"I have data, now what?” This course covers how you can take hundreds or thousands of rows and columns of data and visually communicate a powerful story that will make a lasting impact on your viewers.
How do you take hundreds or thousands of rows and columns of data and communicate a powerful story that leaves a lasting impact on viewers? In this course, Making Data into Something You Can See, you will learn how to prepare data for presentation. You will explore the best visual design principles for data, including how to properly use colors, shapes, font styles, and much more. You will learn how to parse and simplify data in Microsoft Excel, and make your visualizations coherent with a variety of charts. You will see Tableau and other tools you can use to make your data tell the story you want it to tell. By the end of the course, you will know how to visually communicate your data story to the world.
Troy Kranendonk is a Curriculum Manager for Data Access and Analytics as well as an author with Pluralsight.
He considers himself to be a Pixel Ninja. Troy studied Digital Media Education
and loves to innovate and push the boundaries in with tech.
Course Overview Hi everyone. My name is Troy Kranendonk, and welcome to my course, Making Data into Something You Can See. This course looks at gathering, prepping, and the overall best design principles for your data. We will go over making your visualizations make sense and one that will tell the story that you want it to tell. This course answers the question, I have data, now what? We are going to cover how you can take hundreds or thousands of rows and columns of data and visually communicate a powerful story that will make a lasting impact on your viewers. Some of the major topics that we will cover include gathering and organizing your data, making good design choices for your visualizations, choosing the right charts, and what tools you can use to create your data visualizations. By the end of this course, you will know how to parse and simplify your data and make great design choices so that you can visually communicate your story to the world. I hope you'll join me on this journey to learn data visualizations with the course, Making Data into Something You Can See, at Pluralsight.
Gathering and Organizing Your Data Hi. My name is Troy Kranendonk. Welcome to Making Data into Something You Can See. Today, I'm going to introduce you to the world of data visualizations. What is that, you say? Well, it's data plus magic equals visualizations. Well, sort of. In this module, Gathering and Organizing Your Data, we are going to cover visual answers to your questions. We all have questions that can be answered visually. It's one thing to see a graph, it's another thing entirely to see its meaning. Let's talk about data and how to present it with a more visual viewpoint. Data Glutton. We are overloaded with data. We will discuss making our visuals stand out in a more crowded space. Parse and Simplify Data. We will check out a brief example of cleaning up some raw data for further analysis. And finally, we'll dive into Analyze Data, where we will look at an example of using visual graphs as a way to see how your story could develop. And then, we'll cover best practices for picking a chart.
Making Good Design Choices for Your Visualization Welcome to Making Good Design Choices for Your Visualization. You cannot escape design principles when thinking about data visualizations. In fact, it is one of the most important factors on telling your data story. We will be going over various ways to make your data look great, and more importantly, making it easier to be rapidly perceived. This module is not a Design 101 module. Its purpose is to think about what makes design sense in the world of data viz's. So in this module, we will go over why design choices matter. We want viewers to be less distracted and to be able to find their answers fast. I am also going to cover a lot of mini design choices that will play a giant role in creating your data visualizations. For starters, we'll go over visual elements, which is crucial for making your viz stand out. Example, similarity and contrast, dominance and emphasis, scale and proportion, hierarchy, balance and symmetry. Also, we'll go over typography and finally, iconography. As you can see, we've got a lot to go over, so let's get started.
Choosing the Right Chart Welcome to Choosing the Right Chart. Selecting the correct charts or graph to represent your data is key. We will be going through the various ways you can visually communicate your data. Now it's super important that we cover things like different types of data: quantitative, discrete, continuous, categorical. And that leads us into different types of data relationships like part to the whole, distribution, etc. , and all that information will lead us into what types of charts are best to demonstrate those data relationships or those different types of data. We'll see you guys in the next clip.
Tools for Your Data Visualizations Now you can use a lot of tools to achieve great data visualizations. In this module, I chose to go over a few different ones. This isn't an introduction into the tooling, but just showing the tooling's capabilities. In this module, we will go over the following: Tableau; D3; Python and some of its packages; and finally, infographics with Illustrator. With that, let's begin.