The two words "data" and "information" are often thought to be interchangeable. For many people who do not work directly with one or other of these, the difference between the two can seem academic and not particularly important. However, there is a fundamental difference between data and information which becomes apparent when looking at the definitions and applications of the two words.

Data is information in its raw state. Most commonly, data is perceived to be statistical, yet it can equally be in a text format instead of numerical. Data is the result of a collection process. It does not matter how the data is collected, the processes will vary depending on the type of data required. But at the end of the collection period, there will be a large amount of data that requires analysis and presentation.

Data is now most commonly entered and stored in a database. Notice how we rarely say "information-base". Data entry is often seen as a low-skilled and mundane job, yet without data entry, it would be extremely difficult to extract any meaningful information from the raw data. It is the process of data entry into a particular database that facilitates accurate analysis.

Once the data has been stored, classified and analysed, the results are presented in the form of information. The key difference between data and information is the display and dissemination. Information must be relevant, must support or dispute the original proposition, and must be delivered in a meaningful way. Information is derived from data.

While data is presented for analysis often in complex documents, spreadsheets or statistical charts, the information gathered must be interpreted to suit the intended audience. The same data can be interpreted as information in a wide range of different ways. The analysis of the raw data provides the basis for relevant and specific information which is then presented in an engaging and understandable format.

If a government wanted the adult population of a country to all have a particular vaccine to prevent an illness, they would first need to gather data on the effectiveness of the vaccine. The government would then have to consider the public reaction to previous mass vaccination programmes, possibly by analysing previous data on the take-up rates of the vaccinations, and use all of the data to formulate an information campaign that would encourage the public to accept the new vaccine. The public would not need to know all of the data, but they would need to know the relevant parts in an easy to understand format.

Data and information are intrinsically linked, yet are very different links in the knowledge chain.

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