What are the best practices for ensuring your data visualizations are inclusive?

Influencing your visuals with cultural context, educational background always lead to being bias and always skew the results. This can lead to many people from different cultural backgrounds and educational backgrounds to feel lost and couldn’t understand the flow and the main purpose of the visuals. Your audience is the most important thing to consider while creating your visuals or creating story with your data and this must be easy to understand without a technical knowledge, background knowledge, cultural background, educational background, the visual should be able to speak a good language of the data.

Use cores com alto contraste e evite combinações que dificultem a visualização para pessoas com daltonismo, utilizando paletas de cores testadas para acessibilidade. Adicione descrições textuais e legendas claras para todos os elementos visuais, facilitando a compreensão para pessoas com deficiências visuais. Certifique-se de que os gráficos sejam legíveis em diferentes dispositivos e tamanhos de tela. Utilize fontes grandes e fáceis de ler e, quando possível, ofereça alternativas textuais para gráficos complexos. Ao seguir essas práticas, você torna suas visualizações mais acessíveis e compreensíveis para um público diversificado.

The choice of color is very important in visualization, there must not be much coloration, the colors must be minimal, simple and easily communicating the importance of the visualization and the story tend to tell using the visuals. The choice of the visuals can give your visualization more clarity or difficulties, it is very essential to choice a good visuals, the visuals must not be too colorful and be tailor to telling a good story.

Simplifying complexity is a beauty of a visualization and this leading to keeping your audience in mind, your audience is most important things to consider when analyzing and visualizing data, it must be easy for them to understand without the knowledge of technical aspects of data visualization or tools used for data visualization. The more simple and easy your visuals is the more your presentation and work look professional, simplifying complexity is a valuable skills a data analyst must have in visualizing and presentation of the results gotten from raw data

Adding a descriptive text to your visuals increases the chance of your audience understanding your visuals and the result without much effort and questioning. As a data analyst always try to make your visualizations eye appealing and tells a good story of your data without much effort. Addition of text give it more beauty and easily communicate the insights and the results of the analysis quickly. Adding text helps to give more insight on the analysis, visualization, recommendations and conclusions of the analysis.

Testing and iteration help a data analyst to achieve a good result and impactful decision. The analysis and visualization of the raw data must be tested and constantly iterated for adjustments where necessary and improvements on the performance for the audience to see the impact of the analysis without errors or skewed result.

É crucial considerar a acessibilidade tecnológica ao criar visualizações de dados. Nem todos têm acesso ao software mais recente ou internet de alta velocidade. Portanto, projete seus gráficos para carregar eficientemente em vários dispositivos e velocidades de conexão. Além disso, certifique-se de que elementos interativos sejam compatíveis com tecnologias assistivas, como leitores de tela e navegação pelo teclado. Dessa forma, suas visualizações serão mais inclusivas para todos, independentemente de suas capacidades tecnológicas.