Good morning everyone. As she mentioned, I am a developer advocate for LogzIO and if you're wondering what LogzIO is, we provide Elk as a service and if you want to know more about the awesomeness of that and the additional features we add to the Elk stack, please feel free to see me or our table out in the main area there. And now we're just going to shift right into what I am going to be talking about this morning, which as she mentioned is sensory friendly monitoring. So this talk was inspired by a situation that I had developed at when I was actually at a startup, which looked a little like this. Who's been there? Yes. So as you can see, what basically ended up happening is as a small startup, we said we have a small team. So we don't want to risk anything going wrong. And in order to avoid anything going wrong, we're like, oh, we need to make sure that it tells us everything. And so we set it up to tell us everything.  And that is like, now it's not telling us anything at all. So what, you know, the problem we started to encounter was when we try to segregate duties as well as we want to make sure that we actually have a good flow for this to avoid the problem. I'm going to keep shifting this mic a little to avoid the problem of too much noise. That was just overwhelming our then 15 person engineering operation. Because as again, no one was receiving what they needed to hear. Unfortunately, our first attempts were a little futile as well.  And then kind of like this ingrained suspicion we all now had right where we were used to a noisy citizen. And then our system was quiet. And everyone was actually just as anxious. So we tried to find a happy medium and avoid situations like this. When we were trying to more to approach the situation from a place of awareness, we tried to consider the cost of what was going on so that we could actually understand what was actually harming us so badly and figure out where it was costing us, and then move forward based with that information. So one of the things just to kind of provide some additional context is what happens when you have a distracted brain. And I make the joke in context about brains and alerts, but this is true of distracted brains, right? We evolved as a species. We wanted to avoid predators. We're very hypersensitive to our environment. We're very hypersensitive to things wrong in our environment. And what ends up happening when your brain is trying to take in all this stuff, even when you think you're not paying attention to it, right? Like, have you ever lived with a person, family, spouse, it doesn't matter who who was really obsessed about a topic. And suddenly you realize, I've never read about this topic. And I think I know things because your brain was just pulling in from just your environment in this way. So studies have been done because that's how we help ourselves out. So on average, let's say you have a small interruption. And I mean small, not something that causes you to entirely switch up what you're doing, but just a small, you know, Joe developer walks up, hey, I can access the internet. And they're like, the Wi-Fi password is x, y, z.  And they're like, great, I'm going back to confirmation templates. Where was I? 25 minutes on average. Because the idea is when you're returning to the state that you were trying to be in before you were no longer in that state, your brain has half shifted focus upstairs, whatever mental model of your project that you were working on, it's no longer the same in your head anymore. You have to try and reestablish that connection with your mind. And this takes time. So in terms of being able to put a number to the time, it's 25 minutes on average every time someone walks up and gives you a quick little jolt of something else to do. And this was done by UC Irving. The other issue we have is there's a quality degradation. And this was again tested actually by Mason University, George Mason University. And what they ended up doing is they actually had AP students taking the written portion of their tests. And they knew about the 25 minute study that had already been published. So they said, okay, let's give them their time back. Show of hands, how many people think the scores bumped up after they gave the time back? A couple of you hopefuls.  It did not. So what ended up happening is they had, you know, the students taking the test, they did their written assignment, they have the interrupted group, they gave them their time back, and their score did not change. Now the uninterrupted group consistently performed an average of one to two points higher for those who don't know AP scale on a scale of six now, apparently. So you're looking at a scale, a very small scale, right? And so a couple of points is actually rather significant for this type of test, which also kind of slides us into what happens when you try to multitask. And this, you know, flipping back to quality degradation, but also what happens? Are you able to actually focus? And so this study was interesting because what they did is let's say instead of, you know, cloud formation templates or Kubernetes or let's say you're not doing anything completely complicated today. Today is an easy maintenance windowy day, and you're just, you know, sliding through the day and it's fine. It's a repetitive day is what I'm getting at. So this study followed people who did a repetitive task that was short, had three steps, and then they started trying to throw in tiny little interruptions, and they found that people could not complete the repetitive task. Their error rates just skyrocketed. And again, simple task. And for their case, it was intentionally repetitious, right? So whatever tiny little tasks they gave them, they were intended to repeat over and over and over again. It wasn't like they were doing different steps in a multi-step process. So now you're left with, okay, so if I have alert fatigue in the context, bringing it back in, I now have quality degradation, right? I have distractibility.  So we really, really, really, really need to tone it down. And how do we do that? How do we tone it down so that we're actually still getting the information we need? Because going back to Squidward, just since I never thought I'd say in public, going back to Squidward, you know, you have too little noise, especially for a team that's become accustomed or perhaps maladapted to a very noisy, very sensitive learning system, when you start reducing the noise, their anxiety is not going to go up, but... So this is what we started to do at the startup. First of all, we wanted to know where our noise was coming from. You know, we knew how we implemented our app, right? No one, for the most part, no one knows better than you and your engineering team how your stuff is implemented. So we knew what infrastructure platforms we were using. We knew what languages and libraries we knew within a fair degree of margin where we were ever prone, what things were kind of legacy and fragile that we had just brought in, right, as a stopgap solution and things like that. So we knew the sources of our noise. And then we started to categorize them so that we could say, okay, well, this type of noise is infrastructure, right? I mean, this seems kind of basic, but you actually do have to take the time and actually pull this information out of your system rather than kind of feeling it out.  Did the code deploy go wrong? Or is this infrastructure?  And then you want to make sure the purpose of the categories is to so that you're working well. So you want to say, okay, well, now I know who the engineering point person is, and I know who this person is within that team kind of going down the tree. So you might start with, you know, external to the company facing, this is the person in engineering, that's the on call, for example. If someone outside the company knows that something's going on, and then underneath them, you have people responsible for the infrastructure, the front and the back end, things like that. You also, and I can't stress this enough, you need to make sure that you start clearing clutter. And I'm going to be coming around back to that in a minute. So this is what a subset of a place I worked at and their noise systems kind of looked like. You have your traditional stuff, right? Hey, I need to know when there's a bug in JIRA. Hey, I need to know when there's something going on my elastic stack. Hey, it's going through Slack, email, you get the point, right? So you're going to have logging and ticketing and things like that, but you also need to be mindful of your own noise as well. And this is something we had a discussion about as a team, because it wasn't necessarily most straightforward, in the sense that we're talking about our noise. And so we think about things like AWS or Google Compute or pager duty or the things that I just mentioned on that slide. And then we decided to have a meeting about our own distractibility, right? And this goes back to the incoming noise that's unrelated to work, but still uses some of the same mechanisms, right? You have notifications enabled on your phone, which allows pager duty to push a notification, but also allows your mom to say, please pick up the milk on the way home or whomever, right? So when you're talking about your own personal noise, you actually can be muting things because of your noise that are also avenues for, you know, these monitoring systems to be pushing notifications to you as well. And so part of the way that you can kind of push that aside is you actually need to start establishing some boundaries with, you know, just know yourself and know when you work and what you want your workflow to be and what you have experienced your daily life at whatever company or at's workflow is likely to be. And the idea for this is some people, for example, peak in productivity and creativity in the morning, some in the afternoon, depending on a whole bunch of biology worth not getting into. But when you think about that, you're like, okay, I'm most productive at 2pm. So I would really prefer if spouse, other family, you know, other coworkers, unless it's urgent, don't bother me for a few hours around the two o'clock mark. So then when my brain is on, I can devote it to the tasks that really need that heightened creativity. And then I would try to schedule meetings around when I can be more of a recipient than a generating person, right? But also part of this means that you need to let you, you know, these people know what you consider to be urgent. For example, they probably wouldn't be pinging you if they didn't consider it to be at least somewhat urgent, right? Unless they just want to gloriously send you an urgent, which also fine.  You need to say, this is my backup. If, you know, these high priority items go wrong, and if all of that fails, then come to me, you know, give it, give them some sort of boundary to work around for family. Be like, unless you need me to leave work, please don't contact me during this window, that kind of thing. So that people kind of know what you're considering to be urgent for you. But switching back to the external noise, like that, right? When you're categorizing your noise, you probably will start to notice that beyond just knowing what type of noise it is in terms of infrastructure versus, you know, front end versus whatever, you'll also start to notice that some alerts are better behaved than others. We certainly did, right? We mostly ran into the false positive category. I'm just going to quickly give a little example of that. So what happened? One of the developers wanted, had roughly calculated about if hypothetically all the microservices were to connect to this RDS instance, how much memory should it be using? And if it's not that he set an alert to ping because his logic was if the memory usage falls below that, that means someone's not connecting and something's offline. Now, of course, me being somewhere else on the team, I didn't know he had done this. This is one of those things. Startups run lean, right? So everyone has a certain amount of access to everything for a little while when your team super tiny, like five. So, you know, you get that four message from Peter duty that says RDS instance. What? And I'll just kind of flagged it and said nothing's offline. So I'll just ask questions in the morning. And that was the conversation that resulted. So then I said, Okay, now that I understand your logic and what you're intending to do, I'm going to point out that we actually also have alerts hooked into our logging system. And let's alert on failed database connections and stuff. And that was more accurate, right? So the intention, we still captured the intention. We didn't lose it, which was to find out if a microservice wasn't connecting. But that required a conversation and knowing what was going on and knowing what we expected. And the same thing falls through for like the negatives and the fragility where you're saying, Okay, if you have a fragile system, even with the best scoped alert system in the world, it's still going to be noisy. And it's still going to be distracting. And you're still going to have a really hard time picking out, is this actually a problem problem? Is this just kind of a hiccup problem? And you have to know what systems are fragile and set up your alerts kind of accordingly, and make them as noisy as they should be with that taken into account. You don't want to get pinged at 4am. For an RDS instance, that's not actually down, just as an example, right? If it's frequent, you should probably, and this might again seem a bit redundant, but you want to make sure you're taking the time to fix frequent errors.  And then at that point, just by virtue of fixing it, you'll resolve that noise source or type. When you're trying to establish your flow, you need to make sure, and this goes back to the RDS example, we need to know who needed to know what. We need to know why they needed to know it, and we need to know how quickly they need to know it. And the developer made some assumptions when he spun up that because, you know, and it's not from a bad place, right? It almost never is. You don't normally run into a situation where you have, you know, Joe developer who's over here like, ha ha ha, I'm going to wake up versus ads. Usually it's from a place of, I think, a certain, I have a certain mental model of our infrastructure and our app, or apps, and this is based on my understanding is how I'm going to implement a thing, and then someone else is actually impacted by that decision. We all need to make sure that we're having the conversation where if somebody over here can impact somebody's work for over here, they need to know what everyone's logic and expectations are for that. And I knew as the infrastructure person that I didn't need to be woken up over the memory issue when it wasn't an issue. And so I just told him, and we figured out what to do. And it goes back to, you know, the noise level, if the database had legitimately been down, not just a memory threshold issue, but like offline, there were other errors popping up, then I would absolutely expect pager duty or your system of choice to be loud about it, right? You never want to be in the false negative space, where you get human notifications of salespersons or whomever, hey, customers are reporting, right? And after spending all that time talking about how you don't really want to have a ton of noise, I am now going to talk about redundancy, because this was fun. So who uses Slack a lot? Cool. Who enjoys at least-ish Slack? About half of you. Nice. We're going to pick on Slack a tiny bit. And I do love Slack, which is why I wanted to, you know, I do, you know, it does what it needs to do. And it's a mostly available system. This situation then in the happening was rather rare. And I don't know how many of you and your workflows were awakened aware of these time windows, but basically in the early mornings of Eastern time, Slack went down and it stayed there for half a day. Now, we in Logs.io are pretty flexible internally. So although we didn't necessarily think to ourselves Slack is unreliable and we're going to plan around that, we do have the ability to switch up endpoints and get other things accomplished. We don't have everything just dumping into Slack during the day. And I mentioned this because a prior startup I had worked at, we did fall into that trap briefly until we, you know, reassessed and did other things where we had low priority alerts putting in Slack during the day. Now, with a Slack outage, if we had not resolved that in advance, we would have spent half a day figuring out how to switch endpoints and or just an a noise vacuum and just kind of hanging out, sipping coffee and letting the caffeine raise our anxiety levels. So you want to make sure that when something's going down, you're looking at your tooling. And that's of course not about Slack. People use AWS, you can use SNS notifications and things like that. If something goes down, you need to have the ability to switch it up. You need to be able to send it somewhere else so that while your service is down or your third party services down, you're not left in the dark. And if it happens often, so not to pick on Slack, there are tons of other services. I'm sure we've all used a service or a third party service that we noticed over time was not as reliable as we initially thought it was going to be. We need to be able to reevaluate and we need to be able to architect around that so that when something's not behaving as expected, we can within reason easily being a relative word, pull it out and replace it with something else. So for example, if Slack stopped being at least production awesome and started going offline all the time, we would definitely need to be able to switch to another chat system, right? That just kind of half goes without saying, but we want to make sure that we can. And part of this is your engineering team, when they start to adjust to how the new flow of things is going, you don't want Squidward anxiously biting down on his clarinet thinking, why is it so quiet and blasting it into the vacuum of the noise because we want the resilient noise to build trust. You want when it's quiet, everyone knows that it's quiet because it's actually quiet. It's not quiet because something's failing and you don't know. It's quiet because everything is fine. Yes, you can work on that side project you've been putting off for like three months. So when you're, you know, again, going through regularly evaluate reliability of your tools and your services cannot, you know, stress us enough, this goes for internal services as well. I worked at a past company where we know and it's the third party solution we were using for some image scaling was just not functioning quite up to par. We'll leave them anonymous for the purposes of this chat, but we ended up rewriting and rearchitecting and spending the time to put something and implement it internally because we didn't, that, that was just enough of that, right? So reevaluate the internal service, make sure it keeps up and running. And I mentioned that I was going to get back to this. So I mentioned earlier that you need to regularly clean out the clutter, right? Your app is always in a state of flux. It's always changing because your users change because you change and oh, it started off as a really easy idea to just have this app to only this type of, I don't know, financial interactions. But oh, now we have a new potential user base and let's change our requirements. And suddenly rearchitecting and changing things, your alerts may not be alerting on the same endpoints or using the same things anymore. You do not want to just leave them there and let them just kind of hang out. And sometimes this is more obvious than other times because some change is very drastic, real rearchitect a whole solution and maybe you'll switch from, you know, individual dedicated EC2 instances to something like Cloud Foundry and the whole thing's different. And you think to yourself, of course, yes, I'm changing my alert system, but when you're making tiny changes and maybe you have alerts based on more subtle behavior, you definitely do need to take the time and say, okay, did this change anything that I'm checking on metric or monitoring wise? And do I need to make any sort of adjustments? And the reason I nicknamed this sprint cleaning is my suggestion is to actually have this part of your sprint process. If you do it regularly, it's kind of, spring cleaning is a pain for people. I'm just going to switch that up right there. Spring cleaning is a pain. If people just do spring cleaning, because then your house has accumulated clutter and gets a cluttered up and then it accumulates clutter and you get and it takes a long time.  Aside from maybe the first time, it's going to be maybe five to 10 minutes of reevaluate what happened. What alerts went off during the week and are they still relevant? Yes, no, maybe so acts anybody who's not very quick. And that will keep it from becoming a beast again, assuming that you're in a position where you have to fix it from being a beast now. For those of people who like reference slides and things like that, I recommend photographing this slide. This is some of the reading that went into it. It has some of the studies that I reference. It has the Google SRE handbook because Google, but also because there are a few chapters in that about monitoring and alert fatigue that I thought were actually very helpful. And with that, thank you for your time. Does anybody have questions? All right, so I can understand how a lot of this works in a smaller company where you have like five, 10, 20 engineers, but I work in a company that's like more than 100 engineers. So getting everybody kind of like row the same direction or paddle the same direction or whatever is really difficult, especially in this logging, because we have like application performance monitoring, system monitoring, log monitoring, like, and me personally, I don't care about any of it because I don't really care if somebody like, I'm not in charge of the, I'm not on the hook if the application stops working. Okay. Indirectly, I am, but you know, like, I'm not going to be woken up at three o'clock in the morning. So how do we get everybody else to kind of like start caring about this and kind of consolidate our, would you recommend consolidating our logging approach or having each team have more ownership or what? So the answer to that is, and this isn't an escape answer, I promise. It's flexibility. So I've also in the past, I worked at a consulting company that did ops consultancy. So the company itself was small. And then we would contract out to companies of varying sizes. So for the large company, like what you described, one of the things that we did with success is that company had multiple teams, but those teams were sometimes cross responsible for the same apps and sometimes responsible for their own dedicated apps. And when we were architecting the solution with that in mind, we said, okay, things that are logically contiguous need to be together. So in that company's case, there were some teams that we needed to bring together into a room or a Zoom call, right, in the remote case, and have a conversation to get everyone kind of on the same page. And it wasn't a singular conversation either. This isn't a conversation that you have once and everyone changes their behavior. Yeah, it takes 30 days to make a habit. It was something more that we started to say, Hey, everyone can acknowledge that the dysfunction is here. So let's have a conversation so that we don't have all this going on all the way. And you're not getting notified about your app when you can't take any action on it anyway. And just putting it in there and using empathy and putting it in a way where they can understand, Hey, this benefits me and you was really helpful because they don't want to be notified for things they can't take action on. It stresses them out. They have to find the person themselves now, right, or else it's just going to dev not right if they don't do anything about it. So that's what I would say, you know, for the large companies. If it's a large company that's working on a singular thing, you know, I would have the different teams working on that thing have a conversation so that you can say, Hey, now I no longer get alerts on your stuff and you'll get mine. And if it's a large team working on a bunch of different things, just keep them logically separated in that way. Does that make sense? Yeah, one more time for quintessence.


Welcome my name is Erin Kemp and I'm the executive editor of DataVersity. We would like to thank you for joining today's DataVersity webinar, What is a Data Steward and What Do They Do with Bob Siner. Just a couple of points to get us started. Due to the large number of people that attend these sessions, you will be muted during the webinar. For questions, we will be collecting them via the Q&A in the bottom right-hand corner of your screen. Or if you'd like to tweet, we encourage you to share highlights or questions via Twitter using hashtag RWDG, Real World Data Governance. As always, we will send a follow-up email within two business days containing links to the slides, the recording of this session, and additional information requested throughout the webinar. Before we introduce our speaker for today, Bob Siner. Bob is the president and principal of KIK Consulting and Educational Services and the publisher of the Data Administration newsletter, teadan.com. Bob has been a recipient of the Damon Professional Award for significant and demonstrable contributions to the data management industry. And Bob specializes in non-invasive data governance, data stewardship, and metadata management solutions. And I will give the floor to Bob. Hello and welcome. Thank you very much, Shannon. Thank you everybody for attending this greatly anticipated webinar. I think this webinar was originally scheduled for January. We had to postpone it to this month due to some family issues that I had, but I'm glad that everybody is here. And I think this is a great topic, a very interesting topic to a lot of people, and hopefully you'll get a lot of it. As I said, this was originally supposed to be done in January. I just wanted to give you a little bit of a heads-up as to what the webinars that are coming up over the next couple of months. In January, we're going to be doing a webinar called Comparing World Class Solutions and Data Governance with a panel of practitioners doing some Q&A with myself. June webinar is going to be a special webinar. It's actually going to take place on a special day. It's going to take place on a Wednesday rather than a Thursday because I will be speaking at the DGIQ, the Data Governance and Information Quality Conference during that time. So we thought that we would move it up a day early and we'd take advantage of all the practitioners and all of the thought leaders that we have at that conference in San Diego. In July, we'll be doing Governance for Master Data. And then we'll get another set of really interesting webinars coming up in the months after that. I want to talk to you a little bit about this one. I think that you're going to find that some of my viewpoints around data stewards and who they are and what they do may be a little bit different than the mainstream thoughts of who data stewards are and what they do. I think everybody would agree that data stewards play a very important role in most data governance initiatives. And just to let you know, I spend a lot of my time working on data governance initiatives for a lot of different organizations. And the truth is that the way that they define who stewards are and what they do, they differ from one organization to the next. So hopefully you'll see a little bit of yourself and the stuff that I'm talking about. If not, perhaps maybe it'll give you some insight as to some of the things that you might want to be thinking about in regards to data stewards in your organization. So one of the things we all agree on is that stewards play a vital role, a very important role in those governance initiatives. But the question that seems to be asked almost more than any other question is what does it mean to be identified as a steward? What does a steward do? How do they get involved? How much time can we expect to need for our stewards? And you know, if you ask different people from different organizations, you're going to get vastly different answers depending on who you ask. And I apologize a little bit. I'm losing my voice, so I'm going to do the best as I can. Hopefully you can hear me. Hopefully you can take a whole bunch of stuff away from this webinar. The questions that people ask are, is there any industry standard for what data stewards are and who they are and what they do? Or does it depend on the makeup and the culture of the organization? Is there one steward for each type of data, as I've seen with a lot of the organizations that I've worked with? Or are there multiple stewards for each type of data and multiple types of stewards? We're going to walk through those things in the session here. Is this data steward a title or is it a more holistic role? What does being in the life of a typical steward look like and is there even such a thing as a typical steward? I'm going to abstract that perhaps that's you to attend this session here. This is another real-world data governance webinar that I do in conjunction with the final folks from Data Virtuity. The webinar is going to focus on identifying specific activities of stewards and other roles and responsibilities per design of your program. And I think you're going to see that the individuals that are identified as being data stewards really could be almost anybody in your organization and they can play a whole lot of different roles. So this is the agenda for the session today. We're going to talk about the data steward role depending on data governance approach. We're going to talk about what stewards do and when they do it. We'll talk about utilizing data stewards to operationalize your data governance program. And then we'll kind of catch at the end of the session everything else you need to know about data stewards. And if there's things you have questions about regarding stewards, please submit them via the Q&A box down at the bottom, left hand, bottom right hand corner of your screen. So what a data steward is and whether or not there is an industry standard or whether or not there should even be an industry standard under the opinion that there shouldn't be an industry standard for what a steward are. It really depends on your organization and how you put your governance program together. Who should come up with this definition? Well, I think it's really dependent on the people that are defining your data governance program for your organization. And it will really be different depending on what your organization is doing as far as governance and stewardship is concerned. We'll agree that the data stewards are basically the glue that hold governance together. I've seen organizations that have called them data governance programs. Obviously, I've seen organizations that have called them data stewardship programs. Oftentimes, these organizations are saying the same thing. The fact is that governance and stewardship are very different. If you've attended one of my webinars in the past, you know that I define data governance as being execution and enforcement authority over the management of data and data-related assets. So data governance could be a set of processes. It could be a set of procedures that are specific to your organization. The stewards are the people in your organization that have accountability from the data. So the definition that I use for data steward in this presentation is that a data steward is a person that defines, produces, or uses data as part of their job and has a final level of responsibility for assuring the quality in that definition, production, or usage of data. Well, if you look at that definition, the truth is that a data steward could almost be anybody in the organization. Almost everybody in the organization either defines data or produces data or uses data as part of their job. Do we need to identify who each and every one of those individuals are? Probably not. But it's a good idea to know that you have stewards of a specific type of data in a specific part of your organization. So I'll share with you some tools that I've worked with and I've demonstrated in the past that it will help you to record who your stewards are and in what parts of the organization they reside. Many of you are readers of the Data Administration newsletter. That's the newsletter that Shannon mentioned at the beginning of this webinar. But just recently I published an article that was called, Signed Rules for Becoming a Data Steward. Now the intention of that article was to ruffle a few feathers to get people talking about rules basically for becoming a data steward. And the fact was that I expected to get a lot of pushback from individuals a lot of individuals telling me that this is true. But the fact is that almost to a person the people that responded to that article said that I was right on target for what they were thinking. So let me show you these rules for becoming a steward with you and you tell me whether or not it makes sense or not. If you get a chance, please go into the Data Administration newsletter at teadan.com and look for the article of Signed Rules for Becoming a Data Steward. The first rule is, and it's something that I shared with you on the previous slide, is that a data steward can be absolutely anybody. Like I said before, somebody who defines data or produces data or uses data as part of their job typically would have some level of accountability for how you define and produce and use that data. That's the case and if we say that a steward can be everybody or anybody, it makes sense first to record who each and every one of those stewards are. It may be to data and it's not a position. Although I've been in organizations where they identify people as being Data Stewards and they've actually given them the title of Data Steward. I don't really agree with that. I think that again, people that follow a non-invasive approach to data governance, which is the approach that I have talked about in many of the prior webinars, a steward really describes a relationship to the data and it's not necessarily a position. And as I said, anybody in the organization could be identified as a steward but that doesn't mean we need to identify who each of them are. What we want to do is we want to identify certain types of stewards, people that have steward responsibilities for data across the entire organization or across a certain part of the organization. If we went and recorded everybody's name in our database of who the stewards are, I think it would be a little bit of overkill. So typically a data steward is not hired to be a data steward. A data steward is somebody in your organization who already has some levels of accountability for the data. A steward does not have to have the title of Data Steward and in fact for the organizations that I've worked with, none of them have had people in the organization who have had titles of data stewards. They could be a fine person who's entering data into a system. They could be a person who's creating reports and doing analytics within the organization. They don't need to change their title to Data Steward. In fact, as I said before, a steward could be anybody. If they are defining data for their part of the organization or if they are creating reports associated with the data in their part of the organization, they should be able to keep the titles that they have. And they can be identified as being a steward, but that doesn't mean it's a lot more invasive if you need to go and change people's titles to being data stewards rather than the titles that they already hold. They do not have to be told how to do their job, and that kind of goes hand in hand with the sixth rule for becoming a data steward. I do not necessarily agree that there should be public or industry data stewards certification. I think a data steward does what they do within their organization and how governance and stewardship is defined within their organization and have an industry certification of data stewards. To me, I said it's a load of bunk. I know a lot of people probably disagree with that. Some of the organizations that certify stewards would certainly disagree with it. Certainly, I can see certifying individuals to be data governance professionals, people who are running programs, putting programs in place, but the individuals, and there's also many of them within your organization who are data stewards, they do not have to be told how to do their job. They can be told what they're going to get engaged in activities that a steward gets engaged with, but if you go to people and you tell them, here's how we want you to do your job, you're oftentimes going to get a lot more pushback from individuals than if you go to them and say, we've recognized you or we've identified you as being a steward of data. And sometimes I've gone into organizations and I've sat in a room with a whole lot of people and they've pointed at an individual and said, this person over here, Joe, he is the customer data steward. This person, Mary, she's the product data steward. We've got different stewards for different types of data, but we've got one of each. Well, again, that's not necessarily the way that a lot of organizations are putting governance and stewardship programs into place. If there's a couple of different people that are defining data defining the same data, we need to identify who they are. If there's a couple of different people or many different people that are entering data and that have accountability for how they enter the data, we need to identify who those people are. So the fact is, in most organizations, there will typically be more than one data steward for each type of data within the organization. And steward training should focus on formalizing accountability and getting people to do the right thing at the right time rather than telling people how to do their job. So, again, I wrote this article to be somewhat controversial. However, it seemed like a lot of people agreed with me that if we don't go and knock people over the head with a stick and tell them that they're a steward and give them extra work to do, that they're going to accept the role of being a data steward a lot better in that way than if you go and assign them to be a data steward. So please, when you get a chance, go out to the TDAN publication and go to the article and provide some feedback to me on what you think as to whether or not I'm way off base or what I say makes sense about becoming a data steward. So I'm going to talk a little bit about the steward role depending on the governance approach that is used within an organization. There's basically three basic approaches that organizations take to defining a data governance program. And then we're also identifying who the data stewards are. There's a noninvasive approach which you've heard me talk about before. We identify people in the role rather than assigning people to roles. We leverage existing responsibilities rather than giving responsibilities to individuals as something that's new and over and above their existing work efforts. So everything that I talk about tends to point towards the fact that we want to leverage existing responsibilities rather than assign things to people as being new responsibilities. There's a command and control approach and that's when you assign people into specific roles and you give people new responsibilities. Well, if you're going to assign people into roles and you're going to give them new responsibilities, the chances are the first question that they're going to ask is, where does this get prioritized and all of the other things that I have to do? So if we identify people that are stewards rather than assign them and we leverage what they're doing already and help them to do a better job at that, that's a much less invasive approach to putting governance in place. Another approach that I've seen organizations take to data governance is what I call a 2x4 approach and what a 2x4 approach is almost as though you take people in your organization, you smack them over the head with a stick, with a 2x4, tell them the data governance is not optional and that they need to make time. Well, oftentimes that puts people back on their heels where they don't necessarily want to welcome data governance. They look as though it's being forced down their throat, but if you take a non-invasive approach and you identify stewards and recognize them for what they already do, oftentimes data governance is much more accepted into an organization. So the way we identify the steward role really depends on the approach that we take to data governance and it's different being non-invasive than it is to take a 2x4 approach. It's important to clearly identify roles and responsibilities. Well, oftentimes individuals that are identified as stewards, they're not handed a whole bunch of new and new things that they need to do. They're saying that we recognize you from having an association to the data we want to make sure that if you're sharing data that you understand the rules associated with how the data can be shared and how the data can't be shared. If you're defining new data, we want you to already know that there's data with the same definition or a similar definition in your organization. It's very important to identify the roles and responsibilities, but I have not to hand these to people as if something is brand new to them and it's going to be over and above their existing work effort. So one of the typical responses people have to the roles that are defined for data stewards, people aren't concerned about these things that I'm displaying on the screen right here. They're worried about stepping on people's toes, giving them too much or too little responsibility, sharing responsibility. People get concerned, especially when they are handed new responsibilities or having new responsibilities and telling them, you're the data steward for this specific data, you can understand that it would ruffle people's feathers across the organization where there may be other individuals who are also defining and producing and using that data who say, well, why was that person identified as a steward and not as myself? The fact is they both should be identified as stewards and they both should be recorded somewhere so people can get their hands on some type of a list or some type of a database or what I call a common data matrix to help people to identify who the stewards are of the data across the organization. Putting people into positions to make decisions that may not please everybody, that's another concern that we have about identifying or assuming people to be the stewards. Identifying the people that will be the authorities, well, we're going to talk about that in a few minutes. What is a specific role of a data steward, of a certain type of data steward, that people will have responsibility for the data across the organization. They'll be the authorities, they'll be the decision makers. When everybody who's a steward of data is not necessarily a decision maker, they must define, produce and use data as part of their everyday job. People get concerned about escalating concerns of the authorities. The operating model that I'm going to share with you in a couple minutes here that I've shared in previous webinars serves a specific set of roles and responsibilities in a way to escalate these responsibilities or escalate issues regarding data throughout your organization, from an operational level to a tactical level and to a strategic level. Organizations address and alleviate the concerns that I listed on the previous page. Well, first of all, a lot of organizations that I work with and a lot of other organizations as well follow what we call as a non-invasive approach to data governance. By non-invasive, we don't assign people into roles, we don't give people titles of data steward. We identify and recognize them for what they presently do. And therefore, we can have multiple stewards of each different type of data across the organization. Where a conflict might exist is when we identify people to be the decision makers for a certain type of data across the organization. And in that situation, oftentimes it becomes people at the strategic level who can identify and make sure that we know who the individuals are that are the authorities of that data across the organization. Oftentimes, when a program is being defined, that's one of the main backbones of defining a data governance program is defining the roles and responsibilities to go along with the program. And if you define roles and responsibilities in such a way that you give people more responsibility than they should have, or you take responsibility away from individuals that should have it, then obviously that causes some conflict. So we can kind of avoid that conflict by using this non-invasive approach and identifying stewards rather than assigning people to be the data stewards. So oftentimes in organizations, what I suggest is we have the role of the data steward evolved through the natural process. Some organizations have asked me the question, how do we identify who the stewards are? Well, if you're an organization, then create a data, and I'm just going to pick a project, a data warehouse project. The individuals that you would identify to become involved in the defining of the data that can contribute to your data warehouse could potentially be data stewards, because the people that are involved in the discussions, involved in the decision-making, could naturally become data stewards as well, or at least be identified as data stewards. Again, we don't necessarily want to give them the title of data steward, but these are people that are already doing this type of work. My suggestion is that we just identify them, we reward them somewhere, and I'm going to share with you a tool to be able to record some of that information in a minute here. So a lot of organizations that have a role called data steward, and I'm going to suggest to you that there may be a couple of different types of stewards within organizations. There's what we call an operational data steward, who is somebody that works within a business unit, finds, produces, or uses data as part of the job, they have hands-on knowledge of the data they use, or the data that's used by their unit, and so that's how we identify them as being operational stewards. Again, we don't give them the title of being data steward, we just identify them as people that need to know the rules associated with how data can be used and how data should be defined across the organization. So the operational stewards, out of all the different types of stewards, there's more operational data stewards than there are anything else. There's another role that I call the data domain stewards, and those are individuals who have responsibility for a certain subject area of data across the enterprise. And in the past, I've stated in my webinars that a data domain steward, or whatever you call it within your organization, a data trustee, a data custodian, a data maintenance person, a data domain steward is the most difficult role to identify within an organization. Again, these are people that are facilitating resolution of issues pertaining to that domain of data. And these organizations, these data domain stewards may or may not have the decision-making authority for that domain of data, but at least they're people that facilitate conversations in regards to that data across business units of the organization. And then there's another role called a data steward coordinator, where they work in a business unit, they know who the domain stewards are, they know who the operational data stewards are that reside in their area, and they're one of the kind of the point person for discussion, point person for communication with the data governance team, the data domain stewards, and the operational data stewards. There's another diagram that I mentioned a little earlier that shows the different roles and responsibilities associated with a non-invasive data governance program. Down here, and I'm going to see if I can kind of circle some of these things, the operational level, that's one that I just talked about a moment ago. Those are individuals that work within a specific business unit that have responsibility for that data within that business unit, but not necessarily outside that business unit. When we start to identify people that have responsibility for data across business units, that's the next level up, that's the tactical level. And those are individuals that have responsibility for a certain subject area of data across the organization rather than just within their business unit. I want to share with you some examples of that. Organizations oftentimes, the finance data steward or the finance data domain steward would often be the controller for that organization. The HR data steward may potentially be the VP of HR in your organization, but these are people that are really at the definition of production and usage of data of the same data but across the organization as an organizational asset. And organizations are not just a natural person to identify to be your domain steward, so oftentimes it's some analysis of who does what with the data and who the two people are for different types of data. And if there's already a person that you go to to answer your questions about a specific subject area of data, my suggestion is that they potentially could be the domain steward or the subject matter experts for the data across the organization. The Data Governance Council, we're not really going to talk about that in this session here, but the Data Governance Council is a strategic part of the organization it's individuals that represent the different business areas from their organization and they're the ones that make decisions if the domain stewards don't have the ability to make those decisions or don't have the authority to be able to make those decisions. So I'm going to walk through specifically what a data steward does in the next couple of slides here. First I want to just kind of highlight the tactical level and the operational level. So if our organization just identifies people to be the data stewards, you might want to differentiate between who are the data stewards specifically for the data within their business areas and who are the data stewards for the data that crosses across the organization. So that's the difference between the operational stewards and the tactical stewards or the data domain stewards. I mentioned that it would be great if we could identify and we could record who all the stewards are within the organization. And I've shared this diagram in previous webinars as well. I call this the common data matrix. In the common data matrix, all it really does is it cross-references the different sub-area areas of data that you have in your organization like customer data and finance data and it cross-references them with the different parts of your organization whether it's people in IT, it's people in corporate units or business units. So my suggestion is that you want to record at least whether the organization the operational stewards exist. If there's a change to a business role associated with a specific type of data, we want to know without without any guessing who people are across the organization that use their stakeholders in that data. And I oftentimes share an example where I was working with the credit card of a large bank recently where they needed to change the fee structure associated with their credit card. And they weren't sure of where the credit card data was being used across the organization and they changed it everywhere when they thought they needed to be changed and they got it 98% right. They missed a couple of different areas that were specific stakeholders in years of that data. And because of that, they missed out on $8 million of revenue over a two-year period because they didn't change the fee structure because again they didn't know where in the organization that data was being defined, produced, and used. So in this common data matrix where a row meets a column, you either list the people's names in the box or if you just put an X in the block it says this part of the organization, they are people that are stakeholders in this data and we need to identify who they are so we can communicate with them effectively regarding changes and things that are happening to the data that they defined, produced, and used. So it's very simple to develop one of these things. First what I want to do is you may want to define the different parts of your organization across the top. The next thing you may want to do is identify the domains of data and put those down the left-hand side. So in this example here I have customer data and I have finance data but I also have different sub-domains of data across the organization. So customer address data, demographic, financial data in regards to the customer. The fact is these domain stewards that look at data as a corporate asset or an organizational asset rather than a business unit by business unit asset, we need to identify who they are, we need to record who they are, we need to let them know what parts of the organization use the different type of data across the organization. And what could not leave these people here. So once you've defined your domains or subject areas of data down the left-hand side of the matrix and different parts of your organization across the top it becomes very easy for you to go to those parts of the organization and identify who are the operational stewards of data or are the operational stewards of the data in that part of the organization. And if there are we just want to make sure that it's recorded and that we can use that information when we need to to effectively govern data in our organization. So one of the responsibilities of the operational data stewards operational data stewards define the data that will be used by their part of the organization how that data will be used how that data will be managed the data producers are people that produce data as part of their job the data users can be absolutely anybody in your organization. So when we talk about operational data stewards the fact is there's even different types of operational data stewards within an organization. There's the definers the producers and the users and the accountability that go with the different relationships that people have to data are very vital in the role of how those stewards will be utilized. Some additional responsibilities for the operational data stewards they create or review data definitions they're responsible for the integrity and the quality of data definition they're responsible for producing, creating, updating, deleting, archiving the data that will manage all of those things that you see on this page here but most importantly the last two bullets that you see there those are typical responsibilities of the operational data stewards they're responsible for communicating new and changed business requirements to people that will be impacted they have responsibility for communicating concerns, issues and problems that they have with the data to the people that can influence change. So these are some of the responsibilities that the operational data stewards have but it doesn't answer the question of what do these data stewards do? And I'll give you a little bit of time talking to you about that. So now that we've defined what a steward is let's talk about what a steward does. So typically stewards act in one of two ways they either act proactively or they act reactively. Proactively is when you build the things that stewards do into specific activities that are already in place in your organization one of the examples I like to share is if you have a system development lifecycle methodology I'm not suggesting that you would want to go out and you would change the methodology what I am suggesting is that you want to make sure when you're going to utilize operational stewards in what part of the methodology and define specifically what they do during that step of the methodology. The reactive data governance activities are activities that are associated with solving a problem. So if you've got a problem we may go about resolving that problem and we may utilize the stewards a little bit differently than when we want to build what they do into the regular processes and things that we have in our organization. How do we recognize how do we assign our stewards? Well I would suggest that we want to identify stewards and we want to recognize stewards. First of all to apply them is just a matter of noting who they are and recording them somewhere like in a common data matrix recognizing stewards that's actually a suggestion that was given to me by the United States Air Force when I worked with them a few years back if we recognize people as stewards it sounds a lot more distinguished. It sounds like we're distinguishing their responsibility and again we're recording it somewhere you know assigning a data steward that to me sounds a little bit too intense so when you assign something to somebody they're obviously going to feel that this is over and above the existing work culture of their organization and oftentimes people react negatively to being assigned things when certain things when the equal amount of work is not taken away from them as well. So whether we identify, recognize or assign data stewards really depends on the approach that we're taking to governance. So this one slide in there real quickly because a lot of people have been have looked at this slide and said that this is kind of one slide that kind of summarizes what way the governance program needs to do and if we look at this real quickly on the left hand side we have a policy statement in the middle we have different principles that we may apply to the stewards and to the data in our organization and on the right hand side we have the dimensions of how are we going to measure whether or not we're improving the way that governance that the data is being governed. So obviously we want to be able to communicate some of these things with the people that we identify and recognize as stewards so we get a good understanding of what the goal of data governance is in the organization. Oftentimes it is to recognize data as a valued asset in a data governance program to clearly define accountability. Data must be managed for most organizations or all organizations to follow internal and external rules and data quality must be managed consistently across the life cycle. So again this is a slide it's kind of where I put it in the slide deck but it's there to help you to understand what are some of the basic things that we need to communicate to people as data stewards. The basis is what you see in the model there those are the primary principles of governance in a lot of organizations. So we're going to proactively get the stewards to do what they are supposed to do Oftentimes we kind of just build government into these existing procedures. So there are a couple things I'm going to share with you real quickly and I noticed that somebody had asked a question earlier in the session about the RACI diagram and getting people responsibility, accountability those types of things I'm going to share with you a tool that may help you to define those things. A system development life cycle methodology project planning one of the things that one of my pet peeves is that organizations call these things data governance processes. A risk that we run by calling things data governance processes is that people think that data governance interferes with what they're doing that it's going to be over and above the existing work that people do. Well my suggestion is let's not call these things data governance processes let's apply governance to things that already to processes and procedures that already exist within the organization. So the concepts of the noninvasive data governance let's talk about not giving people new job titles and recognizing that the majority of their work isn't going to change let's identify them and engage them according to their present responsibilities let's not create new tasks or time commitments but let's make certain that the appropriate stewards that we've recorded now into this common data matrix make sure that they're engaged in the appropriate ways in the appropriate tasks. I know this slide is a little bit difficult to read and I'm not going to really talk to the details that are in each of the blocks of this diagram but if you look at it down the left-hand side of this matrix some typical steps of a system development lifecycle methodology information gathering and assessing requirements planning the things that would be typical for most organizations as part of a system development or an application development lifecycle methodology across the top of this matrix we identify the different roles that are associated with our governance program whether it's IT roles data domain steward roles operational data steward roles and this is where we can document what a data steward does so during this phase of the methodology the different stewards have these different responsibilities that are associated within this matrix and again it's just an easy way of being able to view specifically what a data steward does and when they do it a lot of the organizations that I've worked with the first question that a person that's identified as a data steward has is well, how do I get involved? what do I do? how do I how do I get involved? how do I know when I need to get involved? and this data governance activity matrix kind of goes a long way towards addressing when the different people that have been identified as either domain stewards or operational stewards when they get engaged in the different processes in your organization again what we haven't done is we haven't redefined the methodology all we've done is really applied governance to the methodology and my suggestion is rather than defining them as all new processes let's take advantage of the processes that we've already identified and let's associate stewards with them here's another picture that I've shared with people throughout different webinars this is called the governance action plan addendum and if you look on this closely you'll see that there's six primary activities that a lot of organizations focus on when they're implementing governance they focus on resolving or researching information quality issues identifying and monitoring risk monitoring quality validating measures all of these different types of things and so these are six of the primary things that I see most organizations most of the processes that organizations apply governance to therefore engage their data stewards in their activities now if I go on to the next piece of the slide you'll see that for example if you would have clicked on where it says resolve or research information quality issues up would come into the box it says these are the specific steps and what we do to resolve or research information quality issues and these are the different roles of the organization we can identify who is responsible who's accountable who should be consulted who should be informed through all the different steps of each of these different types of processes that we apply governance to so we've already answered the question of what a steward is a steward shouldn't be anybody there are people that define produce and use data as part of their job but the question when do we engage them we can answer those questions by putting together either the matrix that was on the prior page or this matrix and we can really sell out for them if they've been identified as a steward when they're involved what they'll do what they'll have accountability for what they'll have responsibility for and so on so this is another tool a very simple spreadsheet I developed for a client some time ago where you could click on each of the different processes and it would give you a detail as to what the data stewards do as a part of that process so then you'd like to get copies of some of these detailed slides or some of these tools and templates please make the request of Shannon and we'll make sure that we add this to what we send to you in the next 24-40 hours another example of something that would again cross-reference a different role of the program with different activities so in this organization they define a bunch of steps for restructuring their data warehouse they define the different roles associated with their governance program and they document what each specific role does in each different step of this process of restructuring the data warehouse in some organizations they'll put how much time is expected when they get involved what decisions they need to make there's a whole bunch of different things that is not kind of a one-size-fits solution for even putting together this governance matrix activity but again I always tell people that if you're a consultant you view things in two different ways one is in a matrix that I have a whole bunch of different matrices and the other way is with the pyramid consultants can use pyramids and matrices a lot these matrices would really help you in your organization to be able to answer the question of what a data steward does and how they get involved I'm running out of time so I don't want to spend too much time on this but here's some other example of again the what they do the who does it and then the details of what they do during each of the steps of the different parts of that process so now we talked about that in a proactive way so we build governance into the processes and procedures that we as an organization can do we're going to take the reactive way of identifying what steward does if you have a methodology for how you resolve issues you can do the same thing that we did with the activity matrices that I showed on the previous pages we could document down the left hand side what are the different steps that we follow to resolve issues and then across the top we could put the different roles that we can identify when do we engage specific stewards in specific activities in regards to what a steward does and when they get involved so here is an example just from the previous picture that I showed you again it details the different steps for resolving research and information quality issues and you can take the different roles that you've defined as part of your program and you become very specific as to how different stewards get involved and what different ways do they get involved and what exactly do they do in our organization that I was working with recently they put together a very high level outline of what they do to solve issues they identify and document issues they ratify issues they implement it in control and here is the sub steps that are listed underneath the primary steps the different steps for resolving issues well the next slide that I'll show you is we take that same concept of the different steps to resolve an issue we identify again across the top of the matrix who different individuals are that participate in your data governance program and again we explicitly define what each different role does in each different part of the methodology for resolving issues so what it does is it takes all the guesswork out of who gets involved and when they get involved it takes all the guesswork out of what they do and in some organizations they even put an additional column off to the far right hand side which says what's the outcome of resolving these stewards in these specific steps of this methodology I actually gave a presentation a real world data governance webinar not too long ago on metadata governance and so the same thing can be applied to metadata governance if we define what the steps are of our metadata methodology down one slide we define the different roles across the top we can be very specific as to what the different steward roles do in the different parts of the metadata methodology so again it's just kind of another way of looking at what we've looked at in the previous slide but this one is more focused on the governance of metadata within an organization so about formalizing accountability once we've identified who the stewards are we've identified where the stewards reside within the organization we can start to formalize their involvement in different day-to-day or project type governance activities so what we're really doing is we're taking the different roles and we're being very specific as to what they do during the different steps and then the reality is that if you go to people and say well this is exactly how we want you to get involved in resolving issues this is how we want you to get involved in new projects and those types of things their first question is going to be well what do I need to do how do we formalize that how do we make sure that the people that are identified as stewards will know precisely what they're supposed to do during these processes so there's already people in your organization that define, produce and use data as part of your everyday jobs one of my suggestions is that we've got to know who they are we have a consistent way of identifying and recognizing them a consistent way of recording them and then a consistent way of using this information that we've recorded to engage stewards at the appropriate time something that I've heard referred to is the bill of rights getting the right person involved at the right time to do the right thing to get the right results all those types of things it's kind of like a bill of rights but that's really the idea of what governance is and once we've identified the stewards and we've identified the processes and we're going to engage the stewards that's taking 90% of the way there to developing a governance program in your organization if you recognize that there's already people in your organization that are stewards then we want to make sure that they're involved in the appropriate ways in different processes across the organization again just to go back quickly to the article that I wrote the last issue of the TDAN publication signers roles for becoming a data steward again a steward can be anybody being a steward describes a relationship the stewards aren't hired they don't need to have the title of data steward they don't need to be told how to do their job they just need to be told when to get engaged at the appropriate time I don't believe that the industry or public certification is necessary there's more than one steward per type of data in your organization and really data steward training those organizations needs to be focused on formalizing people's accountability and getting them involved in the right way at the right time in your organization so I kind of went through a lot of things really quickly here and pardon me again I'm feeling a little bit under the weather so my voice is cracking a little bit one of the things I wanted to highlight for you are the upcoming webinars the May webinar which is going to be a panel of practitioners the June webinar which is going to be interviews with fellow leaders from the DGIQ conference and it's for master data and my suggestion would be go to dataversity.net and you can see all the information about these webinars and future webinars in the real world data governance series or in any of the other series that dataversity holds the fact about it is that the data steward role really depends on the approach to governance that you're taking in your organization we identify what stewards do and when they do it and there's a good way of being able to document that I can't really go through in detail how stewards will be engaged in your organization but I did set you up with a tool that you can use to define the specific activities for stewards during specific projects and processes in your organization we put it into what we do we can operationalize our data governance program that way and at this point I'd like to kind of open up the floor for any questions if there are questions regarding data stewards and what do they do? Shannon? I have a lot of questions coming in and of course the most common question is if people can get a copy of the slides and just let everybody know and just to reiterate I will send out a follow-up email within two business days so by the end of day Monday with containing links to the slides links to the recording and everything else requested throughout the webinar and we had a ton of requests for the matrices and the templates that you use so if you could send those over to me I'll make sure include those as well in the follow-up email and just so everyone knows the follow-up email comes directly from me so if you don't get it by Monday or before you get in in your office on Tuesday just send me an email Shannon at dataversity.net and I'll be sure and get you all that and so and of course we have some great questions for you Bob I'm sorry some of the things that I want to mention is that if we don't get to all the questions I'll answer them in a separate separately and we'll include that in the email that we send to these folks as well Outly Great Awesome with that we'll get the questions started so how should a good approach to start the formalizing accountability I understand that creating positions for data stewards is not the good one how should it be My suggestion is that in organizations that acknowledge the fact that there's already stewards within the organization we might want to identify who were the people that we talked to in regards to a specific project as I mentioned before the people that are involved in the definition of the data for a data warehouse in fact be the stewards of that specific type of data in their part of the organization so before we go out and tag each of them and say you're a data steward start doing data steward stuff what we want to do before that we want to identify well who's already doing some of this stuff and let's record that somewhere so when we go to these people to discuss with them the fact that they're a data steward we could say well this is why we've identified you as a data steward because you are already defining data you're already producing data as part of your job and therefore what we need to do is formalize the accountability for all these individuals that have hands on the data are doing with the data across the organization so that would be a suggestion is take care of your existing activities existing projects and see who are the people that we engaged in those projects and more than likely those are going to be some of the data stewards and you mentioned the question Laracy earlier but let me ask the question just to make sure we didn't miss any points from the questioner isn't more difficult to form accountability if there are more than one person as a data steward for the same data I think in some ways it might be a little bit more difficult to formalize that accountability but the reality is that there are multiple people in the organization that are stewarding the same data and we want to document that and we want to record that and so what we can do is if people are entering data into the system as part of their job we want to make sure that they understand the impact of how they are entering data into these systems so in fact there may be multiple people in an organization that are entering system entering data into a system but they all have the same accountability to make sure that the data that they enter into the system is accurate and appropriate so yeah it might be a little bit more difficult to formalize the accountability of multiple people the fact is there's another type of steward that I talked about which is the data domain steward and then there are people that have an organization and typically you would only have one of those or maybe two of those who are the decision makers for that data across the organization so you have to understand the concern but the fact is we it's just something that we need to deal with because we should acknowledge the fact that there are multiple people that are stewarding the same data across the organization perfect and if people are not identified as a data steward for a particular data domain so when it comes to defining a particular data domain attributes and their usage so the the questioner would like to hear your input on what to do in that situation I'm not sure I took a question out of that but the thing we want to do is we want to identify people that have their hands on the data and we want to record that somewhere so the fact that there may be numerous people that are defining producing and using the data across the organization is fairly typical in fact it is consistent across every organization that I've seen so part of the governance program and part of the responsibility of the domain steward and the people that are running the program is to age the appropriate people at the appropriate time so again I'm not sure that answered a question I'm not really sure I saw the question in there exactly the what should the data steward do should they care about the new customer that is being recorded into the CRM system should they care about the data model of the new application that is in development phase should they care about DW InfoQ the answer to all those questions is yes they should be concerned about all those things but the fact is they may not be involved in the data modeling they may not have the data entry they may not be involved in interpreting reports and using reports for their jobs so they should have formalized accountability for each of the things that are related to the relationship to the data they may not necessarily be concerned with what the data model is going to look like if they don't have any input into the data model unless they feel as though they should have some input into what the definition of the data should be the individuals that are identified as stewards should be concerned about all those things but most specifically the things that they are specifically involved in. Perfect but what if one is labeled as operational information steward who will do this huge work of taking care of the data quality well there are some people who have been identified as being the operational steward you don't necessarily the people that are going to be involved are the you know are the people that need the people from the appropriate parts of the organization that have some input into how specific issues should be resolved how specific they should be defined so we don't we can label them as information stewards or data stewards and yes they will have a large amount of activities but the activities that they'll be involved in so again we don't want them to feel as though this is over and above the existing work effort of the organization we just want them to know what the appropriate way is to behave in different states of different products and processes and procedures. Perfect time for one more question but as Bob mentioned if you have keep the questions coming and we'll be sure to get you written answers in the follow-up email just so to that let me get to the next question here so just a line of lines and from the same question but no one is doing the work of this role is there any other way of doing it otherwise assigning the role for someone else? Well it will be a lot more invasive than the approach that I suggest and in fact what it takes in your organization is to assign people to be data stewards that all means do it there's not a one size fits all solution for data governance so if it requires that we go out and assign people and that we're going to evaluate them based on what they do and how they get involved then by all means do that but what I'm suggesting is a less invasive approach where we're really just identifying the people and we're going out to them and saying this is how we want you to be active this is how we want you to be engaged and oftentimes people will look at it and say hey I'm already doing that already and so this isn't going to be that much over and above the interesting work that I presently do so my suggestion is that we try not to assign people we try to identify and recognize people as just a matter of course it will really have some impact on the way that your governance program is accepted within your organization Bob thank you so much we are right at the top of the hour and we just have so many questions I'll make sure and get those to you and get answers out to everyone thank you everyone for such great interaction in these questions and a lot of comments just about how great and useful this information is so thank you for the quality education for everyone and we really appreciate it and everyone thanks so much for attending this was a great great webinar so Bob thank you you know we like doing these things and I look forward to doing the one next month and I hope everybody will return everyone will thank you very much again I'll get the pop email out to you by the end of day on Monday so let me know if you have any questions in the meantime Shannonatdativersity.net and in the follow-up email make sure you have all Bob's contact information that you see on the screen there as well as all the links to everything have a great day everyone thanks for attending thank you


We told you guys that we actually managed to snack Diego to come perform in Timothy D'Right College, Agale, for a college tea And we're talking Diego from Costa Rica. Like literally he's never been to America before and He's here right now. I haven't seen him yet. He got in late last night. He's actually staying in one of the guest suites in T.D. Super nice right by the way. Oh my god, the guest suite is amazing, but he's there right now. Hopefully he's awake He got in at like 1 a.m. I wasn't here, but I cannot wait to see this guy and hopefully we'll look at his reaction He's a character. Absolute character Here with Diego. It's finally here. It's his first time in the United States I think that is it for less than a day and it's insane. I I'm getting New York. That's something you're not ready to literally And now I'm here at Yale. Everything is Like take like Harry Potter. I feel like Harry Potter. I miss magician. I feel pretty comfortable Awesome, we're headed to Barry brunch right now highlighted a year So I just realized I'm talking about this whole Diego character and depending on which vlogs you've seen You may or may not even know who he is Diego runs the magicians without borders program, which is a Really really great NGO. He runs it the whole program in San Jose, Costa Rica and basically we've been Torring with him through like the all-magic society for like the past two January's two years ago We're in Costa Rica this past January. We're in Colombia. We're hoping to go somewhere cool next year as well Basically, we just we tore around we perform and we we teach magic to two kids that really need it He doesn't just do that though. He's literally one of the most booked corporate magicians in all of Latin America super successful and Honestly, just an incredible performer like what like he is absolutely hilarious and the fact that he did such a great job just performing like In English like not even his his first language. It blows me away So what's absolutely wild is one of the coolest things about Yale is the fact that I could go me and Jake We went we met with our head of college. We're like, hey, like we know this really great magicians his name's Diego He's done a lot of great work with kids teaching the magic in Latin America and running this whole program Like we'd love to have him come up to TD for a college D and she was like Sure, like give me the details. Let's figure it out. Let's make this happen. So literally what you're watching right now is Diego His first time ever in the United States It's it's insane. We got him to come to TD and perform like and he was at Yale for an a whole entire week And I wish I could have gotten more footage, but honestly, I was just enjoying his presence so much It was it was incredible. So as part of Diego's visit He actually ended up performing a fool like hour-long show in the TD dining hall obviously out of respect for him I'm not gonna put those those full routines online. Those are his and everything, but I will Play a little reaction reel of all the the crazy reactions first tricks just to give you guys a little idea Anyways, this was a pretty busy week not only was Diego here But it was also Bulldog days which is kind of the it's the visiting student days for all the kids It just got accepted to Yale they come flood campus spend a couple days living with some current students and Having a great time and getting to see what Yale is really about So I was actually hosting two students at the time and it was super busy So the rest of the vlog is pretty much me trying to figure out how to balance all my activities with Bulldog days with Diego visiting so here you go. All right, so I've been having a little bit of a crisis because I told myself I was going to keep filming and Document the last couple weeks at Yale like we live two more weeks of classes And I keep having this obsession with trying to create a like an entire cohesive story with the vlogs And as soon as I literally stopped doing that, it's like soon as I like I miss a single moment It's like the entire vlog just falls through and I like don't know what to do So I've realized I think I'm just going to kind of do little bits of like snapshots throughout my day And try to put those together and maybe do some narration in between I don't know I just want to capture as much as possible because I'm realizing that it's the memories that really count and It's not necessary to have like one entire cohesive storyline throughout an entire day just to put up a video When hey I could cover like multiple days in a video, you know, um, so I'm thinking about doing that Anyways, it is currently Monday, it's literally the Anyways, it is currently Monday and I've been super busy because it's been the first day of Bulldog days Which for those of you that don't know is kind of the the little three-day period when all the kids that got accepted Yale actually come and visit and stay with Students so I actually am hosting to Prefrosh their stuff is all right there. They're out doing Prefrosh things. They have a lot of events going on tonight. So I'm sure they're having a good time But I'm in here stressing we have like an r2c bag drag tomorrow for field training So I have like all my stuff packed up over there I really need to get to bed because I get up at 5 a.m. But hopefully I'm gonna keep this going as quick as possible But hopefully I'm going to keep this going as long as possible Exposure on my camera is all messed up But it should be interesting it should be a good couple last weeks And I'm gonna try to film as much as possible captures as many of these moments as I can and hopefully Hopefully you guys enjoy Yes, so currently I am working on my military history and for tomorrow morning. I actually have Section tomorrow morning after Air Force PT. So it's just 50 minutes of like my section which is like the 12 12 of us now, I guess just sitting around a table Discussing the readings is actually pretty cool because our military history professor is literally an absolute legend Paul Kennedy Crazy dude. Oh my god. His lectures are so good and literally, you know, you know He's a good lecture and you know, he's a good professor when three out of the nine books you have to read throughout the semester are Written by him. So this is rise and fall the great powers by Paul Kennedy. It has it's probably the book that we reference the most Like I said, there's like nine different books. We have to read. Obviously, we're not reading the entire thing We just have little chunks that we have to read each week. Well, it's around like a I don't know 160 ish pages of reading a week a lot of it's scamming, you know, you can't I don't have enough time to literally read every single word and taking notes on everything but normally you kind of put together what you learned at the lectures the readings of the books and Try to draw the big ideas. So I'll be working on that for the next couple hours and Maybe a little time lapse. All right, so I literally just got back from the Bulldog days extracurricular bizarre so for those of you that don't know it's like Pretty much maybe I'll throw up some clips or some footage or some pictures Something right now, but pretty much every club and every organization at Yale sets up a booth in the Landman Center at the gym and You're all just trying to sell yourself to the pre-froshen show all the cool and interesting things that are available to do at Yale And it's it's an absolute time And I remember when I was doing it as a freshman and make a pre-froshen everything and it was insane And once again, you know, I was there working the Magic Society booth working there for the entire time I think I performed 37 magic tricks throughout the time I was there I met a ton of pre-frosh took a ton of pictures with you guys shout out to everyone if you're there And you took a picture with me or you came and said hi comment down below Let me know how you guys are doing because it's great to meet you all and it's kind of weird, you know, like me just not being the type of person that like I Don't know. It's just weird when so many people know who you are It's definitely something I'm still trying to get used to but you know, it's it was a cool experience regardless And you don't get that very much but anyways, I'm back and just because it's bulldog days and I have a ton of Commitments does not mean that the grind does not stop because here I am working on a CS p-set basically it is a No, I can see my reflection interesting basically it's a it's for AI. It's a P-set on Q learning, which is actually a form of model free Reinforcement learning where it's it's very popular with like video games basically. So we're actually doing a P-set for Pac-Man right now And we did a piece of her Pac-Man early in the semester, but it was all based on like searching and everything This one's entirely Q learning. So we have a ton of skeleton code that's provided for us But I have to fill in a ton of like pretty much every function that actually has to do the Q learning It is really loud outside So hopefully we can basically code an AI for Pac-Man They can go through the maze collect all the food avoid all the ghosts and it kind of like basically the way Q learning works it's like a series of different paths to a solution and depending on it basically randomly assigns like like a path and then you have the you have the Pac-Man character kind of go through the map and as he's Collecting food and getting points or he's following a path that allows him to collect food Basically each state and eat each each state and each action is assigned a certain Q value of like Basically positive or negative of how like good that path is And basically you base once you find a path that works it continually like develops and develops you keep updating these Q values until basically You go through and you take the max of every single one once It's kind of ran enough iterations and you have find like the exact like kind of best path That will allow it to win the game and get the best score. So it's pretty pretty interesting I'm really like kind of fall in love with this whole machine learning Part of the class so far and hope to share a little more and maybe I will show you guys once I get it up and running still got probably Another four to six hours of work on this because I'm still trying to completely wrap my head around the whole algorithm and everything But you know, it's a good time and I love kind of sharing little bits of CS and everything with you guys So hopefully that made some sense and I'll catch you guys later So I'm on my way to grab dinner with some people in TD probably I'm gonna go grind and butter you can also like speaking like today is literally the first day I've been able to wear shorts and t-shirt and it's just absolutely beautiful outside.