4.1 Primary vs. secondary data
A secondary data source refers to a data source that is already in existence and is being used either for a purpose for which it was not originally intended or by someone other than the researcher who collected the original data (Salkind, 2010).
Secondary data can be raw data or published summaries and you can tailor the data according to your research needs. Examples include large databases of surveys, censuses, and social and economic data that are too expensive or unfeasible for an individual to collect.
Other types of secondary data include organisational records and surveys (e.g. employee surveys), market research data, or transcripts of interviews or focus groups. Whether you are collecting data for your own project or compiling a portfolio of evidence, secondary data serves as a time-efficient and easy to obtain source of information.
Primary data, on the other hand, is information collected by a researcher to address a specific issue or problem. As it has not yet been gathered or it may not be accessible, it is data that is unique, first-hand and from an original data source. The data is collected by a researcher using a variety of techniques, such as interviews, focus groups, surveys and observations.
Let’s say, for example, a food manufacturing company was losing market share and wanted to gain a better understanding of customers’ perceptions of their snack products in the light of a cultural shift towards healthier foods. The researchers would have the advantage of conducting interviews with customers using tailored questions, designed specifically to elicit the required information to help them address the business issue. However, this method of data collection may be considered quite costly and time consuming compared to using information that is already in the public domain.
Even if you are planning on collecting primary data, it is a good practice to start your research by looking at information that is already available. This may help you to identify potential areas of interest for your topic that have been under-explored, and therefore strengthen the rationale for your topic selection. Conversely, you may find that there is a shortage of available secondary data for your chosen topic, thereby strengthening your rationale for collecting primary data.
It is worth noting at this point that secondary data can be both qualitative and quantitative in nature. Qualitative data is data in the form of descriptive accounts of observation or data which is classified in a way, whereas quantitative data is data that can be expressed numerically or classified by some numerical value (Ghosh and Chopra, 2010).