Okay, let's do a quick demo with this e-commerce dashboard we have readily prepared for you. And then we'll jump into a lab, where you're going to try this on our own IRS data set. So, here we find ourselves inside of the Google Data Studio homepage. Here is where you're actually going to be creating those new reports. Or if you're like me, you're copying an existing sample of a report that's already been created. So, this is an example of an e-commerce dashboard report that's been created using the data set of Google Analytics behind the scenes. Which tracks things like revenue, and conversions for websites. So, let's take a look at what this report is, and how it was created. I'm going to highlight a couple of things along the way, and you can use that knowledge in your next lab, when you're diving into the IRS dataset. So first and foremost, I got this report from the publicly available samples, and best practices of Google Data Studio dashboards. And then, what I did to make it editable for myself is in the up right hand corner. If you find a report that you like, or if you have multiple copies of a report that you want, you can actually make a copy, an entire copy of this report, which will then make it editable for you. And just as caveat, if you don't have the access to the underlined data set to begin with, just making a a copy of the report is not going to change any kind of data access. It's just going to give you access to a lot of the visuals, as well that you can copy. Okay, let's take a look at what we're facing with. So, a couple of critical points. So, you see at lot of visuals here on this canvas is grid lined. To help you align these different objects, that you're going to be dragging, and creating here. And those grids don't show up for the ultimate end users. So, switching over to the end user view by clicking on view, you'll see that this is how everything is going to be displayed. And you can see as you hover all these visualizations, you get these neat cards as well that pop up. Going back into the altering mode, or the editing mode, let's cover a few of the different basics. So say you have a visualization, this revenue by city, that after feedback from your peers you didn't like. So you can delete that, and of course Ctrl+Z, or the undo, also works. So if you wanted to bring things back, you could do that as well. But, I'm going to remove them, and I'm going to remove this title here. And I really want to get is a copy of this visual here, this horizontal bar chart. I want to get the average order value by the device category. So, the feedback we've been getting is that hey, we really love those visuals that you've been doing, breaking things down by device category. And we want to see more of those. So I'm going to right click, and duplicate this visual. Bring this one down here, automatically puts it into a little bit of an alignment there, and now I have an exact copy. Now once you click on a visual, that's going to open up your dimensions, and metrics. Metrics is synonymous with measures. And it shows the data source, that you're pulling from. And if you wanted to play around with the chart type, you can actually edit that on the fly here. So let's go ahead, and remove revenue, and remove the sessions that we have here. And what we want to do is change sessions, by clicking on that till, and this is your data scheme on. And this is what Google Analytics looks like, it's gotta bunch of nested fields. Inside of Ecommerce, there should be Average Order Value, there is fantastic. We've got the average order value locked in there now. And now you can see, the Average Order Value is much higher. On desktop, it is a mobile or tablet, if you wanted to know what that value is without having to read the label here, you can go into Style, Show data labels. And again, a lot of this is as much of an art form as it is a science. So play around within the tool, see what the best way to display, and visualize the message, that you want to communicate is. And then, actively solicit feedback from your peers, and your audience members, who are going to be interpreting, and then getting those insights from these reports. Another thing that we want to highlight, is the interactive elements of the report. So all the way at the top, you'll notice that there are different filter options, that have been set up. So, you can click on one of these filters, and you can see which data is populating this. So in this particular case, this Ecommerce dashboard has the ability to filter all of the underlying data. It's a global filter by the users country. And that's this dimension field that was populated here. Same thing for the traffic source, and the medium in which the user got to that website, and then the user type as well. So, if you wanted to create new filters all the way at the top, you can create a new filter control with this filter icon here. The rest of these icons, you're going to be clicking, and dragging, and creating all of the different types of charts that you can create. A very popular, and powerful one is this scorecard, which allows you to highlight just key central facts, or central numbers. And on top of that is just the name of that metric, which in this case is just the sessions. Now for stylistic elements of course, you can add things just like colored rectangles, or free text fields, or image logos. But, if you find your visualizations are getting too crowded. Like you're displaying too much on one page, and your audience is basically saying hey, I love this information here, but I really only want to look at, say this top half. And everything beneath it, you can move to an underlying detail page, you can actually add multiple pages as part of your dashboard report. So, right now we're in page one of two, and I have created a blank page two, that I'm going to toggle over to now. So a common practice in report building, and a lot of you, this may resonate with you is to have a summary level report, with a couple of different categories. And those users, say a person's interested in really exclusively revenue. You could have a dashboard that's exclusively focused on revenue, as one of the child dashboards in this report. And you would do that by setting up all those revenue visuals on a sub-page, that you can then hyperlink to from that main page. Okay, that is a very fast tour. We have different types of visuals, that are being displayed. We can toggle out, and see what those visuals are actually going to look like and interact with them, with the filters, and everything that's present here. And again, on the back and all this is powered by the data set that's ingested inside a big query. So those queries, much like your filtering out from the Google Data Studio here, are actually going to be running on the back. And it's at a big query, and returning the data for Google Data Studio to visualize. Okay, so that's the tour. The last thing that I'll mention is, you can share this dashboard with others. So, can share with both your other admin peers, that you want to help edit this Google Data Studio dashboard collaborating with you. Or your audience, who you may want to have just in view-only mode, who can view the results of your reports. Okay, next up is your lab on visualizing the IRS data cell. Throughout this module, we see that visualizing data is both an art, and a science. And we've just barely scratched the surface of visualization theory, and we discussed things like pre-attentive versus post-attentive kind of processing for that quick idea brain understanding. And along the way we say some terrifically bad ways to visualize data, and hopefully get a best a few practices to do it right. Lastly, we looked at Google Data Studio, which is the visualization platform we'll be exploring into more depth in our next lab.
