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A 5-Step Guide to Creating Meaningful Data Visualisations

by | Oct 1, 2023


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.

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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. 

Tableau: Your Data Visualisation Ally 

Enter your data visualisation ally – Tableau. Tableau is a powerful and empowering data visualisation tool that has gained traction for its ability to create interactive and fascinating visualisations. Imagine that – numbers being fascinating! 

You might be thinking, what makes Tableau so different from our trusty pie charts and bar graphs? Here’s why Tableau is a cut above its competitors:

  1. No-Code User-Friendly Interface: Tableau’s drag-and-drop interface makes it extra usable and beginner-friendly, even for users with little to no technical background. You’ll be able to create impactful visualisations even without any programming background.
  2. Real-Time Data Connection: As it has access to various data sources, including databases, spreadsheets, cloud platforms, and web services, this ensures that you are always working with the most updated information and numbers.
  3. Interactive Dashboards: Tableau allows users to build interactive dashboards where you can explore data on your own terms. That is, from filtering and highlighting desired data sets, to linking sheets, dashboards, or external web content together, Tableau allows users to decide what they want to do with their data. This enhances user experience, providing a more engaging experience
  4. Advanced Analytics: Beyond simple charts, Tableau supports advanced analytics, predictive modeling and complex statistical  functions, making it a versatile tool for professionals. Below are some examples of how your data can look like with Tableau:

  5. Scalability: Tableau serves to meet the needs of different users – whether you’re an individual analyst, or part of a larger organisation striving to present your data in a poignant manner, Tableau empowers you to achieve just that. 

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.

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    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.

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  • 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! 

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