Secondary data is data collected by someone other than the user. Common sources of secondary data for social science include censuses, surveys, organizational records and data collected through qualitative methodologies or qualitative research. Primary data, by contrast, are collected by the investigator conducting the research.
Secondary data analysis saves time that would otherwise be spent collecting data and, particularly in the case of quantitative data, provides larger and higher-quality databases that would be unfeasible for any individual researcher to collect on their own. In addition, analysts of social and economic change consider secondary data essential, since it is impossible to conduct a new survey that can adequately capture past change and/or developments.
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As is the case in primary research, secondary data can be obtained from two different research strands:
A clear benefit of using secondary data is that much of the background work needed has been already been carried out, for example: literature reviews, case studies might have been carried out, published texts and statistic could have been already used elsewhere, media promotion and personal contacts have also been utilized.
This wealth of background work means that secondary data generally have a pre-established degree of validity and reliability which need not be re-examined by the researcher who is re-using such data.
Furthermore, secondary data can also be helpful in the research design of subsequent primary research and can provide a baseline with which the collected primary data results can be compared to. Therefore, it is always wise to begin any research activity with a review of the secondar
Qualitative data re-use provides a unique opportunity to study the raw materials of the recent or more distant past to gain insights for both methodological and theoretical purposes.
In the secondary analysis of qualitative data, good documentation can not be underestimated as it provides necessary background and much needed context both of which make re-use a more worthwhile and systematic endeavour [1]. Actually one could go as far as claim that qualitative secondary data analysis “can be understood, not so much as the analysis of pre-existing data; rather as involving a process of re-contextualising, and re-constructing, data”[2].