How do you pick the best data viz tool?

1 Your goals and audience

The first thing to think about is what you want to achieve with your data viz and who you want to reach. Are you creating a dashboard for internal use, a report for a client, or a presentation for a wider audience? What are the main messages or questions you want to convey or answer? How familiar are your viewers with your data and your domain? These questions will help you narrow down your choices based on the functionality, interactivity, and accessibility of the data viz tools.

2 Your data and format

The next factor to consider is the type, size, and source of your data. Do you have structured or unstructured data, numerical or categorical data, time series or spatial data? How much data do you have and how often does it change? Where does your data come from and how do you access it? These questions will help you determine the compatibility, scalability, and flexibility of the data viz tools. You also need to think about the format and style of your data viz. Do you want to use charts, maps, tables, or something more creative? Do you want to follow a specific design guideline or customize your own?

4 How to compare and test data viz tools

Once you have a clear idea of your criteria and preferences, you can start browsing and comparing different data viz tools. You can use online reviews, ratings, and recommendations from experts and peers to get an overview of the pros and cons of each tool. You can also look at examples of data viz created with each tool to get a sense of their capabilities and limitations. But the best way to find out if a data viz tool suits your needs is to try it yourself. You can use free trials, demos, or tutorials to test the features, functions, and user interface of each tool. You can also experiment with different types of data and formats to see how well they work.

6 How to share your data viz

The final step in your data viz journey is to share your work with your intended audience. Depending on your purpose and platform, you may need to export, embed, or publish your data viz in different formats and settings. You also need to ensure that your data viz is accessible, responsive, and interactive for your viewers. You may want to add annotations, explanations, or narratives to enhance your data viz and make it more engaging and informative. And of course, you should always acknowledge your data sources, references, and tools.