I've mentioned a couple times recently that I've received comic books or magazines in the mail that haven't been packed properly. They've been packed actually in such a way that damages them or endangers them. I'm going to show you how to pack a comic book or a magazine properly. All you need is your comic book in a plastic bag with a backing board. If you don't want to bother to get one of these comic book plastic bags with a backing board, you can use a sandwich bag. Just remember not to use any packing tape that touches the sandwich bag. As a matter of fact, don't use any packing tape that touches any kind of plastic bag because packing tape is made to stick to dry cardboard.  All you need are two pieces of cardboard that are larger than the book or the magazine. Give a good inch around the edge to protect the book from being dinged against something. All you have to do to keep the book from slipping around is to take a couple of pieces of scotch tape again not packing tape just scotch tape. This is plenty good and there you go. It's not moving around. Sandwich the cardboard and now take your packing tape. Take the edges of the cardboard together so that the edges are taped together tight and then tape the opposite edges together again tight so that they're sandwiching the book. This is all you need to keep the book from sliding around. This is all you need. You don't need to pack it in bubble wrap. You don't need to put it in a box. You don't need to wrap it in multiple grocery plastic bags. I've seen that happen. All you need is cardboard that's plenty large enough so that the edges of the book aren't sticking out so that no packing tape is touching the plastic or the book. And then slide this whole thing into one of these priority mail envelopes or a large plain envelope. That's all you need. And when you're packing a paperback novel just slip it into one of these little padded envelopes. That is all you need. You don't need anything else. Okay next time.


Hello and welcome my name is Shannon Kemp and I am the Chief Digital Manager of Data Diversity. We would like to thank you for joining the current installment of the monthly Data Diversity webinar series real world data governance with Bob Siner, and guest speaker today Chris Paskins. Today Bob will be discussing data governance and data science to improve data quality sponsored today by Alation. We have a couple of points to get us started due to the large number of people that attend these sessions you will be muted during the webinar. If you'd like to chat with us or with each other we certainly encourage you to do so. And to note zoom defaults the chat to send to just the panelists but you may absolutely switch that to chat with each other. And for questions we will be collecting them by the Q&A section or if you like to tweet, we encourage you to share highlights or questions by Twitter using hashtag RWDG. To find the chat and the Q&A panels you may click those icons in the bottom middle of your screen to activate those features. And as always we will send a follow-up email within two business days containing links to the slides, the recording of the session and additional information requested throughout the webinar. Now let me turn it over to Miles for a brief word from our sponsor Alation. Miles, hello and welcome. Thank you. I'm really thrilled to be with everybody today and to share a little bit of perspective that will blend into what you're going to hear from Bob today. So I'd like to talk a little bit about data governance and data science and what we're seeing out there when we talk to CIOs and CDOs and other data leaders. One of the things that I can't stress enough is that data governance really does matter. It matters to data scientists. It matters to those who prepare data for them. And the key things we find that are really important are that it delivers the kind of agile modern data architecture you need. So if you haven't fixed your data issues, in fact, one CIO recently said in one of the CIO chats that you don't want to take your mess if you're putting it up in the cloud from where it was to where it is, you need to fix the data before it moves. So obviously, that implies the importance of data quality and trust, the need as we increasingly create new repositories of data to govern it, protect it to ensure we comply. And as well, we want to do things that speed up the process of creating analytical models and I'll talk about that in just a little bit. Obviously, what we're all aiming for more agile data processes and the analysts have recently coined a term called data ops to reflect on this and to reflect on the role of data governance. I'm pulling here from a report that Tom Davenport did a few years ago, but it was really interesting. Describe the issues with data. You know, first of all, where is it, what do we know about it. The second how much time these analysts spend just finding things so if it isn't discovered if it isn't prepped, it's very, very hard to actually make use of it in fact, as a Kirk bone. A lot of data scientists are really better labeled as data plumbers. And, you know, obviously proud flower has found similar things to, to Tom Davenport, in terms of how much time is actually spent working on data rather than making data into analytical models, which is obviously the end. So, the big opportunity that large legacy organizations have is they have a lot of data, and if it can be put together as my friend Jeannie Ross likes to say, into a nice neat package they can win against the startups that are disrupting their industries, but they need to be able to get it into a nice neat package. So, you know, if you're going to do effective data governance and you're going to hear more about this from Bob, a couple principles that we think are important. So obviously, being more people centric. I can't tell you how many CIOs have said they hated data governance, because they had to go find the stewards and then force them to do the work that just doesn't work so a new less invasive approach is needed. Increasingly, if you're going to find these people, you want the process to be as autonomous as possible. You want to basically take the work out so that you're using the brain power, but not creating another job for the data steward which obviously, in many cases has an important role in the business. Increasingly, continuous improvement should happen. So each new wave needs to be easier and easier to do. And one big concept that Bob and I like to agree on is that data is not a one and done. It's a continuous process and there was some research done a few years ago by Forrester that showed the data degraded at like 10% per year. If we can do this, however, we can save our businesses in a world of disruption where the life of public corporations gets less and less. Data is how you win is how you win against disruptors. And so there's an important role here to play in terms of what we're doing in data governance, it really does matter. And with that, I'd like to turn it back to Shannon. Thank you so much for this. And thanks to Lation for sponsoring today's webinar and helping make these webinars happen. If you have any questions for Miles or about elation, Miles will be likewise joining us for the Q&A portion of the webinar at the end. And then let me introduce to you our speaker for the series Bob Sinner Bob is the president and principal of KIK Consulting and Educational Services and the publisher of the data administration newsletter teedown.com. Bob specializes in noninvasive data governance data stewardship and metadata management solutions. And with that, I will give the floor to Bob to start his presentation and introduce his guest speaker Chris Bob hello and welcome. Hi Shannon hi Chris. Thanks Miles for a great presentation. I think there's a lot of synergies between the things that you said, and the things that we're going to talk about today. But today, I am very fortunate to have a special guest to join me. And I'll tell you a little bit about Chris in a minute here, but this is an important topic one that we have been looking forward to presenting on for for a while now. And certainly data science is something that's important to everybody. A lot of folks are looking at data governance to help to improve data quality. Let's look at ways that we can marry up data governance and data science or at least bring them closer together with the focus on being able to improve the quality of the data in the organization and before I get started. I just want to share with you a few of the things that I'm involved with. And these are literally just a few of the things that I'm involved with. And as you know with this monthly webinar series. Next month is going to be another great subject where I would hope that you can walk away from that webinar with an actual data governance framework completed so we call it do it yourself. Data governance framework. I talk a lot about non invasive data governance I'm sure that will at least touch on the subject a little bit in today's webinar. I'm speaking at Dataversities upcoming event in December the data governance and information quality conference DGI queue. Like I said I do a lot around non invasive data governance and metadata governance, you can go to the Dataversity Training Center and find several courses and learning plans that I've put together. In the data administration newsletter and kik consulting two of the businesses that that dominate my time. And last but not least, I am recently a an adjunct faculty member at Carnegie Mellon University in their C data, oh, chief data officer program. And with that I'm going to let Chris introduce himself here in a second but you know Chris and I have been have worked together, we worked together years ago. As a client consultant relationship, and Chris is still somebody that I go to all the time when I have questions about how to implement effective stewardship globally, and Chris has been really successful at doing that for Western digital. He focuses a lot on data quality and with that Chris anything else that you want to add to my introduction here. Well, thanks, thanks Bob for that great introduction. Hello everybody. Thanks for joining this is really a passion of mine. Data governance data science and data quality all mesh together. I hope this discussion will be very fruitful. Officially, my my title is global head of enterprise data governance data quality. My unofficial title title is director of cat herding. So as Bob was was kind of explaining, we have a very successful data stewardship program here we have over 1200 data stewards that are named and actively engaged in processes data processes in Western digital. And we are currently a very active and aggressive data science program specifically for data quality. So hopefully guys can get a few key tidbits out of this and looking forward to the discussion. Okay, thanks Chris and like I said before, great to have you with me today. Here as I always do I kind of run through the topics that we're going to talk about in today's webinar and so I know that when Chris and I talk we could take any one of these subjects and stretch it out for the whole webinar, but we can't do that today. We're going to be shorter and succinct and to the point with some of the comments, we're going to talk about the first of all, the relationship between data governance and data science. We're going to talk about how data governance can leverage data science and make use of data science to help to improve the quality of the organization and I think you'll see that in some of the things that Chris talks about. We'll talk about the data scientists role and data governance and then I'm going to turn it over to Chris to tell you a little bit about how he sees the data scientists role participating in his program. His role in improving data quality as well and again that's been the focus of the stewardship that Chris will talk about and then to wrap this up we're going to combine the three topics together, and we're going to talk about data governance and data science being used to improve quality so we're going to kind of bring these three together as that tour to force that might be really beneficial, or we hope will be very beneficial for your organization. But the first thing that we want to talk about is just kind of making that relationship between data governance and data science. And one of the things that I talk about all the time. And then I write about is how data governance really focuses on people in fact somebody told me many years ago we should call it people governance, instead of data governance because we're really governing people's behavior. And the definitions that I'm sharing with you of data governance and data science and data quality. You'll notice that there's a behavioral aspect to each and every one of those things. When I say that data governance is the execution and enforcement of authority that comes down to people's behavior and how they act with data. Data governance practitioners need to make certain that we recognize that people are already doing a lot of the things that we're going to ask them to do. And I expect Chris will be able to bear some of that out when he talks about his data stewards. But we need to focus on people's behavior because if we can get the right people to do the right thing in the right way, we will be very successful with how we govern data in our organization. So kind of the bottom line here from these three definitions and some of these definitions are really a mouthful is that data science and data quality really require improvements in people's behavior managing data. And it's really important to look at how or what approach are we taking to implement governance as we move forward in our organizations. And Chris, what do you think about this? How have you drawn the relationship between data governance and data science at Western Digital? Sorry, I was on mute. I always go back to a more, how do I get the business involved, right? Because here we talk about data governance which, you know, just the word data governance, people already start to take a step back. But right now, most companies are all about data science. So this is a great leveraging point. But how I look at this and how I explain this to a non-technical business person is it's like running a race. The outcome will be a direct reflection of the training and preparation that's been put forward, right? So the outcome, of course, we want are predictions and prescriptions for data quality, right? And then the training and preparation is what you put forth into the data in terms of quality before you even attempt a model or something of that nature.  You have to train a lot. So putting a little bit of analogies together about setting yourself up for success, your data science, your data, you know, analytics program success is really what the business value is and what it should be. I also expressed to them that it's really not a luxury, right? There's a lot of companies and businesses, like I said, embarked in this great thing, data science, and they're going to get so much out of it and then come to find out that, you know, it's hard to do to get the great business value out of. So we also like to stress that, yes, data governance does a lot of great things for an organization, but it also helps to ensure that your data can be used and cultivated to its full potential. And just a quick fun fact, I got into data quality because I was a data scientist in the high tech manufacturing world and my data quality wasn't up to par in my programs weren't as successful as I like. So I now have the best of both worlds and doing both. And I can kind of explain and express that to the executives, to the engineers, and that's what really helps with that. So, so Chris, when you say that it's not that data governance can't be viewed as a luxury.  Data governance is more bland and, you know, we need to convince people get past the why and get to the how. But, you know, what did, what did you experience, did you experience that people did not view data governance as being a necessity? Absolutely. I mean you're always going to have, matter of fact, the majority of the organizations or executives that just have not been exposed, right, because they just turned to a data team IT team or analytics team and say, give me what I need and then, you know, they snap their fingers and it's supposed to happen. So, you know, a good example is as we were, we embarked on a major IT transformational project at WD. And it was really hard to get the foot in the door with that transformational product project as a data governance initiative. So, what we had to do is I had to work with the separate reporting teams, business teams, master data teams in this transformational project and say, does data coding data governance itself, but very particular, you know, have an impact on what you can deliver during this multi-million dollar project. And the answer I got was yes. So, as we had those conversations, you know, we were able to find out what exactly was needed that we can provide not from a data quality perspective, but from a good data governance practice perspective and processes to help them fulfill their deliverables and really lay the groundwork for what's happening today in the company. So, it sounds to me as though not only is data governance using data science to help push its discipline, but your organization is using data science to help to push data governance in the organization. And that's a really cool thing. If we think about really trying to marry these two or at least bring them together so that we're at least in some realms talking about them in the same world. So, the next thing that we're going to talk about and we've got several subjects to get through here is how data governance can utilize data science and leverage data science to improve data quality. And just real quickly before I turn it over to Chris again, you know, when we look at our organizations, they're already investing a lot of money in data, they're investing it in data science and informatics and machine learning data mining big data, whatever is the, the big hot technology of the day, even data catalogs and metadata management organizations are investing pretty heavily in a lot of these, these disciplines. And we need to recognize that there's a common thread between these disciplines and that is the data that is going to be necessary to do informatics to do machine learning data mining, all of these types of things. And really data governance in at least in a lot of organizations I know they're focusing on getting people just to trust the data, whether that's through metadata in the catalog ability to find the data, spending less time wrangling data like I'm talking about, and getting people to really start to leverage the data. So, I've, I've pointed out as a very strong purpose statement for data governance in some organizations is the phrase to use data to use strategic data with confidence because if we can identify what strategic data is, and focus on that first with our governance program, and we can deliver confidence in that data. That's going to be really important. And certainly our organizations investing in these things. There's a lot of organizations that want to lead in these things to. And so they're recognizing that it's really not enough just to label people as data owners and some data governance programs. They do focus on the data owners and that makes me kind of cringe a little bit. Because I don't like the term owner, Chris can tell you what the term steward means and how he's applied it, but it's not enough just to know who the people are that own the data, we need to get people to be engaged in how they define produce and use the data. And, and so that's critical. We want to make certain that we can use governance to leverage data science to improve quality by taking advantage of those types of things. Senior leadership certainly needs help understanding what governed data looks like versus what ungoverned data looks like, and they need to focus on, you know, really being able to tell the difference and seeing the value that comes from it. Chris, I know that you've taken, you spent a lot of time focusing on these types of things. Maybe you can share us with us a little bit about how you're leveraging data science and focusing on data quality. Absolutely, thanks Bob, you know, like I said before we have a very aggressive program for data science to improve data quality for this exact purpose and here are the some of the things that my team is looking at. And you know what, not just my team but there are a lot of companies startups and even as well established companies that are using data science, particularly for data quality but here come some of the areas that my team is looking at. First is anomaly detection, right. It's my data fresh, is it complete. Those kinds of things you can directly translate data quality dimensions into anomaly detection with very specific models for specific data pipelines. And those are the kinds of things that will let you know, you know, artificially if, if things are going well. So that way you don't have to write 10,000 business roles. You know you can use models to help you with that, that which leads to, you know, the next one which is, okay, I have a pipeline that has 200 attributes or 200 fields whatever. What should I care about, right.  But what if there's some, some hidden things that we don't necessarily see or the SMEs don't tell us about. We can use modeling to help us prescribe rules that we might be interested in. And then we as SMEs and experts take a look at those rules and say oh yeah that makes sense let's let's measure this. The next one that we're currently working on is when a data scientist deploys a model or trains a model, right. That model is using data to train. If that data quality degrades over the life of the model, and it is now performing, you know, affecting the performance of that model. The data scientist want to know is the data quality in my training set the same or better or worse than what my my current production run is the same. So this is really big and, and my team isn't the one doing all these model data scoring. All of the data scientists and the company are now coming to me and say, build me a platform where I can do this. The next one is pretty pretty new is impact risk analysis right our supply chain procurement teams use impact risk analysis for their supply chains right. We can do the same thing for data supply chain. If we have a great catalog where we can see the data's movement, we can then start looking at if things are going down or not being refreshed and there's a critical need in the business. How do we reroute things in order to get it back up or an operational. These are the kinds of real things that data science can leverage to improve data quality. You know, I really love the one of model data scoring and being able to say is the data that we're using now for my model the same as the model as the data that, or is it the same quality or is it better or worse quality. And certainly data scientists want to know that, and a lot of that information is available through metadata and information that you'll collect in your catalog. We need to form more formally collect that information and make that information available to data scientists. So they're having that that higher level of trust that I spoke about earlier. I love to see this. These are some great examples of how you can use data science to really focus on improving the quality of the data. Let's spend a couple of minutes talking about what the data scientists roles are in data governance because we're talking about, you know, again using data governance to improve quality using data science to improve quality. And when I talk about roles and responsibilities for data governance programs and I do that quite a bit. You may recall that I, I talk about data governance partners or if you haven't seen it yet, please go look for other real world data governance webinars on roles and responsibilities, but I have the role of the data governance partner. The data governance partner is parts of the organization or functions within the organization that are already governing they're not necessarily governing data, but you've got project management that's governing projects. You've got finance and they're a partner plus they're a business unit, but they're governing the the finances of the organization so I think that data scientists just like it, and they don't always reside within it. And he is also a partner of data governance, we're not here to tell them what to do they're not here to tell us what to do at least we hope that's not the case. We've got to find ways to work together. And if we can bring the power users and the data scientists into the data governance fold and really understand what they're looking for in terms of quality of data. You know, we can really govern the use of the of the data analytics or at least help the power users and the data scientists to govern the use of that. The data scientists are extremely important in the fact that they require confidence and so if we know and we're having conversations with them. I don't know how often, you know, in the days when we were all in the office when you go into the lunch and you find your data scientists sitting with your data governance folks, you know what we need to build relationships with the data scientists, we need to build relationships with the data stewards, so that we can truly understand what their requirements are, and then we're not a data governance program that's shooting at targets of things that haven't been defined. And if we can get these folks to work with us in data governance to provide requirements for the analytical of the data in the organization, we're going to we're going to find that we can strengthen that bond, and we can really provide to them, things that are going to make their life easier. Chris have you done that in, in some of the situations with your global data stewards have you engaged the stewards and the scientists to see, you know how can data governance help us to do a better job of, for one example, improving data quality. Real quickly on that and then I'll kind of go over these these bullets. We have at WD, a fairly large in our global operations function, analytics and automation initiative for the next couple of years. They actually reached out to me and said we need good data help how do we do this. So now my lead a functional track, foundational track for that initiative, and I tie my value and data help directly to their proposed ROI and it's, I can tell you, in the hundreds of millions of dollars of savings over the next three years. So, with that, I do partner very very close with my analytics and data science community because what they're doing for the company to provide that tangible value. They came and said, I need good data quality to make this happen so that's a very good leap forward in terms of relationship building for for our program. But, you know, some in the cases of data scientists role in, you know, data governance is kind of changed over the last, I think, couple of years but in a lot of cases, those data scientists role can be overlooked inside the overarching data governance umbrella. And, you know, I've gotten a list of excuses and explanations. It's not their role in the company. They are not data stewards they don't have time to do this, or they don't have a direct impact or influence on data quality. But you know, the fact is that they're usually aggregating data from several different data domains, and they might claim that they don't have any direct influence on that source data that they're using. But really the truth is that a data stewards to be anyone who has a relationship with the data right, and this includes of course data scientists. In a lot of cases, data scientists can see data issues that arise across domain, they're in the ideal role to make a huge impact. Now it might be a little bit late in the game, but they see data that's being stitched together, across many different domains, and that's the first time there's an opportunity to look at the data in that way. So they can actually give great feedback to the source data owners data stewards to say hey, in order for this program to work out we need better data quality so they are actually a very key role in our data stewardship program, since the company relies really heavily on their expertise to provide business value. Okay, you know what I love what you were saying about where the scientists are in that perfect role. Right, if they're, I mean you I always talk about I break down the actions that people can take with data down to they can define data they can produce data, and they can use data and typically everything falls under one of those three and I've challenged people to give me a fourth or a fifth, and I like that I've kind of found a way to be able to slot everything under those three well data scientists are certainly users. In fact they're power users and they're even power users on steroids I mean they, I love when you talk about how they see a lot of the data problems they see where the data is stitched together because, again, these are scientists that are looking to solve these issues with the data that we have. So I don't know maybe you can even maybe go a little bit deeper in how do they, you know, what kind of things do they see that might not be seen by somebody who's not in that role. You know, it's great great kickback to me so so usually in our global operations this was a manufacturing these are factories that are producing high volume of data high high number of parts and you know with with a lot of things going on so probably in two three years ago, we were using a fraction of the data I would say five to 8% of the data being produced in order to take some decision on. Now we've calculated that's more like 25%, even even collecting at a higher rate. So, we can actually see and do things on the manufacturing floor real time with streaming data that we weren't able to do before and these data scientists are the ones that pick that data source data out of the stream will stitch it. Data engineers will stitch it put it all together and provide data to the data scientists, data scientists are paid to look for needles in the haystack. And they find those needles very regularly when the data quality is good when it's not they're finding pins, not needles. So it's kind of it's kind of, you know, they're in that cross section that they're paid to look at data and use data when people usually aren't looking that deeply into the data. You know what that's something that I really hope people will take away from this webinar because if you are in the position of implementing a data governance program, and you've got data scientists or even starting to have data scientists within your organization to get in touch with them, give them a role in your program. Chris is a perfect example of how data scientists can really help. And because they know the data probably, or they need to know the data in order to do the function of the data they need to, they just need to be a good partner of data governance and there's certainly a big role for them. The same thing that when I talk about data got scientists role in improving data quality. I mean, the, they are quality partners, you know, I think I need to go to my next slide here, or did I. Yep, that was your next slide. That was my next slide. Yeah, sorry about that, folks. I'm going the wrong direction here. Right there. Right here. Okay, so we talked about data scientists role in data governance. Well, the fact is that, you know, just as Chris was talking to their partner in data quality as well, we need to engage them. And that can help us to determine where the pins are versus where the needles or the things that we're actually looking for, or what they're looking for are, we can certainly leverage a lot from them. So, again, as I mentioned when they're partners of data governance, you know, their data quality partners as well. So I don't know if you define if organizations define sets of roles and responsibilities specifically around data quality, but if you did I would think that the data scientists would be a very important role, just even for the reasons that Chris shared with you. They govern the use of the data, they define what their confidence requirements are in the data that they use, you know, they do all the same things for data quality that they seemingly did for data governance and so it makes sense that if you're even if you're doing data quality without doing data governance that we need to be thinking about bringing the data scientists into the fold and like I said before, if there's one real important takeaway from this webinar is the importance of sitting down with your data and understanding, you know how they use the data what will help them to use the data better, what will we, what you can provide to them, so that they can improve their level of quality in the data. So maybe Chris you can share a little bit of how you've gone about that in getting the folks because I know that a lot of what you've been focusing on is the data quality and the things. So just to expand a little bit on the previous slide, before I start actually this one. We don't we don't have a true enterprise data governance team where those 1000 data stewards report to me right, I have a very small, small team of people and, but I have experienced people we call them data governance program managers that work with the stewards that are embedded in the data. So, saying that I kind of Jedi mind trick them into creating a data governance program right, we focus on data quality, but you know in order to get data quality you have to have some processes in place. Then you got to have some roles and responsibilities around stewardship and those processes, and then you can back into policies, you know that way doesn't have to be start from a policy and then try to implement sometimes that never works. And break it down with, with, you know, data scientists are look I'm a very, very pragmatic very practical data science is a wide a range of disciplines inside data science so I look at building the architecture pipelines right we have analysts, architects engineers. And those have a direct impact of data quality because they're building how the, the actual statisticians and analysts are going to use the data, right, so data quality built into the pipe, not bolted on later is very, very important in our program. And using the data, of course, once those, you know, architects and engineers have built the foundation, and then we can safely provide the analysts the statistician, whoever we're you know actually using you know to do the models. So they have the direct knowledge of that data domain, and can give direct feedback on data quality and usually these are the folks the data analysts, the BI analysts or the statisticians are involved in the continuous improvement program and you'll see that, later on the slide deck that this is not a one time build. This will start small and keep building, and it's never finished so you have to have a good continuous improvement program in order for this to be successful. Did I hear you correctly when you said that you played Jedi mind tricks on them to build up. Can you elaborate on that a little bit. Yeah, because when we started the, the, you know, data governance journey at WD, it was data governance. Oh, you know immediately flashes of red tape bureaucracy, just by hearing data governance before we even had one conversation right. So, you know we went down we had a journey just like most data governance teams and we said what does this company care about. And, you know, talking to executives, mid level executives all the way people using the data was data quality. So we kind of flipped it on its head we said we're going to do data quality, but we're going to need these other things to, which are really data governance program practices right. And that is how we backed into it. And that's how I get away with having rather small team. Now the people in the business are performing these processes these checks these ownership of the data. And what my team does is just help them facilitate data governance processes without, you know, calling it data governance process, you know, that's that's the Jedi mind trick right is provide small wins. They'll want more, and then they'll start asking for it. And before you know it. They're doing data governance without even knowing they're doing it. You know what it sounds like to me that you're tricking people into thinking that it's their idea. Absolutely governance is necessary and you know what that's a brilliant philosophy to follow because if people come away thinking that they're being listened to. And you know if it just so happens that governance in the focus on quality addresses the things that they're talking about. You know that's even better and you know I've heard that in meetings with executives to that if we can get them to think that these are their ideas, and that we're following their ideas. So not only are you learning to work with your data scientists in this webinar, you've now got some Jedi mind tricks that you can, you can use to engage your stewards, and get them focused and they're and your scientists to get them focused on improving the quality of data in the organization so it's great when there's takeaways from the webinar but you know when you said Jedi mind trick it was, you know, immediately you start thinking okay so what's, what's how's he tricking people into doing things you're not really tricking people you're getting them to come up with the ideas themselves, and when they make that connection there's nothing that's more valuable than that. And the last subject that we want to talk on in this talk about in this webinar is how can we combine these three topics into a tour de force and in your neck in the next slide when I get to it. There's a great diagram that I think shows how we can bring those things together, but just real quickly before I turn it over to you to kind of share that and then we're going to toss it back to sharing for questions for miles and you and for me to wrap this up. The first thing is that we need to focus on is stewardship. And I know that stewardship has been at the heart of your program since the since I started talking to you, you know, several years ago. And the idea is that instead if you're going to take a non invasive approach, people are already governing data, they're doing it informally. And because they're doing it informally they're doing it inefficiently and effectively, if we can help to formalize that accountability, then like I've been known to say and Chris I know you've heard me say it, many times that everybody in the organization is essentially a steward of the data, because everybody either defines and or produces and or uses data as part of their job. So we've got to focus on that so the stewardship aspect of governance. If we're going to get to the execution and enforcement of authority for analytics data, or for any data in the organization, the way that we're going to do that is through our stewards, which is really. And a big reason why Western digital has been so successful is because they started with that core discipline of stewardship as a piece of governance. And we need to look to, you know, further partner and coordination cooperation with the data scientists with the folks. If there are separate folks that are focusing on data quality, these folks need to be engaged and part of the data governance program. So we need to build out communications around governance around science around quality of data that includes orienting people to the subjects so it's not scary data, the term governance is scary people go running for the hills when they hear it so we need to orient them to what the governance is and why it's necessary and how there are different approaches, like an active approach that elation talks about like a non invasive approach that I talk about, and then there's the whole onboarding of these folks in the organization and ongoing communications, we need to make certain that that becomes a critical aspect of all three of these things, and we can tie them together through those communications. So we, if we can, in our organizations, the ideal scenario would be to get people to view data governance data quality and data science as complimentary disciplines and not as you know separate disciplines that are unrelated that partnership is extremely important and Chris please share how you went about doing that to kind of marry these three topics together, and then I'll go to your next slide here. What I'll say is data science relies on data quality, and we're going to achieve data quality through formal data governance so that is taking people's informal accountability and making it formal. Chris why don't you share with us this this incredible diagram, as to how you kind of bring these three concepts together. So this one has resonated in, you know, in the business right is it's really the name of the game is accelerated value, right. And really business value can be gained right companies have been successful for a while now with with some of their programs and analytics programs right but it takes, it takes longer and they have a little bit more frustration but if we take a look at the diagram and we have data governance right. So, we have here where we've been saying this the whole presentation and data scientists should be part of the data stewardship, and in fact have a very large role in continuous improvement, I think, having a large stewardship base really helps your continuous improvement program because there's no ambiguity of who to contact for your different source systems data quality right. And this is a big part of this to our company because we make products right we we built storage solution we that's what we sell it's it's our value data quality should be treated like a product. Right, so here we're building things but we're also using the data to help build the things that we build. So if we look at data as as a product, then we know we need to, you know, just like any other quality thing that we do in the measurement measurements we got to make sure there's remediation we got to have programs around those. And this is really resonated because, like I said we're engineers we make sense to our minds about how we, you know, do anything quality. And the last is data science right. We're not using data science to replace anybody, or automation to replace anybody where we're using data scientists to make humans more effective and productive because that gives you your business value. In fact, we have a program here at WD that if a data model or any type of analysts analysis or automation affects somebody's job we retrain them we up skill them. So that way they can help be part of the long term viable solution of the company so a few a few notes here is is you know, data governance does not have data stewardship. In this, not just have data stewardship in this core set of competencies, but it is the major factor of success without a doubt, and data quality should be part of a larger management process of continuous improvement. That way, these three things together will get you accelerated business value. And we have on the books with our executive team hundreds of millions of dollars of savings that we can provide over the next couple of years. And the companies really relying on us to make data science work for the company and without these other components. And the ROI wouldn't be there so really, when we're talking to the company and executives, business value is the name of the game and you can tie somehow your analytics programs that need data quality, then the ROI will be self written. So, you know that you and I could talk about this all day and I love the, the concept of data quality as a product, you know you hear about data governance as a service you hear about a lot of different things as services and as products but data quality as a product that really, to me, you know, be a you know that you want your product to be of high quality well if your product is your data then you need to that to be of high quality as well. And that's one question people may have and then we're going to I'm going to wrap it up here in a second then turn it over to Shannon. The one question for you Chris is, how long have you been doing this, how long have you been working on this within Western digital. And when did you come to the realization, and maybe it was right from the get go that data science and data governance really needed to be that tour de force to help to improve data quality was it right away, or did it was there a revelation, that you weren't along the journey. So, at WD we've been down this data governance path for about five years now and it's evolved since the inception. When we started data governance under different leadership that was really focused on policy driven, you know, I would say traditional data governance things for lack of a better word. But I know that you have to deliver you have to get these wins and order for people to take notice and to be interested. So we immediately I would say a year to end to it. We focused on data quality and started driving towards data quality, you know, largely as what the value data governance, quote unquote, can bring to the table. Because I would say a year and a half ago, not even a year about a year and a couple of months ago, where the data science community came together and said, Hey, I need trusted data. How do we build a program to do this. And over the last year, building frameworks building architectural solutions for data health platforms is really when these three really melded together. And it's now viewed as as one of the driving forces of how we are going to gain that value in the company. Well, so you know what you've been like the ideal guest for me to have to talk about this object was like I said when you know when I want to talk about stewardship and how it's been effective I we have conversations about it and so I really appreciate your your help and your opportunity about what you've been through and you know how long it takes and those types of things. So we're, we're coming to the point of the webinar where we're going to start to take some questions just real quickly. What we talked about today, we spoke a little bit about the relationship between data governance and data science, and how important it is to make that relationship. And how data governance can be used, or how we can leverage data science to actually improve the quality of the data and Chris gave several examples of ways that he has gone about doing that. We talked about partnership and where data scientists play a role in data governance and Chris that was a great example that you gave of, you know, the, the meta, the Jedi mind trick in the in governance and improving quality is get these folks to say hey we really need this and let them think it was their idea that is the way to be successful in organizations, and then the last topic that we we trust on was the combining of these three concepts together they are not separate disciplines that are unrelated in some of the frameworks, and they may be separate items but the fact is that the more that we can bring these items together, the more successful we are going to be with data science as data science continues to grow as a discipline within our organizations quality continues to have such an impact on the confidence that people have in data, you know we need to bring governance and we need to bring side data science together to to improve quality. And with that, I would like to turn it back over to Shannon to see if we have any questions today. Thank you all for these great presentations today if you have questions for any of our speakers today feel free to submit them in the Q&A portion of your screen, and just to answer the most commonly asked questions just a reminder I will send a follow up email to all registrants by the end of day Monday with links to the slides the recording as well as anything else requested throughout the webinar diving in here. Are there tooling available to automate capture attribute attribute level and lineages is otherwise a very manually intensive area and data governance program. Well I don't know maybe we'll maybe we'll start with with miles miles do you want to talk about how the elation catalog can help with you know automating the lineage of the data to help people weren't know where the data came from. Yeah, I mean I think you know I really liked the remark that were said earlier around, you know the notion of continual improvement. This is an area where you know data science applied to data really can help so you know a catalog can be a great place to automate a lot of these processes as you go downstream a great place to find stewards. I mean, I've said it before but it's really hard to find stewards if you don't, you know you have to go do it top down so the ability to kind of find who are the people talking about a topic and modifying data and things like that. Those are your natural stewards so yeah I think, and of course lineage is a huge issue where today to come from. You know how do we better control it even going back into the transactional systems is a big deal to so my thoughts are yeah tooling can help a lot but you know you still have to do the process and people stuff to. And Chris did you use a tool to do this to help you to determine who the stewards were to help you to document lineage as you were building out your program. Yeah, great question so right now. We are looking to buy some tooling as this program continues to grow manual. Let's say hurting and keeping up with the steward list and you know, associating them with data assets is a rather large task. So we are currently looking for data catalog tool so the answer is no we don't currently have one me being a solution architect in the past. I've I've built a homegrown solution that was great to learn how to crawl and to walk. But now we're starting to run and we need some automated automated solutions to help us and that's that's the point we're currently at right now. So I guess the answer to the question is yes, it's a great question but I think the answer. The easy answer is yes. Yes, tooling totally can help. But it's but it's not the overall solution. People are the people are the solution. Okay, I love it. So, how do you get buy in from the areas in the organization to participate in data governance to foster collaboration across the organization's data scientists for example, within the research and development departments top to bottom bottom up or combination of both any suggestions. Chris you want to start with that. That's that's that's a great question and it's very very I can see why it was asked. It's very difficult to do. But again, it goes it goes back to what is the value proposition of your data governance program. If it's risk. You know, then the conversation would be a little bit different entry data scientists are looking at models to help assess and, you know, predict risk. Then that has a little bit a different conversation whereas on the manufacturing floor, we sell product. So the, the leap to data science data scientists will produce a model that will help the floor do this, which could save, half a million dollars a year and efficiencies or something right then you can get tie that and that conversation becomes much more easy because you talk to your data scientists and you say, Hey, can you do this model with crappy data. They say no, you know, get engineers to where they have to admit something they'll back you or get data scientists, you know, to back you say no this will not work without quality data. Then you start having that conversation with your data domains towards executives mid level management, and then they'll start putting on the books. Hey, you know we need some resources for this. So, as long as you get someone out of their comfort zone to say, Yes, I need it. Then it becomes easier to have that conversation. No matter if you're in, you know, this operational space of manufacturing or in risk or, you know, credit or whatever. Finance that that kind of is what I always go back to is having them admit can you do this without good data quality. I think that that's, you know, I always ask people what can't you do because you don't have the data to do it or what would you do if you did have the perfect data miles I know you talk to a lot of CIOs. And have you found any specific messaging that seems to really hit home or resonate well with these folks when we're trying to bring together these disciplines and when you're when you're just talking to them about the state of the industry. You know the key thing they say to me all the time is put it as a business issue. So, you know, obviously, one of the things I've been really fascinated with is they'll, they'll describe that I've got data out there that, you know, I don't know where it is and it may be of risk to me or I have, I have, you know, people wanting to make decisions. They can't trust the data so I mean I think if you can talk about it not in terms of technology but talk of it in terms of business problems, you'll get them on board and then they'll help you get the rest of the business stakeholders you need to to get a program established. And you know I think people shouldn't listen to you because I know that you do talk to a lot of CIOs so I think that's really good or not. And I think I have time to slip slip in at least one more question here and you know just to everybody out there keep your questions coming because after the webinar I'll get all the questions to Bob up for the questions we didn't have time to answer so we get those in the follow up email to you. So, um, so Chris are you using a data quality tool is there are some tools now that use AI to do the same things talked about here tools like data buck and others, or are you finding that you still need the data scientists to do the data quality work. So we are not we do not have a data quality tool that does a bunch of the AI and ML, and that is, you know, answer is a couple fold one, they're very expensive. And you got to have a really good ROI to justify just the purchase of that tool. The quality tool isn't going to be all you need you need a good catalog as well because that's just going to hold all of your metadata. So when I say answers to fold is when we start looking into tooling. There's there's some solutions out there that you can buy a data catalog and put a data quality tool on top and then we're talking. We're talking about dollars and when you're trying to build a data governance program, you want the lowest cost footprint available. But I can tell you, since we have partnered with our analytics and automation team and operations. We're not going to give up because they have a large ROI, you know, promise, and the amount of money to buy tools is now very negligible, compared to what they'll save. So it's really, really important. The same, the business problem, the business value needs to have a clear direct link to saving money or, you know, putting the company at less risk. So we don't plan on buying a data quality tool right now. Some of the data catalog tools that we're looking at has some of this built in. But we have a plethora of data scientists that are, you know, at our disposal in the company so we want to take that metadata and utilize it for something very pointed. Some of the data quality tools are getting there. They just don't provide everything that we need enough in order to, you know, get the ROI for that spend. So I guess I could summarize what you said is go where there's money, and if there's money being invested in other things and yeah you're right data governance and the quality tool actually becomes a negligible or at least a minimal aspect of the of the overall investment. So I think that makes sense to me, you hear the expression, there's gold in them our hills, you know, think of the, think of these other efforts as them our hills and go after the gold there.  If you can capture what people think is good data versus bad data, it can help as an initial step. But thank you all so much for these discussions but I'm afraid that is all the time that we have slated for today again, I will get all the questions we didn't have time to get to over to Bob to get those answers into the follow up email I will send out by end of which will also contain links to the slides and links to the recording. Thank you all for these great presentations again thanks to elation for sponsoring and helping to make these webinars happen. Love it. And thanks to our community for always being so engaged in everything we do you guys are just the best. So if you all have a great day. Thanks so much everyone. Thanks. Thanks, Chris.


Good afternoon We will call to order the April 2018 City of Columbia Planning Commission meeting We'd like to welcome Planning Commission members staff and guests. I Would ask that everyone turn their cell phones and PDAs to the silent or vibrate mode The administrator will now proceed with a roll call Mr. Tupper Ms. Hart's Mr. Taylor mr. Cone here mr. Stigamir here and mr. Frost We have formed thank you I'd like to do a brief review of the meeting format applicants With requests before the Planning Commission are allotted a presentation time of 10 minutes This time should include but is not limited to an overview of the project case history and any pertinent meetings held regarding the requests This time also includes all persons presenting information on behalf of the applicant Such as attorneys engineers and architects This time limit does not include any questions asked by Planning Commission or staff regarding requests Members of the general public are given the opportunity to address their concerns in intervals of two minutes The administrator has a timer and will make presenters aware of when that time has expired the Planning Commission Reserves the right to amend these procedures on a case-by-case basis and There's a little timer to your left. It'll have a green yellow and red light when the red lights off time to stop the consent agenda The Planning Commission uses the consent agenda to approve non-controversial or routine matters by a single motion or vote Examples of such items include approval of site plans annexations and street names If a member of the Planning Commission of the general public would like to discuss an item on the consent agenda Then that item is removed from the consent agenda and considered during the meeting The Planning Commission then approves the remaining consent agenda items The administrator will now read the consent agenda Your consent agenda this evening consists of the approval of the March 5th, 2018 minutes as well as Two annexation comprehensive plan map amendments and zoning map amendments, which would be items number two which is 2716 shop road As well as item number 3 1321 Piney Grove Road The consent agenda continues with a zoning map amendment On item number 4 for 42.31 acres on pageant road This is to rezone from Pudr to an RS 3 zoning classification The next item on the consent agenda is a minor amendment to a plan unit development It is item number 5 is 5.76 acres Bounded by corner the corner of wind lane and cliff kinder road and hay meadow lane and That is a large-scale UD and then we also have two three site plans this evening Those consists of item number six, which is 5.76 acres bounded by the corner wind lane The kinder road and hay meadow lane, which is a request for approval to construct a 39 lot Single-family residential subdivision item number seven, which is about 52 acres at 3600 block of pageant road and this request is to construct a subdivision of a hundred and fifty five single-family lots and then item number eight will wrap up our consent agenda this evening, which is for 334 harborson boulevard and it is a request for a site plan approval to reconstruct a convenience store and gasoline service Sales facility on that current on that property. Thank you. Are there any? Commission members or guests today who wish to have any items on the consent agenda moved to the regular agenda tonight If not, I'd like to ask for a motion to approve the consent agenda Mr. Chairman, I'll make a motion to approve the consent agenda as presented I have a second second All in favor signify by saying aye. Aye. Anyone oppose Consent agenda is approved. We will now proceed with the regular agenda I would also like to ask everyone who comes forward to please state their name clearly before speaking So the first item we have this evening on the regular agenda is a major Amendment to a planned unit development district. This major amendment is to this POD and The applicant is here this evening to answer any questions, but I do want to point out. We have one Correction for you this evening that is referencing one of the POD documents in your packet it's actually the last almost the last page of text right before you see the the two drawings for this particular item and It states that the second element of the development will include a plus or minus 6,600 square foot church and the applicant has indicated it should be about a 9,600 square foot church So I wanted to make that correction for you for that that numerical value and The reason for this amendment is basically the POD was very specific of what could go on this particular lot and The church has acquired it and it's this parcel highlighted on your screen and Without amendments, they wouldn't be able to What was staff's recommendation the recommendation for this one is to recommend that you Grant rent the approval for the modification Is the applicant here they are okay Would you like to come forward please? Mary make me know our desire is to as stated to build a building on Kauffman and our original Drawings and not include a space for us to do a food bank within our building as well as Being able to do some additional class space And so that's over requesting the additional 3000 square foot up to 9,000 Okay, do any commission members have questions for the applicant? Any questions for staff? Thank you. Thank you Is there anyone else who would like to come forward and talk on this? If not, I'd like to call for a motion Mr. Chairman, I'll make a motion to approve the major amendment We have a second Yeah, I'll revise them the motion to include up to 9,600 square foot any further discussion All in favor signify by saying aye Anyone oppose? Motions approved so item number 10 on your Agenda this evening is a zoning and map and text amendment. This is for the Seminary Ridge Historic District it is a request to modify the historic district from a Architectural Conservation District to a Protection area district more with our offices here if you want more detail about that I also know there's a number of residents here also Okay, is the applicant here as well The applicant was properly mr. Davis from the city council. Okay. Do we have any questions? Right me if I'm reading this correctly is this to change the heights Right and recently the neighborhood Conversations and meetings with them they expressed interest in simplifying the district down to a protection area Which removes both review some review and more protection from the neighborhood so it's It's a slightly less regulated Born of a historic district in the architectural conservation district All right, but it was driven by the community members that asked this to be reviewed Would anyone like to speak on this? Lance Folsom When we Considered this few years ago. We didn't know what we were getting into it sounded good Our meetings had about 10 people or less if we were lucky as we've seen this implemented We like the idea of the historic part But some of the requirements were pretty strange it a lot of our moderate income neighbors couldn't improve their properties Like they wanted to like energy efficient windows. So when this came up a few months ago our meetings Swell to 20 or 30 people and We voted 27 to 3 in our last meeting to go ahead and proceed to try and change it to a protection area to allow our Residents to improve their properties a little easier and we'd appreciate your help in Helping us do that Okay, thank you Yes, sir proper property owner in Seminole Ridge and I'd like to enhance what? Lance the other day that this is about Hopefully people improving the property become a little more energy efficient making the neighborhood more attractive So that younger people will move in in the future also, but we are interested in retaining the Historic significance of the neighborhood by making this change to this. So I Appreciate you Giving it a good close look and I'll thank you for your time. Thank you Is there anyone else who would like to come forward? District the home belongs to my mother-in-law of Mary Taylor and she passed it over to my wife Jacqueline and me and We would like to oppose the objection because there's never been a homeowners association in the district This is a neighborhood association There's over 200 homeowners that live in this area that are impacted by changing of this If this thing from a historic district or to protection district it's like having an antique car and All of a sudden you say, okay, we're gonna put anything we want on it and that's gonna change the value What's gonna change the value of our homes? And on information and belief the applicant doesn't have the right to submit an application unless they have All the homeowners sign off on it in a letter giving them the right to vote for them as a thing They're not a homeowner's association. They are a neighborhood association So they do not really have the right to speak for 200 homeowners with only 30 people in Present it's also voluntary. There's nothing that's passed to the government. There's nothing that's passed D And there's nothing that's passed through You know when you sell the property so membership is not a requirement So like my mother-in-law, she's 93 years old, you know for the last four years She's had a bad hip so she hasn't been able to attend meetings There's other elderly people that doesn't attend meetings and there's also other people that have houses that are In the other you know that don't live there now the at this meeting He said there was 27 people that voted part of those people were spouses of homeowners So that divides it part of those people were daughter and mother and part of them were renters So how many people present were willing homeowners and that's my question The homeowners are not being represented properly by changing this by a few people Deciding that they're going to vote for homeowners that are not there Thank you for your time. Thank you Before I ask if anyone else wants to speak Amy, can you clarify the difference between? architectural conservation district to ridge protection area An area that has a wealth of original start structures and original material and features So that is why there are more regulations around that because there are more resources there that are important to say Protection area is one where you have more infill more demolitions have happened over time And so it's lost some of that integrity although there is still recognizable patterns of building forms Maybe not quite so much detail and architectural features still extend and so protection areas typically have less Fewer regulations attached because there's not as much there to protect any longer Okay. Thank you. Any one else want to come forward Yes, sir My name is Brian Berg and I've lived in the neighborhood for 16 years. I'd encourage you to Go with the change The median income in the neighborhood is only $25,000 Which makes it virtually impossible to maintain the homes at the level required under the current guidelines Would also like to clarify that this was an effort on behalf of the neighborhood Association we don't have a home association So everyone who lives in the neighborhood is allowed to vote Thank you Anyone else want to come forward? Any questions from the Commission to staff? Okay, if not, I'd like to call for a motion, please I'd like to make a motion that we recommend for approval the amendment of the text of the city of Columbia's code and ordinance to delete 17.681 and modify 17681 To add Seminary Ridge architectural conservation district to Seminary Ridge protection area Do I have a second? Any further discussion? I'll in favor signify by saying aye. Aye. Anyone oppose? Motion passes. Your next item this evening is also a zoning map and text amendment. It is item number 11? Yeah, hold on a minute though. I have a different one also My intention was to actually have number 11 at number 12 and number 12 item number 11 because there's a sequence in a relationship between the two and Item 12 were you should really address 12 before you address 11 So if you would give somebody would be interested in making a motion to take item number 12 first Followed by item number 11. That would be great. I think the two will make more logical sense together that way And we have a motion to move number 12 first before number 11 I make a motion that we move number 12 To number 11 second I'm favor signify by saying aye. Hi. You want to pose? Ocean is approved to move number 12 to number 11. I mean in front of number 11 so item number 12 the item before you at the moment, which is item number 12 on the agenda is a zoning map amendment to Rezone parcels from light industrial district M1 having industrial M2 the design development area DD Innovista ID overlay the Design preservation area, which is a DP zoning district and the mixed-use urban district MX to To an MX, I'm sorry to the mixed-use urban District MX to the innovative design overlay and the design preservation area DP the So the reason for this is as you noticed in the agenda there these two particular parcels have a lot of zoning classifications on them and The request is to actually rezone them so that the parcels that are all in one ownership So there are a number of parcels Particularly you'll see the one that's highlighted on the screen as well as the one just to the south That's a kind of an empty lot with trees that has a different zoning. It's the intent of the owner to Have all both of these properties in the same zoning district so that you don't have all these different lines chopping them all up and Basically clean up the zoning from that perspective And so that's the the the proposal before you the applicant is here And we'd be glad to dive deeper if you have any questions Okay With the applicant right to come forward Mr. Chairman, my name is Bob Fuller. I'm a lawyer in Columbia, and I'm here this afternoon with Ben Arnold who is the Chairman or president of Southern Realty Development Corporation who is the applicant and as Mr. Fellows has already suggested to you. This is more a procedural matter to Consolidate and make consistent zoning On a parcel that is now more than a single parcel By virtue of its size and use The company has the ability to acquire an additional three acres to adjoin this 8.7 acres the Property that is under consideration for purchase is Zone Mx2 and has the overlay district for the investor and the design district The property that is presently under your consideration is a larger piece. It's 8.7 2 acres It has a portion of M1 zoning. It has a portion of M2 zoning It has presence in three of the additional overlay districts it will make going forward and Developing a cohesive parcel difficult to have the prospect of having to cross Zoning district lines within the development parcel when it is being planned out. It's really Property that is being asked to have a Little facelift in order to make it More realistic to work with as future plans develop. There is not a proposed Development plan to be considered today. There's not a use imminent to require it to be Resowned this minute, but it will certainly facilitate the ability to to realistically and Cohesively deal with the entirety of the 11 acres over time as it is appropriate to do as you know, Mr. Arnold's companies have been in the Vista for a good many years of its as long as it's been the district and are Very conversant with the requirements that are At present both presently and to be Consolidated if it goes to all mx2 We're not asking for variances or special exceptions or any particular treatment on any portion of the property it's simply to To have what has already been a parcel of several Identifiable lots becoming yet additionally Consolidated with Consistent zoning throughout the 11 acres That's what the proposition here today, and we ask your help to do that Any any questions for the applicant any questions for staff Anyone else like to come forward on this if not, I'd like to call for a motion I'd like to make a motion chairman that we Recommends for approval the request to rezone the parcel from M1 M2 DD ID and DP to Mx2 ID and DP We have a second Any further discussion? All in favor signify by saying aye. I anyone opposed Motions approved now. We're going to item number 11 Correct item number 11 on your agenda is a map and text amendment and its modifications of the Innovista design district and the guidelines as well as the rezoning of 11 1100 Wayne Street the Probably the easiest to describe this. Let me get to the right slides So there in your staff report there are four essentially four amendments summarized which I'm going to go over The first proposal within this application is to rezone a portion of 1100 Wayne Street from the MXD mixed-use urban district Mx2 DD and ID and DP to a mixed-use Mx2 ID Item number the second sub part of this Application is to amend the Innovista design guidelines to reflect proposed changes To the boundaries and the height requirements in the buffer areas and for clarification purposes Item number three or sub point of three of this particular application is to amend the city of Columbia's official zoning map to extend the boundaries of the ID zoning district and remove the DD zoning district from the same area and the final sub point of this particular Map and text amendment is to amend the city of Columbia's code of ordinances in the Vista design district To reflect proposed changes to the inner Vista design district guidelines With the item that came before the way the inner Vista design district I think if I can summarize this in just a few words is that it was very specific on a boundary by Expanding the boundary. There's a number of items that in the documents that Become More difficult to enforce and they create some awkward Situations so for instance in the inner Vista design district it states, you know, which streets should Parking garages have access to and which streets should parking garages not have access to So there's a lot of things like that and so for instance dervay Street was not listed So we needed to add dervay Street under one of those claffets Classifications, so that's just one example. They're all detailed within the staff report but essentially That's the sort of the gist of a lot of these changes. The other change is there is a buffer boundary that needed to be modified and With that, I don't know how many of you were on the commission when we did the West survey plan But there was a recommendation to do a a stepped buffer type height Recommendation from within the historic district and so we're including that within this particular proposal So I think there's a map in here Yeah, so for instance on the map that's on your screen, which should be on your tablets There is a 55 foot zone. That's approximately So many feet back from dervay then an 80 foot zone and then when you get to that, you know, Vista district The original boundary there then it goes up to 150 feet and in a vista itself is an unlimited height district So this creates that stepping Situation envisioned from the West survey plan on this particular parcel not district-wide but just for this area And so that's sort of a quick summary of all the pieces within this document before you We have any anybody have questions for staff I've got some concerns about these height limitations this purple area You're really saying that has a height limitation of 150 feet that sounds terribly high That is that location or any location that close to dervay Street, that's about It's approximately one block away. So It is it is a block you can see Senate Street just off to the side there. So it's very long It's probably 400 deep and I don't know if that's probably a little bit more So it's probably six to seven feet long that orange area So it's not unlike Other areas of the historic district in fact, there's some other boundaries to the north where you can actually go from the Height limits that are in the historic district all the way to unlimited particularly when you get towards, you know assembly Street, so 150 is tall, but if you look at the perimeter of that district This does keep that height down the context of what is surrounding this area. I think it's too tall. I think it 150 foot tall building would be out of place here Not much The hotel Just east I mean it's it's a hundred or so and I can't see another building 50% higher than that The Hilton or the Hyatt which hotel I'm sure the one where Ruth Chris is I forgot the name of the hotel Okay Hey John, can you go ahead a couple of slides? I want to ask you a question about a slide that we're not on one more That slide It won't back Am I understanding this previous slide that if you go back to where we were just were To show all of the area that's currently purple in that slide has unlimited height currently correct Okay, it's currently anything that's purple on this map has an unlimited height anything that's green as a height of 75 feet and The area that I'm going to call teal, which is that area behind the subject parcel that we're talking about that currently also is So I think this is a telling slide here because if you can go right across the railroad tracks and basically build unlimited This is actually in some respects if we were to go to an innovative design district is a little bit more restrictive This is it is More restrictive than the purple correct. It is a little bit more Progressive than the other side it allows for a little bit more than it currently does I've got some real concerns about particularly the unlimited heights in this old Well, this unlimited height has been on the books for not close to a decade Still got concerns about it Had concerns about it. Is there anyone that wants to speak on this? Tonight I don't know. I'll just follow up a little bit on the try to address the concerns of the unlimited height What we have found with from a zoning perspective on limited height is it is in essence is self-regulating so for instance Main Street a lot of the areas along assembly Street. Those are also unlimited They've been unlimited for decades You say along Main Street Main Street assembly Street in the downtown core. That's not this that's Main Street Correct in this area is in a vista and in a vistas had a unlimited height for for quite a while here and what we have Found is that it is in essence a little bit of a self regulatory thing because as they have to provide parking And they have to provide other things. There is a balance in terms of economics of how tall you can go So we have seen some proposals come in that are fairly tall But they usually to go a little bit shorter. So Right now, you know, we kind of see buildings that are you know Trying to think of the one apartment building that's being built But it's probably think it's about seven stories or something like that. So we haven't seen a tremendous Height in a lot of our unlimited areas because they have to balance a parking garage and you know all the spaces in that with the height and all that Economics, so it's that one small section Any further questions for staff? I'd like to call for a motion then please Mr. Chairman, I'd like to make a motion the motion is to recommend approval to rezone a portion of 1,100 Wayne Street from mixed-use urban district design development area and a VISTA design district and design preservation to mixed-use urban district in a Vista design district and design and preservation area to to amend in a Vista design District guidelines to reflect proposed changes to the boundaries and height requirements in the buffer areas Three on then the city of Columbia's official zoning map to extend the boundaries of the ID zoning district and remove the DD zoning district from the same area for a men's city of Columbia's code of ordinances 17-291 and 17-325 to reflect proposed changes to the Univista design district guidelines in the official zoning map Do we have a second? second Is there any further discussion or questions for staff all in favor signify by saying aye aye? Anyone opposed? Motion is approved Only other businesses is we do have a work session coming up later in the month. We did send a Meeting invite to you, so if you haven't seen it if you were out of town last week or something like that We set a date yet Have we set the date yet? We did. I believe it's Thursday at lunchtime. We'll have sandwiches That was this was it the 16th? No, no 20 Thursday, I think I think it's next Thursday, which is the 19 No, yes next Thursday night I'd like to get a motion to adjourn, please second so all in favor meetings adjourned


team keep it clean what's going on is engraving here with another video and in this video we're here to talk about the game that we're watching right now between the Ravens and the Texans where the score is 17 to 10 before we get into this let me introduce myself me I'm engraving vids and this is my YouTube channel engraving vids and I'm a Ravens fan and a fan of a team where the offense just can't seem to get it together still but anyway on this channel we talk about the Ravens a lot but we also talk about football period so if you're a Ravens fan if you're a Texans fan if you just love football love the game of football love talking football and everything about it then it's the perfect place for you and like my guy Ryan Mallet always said leave a like on a video because it is completely free and subscribe to the channel turn your notifications on so you never miss a video so and if you can follow on Twitter Instagram and Snapchat especially Twitter because we'll be talking about the game as it goes on live tweeting so to speak during throughout the game Twitter Instagram Snapchat all three engraving vids like I said but anyway in this game yes I'm having a good game good game Jagger appreciate that so in this game y'all make sure you like on a video it's 25 people in here but it's only eight likes you gotta fix that click that thumbs up button but anyway in this game same story same story same story the defense continues to do their thing even though with the defense they've been on that first Texans touchdown drive penalties penalties penalties penalties penalties they were so bad the penalties were killing them murdering them the penalties were so bad so bad the penalties literally moved the the Texans deep offense up more and more the penalties were terrible ugly and then I know even even if you go back before that if you go to the Ravens first offensive drive Flacco should have been picked off he should have been picked off and because it was on the second play on the first play of the game I forgot what they did but on the second play the first play the game they got like eight yards so it was second in two so on the second play the game they threw a quick a quick little out route to Jeremy Macklin but I think Jeremy Macklin fail he failed so that it should have been it should have been a pick six you're right Paul it should have been a pick six but the the cornerback just couldn't get it and obviously to receive a fail so Flacco was it was not expecting to receive it to fall it was a timing route and it was just they were just off and Flacco has looked off all game him and Macklin him and him and Macklin definitely him and Wallace have been had a better connection than him and Macklin him and Macklin the timing has just been disgusting the timing has been disgusting and while Wallace remember on that pass remember when they called a defensive holding on on McKinney it was on like a third and long I think and Flacco dropped back he dropped back and he threw the ball deep to I think it's for Jeremy Macklin Jeremy Macklin was he was going deep but then he stopped and he was looking back but Flacco threw the ball like Jeremy Macklin was still going in and that's when Kevin Johnson almost picked it off and it was just like I didn't know who he was throwing to I didn't know what was going on it was just ugly it was ugly but the timing of the routes the timing just the timing and the accuracy have both been off everything has been off with this with this offense it's just been off off shout out to Alice Collins shout out first and foremost shout out to Sam Cook shout out to Sam Cook that guy this the second time he's had to do this he had he's had to give life to our offense if not for him oh boy who knows what the score would be right now if not for him who knows what the score would be Sam Cook he that pass was perfect the timing of the pass was perfect and for you to be a punter and to for you to be a punter and to throw throw that pass as perfect as he did and with the with the accuracy that he did that was timing at his finest because if you go back and look Chris Moore wasn't even open when Sam Cook threw it he wasn't open when Sam Cook threw the ball he wasn't open when he threw it so the dude Sam Cook dropped back even even like pump fake a little bit he looked downfield he saw Chris Moore threw it perfectly and he threw Chris Moore open do we need to start Sam Cook at quarterback I don't know man but um anyway yeah it's just and then a couple plays later and then they did then the Alice Collins the pitch on fourth and fourth and one now me I hate pitch plays I hate toss plays they are definitely not my favorite I don't like them at all but especially when they're on fourth and short I hate when people pitch it or toss the ball on fourth and short because I feel like it's so stupid and it's so risky because you're throwing a ball backwards and you're throwing a ball backwards like three four yards so it makes it easier and gives the defense more time to close in on the running back but in this case and y'all make sure I leave a like on a video it's 50 people in here but only 17 lights what's going on y'all don't appreciate the videos man come on now I know we better than that let's click that thumbs up button but anyway I hate when people do pitch plays because like I said I feel like it it just gives the defense more opportunity to stop the plate but in Raven's case it worked out for it worked out for him because Alice Collins got 29 yards and like I said earlier today I wanted Alice Collins to go off and I wanted him to get his next touchdown of the of the year and he did that he did that no jokes like I know that I'm just messing with y'all I know that and I appreciate y'all man I appreciate y'all but I'm glad that he I'm glad that he did it I'm glad that he got his next touchdown I know they were talking about they kept showing them before the game saying he was gonna do the whole Irish dance thing with the whole team but they switched that up I guess he wasn't into it like that he was like uh he said you know what we don't deserve to dance right now so we ain't gonna do too much they let Austin Howard do his little thing whatever and that was it so they didn't they didn't do the I appreciate it Tristan thank you so they didn't do the whole um dance now the touchdown by Buck Allen I didn't think it was a touchdown I didn't think it was a touchdown I thought it looked like he was short but like I said I did tweet out that the play was gonna get it was gonna stand but it wasn't gonna be confirmed and it's a difference when something stands and when it when it's different between when something stands and when it's confirmed if it stands that means it just wasn't enough evidence to overturn it or to confirm it so then when they said it's when the play is confirmed that means there's enough evidence on the on the replay to show that it was or it wasn't a touchdown or completion or whatever the call might have been and in that case I don't think that was a touchdown it looked like he was short it looked like he was short but anyway yeah so yeah they didn't have an angle to see it you're right vegan king clowny yes Joe Flacco is elite but now he's hurt clown he said clowny is sick yes clowny is a monster and imagine imagine how this game would have been going and it's a bittersweet thing because as a football fan you want the best of the best you want the best of the best to to go up against your team so you want a Jadavian clowny and a JJ Watt and a Roy Rage Brian cushion and a Doshan Watson and Will Fuller you want the best of the best to go against your team but at the same time when you realize how your team plays and you realize what your team is capable and incapable of it's almost a bit it's a bittersweet thing or Whitney merciless too that's another one it's a very bittersweet thing because it's bitter because we're not playing the best Texas that they are but it's sweet because even though we're not playing the best Texas that they are they're still in this game and we still got this game like we're still struggling with them still struggling but yeah just imagine if all of that guys were playing this game might be a little different but one guy that is playing is DeAndre Hopkins and I see a lot of people saying Jimmy's getting exposed he's getting smoked Jimmy Smith on the first DeAndre Hopkins catch it was such a great throw and it was such a great catch and Jimmy Smith was in great position he just couldn't swat the ball he tried to but he just missed it then Hopkins broken got got a little bit loose it was such a great throw by Tom Savage it was perfect but then yeah Jimmy Smith has been getting caught on now there was another play that they were playing zone where DeAndre Hopkins you could see Jimmy Smith was really frustrated because he knew his safety was supposed to be behind him or in that zone where because Jimmy Smith was he was playing on his side of the field and it was more towards the middle of field DeAndre Hopkins ran up on Jimmy Smith side of the field and cutting and Jimmy Smith I guess he figured there's supposed to be a linebacker safety right there but there wasn't and Jimmy Smith when he saw DeAndre Hopkins catch the ball he threw his hands up and air and frustration and you could tell it was just it was bad it was bad it was bad so DeAndre Hopkins but he been getting off he didn't get I mean not getting off all the way but he's been doing this thing they got a tight enough with him man they got a tight enough and they they got to get more pressure on they got to get more pressure on Tom Savage up the middle I think the up the middle pressure has been the best because they've been swatting his passes the defensive line been swatting his passes that the pressure up the middle is what caused that Tony Jefferson interception now the Tyrell sucks exactly that was very nice that was beautiful that was Tyrell sucks he didn't bite at all I wish and I'm not even mad at him I'm I'm not mad that he that he bit on it but you remember when the Texans were in the red zone and remember when the Texans were in the red zone let me just make sure the game ain't starting yet okay I just had to check I know y'all will let me know to all the game is starting okay there it goes right there so remember when Texans were in the red zone and Tom Savage they did like an in the round play action and and Zadaria Smith he could have had an easy sec to him he could have had an easy sec on Tom Savage but he bit on a play action you couldn't even be mad at him for biting on that because that was tough that was a real that was a nice play by the Texans now and last oh Matt Jude on Matt Jude on gotta chill out great player makes great plays but you can't slam people down you I know I heard it too they blew like 50 whistles before he even slammed the player down he got to chill out man he got to chill out you can't be doing that or the game ain't starting all the way yet or is it I see John Groot I mean J Groot and no John Groot and the other guy talking but anyway Jude on gotta chill man he got to chill so anyway oh no that's a replay okay they show on the replay all right but yeah he gotta chill now yeah Collins Collins was nice Collins did his thing I'm sure they're gonna get him more involved so let's see anyway see y'all after the game I appreciate y'all I look forward to seeing you after this thing is done we out