In the world of data visualization, choosing the right chart type plays a vital role in effectively conveying information to an audience. I have battled with this for a long time. You could imagine the meetings I conducted where I confused Manco and Exco because of mixed messages conveyed by my visuals/charts. While numerous chart types are available, it is crucial to select the most suitable one that communicates a message with absolute clarity. This article is for us to delve into various chart types and their unique characteristics, allowing data visualization specialists to make informed decisions about their visual representations.
Let us not confused our audience and rather share information about how to be better at making effective visuals. In so doing, it would be better for us to provide (Part 1) an overview of each chart type followed by (Part 2) how we can focus the attention of our audience. We know the hidden messages in data, and we have the power to bring these messages to life or squander the opportunity.
Part 1: An Overview of Chart Types
Bar Chart – The bar chart is a widely used chart type that presents data in rectangular bars, where the length of each bar corresponds to the value it represents. It is excellent for comparing discrete categories and their respective values. I used this to show trends especially to highlight seasonal peaks and floors. It is mostly well received by many meeting attendees. The downside is that not everyone is comfortable reading vertically. This could be solved by horizontal/vertical columns.
Column Chart – Like the bar chart, the column chart represents data using vertical columns instead of horizontal bars. It shares the same characteristics and applications as the bar chart but provides a different visual perspective. We don’t go wrong with this chart type because of most Exco members’ preferences. We can highlight anomalies and also predict where the shape of the next columns. Sometimes having a line instead of columns could do the trick.
Line or Area Chart – The line chart displays data points connected by lines, while the area chart fills the area below the lines, providing a visual representation of cumulative data trends over time. They are particularly useful for illustrating trends, patterns, and changes in data. The other nice part about this is that they remove clutter and the line (or area under the line) is ideal to visualise moving averages. Sometimes we might want to show the composition of our numbers, especially the positives and negatives.
Waterfall Chart – A waterfall chart demonstrates the cumulative effect of positive and negative values, displaying how an initial value increases or decreases over a series of intermediate values. This chart type is commonly used for financial data analysis and showcasing the contribution of different factors to a total. We also used waterfall charts to break down the numbers into categories. But at times we might be asked to show a minimalist approach.
Card – The card is a concise and minimalist chart type that showcases a single data point or a small set of data points, often used to display key metrics or summary information. We can also use this to highlight key metrics (KPIs) important to each Manco member. Imaging showing the headcount (HC) growth number on a card for the HR department. The number could be green when heading in the direction of strategy (increase or decrease HC) and red in the adverse direction. Sometimes we could be asked to show single data points in a group.
Scatter Chart – Scatter charts represent data as a collection of individual data points plotted on a Cartesian coordinate system. They are effective for identifying relationships, clusters, or correlations between two variables. Following our HR department example, we could show HC growth by seniority on a plot. This will allow us to see movements.
Tornado Chart – The tornado chart, also known as a butterfly chart or population pyramid, visualizes the comparison of two variables using bars that extend in opposite directions. It is commonly used for comparing the positive and negative impacts of different factors.
Box & Whisker – The box and whisker plot displays a statistical summary of a dataset, including median, quartiles, and outliers. You can see all of this on Datapoint. It is ideal for an audience that needs descriptive statistics per data point. This is because it provides a concise representation of the distribution and variability of the data. I have only learned about this in technical analysis. Perhaps investment analysis might be using Box & Whisker chart a lot.
Tree Diagram – Tree diagrams represent hierarchical structures or relationships between categories. They are commonly used to visualize organizational structures, decision trees, or hierarchical data. My Exco loved this type of diagram to show vendor spend analysis. We could easily see who the biggest vendor is in my category and how much has been spent on them. Depending on your preferences, the diagram groups small values together as other categories.
Heatmap – Heatmaps use colour variations to represent values in a matrix format. It might look like a tree diagram at first and you will soon recognise that each block size is not a representation of the amount. They are excellent for displaying large datasets, identifying patterns, and visualizing the intensity of values across different categories. Try this chart if you want to show areas that have a high number of backdated journals compared to others without using heat – colour grading.
Map – Maps present data geographically, allowing for spatial analysis and insights. I was excited to see this feature on Power Bi after struggling with Power View for a long time. They are used to display regional or global data, such as population density, sales distribution, or geographic patterns. I used this to remind Exco about the location of a market being analysed. Having a visual to show the location often changes perspective.
Donut or Pie Charts – Donut and pie charts represent data as sectors of a circle, with each sector proportional to the value it represents. They are useful for illustrating the composition or distribution of data categories. They are also preferable if you want to highlight something. But before we could start using this chart type, let us spend some time discussing how visuals grab attention.
Part 2: Focusing Audience Attention using Visuals
To captivate and engage the audience effectively, data visualization specialists can employ the following techniques:
1. Highlighting Values: (1) Colour can be a good attention grabber, thus using vibrant or contrasting colours to draw attention to specific data points or categories; (2) Enclosure of important data points or categories within shapes, such as boxes or circles, to emphasize them; (3) Shaping can also be useful when utilising distinct shapes or symbols to highlight significant data points or categories; and (4) Position on what we want to talk about/ critical data points or categories in prominent positions within the visual to attract attention.
2. Presenting and Comparing Values: (1) Use the length of bars or lines to showcase the magnitude or scale of values which could be ideal for bar and column charts; (2) Vary the size of visual elements, such as circles or icons, to represent different values or proportions; (3) Annotation could be useful by adding text or labels to provide additional context or explanation for data points or categories; (4) Ordering you data can make a huge difference thus try and arrange data points or categories in a specific order to convey a particular narrative or emphasize comparisons; (5) Display average values or reference lines to enable better understanding and comparison; (6) Use dual axes to visualize two different scales or units on the same chart, allowing for direct comparison.
Conclusion
Choosing the right chart type plays a vital role in effectively conveying information to an audience. Now we don’t have to battle with data visualisation anymore, especially after understanding chart types. Choosing the right chart type and employing effective visualization techniques are crucial elements in conveying data with absolute clarity. By understanding the characteristics and applications of various chart types and implementing visual techniques to focus audience attention, data visualization specialists can ensure that their visualizations effectively communicate insights and drive meaningful understanding. Remember, the best chart is often the simplest one that conveys the intended message clearly.
