Data visualisation is the presentation of numerical data pictorially or graphically so that users can more easily make sense of complex data to identify patterns and trends. Usually, data visualisations allows input of new sets of data (or circumstances) so that the solution can model the effects of that changed data. When working with large amounts of data, tools are needed (for example, a spreadsheet or programming language such as Python) to manage the volume of information and get the most value from it. Databases enable data to be stored so it can be efficiently and reliably retrieved using relevant queries. When students are asked to respond to meaningful questions that they want to answer, they will be engaged when applying their understandings and developing their skills of data analysis and visualisation.
Flow of Activities
Students consider meaningful questions that they want to answer. They use these questions to apply their understandings about, and develop their skills of, data analysis and data visualisation.
When acquiring data, students consider whether the data set is representative of the entire audience. Some data sets may be biased as they are from a sample that does not fully represent all views.
Data acquired from a range of resources may include both quantitative and qualitative data. To effectively use qualitative data, techniques may need to be applied.
To undertake useful data analysis, students need to start with quality data. There are plenty of things that can go wrong with data; for example, data may be inappropriately structured or organised, may have formatting issues such as empty cells or apostrophes, may have spelling errors or may be numeric data imported in an incorrect format such as date or currency.
In acquiring data from a database, students should develop an understanding that data is stored in a way that allows it to be efficiently and reliably retrieved, and this is different to how it is presented.
When working with large amounts of data, tools enable the user to manage the bulk of information to get the most value from it.
Spreadsheets enable you to sort and filter data insert subtotals into sorted lists, use simple formula and visualise data.
More complex data sets may require the use of pivot tables to make it easier to analyse all of the information in your worksheet. Pivot tables help make your worksheets more manageable by summarising your data and allowing you to manipulate it in different ways.
When using large data sets, it is possible to use a programming language such as Python to read and write the data enabling analysis. To do this, data should be in CSV format, which is like Excel standard spreadsheet format, presented in plain text.
Data can be encoded and represented visually as channels of information. These visual channels include spatial position, colour, size, shape, orientation and direction of motion. Multiple visual channels can be used to simultaneously represent data.
Heat maps are a way of visualising numerical data represented as colour. Interactive data visualisations help further to model processes and examine relationships.
Both the appearance and functionality of information contribute to its quality. Appearance relates to the aesthetics of information and it usually draws on design principles, such as alignment, repetition, contrast, space and balance. Alignment connects elements visually through an invisible line. Contrast shows differences between elements. Repetition involves re-using the same or similar elements for consistency. Space relates to the distance between elements. Balance relates to the weighting given to different elements.
Functionality also contributes to the effectiveness of information. Characteristics of functionality include the useability of a solution such as its flexibility and ease of use, and accessibility such as its ease of navigation.
The quality of information is also enhanced if conventions (or normally accepted procedures) are applied such as a chart having a legend, heading and labelled axes. Similarly, the use of colour should promote contrast but also consider users who are colour blind.