1. Data visualizations
In this chapter, we're diving deeper into how to communicate insights. First up is a tool you know already: visualizations.
2. A picture tells a thousand words
Visualization is a powerful tool. It helps us understand complex data at a glance and makes it easier to understand the insights we've previously identified in our data.
Many data tools and methods rely on visualization to convey their message, like exploratory data analysis, dashboards, or infographics.
An infographic is a visual, condensed summary of a topic intended to present information quickly and clearly, like the infographic about infographics on this slide.
3. Common types of visualizations
There are several types of visualizations, but which one you need comes down to the point you're trying to get across. We'll discuss some of the common types.
If you want to capture a trend, particularly over time, a line chart is the most straightforward way.
For visualizing relationships, use a bar chart to compare categories or a scatter plot to show the relationship between two variables.
If you want to visualize the distributions, a histogram or a box plot are the best choices.
If you would like to know more about the different types of visualizations, check out the link to Datacamp's data visualization cheat sheet.
4. What makes a good visualization?
What do you need to keep in mind when creating visualizations?
A first important tip is to ensure that the visualization is as clear and readable as possible by providing the correct labels and avoiding things like 3D effects, excessive use of color, or double axes, which make it harder to read the graph correctly.
To help your audience, you also need to focus their attention on the key aspects of the visualization. Do this by linking the visualizations to the key insights and highlighting key elements.
Even though you are already communicating by showing a visual, you still need to explain this to your audience and provide context. A technique to help you with this is the McCandless technique.
5. McCandless technique
The McCandless technique is a set of five steps that can help you explain a visual. The first step is to introduce the visualization by name.
The second step is to anticipate possible questions, for example, on which data the visualization is based.
The third step is to state the insight the visual is trying to convey. For example: 'the introduction of our new policy in 2007 has ensured that average length of hospital stay is steadily decreasing in our hospital, and is getting closer to the national average.'
The fourth step is to provide supporting evidence to our central insight or provide additional background if necessary.
The fifth and final step is the closing statement. This is the time to explain why this matters and to make the transition to the next point.
6. Let's practice!
Time to put your knowledge about visualizations into practice!