In our previous article, we discussed the pertinence of data visualisations, as well as leveraging tools (ahem, Tableau) to create powerful visualisations. This week, let us revisit the foundation of data visualisations and go back to basics. Before we can create meaningful data visualisations, we must first understand the principles and process of effective visualisations.
The 5-Step Process of Data Visualisation
1. Define Your Objective
Before you dive into creating visualisations, it is imperative to have a clear understanding of your objectives. Ask yourself what message or insights you are trying to convey. Are you trying to spot trends, make comparisons, or tell a story? Having a clearly defined end-goal will guide your decisions in crafting impressive and well-suited visualisations.
2. Gather and Prepare Data
Ensuring that your data is of good quality is the cornerstone of effective visualisations. Your best effort will render futile if your data is not accurate, complete or relevant to your goals. Before diving into the visualisations, clean and format the data to make it suitable for visualisations. Use tools like Excel, Python, or R to help prep your data for some sprucing up!
3. Choose the Right Visualisation Type
Next, it is pivotal that the appropriate visualisation type is chosen for effective communication, as each type serves a different purpose. Some visualisations that we know and love include bar charts, line grapes, scatter plots, pie charts, etc. When making your decision, carefully consider the data you are working with, as well as the message you wish to convey.
Image source: https://www.polymersearch.com/blog/data-visualization
4. Create the Visualisation
With that in mind, it is then time to materialise and execute your plan, i.e., creating the actual visualisation. Tools like Tableau, Excel, Power BI and Python libraries (e.g., Matplotlin, Seaborn) can help bring your data to life.
5. Refine and Interpret
Last but not least, take some time to refine your visualisation by adding labels, legends and titles for clarity. Then, interpret and derive insights from your well-crafted visualisations. Ask yourself what the patterns and trends in the data reveal. Most importantly, remember that your visualisations should answer the questions posed in step 1.
Characteristics of Good, Impactful Visualisations
- Clear and Easily Comprehensible: A good visualisation should present insights in a manner that is both accurate and easily understood.
- Relevance and Simplicity: Each and every element in your visualisation should serve a purpose and have relevance to your objective. Avoid clutter and distractions to ensure that attention is not drawn away from the main point. Less is more – keep your visualisations simple to convey your point effectively. Excessive information, labels, or use of unnecessary embellishments may overwhelm viewers.
For instance, the graph on the left adequately conveys the message, but the one on the right does the same without the extra lines and colours to distract viewers.
- Accuracy: Ensure that your data is accurately represented, as misleading visualisations can lead viewers to draw incorrect interpretations.
- Consistent Scaling: While on the topic of accurate data representation, it is crucial to ensure consistent scaling on axes. Inconsistent scaling may distort data and mislead viewers. For instance, if you use images to represent a measure of data within a bar graph, the image size should be standardised across columns.
Image source: https://online.hbs.edu/blog/post/bad-data-visualization
- Engagement: Lastly, engaging visualisations will capture viewers’ attention, promote curiosity, and encourage exploration. Use colours, interactivity and story-telling to captivate viewers.
In your journey to mastering data visualisation, keep in mind that practice makes perfect! In addition, continuous learning will also help in refining and honing your visualisation skills. This is where Heicoders Academy comes into play. Kickstart your visualisation journey with our DA100: Data Analytics with SQL and Tableau course, where you will gain mastery in generating insights via data visualisations with Tableau. Happy visualising!