The Data Visualization Process

The process can be summarized as follows:

1. Choosing the Right Data for Your Narrative

You've probably heard that people are "wired for stories." Let's keep this brief. According to the 2021 Data Visualization: State of the Industry survey, "pen and paper" ranked as the sixth most utilized tool, proving that even in a digital age, many still rely on traditional methods.

It's common for individuals to feel overwhelmed by data, often due to confusing dashboards that hinder their ability to formulate meaningful questions. Drafting your "storyboard" can help clarify your thoughts and identify the relevant data points necessary for effective communication. Personally, I always sketch out the visuals I plan to create before diving in.

Your approach may vary based on your familiarity with the data at hand. Typically, I identify two primary steps:

• Analyzing data to derive insights.
• Visualizing those insights to persuade others.

This discussion will concentrate more on the latter, but we will revisit the initial step in a future installment. You might have a clear idea of your message, allowing you to seek out supporting data, or you may adopt an exploratory mindset to uncover insights as you analyze the dataset. Frame your narrative as a series of questions, allowing each data-driven answer to advance your argument.

Consider the context and the impression you wish to leave on your audience. For practice, here are some excellent data resources:

Additionally, the publications I mentioned in the first data special are great for inspiration.

2. Selecting the Right Visual

Many tools, including Excel, Tableau, and Google Sheets, offer auto-suggestions for charts based on your data, though they don't always hit the mark. General guidelines can aid in selecting the most appropriate chart type, serving as a classic reference when you find yourself stuck.

These resources can help keep you on the right track. However, we should also contemplate the precision needed for our message. What specific comparisons do we want to highlight? Are we illustrating a broad trend or a precise causal link?

Think about your audience: Will they engage with the visuals, or do we need key findings to stand out? Answering these questions can guide you toward selecting the right format.

For instance, a simple straight line between two points effectively conveys precise information. From an evolutionary standpoint, we are naturally inclined to recognize such figures in our environment.

Consider this example from The Economist:

The chart clearly illustrates that the gap in prize money between male and female players widens as their rankings increase. The x-axis uses a log scale to emphasize higher rankings while grouping lower rankings to depict a general trend. The visual effectively directs attention to significant figures, much like the ukiyo-e artists influenced by Monet's work.

At the upper end of the scale, the stark contrast between Djokovic and Barty is evident, while still providing context with other top players. While it's easy to argue Djokovic's superior performance in 2021, it doesn't fully explain the growing disparities across rankings.

For more generalized points, color can be a useful tool, particularly in maps. The Economist excels at producing compelling visualizations, as demonstrated in another example that depicts the most streamed Spotify songs by language. Users can quickly discern that Spanish-language songs prevail in Spanish-speaking countries, with grouped country visuals facilitating navigation through extensive datasets.

3. Eliminating Clutter

If you're looking to me for advice on simplicity, it might be akin to asking a Labrador to play the piano. While I may not excel at minimalism, I recognize its importance in effective communication.

Let’s examine how experts enhanced a visualization I created by simplifying it. Recently, I shared charts regarding the male-to-female ratio of athletes in the Beijing Winter Olympics since 1924. Initially, I opted for pie charts to demonstrate composition and total share, adding a larger legend for clarity.

However, The Economist produced a more streamlined version using line graphs, making trends more apparent. Their approach emphasizes the gradual progression toward a 50/50 split while keeping the visual clean and straightforward.

4. Annotating Your Visuals

Recently, I encountered a language style guide that discussed the "curse of knowledge," which resonated with me. Imagine hiding an item in a room, assuming someone will easily locate it, only for them to struggle. Your familiarity with the item's location clouds your understanding of what someone else might perceive.

This concept frequently applies to data visualization. After conducting analysis, the insights seem self-evident, leading to a reluctance to label findings, which can appear patronizing. However, successful data visualizations tell a story, guiding viewers to conclusions by utilizing every tool at their disposal.

For example, a chart with highlights and annotations can clarify key points. To improve your work, ask someone to review your visualization and summarize what stands out to them. If their feedback diverges from your intention, consider adding labels or reevaluating your chart type.

In the last annual data visualization survey, participants identified "lack of time" as their greatest obstacle, illustrating why producing effective visuals can be challenging.

Next time, we'll delve into data visualization tools and explore further inspiration, including the best historical and contemporary examples.

The first video titled "Data Visualisation: Your First Step into Data Science" offers an introductory look at the fundamentals of data visualization. It discusses the importance of visual data interpretation and provides insights on how to get started with data visualizations.

The second video, "Designing Data Visualizations," focuses on the principles of effective design in data visualization. It emphasizes the importance of clarity, simplicity, and audience engagement, providing practical tips for crafting impactful visual representations of data.