How can you keep a data visualization project on track?

1 Define your goals and audience

Before you start designing your data visualization, you need to have a clear understanding of what you want to achieve and who you want to reach. What is the main message or question you want to answer with your data? Who are your intended viewers and what are their needs, interests, and expectations? How will they access and interact with your data visualization? These questions will help you define your goals and audience, which will guide your choices of data sources, formats, tools, and styles.

2 Plan your process and scope

Once you have defined your goals and audience, you need to plan your process and scope. This means breaking down your data visualization project into manageable steps, such as data collection, cleaning, analysis, design, testing, and deployment. You also need to estimate the time, resources, and budget required for each step, and set realistic deadlines and milestones. Additionally, you need to communicate your plan and scope clearly to your stakeholders, and agree on the roles, responsibilities, and expectations of each party.

4 Design with principles and feedback

When you are ready to design your data visualization, you need to follow some basic principles and best practices to ensure that your data visualization is clear, accurate, and engaging. Some of these principles include choosing the right colors, fonts, shapes, and layouts, avoiding clutter and distortion, highlighting the most important information, and adding context and annotations. You also need to seek feedback from your stakeholders and users throughout the design process, and test your data visualization for usability, functionality, and accessibility. You need to be open to suggestions and criticism, and make adjustments as needed.

5 Document and share your work

The final step of keeping your data visualization project on track is documenting and sharing your work. You need to document your data sources, methods, assumptions, and limitations, as well as your design choices and rationale. This will help you explain and justify your data visualization to your stakeholders and users, as well as demonstrate your credibility and transparency. You also need to share your data visualization in a suitable format and platform, such as a report, presentation, website, or social media. You need to consider the best way to distribute and promote your data visualization, and measure its impact and effectiveness.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?