Hi guys. In this video, I'm going to show you some examples of dashboards that will be useful to you, in order to test the financial assumptions of your watershed model. Now, I want you to know, we do not want you to duplicate these dashboards. In fact, it's important to us that you don't. You will be tested on whether or not you can make some of these graphs, and whether the graphs you are showing display the correct information. But you are not going to be tested on whether they look exactly like what I'm showing you here or whether they're in the exact same place. That's going to be all up to you and your creativity and what you think is best. So make sure you keep that in mind. What I'm showing you here is just for inspiration and to show you some types of graphs that I haven't shown you before. The next thing I want to warn you, is that I've purposely set up the model I am displaying in these dashboards, so that they are incorrect. I did that because we really want you to come up with the model and answer with that model on your own. So, I didn't want to give you way the answers. So, don't make your dashboards can be exact the same answers as my dashboards. If you do, we'll have the incorrect answer. The other, two things I want to tell you before we do something to the dashboard themselves is that first of all, dashboards are different than presentations or at least the way we are using it in this case, it's very different. The dashboards here are meant to show you all the information you need to make a decision in one place quickly and efficiently. That means that you're going to see a lot of information there and it's going to be pretty busy. So you would never use this format in a presentation. You would never put all of a dashboard in one slide, for example. Because your audience would be looking all over the place and you wouldn't be able to control where they are looking. You would only use a dashboard of this kind for study, when you're trying to study the results of what you are seeing. And that could be for you to study it, or for someone else to study it. And I'll use that as a segue to say the last thing I wanted to tell you. Which is that there are two reasons you might want to make a dashboard like this. One, is so that you can convince yourself of the reliability of your model. The other, is so that you can convince somebody else of the reliability of your model. I say that because you should feel free to make whatever visualizations you need in your first dashboard. But then before you show that dashboard to someone else or to another audience. You should always find out whether your audience likes getting that information in a different type of way or whether they're used to seeing that information in a different type of way. In my case, I ended up having to make two dashboards too. I made the first one for myself, and then when I showed it to other people, they said they really wanted the information they were seeing in a different format. So I did that for them as well. So I will show you both of those versions. And you should think about that yourself, when you are going through the rest of this project. With that, let's jump in and take a look at these dashboards. So here is the dashboard I made for myself. Let me orient you to the different types of information I wanted to see. First of all, over here in this part of the screen are all of my parameters or all of my assumptions. So I made a different parameter for each financial assumption in my model. And I can change those in each one of these boxes. Over here, are the basic metrics that I think are most important from making the my decision about whether watershed should convert their properties to short term rentals or not. I have actually eight different metrics here. In this bar graph, I'm going to start with dividing them into four groups, and you'll see why there are actually eight groups here. So in this bar graph, I'm showing the yearly cash flow for all the properties that are considered profitable based on this cut off. The cut off we learned about during illicitation, that was $6,000. So if any property brings in, at least a profit of $6,000, they're considered profitable and I total all of those of the profits from those profitable properties together and I show them here in this bar graph. This bar graph shows that cash flow from those profitable properties during the conversion year. And this bar graph shows the cash flow for those profitable properties, all the years after that first conversion year. In this bar graph, I'm showing the profits rather than cash flow for the conversion here. And in this bar graph, I'm showing the profits rather than cash flow for all the years after the conversion year. Now within each one of these bar graphs are actually two different bars that represents two different types of information. The dark blue bars on the inside here, represent the totals of all the profitable properties when I define profitable properties based on the original assumptions in my model. So these are all the ones that we got during elicitation. The light blue bars on the outside, on the other hand, represent the profits and cashflow as calculated if you change the financial assumptions based on all of the bars put in over here. So what you'll see, if I change any of these parameters, is that the dark blue bar will stay the same, but the light blue bars will change. So if I make depreciation here is three for example, the light of bar change but the dark will varies all stay the same. One other thing that I have in this part of my screen is the Total Cash Needed if I was going to convert all of the Profitable Properties based on the parameters is there, defined over here. So everything other than this dark blue bars in my dashboard are based on the parameters that I'm entering here rather than the original parameters. This dark blue bars are the only part that I'm showing that can give you an idea of how changing the parameters will relates to the original parameters themselves. This part of the screen shows me all of the aggregated data from the profitable properties. Everything down here on the bottom half of the screen shows me all the data from the unaggregated profitable properties. So it's showing me the data for each individual property. Here this top part, of this graphs I'm showing over here is a box plot. And you guys know how to make that, and have seen those before. So each one of these dots shows the profits that you could expect from that specific property, if you converted it to a short term rental, taking into account the conversion year. So these are the profits after the conversion year. And you can see that if you hover over one of the data points, it gives you all the data about that specific property. I'm showing the same data in a different way down here in this graph. This graph is what's called a histogram, and I will show you how to make these in a later video. But basically, what they are, is they take all of the numbers here on this X axis, they break them into bins. So in my case, I've broken them up into $10,000 bins, and then it counts how many of these points are in each one of those bins. So, for example, you see that there's only one point here, that's over $160,000, or has increased profits of over $160,000. So I have only one data point here in the $160,000 bin. Down here though, you can see that there is one property that is 61,000 or has profits of 61,000 and another property that has $68,000 of profits. So there are two, this one as over 70, so there's only two data points that are in the bin from 60,000 to $70,000, those two data points are represented here. So this is just a different way of giving you an idea of the distribution of the individual profits within the properties, the profitable properties. And lets you know in general, most of your properties are going to have profits that are in the, according to the fake model I'm showing you here, 5,000, 10,000, 15,000 or 10,000, 20,000, $30,000 range. You don't have too many that are outliers out here, but you do have some important outliers and so these are ones you would definitely want to consider converting. Over in this part of the screen, I'm showing you where each of these individual properties are located. So this is actually a pretty neat type of graph, I did not make up this type of map. This is using what's called a jittering technique which I will show you using other materials, later on in the course, how to make. But since we have a unique issue with our data, in our data we have many data points that are in the same geographic location. So if you try to map them, it can be very tricky especially if you want to be able to show things like, what type of property type is in each data point. If you use a normal map, or use normal mapping techniques, those data points will just get put on top of each other. So what the jittering does, is it takes all the data points, from the same geographical location, and it puts them in a circle around that geographic location. So, all of these data points are from Miami, Florida, for example. So I'll show you how to do this later. There are a couple other features of this dashboard that I thought were useful at least were useful to me. Every time you click on a data point in the map, it will highlight that data point in both of these charts over here. Likewise, if you click a data point on either the box plot or, the histogram. It will highlight the corresponding part on the map and the e box plot. So that makes it easy to be able to visualize and, of course, when you hover over any of these data points it also gives you the actual numerical values for them. So you can either visualize, the properties of these data points, these individual, or you can actually see the raw data. There are a couple other quick things I wanted to point out to you. First of all, if you don't remember, the way that unhighlight a data point is to just click on it again. And you can do that in any of these visualizations. So if I click on this bar and then click on it again it will unhighlight. The other thing I wanted to show you is that, it's not just the, either the bars or the graphs or this number that are changing when I change the parameters. I also made it so that my title changes. So I wanted to be able to tell myself easily, how many profitable properties are there when I make the assumptions that I've indicated in these boxes. So you can see that if I change, use parameters. This number of total properties will change as well. Save it again. So that's based on a calculation and I will show you how to do that. So that gives you an idea of the dashboard I made for myself, in the next video, you'll see the dashboard I modified for a different audience.
