Organizations increasingly need someone to make sense out of all the “Big Data” they are generating. This course will teach you how to identify the signals hidden in your datasets and choose visualizations that tell compelling, interesting stories.
Data Visualization Designer is one of the hottest new careers in tech because organizations around the world are drowning in all the “Big Data” they’re generating. They need people with the skills to turn raw facts and figures into visualizations that tell a story and make an impact. In this course, Designing Data Visualizations, you'll learn how to use your creativity and intuition to find the insights in datasets, as well as basic data-analysis techniques, to create “enriched” data and choose the correct visual to communicate real meaning. First, you’ll see how to spot “signals” in the data – it turns out that human common sense and knowledge of context are not only still relevant, but absolutely crucial. Then, you’ll learn techniques like pivot tables, conditional formatting, and data joins and merges to generate clear insights, while avoiding the “Four Deadly Sins of Data Visualization.” Finally, you’ll explore what kinds of visualizations match up best with what the data is telling you. When you’re finished with this course, you'll understand how to look inside the data, pull out what your audience needs and is most interested in, and use that to design data visualizations that stick.
Course Overview Hi everyone. My name is David LaFontaine, and welcome to my course, Designing Data Visualizations. I'm a senior UX designer and researcher, although I also like to call myself a creative data scientist because I believe strongly in bringing together numbers and data and design and human factors. And this course is definitely going to help you learn how to use your creativity and intuition to transform raw data into compelling visuals that tell a story. This skill is in increasing demand as more and more organizations generate data that they need someone to interpret for them. Some of the major topics we're going to cover include discovering what we call signals in the data by using simple data analysis techniques like pivot tables, understanding how those signals are key to choosing the relationships to visualize, how to avoid the four deadly sins of data visualization, using interpolation and extrapolation to go beyond just what's in your data sets, and, finally, how to choose the visualization that best communicates what you see in your data. By the end of this course, you'll know the basic techniques that will help you turn raw facts and figures into visualizations that tell a story and make an impact. Before beginning this course, you should be familiar with basic Excel or spreadsheet functions, as well as common charts and graphics. I hope you'll join me on this journey to learn data visualization with the Designing Data Visualizations course here, at Pluralsight.