As a data analyst, you probably already know how to build visualizations and use tools like Excel and Illustrator. This course challenges you to go beyond the data, beyond the software, and start thinking more clearly and strategically about the foundations of great communication design. Bill Shander, founder of Beehive Media, focuses on the key challenges analysts face trying to communicate complex information, and how visual communication can help. He breaks down ten key components of great data visualizations?built in any program?and shows innovative ways of rethinking the slides, charts, diagrams, and templates you work with every day.
LEVEL – Beginner
COURSE TOPICS:
Why visual communications matter, and how they work
Communicating via story
Communicating with color
Using legends and sources
Sketching and wireframing
Rethinking slides, charts, and diagrams
Rethinking your templates and brand guidelines
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Instructor’s Welcome Note:
– Welcome to Data Visualization For Data Analysts. I’m Bill Shander founder of Beehive Media an information design and data visualization consultancy in Boston. This course is intended to help data analysts. People who are neck deep in data all the time. You already know how to work with and think about and even visualize data, I bet. It’s what you do everyday. But I’m going to help you get beyond the data and think more clearly and strategically about how to present that data to an audience. We’ll cover a bit about the primary challenges we face as communicators in today’s world and how to begin to think about solving them.
Then we’ll go through ten primary lessons. The most important things to think about when visualizing data for your audience. So you’re not simply kicking charts out of Excel, Stata, Sas, or whatever tool you’re using. But rather you’re really delivering the best visualization to tell the story you’re trying to tell. And I’ll share some examples of redesigned visualizations I’ve done to make the theoretical more tangible. I hope you find the content fun and interesting and of course helpful in your day to day data analysis practice.
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