Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Data Visualization: Best Practices

via LinkedIn Learning

Write review

Boot.dev

The Most Addictive Python and SQL Courses

Train in Data

Master Production-Ready Machine Learning, Step by Step

Overview

Google, IBM & Meta Certificates – 40% Off

One Coursera Plus subscription covers most Professional Certificates on Coursera.

Unlock All Certificates

Learn how to build accurate, compelling data visualizations, as well as charts and graphs that look great and stand up to analysis.

Syllabus

Introduction

Best practices of data visualization
What you will learn
Exercise files

1. Why Data Viz Matters

The importance of data viz in today's market
A quick history of data viz
Our level of data literacy: The brain science
Our level of data literacy: The charts that matter
Using simple charts and graphs
Using complex charts and graphs
Challenge: Pop quiz
Solution: Pop quiz

2. Identifying and Shaping Your Data

Key questions to ask
Question 1: Who is your audience?
Question 2: What are your objectives?
Question 3: What data will serve your objectives?
Question 4: What chart or graph is best?
Challenge: The best charts to use
Solution: The best charts to use

3. Data Viz Mistakes to Avoid

Being a data fiduciary
Mistake 1: Putting form over function
Mistake 2: Improper use of scales
Mistake 3: Manipulating the axis
Mistake 4: Forcing your audience to do math
Mistake 5: Organizing data passively
Mistake 6: Assuming percentage equals pie
Challenge: Data viz mistakes
Solution: Data viz mistakes

4. Designing Charts and Graphs

Creating bar graphs in Adobe Illustrator
Creating pie charts in Adobe Illustrator
Creating line and area graphs in Adobe Illustrator
How to use labels and color

Conclusion

Thank you

Taught by

Amy Balliett

Reviews

4.7 rating at LinkedIn Learning based on 232 ratings

Start your review of Data Visualization: Best Practices