Visualising data from multiple sources helping organisations make sense of the forces driving change in their world

Data Visualisation

What We Do

Data is the best way to explain your organisation’s story or cause through analytical data . Often just throwing numbers at people doesn’t mean a lot, but by showing a relationship alongside other data examples it gives a clear picture, when represented in an appealing way.

Data visualisation is a specialisim that deals with the graphical representation of data. It is a particularly efficient way of communicating when the data is numerous as for example, for showing changes of behaviour over a period of time. From an academic point of view, this representation can be considered as a mapping between the original data (usually numerical) and graphic elements (for example, lines or points in a chart). The mapping determines how the attributes of these elements vary according to the data. In this light, a bar chart is a mapping of the length of a bar to a magnitude of a variable. Since the graphic design of the mapping can adversely affect the readability of a chart, mapping is a core competency of Data visualisation.

By taking data from multiple sources by using something such as GraphQL we are able to display information that tells a better story and take advantage of multiple bodies of research, as well as your own information.

Often, the data needed to be shown in a line chart or scatterplot can be hard to interpret with lots of datapoints taking up limited space. Instead of putting everything on the screen at once, we can focus your audience’s attention and animate them when in view or when interacted with.

Showing each piece of data is not the only way to animate your data. We can create visualisations in which the elements smoothly transition from one position to another.

Creating animations with data can engage readers and viewers in ways other visualisation types may not be able to. Animations can help people see transitions from one state to the next and enable them to more easily track changes as parts of your datasets move from one point to another.