 Oh. Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Officer of Data Diversity. We'd like to thank you for joining the current installment of the monthly Data Diversity Webinar Series, Real World Data Governance with Bob Siner. Today Bob will discuss data catalogs are the answer. What is the question? It's sponsored today by Alation. Just a couple of points to get us started due to the large number of people that attend these sessions. You will be muted during the webinar. If you'd like to chat with us or with each other, we certainly encourage you to do so. And just to note Zoom defaults the chat to send you just the panelists, but you may absolutely switch that to network with everyone. For questions we will be collecting via the Q&A panel. And to find the chat and the Q&A panels, you may click those icons in the bottom middle of your screen to activate those features. And as always, we will send a follow-up email within two business days containing links to the slides, the recording of the session and any additional information requested throughout the webinar. Now let me turn it over to Jason for a brief word from our sponsor Alation. Jason, hello and welcome. Hello Shannon, thank you very much. Hello everyone. Jason Lim here from Alation joining you from Redwood Shores Bay Area, California. Very glad to be sponsoring and talking about Alation and joining Bob Siner as he's the expert on data governance. And that's where we like to play and add value. So let's jump straight in. The question that was posed, well, the question on Jeopardy! to start question was data catalogs are the answer. So what is the question? And Alation, although it's a data catalog, we really call ourselves a data intelligence platform. So that poses the question, what is then data intelligence? And we'll jump into a few examples of how Alation does that. Okay. But first of all, let's answer that question. So really, we believe data intelligence is an organization's ability to deliver the right data to the right person at the right time, the right purpose in the right medium and context. So you've heard that probably many times in many different ways, different new flavors. But really what this delivers is, and gives us as a data intelligence system that learns and manages the who, the what, the when, the where, the why, and the how of data. So I often like to call this giving you context about the data. It gives you intelligence, it gives you context to make better decisions about it. And that all leads to being able to make better informed governed decisions as well. So when I say data intelligence platform, what does that really mean? And how does it become successful? We believe that Alation and data intelligence platform to be successful has to connect to everything. And it needs to be engaged and adopted by everyone. So we don't want to be a simply a solution that is only used by data X people, like the data scientists or data analysts or data governance or the stewards or data ops people. It's exclusive to the broader community of everyone that can use and get value out of data, which is practically everyone right now in an organization, including the business users and functional departments like marketing where I sit and product marketing, or sales or operations. So everyone should be able to get context and intelligence about data to make better informed decisions. And, you know, we all know in this community that governance is critically important with different rules and regulations happening but it's not just about the rules and regulations of compliance. It's also about making good choices with good quality data. So with that I just want to give a quick shout out to a Riley report that we helped sponsor and produce last year called implementing a modern data catalog to power data intelligence, and make trustworthy data organization. I helped co-author it with Fadi Mali. And really this report dives into ideas about the different types of data catalogs out there, the different flavors, different styles, how to implement a data system, how to think about the solutions, how to think about the rollout strategy, how to make it successful because it's not that simple and it's not easy because it's not just about technology or process it's also about behavioral change and a mindset shift for many people that have never used a data catalog before and are just trying to get started and that always takes longer than expected. So this report dives deeply into all the practicalities of what is the data catalog to different types of data catalogs to how to get started and get rolling so again please check it out elation.com on the resources page. With that quick plug. Let's go back to the premise of what I talked about, which is being able to for a data intelligence platform to be successful it needs to connect to everything. So elation has universal connectivity to all the different old cloud and on-prem data sources and different types and categories of data sources and types. And we call this like a wide breadth and depth of connectivity, not just the types of things we can connect to, but also how deep we can connect and extract information from each type of source. And I'll talk a bit about that soon. But just to talk about the breadth, you can see on this slide here we are able to catalog and index spreadsheets like Excel and Google Sheets to graph exploration tools, different applications to data tools, ELT, ETL tools, data prep tools, data observability and quality, access rights, we allow them to connect to us so we can provision access to different data, PII classification, databases, data lakes, data warehouses, and really that's the bread and butter of where elation started in the relational database space. But the point of this is to show that we can connect to a lot of different types of things. And when I say depth, really what we're saying is we can do the metadata extraction, but we can also extract the query logs and ingest them and process them and turn those query logs into intelligent things about who the top users are, what how popular data is, when data was last used, and all those types of intelligent things that we started at the top of the hour like the who, what, where, why, how, etc. On the right of the screen, you can see that the connectivity is able to be used by different types of people. So the data analysts, the business users, the business analysts, the government's offices, the data stewards. As a platform, it's kind of inclusive to a wide community of people. Now here's some screenshots of how we do that we can augment the catalog with best of breed metadata. We connect to different things like data quality data observability tools. So you can get context, and where we don't play the best where we don't deliver data quality or data observability, we can work with other partners that gives you choice to plug that context and data quality into the catalog. And we do that by a variety of open API frameworks for seamless integration so it looks like it's part of the catalog but really some of those external information is coming from third party providers and our partners. So here's a concept of elation anywhere where elation is a catalog, but we know and we recognize that not everyone lives or uses the catalog every day. So we actually push that context and extended out out of elation into third party tools like Slack like Microsoft Teams like Tableau, like probably Chrome and even your email so you can get information at your fingertips, rather than having to go back to the catalog. And for example, you'll see some descriptions here about what this field name means and that comes from elation, but it's living within the Tableau dashboard. And another example of Slack, you can, you know, to make a slack action and call a database, or a query from elation into Slack and send it and collaborate with others inside your organization. So here's a little bit about how it works with different personas. I said it's inclusive of everyone. So we do of course work and serve the data analyst and data science community. So here's an example of our compose SQL query editor, but it's not just any query. So it actually connects directly to the catalog so you can get that rich context from the catalog and answer questions like what data can I use in my query suggests me what this is. But also what does this mean what the columns mean, because you may have multiple columns name the same thing but without the context from the catalog, you don't know which is which. So here it can even give you trust check signals that say you know this is related to PII this is related to GDPR at the time of use at the time you're writing the query so we can guide you to good queries it can guide you towards writing better compliant queries and away from the bad non compliant queries that you might get in trouble for later down the line. So here's an example of how we work with data engineers and data ops. Of course we have a lineage graph on the left, and you can answer questions like where does come from and draw down to the column level and perform impact analysis and look at the etl data flow objects to understand how it was transformed. On the right you see a typical catalog page of a table in a, in a database but here we see the health score being plugged in from those third party tools. So you can look at is this quality data, how much do people use this data and that's driven by a machine learning algorithm to determine how much data is used and therefore you can prioritize where to spend your time where to look first. So if you don't waste your time looking at unused data or you can even get rid of and delete unused data or tables or schemas. Finally with business users, you can answer questions I talked about where we can catalog and we actually have any tool correlation can concheats, but you can answer questions like what data can I use in my spreadsheet and that answer comes from the catalog. How do I get updated data quickly into my spreadsheet and that answer can come from the catalog. And is this data in the spreadsheet compliant with different rules and regulations and that answer can also come from the catalog but we extend that intelligence into the spreadsheet in this case, this is an example of Google Sheets but we also have connections to Excel coming up as well. There's not too much detail but we cover a lot of different industries across almost 500 plus customers across different use cases across self service analytics data governance of course and cloud transformation. And my last shout out or see to call to action here is if you'd like to learn more about elation please register for the test flight. So here's the hands on lab where we'll actually walk you through and you'll get a free trial of elation you can sign up and get that at elation.com slash snowflake hands on lab. And here's the dates on the right if you want to take a picture of it or find out more information, but you will get a free trial you don't need to be a snowflake user but anyone can sell a free trial elation for 14 days and learn about it through self guided tours. But I'm done so thank you very much, Shannon and over to you, Bob. Jason thank you so much for kicking us off with this great information and thanks for elation for sponsoring today's webinar and helping to make these webinars happen always appreciated and always great to have you guys with us. And just reminder if you have questions for Jason feel free to submit them in the q amp a as he'll be joining us in the q amp a portion of the webinar at the end here with Bob. And then let me introduce to you our speaker for the series Bob Siner Bob is the president and principal of kik consulting and educational services and the publisher of the data administration newsletter T Dan calm. He specializes in non invasive data governance data stewardship and metadata management solutions. And with that, I would get the floor to Bob to start his presentation hello and welcome. Hi Shannon hi thank you very much Jason thank you elation. Thank you everybody for taking time out of your schedule to sit in on this webinar today. A lot of things that Jason talked about you know everything to everybody, being able to get all those different types of metadata that Jason shared when he talked about things that can be included within the data catalog. I mean that is the challenge that is a challenge, because there are so many things that you can collect. And there's so many answers that the catalog can provide regarding the data, we're going to talk a little bit about that today we're going to talk about what are a lot of those things that are in in your environment. There's a lot of metadata that you want to include within your catalog, to be able to provide the answers that are most appropriate, the answers that people have about the data. So before we get started. As at the beginning of all the webinars that I do, just tell you a little bit about some of the things that I'm involved in. We do this webinar on the third Thursday of every month, next month. I'm talking about metadata governance I talk a lot about how the metadata itself will not govern itself that we it really requires that people to find produce and use the metadata appropriately. And we'll talk a little bit about that today in the webinar as well. In the coming events I'm going to be speaking at a couple of diversity events coming up a couple times at the enterprise data world digital event that's coming up in March. I'll also be speaking at the DGI Q West event in San Diego in June. I talk a lot about non invasive data governance just to let you know that the second book on non invasive data governance will be coming out in the second quarter. I also have learning plans available through diversity on non invasive data governance non invasive metadata governance business glossaries dictionaries and catalogs. In my spare time I also work as a faculty member at Carnegie Mellon University here in Pittsburgh. And so I don't want to spend too much stuff, a time on that. I want to get into what we're going to talk about today in the webinar. So as Jason I talked about there's a lot of different types of metadata in your environment. So we want to make certain that we're selecting the appropriate metadata out of all those different types of metadata and then the combinations of metadata are basically endless. Basically, so how do we go about selecting the appropriate metadata to govern. We're going to talk about the business and the technical value that people are looking to get out of the catalog. One of the ways to get the data catalog to answer the questions that people have is to build it into what people do. So we'll talk about a little bit of a strategy as to how to do that. We'll talk about positioning the catalog for success. And then we're going to wrap up by using my framework basically to determine what are the most appropriate questions that we need the data catalog to answer. Before I get started with that just quickly to go through the definitions that I use for governance and stewardship and metadata data governance I use a pretty strongly worded definition which is data governance is the execution and enforcement of authority. At the end of the day, no matter what approach you take to governance, whether you take a command and control top down traditional, you know, if you build it they will come type of approach, or a non invasive approach, you need to execute and enforce authority over data you need to change behavior, you need to have formal accountability for the data. And that's really my definition of stewardship. Stewardship is formalizing accountability for the actions people take with data in your organization. So a steward basically you've probably heard me say before that everybody potentially is a data steward, but anybody who has a relationship to the data that's being held accountable for how they define or produce or use data is a steward of the data. That's not something to be opted into or opted out of. We need to know who those people are we need them to recognize themselves as stewards. Metadata is basically any information about the data that's going to help both the business and the technical community to understand the data, and that's really what we're talking about that we're going to include within our data catalog. Let's just start out by listing a bunch of different questions that people have lots of questions that people are looking to the catalog to be able to answer. So if you look through these questions I know there's a lot of them on the screen, just want to highlight the two of them that are in kind of a brownish color. That's why are the same results different. People ask the same question to different people and they get different results and that drives people crazy. They don't know where the data came from. They don't know how it was manipulated they don't know how it was calculated, or even what data that is used I had another client that was saying they wanted to know how data had changed over time they had no record of how data got from the way it was initially entered into the system to the way that it was being used. A lot of these questions are the questions that people want to be able to get and need to be able to get from their data catalog. So we can address each of those questions today I kind of want to take an approach to helping you to understand what are the answers that you need to get from your data catalog, or that the people in your environment and your organization need to get from the data catalog. So that's where really where we're going to focus today, we're going to hopefully end this webinar with a list of questions that you really want your data catalog to be able to answer. And just as Jason had talked about a little bit earlier there are a lot of different types of data. There's a lot of different types of metadata in the organization. The first first step really identify the appropriate metadata that we're going to govern, and we need to prioritize that metadata because you're not going to flip a light switch on and have all the different sources all those different types of sources that are available to be collected into the catalog available at one time. So you're going to need to be able to prioritize them. And then you're going to need to govern them to make certain that the quality of the metadata coming from these sources is valuable. Is defined well is produced properly is used the way it's meant to be used. And then we want to come up places to govern your metadata so first of all we need to understand that there's several different types of data within the organization and most organizations take those down into structured and unstructured data. So structured data would be data that resides in information systems in analytical platforms in data resources databases, unstructured data could be almost anything else can be text records documents content types of things, but even beyond the structure data and the unstructured data. There's data that's being generated internally within your organization, and there's data that you're getting from outside of the organization. And there's real time data and there's data that you're purchasing. You know, basically, there's data that you as an organization own, and you have influence over but there might be some data that you don't have influence over, and you still need to know about that data, and you need to be able to let people know what you don't know about that data, just so they can have the proper level of confidence when they use that data. So the first thing we need to realize is there's different types of data, they're coming from different places, what we know about that data is different. We need to be able to catalog. In order to answer the questions that most people are going to want to get out of the data catalog, we're going to need to have answers, we're going to need to have information about the data in all these different types of basically. And the interesting thing is that the metadata about structured data and the metadata about unstructured data, some of that metadata is the same but some of it's different as well. And some of the metadata for real time data or data that you're receiving from the outside may be different as well. Because data governance and data management and metadata management practitioners need to help the organization to identify what metadata needs to be, what metadata needs to be governed we need to prioritize that into the appropriate metadata to include within our catalog, if we expect the catalog to answer the questions that we have. So, there's different types of metadata there's there's data about the data definition like your data modeling tools, your spreadsheets anywhere where you have data dictionaries and glossaries. There's data about your data definition in those places. There's data about your data production where is the data being produced, how are values being calculated. There's data about how data can be used and can't be used. And there's business rules that need to be connected to the data and there's protection rules and privacy rules, all these rules about data usage. They're all metadata they're all things that people need to be able to have to get full value out of the data and if you really want people's eyes to glaze up and roll back in their head, start talking about the data about the data about the data, the meta metadata that we as data management and metadata practitioners need to know we need to know even what metadata we have, where we go to get it, who's responsible for that metadata. And basically need to know who will use the metadata. How do you even know that people are going to use the metadata. And then the questions become what are you going to do about it how are we going to get this information into the catalog and start to use it. So, when we go about prioritizing the metadata. We need to number one and recognize what metadata we have. We need to know where it's located we need to know if it's being kept up to date oh sure we have a data dictionary about system ABC. It's been in 2017 and it hasn't been touched ever since. And we need to know when if it's even being kept up to date and who has responsibility for doing that. Now I mentioned earlier that next month's webinar is going to focus on the fact that the metadata is not going to govern itself. Somebody has to have responsibility for the definition of the metadata, the production and then hopefully as you would all expect the metadata, and we want to know how people are going to get access to the metadata and the answer to that question often falls within the ability of the data catalog to be able to share that information. Additional questions to ask when you're prioritizing your metadata is, you know which metadata is going to bring the most business value. Who's going to use it. When do we need to be able to deliver that metadata and I'm going to talk about that in a couple more minutes here of how do we deliver the metadata when it's going to be the most useful to people. What will take to make it available how are we going to be able to determine whether or not that metadata is being used. Jason talked about that a little bit that the tool can tell you how often people are accessing information, either the data or the metadata about that data. So when you're prioritizing your metadata there's you know you look at what the what's the immediate need. Where can we get the most bang for our buck or where can we provide value quickly so that people can see that the catalog has the ability to answer the questions that we have all these questions need to be asked when you're prioritizing what metadata to manage. So, like I said next month in this webinar I'm going to talk about governing metadata, and that that it's not going to govern itself. And if we go back to the definition that I shared at the beginning of the webinar that data governance is the execution and enforcement of authority over the definition and production and usage of data. It's the same thing over metadata. Somebody needs to, if we are going to be able to provide effective metadata to people, somebody is going to need to be responsible for keeping that metadata up to date. Somebody's going to need to be responsible for getting that metadata into whatever resources necessary to make to formalize that metadata and make it available to people. So basically, again, kind of going back to the definitions that I shared at the beginning, we need to formalize accountability for the definition for the production and for the usage of data. And, you know, really recording who does what is the first step towards formalized accountability, then operationalizing that is the second step and actually the most complex step. When it comes to determining, you know, what is the best way to select the appropriate metadata and to make certain that that metadata is being governed as a resource. Because again, the information within the catalog is going to be as good as it was governed on its way to getting into the catalog, if the catalog is not its native source. So when you're thinking about selecting the appropriate place to govern your metadata, look at all the different places where the metadata resides in your native sources in the spreadsheets in the dictionaries or in the desktop applications that you have spreadsheets, documents, you know, oftentimes organizations to have folders and folders of information about their data, but it's very unorganized. So we need to make certain that we can get the information from those resources and get it into the catalog, if that's going to answer the questions that people have. And from the, from my experience as being a metadata repository administrator years ago anywhere where you can automate that process of getting the metadata into the into the catalog tool is going to be really important. So automate wherever you can, like I said, it's change management at its finest. You know, some people actually govern their metadata within the data catalog itself, it's not all coming from the outside. So that's another place that you need to govern your metadata, basically anywhere where metadata lives within the organization, it needs to be So let's talk about so we talked a little bit about how do we go about selecting what the right metadata out of all those sources are for us to govern. Let's talk about the business value and the technical value that's going to come from your catalog through the answering of the questions that we just talked about. So we'll talk about catalog functionality, aligning functionality and value. Again, this is kind of a leader, a lead and slide to the next couple slides. So I found a really good resource that I used that came from competing media source and talked about data catalog functionality and I added my spin to it and just wanted to share that with you as well. I'm talking about what the functionality that you expect from a catalog may be, and some organizations have them without clearly defining what functionality they want to use. Some organizations are very proactive in defining where they're going to get their value out of their So I want to break it into a couple different functions. I've got a storage function, a governance function itself, things that are more related to the tool functions, and then the things that really are the ultimate outcome for everybody which is the business use functions. Business metadata, we got technical metadata, operational metadata, you know, from governance perspective we need to know who's responsible for the data and the metadata, how is this going to enable people to get to the data that they need. All of the things quality and those types of things when it comes to the technical tool functions, it's connectors to all those things that were shared at the earliest part of this webinar. There's the artificial intelligence that was talked about and machine learning, you know, all these different functionalities are tool functions, and then ultimately, where is the tool going to be used it's going to be used where analytics are taking place where functioning is taking place where we're making certain that we're compliant to all the regulations that are being shared with us. And so when we talk about aligning functionality and the value, you know, consider looking at it from those four areas, the storage function, the physical storage of the metadata itself and getting it into the tool, the governance function which includes getting people to be using behavior when it comes to data documentation, the tool function itself which is again the ingestion and the rationalization that can take place within the tool, and then deriving the value. So if we look at it from those four functions, I just want to walk through each one relatively quickly here. The first one that I think people are going to want to focus on the most from a business function, business value of a data is going to be to support their enterprise analytics, their enterprise or corporate decisioning or organizational decisioning. All organizations are looking for ways to improve their efficiency and their effectiveness, you know, as a way to add value to the customers to the internal customers within an organization. The organizations are focusing their governance initiatives and their catalog initiatives on improving the quality of the data. Every organization I talked to talks about trust and confidence as being one of the true examples of business value to the organization. If we just trusted the data that we're getting that we're accessing that we're making decisions from. As a company would feel a lot more comfortable with the data that we're using and regulatory compliance is not something that is optional. We need to be able to add value to these functions from the business perspective, in order for the data catalog to truly answer all the questions that people have. I lump together the storage in the tool functions because we need to a place to be able to inventory things the business the technical the operational metadata. I know as a former metadata repository administrator that the connectors to the tools and the change management the automation to get the information into the catalog tool is a pretty complex function. But if you're going to be able to answer the most necessary questions in the organization, you're going to need to develop these connectors. There's a lot of artificial intelligence and machine learning built into tools, the ability to be able to search and discover on your data. People want to know where their data came from. These are all things that I at least list under being value to the technical audiences. They're also a value to the business audiences as well. And then when it comes to the, the stalwarts of data governance. It's really formalizing stewardship formalizing accountability for the definition production and usage of data. It's enabling people to be able to find the data that they need, providing people the ability to to perform self service bi and analytics. And the inventory of the assets improving the quality. All these things are really important when it comes to the value that's being demonstrated from a data catalog. So I want to spend a few minutes also talking about building the catalog into people's routines. And so yes they probably have a lot of questions about what the, what the data is that they have access to, or, or what's available that they might not have access to. We've got to be able to address the data, where it lives, who it lives with, when it lives, why it lives, how it lives. So let's kind of walk through each of those real quickly. So when I talk about meeting the data where it lives and providing value to people from your catalog. I'm talking about anywhere in the organization where people are defining data as part of their job. And many organizations have business glossary initiatives underway, data dictionary, enterprise modeling, corporate modeling, they're developing new systems, new data is being developed all the time. So we need to meet, we need to have the catalog meet the data where it lives, where people are actually defining the data of the organization where they're producing the data. It's hard to produce quality data, if you don't know what quality data is, or if you have a, an empty free form field, and you're expecting the data to be consistent in that field. It's typically not going to happen. But we need to provide the appropriate metadata to people where people are producing the data, and certainly where people are using the data to do analytics to do reporting to do the decision making, but anywhere where data is being shared within the organization. We need to build the data catalog into the routines that are taking place where people are defining, producing and using data. We need to meet the data who it lives with. So if we're going to build the catalog into people's routine routines, we need to know who that data lives with. And that's in terms of the stakeholders, the stewards, again, the people that are being held accountable for defining, producing and using data, the analysts, the regulatory people, the people that are responsible for reporting and compliance. So not only do we need to know where it lives, but we need to know who it lives with and make certain that we understand from these people. What are the questions that they want the catalog to be able to answer, because that's where you're going to, you're going to focus on the metadata that you're going to collect and you're going to record, and that you're going to govern in your catalog. So who it lives with stakeholders, stewards, analysts, regulatory folks, you know, it could be basically anybody within the organization. When it lives, again, I always use these three actions to define what you can do with data within an organization, you can really only define, produce and use data. And almost everything else, I've been challenged on that, but I would say almost everything falls under either the definition, the production, or the usage of data. So if we're going to build the catalog into people's routines, it has to be when they're accessing the data, when they're defining the new data, when they're producing the data. So again, good quality data production comes from good quality data definition. Without good quality data definition. It's very difficult to produce quality data. How it lives. So these two are somewhat the same, why it lives in the how it lives, basically, but you know, where do people, where are people using the data to make decisions. They're making decisions through daily operations. They're making decisions through the reporting and analytics arms of your organization. And I'm sure certain that you have those. Certainly, that's where people are using the data the most we need to be able to deliver metadata to them. We need to understand what questions they need to understand so that they have confidence that the reports and the analytics that they're doing are proper are correct are correct at least with the understanding of the data within the organization. How it lives also includes the sharing of that data, the protection of the data, the collection and the monitoring of that data to make certain that it's only getting into the people's hands that it's appropriate. We are supposed to get into. And then we talk about why it lives. Again, it comes down to the daily operations, the reporting and the analytics and the sharing the protection the collection and the monitoring of the data. So one of the last subjects I want to talk about is positioning the data catalog for success. So in order to do that we need to define what success looks like. To get the people to tell you what questions they want the catalog to be able to answer you need to get them to contribute to what knowledge base you're including within your catalog. So we need to reward contribution and usage usage of metadata reward innovation in the use of metadata promote successes within the data catalog. So for the success of your data catalog, you might define it these ways for metadata management it might be what metadata are we collecting in the catalog. Is it of high quality do people trust it. Is it being maintained. Is it being made available to people that need that information. And so I keep alluding back to the stuff that that Jason from elation shared earlier in the webinar, where you talked about all those different sources of metadata. Yes, you can potentially manage all of those things in your catalog. But is it going to mean success when you just have all those things available if nobody's using it, if they're not connected, the way they need to be connected. You need to define what success looks like for the metadata management aspect of the use of your catalog, certainly from the data governance perspective and I did not know that this was what the, what Jason was going to talk at the beginning of the webinar of increasing data intelligence. That's what we are all trying to do with the data catalog. That's what we're trying to do by answering the questions that people have. We're looking to increase data intelligence, and we're looking to increase data literacy. So, if we get this part of people's daily routines if we're meeting the data and the people where they work with what they do with the data. And if they're getting value from it, you know, a lot of times, they're going to see as they see the value in it they're going to become regular contributors. They're going to see people that are going to provide definitions of what metadata they need and produce the metadata or stay on top of the keeping the metadata up to date. They're going to be the users of the metadata. You want to engage these people, you know, I talk about or a lot of people talk about data stewards. I talk about metadata stewards too because somebody has to have the responsibility for defining what metadata you're using, ultimately for producing that metadata or getting it from somewhere. And then people have responsibility for using it as well. So you're going to engage these people as stewards of the metadata, but you want to help them. And this is something that's kind of recently came to me, which is reward for participation of helping them to improve their confidence in their data. I mean, you're not just improving confidence in data. It's the data that they pay attention to the most. So if we can reward participation for improving the confidence in their data, they may be more inclined to work with us to make certain that we're providing high quality metadata. So reward participation in data catalog activities, reward students for the stewards in the organization for using the catalog, potentially gamifying the use of the catalog, giving value to organizations that are primary users of the tool. They reward innovation as well. Innovate ways people are responsible for collecting the definitions of the data for validating for certifying the definitions of the data for producing the data and for using the metadata. So make certain that you're rewarding people so that they see that you see that they're valuable to the whole positioning of the data catalog for success within the organization and certainly promote those successes wherever you see the successes. So whatever it means you have necessary to do those promotions, you know, certainly create it through your homepage for data governance within your organization, or even through the use of the catalog itself. It becomes the marketplace that people go to to get access to the metadata. And oftentimes it's just word of mouth. We did this for this part of the organization. We can do this for another part of the organization. And certainly by providing the answers to the questions that people have from their catalog. So the last thing that I wanted to talk about before just throwing it back to Shannon to see if we have any questions today is to relate to the data, the data governance framework that I've shared in a lot of these webinars. Let's break it down into core components of a data governance program. And those are the data, the roles. Excuse me, the communications, the metrics and the tools. And in this framework, what I do is I look at these things, each of these core components from the perspective of, okay, what data is important to the executives, what data is important to the operational folks. What are the processes that are engaged the strategic folks, what communications has to go. Again, it's for each of the components by each of the levels. And I started thinking about, well, how can we use this to determine the questions that the data catalog can answer. So I just want to walk through these quickly. And then like I said, turn it back to Shannon. Think of things in terms of what are the questions that the people at the highest level of your organization have about the data. You know, are we being compliant or you know how many customers do we have what are the KPIs to the executive level, consider what are the data questions that need to be answered at all the different levels of the organization at the strategic, the practical, the operational and even the support level of the organization. What are the questions that for example, IT security or information security has about the data. Those are questions that they might want to get out of the data catalog. So that you just focus on the first column of the framework and determine what are the questions about data that are that need to be known at each of the different levels. The same thing holds true for the roles. You know, who has responsibility. Who's the owner. I don't like to use the term owner, but who are the stewards or the subject matter experts for data at different levels of the organization. Who uses that data. Who do we need to make certain follows all the protection roles associated with the data. The process questions at each of the different levels, the communications questions, what do we need communicate to people at different levels of the organization, and you can include those. If there is metadata that is available about those questions, and you want to include that as well. And tools. And so basically use the framework the way the framework is defined to determine what some of the questions are there being asked by people at different levels of the organization. So, in this webinar today basically we walked through selecting the appropriate metadata to govern. We talked about the business and the technical value of the catalog. Building the catalog into people's routines positioning it appropriately in the organization, and then I just thought I'd share with you using the framework that I use. It might help you to get to the bottom of what are the, and what is the question that you want your data catalog to answer. And with that I'm going to toss it back to you Shannon. Thank you so much for another fantastic presentation and just to answer the most commonly asked questions just a reminder I will send a follow up email to all registrants by end of day, actually Tuesday for this webinar since Monday is a US holiday. So diving in here a couple questions that came in Jason during your presentation does elation index Oracle Analytics cloud server content. Oracle Analytics, so the content, not exactly Oracle Oracle ebiz Oracle RDS we do. But our nation actually has a way through the open connector framework for anyone to build a connector themselves, or for relation to partner with some to build the connector so you know there's no reason not to connect to it. Basically yes. Perfect. So and can elation mine SSIS packages at database stored procedures for lineage and what about GitHub repose. Yes, we can index SQL server, including seek stored procedures for lineage. We also do index GitHub repose. So, should the data catalog be integrated with the data governance tool data quality tool data lineage tool and data privacy tool. You should you buy all from a single vendor or can you buy it from multi vendors and how do you integrate them what's what's the best approach here. Okay so I'm going to let you hit that first and then I'm going to answer that after you. Okay, so in the earlier slide I did say that elation is a data intelligence platform. Now fundamentally to relation is a data catalog. But we take a, like an open framework and openness interoperability approach to the market where we do our data cataloging best and we help people and data governance people and data stewards curate data within it to give context about it. It's kind of almost impossible for one vendor to be perfect or very, very good at every single thing like the quality data access rights, and these are whole categories in themselves so you know we believe that we can buy everything from one particular vendor because you'll get like a mediocre solution. If you try and do that. So, you know what elation does is, you can buy elation as a platform, but then we can integrate with the best of breeds data quality providers it access rights. Things like that. So, I think the answer is, no, don't buy it. One thing from everyone. And I'm going to take a stab at it as well the, you know, think about the things that I talked about in the webinar if there's metadata in your data governance tool that is going to be helpful to people through your catalog. And yes you want to create a connector to be able to get that metadata whether it's a built a pre built connector or built the kind of connector Jason, I think you just talked about is building where there's a will there's a way to get metadata from a tool into the data catalog. As far as one vendor, I be right on with what you said Jason is that it's very difficult for a single vendor to be able to provide all of those tools that work seamlessly together because if you think about it the tool market and the different companies are changing at different times. And so, to have one vendor that could could cover everything it would be very difficult to do. That's why it requires some time, even just if you think back to the slide that I shared about the tools and the connectors and all the keeping the information up to date. There's going to be a lot of attention that needs to be paid to that. So, the answer is to me at least is, if there's metadata in the tools all those different tools that were listed in the question. And that's needed by people, by all means put it in the catalog and whatever way you can get it there. Thank you. And, can we have an example of what gamifying the catalog means. Yeah, I'll take a, I'll take a stab at this and I think by before you have good examples too. But when we say game we find the catalog so, you know, a lot of the information in elation when we extract it, there's like two parts to how we do it there's like the automated extraction where you can get the basic information into the catalog but then a lot of the, the richness of the context actually happens from people's real life work with the data. So they use it day to day they use it for their reporting for their analysis. So they know what best so they can actually contribute context and contribute it back to the catalog, like a crowdsource tool like Yelp or, you know, some other thing like LinkedIn or whatever. But really, not everyone is always going to do that or incentivize and that's I think why Bob said, you know, you people have to take accountability for it. But sometimes to get people or encourage them to actually contribute back to the catalog. We try and gamify that creation like you contribute will reward you with something, whether it's points or whether it's some type of, you know, cash value or some type of other, you know, gift voucher or something. There's ways to help spin up that and kickstart that behavior to contribute to the catalog. Yeah, and even friendly competition between business units to get their most critical data defined well, and to get them certified. So you can gamify, and there's a lot of different ways to be able to gamify or to add some pleasure or enjoyment into what people are doing which might oftentimes feel like a very mundane task. But you can have challenges I had a client that I worked with that had instead of if you're familiar with the game capture the flag. It was capture the definition or capture the steward. You know, or those types of things. So, you got to be careful because you don't want to gamify it to the point where people think of it as, you know, nonsensical or not truly adding business value. So that's a line that you need to draw. But it is, but there are ways to make the use of the catalog more interesting to use, and you can gamify it in a bunch of ways. I love it. So, and do you consider data catalog and data dictionary to be the same thing. If not, how are they different. Say that again so the data dictionary and the what data catalog. I'll give my answer Jason and you can do it. I mean, I, a data dictionary the information that you're collecting in a data dictionary is typically about the data elements within a specific data resource. So you have a data dictionary for your data warehouse and dictionary for system XYZ. That should certainly be collected in the data catalog. They're not the same thing, at least not to me, the data catalog can include all the different types of metadata. Jason talked about that I talked about throughout the webinar. The data dictionary functionality within a catalog is certainly a big one. From a relations perspective, a data dictionary is a small part of the data catalog. It's almost the baseline of it where we capture all the data elements or we call them objects, whether they be, you know, schemas tables columns, bi reports, lineage articles about data policies about governance, all those types of things. You know, so it's kind of a part of the catalog where we've got other capabilities inside it like the lineage like I showed like the sequel editing to compose users. But often I think the question that we often get more asked is what is the difference between a data dictionary and a business glossary there's actually a blog on our website about the difference. You can check out. But yeah, we don't think they are the same thing it's a small, the data is a small part of the catalog platform. And that's why I had shared and repeat the question because I wanted to make sure it wasn't data dictionary and business glossary because that is the more common question is not are the data dictionary and the catalog the same thing. And the glossary is typically business terminology versus the dictionary is all the things Jason just talked about. Yeah, that's right. Yeah we in a relation actually have, you know the data dictionary you'll see it in in the catalog pages for the different data sources but we actually have a separate part of the catalog which is just simply the business glossary, we can capture business terms. And I think we've got time for a few more, at least, maybe two more questions here we've got about five minutes left. Do you have some specific examples of rewarding participation for someone using the catalog and proving confidence and data through the catalog etc. So along the same lines of the gamification but maybe expand it a little bit more. Yeah, so ways that they've been rewarded is that there's recognition. I mean I've had organizations that I've actually had a trophy that I've gone around, especially when it comes to a digital transformation or a business transformation, or any type of bringing together data from multiple resources into a single resource. And we've, I've seen, or parts of the organization get rewarded from for their participation by getting gift cards getting some any any silly things even but having a trophy that is passed around back in the days when everybody was in the office, and we were in cubicles everywhere and maybe a lot of people are back into those environments. You know, the trophies would be displayed very proudly that and it was, and you would notice that on Fridays a certain group would be able to wear blue jean Fridays or something like that. I mean, this is ways of recognizing that a group has done a good job and you know what it doesn't even become an issue. If all of a sudden it's competition really it's down to two groups, and to reward them both. I mean they're going to be more and feel more empowered to do it the next time, if they are congratulated and rewarded in game and it's been gamified for them this time. I'll give a funny example that you mentioned a trophy so one of the people gave a customer a client of ours a trophy called. It was like a basic curats like you know karate but it was curate like you're curating things. So they put that on the trophy like you're the you're the winner of the curate challenge. And also, you know, one thing that we've learned from customers that it helps to brand and give a sense of like, you know how do you tie this whole effort back to your own company and personalize it so we've got many customers that name their catalogs name their name their things instead of calling it just elation they'll call it, you know the data log, or some other thing like they'll have a persona like captain curation. And then this person can, you know, promote and encourage people to do things inside the product actually we've got even a leaderboard that measures how much curation people are doing. And it gives you a scoreboard and tells you like you're, you know, what number out of the top 10. But beyond that yeah you can give incentives or some type of recognition to encourage people but generally I mean the output of this should be that people contribute crowd source and people other people get value from it because you know it's like looking at Yelp if someone contributes and says something good about a restaurant something bad I know whether to trust the crowd or not or that gives me some type of indication to it. One thing I'll add is that sometimes our customers have like curation days where they'll get a bunch of people into the same room and spend like maybe half a day or two hours just like working together and creating things together so it's like a session where people almost like a hackathon but they're working on curating content in the catalog. I love the idea of captain curation, I got to use that somewhere. It is great and I love these discussions of the, of using the tools better not just how to use the tools. So, I'm going to throw in one more question and you know for this webinar keep the questions coming I love all the questions we're not going to have time to get all of them today but I will get them over to Bob to get into the follow up emails so slipping one more in here should data catalogs be integrated with internet search. Wow, you know what that's an interesting question Jason I'd love to hear what you say about that. Yeah, I'm not sure exactly what it means like if you mean integrating with Google or anything but I'll give you one example so we now have this concept of elation marker places within the catalog so actually, you know for people that don't just have to log or index their own data environment that they've got like all the different database and data sources. Oftentimes they might need the external third party data that you know is either provided by the government or provided by some other third party data provider like Nielsen, but we actually have the ability to connect that and use the it's almost like Google search but searching third party data marker places and so you can find that data source filter it down for the data source type you need whether it's CSV file or whatever, and actually go procure that data set and then bring it into the catalog so you can augment both the third party external data with your internal data environment I'm not sure that's the vein of the question but you know that's how that's something that we are looking at to try and connect the outside data into elation. And that's how I interpreted the question was as well is, is, but then there has to be a certain level of governance for any data that is external data that is brought in to the tool. Right. And so I think it's a very interesting question and kind of meshes the the rest of the world with your internal data. Well, yeah, indeed so Bob and Jason thank you so much that's perfect timing is brings us right to the top of the hour. I'm afraid that is all the time that we have for this webinar thanks to elation for sponsoring today and helping to make today's webinar happen. And thanks to all our attendees for being so amazing and great and everything in engage in everything with that we do. Again, just a reminder I will send a follow up email by end of day Tuesday for this webinar with links to the slides and links to the recording along with the answers to the additional questions that we didn't have time to get to. Thanks y'all. I hope you'll have a great day. Thanks Jason. Thanks. Good day, Bob. Take care.