Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Manager of Data Diversity. We'd like to thank you for joining the current installment of the Monthly Data Diversity Webinar Series, Real World Data Governance with Bob Siner. Today, Bob will be discussing using tools to advance your data governance program sponsored today by Top Quadrant and Blanco. Just a couple of points to get us started. Due to the large number of people that are attending the sessions, you will be muted during your webinar. If you'd like to chat with us or with each other, we certainly encourage you to do so. Just click the chat icon in the bottom right hand corner of your screen for that feature. For questions, we will be collecting them by the Q&A in the bottom right hand corner. Or if you'd like to tweet, we encourage you to share our highlights or questions by Twitter using hashtag RWDG. And as always, we'll send a follow-up email with two business days containing links to the slides, the recording of the session, and additional information requested throughout the webinar. Now, let me turn it over to Fredrick for a brief forward from our sponsor, Blanco. Fredrick, hello and welcome. Hello, Shannon, and thank you very much. So I know that this is a very good session coming up. We will learn everything we need to know about data governance and the tools. What I would like to give you as an introduction are a few pointers when it comes to data governance. We focus on a strong finish, i.e. the data end of life when you need to dispose data securely. And I want to share a few insights during these specific times. And hopefully those can be inspiring. So first of all, when we have a strong finish and we need to dispose of data, we talk about data sanitization. That basically gives you two options. One, let's destroy the hardware containing the data. Two, my personal favorite, let's use software to make sure that we can remove the data and continue seeing value and usage of the hardware. And what do you need to know in today's data sanitization industries that you can get the same high level of security, the highest level, the highest level of security using software? So think about sustainability. Think about never destroying any kind of IT assets only to protect the data. There's no need to do that today. Another thing that I would like to share with you is how is this industry viewed if we look at Gartner, for example. And what I want to show you with this very busy slide is how we during the last five years have moved from the left side to the right side where Gartner today is saying that robust data sanitization is a core C level requirement for all IT organizations. Why are they saying that? Basically you have a whole puzzle to put in place to protect your data. One of those things that you need to be able to master when you're doing data governance, data management is when data is beyond retention, for example, what to do. And having a software solution in place where you can target data wherever it sits, it's definitely a core requirement today. Finally, I would like to share with you if you feel a need to destroy, you actually need to be able to achieve what we see on these pictures. An HDD needs to be six millimeters in size for someone not being able to withdraw data from what's left. An SSD drive needs to be two to three millimeter size. So when to use this is definitely when you have broken equipment that doesn't respond anymore to hardware commands or software read and writes. But when you destroy, don't fall for the drill or the sledgehammer, go for what is mandated according to different guidance that's given in the market. And then finally, we are all sitting in home offices. It used to be a place where we could just take up our laptop and be mobile around our work. Today, we're sitting in very well equipped office environments for processing data. That's a big thing to think about when it comes to data governance. In that home office, think about data sanitization proactively. Think about how you can remotely deploy erasure of entire systems or selected files and folders. So you always minimize that risk that you carry managing your data. So with that said, think about a strong finished data end of life. Make sure that no equipment leads your side with any data on it. That would be me. Thank you very much. Frederick, thank you so much. And if you have any questions for Frederick or from him or on Blanco, he will be joining us in the Q&A portion of the webinar at the end. So feel free to submit those questions in the bottom right hand corner. And now let me turn it over to Jesse for a brief word from our sponsor, Top Quadrant. Jesse, hello and welcome. Thanks, Shannon. And a big thanks to everyone else for joining us today. I'm here to talk to you about support environment for data governance built on the foundation of knowledge graph technology. Top Quadrant has been committed to and using knowledge graph technology since its beginning in 2001. We offer knowledge graph technology for data governance to provide you with a more expansive and connected view of the most important things in your enterprise. Top Rate Edge, enterprise data governance, is an agile data governance solution for today's dynamic enterprises. Simply looking at a sample homepage here, you'll see many of your needs, such as the tasking, actually, sorry, it's, it zoomed in. Sorry there. Hopefully the slides are back to normal here. So I was trying to point out that many of your needs are right here on the homepage, which would include tasking, a specific set of stewards or roles through controlled workflows of all types of different information across many different asset collection types. One important thing here that I would like to point out is that we've designed Top Rate Edge to One second here. My slides aren't working, Shannon, sorry. Are you seeing the slides? Yeah, they look good. All right. All right, thank you. So what I was wanting to say is that Top Rate Edge is designed knowing that ramping up a new data governance program can be difficult and different organizations may have differing priorities and starting points. With Edge, you can start incrementally and by licensing and using modular components and capabilities to support your comprehensive yet staged approach to data governance. With Top Rate Edge, you can catalog and connect all of your assets, curate your data and collaborate with all data stakeholders. With Top Rate Edge, though, there's over a hundred different types of assets, such as glossary term, database, ETL script, and many others, some instances of which are shown in this illustration. An asset can be any technical business or operational resource governed by an organization. The triangle here illustrates Top Quadrant's view of a comprehensive nature of data governance. Executive or top down data governance concerns would be things like policies, rules, data governance roles, and so on. While the bottom up or representative data governance encompasses the large and growing number of information assets types and their properties, while applied focuses on the bottom line business reasons for doing data governance, such as analytics, lineage, regulatory, compliance. All of these aspects need to be connectable. What a perfect requirement for knowledge graph technology. All of these aspects must be available. Another perfect requirement for an open API driven knowledge graph solution. Edge was designed to be a rich knowledge graph platform to support data governance. It can represent metadata and data, models that give the information meaning, rules and other semantic layers, and any other necessary aspect of information or knowledge. This approach is comprehensive, flexible, extendable, and evolvable. And we believe that knowledge graphs are the best way to support integrated governance. Edge's standard spaced approach and open APIs can support information and knowledge produced by your existing tooling and other point solutions. As an example of applied data governance, consider lineage, which is increasingly important for many enterprise purposes, including impact analysis and compliance. Here is an interactive lineage diagram within top rate edge taken from the medical domain. Behind this deeper in the knowledge graph behind this view are the connected knowledge graphs of many types of assets, business, technical, and governance framework components. This example is a view based on a scenario where a hospital needs to make a change to one or more fields that are on a patient discharge form. Clicking on a link, you will get deeper information and the ability to really dive into the actual information and knowledge itself. There are a number of business and technical assets connected that need to be represented, including the discharge form itself, the terminologies, hospital systems, applications, data sources, data elements, and more. Additionally, though not reflected on this lineage diagram itself, the overarching executive governance concerns such as policies and workflows and roles being called upon at the right time and so on would need to be brought to bear. Such features and elements would be used to help guide things like the changes to the form itself. I hope you've enjoyed this exploration of an integrated governance approach that is based on knowledge graphs. And please remember that they are a flexible, standards-based approach to seamless data governance. And let us know if you're interested in our top rate enterprise data governance solution. I apologize for that tricky beginning there. Hopefully this slides up very well. And now we're back over to Shannon so that we can learn everything that we need to know from Bob. Thank you so much. It was great. And again, if you have questions for Jesse, feel free to submit them in the bottom right hand corner of your screen in the Q&A section. He'll be joining us in the Q&A portion at the end of the webinar today. Now let me introduce our speaker for the series, Bob Planner. Bob is the president and principal of KIK Consulting and Educational Services and the publisher of the data administration newsletter to Dan.com. Bob specializes in non-invasive data governance, data stewardship, and metadata management solutions. And with that, I will give the floor to Bob to get his presentation going. Bob, hello and welcome. Hi, Shannon. Hi, everybody. I hope you're all doing well and I hope you're staying safe where you are. Thank you very much to Frederick and to Jesse for their important pieces of information that they shared before the webinar. It's very important and this is the subject of today's webinar is using tools to advance your data governance program. And they both represented the fact that the data from the beginning to the end of the life cycle has to be, has to be governed. And that includes the setting up of a framework for your organization, collecting the appropriate metadata all the way toward the end of the data's life cycle and eliminating that data. So thank you very much to Blanco and Top Squadrons for the information that you shared today. I love this subject. I think that it is so important that we recognize how we can use tools to advance our data governance program. But before I get started today, I wanted to just share a couple of bits of information with you about some things that are coming up as you probably know that the real world data governance webinars series take place on the third Thursday of every month. Next month, we will be talking about master data governance in action. I also spend a lot of time talking about non-invasive data governance. And for your information, there is a book called Non-Invasive Data Governance that's available at your favorite bookseller. I will be speaking at several dataversity events that are coming up shortly. In fact, one as early as next week, I'll be speaking at Enterprise Data Worlds virtual events with my friend Anthony Altman, where we'll be talking about three sides of a coin. Data governance, data leadership and data architecture. I'll be speaking at the GGIQ event in December as well. And pretty soon you'll be starting to hear information about the Enterprise Data Governance online event that takes place every year in January. So I look forward to seeing you at those events. And hopefully we can connect there as well. Some big news to let you know is that I have now released or I say dataversity has released my third learning plan available through the Dataversity Training Center. And this one is specifically on business glossaries, data dictionaries and data catalogs. And in fact, that's real important to consider as well because we're going to be talking about tools and capturing the information that will need to be available, made available through your business glossaries and your dictionaries and your catalogs. Also, as Shannon mentioned, I'm the publisher of the Data Administration newsletter, T-DAM.com. If you haven't been out there yet, it's a free online publication that I publish things from people all around the country, all around the world who want to share their experiences with managing data. And last but not least, this is also important, kikconsoling.com is the website to go to to learn everything that you want to know about non-invasive data governance. And for your information, that website has just been updated. So please go take a look at it and let me know what you think of the new kik consulting website. The information that I'm going to share with you today, there are several items that I want to talk about in the time that I have. The first one is, I'm going to share with you several easy to build do-it-yourself data governance tools. And so there are tools that are available on the market and there's also tools that you can build yourself. And we're going to talk a little bit about how can we customize these tools to help to address specific issues within your organizations. I'm going to combine those two subjects and kind of go through a couple tools that I have shared. Sometimes I've shared before but I want to share them with you in this session and talk to you a little bit about how to customize those tools. We'll talk about how developing those internally or how to use internally developed tools that how that can help you to lead to the tool acquisition. If at some point you're going to be bringing tools from the outside into your environment, knowing when it's the right time to acquire the tools and integrating the metadata that's being collected in these do-it-yourself tools with some tools that are acquired on the market. So before we get started, I thought there was a couple different ways that we could address this subject today. The first one was to focus on the tools that are already in your environment or the tools that you're going to go about acquiring and or we could focus on tools that you can create yourself and leverage in the industry. And I know from past experience that a lot of organizations really like to attend the webinars to take away tools and templates. And as Sharon mentioned, when she does her follow-up email to this webinar, she'll be providing you with copies of the tools and the things that I'm talking about today during the session. So there are software tools like data governance and catalog and repository and quality and data elimination tools as Bronco talked about and knowledge graph tools, but then there's also some do-it-yourself tools and those tools take different formats.  And oftentimes that's where a lot of organizations start. They start with tools that they're developing internally and showing that there's value in those tools before they take those tools and share them more widely within the organization. So when you look at the tools that the vendors provide like Bronco and they spoke very elegantly about covering physical data destruction and data erasure and that's what the aspect of governance that they focus on. And then Jesse talked about about enterprise knowledge graphs for data governance and how they can collect data that is meaningful to your organization throughout its life cycle. And their goal is to make the data meaningful and turn the data into information by adding metadata context to that data. So both of these tools and both of these vendors share with you how they envision their tools being used to advance governance of data in your organization. However I want to share with you a couple other tools of things that you can build yourselves that might get you ready to be able to acquire one of the tools that these gentlemen spoke about earlier in the webinar. First one being a non-invasive data governance framework. A common data matrix which I've shared before which is a very popular tool that organizations like to use inventory their data. Then there's the governance activity matrix and you may be more familiar with it being called a racy matrix. And then also how a lot of organizations view communications as being vital to the success of their program. How can we set up a communication plan for our organization? So those are the four tools I'm going to share with you. I'm going to share with you the full tool meaning kind of a backed out version of the tool first before I start to kind of zoom in on specific things that you can focus on and that you can update for your organization. So the first one I'm going to talk about is the non-invasive data governance framework. And many of you might be familiar with the tool that was created by a gentleman by the name of John Zachman and it was the Zachman Enterprise framework. And the non-invasive data governance framework which I will show on the next slide was inspired by John's framework. So the Zachman framework is a way to look at the who's, what's, why's, where's, when's and how's of your organization from a whole lot of different perspectives. And so he highlights and I highlighted my framework the core components of a successful data governance program at different organizational levels or different perspectives as Zachman put and within his his framework from the executive level to the strategic and tactical all the way down to the operational and support levels of your organization. And you know a lot of organizations that I work with use this framework to help to define what they need to plan to work on in regards to an effective data governance program. And in the framework you'll have the opportunity to customize the framework to fill in the nouns and the verbs that will be used to really describe the steps that you're taking with your data governance program in your organization. So this is a copy of the blank non-invasive data governance framework and I'm going to walk through it a little bit more specifically but I'll also share with you a filled-in version of that of this tool in a minute. But one thing that I want to highlight is that the information that you're collecting in any one of these boxes that cross-reference between the rows and the columns. There's metadata that are stored that are pertaining to those specific areas of a formally developed and successfully deployed data governance program. I'll share with you some examples of what you can fill in there in a minute. The first thing I want to do is kind of focus on the top row of the framework and those are what I consider to be the core components of a successful data governance program. Certainly first and foremost are the data, the assets that you're governing as part of your program. As most of us recognize the roles and responsibilities that we define associated with the governance of data in your organization are truly the backbone of successful governance programs. So again from each of the different perspectives we're going to want to talk about the different roles that are necessary at the executive layer all the way down to the operational level and the support layer. So I think that will become really evident when I showed you the completed version of the diagram. Same thing holds true with communications. We're going to communicate with people at different levels of the organization in different ways. We can't necessarily communicate with our executive team or our management group the same way that we're going to deal with and be communicating with the subject matter experts and the data stewards within the organization. Then there's metrics from different perspectives and the different tools from different perspectives. So I want to share with you again the different levels that are along the left hand side of the framework. Those are typically the roles and responsibilities that are necessary for you to develop a program that's going to be successful within your organization. The executive level plays a role certainly at the strategic level where a lot of organizations have data governance councils or committees. That's an important role. They play an important piece, an important role in the success of your program. The subject matter experts or the domain stewards, people that have knowledge and authority associated with specific subject areas of data are important. The operational, the people day to day that have jobs as data stewards. They are the ones that define and produce and use data as part of their job. Then I added kind of grayed out on this slide. The administrative level. It's something that one of my clients brought to my attention that they didn't necessarily fit into any of the other levels. It is who it has the responsibility for guiding the program. In the framework you're going to see that the administrative program has been put under the support level of the framework. But you could develop your own framework or you could take my framework and expand it to cover whatever is most important to you in your organization. Again, this is the blank framework. As you see, it has all those core components across the top. It has all of those different levels down the left-hand side. What I wanted to do was share with you a version of that framework that is filled in. These, as I mentioned in an earlier slide, these are the pieces of information or the verbiage or the statements that you will use, terminology you will use to help people to understand what is necessary to put a successful governance program into place. Let's just look at the roles column for a second and see exactly what I mentioned earlier. The roles and the roles column as a core component at the executive level you may have a steering committee. At the strategic level you may have a data governance council. At the tactical level domain stewards or data owners as is called in a lot of organizations or certainly the subject matters experts of data in your organization. At the operational level the specific operational data stewards, the people that define and produce and use data as part of their job. And then there's the support function, the support level as well. What do you need as supporting functions or what parts of the organization are already governing data that we can take advantage of within our organization and the development of work groups to focus on specific issues and problems and opportunities to improve the value of data within the organization. I could talk through this diagram all day. I don't have all day to be able to speak to it but you can see even under metrics and under tools how they change as it goes from executive to strategic and tactical, operational and support levels of your organization. So this is a very valuable tool just for even getting started with your governance program and recognizing what information you can collect about your information, about your organization that will help you to be more successful in the governance, in the formalizing of your governance program within the organization. So what do people use frameworks to do? They use them to communicate effective program management. They use it to highlight that key terminology that I mentioned that really describes the approach that you're taking to address each of those components by each of the levels or perspectives that we have in the organization to outline the metadata that's needed to be included in the tools that you're going to use, like a Blanco, like a top quadrant. It outlines what metadata specifically needs to be captured in your organization and it simplifies the whole concept of data governance. Yes, the framework looks large. It looks like it has a lot of different pieces to it but the fact is that we know that those core components are going to be required in order to be successful in your organization. So one thing about this slide here, if I just highlight those first letters, you know, it basically describes what we're trying to do by using a tool like the data governance framework, it basically applies order to what might feel like it's going to be chaotic or to apply order to chaos within your organization. The data governance framework is a very valuable tool that you can build, that you can develop, that you can use to communicate effectively across your organization. All right, we're going to go on to the second tool and the second tool, you know, I have to be honest with you that some people that have read through the non-invasive data governance book or have attended these webinars or other data diversity presentations that I've done, this is the most requested tool and this tool continues to evolve in my thinking and it's being used in many different ways in many different organizations. Common data matrix doesn't really describe what it does, it's really more of an inventory and accountability matrix and you'll see what I mean in a minute when I share with you some different versions of that tool. But really what we're trying to do is we're trying to cross-reference the domains or the subject matter experts all the way down to the critical data elements for your organization and recognize who in the organization is defining and producing and using that data across the organization. Now oftentimes the information that we collect within the tool and it aligns with the use of glossaries and dictionaries and I guess I meant to put data catalogs there instead of the second use of the word glossary but it really aligns well with a lot of the information that we're going to collect and we're going to store within our business glossary, within our data dictionary and certainly within our data catalog. So organizations use the common data matrix to demonstrate need for other tools. So this is a tool that you can develop at very little cost and it says here you'll love the price because it is really no cost associated with it other than your time and what it takes for you to build out this matrix and understand how it can be used to leverage the data and information and who has accountability for that data across the organization. So this is kind of a pulled out view where we're backing up a little bit. I know some of it on the screen is somewhat small for you to read but just to talk through it really quickly and then I'll show you a more honed in version or zoomed in version but we're going to take the data of the organization broken down by domain or broken down even by critical data elements and recognize where does that data reside in what system and who in the organization from the IT perspective knows that data. Who are we going to go to when we've got a problem with something technical associated with the data then as we work our way across the common data matrix we can also recognize who in what part of the organization is getting their data from where and the reason that's important is because when it thrives executives and management crazy when they ask a question and they get a different answer depending on who they ask. So there's a good reason for that because oftentimes people don't have the same understanding of the data or they're going to different places to get that data so I'm going to show you a little bit more of a zoomed in version on the left side of the common data matrix and this example focuses on the domains with the subject areas of data and I'm also going to show you another version that kind of hones in on the critical data elements down to that level of granularity within your organization and if you can see that the role color key that's on the upper left hand side that aligns with your operating model for the roles and responsibilities at the different levels of the organization that I spoke about in terms of the framework diagram that I just shared with you. So you can use this tool you can develop it yourself we will share a version of it with you that you can start to fill in so you can do an inventory on your most important data assets and who has responsibility for them who are the subject matter experts that we're going to go to when we have a question about it who do we go to in IT it really starts to make your data governance program more efficient and more effective when we have this information catalog somewhere. So here's another backed out version of even a more recent common data matrix where the focus is really on critical data elements the CVEs that I mentioned on the slide where again you've got the role key that identifies well what people when we fill names in to some of the colored squares you know that this is the person that we're going to go to when we want information about customer name the sub domain within the domain of customer and all the way down to the business term or the critical data element within the organization such as customer contact name might be the business term that you use in your grocery who's the person that's a subject matter expert associated with that piece of data what is the critical data element called and you can you can feel free to customize this tool excuse me to make certain that you are collecting the appropriate information like for example if you're moving several packages into into another package and doing system integration that way you might want to know what are these things called in the different systems and then what do we want to call it as a standard name moving forward and just to work for work across in this diagram you can take the critical data element and say okay and it resides in Salesforce and this is the person in IT that we go to or it's in system ABC or within your data lake you know where are people getting their data from the common data matrix is honestly a very appropriate tool for you to use in your environment to start to catalog who does what with the data across the organization so I've talked about the framework I've talked about the common data matrix I also want to spend a couple minutes talking about the governance activity matrix and this is what a lot of organizations speak to as being a racy diagram where we're going to document who's responsible for this step of a process and who's accountable and who's consulted and who's informed so the idea of using a racy is obviously a formalized data process formalized stewardship of the process and cross-preference those roles that you've defined as part of your program that you've outlined in your framework to the different steps that are associated with the delivery of standardized processes within your organization so some organizations will put an R and A a C and an I in the charts as the one I'm going to share with you here in a second and other organizations will put things as far as amount of time in the outcomes and the deliverables that are expected from those activities within those specific steps so again I'm first showing you kind of a backed out version of what a total racy chart would look like and again this one you see the colors are a little bit different but another way to be able to customize the tool for your organization is to utilize the colors that are associated or your corporate colors if you know what RGB is and coming up with the specific colors that are parts of your logo to make it more meaningful to your organization so let me go to a more blown up version in that and just showing you a piece of it basically across the top we have those different roles that align with the framework that align with the operating model of roles and responsibilities the different steps of a process and who's responsible who's accountable who's consulted and who's informed so these are tools again or this is a tool that you can customize in your environment to formalize your process I've spoken to a lot of organizations that talk about governance and process of process governance should I say where the process is we have processes but not everybody knows what they need to do you know this is a way to formalize that to make certain that we're getting the right people involved at the right time in the right way in other webinars I've spoken about the data governance bill of rights and the word rights is in quotes let's get the right people involved at the right time in the right way and that is truly what data governance is all about and the last tool that I want to share with you before I spend a couple minutes talking about those other subjects that I've brought up was the communication plan matrix and oftentimes when I'm assisting an organization to deliver a communication plan that communications is broken into three different categories orientation on-boarding and ongoing communications and if we recognize that we're going to communicate differently with the different people at different levels of the organization it's good to have a communication plan if you have corporate communications people that can work with you you certainly want to get engaged them to make certain that the messaging is appropriate but things that you can include within the communication plan are things like the messaging the cadence how often are these meetings taking place how are we delivering the this information to people and who is responsible for developing the materials and who's responsible for delivering the materials to the organization so those four tools the framework the common data matrix the activity matrix and the communication plan matrix are tools that you can build yourself to really start to enable your program and advance your data governance program within your organization here's a copy of a communication plan matrix again backed out a little bit just to give you an idea as to what the whole thing looks like but we can hone in a little bit on parts of it and you can see I have the orientation and onboarding communications listed as being part of the the development of communications in your program and then there's different types of communication that are associated with orientation and onboarding and ongoing communications and again consider adding to this diagram or to this chart you know what's the cadence of the meeting how often are we going to meet what are we going to talk about what what tools are we going to use to deliver the messages that we need to deliver so those are the four tools and I find them to be the ones that are most requested and used most often within organizations so I want to spend a little bit of time here before we turn it back to Shannon for some Q&A to talk about how these internally developed tools can help you and help to lead you to acquiring the appropriate tools for your organization so there's some potential issues around that and I just want you to keep in mind that some of the information that I shared with you in those tools that I shared may or may not be part of the functionality of some tools that are on the market and if they are important to you then certainly go after tools that have those types of capabilities within your organization so one of the potential issues are it depends on what the tool the internally developed tool the do-it-yourself tool does and it depends on what the tools on the market do and obviously in most organizations it has to do with the budget that is set for acquiring tools that's often why organizations start with do-it-yourself tools is that they don't have a budget that's set or it takes time to get budget it also takes resources to implement and deliver those tools but it also takes time and resources to utilize these internally developed tools as well so if you're looking to acquire a data catalog they're not inexpensive they're not plug and play you can't plug it in and have it govern the data of your organization for you yes automation can be very important in the success of your program but it takes resources and it takes time in order to implement these tools and get people across the organization to use them effectively oftentimes you'll be able to tell by using do-it-yourself and internally developed tools to see how good is the information that we're collecting in those tools sometimes there's a lack of governance or a lack of quality in the information or in the metadata that you're storing within the tools sometimes we don't necessarily have the appropriate stewardship who's defining what information we're collecting who's producing that information who's and who's using that who do we expect the users of that information to be and oftentimes there's a lack of acceptance of tools that you develop yourself so if they're demonstrating value in parts of your organization share that across your organization so that people know what value is coming from these tools that you're developing internally and see if they'll kind of gravitate towards using those tools so usage and acceptance oftentimes with do-it-yourself tools we need to spend time to focus on that and making certain that these tools are being used and that they're being accepted across the organization and we have to demonstrate the value of these tools and oftentimes that will help us to get prepared for bringing a tool that we're acquiring from the outside into our organization so what are the things that we can put in place while we're utilizing do-it-yourself tools while having requirements for what we're going to use the tool for having the resources identified that are going to be responsible for maintaining that tool how are we going to go about collecting the information within these tools and what are the processes that we're going to follow to make these tools successful within our organization and formalizing this stewardship and who has formal accountability for the metadata that goes into these tools I'm often known to say that the data won't govern itself but the fact is the metadata is not going to govern itself either you know any of these tools that you're going to use in your environment whether it's do-it-yourself or it's tools that you're bringing in from the outside it requires that people have time and people behave appropriately by making certain the right information's being collected in the right ways that people can use it appropriately some other things to think about are standards and consistent ways of collecting the metadata I'm working with a client now that is moving multiple systems into a single system and I've stressed to them the importance of being consistent in the way we're collecting the metadata even in the spreadsheets in the data dictionaries that we have within our organization so having standard and consistent ways of collecting the metadata being able to recognize how we're going to map that metadata to the metadata in the acquired tools assuming that there's a chance for us to be able to leverage and value the information that we have as we move it into acquired products you know knowledge of how the tools that we're bringing in and the tools that we're developing represent that metadata are we going to provide it to people through the tool itself or through reports or through dashboards that are being provided are we going to do we understand how this information is going to be used and how we're going to measure the success of these things and change management is critical in the use of any tool whether it's a do-it-yourself tool or a tool you acquire because once you've entered information into that tool it's a snapshot of a point in time and you want to make certain that you have the ability to be able to keep that information up to date so people understand that the data can be the metadata within these tools can be trusted so let me spend a minute here talking about what how do you know when it's time to acquire a tool well it's time to consider acquiring a tool when the tools that you're developing yourself don't have the functionality that the other tools in the marketplace have and some of these tools like the common data matrix it's great for inventory and accountability but there are other tools in the marketplace lots of other tools that will help you to collect that information and represent that information so if the do-it-yourself tools don't have the functionality you need it's going to be time to start considering acquiring new tools and bringing them into your environment and the same thing holds true with these tools being accessible you know by the relevant stewards within your organization a spreadsheet is not the best way to share data organizations do do that but the the fact is that you may outgrow your ability to be able to address all the people in the organization that can use these tools or these tools don't have the capacity to hold all the metadata that you need or interoperability becomes an issue where these tools don't communicate and talk with other tools and that's certainly something to consider and I'll talk about that more in a second how do these tools interact with other tools in your environment in your infrastructure that you have within your organization you'll know it's time to acquire a tool when the maintenance class of the do-it-yourself tools become greater so then the acquisition cost and the maintenance cost maintenance cost of the tools we're bringing into your environment that you've got people in your organization that are calling out for the need of a formal tool set you know instead of using the tools that we as data governance practitioners have put together or that the requirements are defined in now and from using the do-it-yourself tools and budget is now available that's going to be a time where you might want to consider leveraging some of these tools that are available to you or you've outgrown the ability to use these tools that you've developed internally and it's time to move on to things that are greater or have or might behave or might provide benefit to a greater portion of your organization so I want to go real quickly through the steps to acquire a tool at least the ones that I've experienced and it certainly starts with documenting what your required functionality and your and also understanding the vendors that are available and what's the financial viability of these companies and how is their customer support so you're not typically just acquiring a tool you're acquiring the working with the vendor as well so do some research on the vendors of the tools and make certain that they're going to be there to be able to support you the way that you need to be supported you know conduct a market analysis of tools and vendors that might meet your requirements conduct an RFI if you know what that is a request for information to take a greater list of vendors and limit it down to more selected list of vendors and then select the tools that you're actually going to consider asking to submit proposals to your organizations and conduct an RFP process a request for a proposal with more detailed requirements typically the RFI doesn't detail the requirements as much as an RFP does but then you send those out to the vendors that you're considering you evaluate their proposals you select a vendor oftentimes conduct a proof of concept to demonstrate that the tool will do what they said it would do and that it will work effectively within your environment and last is contract with the tool contract with the vendor of choice for the tool that's going to make most sense to work in your environment and keep in mind you may be considering moving metadata from some of the tools you have in your or some of the do-it-yourself tools at some point into these tools so be consistent in the way you collect information in spreadsheets if that's a way that you're going about collecting your metadata prior to being able to acquire or to use a tool from that's not being developed internally in your organization so let's talk for a second about integrating the do-it-yourself tools with acquired tools we'll talk about integrating any tool with the do-it-yourself with the acquired tools as well just consider these things the effort that's going to be required and the resources that are required to get these tools up and running in your environment the ability to pull metadata out of the do-it-yourself tools or out of other tools in your environment and to extract them so that they can be loaded into the do-it-yourself tools or loaded into the tools that you acquire the format of the metadata extraction your ability to create your own loads of information into those tools the versioning of the metadata and how that metadata is being represented within the tools you know governing change management again we don't want a snapshot of metadata that's going to evolve as the organization evolves so governing change management is critical the ability to automate that extraction and that loading process is key if we want to reduce the the manual effort of pulling metadata out of tools and sharing it into other tools and you'll notice that this slide is very similar to the last tool or last slide because I'm really talking about any tools here and so again it's the effort and the resources the ability to select metadata the formatting of that metadata you know a lot of tools provide connectors between their tool and other tools to be able to bring metadata in it's something good to be thinking about when you're thinking about advancing your program with tools you know versioning of the metadata also making certain that the tools are that you can keep up to date with the tools on both ends of that connectivity or that those connectors that we spoke about so the last thing I want to talk about is considerations for purchase tools you know consider when you're looking at tools the interoperability of tools that come from the same vendor or might be being sold to you as being a suite you know certainly understand how those tools can connect to each other and how they share the information that's being collected the resources that are required to deliver and maintain that connectivity and that interoperability between tools what types of interfaces do you have the availability and the cost of the interfaces interfaces and the ability to be able to connect either the do-it-yourself tools or tools that are already within your environment with tools that you're looking to acquire there's a lot of different options for bringing in these vendors the options to purchase or to lease you need to consider what platform is this information going to be delivered on you know keeping up with the releases of the tool and especially when you're connecting one tool to the other but what happens when one vendor updates a tool and the way the metadata is represented in the tool you want to make certain that you have that ability to connect your tools together to make to take the best advantage of the metadata that you have so in this webinar I've shared with you several things I shared with you those four easy to build do-it-yourself governance tools I talked about customizing those tools to address your specific issues and how internally developed tools can help you on your path to tool acquisition knowing when it's time to acquire a tool versus using do-it-yourself tools in your environment and integrating the do-it-yourself tools with the acquired tools within your environment and with that I'm going to turn it back over to Shannon to see if we have any questions today thank you so much for this great 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 Monday for this presentation with links to the slides the recordings the matrices Bob showed off here we'll get those out to you as well and anything else requested throughout so and if you have questions for Bob or Frederick or Jesse feel free to submit them in the bottom right hand corner of your screen there and just saving in here Jesse this question came up during your presentation in the data flow diagram you showed would that also represent a full business process or only the flow around the data and metadata would you also connect for example web services to it or for runtime or only for design time all of the above everything from the technical asset modeling to the enterprise asset modeling the technical would be things like the web services the enterprise level would be for things like the business process and connecting that down you know to maybe possibly like dependencies on the technical application or services and this is available for the human user in real time but it's also API available so it can actually be at runtime metadata being retrieved and consumed externally to the top rate edge system perfect I love it if you want to kick us off with this next question what is the formalized governance process look like Hi I'm so glad you asked that question because it is you know a lot of processes are informal meaning people think that they know what they need to do in what steps of the of the process and you know it really it really focused so utilizing a governance activity matrix or a race you like it's it's referred to in most organizations gets very more gets a lot more specific as to who does what and when do they do it and what do they do how do they do it what is the outcome of them participating in the process that way so an informal governance process would be a process that it's not documented that we don't know who does what or maybe we have an idea but it's not formal it's not known it's not repeatable within the organization a formalized governance process changes all of that it documents these are the steps we're going to follow here's who we're going to engage here's who's responsible accountable consulted informed during the process and as I mentioned you know maybe even stating you know the specific actions that take place during that step of the process and how different people are involved so my suggestion is that you probably already got governance processes taking place in your organization it's a big step forward for you to formalize that to document that to communicate that to the appropriate people so that they know what role they play in each of the steps Frederick anything you want to add to that or Jesse this is Jesse I would add that tools I mean I'm representing pop quadrants edge system of course have a very social framework built into them so absolutely use DIY tools get ready and then go the route of you know doing your research and your RFI paths but the tool should have those social aspects built into them too so that the framework lives with the actual work being done for data governance so when you're assigning stewardship and linking to documents and policies and procedures that should all be interconnected through the entire life cycle it's not something that you can do up front and then leave behind your tooling needs to include it through the entire life cycle the big picture end to end and I know that systems like top rate edge already have that in there for you when you're ready so that would be my addition and you know I'll just add to that Jesse that you know again that's some of the things that I talked about in this webinar is how do we get ready because it's a big change for organizations when they bring in tools those tools can add a lot of value it's a significant investment for the organization so anything that you can do ahead of time to get your organization ready to acquire those tools is in your you and your organization's best interest I can also add Shannon that I saw a comment from Bonnie in the chat during the presentation that it's policy process and documentation then tools I think that was a great summary quote and we often see that both policies and process documentation are quite all that have been quite stale they haven't been revisited updated so sometimes you even have a starting point that you have to revisit very quickly afterwards once you start with implementation so really do your homework before you start getting into the tooling part perfect I love it so and I'll open this up to all of you guys in the in your experience how have organizations dealt with functional mandate-based ownership versus system-based ownership I see that function mandating and during is this responsible for for technical and business responsible for lifestyle co-management of the data I don't know if I read that well but so let me know if you can read that I'll be glad to let them answer first and as before I have an answer as well well okay so let me just jump in then and so when you're talking about functional ownership versus system-based ownership the truth is that the same data can reside in multiple places in your organization for example you may have multiple CRM tools that you're using that you may be integrating into a single CRM tool moving forward and if you go by system ownership and you first of all I don't like to turn ownership to begin with some of you may already know that it's more stewardship you know we're taking care of this for the organization we don't necessarily own it but knowing who is responsible for the system is very important but consider that the data is could be somewhat the same across different systems so in order to move your program forward with formal governance requires that somebody is a decision maker associated with that data we can't have all three of the owners of the systems bangheads agree to disagree and go on their merry way it's not going to solve anything so it almost needs to be more functional or should I say domain or subject area ownership rather than system-based ownership even though in a lot of organizations system-based ownership is what already seems to exist within the organization recognize that there's data that's shared between systems or the same data you know we hear about silos of data but the same data can be shared or be represented in different systems we want to get to one view of that data and one set of common terminology that we use so I try to move away from the system-based ownership and move more to a functional or a domain-oriented ownership or stewardship of data I can add one comment to that when we see systems we often see also automation that systems are processing certain data and then someone has made a decision that this data needs to have for example data end of life after retention period we often see that on the system level someone has taken a decision to automate that it happens automatically doesn't include an owner it's based on a policy it happens automatically believe that on system level whenever you can automate that's a great thing if you have a clear understanding of why you're doing it yeah I would add that planning for and laying out data governance is okay for there to possibly different teams different offices but operational and daily data governance when an organization especially large organizations are truly pulling it off operational data governance they're putting everybody on the same team it's it's how it matured into dev ops you see data governance really maturing into data governance ops and they work together and it doesn't matter you know nobody really cares about the ownership anymore it's not mine it's ours and that comes with daily data governance instead of just planning it I agree with that statement for sure well thank you all for this a great presentation and I'm afraid it's all the time we have for today and thanks to Bronco and Tough Quadrant for sponsoring today's webinar and helping me make these webinars happen and thanks all of our attendees for being so engaged in everything we do again just a reminder I will send a follow-up email to everybody by end of day Monday with links to the slides and the recording and the matrices as well as contact information for everybody so I hope you all have a great day thank you and stay safe out there thanks all thank you so much thank you thank you thanks guys thanks thanks everybody bye


Hello and welcome to the session. In this session we are going to discuss the following question and the question says that the table given below shows the retail prices of various commodities. Identify the given data as qualitative and quantitative data explained with reasoning. We know that quantitative data is data that is given numerically and qualitative data is data that is not given numerically. With this key idea we move on to the solution. In this question we are given a table that shows the retail prices of various commodities. The table can be separated into two data sets. One data set contains the name of commodities and the other data set contains the retail prices of the commodities. Now here we see that the names are non-humerical entries. So these are qualitative data and here the suggested retail prices are numerical entries. So these are quantitative data. Thus we have shown the name of the commodities as qualitative data and retail prices of the commodities as quantitative data. This is the required answer. This completes our session. Hope you enjoyed this session.