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What are the best practices for using data visualization to identify opportunities and risks?

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Data visualization is the process of transforming data into graphical or interactive formats, such as charts, maps, dashboards, or infographics. Data visualization can help you communicate complex information, uncover patterns and trends, and support decision-making. However, not all data visualizations are equally effective or appropriate for different purposes and audiences. In this article, you will learn some of the best practices for using data visualization to identify opportunities and risks in your business reporting.

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Ts. Izuddin Abdullah

Head of IT at TNB Integrated Learning Solution Sdn Bhd

1 Choose the right type of visualization

One of the first steps in creating a data visualization is to choose the type of visualization that best suits your data and your message. Different types of visualizations have different strengths and limitations, and can convey different meanings and impressions. For example, a pie chart can show the proportions of a whole, but it can be hard to compare the sizes of different slices. A bar chart can show the differences between categories, but it can be misleading if the scale is not consistent. A line chart can show the changes over time, but it can be confusing if there are too many lines or if the axes are not labeled. A map can show the spatial distribution of data, but it can be distorted by the projection or the color scheme. A dashboard can show multiple indicators at a glance, but it can be overwhelming if it is not well organized or interactive. A infographic can tell a story with data, but it can be biased or inaccurate if it is not based on reliable sources or if it omits important context. Therefore, you should always consider the type of data you have, the question you want to answer, the message you want to convey, and the audience you want to reach when choosing a type of visualization.

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Ts. Izuddin Abdullah

Head of IT at TNB Integrated Learning Solution Sdn Bhd
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Choosing the right visualization is not always about attractive charts. A plain line chart is sufficient to show trends over time, as long as it serves its purpose.

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2 Follow the design principles

When creating a data visualization, it's important to adhere to design principles that promote clarity, accuracy, and aesthetics. Such principles include using colors, shapes, and sizes that are consistent, meaningful, and contrast well with the background. Labels, titles, legends, and annotations should be clear, concise, and informative. Axes, scales, and grids should be appropriate and aligned. Finally, white space, alignment, and hierarchy should be balanced for a harmonious look. By following these design principles, you can ensure your data visualization is effective and easy to interpret.

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3 Test and refine your visualization

The final step in creating a data visualization is to test and refine your visualization based on feedback, evaluation, and iteration. You should always test your visualization with your intended audience and ask for their opinions, questions, and suggestions. You should also evaluate your visualization based on the criteria of effectiveness, efficiency, and satisfaction. Effectiveness means how well your visualization achieves its purpose and communicates its message. Efficiency means how easily your visualization can be understood and used. Satisfaction means how appealing and engaging your visualization is to your audience. You should also iterate your visualization based on the results of your testing and evaluation, and make any necessary changes or improvements.

By following these best practices, you can create data visualizations that can help you identify opportunities and risks in your business reporting. Data visualization can help you discover new insights, communicate your findings, and support your decisions. However, data visualization is not a magic tool that can solve all your problems. You still need to have a clear goal, a relevant question, a reliable data source, and a critical thinking skill when using data visualization.

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4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the best practices for using data visualization to identify opportunities and risks?

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1 Choose the right type of visualization

2 Follow the design principles

3 Test and refine your visualization

4 Here’s what else to consider

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