Here's how you can enhance your communication with stakeholders using data visualization techniques.

Tailor your approach based on the knowledge level and expectations of your stakeholders. For Non technical stakeholders simplify complex data and use clear and intuitive visuals such as Bar charts, pie, line. For technical stakeholders, provide detailed data rich viz and complex dashboard with visuals such as heat maps, scatter plots, box plots, network diagrams and so on.

A key part of knowing your audience is understanding what their goals are. Different stakeholders will want to get different things from your presentation - you need to understand what their goals are and how your work helps them, and then you can grab their attention.

Enhance your communication with stakeholders using data visualization techniques by choosing appropriate visualizations (e.g., charts, graphs, dashboards) that convey key insights clearly, using color and design principles effectively to emphasize important information, providing context and annotations to aid interpretation, creating interactive visuals for exploration, and aligning visuals with stakeholder preferences and objectives to facilitate meaningful discussions and decision-making.

Understanding the knowledge level of your audience is crucial, if your audience are not well versed with data science ,be mindful to avoid jargons and use simple visualizations such as bar charts, pie plots. Also avoid overloaded charts, remember the intention is make the data easy to understand and not to showcase every piece of the data you collected. For tech savvy audience - incorporating complex visualizations such as heat maps or graph networks can be more appropriate.

Visualizations are powerful storytelling & communication tools; they can very quickly convey meaning for complex ideas. However, clear communication often has more to do with what is left out rather than what is included. You may be tempted to include every interesting chart and graph you produce, but you must be ruthless in cutting everything that is extraneous to your core narrative. Make sure that visualizations are not complex for the sake of impressing stakeholders. Make sure to remove any unnecessary datapoints or features. Make sure that every slide or visualization is focused on only a single point. Remember that no one knows the data better than you and you have to distill and simplify for your audience.

In addition to simplifying your data visuals, focus on storytelling to effectively convey your message. Structure your visualizations around a narrative that guides the viewer through the insights and conclusions drawn from the data. Start with a clear purpose or question that your data addresses, then present the key findings in a logical sequence. Use annotations, captions, or headlines to provide context and highlight the significance of each data point.

Speak Their Language: Data Viz for Stakeholder Engagement Data scientists, boost communication with stakeholders using data visualization! Audience Awareness: Tailor visuals to their level of data expertise. Chart Champions: Choose the right charts - bar charts for comparisons, line charts for trends, etc. Less is More: Simplify data, highlight key insights, avoid overwhelming viewers with information overload. Storytelling with Stats: Craft a clear narrative with your visualizations, guide them to key takeaways. Interactive Insights: Consider using interactive dashboards for deeper exploration and engagement. Refine for Resonance: Gather feedback, iterate on visualizations to ensure clarity and impact.

Reviewing is critical but I definitely question the location of this step in this answer. If you're a data scientist/expert who is visually presenting data insights to a supposed audience of non-experts, you should have been careful about following things to begin with. It is not something to review, but something to START from: 1. Selecting appropriate visualizations for the type of data being presented. 2. Selecting appropriate complexity of visualizations based on the audience you're presenting to. 3. Considering the appropriate charts, color schemes, scale, and axes BEFORE creating the visualizations. After creating these, the only review/refinement required should be to identify outliers or events or values to highlight meaningfully.