Data visualisation is the process of representing data graphically in order to identify trends and patterns that would otherwise be unclear or difficult to discern. Data visualisation serves two purposes: to bring clarity during analysis and to communicate.
The choice of what type of graph or visualisation to use depends greatly on the nature of the variables you have, such as relational, comparative, time-based, etc..
That said, sometimes graphing data with an inappropriate visualisation can lead to insights during analysis that would have remained hidden. Experimentation with visualisations during analysis is okay, but when communicating a visualisation, use the graph types listed under the proper options below. Incorrect visualisation leads to confusion, errors, and abandonment among viewers.
The options listed here can support both purposes of analysis and communication. You may want to graph data during analysis to see, for example, spikes in website traffic related to your social media campaigns. Visualisation, in this instance, eases data analysis. When communicating that data, however, the visualisation may need to be simplified and key areas may need emphasis in order to call the attention of readers and stakeholders. See the discussion under Report and Support Use for more information about how you may want to repackage a data visualisation for communication purposes.