5.7 Review chart types - Video Tutorials & Practice Problems

<v Instructor>When building dashboards reports</v> for consumers, it is worth stepping back to get a handle on selecting the appropriate visuals for what is being measured. There are four basic presentation types that you can use to present your data. They are comparison, composition, distribution and relationship. Unless you're performing data science activities, you will primarily use the first two. In addition, trending is something that's often broken into its own category, as aspects of trending overlay both comparison and composition types. Over the next few slides, we will go through a few high-level questions you may ask yourself to help guide you towards selecting a proper visualization for your needs. Now, let me be the first to say that this is not meant to be a comprehensive discussion on visualizations and how to use them to help tell stories that are easy to follow and digest. This sub lesson is meant to highlight need to think about the selection of visualizations and what should guide your choices. As we go through and create our pivot charts in subsequent lessons, we will highlight the requirements and why we chose the visuals we did. So some of the first questions you may wanna ask yourself, are you trying to compare values? The following are useful for comparing one or many categories of data, as they can enable you to identify low and high points in the data itself. These are the column, bar, and line charts. Do you want to show the composition of something? The following are useful for showing how individual parts make up the whole. These are the pie, bar, and the variants of bar chart, stacked column and waterfall. Are you interested in analyzing trends? The following are useful if you want to know more about performance over time. These are the line and the variants of line, and the column chart and the variants of the column chart itself. Are you trying to understand the distribution of your data? The following are used to highlight outliers, display normal tendency and the range of data in your data set. They are the column and bar charts. Do you want to better understand the relationship between value sets? The following charts are useful for showing how one variable relates to one or more different variables. These are the scatter plot, bubble, line and variants of line. So that's it. Here's some additional resources to help guide appropriate visual selection. The following site has a tool called The Chart Chooser, which will help guide you towards appropriate visuals. In addition, Juice Analytics has an online chart chooser, as well, to help you choose an appropriate chart. Please follow the links to learn more. And that brings an end to this sub lesson.