Visualization of data and information can take many forms. Data in the form of text and numbers often don’t convey the obvious conclusions that may be reached from the data. Visual representations of data however may make data far more simple to understand and, particularly with large and complex data-sets, quicker from which to draw conclusions. Data are usually represented as graphs when a visual representation is required.
Data analysis, and the subsequent conclusions reached, may have wide ranging implications; take for example data about education, training and skills attainment in a country or region. This data are often used for government policy relating to future education and skills needs. The conclusions reached from the data-set therefore have far reaching implications and it is hence of importance that the data are understood by the various stakeholders. To make the data more meaningful for the audience graphs and other images may be very beneficial.
In order to demonstrate a few different means of displaying the same data, I have created the images as below from a data-set; The data are from the Australian National Centre for Vocational Education Research (NCVER) and represents ‘Students by major courses and qualifications, New South Wales, 2008’ (all data values are in thousands and related to Vocational Education and Training). All images have been created using the same data-set from NCVER:
|AQF qualifications||Total (‘000)|
|Diploma or higher||43.4|
Bubble Chart 1:
Bubble Chart 2: