Working with data

Aims and objectives

This module will:

  • explain what data is
  • examine how data is used
  • explore ways to analyse data.

After completing this module, you will be able to:

  • find, clean and use data
  • evaluate and select tools to analyse and display data.

1. What is data?

Data is raw information or numeric files.

Data can take a variety of forms, including numbers, text or people’s opinions. Data can be manipulated, analysed and interpreted to give it meaning. Once data has meaning, it becomes information. Data can be collected from measurement, observation, experience or experiment.

Note: Data is the plural of datum. However, data is commonly used as a singular collective noun. You will see both "These data are ..." or "This data is ..." in scholarly information. Check with your lecturer or school for the form you are expected to use.

Data becomes information

If you observed ducklings around UQ Lakes, what kind of data could you collect?

  • The number of ducklings
  • Their size
  • Where they go
  • What they eat 

If you continued to observe the ducklings over time you could gather more data. If you organise and analyse the data you gather, it could reveal information about patterns of behaviour and identify potential impacts. e.g. growth or decline in the number of ducks around the lakes.

2 ducks with many ducklings
Source: UQ Ducks by Flic French, CC BY 2.0

Primary data is data you have collected yourself.

Secondary data is data collected by others, including public datasets.

Types of data

Data can be described in many different ways. One way to describe data is to use the terms qualitative and quantitative.

Qualitative  — data that records qualities e.g. descriptions, concepts and opinions. Qualitative research is often focused on how and why something occurs.

Quantitative  — numerical or spatial data that records quantities, measurements or frequencies e.g. size, location or scores.

Qualitative data can be analysed through quantitative approaches, such as statistical analysis, by giving the data a numerical value or ranking. Qualitative data is generally harder to analyse than quantitative, as it is usually in a format that is difficult to analyse quickly with basic statistical techniques.


Metadata is data that describes other data. It is useful for finding, sharing and evaluating datasets. The metadata may be automatically generated and contained within the data file, such as with images, or it may be manually created and exist external to the file. The Working with files module gives more information about the purpose of metadata.


Datasets are collections of data. Datasets can be in a wide variety of formats, including:

  • Spreadsheets
  • Text
  • Transcripts from interviews and focus groups
  • Videos
  • Images
  • Code.

The Working with files module provides information on the different file formats that you may encounter and the software needed to open the files.


Statistics are not the same as data. Statistics are:

  • data that has already been processed and analysed
  • an interpretation or summary of data
  • used to make comparisons
  • often presented in tables, charts, graphs or percentages.

Get more information on statistics:

Duration:   Approximately 30 minutes

Graduate attributes

Knowledge and skills you can gain to contribute to your Graduate attributes:

 Independence and creativity

 Critical judgement

 Ethical and social understanding

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