Data Visualization: Best Practices
1h 38mBeginner2021-12-13
Authors

Amy Balliett
CEO and Founder of Killer Visual Strategies
Course details
Media and marketing efforts often rely on data visualizations to prove a point quickly. But poorly designed visualizations can be misleading and can even become a source of global scrutiny. To succeed in design and marketing today, you need to know how to interpret and properly visualize data. This course, developed and led by Killer Infographics CEO, Amy Balliett, walks you through the ins and outs of creating accurate and compelling data visualizations. She shows you how to identify and shape your data with key questions, as well as how to avoid common data visualization mistakes. Amy covers creating bar graphs, pie charts, line graphs, and area graphs in Adobe Illustrator and goes over how to better contextualize your data visualizations with labels and color. Using these tips, you'll learn how to stand out from the crowd and create charts and graphs that combine precision with visual appeal.
Skills covered
IllustratorData VisualizationAdobeLearningData ScienceBusiness Analysis and StrategyBusiness Software and Tools
Concepts
0. Introduction
- 01 - Best practices of data visualization
- 02 - What you will learn
- 03 - Exercise files
1. Why Data Viz Matters
- 04 - The importance of data viz in today's market
- 05 - A quick history of data viz
- 06 - Our level of data literacy - The brain science
- 07 - Our level of data literacy - The charts that matter
- 08 - Using simple charts and graphs
- 09 - Using complex charts and graphs
- 10 - Challenge - Pop quiz
- 11 - Solution - Pop quiz
2. Identifying and Shaping Your Data
- 12 - Key questions to ask
- 13 - Question 1 - Who is your audience
- 14 - Question 2 - What are your objectives
- 15 - Question 3 - What data will serve your objectives
- 16 - Question 4 - What chart or graph is best
- 17 - Challenge - The best charts to use
- 18 - Solution - The best charts to use
3. Data Viz Mistakes to Avoid
- 19 - Being a data fiduciary
- 20 - Mistake 1 - Putting form over function
- 21 - Mistake 2 - Improper use of scales
- 22 - Mistake 3 - Manipulating the axis
- 23 - Mistake 4 - Forcing your audience to do math
- 24 - Mistake 5 - Organizing data passively
- 25 - Mistake 6 - Assuming percentage equals pie
- 26 - Challenge - Data viz mistakes
- 27 - Solution - Data viz mistakes
4. Designing Charts and Graphs
- 28 - Creating bar graphs in Adobe Illustrator
- 29 - Creating pie charts in Adobe Illustrator
- 30 - Creating line and area graphs in Adobe Illustrator
- 31 - How to use labels and color
Conclusion
- 32 - Thank you
Related courses
- Data Visualization with Matplotlib and Seaborn
- Data Visualization with Python in Excel
- Power BI Data Analyst Associate (PL-300) Cert Prep: Creating Reports in Power BI
- Python for Data Science Essential Training Part 1
- Data Analytics: Dashboards vs. Data Stories
- Introduction to Career Skills in Data Analytics
- Using Tableau to Discover Powerful Business Insights
- Microsoft Excel to Power BI
Related learn paths
- Master the Concepts of Data Visualization and Storytelling
- Prepare for the Power BI Data Analyst Associate (PL-300) Certification
- Visual Communication for Business Professionals
- Introduction to Fundamental Skills for Data Work: Data Storage
- Advance Your Database Administration Skills
- Database Foundations: From Concepts to Applications
- Master Dashboards and Data Viz in Power BI
- Advance Your Data Engineering Skills