Secondary research (SR) is a type of investigation that utilizes systematic inquiry in which a researcher relies exclusively on existing data. SR design entails compiling, collating, and dissecting the gathered data samples rigorously. A typical example of quantitative SR design is the meta-analysis research, which uses statistical methods to combine the findings of multiple empirical publications to increase the analytical power due to the aggregated effect of sample sizes from the previous relevant studies.
Relying on others’ work, it can be challenging to find the exact information the researcher needs for their investigation, particularly if the variables of interest are out of data. Another challenge can be assessing the data sources’ validity and reliability, which might be demanding, i.e., consuming a lot of time and effort. The following references could render further helpful inputs.
Flemming, K. (2010). Synthesis of quantitative and qualitative research: An example using Critical Interpretive Synthesis. Journal of Advanced Nursing, 66(1), 201–217. https://doi.org/10.1111/j.1365-2648.2009.05173.x
Manu, E., & Akotia, J. (Eds.). (2021). Secondary research methods in the built environment. Routledge. https://www.taylorfrancis.com/books/edit/10.1201/9781003000532/secondary-research-methods-built-environment-emmanuel-manu-julius-akotia?refId=3a100269-8031-4d4d-bcac-8629fd39966a
van Wesel, F., Boeije, H. R., & Alisic, E. (2015). Towards a method for synthesizing diverse evidence using hypotheses as common language. Quality & Quantity, 49(6), 2237–2249. https://doi.org/10.1007/s11135-014-0105-9
It depends on what research problem you are dealing with and the research questions you intend to answer.
In some instance, secondary sources are the only available sources for you and you've no option but to rely on them in constructing your argument and answering the questions raised.
In research, there are quite a number of factors that determine the sort of data you collect.