Data analysis describes a method by which data is collected, organised and evaluated, with the goal of discovering useful information or interesting trends. Data is gathered, reviewed and analysed in order to describe a reality or to identify trends in a community. In journalism, very often the results of data analysis are transformed to visuals in order to enhance the interest of the public. One interesting example is Bloomberg’s 2015 analysis of the most dangerous jobs in America.
Data analysis consists of several steps: defining objectives, data collection, data cleaning, data analysis and drawing conclusions. After the set-up of the research objective, raw data can be collected from different sources such as: interviews, observations and documents (qualitative) as well as records or [LINK inside the glossary] databases (quantitative). Before starting the data analysis, the data needs to be sorted and cleaned.
In order to analyse data several open source and paid for software tools have been developed. Examples of open source data analysis programmes are: R Programming and Splunk. Paid data analysis programme are: Tableau Public, SAS, Microsoft Excel, and Rapid Miner.
