 So, and look, and my name is Shannon Kemp and I'm the Chief Digital Manager of Data Diversity. We'd like to thank you for joining the current installment of the Monthly Data Diversity Webinar Series, Real World Data Governance, with Bob Siner. Today, Bob will be discussing data and metadata will not govern themselves sponsored today by Irwin. 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. Click the chat icon that was in the bottom right-hand corner of your screen for that feature. And for questions that will be collected by the Q&A in the bottom right-hand corner or if you'd like to tweet, we encourage you to share highlights or questions by Twitter using hashtag RWDG. And as always, we will send a follow-up email within two business days, containing links to the slides, the recording of the session, and additional information requested throughout. Now let me turn it over to Danny for a brief word from our sponsor Irwin. Thank you, Danny. Hey, Danny. Hello, and welcome. Thank you, Shannon. And welcome to everybody out there. Thanks for joining. I know you're here to listen to Bob, so I'm not going to waste a ton of your time up front, but just wanted to say hello and happy to be sponsoring this event, especially when Bob's the speaker. So just a few bits around Irwin. If you're familiar with us, we started out as the little data modeler that could, turned into the data governance company. And as of January 1st, we are now part of Quest. So lots of excitement going on there, and I think lots of interesting things from a solution perspective in terms of our ability to really drill farther into the enterprise in support of good data governance and really driving the data-driven enterprise. So what I'm going to talk about a little bit just as, and I think it relates well to this topic because, you know, the data is definitely not going to govern itself, and what I wanted to talk about is sustainable data governance through the concept of data intelligence. So let's get to that. For those of you that, you know, aren't familiar with the term data intelligence, it's really an approach to looking at your overall data landscape, the estate, if you will, and really providing the capabilities that are required to build a canvas that's going to support all aspects of your data ecosystem, whether it's the folks doing data governance, DevOps, folks that are consuming that, obviously with the goal of getting the most out of your data while reducing the risk that is inherent with leveraging that data for different purposes across the enterprise. Data intelligence in a nutshell is really the ability to do five basic things. It's harvest what you have in terms of your physical world of real data, organize that in a way that you can understand what you have and how it relates to each other, curate that data so that you can provide a number of different contexts to that data, primarily a business context, but also looking out into things like quality, looking at the infrastructure that's supporting that, and the people that are responsible for that data and have accountability for it, ensure that you're supervising that data in a way that people understand how to use it, how not to use it, what type of data they're accessing, and what the potential benefits and risks might be, and then socializing that big picture out to all of those different constituencies so that they can understand their data landscape and then collaborate together to deliver the value of whatever role that they have, but with the benefit of having all of the inputs of all of those other folks and the visibility into the things that they're doing around data so that you can work much more effectively together. So data intelligence, when we look at the topic today, it really is the functional canvas that's required to create one I'd like to call your data governance masterpiece. So, you know, on the left is what, you know, many organizations that are looking at, which is a lot of data, a lot of different technologies, a lot of different infrastructure, and then a lot of other things on top of that that are going to, are requirements for you to really, truly govern that data in the organization. So the left is the data governance or the data steward with their head and, you know, shrugging and wondering what they're going to do with that mess, or looking on the right side, which is, you know, that canvas where people can start to look at that data, see the connections between them and are looking at something like a customer and understand all of the business assets that are associated with customer, and then all the places where customers instantiated so that people can start to navigate that drill down into the details behind that and really leverage all of that good information to make better decisions and get to the end state of what they're trying to deliver the company much more quickly. So, actually, last year, we did a great survey in conjunction with Dataverse, the looking at data governance and specifically looking at automation and bottlenecks to successful data governance. And we got some great information back in terms of what are the things that people are finding really tough to put up, stand up and maintain in a sustainable way over time? Because again, that canvas needs to be up to date, it needs to be fresh all the time, because if it's not, then you're taking people down, down rabbit holes that you don't want to take them. So, a lot of challenges around that. And, you know, not surprisingly, things like understanding the lineage, you know, where did that data come from, what happened to it on the way, understanding the quality, finding and identifying what data they have and what's appropriate for their use case, and then being able to consume that data in a way that is understandable, useful and usable to them are all things that are very tough for a lot of organizations. And this is where we get to the spoiler alert from the first slide, which is automation absolutely is the key because that's how you can keep things there ready and up to date. So, you know, looking at key automation points that you can that you can create in your data intelligence fabric that will enable sustainable data governance, you know, it starts with with all of that metadata that you have out there, and the ability to auto document all of the data sources, data models, all the movement process, all the consumption points, as well as as auto document, the business aspect of that, whether it comes in terms of industry standard glossaries, things like that and being able to pull them into an environment where you can start to work with them. Looking at automation around the work of connecting all of this stuff together, because that's a huge lift, you know, you have lots of technical assets that you don't necessarily out of the box can see how they are associated, creating connections between things like terms, policies, rules, data sharing agreements with specific physical data assets, building those out, finding and discovering where your sensitive data is and classifying it appropriately. Again, another great place to leverage things like, you know, artificial intelligence and machine learning to really, you know, do the heavy lifting and allow you to focus on doing the things that you want to be doing from a governance perspective and truly building up that that governance, you know, infrastructure and, you know, society within your organization. And then the ability to give them things that are going to accelerate their understanding. So, you know, the ability to navigate this entire framework and render different visualizations that are out there, things like lineage, things like impact analysis, that visual mind map that allows you to see all aspects of something in data and use that to start to navigate dashboards that pull up and really focus on specific use cases like sensitive data, regulatory compliance, GDPR, CCPA. And then, you know, if you take it a step further, which is actually auto generate, you know, a lot of your data pipelines, your workloads and start to automate aspects of DevOps that are occurring, but are that are equally important to your folks in data governance because that's the next thing that they need to govern. So very important pieces to consider in terms of looking at supporting data governance from a technology perspective. And if I can just sort of finish it off with a quick look into an automation case study, a global farmer, farmer leader had made the decision to move forward and modernize their data warehouse, taking it out to a cloud environment. But more importantly, looking at a data vault approach to to maintaining that to provide more agility. But the, you know, manual work involved in it was tough. It was taking a lot of time, it was actually reducing the impact of this new approach and the and stopping the benefits from being realized. And on top of it, you know, they still needed to govern that they had to make sure that they were safe guarding things like personal health information and all the rest of that. So they brought us in. And with our data intelligence technology, they were able to automate their entire data vault environment and not just the initial creation of it, but the ongoing, you know, change and maintenance and change management. So that DevOps piece, where they had, you know, a lot of infrastructure that was basically reduced down to 10 to 12, you know, automation scripts and connectors that we supplied, and really made an impact in terms of reducing manual development time. And really getting to them to the finish line faster, with the benefit being that that same environment that automated the whole environment had governance mechanisms and capabilities that they could leverage throughout. So as they move to this new platform, as they move to this new approach, they were able to govern through the entire process and have data governance on day one, once they were set with what they had. So that's my small piece, you know, data, data absolutely will not govern itself. And when you get ready, and you are ready to govern that data, you really want to look at a sustainable backbone that you can rely on to practice your data governance on. And with that, I will pass it back to Shannon, and to Bob, and we'll get to the meat of the discussion. Thank you very much. Danny, thank you so much as always. And thanks to everyone for sponsoring today's webinar and help making these happen. And if you have questions for Danny, we will likewise, he'll be joining us for the Q&A portion at the end of the webinar. So feel free to submit your questions in the Q&A portion of your screen. Now let me introduce to you our speaker for the series, Bob Sinner. Bob is the president and principal of KIT Consulting and Educational Services and the publisher of the data administration newsletter, TDAN.com. Bob specializes in non-invasive data governance, data stewardship and metadata management solutions. And with that, I would give the floor to Bob to start his presentation. Hello and welcome. Hi, Shannon. Hi, everybody. And thanks, Danny, for for the presentation before jumping into this material. You know, Danny talked about how the data and the metadata will not govern themselves. And the key word that he spoke about was the word stewardship. I'm sorry, he spoke about automation. And the key word that I don't want to speak about, I'm getting ahead of myself here, is that I want to talk about stewardship and data and metadata. Because truly, unless you have some type of a pixie dust that you can sprinkle over your organization to automatically, you know, create and use the metadata of your organization and the data of the organization, it's not going to happen in a way that where that data and that metadata is truly governed. So we'll be speaking a lot about metadata. We'll be speaking a lot about the data. We'll speak a lot about stewardship as well. And so let's get moving on the topic at hand. And just real quickly, before I get started, there's always a lot of things to share with you at the beginning of the webinar. We just wanted to point out a few of those things to you. The real world data governance series will continue into February. And the subject for February is data architecture is data governance. And I've got my special guest, a good friend of mine, Anthony Alvin will be presenting with me for that webinar. I talk about noninvasive data governance a lot. So if you're interested in picking up the book on noninvasive data governance, there's some information for you to help you to locate it. I will be speaking at a bunch of data versus the events that are coming up and one that I'm really excited about actually, I'm excited about all of these. But the one that's taking place next week, next Wednesday is the Enterprise Data Governance online conference. It's a virtual conference that's been taking place annually for several years. And it's just a fantastic event from beginning to end. So we hope that you'll register and join us for that. I am going to be conducting some live online training through Data Diversity on March 12th, a half day, where the topic will be a complete set of data governance roles and responsibilities. I'll be speaking at Enterprise Data World a little bit later in the year in April as well. I have several courses that are available online learning plans through Data Diversity. The first one called noninvasive data governance. The second one called noninvasive metadata governance. And yes, metadata governance is a real thing. It's not being, the term's not being used by a lot of organizations, but the truth is the metadata won't govern itself. If we want to have strong metadata to improve the quality and the value of the data, we need to govern the metadata too. So there's a course on noninvasive metadata governance. And then the one that was introduced recently was the business glossaries, data dictionaries and data catalogs. So please go to the Data Diversity Training Center. There is a lot of great stuff out there. And please take a look at my courses and my learning plans, as well as all of the other instructors that provide them there. Shannon mentioned the data administration newsletter, TDN.com. If you're not familiar with it, please go out and take a look at TDN.com. It's a free publication, published twice a month, was published yesterday. So a new issue was made available yesterday, where I talk about the explosion of data catalogs and a lot of other great subjects. And the last subject is KIT Consulting and Educational Services. That is my consulting and education business. And please go check out KITconsulting.com. The website is new. And I refer to that as the home of noninvasive data governance. So there's several subjects that I want to touch on today. And the first one is, you know, how does data governance apply equally to both data and metadata? If you've been attending these webinars over the years, you've probably heard me say that the data will not govern itself. I've also started to say that the metadata will not govern itself either. So we want to make certain that we're applying governance equally to the data and to the metadata in order to provide valuable resources, data resources to people across the company. I talk now a lot about what I consider to be a resolute effort. And I'll describe to you what I mean by a resolute effort. We need to put effort. We need to put resources. We need to get people involved. We need to get metadata stewards as well as data stewards in order to be successful. I'll talk about how the governance of data and metadata increases the value of both the data and the metadata. I'll spend a little bit of time talking about the people who must be held accountable for the data and the metadata. And then we'll talk about communicating that whole concept of the fact that the data and metadata will govern themselves to the people in the organization that'll make a difference. So let me real quickly just start by sharing the definitions that I use for the terms governance and stewardship because I've already used those. And it's good to get everybody on the same page in terms, in the relationship to what the terms mean. And I word my definition to data governance very strongly. But I do that with a reason that, you know, at the end of the day, if we're not executing and enforcing authority over the data itself and other data resources, we're truly not governing our data. So there are other softer definitions to data governance, but I like to word it strongly. I like it to people to sit forward in their chairs and ask questions about what do we mean by the execution and enforcement of authority because no matter what approach you take, whether it's the non-invasive or the command and control or the traditional approach to data governance, at the end of the day we need to make certain that we're executing and enforcing authority over the data. And then I'll be talking a lot today about data stewards and data stewardship and metadata stewards and stewardship, but really data stewardship is the formalization of accountability. So I've always said that everybody in the organization is a data steward and we need to get over that fact well if you use sensitive data, the fact is you're a steward of that data, you need to know the rules, you need to follow the rules associated with privacy and some of those regulations that Danny spoke about a little bit earlier in the session, but data stewardship is that formalization of accountability so we can build on the efficiency and build on the effectiveness of the organization. Non-invasive data governance basically takes those two definitions and brings them together. It's really the practice of applying that formal accountability using non-invasive roles and responsibilities. We're going to apply governance to existing processes or apply it to the new processes that we as an organization are developing to make certain that the definition production and usage of the data does all the things that we know that we need to do, assure regulatory compliance, security, privacy, protection, improve the quality of the data. And really non-invasive describes how governance is being applied in your organization. The last definition and I'll just I'll just share this with you on the screen real quickly is what does it mean to govern something. So I went to freedictionary.com and I took some of the things that they used to describe what it means to govern something. So let's think about that in terms of governing the data. Let's think about these things in terms of governing the metadata because we know the bottom line is that these things will not govern themselves. So let's talk a little bit more about that. Let's first talk about how governance applies equally to data and to metadata. So we've probably all heard the term that data is an asset and you know truly organizations are setting up strategies and policies to make sure that the data is governed and managed that way to make certain that it is recognized as an asset. And you know the truth is that data itself and I'll share an example with you in a minute it's worthless unless we provide some context to that data and where are we going to get that context we're going to get it through the metadata it's the data about the data it's the information that's going to help us to differentiate between different pieces of data and truly have that context and know how that data can be used throughout the organization. So if we think about that we think about that metadata is really important and the data is actually worthless without it metadata becomes an asset too which means it also needs to be managed it also needs to be governed and the truth is that that stewardship getting people to be formally accountable for the management for the definition the production and the usage of metadata it's required we need to formalize accountability for the metadata in order to govern the metadata just like we need stewardship in order to govern the data of the organization and as I mentioned earlier in the session metadata governance well it's a real thing we need to make certain that we are taking a resolute effort to govern the metadata within our organization so I'll talk a little bit more about that in a minute but there's a resource that I've gone to a few times the CPA journal that has a really good description of what do we mean by data being an asset so data and they recognize that data is an economic asset that can do all the things that are listed on the screen they can help you to improve your operations increase revenue I've had several clients recently that have looked to make the data available to their clients in a self-service fashion and the the only way that they're able to make it self-service for for these their clients and for their customers is to increase the understanding and the knowledge of that and so that's actually a revenue-increasing opportunity you know certainly when we solidify the rate relationship with the stakeholders the people that are going to use the data to perform their job functions and use the metadata to better understand that data you know having data as an asset it certainly solidifies the relationship with stakeholders prevent provides produces new revenue streams improves the quality establishes competitive differentiation which is extremely important to a lot of organizations it allows innovation it reduces risk I just think this is a great snapshot of how we can consider or why we should consider data being an economic asset so the fact is to our organizations also recognize that metadata is an asset and again I'm not going to go through each of the bullet points on the screen but I want to tell you that you know you think about how metadata will do each of these things in order to to get people to get better to use and to better understand and to have better confidence in the data we need to make certain that we're governing the metadata as that asset as well so data is an asset everybody's heard that metadata is an asset I hope that you understand that I hope that you believe that because it's certainly true we need to have metadata for the data in our organization at least for the most critical data that people are using to make business decisions so let me give you an example of how data is worthless without context and the piece of data that I'm providing to you is the 1299 with you know rate justified in zero filled to the left and if you just saw this piece of data zero zero zero zero one two nine nine you know what is your guess as to what that piece of data means well the fact is you don't know unless you have the field name unless you have other information the description of the field you don't know if that's a dollar amount it might be it has a ninety nine at the end of it we see a lot of prices with ninety nine and it it could be an address actually I used to live at one two nine nine on a specific street but you know so it could be that it's an address it could be a quantity it could be a measurement the fact is we don't really know what that data means unless we've provided the context and we've provided the metadata and the metadata is not going to produce itself it's not going to define itself it's not going to use itself so we need to make certain that we're governing that metadata associated with the data to add that context to the data so you don't know if it's a dollar amount or an address or a quantity or a measurement you know or is it really something completely different it could be anything to your organization so we know that we need the data is worthless without the context and we need to add the context and that context comes from the metadata that's collected in tools like the one Danny talked about collected in other tools in the environment we know that metadata is a valuable asset to the organization so i said the data is worthless without context well the data by itself is meaningless and the value that the business derives from that data without really understanding what that data is it's truly minimal actually when i put down that it's minimal i thought you know it's even less than minimal it's really worthless to the organization unless we have governed metadata that people have confidence in when they're going to use the data that's most important to their job and their job function so the data and the metadata must be connected at the hip i couldn't find a good image of connected at the hip so you know i brought in this this image for this slide but it's truly the better the metadata the better the value the better the quality the better of the understanding the better the confidence that people have in the data so therefore the metadata must be governed as well as the data so we know that that just left to their own accord they're not going to govern themselves so let's talk about that a little bit and as i mentioned at the beginning of my session my part of the session today it's all about the stewardship stewardship is required to govern data and metadata and since we know that these things won't produce themselves we need to have people in the organization that are formally accountable for managing the data and the metadata but you know we don't really talk about stewards in terms of metadata anymore and we know that metadata is actually different in most situations than the data itself so if we know we're going to improve the quality and the value of the data we and we want to improve the quality and the value of the metadata we need to make certain that data that metadata stewardship becomes a real thing within our organization so the question becomes well what does it take to govern metadata well it actually it involves having a plan because again it's not going to happen on itself or on or left to its own you need to have a plan for it it takes having people accountable for the metadata those are the metadata stewards i'm talking about it really takes having metadata stewards people that are defining what metadata is going to be managed by the organization putting definition to that metadata there needs to be people accountable for producing that metadata and certainly we want people to have access to the metadata so it takes people using the metadata and being formally accountable for using the metadata to best understand the data that they're using to make decisions for their organization so is metadata governance a real thing well the truth is that if you don't have metadata governance you know potentially the quality and the value that you're going to get from your metadata is not going to be as strong as if you had people that had accountability for the definition production and usage of that metadata so i say that metadata management requires data and roles and processes and communications and metrics and tools in fact i talk about these things all the time as being the core components to data governance well the fact is there are also the core components to metadata and metadata governance as well and if you've attended my webinars in the past you've seen this diagram before it's the non-invasive data governance framework but i tend to share a lot and those items that i just mentioned that metadata management requires are the items across the framework and so if you're interested i know Shannon always connects or or makes available a copy of the data government of the non-invasive data governance framework as part of the follow-up email that she does but please take a look into this non-invasive data governance framework and realize that a lot of the same things are going to need to be in place in order to govern the metadata as well so let's talk about that idea of resolute effort and what does it mean to have a resolute effort in order to get something done so what's the definition of resolute you know resolute basically requires things as such as management's commitment management's understanding as to the role that metadata plays in the improvement in value and quality and usage of the data resolute effort requires resources and certainly tooling will become part of the job part of the effort in getting the metadata managed and getting the metadata governed so the Oxford Dictionary defines resolute as being admirably purposeful determined unwavering unswerving well you need to have people who have the responsibility for metadata management you need to have data of metadata stewards you know all these things that are mentioned in the Oxford dictionary definition of resolute they all apply to metadata governance as well so people in the organization and that's oftentimes the management of the organization first they need to be sold on the investment that the organization needs to make in terms of people and process and roles and the things that are all necessary to govern the metadata just like the data itself so people need to be led down the path the leading of people down the metadata path will not happen on its own either and we need to make certain that we have people that have the responsibility for it if that picture is not familiar to you that's the resolute desk that's the desk that's in the White House you might be familiar with it that picture of JFK's son under the resolute desk but you know the idea is that you know being resolute in your effort to govern your data is extremely important and don't let anything get in your way and that is truly what you need to be successful with data governance so resolute I mentioned it requires management commitment and understanding you know if you think the data governance kind of teeters on that brink of being something that you must have well hopefully you're not in that situation hopefully you're in a situation where people in your organization truly understand the value of data governance well you can think of well what is it in terms of metadata governance that that Peter's even even worse on the brink we need to be able to explain to people what metadata governance is and why it's important and I talk a lot about best practices associated with data governance and the fact is that those same best practices apply to metadata governance as well like the first one being senior leadership support sponsor and understand the need and the fact that governance for metadata is necessary just like it's necessary to be able to have an effort to govern the data in your organization that the resources must be allocated I've talked about the stewards and getting stewards engaged you know we need to have resources allocated to this discipline we need to define the goals and the scope and the expectations for metadata management and metadata governance we need and just like we do for data governance the roles associated with the data and the metadata must be clearly defined approved and communicated and we want to be consistent in the way we do these things across the organization so resolute also as I mentioned before requires resources so a resource is basically a source or supply from which benefit is produced and that has some utility and I mentioned that everybody in the organization is a data steward and we need to get over the question is is it necessary that everybody in the organization is a metadata steward and that's not necessarily it's not as necessarily as strong a case for the metadata stewards being everybody but we know that we need people that have the responsibility for defining what metadata is necessary for producing that metadata because it won't produce itself and for using the metadata to help them in their job so those resources basically take the form of people and time and money and we need to make certain that we're allocating those or that we have those in order to be successful with metadata governance as well as data governance and certainly to have a resolute effort it often really helps to have tools involved and those would be tools that would be used to govern your environment your data environment your data landscape the business glossaries the data dictionaries the data catalogs and then you could also create do-it-yourself tools like one that I share a lot which is the common data matrix and I'll share with you an image of that in a second if you're not familiar with the common data matrix but you know often organizations start with do-it-yourself tools and they build out the requirements that are necessary before they go about acquiring tools and oftentimes if you're going to implement a tool and I know this from all the organizations that I work with that are implementing data catalogs metadata repositories data landscape tools there needs to be somebody who's the owner of the system if you call the metadata catalog the system somebody needs to administrate it somebody needs to be analysts who are working with the business people in your organization you need resources they're required for tooling and I mentioned the common data matrix just want to share a quick image of it with you it's a it's basically a spreadsheet that you can use to recognize who's accountable for the data across the organization from the from the operational stewards to the subject matter experts to the steward coordinators the council and so on and so forth it becomes a really powerful tool it is the most requested tool from these webinars and from any presentations and articles and things that I write so the common data matrix that's also going to be made available through Shannon at the end of the webinar so let's talk about how governance of metadata of data and metadata increase their value well it's going to increase their value by basically having formal definition of these things formal definition of data and metadata formal production of that data and metadata again unless we make that formal the chances are that it's not going to happen on its own certainly we can use automation to ingest some of the metadata from our environment but even setting that up and making certain that that's working and that we're checking to make certain that the changes are being reflected in the data and in the metadata that requires effort you know formal data and metadata usage that's another way to increase the value and formal data and metadata stewardship as I've been talking about so far let's talk about each of these things real quickly as well so the increased value from the formal data and the metadata definition well if you formally govern the data and the metadata definition people will know what data and metadata are available they'll go to the tool they'll go to the environment that you're setting up to support them and they'll know what data is available they'll know what metadata is available to help them to understand the data and that takes effort it takes somebody communicating that information to all of the stakeholders across the organization they'll not only know what's available but they'll know what that data and that metadata mean I mean for example with some glossaries and dictionaries that I've been setting up recently we've included descriptions of what each of the pieces of metadata are because if we're expecting people to be metadata stewards out in the business areas they need to know what information to be entering into these glossaries and dictionaries that we hope that will adjust into the catalog at some point in time and people will have confidence in the data and the metadata if they know what exists and they know what these things mean to the organization they'll be able to make more informed decisions they'll get more value from the data and the metadata if we can formalize accountability for the governance of the data and for the governance of the metadata and that requires that we have stewards that are associated with these really valuable assets to our organization let's talk about how it increases the we can increase the value of the data and the metadata through formal production again the metadata and the data they're not going to produce themselves we need to have people that have the responsibility for these things so people will produce the data closer to the data specifications if they know what those specifications are and how do they know what the acceptable ranges are how do they know the format of the data you know unless we unless we share with them what the specifications of the data are you know we can't assume that people are going to know those off just off the top of their head you know they're going to produce higher quality data and higher quality metadata if they understand the data specifications if they understand the metadata specifications and that's what I meant about you know adding to the glossary and dictionary spreadsheets even you know what do these things mean how are they going to be used across the organization people will be held more accountable for both data and metadata production so again if you have people that are entering their definitions into the data modeling tool or into the glossary I always joke about the concept of cheeseburger definitions and well what's the definition of a cheeseburger it's a burger with cheese what's the definition of a student account student account number it's the account number for the students if we want people to be accountable for providing definitions to the data they're going to help business people to understand that data when those people that are putting the definition to the data shouldn't be allowed to get away with cheeseburger definitions they should be following the specifications of what is meant by a true business description of business definition of the data people will produce the metadata on a more regular basis if we they're formally accountable for it people will know where the data and the metadata come from which will both improve their confidence in the data and improve their confidence in the metadata as well so we're going to increase the value of the data and the metadata usage because people will gain more efficient and effective access to these things to the data and the metadata it'll help them to have improved confidence in the data that they require to do their job and certainly we want them to have confidence in the data and in order to do that we need them to have confidence in the metadata so if we have formal definition in production of the metadata there's a better chance that we can also increase value from the way people use that metadata because we'll be providing that context to them so that they'll better be able to make use of that information the people will understand the importance of the glossaries and the dictionaries and the catalogs and if they understand the importance of the glossaries, dictionaries, and catalogs they're going to be more likely to participate in those initiatives to get those things collected get that metadata and the data collected and make that available to people across the organization and then really the last thing here is to increase the value from formal data and metadata stewardship we need to hold people accountable for data that's what data stewardship is all about we need to hold people accountable for the metadata because without it the metadata won't govern itself and definition in production and usage of the data and metadata need to be governed in order for people to get the most value out of the data and metadata that we as data practitioners are sharing with them so without formal accountability for data and metadata well the data and the metadata the definition of that will stay the way it is and the production will stay the way it is and the usage of the data and the metadata will stay the way it is so the truth is if the status quo what is the status quo right now for the governance of the data and the metadata is satisfactory to your organization maybe metadata stewardship and metadata governance will feel less important to you but the truth is in a lot of organizations people are not satisfied with the accountability for the data they're not satisfied with the accountability for the metadata and if you find yourself in that category then you certainly want to start thinking about putting a metadata governance program into place making certain that you have metadata stewards that are formally accountable for the definition production and usage of that data all right so let's talk about the people who are going to hold accountable for the data and the metadata these metadata stewards so basically I typically break what people can do with data and now metadata into three categories and that is they can define it they can produce it they can use it and typically whatever you're thinking of that might fall outside of this thing is probably can be categorized under definition production or usage so the people who are accountable for the definition these are the people that are required to to define which business and technical data is necessary there are people in the organization say we need to collect information about this well there's also people in the organization that need to because metadata is such a widely ranging category of data they need to select what metadata is most important to your organization so the definition of the data and the metadata is extremely important so we want to make certain that we're holding people accountable for providing solid business definition to the data and also business definition to the metadata itself providing the business definition you know we need to provide business definition to both of these things and we need to give people the opportunity to provide feedback on that data and on that information that we're making available to them and as I mentioned earlier data stewardship is all about formalizing accountability for the management of something and in this situation it's data stewardship metadata stewardship it's formalizing accountability to the definition of the data and of the metadata that's important to the organization so the people who are accountable for the definition it's people that participate in defining what metadata you're going to collect providing the definition of the technical data that's going to be collected and even providing the definition of what that metadata means for the organization provide there's people that provide a means of collecting these definitions provide the access to the definition of the data and the metadata the metadata production as I keep saying it's not going to happen on its own we need to have people that are formally accountable for it and these are the people that are participating in the production of the data production of the metadata you know if we allow them to use cheeseburger definitions they're going to take the path of least resistance and they're going to provide the easiest definitions that they can but if you have standards for what those definitions look like and people are producing the data and producing the metadata to match those requirements you're going to have more value you're going to get more value out of that metadata and that's going to help you to drive more value from the data itself so we need people who are people who participate in recording the metadata whether it's through a data modeling tool or a data quality tool or whether they're practicing data science and data analytics there's a lot of metadata that's collected about the data through those processes and we don't want the that information just to stay in the tools that they're being entered into we need to take the covers off that metadata and make it available to people across the organization so collecting the appropriate metadata the people that participate in collecting the appropriate metadata you know they certainly have an accountability as well and then there's people that participate in the data and the metadata usage and these are the people that are using data to perform their job function using metadata to help them to understand the data better so they can better perform their job function these are the people that use the data to make decisions based on their knowledge of the data using the data to improve the operational efficiency and the operational effectiveness of managing these things as assets if we go back to the early slide I talked about managing these things as assets and a lot of the things that are necessary in order to do that and that includes improving the operational effectiveness and efficiency and using the data that's classified as sensitive or that must be protected these are people that are going to be accountable for the data and the metadata usage within your organization so the last thing that I want to talk about before I switch it back to Shannon and Danny and I take some questions are the people that really make a difference within your organization so you know so I'm going to talk about executive sponsorship of your metadata activities executive sponsorship of your data activities the people that are managing the governance effort the stewards and the stakeholders of both the data and the metadata so the executive sponsors certainly make a difference in fact as I mentioned in the best practices before you know the criteria I use for best practices if we need it you know we're going to be at risk if we don't achieve this best practice and the support sponsor and understand the data and the metadata governance and the needs for these governing needs for these governing activities certainly your organization is going to be at risk if your data is not governed or if they if the people at the executive level don't support sponsor and understand what the heck it is we're doing when it comes to data and metadata governance now these are the people that approve the efforts and approve the you know the people in the organization that are going to be accountable formally accountable for the data and the metadata recognize that you know the value these folks are make a difference because they recognize the value that comes from governed data and metadata they provide the appropriate human resources and other resources to your organization and one of the most important things is oftentimes at the executive level those are the people that approve the funding for the effort to start and maintain a data governance program and a metadata governance program they approve the funding for the acquisition of the enabling technology if you're going to be able to use any of these tools you know this leadership of your organization is going to need to understand why these things are important and the value that they're going to bring to governing data as an asset governance management makes a difference they also need to support sponsor and understand the activities they approve the efforts and hold certain people responsible for these activities so if you're going to apply metadata stewardship we need to keep them or hold them formally accountable they recognize the value that comes from the governed data and metadata they provide the human resources and often the people who are managing governance are the ones that are requesting the funding to start and to maintain programs associated with data and metadata governance and they request the funding for the acquisition of these technologies that are going to be beneficial to us the data and the metadata stewards make a difference and we need to communicate to them that the data and metadata won't govern itself now they need they understand the value they need to understand the value of governed data they recognize the benefits that they're getting from governing that data and metadata they are communicated with and they communicate their requirements for improving data and metadata they participate in those activities the definition production and usage activities of both data and metadata and they're the ones that are oftentimes involved in the in measuring the effectiveness effectiveness of our governed data and our governed metadata initiatives within our organization and the last group is the data and the metadata stakeholders you know I typically suggest that one of the best ways to convince your stakeholders that metadata and data management are really important is to ask them two critical questions and the first question is what can't they do now because they don't have confidence in the data and the information about the data that they need to produce their job or to follow through with their job so you know what can't you do what is preventing you from doing it what in terms of data and metadata is preventing you from being able to do the things if you had better understanding of the data if you knew how it was classified you knew where to go get it would that help you in your job and the second question which is a lot like the first is well what would you be able to do if you had improved confidence in the data if you had improved confidence in the metadata and there's really a third question that really relates to the first two which is you know understanding how governance actually relates to what they can't do and how governance relates to giving them the capabilities to do the things that they would do with the data and the metadata if they had improved confidence so share the value that they receive from governed data you know participate in the conversations about well what did it look like before and what's it going to look like in the future as we get more formal in how we govern the data and the metadata of our organization so in this webinar I talked about how governance applies equally to data and metadata I talked about the resolute effort and how that's necessary we talked about the governance of data and metadata and what that does to increase the value of the data and metadata I talked about the people who must be held accountable those metadata stewards are really important and then I talked about communicating that whole idea with the different stakeholders and with the different people that need to be communicated with in terms of the fact that the data and the metadata will not govern themselves and with that I want to turn it back to Shannon to see if we have any questions from today Bob thank you so much for another great presentation as always and to answer the most commonly asked questions just a reminder I will send a follow-up email by end of day Monday to everybody with links to the slides the recordings and the additional resources Bob mentioned there so diving in here to Bob and Danny you know what differences between what are the differences between non-invasive data governance adaptive and agile governance Danny I guess I'll take that I'm hoping you're going to take that one I'm very interested in hearing you can take on that as well but the terms adaptive data governance is not one that I'm real familiar with and I'm assuming that that means that it's adaptive to your organization and that as your organization changes it also can change with it the term agile data governance probably would be very similar to the definition of adaptive data governance in my book agile means that you know we don't we know we want to get things done quickly we want to do things in pieces you know non-invasive data governance first looks at the premise of we're already governing our data and we're already we're already stewarding our data but we're not doing it as formally as we need to and we can lead because it's informal it's leading to inefficiencies and ineffectiveness so if we can recognize where governance and stewardship is already taking place that's a good start in developing your data governance program so non-invasive data governance is basically based on that premise you know the other approaches of data to data governance that I am most familiar with are kind of the command and control approach which is now shall do this you know it doesn't matter how busy you are you must find time and it feels very threatening to the organization data governance sounds threatening to begin with and if we go with that command and control approach it's a lot different than saying hey you know what you're already governing the data we're going to help you to do it better and then the traditional approach is I liken it to the field of dreams or the movie field of dreams that if you build it they will come to a lot of organizations build governance programs and hope that the people of the organization gravitate towards those gravitate towards the program that you've defined so that's why I say if you build the program you hope the people are going to come to it I don't have a real good answer about adaptive governance and agile governance Danny can you help me out here well I'm not I just saw one of our attendees gave us gave us the clue to adaptive I guess that's a term from Gartner and it isn't the same as agile data governance but absolutely it's a it's a newer term to me and you know I think that that you know the non-invasive approach or the adaptive approach or adaptable approach or the agile approach I think it really speaks to the to the reality of two sides of the coin you can't let data governance get in the way of what it is that you're trying to do it's supposed to enhance that it's supposed to you know make as as Bob has said make things better and it also has to be ready to you know to pivot because what you have today will not be what you have tomorrow or the day after that the day after that so you know what I've seen in in terms of you know our customers and how they're approaching data governance especially as they look at taking that step to actually operationalizing it is is embedding the governance processes right along with the data management processes and the rest of those things right you know so so that when you're turning the ship everything turns together now is that an easy thing to do I think it comes back to to you know looking at what you're trying to achieve through governance the KPIs that you've associated with that and then looking at and making sure that governance isn't just looking at your your data landscape as it sits today but that you have great visibility into the roadmap of where you're going right so because that roadmap will allow you know just like everybody else has to prepare for you know some sort of significant change in in the database or something else like that so does data governance so you know if I can speak to experience with that with our customers it's really about making sure that you are in and all the folks that are responsible for data governance are aware of the entire you know pipeline of data in their organization as well as the roadmap for that pipeline so that they can be preparing and readying and understanding what's going to be different what's going to be the same what do I need to do different to react to this next new thing I think that was very well said Danny thank you let me say this about that okay well I think we have time for a couple more questions at least one more question in here so is data steward and metadata steward the same person for given data domain well it depends on what the domain is and so I use the word domain to mean subject area so subject areas of metadata may be different than subject areas of data so you might have customer and product and vendor and material and all of those things when it comes to your data can they be the same person well I think yes they can be the same person you know if somebody is defining that certain data around customer is important important enough to manage and having those same people having responsibility for putting good business definition to the data then for sure the data steward and the metadata steward can be the same person does it mean they are the same person not all the time you know the people that are producing the metadata may not be for example some of those front line people that are producing the data the people that are using the metadata well you know if it becomes a more formal that you have solid metadata for folks then you know potentially the users of the metadata may be the same people that are using the data so you know again it really depends on how you define domains but I say that at least part of the time yes the data stewards and the metadata stewards can be the same people yeah hey Bob and you know I I agree with you there Bob and it but I think that there's a key element there in terms of where that data steward comes from because you know there are different skill sets that are required to to be a data steward and a and a metadata steward especially in terms of how they're going to actually make that metadata stewardship and metadata governance a reality right so what I've seen in our customers is we have data stewards and data custodians and they work very closely together the data stewards really stewards the data and underneath the covers the data custodian while is steward is stewarding the data they're doing it from a metadata perspective and a more technical perspective so that's one approach that I've seen you know metadata stewardship metadata standards and metadata governance is something that you know and thank you Bob for for bringing this up because I've seen a lot of organizations do it through their data modeling practices especially if they formalize that practice where you can start to set metadata standards and specific requirements for a data model to be approved and to to you know move on through the life cycle and then leveraging you know review processes to make sure that's happened and I've seen people really increase the quality of their metadata by setting those rules up front because you know the data model is a great place to extend metadata that is you know naturally captured in a you know you know in a database catalog or somewhere else and you can print all that other context to it in that environment so a lot of folks doing that type of stewardship they probably didn't even know they were metadata stewards while they were doing it but they do now and they're probably going to ask for a raise but but you know it is a place where you can start to do that but you know and and I just like to say hallelujah Bob that you're bringing up metadata as an asset metadata quality and metadata governance because that's where it all starts the better you do that work the the better chance you have that the data that's sitting in those structures and being moved around your organization is good because it was designed to be good I agree well thank you both but I'm afraid that is all the time that we have for today but just to let you know I will get these questions over to Bob that didn't get answered or if you have more that you want to slip in here really quick I will get those over and I'll include the answers from those questions in the follow-up email which will go out by end of day Monday which will also include links to the slides and links to the recording as well as the other things requested and again thanks to Erwin and thanks Danny for sponsoring today's webinar and helping you to make all these happen thanks to all our attendees for being so engaged in everything we do we hope you all just have a great day and stay safe out there thanks guys thanks everybody thanks Bob thanks Shannon