How do you use data visualization with other teams?

This is an excellent reminder, put yourself in the position of your intended audience. When it comes to building out visualizations for stakeholders in my organization I look back on what they’ve found engaging in previous presentations or reports. This helps me engineer impactful presentations & reports to maximize their use case amongst their teams.

You will never create a dashboard that fits 100% of user user base unless they are a targeted user base. You need to have your dashboard fit the majority of your users so knowing your user base is key.

I agree whole heartedly. I always live by the motto “Right chart for the right data”. Line charts for trending, bar charts for comparison, and scatterplots for correlations. Pie charts are almost always better as bar charts.

Choosing the right format for data visualization is crucial for effective communication. Consider the data's nature, audience, and purpose. Bar charts for comparisons, line graphs for trends, and pie charts for proportions. Infographics are useful for summarizing complex data. Interactive dashboards enable exploration. The right format enhances understanding, facilitates decision-making, and fosters collaboration among teams.

Using design principles in data visualization elevates its impact and comprehension. Prioritize simplicity, clarity, and consistency. Balance aesthetics with functionality. Employ appropriate colors, fonts, and spacing to enhance readability. Align elements purposefully. Incorporate data storytelling to engage and evoke insights. Iterative feedback and user testing can refine the design. By following design principles, data visualization becomes a powerful tool that informs, persuades, and inspires better decisions and collaboration across teams.

Using best practices is crucial for the data storytelling. Using those practices will allow your audience to interpret and take action on the data quickly if there is quick comprehension of the insights the dashboard provides.

Adding context and narrative to data visualization enriches its meaning and relevance. Contextualize data by providing background information, explaining methodologies, and defining metrics. Craft a compelling narrative that guides viewers through the insights and implications of the data. This helps users grasp the significance of the visualizations and empowers them to draw informed conclusions. Utilize annotations and captions to highlight key findings. Remember, data alone may not resonate; it's the story woven around the data that captivates collaboration with other teams.

Testing and refining data visualizations are crucial steps in ensuring their effectiveness. Conduct usability tests with representative users to gather feedback and identify areas for improvement. Analyze how well the visualizations communicate the intended message and whether they align with the audience's needs. Refine the visuals based on the insights gained from testing. Iteratively optimize the design, layout, and interactivity to enhance user comprehension and engagement. Data visualization is an ongoing process; continual refinement ensures that the visuals remain relevant and impactful.

Engage with team members, stakeholders, and decision-makers to solicit their feedback and insights. Encourage open discussions and brainstorming sessions to explore new perspectives and potential use cases. Share the visuals through accessible platforms and mediums, such as interactive dashboards or presentation slides, to enable easy access and understanding for the intended audience. Collaborate with cross-functional teams to integrate data visualizations into their workflows and decision-making processes. Emphasize the importance of data literacy and provide training to empower others in interpreting and utilizing the visualizations effectively.

I absolutely agree with the discussion. From experience, it is so important to remember that it's an iterative design process. So the last two stages are key: share, listen and enhance. So very much inline with Shaurya's comment. I imagine many folks are like me, where we've started overly complex data visualisation, which isn't addressing the questions the audience has. So, simplify. I like to work with a few key stakeholders in the story forming, mocking up phase.