"Making Decisions with Data Visualization" - Highlights
Key takeaways from episode 23 Making Decisions with Data Visualization of Bill Shander's Data Visualization, Data Storytelling, and Information Design - Lesson and Listen Series:
- Data visualization is crucial for enabling decision-making, as raw data can be boring and difficult to interpret.
- Understand the decision that needs to be made. Know what questions need answering
- Understand the data and its meaning in context. Know what your data is saying.
- The clearer you define questions, the more likely you'll gather and share data that helps your audience make the best decisions.
- Knowing the data and its relevance to the decision-making process is crucial, going beyond simply locating and calculating KPIs.
- Visualizations help to identify patterns and trends that may not be apparent in raw data, aiding in better decision-making.
- Creating visualizations is a consultative process
- The Listen part of the episode has an interview with Steve Wexler, an expert in data visualization & one of the very few inductees into the Tableau Zen Master Hall of Fame. He emphasizes:
- Time to insight is critical
- Personal connection to data increases engagement
- Graphic literacy ("graphicacy") is important for both creators and consumers of visualizations
- Humans are better at interpreting visual information than raw numbers
- Highlight tables or conditional formatting in Excel is a sort of a gateway drug to visualization
- Collaborate with stakeholders and iterate on designs
- Insert the audience into the dashboard to make it personally relevant
- Ensure that color choices are accessible & culturally appropriate
- Understand your specific audience and their needs. They are often drowning in data and are thirsty for insight.
- Don't blindly copy famous historical visualizations without considering context
- Stick to fundamental chart types (bar, line, and sometimes pie) for most business uses. Fun fact: William Playfair (1759 – 1823), the founder of graphical methods of statistics, invented several types of diagrams: in 1786 the line, area and bar chart of economic data, and in 1801 the pie chart and circle graph, used to show part-whole relations. They are still relevant after 220+ years
- Collaboration between stakeholders and practitioners is crucial
- Focus on providing the greatest understanding with the least effort
- Make visualizations about the audience and their goals
- The ultimate goal of data visualization is to help people gain insights and make better decisions, not to create art.
Recommended reading:
- "The Big Book of Dashboards" by Steve Wexler et al.
- "Bad-ass: Making Users Awesome" by Kathy Sierra
- "The Big Picture" by Steve Wexler
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