Hello and welcome. My name is Shannon Kemp, and I'm the Chief Digital Officer of Data Diversity. I'd like to thank you for joining the current installment of the Monthly Data Diversity Webinar Series, Real World Data Governance with Bob Sinner. Today, Bob will discuss how to select the right metadata to govern. Just a couple of points to get us started. Due to the large number of people that attend these sessions, you will be muted during the webinar. If you'd like to chat with us or with each other, we certainly encourage you to do so. And just to note the Zoom chat defaults to send to just the panelists, but you may absolutely switch that to network with everyone. Just for questions, we'll be collecting them by the Q&A section. And to find the chat and the Q&A panels, you may click those icons at the bottom of your screen to activate those features. And as always, we will send a follow-up email within two business days containing links to the slides, the recording of this session, and any additional information requested throughout the webinar. Now let me introduce to you our speaker for the series, Bob Sinner. Bob is the president and principal of KIK Consulting and Educational Services and the publisher of the data administration newsletter. Or, and was, I'm the publisher. And Bob specializes in non-advocacy data governance, data stewardship and metadata management solutions. I need to update your bio, Bob. Before you. And with that, I'll give the floor to you to start the presentation. Hello and welcome. Hi, Shannon. Hi, everybody. Thank you very much for taking time on your schedule to attend the webinar today. Yeah, things change over time. And I think we made that announcement a couple of months ago at the webinar, but yeah, we got to update the bio for sure. Thanks again, everybody for coming today. This is a great topic. I know I always say this is a great topic. But, you know, when I work with Sharon, I've worked with her for long enough, we seem to come up with topics that seem to be very timely, whenever they seem to appear during the calendar. And we set them during the beginning of the year for all the months. The interesting thing about this one is the word right is in quotes, because selecting the right metadata to govern for one organization may not be the same as what is the right metadata for other organizations to govern. So I'll go into that a little bit more detail as we go. I'm also going to spend some time talking about what does it even mean to govern metadata. Because, you know, I always say that the data will not govern itself. Well, now I'm going to talk a little bit more about how the metadata is not does not govern itself and what are some of the actions that are required in order to govern and to steward metadata. I'm just going to take a quick minute here to go through some of the things that I have going on. Lots of things going on as you know this monthly webinar series has been going on for many years and it will be going heading into 2024 as well. Next month, we're going to talk about why governing data quality is so hard. Coming, I will be speaking at the data versity event data governance information quality East in Washington DC coming up in a couple of weeks. I always talk about non invasive data governance. I now have two books on the subject. The first one was published in 2014 called just non invasive data governance and then the one in 2023 was called non invasive data governance strikes again. So please take a look at those. There are a bunch of learning plans available online learning plans available through the data versity training center, one on non invasive data governance one on non invasive metadata governance. You know, basically the topic that we're talking about today. And then the one that's most recent is one on business glossaries dictionaries and catalogs. So if you want to find me, you can always find me at kikconsulting.com, which is the home for non invasive data governance. On the side I am also an adjunct faculty member at Carnegie Mellon and their chief data officer certificate program. What are we going to talk about today. I'm going to really break it into several subjects and I just want to walk through the subjects real quickly with you. First of all, what does it even mean to govern data so govern metadata. So we've talked before about what it means to govern data. You know the same thing holds true for metadata but let's go into a little bit more detail about that. There's a lot of information in the slides in this deck so hopefully, if you find a need, you can go back and refer to these slides because I kind of inventoried all a bunch of the different types of metadata categories of metadata to consider. I'm going to walk through a few of those. I'll talk about why inventorying the metadata you already have is really important because in chances are in most organizations, you do already have metadata. It might not be being governed yet, but again, we'll talk more about that here in a minute. We'll talk about prospecting through the organization for business and technical metadata requirements and also people to steward and to govern the metadata because it needs to be governed as well. And then we'll wrap up by talking about how do we go about selecting the right metadata to govern and like I said before the right metadata for one organization may not be the same as another organization. I'm going to go real quickly through the definitions that I share in all the webinars that we've done together. And my definitions are worded pretty directly and pretty strongly. I talk about governance being the execution and enforcement of authority over the data. It doesn't matter what approach you take to data governance. At the end of the day, you need to have rules that are being followed.  My definition of stewardship is it's the formalization of accountability. You've probably heard me say everybody in the organization potentially is a data steward if they have a relationship to the data, and if they're being held formally accountable for that relationship. So basically, a data steward is a person that's held formally accountable for their relationship to data. Today we're talking about metadata and not only is it data about data. But here's my definition. It's data steward in IT tools. And you can read the rest that improves both business and technical understanding. It's basically data about data. But the fact is that that data may not be real valuable to people unless it's being governed. So we're going to talk about that and then we'll talk about how to go about selecting the appropriate or the right metadata to govern. So the first thing I want to talk about is what does it mean to govern data? And the question that I know a lot of people seem to have is does metadata need to be governed the same way or in similar ways to the rest of the data of the organization. So talk about that. The truth is that you do need to execute and enforce authority over metadata, especially if the metadata is being required by somebody to do their job or it's being required by an agency that says we need this information. You need to execute and enforce authority. You need to formalize accountability. We need to recognize who the metadata stewards are. So let's kind of jump into these topics here real quickly. So the question of does metadata need to be governed? Well, I think the easiest answer to that question is yes. Because ungoverned metadata may be incomplete. It might not be of high quality. It might not be accessible. It might not even be the right thing to provide to the people in your organization that are looking to get value from the metadata. So the answer to the question of does metadata need to be governed? Well, if you need to assure the metadata quality and accuracy, the discoverability, accessibility, all those things that you see on the screen here. And I would say that in most organizations, they do need to be able to assure that you don't want to give wrong incorrect invalid untimely information to people.  It's high quality and it's being kept up to date. I often times talk about cheeseburger definitions for data. What's a cheeseburger definition? It's a, what's the definition of a cheeseburger? It's a burger with cheese. What's the definition of a student account? It's an account for a student. If we want to assure high quality definitions for data, somebody has to have the responsibility for putting those definitions together. Somebody has to be responsible for vetting those definitions. So that's what I mean. We need to govern metadata to assure that it's high quality, that it's discoverable, that it's compliant, that people know where it came from and all those types of things. And the answer to this question is most definitely yes, that the metadata needs to be governed. And if you've been attending these webinars for a long time, there's several statements that I make. You know, the main one is that the metadata will not govern itself. The metadata is not going to select itself as to which metadata you're going to provide to people. It's not going to produce itself. Well, maybe sometimes it will depending on the source that you're going to for the metadata, but the metadata is not going to use itself. So again, just to answer the question of does metadata need to be governed? Well, the metadata is not going to govern itself. So again, I say the answer to that question is most definitely yes. So if you think back to the definitions that I used at the beginning of the webinar, the definition of execute and enforce authority over data, now let's apply that to metadata. So what does it mean to execute and enforce authority over metadata? Well, again, this is where I hope that you'll come back to this slide deck if some of the things that I put in are meaningful to you. But it really means that we need to establish those guidelines, those processes, get people to be accountable for the metadata, formalize those responsibilities. And all of those guidelines, processes and responsibilities, they need to be around the definition of the metadata. Again, I'm going to go through in a couple minutes here. Several categories of metadata and different types of metadata and you can see there's tons of metadata that can be managed. The question of which metadata are we going to manage and the definition of that metadata that we provide to people is really important. Again, the definition of the metadata is not going to not going to magically appear. If somebody has to have the responsibility for it, it needs to be governed. Same thing holds true for the production of metadata. Again, you're looking to go to get the metadata from somewhere where that means that typically somebody somewhere had the responsibility for at least making certain that that metadata was being produced. So, again, what does it mean to execute and enforce authority over metadata? We need to do that over the production of the metadata. We need to define what metadata it is we're going to collect somebody somewhere somehow has to be responsible for producing that metadata. And then of course, why are we doing this? Why are we collecting the metadata? Because people are going to use the metadata and there's ways that we need to govern how people are going to use metadata, getting it into the right people's hands, sharing it appropriately. Again, the use of metadata also needs to, we need to execute and enforce authority over that. So, I talk about authority and governance and the enforcement of policies. Again, these are just different ways that if you think about that these things are not going to happen on their own. If nobody is given the authority to establish who's responsible for the metadata, nobody's going to be responsible for it. So again, I'm just providing different ways that there needs to be governance over metadata. There needs to be enforcement of policies. I know with a lot of organizations, some of the organizations that I work with, they're creating metadata and then they're reporting that metadata to someplace else that somebody is requiring that they provide that level of metadata. So there could be policies around your metadata, somebody needs to enforce them. There's just some additional ideas of ways to execute and enforce authority over metadata. It comes down to compliance and monitoring comes down to the resolution of discrepancies. Let's say people have different definitions for the same critical data elements. That needs to be governed. There needs to be some path towards resolving what the definition is or having two definitions but not necessarily calling the data the same thing. If you don't have data called the same thing that has different definitions, maybe add context to how you're defining your data, but there needs to be a way basically to resolve discrepancies around the metadata. And again to keep the metadata governed there needs to be continuous improvement around the governance of the metadata in your organization. And again going back to the earlier slide where I talked about my definitions I talked about formalizing accountability for data that was my definition of what stewardship is. Well, if we think about it again like I said that the metadata is not going to define or produce or use itself the metadata needs to be governed. We need to formalize accountability for doing these things. Again, or they're not going to be done unless it's metadata that's magically appearing out of the blue somebody's going to be need to be responsible for producing that metadata. Somebody's going to again be responsible for with all the different categories of metadata defining which specific metadata we're going to manage and which we're going to deliver to our clients internally within our organization. And then there's the formalization of accountability for the use of metadata. Again, some other quick definitions of ways that you can formalize accountability, set up roles and responsibilities. Who's going to produce the metadata when are they going to do it, how are they going to do it, where are they going to do it, you know, set up some expectations around roles associated with governing your metadata and stewarding your metadata. Again, documentation of the responsibilities and the establishment of policies and standards. Again, what I'm hoping to do with this slide deck is provide you a resource to go back to when you so when you're thinking about what do we need to do in terms of stewarding the metadata in our organization.  And here's even some more things that need to be done in terms of stewardship around the metadata. There needs to be training and education people are not naturally going to know, excuse me what metadata exists or where to go for that metadata or how to access it. If they do know where to go. So there needs to be training and education and needs to be training and education in terms of how they use the metadata, basically how the metadata is produced. If we're expecting to hold people accountable. We can't expect that they know exactly what to do without some level of training and education. And then there's the oversight and governance and the monitoring and reporting. You know, as I said, data needs to be governed just as much as I'm sorry metadata needs to be governed just as much as the the the data itself. But there needs to be somebody who is focusing on formalizing that governance and formalizing that stewardship around the metadata. The governance of the metadata may be somewhat different and I'll talk about that here in a minute as to who are the stewards of the metadata. They may not be the same exact people as the people that are the stewards of the data. In some cases that might be true. In some of the cases, the people that are actually defining and producing the metadata are not the business stewards of the data. Or maybe they need to be involved but they're not ultimately the ones that are making certain that that metadata is being governed. So I mentioned that I want to talk about recognizing metadata stewards. So I always say that it's very simple to recognize who your data stewards are and your organization because if somebody is defining data as part of their work, or they're producing data as part of their work, or they're even using data and that's the category most people fall into use the use the data in the organization. They're stewards they don't have to be called stewards they don't have to have to be tagged on the shoulder and told their stewards, but they if they're being held formally accountable for how they define produce and use data, their data stewards. I often say everybody is a data steward get over it. The only way we're going to cover our entire organization is to know who those people are that are defining and producing and using data within the organization. When it comes to recognizing metadata stewards there's not going to be as many people. There's going to be in these people may be more technology focused than business focused but I think you need to work with a business focus. People to determine what is the appropriate metadata that we need. And how should that metadata be defined. So I'm not sure you're going to find a lot of people that are already defining metadata. But where you have tools in your environment and there are certain pieces of information within those tools that are going to be critically important to people. Those people can help you to define what metadata is available and to help to make that that metadata available to people across the organization. You know, are there people producing metadata certainly there are certainly when you're creating data models and you're entering business definitions into data models and they follow your whole pipeline till they get gets to the catalog and into the hands of the people that are using it. Somebody's producing that metadata somebody's producing that definition. So yeah there's already people producing at least some of the metadata within your organization. And certainly there's people already they're using the metadata what I'm just suggesting is when we go out and we try to recognize who those people are. You're going to probably find a lot less people who are defining producing and using metadata, then our defining producing and using data. So just keep that in mind. So the question is do these people exist within the organization are there ways to hold them formally accountable, certainly by setting up standards by standard operating procedures and those types of things we can help metadata stewards to do the job that we're expecting them to do. But we also need to some degree when I talk about stewardship of the metadata, we need to find ways to be able to hold those people formally accountable. And so the question that I get for people is should we assign metadata stewards and if you know me and you've heard me talk about non invasive data governance. I say assigning stewards is very command and control ish. It's very top down very bureaucratic. I say even identifying people as data stewards is feels invasive it feels over and above I usually say, let's recognize people. It's the only way to really truly formalize accountability is to assign people to be metadata stewards. Then if you need to do that then I would suggest that you go ahead and assign people to be metadata stewards. So yeah the metadata will not govern itself, you know one of my favorite state it's one of my favorite statements along with the data will not govern itself. Everybody is a data steward, get over it. And so applying governance to data process. One of the other lines that I tend to use one of my favorite statements and this. I say this to people when they ask how long I've been married to my wife. I say we've been married 35 years and that's a long time to put up with a person and I'm talking about her putting up with me and not what's in reverse. So these are some of my favorite statements. And again, you keep coming back to the idea of the metadata will not govern itself. So let's talk a little bit about the definition of the metadata here and let's go through some of the categories of metadata that you might want to consider. If you're just starting your metadata program. So I'm going to go with the same three actions that I say that people can take with data or can take with metadata. And I've been challenged and people have said, people have said to me that oh there's other categories other than definition production and usage. Everything seems to fall under the action of either defining the data, producing the data or using the data. So what I want to do is I want to provide to you a list of some of the most typical metadata that falls under those categories and where you may be able to look in your organization to gather some of that metadata. So we're going to go through data definition metadata data production metadata usage metadata. We need to govern metadata about our stewards and metadata stewardship so it's kind of sounds kind of redundant but metadata stewardship metadata is another one of the categories and then metadata process metadata is another one of the categories that I want to go through with you today. So I'm going to start with and I typically go from from beginning to end with definition then production and then usage. So I'm going to start with the definition metadata and what are some typical examples of what I would consider definition metadata for your organization. And if you can see a lot of these items are things that you probably already have in data dictionaries business glossaries data catalogs is certainly the data element name the data type the size. And I don't want to go through each and every one of these. But this is some of the most typical data definition metadata that is being used in many organizations and that can be collected through your data catalogs, you know all the way down to who's the owner of the data. How is the data being classified. What are the tags that people we need to apply to the data so that people can find it what steps are going through or we're going through as an organization to validate the data. So all have to do with the definition of the metadata. And again this is just a list and in most organizations, they do don't necessarily record all of these things. But again it's just a good starter list for what you may need in terms of the metadata, the metadata that's going to help with the definition of the data. So the question is, if we need to govern all of those different types of definition metadata. Where can we find this metadata in our organization. And I know that that many metadata repository administrators they recognize that a lot of these tools that the database is for DB to an Oracle and SQL server and tear it in wherever you have your data in the cloud in snowflake the database schemas. That's data definition metadata. We need to be able to incorporate that metadata into our data catalog, because ultimately people are going to want to even if we're giving them definitions and business terminology, where does the data reside what does the data actually look like data modeling tools. Those are strictly metadata tools we're actually entering in information about the data, you know the entities the attributes the relationships the, you know all of those things that we entered data modeling tools, those are data definition the dictionaries obviously your BI tools your warehouse, all these different places may there may be that there may be metadata about the definition of the data found in all these different places. Now the chances are if you have a data catalog you're not necessarily going to pull from each and every one of these. But you might want to consider if you're looking to find some of that metadata that I listed, or data definition metadata that was not on my list. It may reside in one of these platforms or in one of these places, the challenge of the metadata repository administrator or a catalog administrator is how do we get the metadata out of the tool and into the place where people are actually going to go and be able to see the tool, see the metadata. So data definition definition metadata resides in a whole bunch of different places. And as I shared with you a second ago, there's a whole bunch of different metadata that can be considered data definition metadata. So I'm going to go on to the next action which is the production of the data the production of the metadata. What are some of the examples of data production metadata. You know when was the data created when was the data modified who did it who was it modified by what the version is all of these different items have to do with the production of the metadata, what, or the production of the data itself. And where does that information exists it exists within the metadata. So even the ETL and the data movement and that type of metadata those are examples of data production metadata, the transformations the rules that are being followed as you're integrating data or moving data from one place to another. That's all metadata that's associated with the production of the data. So there's a lot of different types and again organizations don't necessarily manage to each and every one of these. But at least this is again I want you to be able to come back at if you feel it's appropriate, come back and look at this list and say, what other types of production metadata, do we need to govern. And, and I'll talk about this a little bit later in the webinar, but how are we going to know what metadata is most important. I got an answer for that. And you know you really it's pretty logical we just need to talk to people to see what information they need to make the data more meaningful to them. So where can the data production metadata be found again don't want to go through all of these things that there's a whole bunch of different types of places that you can go. Again, depending how on what you've defined as being metadata, where you can go to get your data production metadata. I'd say the one that's probably used the most is data source documentation out of all of these. But there are different places within your organization where metadata is hidden within tools hidden within instruments within your organization. There are places that provide information about the production of the data that may be useful to people at some point in time. And so again when we're going about selecting the right metadata to manage. Not only do we need to give them data definition metadata, but we need to also give them data production metadata because I know that anybody who uses a data warehouse, or a tool like that wants to know where the where the data came from. How was this data actually produced, and that resides in your data production metadata. And wow I think even the list of the data usage metadata is even longer than the production which is longer than the, the definition metadata. But here's a whole bunch of different examples of data usage metadata. And again I could have made this into 110 slide webinar but I decided to cram them all on a single slide because I thought that they were appropriate to be grouped together. So when was the when was the data last accessed what method do people use who did it of all these different pieces of data usage metadata are important and so we need to look to see where does this metadata exists within the organization. And here, I'm providing here a list of places typical places that the usage of the data is being logged somewhere. Is it important to you I guess we need to ask the business community as to whether or not information about the usage of the data is important to them. And for a lot of people the answer to that question is going to be yes they want to know who's accessing the data how, when, you know, where are they accessing the data and those types of things. So data usage metadata, again I've provided lists now of data definition data production data usage metadata where they can be found. The last two categories that I have, and the first one focuses on the metadata stewardship metadata. So, there may be questions when when you actually start to give people access to the metadata as to, you know, who's, who's defined the metadata, who produced it who's using it, who's using the data who's using the metadata. When was the last time that we actually formalized the responsibility for somebody to take care of the definition the production and the usage of the metadata. And then it's also nice to be able to carry information about how stewardship has changed. Now people that developed systems 10 years ago that your organization is still still using, they may not be around anymore. So they're so that definition if it was ever recorded somewhere, or if it wasn't recorded somewhere, it's gone with a person that that knew how these things were defined at that point in time. So just knowing how stewardship has changed in your organization is another angle of metadata that we got to consider managing. The question is, is it the right metadata for your organization to govern, and then there's the metadata process metadata, you know what processes in place to define and to produce and to use the metadata who participates in the process. You know, when does the process take place. Again, this is metadata process metadata. What I didn't do is I didn't go all through all the different categories of tools. Because you can do that to you could go through the different categories of tools in your organization and kind of cherry pick or pick out those specific pieces of metadata that are important from each tool. I decided to take the approach of defining the metadata categories in terms of the actions that people take with data, the definition the production and the usage of the data. Let's talk about inventorying metadata that you already have because the chances are that you already do have metadata. I can remember years ago, we're talking to potential clients who said, well, we don't have any metadata and I asked them a couple simple questions. Do you have a data warehouse? Do you use a relational database management system? Do you have a data dictionary or a business glossary? Yeah, yeah, yeah, we have all those things. Well, then you already have some metadata. And so the what the first thing before you go about producing new new metadata, let's look at the most common places where metadata exists. Let's talk about the uncommon places to look for metadata. You'll be surprised by some of the items on the list. Real quickly, I'm going to go through the characteristics of what valuable metadata is, and then the benefits and what it means to govern the existing metadata. So where are the most common places in your organization that metadata already exists? Well, here's a list. Again, I don't want to read through all of them. I might pick out a few of them. But in your filing system, in your DBMS and in your databases, in your document management system, a lot of organizations keep structures of their data, keep a lot of the rules associated with the data in things like SharePoint and other tools, OneNote and things like that. So look to see where in your organization you have existing metadata or even in your document management systems or content management systems and emails and all those types of things. So when you go about inventorying the metadata that you already have and start trying to identify what the value of that metadata is, these are some of the places that are really most common for people to be able to find metadata that already exists within your organization. Here's some additional places, the content management system, digital asset management, warehouses, you know, those types of things. Typically, if you've invested in data technology, there's tools in your environment that are housing a lot of metadata that might be useful to people if you could get it into their hands. So again, these are just some of the places, common places that you can go to find metadata. And then there's uncommon places. And when I went to look to see what were some of the uncommon places to look for metadata. Well, it gave me a list. As I was researching it, I received a list of all these places. These may not apply to you. But the bottom line is not just to look at the obvious places for metadata, there may be other places within your organization that metadata exists. And here's some more criminal justice, information system, language translation tools, you know, all these different platforms may house metadata that's going to be valuable to people within your organization. And real quickly, I'm just going to go through what some of the characteristics of valuable metadata is. And I think most of you probably understand it, that it needs to be accurate. It needs to be relevant, complete, consistent, timely. And it needs to be accessible and made available to the people within the organization. So I say if you can say that your metadata is all of these things, it's going to be valuable to your organization if you've done the research to determine that there are people in the organization that have an interest in using this metadata to access the data or to get the more use, get that more value out of the data. So what are some of the benefits of inventorying your metadata? Well, certainly, you know, if you're going to get to a point where you're providing metadata to people, you need to know what metadata already exists. You need to then focus on the metadata that doesn't exist to make certain that there are processes in place to define, produce, and to use that metadata. But the basic reasons of why we are going to inventory the metadata is because we want to be able to improve people's understanding and context. We want to enhance our ability to govern data across the organization, provide data discovery and retrieval all of these things. So again, I hope this is a list that you'll consider coming back to at some point in time of what are some of the benefits of even inventorying your metadata. I talked to a lot of organizations that do a lot of work around inventorying their data. There's a lot of inventory programs going on in organizations right now. We should also be inventorying our metadata because if we're going to provide this as a valued resource, we need to know what's going to provide value and where that stuff is. What does it mean to govern existing metadata? Well, that means some of the things I talked about earlier, defining policies and standards, assessing the quality, establishing stewardship roles. Basically, it means the same thing as it means to govern data. It just may be different because the people may be different and the places where the metadata exists may be different. What does it mean to govern existing metadata? It means addressing all these things. Where did the metadata come from? When the metadata changes, how do we update the metadata store and give people access to up-to-date, on-time, delivered metadata? Monitoring and auditing metadata activities, all these things is what it means to govern the existing metadata in your organization. So I told you I was going to talk about how do we go prospecting into the organization for requirements around metadata and for people around metadata? I'm going to run through a couple of questions with you real quick and see what you think about them. The first one is we go to these people and we ask them the question of what they can't do. What can't you do because you don't have the data to do it or you don't trust the data, you're not confident in the data, you don't know where to go? And these are the things that people that I talked to are telling me. They can't make informed decisions. They can't conduct analysis of the data because, again, they don't know what data exists or they don't know the quality of the data or they don't have a high level of confidence in the data. Other things that they tell you, they can't implement these types of things within their organization. So one of the best ways to figure out requirements for something is to ask the business people in your organization what they can't do, what challenges are they having? And then marry that up to the idea of, well, if we provide you information about the data, is it going to help you to do those things better? The flip side of the what can't you do question is what would you be able to do? So let's think outside the box a little bit. We know we're all restricted by the data that we have and the knowledge of the data we have. Well, let's say you had access to all the data that you needed and the understanding of the data. What would you be able to do? And again, I've documented what some of the most common things are that I hear from people. They have the ability to make informed decisions, conduct meaningful analysis. Again, I don't want to read through each and every one of these, but if you ask the people in your organization, what can't they do and what would they be able to do? And you can relate that to the metadata, the information about the data that would give them the ability or give them the confidence level to be able to do those things. I think you're heading in the right direction. So ask them what they can't do. Ask them what they would be able to do, but keep in mind that you're going to need to be able to relate that to metadata management and where the metadata is going to help them to address some of those challenges and some of the things that they'd like to be able to do. So I have been using a term recently and I did not come up with this term and you could do research on it and you can find information about it on the internet. I don't know if it's ever really been formalized as a term, but I know that one of the things that organizations are trying to do with metadata is to raise people's data confidence level. And so I'm just going to refer to that as DCL. In fact, I'll be talking about that in my tutorial that I'll be giving in DC in December about governing data dictionaries, data catalogs, business glossaries. Why are we doing this in the first place? Because we're trying to raise the level of confidence people have in the data that's being provided to them. So what do we want to do by raising the confidence? We want to provide clarity. We want to ensure accuracy. We want to enable efficient searches for the data. We want to support lineages that give people the understanding of the source and the transformation of the data within the organization. We can facilitate compliance, enhance data quality. All of these things are really important. Again, the whole concept of data confidence level. If we ask people what level of confidence they have in the data, again, what I hear from a lot of people is the reason why we can't use the data the way it's being provided to us is that we don't have confidence in it. And you've probably heard the term data wrangling. People are spending 80, 90% of their time wrangling the data and the data analysts are only spending 10% of their time actually analyzing the data and making decisions from it. Well, why are they spending that 90% of their time wrangling the data? Because they don't have necessarily the confidence in the data the way it's being presented to them, or they need to take some actions in order to get the data the way that it needs to be in order for them to get the most use out of it. So one of the things that I suggest is also let's prospect for our requirements by having conversations with people within the best business. You know, understand what they're going to be what they're using data for align what you're providing your metadata to do with the business goals that that part of the organization has. I have a client right now that we're doing that we're aligning everything with the vision and the mission for the organization. In research you'll find that that's one of the first things that people suggest about data governance metadata management data management is that these things need to be aligned with business goals. So share with them that what effective governance looks like, you know, and explain to them what's possible in terms of what metadata you have. You know, all of these things you get these are just this could be a series of topics that you discuss with the business when you're meeting with them to determine what types of information do they need that's going to raise their data confidence level. And so the idea of turning these prospects these people that you're meeting with in the organization in the customers what are some of the steps that you can do that. You can provide training. You can ensure that people have user friendly and easy accessible tools to access the metadata that the metadata is integrated so people don't need to go to six different sources in order to get six different types of metadata. That's the whole concept of the metadata repository the data catalog. It's kind of like building a data warehouse of metadata for people. So some of the things again to turn prospects into customers, educate and train them provide user friendly metadata access integrated into the applications and the tools I found that one of the most effective ways of delivering metadata is to deliver it along with the data. I know there's tools on the market where you can hover over certain pieces of information, and it will then go to read from your metadata resource and provide the metadata as people are doing analysis of the data. There's customized providing customized metadata views engaging these folks in some type of a feedback loop to see whether or not what we're providing to them has been beneficial to them. So again, there's a whole bunch of different ways to prospect for requirements within the organization. And the truth is, you know with all these different types of metadata that are available and with all the different places that metadata already exists out there with all the different applications of metadata, or what you're trying to do with metadata. The first question is, how do we select which metadata is right to govern. And that was the point of the webinar today. My answer is to talk to the people that need to understand the data ask them what metadata or ask them basically what information about the data is going to be most useful to them to improve their data confidence level. Educate them on the metadata that's available and the effort that they need to go through in order to get access to that metadata. Build literacy with metadata, you know, provide content. There's a lot of things that that metadata can do to help to improve literacy across the organization. It can provide context and meaning it can clarify the relationships between data and other data in the organization and even the dependencies between the data. It still facilitates discovery and access supports lineage. It does all these things. So if you get to the point where you're selecting the right metadata to govern and you're making it available to people, and you're using it effectively, you can use it to build literacy across the organization, using the metadata that you have. One of the things that improves literacy is helping people to know that there's even metadata available or where they can go to get that information about the data that's going to raise their confidence level. And it guides usage and interpretation and system regulatory compliance. There's a lot of things that collecting metadata will do for the business community as well as the technical community in your organization. Let's go back again to the first definition or one of the definitions I shared at the beginning that metadata is data stored within tools within it tools that improves both the business and the technical understanding of data and data related assets. That's what we're trying to do. That's the metadata. We're going to build literacy through providing these people with the most relevant information in the most relevant way to address their concerns and their requirements. So I know I went through a lot of these slides relatively quickly, but here's what I talked about today. What it means to govern metadata and what it means to steward the metadata. What are the categories of metadata that people should be considering and I broke it down into metadata about the definition of the data, the production and the usage of the metadata. Steps that you should take to inventory the metadata that you already have because I'm guessing that there's metadata stores storage places within your organization that you might not even know exists. So while you're inventorying your data inventory your metadata as well or maybe inventory your metadata as your inventorying your data itself prospect for business and technical metadata requirements. And again select the metadata that's going to be most meaningful to the to the business community and the technical community within your organization that you are hoping will get the most value out of the metadata. And with that Shannon, I am going to kick it back to you and see if we have any questions from today. Thank you so much for another great webinar if you have questions for Bob feel free to put them in the Q&A portion of the screen. And just to answer the most commonly asked questions just a reminder I will send a follow up email by end of day Monday for this webinar with links to the slides links to the recording and anything else requested. So Bob diving in here so if an organization does not yet have any formal data catalog, what comes first the chicken or starting producing some metadata or the egg of establishing some metadata governance. Well the fact is that even when you do get to the point where you acquire a data catalog that metadata is going to need to come from somewhere. So a lot of those, a lot of that somewhere is from tools from technical tools within your environment, but then there's also other metadata that's going to improve the business understanding of the data. And that's going to be the definitions and the terminology. And, you know, even the stewardship and the processes and those types of things that I mentioned earlier. So yeah, there's things that you there's it's not a chicken or an egg. At least I don't consider it to be that type of a scenario. While it takes a while to number one even get the ability to bring in a tool, let alone to acquire the tool to install the tool to to productionize the tool. In the meantime, we should be actively working to collect at least the metadata that we can, so that when we do have the tool we're able to port it over. So I would say it's not a chicken in the egg I would say it's a chicken with the egg. So can we use that answer for for all of life. All right diving in here further so. So Bob Stewart equals person held formally accountable for their relationship to the data, who is there. Just the steward of her himself or what about the story being accountable for on behalf of an entire group or team relationship with data. That's that's good I mean they can be responsible for their entire team or their entire function, at least for the defining and the producing of that metadata. But the fact is that most of the other the there that I'm talking about is specifically them a steward is somebody who either defines or and or produces and or uses data as part of their job. And they're being held formally accountable for how they define produce and use that data. So, I mean the fact is that yeah one person may have certain levels of accountability or stewardship around the data for their part of the organization, but they can't be the only person. So that's why I say everybody potentially everybody is a data steward, and that the only time that we'll get to a point where we're covering the entire organization is when organizations get over that fact that potentially everybody is a data steward. So, yeah it's good to have group representation because that's necessary somebody needs to take the lead. So, just to show you that the people who are the stewards of the data, potentially the people that are the stewards of the metadata are going to be much more than just that single person. Okay, so Bob, this is more of a statement than a question but a persona, or some running examples of what these terms mean in an organization context could be really helpful. You know what, when I talk about roles and responsibilities and Shannon you know we do a lot of the webinars on roles and responsibilities. In a lot of ways, you can take the operating model of roles and responsibilities and you could translate it to the same types of roles, maybe at a little bit of a different level for metadata. I would say that, yeah, it's a great statement, but the fact is that, you know, some of these roles already exist if you have any if you have if you're building a data dictionary. And seems like every organization is building data dictionaries, or business glossary, or data models, these people have responsibility, formalizing that responsibility and formalizing the roles around metadata management is very important. Um, there's been a few questions, you know, about the past recordings and stuff. So I'm going to put a link in that sort of link just to the recordings from your series. I can give you a different link for all day diversity webinars, but this is specifically for this. I'll look for specifically for the one that you're talking about that we've done in the past on roles. We've done, we've done several of them. And it's again, how do you apply? I think we've even talked about metadata roles and responsibilities. So, or if somebody wants to talk about it in more detail, they can reach out to me and we can talk about it. Perfect. Thank you. So moving on then, our organization is moving to data mesh architecture. It seems that traditional metadata repositories work pretty well for this purpose. So, I'm going to go to the data domain, subcandidate, gory equals data product, business term equals data elements in the product. Have you represented data mesh in a repository yet? And does your approach resemble what I described? You know what I'd really loved it sounds logical what you described, but to date, I haven't had a lot of enough experience to truly talk to how the data mesh would be represented within a metadata tool. I think that if it's anything like any of the traditional types of data stores that you would want to collect the information about it the same way you would also want to collect information about who the stewards are because I know pushing the accountability and the responsibility out to the business areas is one of the highlights of utilizing data mesh technology. So, certainly the data steward metadata would be part of it, but I don't want to try to make something up for something that I don't have a lot of experience in. I appreciate so. Hard to admit I don't know. But again I'd love to have that conversation because I think you see or I know you're going to see more and more organizations that are applying data mesh. And, and there's, and there's many, many organizations that are acquiring and implementing data catalogs and metadata solutions. So, I think that's something that's going to need to be answered very soon. Do you have any recommendations to manage to critical data assets, second party data and third party data in a cooperative database environment. These are great questions today wow these are really tough questions to know a lot of it will have to, I think your ability to handle the second and the third levels of data from data from outside of the organization if I correctly is the willingness to be able to, to share that information about the data so that that information can also be provided within your organization if I understand the correctly, the question correctly is, we're going to need sometimes you need to rely on other people providing you metadata in order for you to have access to the metadata because again you don't want to make it up you'd rather use the real metadata that's coming from outside sources. So that's what I suggest is work with those folks to get metadata in a format that it is ingestible into the tools that you use. Each seven minutes left so I can try and slip in as many questions as I can hear great questions. Yeah, they're great questions. metadata stores include people already using metadata it really is this the relationship also alone sufficient to be appointed as a governor for some metadata. So if you're just a user of the metadata you might not have anything to do with the definition or the production of that metadata. That's why I try to simplify it into those three actions that the data and metadata definition the data and metadata production and metadata usage. So it is possible that as just a user of the metadata that you might have some level of responsibility for making certain that that you're using the metadata correctly that the people that you're sharing it with are using the metadata correctly. So I would say a user doesn't not does not necessarily isn't the one governing per se the the organization of the organization at least the definition of the production of that metadata. So, again, it's different for every organization again if they have the accountability and the responsibility for how metadata is used then yeah they're governing the metadata. But in a lot of cases, a lot of the true governance that I talked about is in just in selecting the right metadata and producing that metadata and getting it into the hands of the people. Bob, are there effective step by step guides or instructions for implementing a metadata catalog when not driven from a vendor perspective. I think there's a lot of places that you have first of all I think vendors can provide you with lists like that. I also think that you can use things use tools that are available use artificial intelligence and ask questions that relevant questions as to what specific actions need to take place. To give you a good starting point it's not going to answer your question 100% for you but use the tools that are available to you so I think there are a lot of step by step processes again I didn't go through one today. But again if somebody wants to talk to me about it we can we can certainly have conversation about that. There's probably an endless list of specific actions that you can take to start governing your data and you're governing your data catalog and providing this kind of a tool to your organization. We've done some data catalog demo days I'll put a link in the chat there as well with as we've got all vendors in there so it can't sort it yet we'll be working on that. I don't know if you're a client of the you have to be a client of the vendor for them to provide you those actions. I don't know but I would also say that just doing searches on the internet to find plans that other people have published will again get you part of the way there but again you're going to need to customize it specifically for your organization, but there are a lot of resources that can provide you that information. Yeah, absolutely. So, but when capturing a data production metadata can you give examples of how you capture data sources when data sent to a data warehouse to use the system name and identifier something else. Could you ask the question again because I'm not sure I understand. Sure. So when you're capturing data production metadata. Can you give examples of how you capture data sources so when data is sent to a data warehouse to use a system name and identifier something else. Well, the idea is that you need to rationalize and bring that information and tie it to the appropriate information within within the tool. Again, I'm not really sure what they're asking about but you know as the data is working throughout its lifecycle, the metadata about the data and the different points of the lifecycle have to be made available. So again I'm not sure I'm answering the question exactly but again I'd love to talk about it if somebody's interested in talking about it. We've got about three minutes left here so. So, okay so the question of the day how do you govern metadata without a data catalog. Well that means that you know if you have your metadata in a data dictionary or you have it on a SharePoint site or you have it somewhere within your organization, the question of how do you govern it. Well, you make sure that you're defining the appropriate metadata into that data into that metadata source. You make certain that somebody has there's first of all there's rules associated with what the produced metadata needs to look like, and then there you govern the people that are entering that information into it directly into a catalog or you said without a catalog directly into some of these other tools. If people are expected to use your data dictionaries that are in spreadsheets. Well you need to govern the metadata in the spreadsheets because that's just the way people are accessing the metadata. Yeah you still need to govern it when you when it's being made available through the tools itself. Yeah, I say that you know we.  It's not very helpful to a lot of people. But but if you want to make it helpful then converting that into a model that people can see and they can use maybe beneficial. Again it takes governance of all forms of metadata whether it's in a catalog or outside of catalog. Well Bob, that brings us right to the top of the hour lots of great questions I won't be sure to get those over to Bob and I'll include those. The answers to the questions we didn't have time for today in the follow up email which will go out by end of day Monday with links to the slides and links to the recording as well. But thank you so much for another fantastic presentation and thanks to all our attendees for being so engaged in everything we do. Thank you Shannon thank you everybody I hope this was helpful to you. Have a great day. Bye.