Data science isn't all logic and math, your job is to uncover the humanity in the numbers. Learn about the value of story, and how visualizations can help you to see it.
(light music) - Data is truth. Data is fact. Our goal is to make beautiful, impactful and insightful visualizations out of these fact-based things. So the truth that is contained in that data must drive every decision we make. We need to take a fiduciary standpoint, a position of objectivity, trust and care when presenting data. Think first and foremost about being honest with your data and have a skeptical eye on your own work. Try to imagine what a naysayer would say about it and be sure the decisions you make will all help you make your case without damaging your credibility. Be responsible and own your truth. - Your job as a data science team is to reveal the humanity behind the numbers. That's why you shouldn't just communicate the information in the language of numbers. It's the story that the presenter tells that has all the value. That's why you should start with a story. You don't want to put too much emphasis on the data. The data won't be worth anything unless it connects with the audience. The data on its own can't do that. It's the story you tell about the data that will help the audience connect to some meaning. - We live in a world full of data. Making sense of it can be a challenge. There are many tools out there that allow you to create beautiful, interactive data visualizations that help you to see and understand your data. By knowing the most effective chart type for your data and the questions that you want to answer, you'll be able to design a beautiful visualization that will bring your data to life. - [Narrator] There's nothing like spending dozens of hours on a great piece of visual content only to find that one graph of data has not been properly visualized. This can make a great design seem rushed, misunderstood or in some instances, intentionally inaccurate. - [Narrator] Ggplot2 is part of a collection of our packages designed for data analysis, known as the tidyverse. The tidyverse packages provide our developers with a set of tools that follow the entire data analysis life cycle. You can use ggplot2 to create your own data visualizations, learn about the grammar of graphics and how ggplot allows you to build visualizations piece by piece, discover how to create your own basic visualizations and then how to beautify them by applying different aesthetics, learn how to perform common visualizations using math data.