 Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Officer at DataVersity. We'd like to thank you for joining this DataVersity webinar. Data Governance takes a village. So why is everyone hiding? Sponsored today by Elation. 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. For questions who will be collecting them by the Q&A in the bottom of your screen. And if you'd like to tweet, we encourage you to share highlights or questions via Twitter using hashtag DataVersity. And 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 change that to network with everyone. To access and open the Q&A or the chat panel, you will find those icons in the bottom of your screen for those features. 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 any additional information requested throughout the webinar. Now let me introduce you to our full House of Speakers today, Mary Williams, Kurt McAdams, Bob Siner and Susanna Barnes. Mary is the Associate Director of Enterprise Data Governance at Exact Sciences. Mary has been highly regarded as a thought leader in data governance and data management throughout her career. Kurt is the Senior Manager of Operational Data Governance at Exact Sciences. Kurt has many years of data experience from data modeling to building data governance teams. Bob is the President and Principal of KIK 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 Susanna is the Data Intelligence Program Lead Adolation as a data governance professional. She previously worked with Mary in data governance at American Family Insurance. And with that, I would give the floor to our team of speakers to get today's webinar started. Hello and welcome. Hi, Shannon. Hi, everybody. I am really happy to be here today. This is Bob Siner that is talking. Today we're going to do something that's just a little bit different than your run of the mill webinar on data governance. We're going to turn this into a little bit of a talk, not a talk show, into a game show. We're going to actually take a game show that most people know and we're going to use that to discover why data governance really takes a village and why everybody is hiding. So first thing I was going to do, I was going to hum a few bars from a well-known theme of one of the game shows. But then I realized that I'm in the United States and I don't know where you are with by the chat. You can see that people are coming from all over the world into this event. The theme shows, the theme songs might be a little bit different where you are. And certainly the village of data governance for diversity certainly covers the entire world. So I've never hosted a game show before. Let me move forward by introducing to you our illustrious panel of contestants. And I'd like you, each of you to say something real quickly about yourself to the audience today. So Mary, let's start with you. Hello, everybody. And great, great job, Bob. Look forward to you being the host of this. So something besides data governance to know about me, I'm a recreational musher. I've been to the editorat twice in Alaska and I've been a dog handler and I've also been a editor writer for the opening ceremony. Okay, very cool. Kurt, how about something about you? Thanks, Bob. And it's great to be here. I guess something different about me other than data is I do a lot of outdoor cooking and I do like local spots on news in Dayton, Ohio. Very good. Okay, Susanna, something about yourself. Yeah, thanks for having me today, Bob. So I guess something non-data related about me is that before I moved into the data space, I spent a decade working in regional theaters as a scenic artist and a stage set designer. Wow, very good. So we've got a really great group of folks to talk about how data governance is a village and about this idea of the fact that everybody is hiding and how do we bring them out from hiding. The game show that we're going to kind of mimic is that of the $10,000 pyramid or now it was $25,000, then $50,000, it might be up to $500,000 pyramid for all we know with the way inflation is today. So we're going to talk about these four categories and we're going to go through the contestants and we're going to talk about data governance and data catalog. We're going to talk about proving the value of your governance program to your organization and recognizing who those people are in the organization who really have to be behind data governance. We're going to talk about the maturity and the success of governance programs and cultural change and how all these things have to do with the fact that data governance truly takes a village and we want to bring people out from hiding. So the first thing I'm going to do is I'm going to go to Mary. Mary, can you pick a category for us to talk about today? So let's do the defining the need for data governance in a data catalog. Okay, very good. Well, I got a question for you. So if we are really defining the need for data governance and we are talking about data, the data governance data catalog. First things first, how do we get those people in the organization that are going to be stakeholders of governance and the data catalog to understand the need for the for data governance and for the data catalog and are these the same people are they different people. You know, how do we get those people on board? So, in my experience as a data governance practitioner and that and trying to get people to really understand those stakeholders, you know, the need for data governance. I've always come back to some very basic questions and that to kind of give the organization an idea of where they're at and so it's starting off with really four simple questions of, you know, what data is available. So you have stakeholders, do you have your analyst your scientists trying to understand what data your organization has. The second thing is, you know, are you trying to figure out if I have questions about the data because I've been able to find it. Who do I contact with questions and that that can be another piece of like, you know, are we struggling to, you know, stand up data governance or have an understanding of it. Or are we creating dashboards and different types of reports. And we may not be talking the same language even though it looks the same so we have, you know, maybe customer numbers and that on sales. But we're not really sure, you know, if the meeting is the same because the numbers don't match up so it's like, are we speaking the same language. And, you know, do we have those common definitions. And then it finally comes down to, you know, can I trust the data. And so within an organization, if your stakeholders are asking these questions are struggling. That's where you really need to take a step back and start getting an understanding of where your pain points is it around quality is an understanding business terms. And then starting to move forward with identifying really some of those individuals to be a part of this so called village and they may not even really recognize it so I try to start off with these basic things. And then try to move forward with more of a, an understanding of where we need to focus. But I'd be real curious because there's other individuals Susanna and Kurt also participating in our game show. What thoughts do they have around getting people to understand the need for data governance and where they started. Kurt. Well, it's really easy when you start talking about data and data governance to get into this, you know, data speak type stuff. And what I find is when I try to talk to people that are dealing with the data for that for the business operations that are going on. They gloss over really quickly when that happens. So I think one of the main ways to get people interested and involved is you've got to learn the impacts to them and what it means to them not how, how I can talk about how much I know about data. So I think really finding their pain points that way and working with them on direct ways that governance activities can help them. It goes much farther than showing that you can write a dissertation on data governance. So Kurt when you talk about what it means to them do you include them in the village. Do you talk about it taking a village. Are they some of the people that are hiding in the village right now those people that need to be able to describe what it means to them and and so that we can address those things. Much so because typically the data governance teams a small group that that I look at really Morris facilitators for the activities to get done. It's really that business community that's using data that is the village. You know, most of the population of the village. And without them, it's really going to be tough to get any true governance done. Yeah, Kurt, I would agree with that completely to I think it's, it's really important to appeal to their, you know, their nature as kind of selfish, you know, everybody's a little bit selfish so you're not going to convince anybody to jump on board of your governance program just because it's the right thing to do you really have to speak to them and help them understand how it delivers actual business value to their teams and how governance will make make what they're trying to do better and more successful. So how can we better get those people that are in the village that we need to understand what, so they understand what's in it for them, and that they're back how we get them to understand what's in it for them. Are there tricks and techniques for doing that. I think it's really kind of when you think of, again, like going back to some of these questions of getting them involved it's like, if they've been dealing with like poor data quality sharing with them or understanding what some of their challenges they have around data quality and how either a, you know, data governance can help them out or even just a catalog by being able to identify those sources. And so approaching those individuals to understand, I think is even curtain maybe Susanna said their pain points. And then, how can you offer them some additional tricks maybe it's even matching them up with other individuals who are maybe experiencing a similar challenge or maybe even with that same data set, and coming to some common ground of how you might address, you know, like, you know, poor data quality, or even defining some business terms they may not even realize that somebody else is experiencing that same situation. Well, and I'm really glad that we had a chance in the in topic number one around the governance and around the catalog itself. I'd also like to address the catalog aspect of it as well, and make certain that we're that people understand what in it for them in the as well because without that I think without including them in the village. It's going to feel like they're hiding, and we're going to be shooting at requirements that are are kind of in the dark. So, oops. Susanna, I'm going to go to you to pick the next category if you would. Hey, why don't we pick prove your value. Good idea. Thank you very much for that. You know what, but I'm going to go back to Mary because I want to I want to kind of elaborate on this idea of the right champion, who is the person in the organization that we need to prove the value to. I know Kurt to talk about we need to prove the value to the people of the organization, hit them where they have their pain points all the things that all of you said but how do we go about figuring out who we need to prove the value to how did you go about doing that. So, in some of my programs and finding that champion and, and working with them. It's, again, understanding, you know, some of the pain points. And it's finding out like, is there someone that has influence or credibility that you can partner with. I think through some of my experience when it's been, you know, hey, maybe data governance can help out over here or actually trying to find that champion one of the things that people gravitate to sometimes is let's go for this big project you know because they're going to have visibility in that. And I find at times that that's not really the right approach. It's to look for maybe an area that is struggling. Maybe it's with terms maybe it's with quality maybe it's knowing what data is available. And partnering with them understanding what their challenges are, and really evaluating what is like that individual do they have influence across the organization. Maybe they report on something that's pretty critical to like the financials or innovation for the organization they have some major capability that needed. And it's starting to kind of view not only the individual and are they, you know, viewed as having influence are they credible, but also, you know, what are they supporting or working on that could add some kind of light or highlight some of the work that they're doing, but then how data governance and that can help out on it. So it's, it's not always going to this term of like you know the shiny object or going to that big project, but it's taking the time to look for them again in the champion and kind of the sponsor and that they don't always have to be the same. It could be two different individuals you could have someone who's a champion of a catalog because maybe they're an analyst and they do a lot of reporting, and that and a lot of different dashboards and reports they generate. And maybe there's somebody else who's doing a lot of innovative work that's getting visibility at a senior level that you want to partner with, and can see how you can help them kind of do their work kind of faster and, you know, deliver some of that insights to the organization. Susanna, you and I definitely work together at American Family and that you know what thoughts do you have around like, you know, proving the value and building the case. And I think your point about different types of champions and different types of sponsors is really important Mary because what I always found was that there are data champions that already exist on almost every team. And if you can find those people, you know they're already creating their own documentation they're defining things they're making sure people have a single place on their team level to go for information. If you can find those people and you can help them understand that you're giving them the tools through a catalog to work smarter and faster, and allow them to share that authoritative information they've aggregated in a, you know, in a place where everybody can take advantage of it. They will kind of just gravitate towards it themselves and that they sort of become those natural catalog champions. What's really important is that, you know, from the, you know, I work for the software company now I didn't always but now we talk about finding a catalog champion but one of the key responsibilities of that catalog champion is to breed other champions internally within an organization. So you need to have someone who can kind of inspire and motivate people and get excited about the catalog program that you're trying to build. And I think that that is very much aligned with what I talk a lot about which is the noninvasive approach to governance which is that let's recognize people so if you see people that have energy, and have interest in, in making certain that this is going to be successful, let's leverage those people let's take advantage, not not in a bad way but let's take advantage in a positive way of these people's energy to get us really where we need to be. And so, you know, we talk about anything Mary you talked about the use cases and not picking a specific project. How can you put your arms around something that you can then prove your value and build your case for your governance program and for your catalog. So it's sometimes it's, you know, in building that case it, it's picking that kind of something that's happening in the organization maybe there's a struggle that's taking place with some type of reporting. Maybe there's a lot of rework, where it's not a formal project it's more of that, you know, maintenance, ongoing activities that might be taking place that you can focus on, and help that because if there's been like this, I'll just say like a production problem that keeps reoccurring over and over, and every month people are spending time on it. If between either a governance program or actually even a catalog again because the catalog can help identify possibly those right sources. It can also help with understanding some of the truth or how you're defining things. It can lend itself to removing kind of that repeat over and over of maybe having to fix the same issue. And by doing that, you start getting that speed to delivery, and you're able your analyst, and that are able to focus on other things instead of maybe those reoccurring problems. So demonstrating the value sometimes is productivity is basically what I've stated there it's being able to, you know, maybe not keep doing the same thing over and over again. Or maybe they've been able to reduce some of the wrangling because they know what data sources to use. They might have had two data sources look very similar, and maybe they were using the wrong one. So, by spending time documenting it, putting things in the catalog and knowing what source to use, and that reducing that data wrangling actually can improve the employee's productivity. It can help the organization innovate, and it can bring about maybe some additional business capabilities that you didn't realize existed today. So when you're talking about, you know, people. You're talking about really a lot of behavioral change activities right I mean you're talking about getting people to do the right thing getting them to go to the right source. It may not be a quote unquote data quality issue it could be a behavioral issue is that a is that a potential way of being able to demonstrate value to your organization is being able to correct those behaviors that are not the way that they need to be right so if you think of governance governance as a whole is about influence so you don't have control over everything. It's being able to influence and the second piece of it then is governance is that change management. So you're again influencing and trying to drive different behaviors within the organization and getting that adoption or those champions to start wanting to leverage a catalog or seeing the value in maybe it is entering notes telling somebody that use this source but use caution if you're going to use a particular data attribute. You know, it's, it's getting them to think about one, taking the time to enter things into a catalog is going to be worth their time, or maybe one of their coworkers time, and it's going to, you know, save in the long run, it does not feel like it upfront. And so it is that change in behavior is one governance isn't always iron fist and that that it's adaptable to the various levels of governance depending on if it's a regulatory that needs to be very strict and tight and have a lot of rigor to that that is maybe more for data scientist and doing some what if scenarios that's a little bit looser. So starting to then work them through that by adopting or embracing, you know, some of the guidance and guidelines that a governance team or program can offer, as well as marrying that up with some of the things that can be captured in a catalog from sharing notes of, you know, do's and don'ts, or even some best practices, and that can help them and also drive that value overall to the organization because they start seeing that maybe it's taking them less time to do things and they can spend time on, you know, maybe things that are a lot more innovative, maybe doing some new development learning some new things instead of, you know, doing a lot of the same thing over and over again. So I think, you know, definitely that change management aspect is very important because you don't know about some of the inefficiencies, because sometimes you just like this is the way we've always done it. So it requires thinking a little bit differently about it changes never easy, you know, it's like to, you know, change how you do something it's not always easy. So you got to keep working at it. Okay, I love that answer and we're going to give 50 points to Gryffindor for that one know we're married. That was a really great answer I really like the idea of the influence in the credibility. I mean, and I think really think that's a key. And I don't know if we could extend this webinar for another hour or more, you know we could spend a lot of time on some of these topics, but we really agree on the next topic. So this time I'm going to have Kurt select a category for us to talk about. I'm going to choose maturity and success Bob. That's a great one to pick very good. And again, we're going to go back to Mary so when we recognize that resources are an issue that they're not growing on trees that people who are not only passionate about this subject but also really want to do the right thing. So there's challenges on bringing these types of people's people on board, not only from a data governance perspective, but from a data catalog perspective so what are some of the challenges that you faced when you needed to fill out a data governance office or a data governance team, or the same thing with the data catalog. How did you go about finding resources that would fit what you're trying to do. So finding resources to, you know, be part of either data governance program or even being involved with the data catalog. It's a challenge and it's a challenge because, you know, you can go to school and, you know, get a four year degree and you can get it in business you can get it in it your computer science marketing, you know, a very diverse group of diplomas and that and degrees you can get. But when it comes to something like data governance or data management or even the catalog. They don't really have curriculums at the universities or even the technical schools around that education so as I've tried to bring in people. And that to the team either, you know, from the various organizations that I've been a part of. It's usually trying to select people that have a passion around data, are they curious. Are they willing to learn about, you know, the topic by, you know, maybe attending webinars like on dataversity here, or are they willing to, you know, pick up a couple of books here I'll give you a plug not invasive data governance. Are they willing to go to some conferences and step out of their comfort zone to say I got a degree in, let's say marketing, but I'm really passionate about data. And I want to be part of this team but I'm going to have to kind of roll up my sleeves and do some of my, you know, own learning. I would actually, you know, put together a kind of a high level framework for how I would onboard those individuals so I would create somewhat of a curriculum of, you know, here's some webinars that I know or here's some authors that I know or here's some courses that are offered that you could, you know, take either as a self study, or, you know, maybe enroll in a, you know, a six or eight week type session and that. The other way. So it's, it's looking at that individuals, kind of their passion and do they have kind of that data mindset, building that curriculum. The other way of really bringing on that talent and trying to find them is looking internally, sometimes if an individual knows the organization that they're a member of, but they're in another department. But they seem like they could be a good fit. You know, I've been successful in bringing people from a totally different job category, and bringing them into the program and again taking some of these same same steps and working through it. So are these, are these data people to begin with, or are these people that are, or are they, they have a data mindset how do you have a data mindset. Most of them have not been data people so good clarification. So they have a data mindset, they may be asking questions around, you know, can I, let's take an example of someone who had been in sales, but had not had any formal training around data. They actually took some of their goals that they had from a sales perspective, put it in a spreadsheet, and they were trying to track out how they were going to be successful. Now that individual was interested in a position on a team, and that they didn't really think about the data skills that they were using or that mindset of how it could translate into being a member of a data governance team or actually even using a catalog, until sitting down and talking to them and pointing out that, you know, you would be a really good data analyst, but you could also, you know, be a part of a governance team of, you know, helping identify data sources, or even teaching people from a literacy, literacy perspective of how they could use the data. So, so those individuals, when I say that they've got a data mindset, it's that they've been using data, and that to do their current job, but not in a role of like a data analyst or a data analyst. Okay, so a question that I have for Susanna because I know there's been some work in that and she's talked about some things around the same thing around educating and training people. Can you share some of the ideas or things you were thinking about Susanna. Sure. Thanks Mary. I definitely would like to give you some hope there's light on the horizon for hope governance and higher education. Because there's numerous programs colleges and universities that that are now starting to add specific, they may not be like a data governance degree but within their other data analytics or their business programs. So they're adding training programs and courses specific to data governance to data quality to, to all of these data management practices and disciplines, and then these same universities are also once they've seen some success here with these undergraduate and graduate level courses. They're also beginning to look at micro credentialing programs so people who are in the workforce who have that data mindset, but maybe not that data background. They can actually go to these schools and they can take smaller courses like you're talking about and get these micro credentials that will teach them these sort of targeted skills for for what they'd like to do next really within the workforce. Elation is working with some of these programs by offering our catalog to them to use in the classroom as part of that training program. Whether they're using our our program or not. There are lots of schools that are starting to add this and in fact we, we did a little bit of analysis on kind of LinkedIn job postings and you can kind of see how these entry level job listings for for people that need to work in governance or work in data catalog or metadata management, they're starting to creep up as these programs are getting more mature they need people at entry levels to come in so having seen these this growth in the college area is is really promising for kind of getting that workforce built up and Susan and I've seen some of the same thing I mean with some of the local schools here in Pittsburgh where I'm located. They have our, they're starting to focus more and more on data management skills so there is a lot of information out there. Again, if we had more time I'd love to go into the detail as to how can we get. How can we take this education and turn it in to ways that were maturing the program, but we've got another category that we need to select and Mary I would go back to you to select it. I wonder which one it is. Is it cultural change by chance. I was hoping you were going to pick that one. What would you have done if I pick something else. I think we would have punted at that point but okay. So when we talk about culture, I think a lot of the things that we've talked about have really come into kind of building that culture. And when we talk about a village when we consider our organization to be a village that's probably made up of villages as well, but we're looking for overall kind of cultural change of the organization. So, I know Mary that you've been a couple different places I know Kurt you've been a couple of different places I think Susanna you have. I'll go to Mary first are there any specific types of company cultures that are going to be more receptive to the two cultural change than others, and what are some of the traits of those and what's been successful for you. So, I guess there's two kind of camps of one the company cultures that are kind of receptive to, you know, this change or cultural change that needs to take place and one is an organization that maybe has been into some, I'll say regulatory issues or compliance issues that you know they need to embrace this because they've been penalized and they need to really start putting into place some good ground rules and practice around managing and governing their data. Those probably, you know, they're those situations aren't fun but those kind of organizations exist. And so you'll find in there that they are a little bit open to adopting to this because they need to change. And that's one scenario that may not always be fun, but it's out there. The second kind of company culture that is receptive to this change as well. They are those organizations that want to continue to innovate and grow, and that are in an industry that is seeing a lot of growth and you got to have, you know what's kind of that latest thing what's the competitive edge. So you'll find those organizations that maybe they don't have a lot of the 50 year 100 year old background but maybe they're more than 10 to 15 year realm of where they've been around that are a little bit more open and flexible to kind of changing their and adopting, you know, the various types of governance in place, getting people to be more engaged about using a catalog for the simple reason they may have a workforce or staff members that are very much into kind of some of the social media crowd sourcing that so that the way they share things kind of outside of work is through different mediums so that when they're at work and using something like a catalog it's very natural and so those organizations that are kind of fairly young. I have found to be more, you know, willing to adapt, but then on the other hand, there's been some that when there's some significant growth or they want to really pivot to where they're going, that they've been willing to adopt and change sometimes the data analyst and even some of their leaders are tired of the way things have been going in there, they really want to see some change. And so it's, it's that willingness to kind of open up and maybe take a little bit of a risk and that. So, you know, it's, you have to kind of assess where is that organization where are they trying to go. And then how can you move forward. Are there some techniques and things like that I mean I love this analogy because everybody or most people remember the old libraries and the books and the, and the card catalog and those types of things. I mean, are there tricks, things that we can use to get the culture to change just by people recognizing that this is not all new stuff this is very similar to the way things have been. It's just a step better. Yeah, so one of the things, as we've been looking at like, you know, data catalogs are talking about it. When introducing like a data catalog to an organization. I've had questions over and over again of what is this catalog. Why is this important. How is it going to help me, and the best way that I found to describe it it was like to take people back to something they know kind of like what you mentioned. And it's to do the library book type scenario. And so it's framing it up with the analogy of, you know, there's a public library. There's a library in your, if you have kids at their, you know, school, or there's the library of Congress. And so the idea is that, you know, the data catalog is very much a library and you can have a library, like in a grade school that probably only has maybe a few books, compared to a public library that could have thousands of books to then the library of Congress which can have thousands and thousands and hundreds of thousands of books. And so the idea is to get them to think about, I'm going to catalog my data. And I'm going to think about this in the same way as I do a library that if I partake in this, I can document what data we've got. And I know where it's at. I know who to contact. And I know if I can trust it, and I can actually kind of maybe be an author or even a blogger if you want to look at it that way. And I can share some of my knowledge with some of my peers by creating articles and that so, you know, as you look through, you know, the overall analogy it's like, you're going to catalog your data sources. You're going to put some titles to it. You're going to write kind of an overview if you're bringing in something new about, you know, maybe it's, you know, customers or maybe it's around some of your regulations that you need to deal with. And one of the other points is like, if you think of the old card catalog, or even in a book, you actually knew like where something was located, what floor, what shelf, where specifically to go and look. And so with, you know, a data catalog, and that's the same thing, things are indexed, you know, you know, where to go and look for something so that it's easy to look up a term, you know where it's used, you know, who actually helped write it. And that, and there's also, you know, very much like on Amazon or other websites, people can put reviews so you can say, you know, this has been, you know, very helpful and give it a five star rating or four star rating or whatever. And then also it's letting people know that, you know, there's a glossary. So how did we define something. Again, in a book you can look to the glossary in a catalog, there's a glossary you can look it up. So in defining and explaining the data catalog in the library book analogy, it's helped people, at least that I've worked with, and organizations to understand that this isn't such a new concept, but it's a way to help them think about their data. And there's also within the catalog, you know, data consumers, as well as governance team members can put in their best practices to help people understand, not only more about the data, but maybe about even how to use the catalog better, because again, you know, that crowdsource and get others to participate in it. And, you know, it's all about getting people to understand the value and to use things like this to help them to help to build a better culture, help to build a better village, we only have a few minutes before I'm going to kind of turn it over to Susanna for a couple minutes here and then Q&A at the end. But just want to hear some last words, I'm going to go to Kurt first. We talk about building a village. We talk about people hiding. Tell us what that means to you and tell us how the catalog and governance is, you know, how building a village is going to help us and try to sum it up for us. So I don't know that people are actually hiding, they're just really busy, and they have their things to do. And I think it behooves us in governance to adapt what we're doing to speak to them, to get them involved in things that show value quickly, not low value, you hit high value things as quickly as you can, and you build up confidence and involvement, and you use the village itself to grow the village to be bigger by bringing in other people in other areas of the business. Once you've shown that it's worth their time doing it. That's a great answer. We'll give you a bunch of points for that one. Mary, what do you think about the village and are people hiding? I think they're hiding because they're really not thinking about that. They're actually maybe playing the role of a steward or a data custodian. They're very much involved in their day to day activities. So they're not thinking about, you know, possibly that type of a role, even though they're maybe already playing it. And so in bringing them out, I think from, you know, maybe some of that hiding is to bring awareness to some of the things they're doing, and maybe even like highlighting that there is a data community without even maybe saying that, you know, these are stewards or whatever the data, but that there's a data community and recognizing what they're doing, maybe through, you know, badges, awards, maybe even doing, you know, lunch and learns and sharing. Maybe some best practices or how they've gained things, you know, in their day to day job, how they've gained some productivity. I think those kind of things starts highlighting that those individuals are already out there. Maybe they're hiding. Maybe it's just they aren't even aware that, hey, I'm really playing this role and I can play a bigger role and help the organization move forward. So in other words, what both of you are saying is that they're really, and it's very non invasive and they're hiding in plain sight. So these are people they're hiding, they're busy as Kurt said, they're hiding but they're there, they're there they're not necessarily hiding we just need to recognize them we need to formalize them. I'm going to go last to Susanna what are your thoughts about the village and our people hiding, and then we'll we'll take it from there. I'm glad that Mary mentioned the data community because it in a lot of ways your data community is, it's really it's made up with multiple villages. So these people are all they're just doing their jobs and they're there's separate areas of the business. But they do have this shared resource the data is this common resource that has to be managed and shared across across all of these little mini villages right so your data governance policies your data catalog. So that provides you with the infrastructure to manage this common resource that for the benefit of everybody involved and I think that that's where governments really provides the most value because it helps everybody get the most out of the data that belongs to the organization. And I was gonna say it was a very close contest leading into the last question, but you all answered it very well Mary I'm going to give you the, give you the victory with Susanna and Kurt being a very close second. I'm going to turn it back over to you Susanna. Thanks Bob I'm going to complete conclude here with just an overview of elation and then we'll jump back over to Shannon for some questions and answers so relations was started in 2012 so just under 10 years ago. It's time we've grown to over 400 customers right now actually as a, as of today over 800 employees. And I, but I think the most impressive stat here really is that 25%, a full quarter of the fortune 100 companies are relation customers and you know why is that important because it's really a point that differentiates elation from a number of our competitors. There's a lot of catalog catalogs out there in the marketplace it's a very crowded landscape. There are some that are very user friendly to drive rapid adoption but they may not scale well for enterprise employment, or they may not be able to address the complex enterprise scale security and regulatory requirements that exist. Other catalogs may be really well suited for those complex environments, but they don't have the usability that you need for that data community really in gender that buy in for your business partners. An elation really stands alone in its ability to meet both of those needs we can scale to enterprise complexity, and we also provide a very approachable and user friendly experience. And you can kind of see that and that industry recognition there across number, a number of different panelists firms. So, next slide Bob. Our customers have been using elation for data governance from the start, even before we really started marketing ourselves as a data governance application. We were seeing that the catalog was an integral part of the active data governance programs that they were building. So elation decided to launch the data governance app. It was launched in the second half of 2021 and right now we have a number of large customers that are adding the governance app on a regular basis so we currently have over 70 governance app customers. Next slide Bob. But you know as I mentioned, many of our customers were already using elation for active data governance. So we started marketing to elation for governance of just over two years ago. And our headline news then was that a third of our customers were already using elation for governance, despite the fact that as a company we'd never really spoken about elation as a governance tool. And the reason for that is that our customers knew that a critical outcome of governance was guiding users to the right data at the right time. And that meant the data was easily found, it was easily understood, and it was appropriate for their use users could easily see if the data was fully compliant and if it was a good quality. Elation really allowed companies and governance teams to achieve these goals through the stewardship dashboard where curation tasks can be prioritized and focused. The agile approval processes that provide a transparency and powerful workflows, and the trust flags that allow users to quickly see critical information about the status of the data that they're using. Next slide Bob. So, in the span of two years elation developed and introduced our data governance app. And this app includes a policy center for applying and enforcing data policies and defining business policies and a centralized location. And this centralized management of policies is really critical for these complex enterprise environments. We've got change management workflows. And it's dashboards for monitoring curation progress across different systems. And we also have the stewardship workbench. And, you know, I really want to focus a little bit on the stewardship workbench here because it's especially critical for data governance success, your business subject matter experts, you know we heard about this when we were talking earlier. They're often your natural day stewards, but they aren't paid to curate data, they're paid to make data driven decisions, and it can be hard to get them to find the time to complete stewardship tasks. So with our stewardship workbench we're really trying to allow them to curate data at scale by automating their tasks, implementing both curation in a simple, simple interface. And what this really does is it makes stewardship easy, unless I'm an additional responsibility that's layered on to their many other responsibilities. Next slide. So elation believes, you know, at its core that true success comes from the combination of data intelligence with human brilliance. And for this to be true collaboration has to always be a central goal. So we really strive to create a platform that lends itself to organic and organic adoption model. You know, that's really encouraging broad community of participation throughout the organization so not just your experts on data but your people who are reading reports and you are seeing, you know, seeing this things in presentations are seeing dashboards and presentations and they need to understand what these things that they're being talked to about mean so they need to raise the data literacy of your entire organization. So we really look to a human centered design approach. We really want people to easily be able to adapt, adapt the catalog where ease of use features like search and query auto complete the kinds of things that you really expect from any kind of an interface that you're working with. Next slide Bob. And so collaboration means there's a focused effort on the crowdsourcing of siloed information and knowledge across the organization into the centralized platform. We try to automate expert identification of ideal stewards through behavioral analysis and machine learning, and we allow the creation of not just you know data dictionaries but wiki articles to enable this distributed enriched knowledge environment for people to take advantage of. Next slide Bob. Users can communicate with one another within the platform using conversations integrated with catalog pages that keep them connected to people and information they care about. The conversations are fully searchable so knowledge isn't lost in email and instant messages or somebody leaves the company you don't lose that that knowledge. And these conversations in a sense become a living FAQ repository so that users can also subscribe to articles and data objects to stay informed with changes to the information that they need. These deeply ingrained collaborative features really help you build the data community that truly reflects the needs of your, your particular users. With that, we'll go back to Shannon for the Q&A session. Thank you so much and thanks to all of our speakers for today has been a very entertaining and educational conversation I just love it there's a lot of questions coming in I'm going to try and get as many as possible. If I don't get have time to get to your question I will get them over to Elation to see what we can do to get some follow up for you. This is one of the most commonly asked questions just a reminder I will send a follow up email by end of day Thursday for this webinar with links to slides and links to the recording along with anything else requested. So diving in here now, you didn't touch on this at the end here, you know, and to everybody, you know, there's this is the most popular question, you know, for second most published say how do you help them engage when their plates are overflowing already. I'll jump into that first and so their plates are overflowing but you got to recognize why their plates are overflowing and all the things that they're doing that I wouldn't say they're doing data governance I would say they're governing their data but they're doing it either very formally or very informally or somewhere in between. So, if you can recognize that the things that they're doing. I'm going to go back to what Mary said earlier about the percentage of the time that people are spending wrangling the data. Certainly we want to decrease that so people can become more productive, and then have time to be able to spend on different things, but recognize that a lot of the work that people are presently doing are either because they're natural and just governing the data, or they're doing them because the data is ungoverned and they have to do them. So, everybody is busy everybody is a day job. So, you got to recognize that and if we try to hand them a lot more. They're going to rebel they're going to push back, and that is really one of the core tenants of need I say the non invasive approach is recognize that people are busy but help them to build it into what they're doing. Everybody's busy. I'd be curious as to what Mary thinks about that. I think, you know, what I've experienced is, yes, people are busy. I think it's helping them recognize it is like those people that kind of naturally gravitate that are kind of those custodians of the data even though they may not really realize it and like playing that role. It's understanding what they're doing and then how you can help them without making it feel like you've just added to their plate, but how you can really remove some things for their from their plate or actually again like, how can you share some practices or maybe there's some efficiencies that are available that they don't even know that can spread some of that maybe load or bird. So, I know everybody's busy, but there's a way I think to help them see that there's things out there to help them and that being a steward or even being part of a governance program is kind of part of your natural job that you're doing. And it's how can you make it easy and have them embrace it rather than run away from it so a little bit of your non invasive governance Bob. Maybe they'll stop hiding. Yeah, maybe they'll stop hiding. All right. All right, I love it so I'm finding the phrase quote unquote data governance means different things to different stakeholders can you address how to pull at these stakeholders into a common vision. I'll take that one first to if you'd like. First of all that you're right there's there's a lot of different definitions for data governance so coming up with a definition that makes everybody happy is not very easy to do. But it's not orchestrating and harmonizing and all these things that people talk about for the data it's not just people process and technology. And all comes down to making certain that there are guidelines and standards and that we're following the rules, and that we're doing the things that we need to do. So when I say data governance is the execution and enforcement of authority. What I'm saying is, whatever that authority is to improve the definition of the data to improve the production to improve the usage of the data, whenever that authority is, we need to be able to execute it. It doesn't matter if it's through harmonization or however you plan to pull your village together. So data governance is scary to a lot of people. And even though we say that I say it's execution and enforcement of authority. I say we can do that in such a manner of just kind of formalizing accountability, where it exists already. You know, we can address different stakeholders but I would suggest that we come up with a single definition of governance that's acceptable to your organization, and then just kind of pull everything towards that because if we have many definitions. There's going to be ongoing confusion. No, I think I would agree with Bob on that. There's a lot of definitions around what is governance, what do you mean. And I think the one thing I want to point out, because early in my career on some of this, I kept like going to different books trying to figure out like, you know, what is governance or what should it be. And then, over time realized it's what governance should be for your organization what does it mean, like Bob said there's some guidelines and standards, but I think it's not worrying about, you know, what's the definition you may read on a website or from a book, not picking on Bob's book but just overall it's not trying to adopt something that may not work. Instead it's listening to your organization and what would governance mean to them and what are those, you know, guard rails that come up. One other thing on top of that is, when you think of governance there's always this question of how do you demonstrate value or how do you move people, you know, to understand it or participate in it. And one thing is really being able to understand from maybe some of your super users and maybe your junior members, how much time are they spending on data wrangling trying to find the right data source getting access to that data source. Understanding, you know, the time that's being spent on that, taking that and then looking at, you know, what are the hourly rates of those individuals and getting an idea of, you know, it's a certain dollar amount certain number of hours being spent that if you can take those numbers and show by doing a formal governance program, maybe having a catalog, and some other capabilities that you can actually save time reduce costs by, you know, adopting some of this so it's bringing in, you know, not only with the organization how they define governance, but how you can actually explain that value is being able to capture maybe some from some of your project or those experienced users. How much time are they spent trying to phone a friend, find data, maybe not the right data maybe not the right quality to answer business questions. And if you looked at that on an annual basis or even over a two or three year period, you could see there'd be some cost savings. If you were willing to adopt a formal program and a catalog to help. Mary, I would. Sorry, I would just jump in there to like it. You've got the time that they're saving. Yep. How much more productive is that making them right more focused are they now able to be on on what should be their real job, which is actually using the data to find insight. Right, instead of finding it. And all I was going to add is it's reducing that wrangling time that wrangling time could be phoning a friend it could be doing the discovery it could be what they're what you're really hoping to do is build up the percentage of the time they're spending where they're knowledgeable where they're skilled. Nobody wants to go around wrangling if we can get them to do most of what they're paid for and spend their time doing that they're going to be a lot of happy. You know, they get to do what they were hired to do what they like to do. And they probably feel like they've accomplished something instead of constantly trying to find, you know, the right data set or whatever. Thank you all again so much. I'm afraid that's all the time that we have for questions and for the webinar. There's so many great questions that again I'll get any questions that have been left unanswered over to elation. Thank you everybody for speaking today and thanks to all of our attendees for being so engaged in everything we do really appreciate it. Again, just a reminder I will send a follow up email by end of day Monday with links to this or excuse me end of link to the slides at recording as well. So thanks everybody. I hope you all have a great day. Thank you. Thank you.