What are the best data visualizations to showcase your portfolio? (2024)

Before you start creating any data visualization, you need to have a clear idea of what you want to achieve with it. What is the main message or question that you want to convey or answer? Who is your target audience and what are their expectations and needs? How will your data visualization fit into your portfolio and support your overall story? Knowing your purpose will help you choose the right type of data visualization, the appropriate data sources, and the most effective design elements.

There are many types of data visualizations, each with its own advantages and disadvantages. Some of the most common ones are charts, graphs, maps, tables, dashboards, and infographics. Depending on your purpose, you may want to use one or more of these types in your portfolio. For example, if you want to show trends, patterns, or relationships in your data, you may use charts or graphs. If you want to show geographic or spatial data, you may use maps. If you want to present a summary or comparison of key metrics, you may use tables or dashboards. If you want to tell a story or explain a complex concept, you may use infographics.

One of the biggest challenges of data visualization is to balance clarity and simplicity with accuracy and complexity. You want to make your data visualization easy to understand and interpret, but also faithful and relevant to your data. To achieve this balance, you need to follow some basic principles of data visualization design. For example, you need to choose the right colors, fonts, shapes, and sizes for your data elements. You need to avoid clutter, noise, and distortion in your data visualization. You need to provide labels, legends, titles, and captions for your data visualization. You need to use appropriate scales, axes, and formats for your data values.

While clarity and simplicity are essential for data visualization, they are not enough to make your portfolio stand out. You also need to add some creativity and personality to your data visualization, to make it more engaging and memorable for your audience. You can do this by using different styles, themes, animations, interactivity, or storytelling techniques in your data visualization. For example, you can use a custom or unconventional style that matches your personal brand or project theme. You can use animation or interactivity to draw attention or invite exploration in your data visualization. You can use storytelling techniques to create a narrative or a context for your data visualization.

Finally, you need to make sure that your data visualizations showcase your skills and achievements as a data scientist. You need to demonstrate that you can handle different types of data, use different tools and techniques, and solve different problems or challenges. You need to highlight the value and impact of your data insights, and how they can benefit your audience or stakeholders. You need to provide evidence and documentation for your data sources, methods, and results. You need to include a brief introduction and a call to action for each data visualization in your portfolio, to explain your goals, process, and outcomes.

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?

Data Science

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