I love this question because I don't think it's talked about or considered enough. Visualisations should always be accessible to anyone who may come across them - full stop. You can run a screenshot of your final visualisation through various websites to ensure that colours, text and layout are all up to scratch. You can also provide alt text to your visuals that are stagnant. I would recommend always using the same colours to represent the same things across a dashboard, as well as using logical colour choices (ie count of bananas should be yellow, not purple). Lastly, I use the rule of thumb where if someone can't understand the main takeaway of your chart within 3 seconds, it's too complex. Simple visuals > complex visuals.

To ensure accessibility for all users in data visualization, below are some of the important points which I could thought of: 1. Charts should be easily interpretable. 2. The consistency of colour should remain consistent throughout the dashboard. 3. Use of tooltips and labels should be highly encouraged 4.Colours should be easily distinguishable for colour blind audiences. 5.Legends should be mentioned wherever neccessary 6. The text / font should be simple and readable 7. Provide easy interactivity (Filters/slicers) with the dashboard Using above steps one can make a dashboard easy to adopt by even a less technical person

5 Tips for Inclusive Data Visualization Creating accessible visualizations ensures everyone can benefit from your insights. Here’s how to make yours more inclusive: 1. High Contrast Colors: Use contrasting colors to help users with color blindness distinguish elements. 2. Text Alternatives: Add alt-text and descriptive captions for screen readers. 3. Simplify Design: Avoid clutter—simpler designs are easier for all users to interpret. 4. Use Patterns and Labels: Don’t rely on color alone; add patterns, textures, and direct labels to clarify information. 5. Interactive Features: Add tooltips and adjustable settings for contrast and text size to let users customize their experience.

This is the one question that every data analyst needs to consider before they working on a dashboard. Use Clear Colors and Labels: Choose high-contrast colors and avoid color combinations that are hard for colorblind users, like red-green. Add labels and tooltips to explain data points clearly, so users don't rely on color alone to understand the visuals. Add Descriptions(Toolips) for Screen Readers: Include brief descriptions of your charts and main insights as text, so users with screen readers can follow along without seeing the visuals directly. Keep Visuals Simple: Avoid cluttered charts by focusing on one key insight per visualization. Too many details can make it harder for everyone to understand the data quickly and easily.

I found these three areas are how I tend to approach it: 1) Is your visualization good CRAP by itself and when combined? The Graphic Design principle CRAP (Contrast, Repetition, Alignment, Proximity) can be helpful to find design deficits that cause visual challenges. 2) Can you AB test with your target audience? Know your primary audience personas and design options for them. Then, test the options with your primary audience (real people), assessing on accessibility and usability constructs. Repeat with a larger audience. 3) What is the focal message? Not all data visualizations need to have a message. When it does, look for cognitive flow in which the pattern or message is not seen as intended, like different starting points.