There are a wide range of tools available to refine and query your data, and to create, edit, and display your visualizations. The types of tools available for building visualizations fall into four major categories: basic productivity applications, visualization software, business intelligence tools, and developer based packages.
It’s critical to select the tools that work best for your workflow. When evaluating a new data visualization tool, consider the following:
- Sharing – Can others view and edit your visualization and analysis? The ability to share your charts and graphs with others enables collaboration for data visualization tasks.
- Output – Can you publish visualizations to the web, create PDF documents, and embed them into other applications? The ultimate destination of your visualization will dictate tool choice. For example, if your audience is interpreting your graphs online, you may want to design them to be interactive to allow for exploration.
- Interoperability – How easily can you connect to other data sources? For instance, does the software allow you to import diverse file types, such as .xls, CSV, .txt, or allow you to link to your databases?
- Display types – What types of visualizations do you intend on building? Maps, networks, and text based visualizations are not available for every tool.
- Data exploration – Do you need a tool to explore and present your data visually, or to present a data visualization? Features such as visual querying are not standard for every tool.
- Simplicity – Are you looking to create charts and graphs quickly? Some tools require a steep learning curve, even to build a simple bar chart.
- Persistence – Do you think that you will have to go back and revise the visualizations you create? It would be important to choose a technology that you think will be around for a while.
Dr. Kristen Sosulski develops innovative practices for higher education as the Director of Education for the NYU Stern W.R. Berkley Innovation Lab. She also teaches MBA students and executives data visualization, R programming, and operations management as an Associate Professor at NYU’s Stern School of Business.
Kristen’s passion for technology and learning sciences converges in all facets of her career, inside and outside of the classroom. Follower her on Twitter at @sosulski and learn more at http://kristensosulski.com. Stay connected and join her newsletter.