Objectivity in Data Visualization

The ability to interpret the truth, accuracy, and objectivity in data visualizations is incredibly important, whether you are creating your own visualizations or are interpreting those you see. This course will teach you these skills.
Course info
Level
Beginner
Updated
Apr 22, 2019
Duration
2h 1m
Table of contents
Description
Course info
Level
Beginner
Updated
Apr 22, 2019
Duration
2h 1m
Description

We live in a period of time where we can capture and process unbelievable amounts of data. In this course, Objectivity in Data Visualization, you'll gain the ability to evaluate the truth, accuracy, and objectivity of data and visualizations both for creating visualizations and for interpreting those created by others. First, you’ll learn about objectivity in data – the meaning of data and the impact of data selection on objectivity. Next, you’ll examine objectivity in visual elements – how the visual elements of a chart or graphic can influence objectivity or distort the truth. Finally, you’ll explore interpretation and storytelling – where you’ll discover that accurate data and carefully crafted visuals are not enough on their own to tell an objective story. These skills are especially important today as we are constantly bombarded with data and visualizations that claim to tell objective truth but are, in fact, full of lies, whether intentional or unintentional. By the end of the course, you'll be able to detect the lies and hidden biases in visualizations you see and will be able to create visualizations that you can stand behind with confidence.

About the author
About the author

Dan Appleman is a well known author, software developer, and speaker. Currently the CTO of Full Circle Insights, he is the author of numerous books, ebooks, and online courses on various topics (technology and other). His latest book is "Advanced Apex Programming" - advancedapex.com Personal Website http://danappleman.com.

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More courses by Dan Appleman
Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi everyone, my name is Dan Appleman, and welcome to my course, Objectivity in Data Visualization. Throughout my career as a software developer and an entrepreneur, I've had to deal with the challenge of objectively analyzing and visualizing data. One of my very first jobs involved creating the software for test equipment that captured and displayed large amounts of data, at least by the standards of the day. The products I work on currently capture, analyze, and display vast amounts of marketing and digital marketing data. Where early in my career I perhaps cared more about the mechanics and algorithms of working with the data, as time passed, I learned to care much more about the meaning of the data and its ability to tell stories and influence actions. I've learned that the amount of data is much less important than its quality, its meaning, and what one chooses to do with it. We live in a period where we can capture and process unbelievable amounts of data. At the same time, there seems to be a trend to increasingly ignore, dismiss, mislead, and manipulate that data. From executives with agendas to politicians with platforms, we are bombarded with data and visualizations that claim to tell objective truth, but are in fact full of lies, sometimes intentional, but often unintentional as well. Without the ability to evaluate the objectivity and truth of data and visualizations, the response is often to just go with gut feelings or to simply ignore the data. The results of this can be deadly. Consider the antivaccination movement. The ability to interpret the truth and objectivity in data visualizations is incredibly important, whether you are creating your own visualizations or are interpreting those that you see. It is a skill that everyone should have, not just those working in technology, and that is what this course is about. After a brief introduction to the nature of objectivity, we'll go into the three main modules. First, we'll cover objectivity in data, the meaning of data, and the impact of data selection on objectivity. Next, we'll look at objectivity in visual elements, how the visual elements of a chart or graphic can influence objectivity or distort the truth. Finally, we'll explore interpretation and storytelling where you'll discover that accurate data and carefully crafted visuals are not enough on their own to tell an objective story. By the end of this course, you may never look at a data visualization the same way again. You will be able to see their underlying truth, and the visualizations that you create will be what you truly want them to be and will accurately convey the information and stories that you want to tell.