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How do you apply data visualization techniques to other fields?

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Data visualization is the art and science of transforming data into visual forms that communicate insights, patterns, and stories. It is a powerful tool for analytical skills, as it helps you explore, understand, and communicate data in meaningful ways. But data visualization is not only useful for data analysts, statisticians, or scientists. You can also apply data visualization techniques to other fields, such as education, marketing, journalism, or design. In this article, you will learn how to do that and why it matters.

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1 Benefits of data visualization

Data visualization can be used to achieve various goals in different fields, such as engaging your audience, explaining your findings, and discovering new insights. Visuals can capture attention, evoke emotions, and make complex concepts more accessible. They can also help you summarize data in a clear and concise way and reveal trends or correlations that might go unnoticed. Data visualization also enables you to explore, manipulate, and interact with data in a dynamic way. In education, it can enhance learning outcomes. In marketing, it can increase brand awareness and influence purchase decisions. In journalism, it can provide evidence for stories. In design, it can help you present research or prototypes to clients or stakeholders. In science, it can help you conduct experiments and validate results. In business, it can help you monitor performance and make informed decisions.

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Preeti Semwal

Head of Data Science @ Expedia | Kellogg MBA | IIT Kanpur
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In this age where content rules the roost and we're drowning in a sea of information, nailing visualization is like adding jet fuel to your insights. And what does good visualization mean? It's all about being sleek, crystal clear, and to the point. For me, it's been a journey from crafting intricately good looking visuals communicating too much to streamlining into simple, straightforward and powerful. It makes all the difference.

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Jeremy Gilby

Sr. Business Intelligence Analyst at Comcast
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Everything is a data conversation, the real question is what data is available for the conversation. Are you looking to visualize impact? your footprint? your influence? Or are you looking to visualize changes, a before and after to document what your organization did? A personal example: I made a visualization of my resume, using horizontal Gaant charts to show my position and duration in that position for each of the companies I worked for, overlaying with my years of education from the various schools. It reduced the need for start and stop times and instead showed the journey in color.

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Suresh Bairwa

Project & Data Analytics Leader | Technology & Healthcare | Team Leadership | Strategy | Business Intelligence
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Absolutely, couldn't agree more! The power of data visualization lies in its ability to cut through the noise and deliver impactful insights with clarity. It's not just about creating visually appealing graphics, it's about presenting complex information into simple yet potent visuals that resonate with the audience. The transition from detailed visuals to sleek and straightforward representations is a journey that highlights the essence of effective communication. It's fascinating how the right visualization can amplify the impact of data, making it an invaluable tool across diverse fields. And at the end, without visualization, data is just numbers, it's the visualization that breathes life into the data, giving it meaning and relevance.

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2 Data visualization process

In order to apply data visualization techniques to other fields, it is necessary to follow a systematic process that includes four steps. Firstly, you must define your goal and scope your project by asking yourself what the purpose of the data visualization is, who the audience is, what message you want to convey, and what action you want to inspire. Secondly, you must collect and prepare the data by determining where it will come from, how it will be cleaned and organized, and which metrics, variables, or attributes will be used. Thirdly, you must choose and create visuals that best fit your data and goal while taking into account design, layout, annotation, and the tools or software that will be used. Lastly, you must evaluate and refine your visuals to ensure they are communicating your message effectively and achieving your goal by considering feedback, testing, or iteration.

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3 Data visualization types

Data visualization can be used for various purposes, depending on the data and goal. Charts, for instance, are graphical representations of data that use symbols, such as bars, lines, or points, to illustrate quantities, proportions, or trends. Maps are graphical representations that use spatial dimensions to show patterns, distributions, or relationships. Diagrams also use shapes, icons, or text to depict concepts, processes, or structures. Lastly, dashboards are graphical representations that utilize multiple visuals to give a comprehensive overview of a topic, situation, or performance.

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4 Data visualization tools

When creating data visualizations, you have a variety of tools and software to choose from depending on your level of skill, budget, and preference. Excel is a popular spreadsheet program that offers basic data analysis and simple charting capabilities. Tableau is a powerful and versatile data visualization software that allows for advanced data analysis and interactive dashboards. Power BI is another data visualization software that provides complex data analysis and dynamic reports. Finally, Canva is a graphic design software that enables the creation of beautiful visuals, such as diagrams, infographics, or posters. Each of these options has its own strengths and weaknesses to consider.

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5 Data visualization tips

To apply data visualization techniques to other fields effectively, you need to follow some best practices and tips. Understand your data's characteristics, limitations, and implications, as well as the needs, expectations, and preferences of your audience. Additionally, you must be aware of your goal and what you want to achieve with your visualization. Additionally, choose the visual that best matches your data and goal while considering the type, format, and quantity of your data, and the purpose, context, and medium of your visualization. Lastly, design for clarity by using colors, shapes, labels, and legends appropriately while avoiding any clutter or distortion.

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Kris Oey

Experienced accountant/analyst who is passionate to learn more about process and control
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Color plays an important role in data visualization. We often forget to consider the color schematic to our graphs. Moreover, we have to be considerate to others; I like green but I often forget that there could be some people who are color blind and cannot distinguish this color.

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6 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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How do you apply data visualization techniques to other fields?

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1 Benefits of data visualization

2 Data visualization process

3 Data visualization types

4 Data visualization tools

5 Data visualization tips

6 Here’s what else to consider

Analytical Skills

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How do you apply data visualization techniques to other fields?

1

2

3

4

5

6

1 Benefits of data visualization

2 Data visualization process

3 Data visualization types

4 Data visualization tools

5 Data visualization tips

6 Here’s what else to consider

Analytical Skills

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