Okay, now we're going to play a little bit of a game. So, it's the good and the bad and the ugly when it comes to data visualization. There's many different ways to visualize the same data as you're going to see when we jump into our Google Data Studio exercise as many different chart options are available to you. So, here's an example and I want you to think which visual presents this data set better. And the data set is Game of Thrones characters by gender. So, take a look. Most of you would probably say the one on the left. So, the one on the right, using something like a time series for this discrete analysis, generally is not the best thing that we want to do. I would actually never do that. And on the left, you just see a much clearer picture of the division between the count of male characters and count of female characters. I think of what are some additional ways you could add other than encoding attributes that could be beneficial here. So, one of the things that you could say that the graph in the right actually does give you is the actual numeric count of those characters. Whereas, the graph on the left does not have any kind of labeling or any other type of measure documentation that we can see what the actual values are. So, both of these graphs could definitely be improved but I would lean towards the one on the left and then add in something like a percentage or other data label that you conclude. Again, this is a continuation of something like the count-to-fives exercise where we added that blue coloring. Adding additional encoding measures like data labels, a color, a good use of white space can continuously help make your message clear. But at the same time, you don't want to overload the audiences' eye with too much going on on the screen. Let's try another one. Okay, now we have the same doughnut chart, but it's going to be on the right. And then we have a horizontal bar chart on the left. And then this is the data set of Game of Thrones books by page count. Take a look. Okay, so let's take a look at the one on the right. So, this doughnut chart has labels this time and a little bit hard to read because you have that white on a potentially white background there. And then you have a lot of these different books here, some of which are not showing like that teal color, The Winds of Winter, so because you can't actually display potentially negative values or zero values on a doughnut chart. That doesn't exist in that space, whereas, you contrast that to the bar chart on the left, you can see the last two books: The Winds of Winter, and A Dream of Spring. Why would those have zero values for the page count? And you probably have to be a Game of Thrones fan to know this but those books have not yet been written as of late 2017 when this was recorded. And at the end of day, you have to think of what is the ultimate message that you want to convey. If it's comparing page count between the books, maybe something like a bar graph with an additional label saying how many pages are in the actual book. Now, this is one of my favorite slides when it comes to talking about visualization theory. We tell you the benefits of cleaning up your data sets, writing beautiful queries and ultimately, finding those insights, in a larger part, if we had to do a pie chart on how you actually spend your time, maybe but 80 percent of that pie chart is going to be filled with doing data analysis and getting to that point of those insights, and maybe 20 percent of your time is actually going to be spent on building up those beautiful visualizations and sharing them with your peers. But, as we all know, a beautiful picture or visualization of those insights is large in part what the audience is actually going to care about. How you're delivering that message is just as important if not more important than the actual methods that you did to actually get those insights in the first place. Because at the end of the day, even though we both write beautiful SQL statements, unless you're presenting it to a peer who also wants to review the code quality that you have, a lot of times the executives or the other members in your organization are just going to see those visuals. So, put a lot of good conscious thought in how those visuals are being created and how that message is being conveyed.
