Selecting the appropriate data visualization tool can be challenging, given the many available options. You will want to consider:
A program such as Microsoft Excel, while fundamentally a spreadsheet product, offers at least 20 different types of graphs, charts, plots, and other visual representations. Other spreadsheet programs are also likely to provide ways of creating visual representations of spreadsheet data.
Widely used by the business and research communities, Tableau allows users to connect, visualize, and share data powerfully and interactively, providing a wide range of tools and features for creating dynamic, interactive dashboards, charts, maps, and other visualizations. Tableau Public is free (with certain limitations) while Tableau Creator can be purchased from DoIT.
As a member of the University, you have access to Power BI through Office 365. You can connect to various data sources, analyze data, and create interactive visualizations and reports.
Datawrapper is an online data visualization platform. It allows users to create data visualization by simply copying and pasting data into the site. After analyzing the data, it will help you pick the visualizations.
Looker Studio (formerly Google Data Studio) is an online platform allowing connection to a wide variety of data, creation of visualizations and dashboards, and sharing reports and dashboards with individuals, teams, or the world.
While data visualization products continue to become more sophisticated and capable, you may still find instances where your project requires capabilities or a combination of capabilities not offered by these products. In such cases, the following languages have significant visualization capabilities along with ability to create, gather, and clean data in one program.
The R language is commonly used for statistical analysis and also offers significant methods for creating data visualizations. The primary visualization library package used by R is Ggplot2 but many other packages build off its functionality.
Python is a general-purpose programming language that, among other abilities, can make use of programming libraries for data visualization. The most commonly used data visualization library is matplotlib but others, such as seaborn, plotly, and geoplotlib are also available.