To me, the principles and the purpose and the process, everything we're doing in data governance, at least at PNC and what I hear from a lot of practitioners, you can apply all of that same stuff to big data as well as any other data sets. I mean, some of the nuances might be a little different as to your lineage or the tools or other data tools for your big data sets. But everything else to me is the same. It's all about data ownership, data stewardship, terminology, et cetera. I get the question fairly regularly if there is such a thing as big data governance. And I'd say, yeah, there's data governance. That's a lot of big data. There's data governance applied to metadata. There's data governance, master data. It's still data governance. Yeah, you're right. There are nuances that you see. Gwen, can you insight into that as to, you know, is there anything different when it comes to governing big data? No, I like your answer totally. What I will say about nuances is that some governance activities are focused towards people and process and the organization. Some are focused upon actions taken upon the data itself and expectations for the data itself and the actions and controls to meet those expectations. When it comes to big data, you can send a question about a data value to a council sitting around a room. Obviously, it doesn't work that way. So our focus is for big data governance is on those expectations, standards, the application of business rules, those control mechanisms that we place upon the data itself. That's our grand objective. In order to do that, we also have to do the human side of data governance to at least design the little g governance. Okay. Nothing. So I know, Gwen, you've written about big g governance and little g governance. Where could people get information about that? I don't know. Probably on the data governance. Oh, yes. That's right. datagovernance.com. Thank you. To that for you, Gwen. One last question that I want to go through and it's kind of interesting in the way that it was asked. In fact, it was asked kind of towards the end when we were talking about master data. How do you even implement a data governance solution without master data? And I would kind of view that as maybe the other way around. How would you implement a master data solution without data governance? Let's move on to Pablo first. Pablo, any response to that? How would you implement a data governance solution without master data? Or is it being asked backwards? Well, I really think that not very well. Okay. So, yeah. So, they are really kind of two sides of the coin. All right. The master data, in my mind, that's kind of the technical integration, basically being able to pull all the information that is most important to the organization together. And then governance, all the processes, the approvals, the soft part of actually making that master data available to the organization. Okay. So, we work really close together in those things. We have quite a symbiotic relationship in the teams. Okay. You've got a quick answer for that. We're running out of time here. I typed one in there. It depends on how you define master data. If we're talking, if we loosely define it as sort of the contents of having data domains free, you have to have those defined for a successful data governance program. I pointed out, though, there's a lot of tools and processes and practices out there under this label of master data. We don't have those in our world today and yet we have an active data governance program. Okay. Go ahead and make the last comments on that. I have a comment on Dan's. You may not have those tools, so you may not fit a vendor's description of master data management, but you certainly have master data and you are managing it and you are also governing it. So, you're doing well. Great. That's my resume. Thank you very much to Dan Daly of PNC, Gwen Thomas of the IFC and Pablo Rebaldi of the LDS. It was a great webinar. We went through a whole bunch of different subjects, data stewards, to metadata, to master data. We had time for the Q&A. If we didn't get to the Q&A already, what we're going to do is we will include them in the follow-up email. Shannon, is there anything else that we need to touch on here? I mean, here's a list of when the upcoming webinars are for next month. Again, it's a special Wednesday date and then the following month is really focused on governance for master data. I want to thank each of the panel members. I want to thank Shannon for her help, as always. And thank each of you for attending. Hopefully you'll provide some feedback to us. Let us know if this type of webinar was helpful to you, and perhaps we can provide something similar to this in the future. Again, thank you very much for attending. Have a good day. Thank you, everyone, and thanks again to our panelists and Bob, of course, to you. I hope everyone has a great day. As mentioned, I will get the recording out. Links to the recording, links to the slides. And as Bob mentioned, answers to questions we didn't have a chance to get to and make sure that we get that information to you by end of day on Monday. So keep an eye out for that, and that'll come from me. Have a great day, and thanks again for attending, and panelists, thanks again for participating. This was a great discussion. Thank you. Great. Thanks.