You want to improve your data visualization skills. How can you use feedback to achieve this?

Feedback helps you understand what you're doing well and where you can improve. It provides valuable insights from others' perspectives, helping you see blind spots you might have missed. Example: If you create a bar chart to represent sales data but your colleagues find it confusing, their feedback can help you refine the visualization to make it clearer and more effective.

As data visualisation designers, our ultimate aim in most business scenarios is to create something useful for our audience. How can we judge whether we have succeeded without asking their opinion? As an experienced designer, I cannot think of a single project I have delivered which has not been improved by considering and acting on feedback.

The most fundamental and essential step is to seek feedback if it's not provided. The process of designing visualizations should include ongoing, open communication, allowing stakeholders to identify what is effective, what needs improvement, and what is lacking in the data analysts' presentations.

Gather feedback from a variety of sources, including colleagues, mentors, supervisors, and even users or stakeholders who interact with your visualizations. Each perspective can provide valuable insights into different aspects of your work.Approach feedback with an open mind and a willingness to learn. Even if it's critical, constructive feedback can help you identify areas for improvement and grow as a data visualization practitioner.

Feedbacks can definitely be great help in improving your learnings. 1. I will get in touch with people who has expertise on the tools and will understand their perspective on the design. 2. Giving more insightful outcome is what I need to focus on. Hence, I will focus on data analysis and identifying KPI so that i can draw efficient, Interactive and insightful dashboards. 3. I will proactively participate in more collaborations sessions and this too to validate my way of thinking. 4. When you know your weaknesses and you continuously work to improve it, you get it all. I believe practice is the Key to achieve the best

As a data visualisation designer, some of the most valuable feedback I receive is from watching clients interact with my dashboards. It can even be non-verbal, for instance they may struggle to understand how to filter a graph or navigate to a different view. This sort of feedback is valuable as it helps to improve useability, rather than focusing on more subjective opinions around aesthetics.

Be open and receptive to feedback from peers, mentors, or users who interact with your visualizations. Ask specific questions about what aspects of your visualization worked well and what could be improved. Example: After presenting a data dashboard in a team meeting, ask your colleagues for their thoughts on the layout, color choices, and clarity of the information presented.

There are a few ways to seek feedback from leaders. One way is to ask them directly for their feedback on your data visualizations and insights. You can also ask them questions about how they use data visualizations and what they find most helpful and insightful. For example: "I'm interested in getting your feedback on the data visualizations I created for the recent project. Did you find them helpful in understanding the data?"

Actively seeking feedback is essential. Start by identifying colleagues, mentors, or industry peers whose opinions you value and who have a good understanding of data visualization principles. Participate in forums or communities dedicated to data science and visualization, and don’t hesitate to present your work at meetings or conferences. Be specific about the kind of feedback you’re looking for—be it on the clarity, accuracy, aesthetics, or the storytelling aspect of your visualizations.

Analyze the feedback you receive and look for common themes or patterns. Use constructive criticism to identify areas for improvement and adjust your visualization accordingly. Example: If multiple people suggest that your line chart would be easier to understand with clearer labels on the axes, update the visualization to incorporate their suggestions.

Receiving feedback is just the first step; using it effectively is where the real improvement happens. Organize the feedback into actionable insights—what aspects are working well and what needs refinement. Prioritize the feedback based on its potential impact on your work’s clarity and effectiveness. Implement changes iteratively, focusing on one or two aspects at a time, and measure how these adjustments influence the audience’s understanding and engagement.

Remember, not all feedback is equal. It can be subjective, implicit and even contradictory! As a data visualisation designer, part of your role is to assess feedback without ego and apply it only where it serves the overall purpose of your visualisaton.

El feedback es importante para saber que de lo realizado esta óptimo, que se puede mejorar y que se debe cambiar. Es de las tareas más complejas ya que involucran habilidades blandas como la empatía y el respeto. El mensaje debe ser claro, asertivo y educado.

When giving feedback to others, be specific, constructive, and respectful. Focus on providing actionable suggestions for improvement rather than simply pointing out flaws. Example: Instead of saying, "Your pie chart is confusing," you could say, "I think adding data labels to the slices of the pie chart would make it easier to interpret."

Giving constructive feedback to others can also enhance your own skills. It encourages a deeper engagement with data visualization principles and practices. When providing feedback, be specific, objective, and constructive. Focus on both strengths and areas for improvement. Offer concrete suggestions rather than vague critiques, and always frame your feedback in a way that encourages growth and learning.

When giving feedback on a data visualisation, it is important to ask the creator what the overall purpose of their work is. So if a visualisation is designed to catch the eye, ask yourself whether it meets this goal and not whether the information can be communicated in a more straightforward way (and vice versa).

Embrace feedback as an opportunity for growth and learning. Implement changes based on feedback and observe how they impact the effectiveness of your visualizations. Example: After making adjustments to your scatter plot based on feedback received, compare how users interact with the updated version compared to the original to gauge the effectiveness of the changes.

How do you interpret the feedback and what is your plan to do with it? Understand the importance of feedback in your learning journey. Feedback is one valuable tool for improving your data dashboards, only when you are open to feedback and willing to make changes. You can create dashboards that are more effective and impactful. When you explore what did they find confusing or unclear, you find the underlying information that can help you identify areas where your dashboard can be improved.

Seek feedback from a diverse group of people to gain a range of perspectives. Don't be discouraged by negative feedback; use it as motivation to improve. Continuously seek opportunities to practice and refine your data visualization skills, incorporating feedback along the way.