Finding the Story in Your Data

Trends, Correlations and Outliers

Data visualisation is very much a mathematical endeavour as it is a design one. It is important to analyse the data you have collected in order to find anything interesting which a data visualisation would serve the purpose of explaining this in a visual and easy to understand way.

Know Your Data

Quantitative

Data that can be counted or measured; all values are numerical.

Discrete

Numerical data that has a nite number of possible values. Example: Number of employees in the office.

Continuous

Data that is measured and has a value within a range. Example: Rain fall within a year.

Categorical

Data that can be sorted according to group or category. Example: Types of products sold.

Types of Data Visualisation

10 Data Design Do’s and Don’ts

1. Do use one colour to represent each category
2. Do order data sets using logical hierarchy
3. Do use call outs to highlight interesting information