One can go ahead with building up a theoretical model, which is focused at solving a particular real world problem being faced. Unless the model is tested with real life data, which is contextual in nature, the relevance of the model can never be justified. In accordance with the nature of the model, it can call for several kinds of data, may it be qualitative or quantitative. For qualitative data, primary data collection is needed to be done, as the variables used in the model require the observational records. For quantitative data, the data collection procedure may be easier compared to qualitative data collection. As many organizations across the world collect secondary data on various indicators, collection of secondary may prove out to be easy. Firstly, based on the nature of the indicator, one should try to look for the proper organization, which publishes that data. Subsequent to visiting the website of that organization, one should look for pages like “reports”, “data bank”, “proceedings”, etc. Many times, some data points are intentionally omitted in the dataset published by those organizations due to several reasons. For that purpose, one should contact that organization directly mentioning the purpose of the data. To know more about the data collection procedure, kindly browse the pages of learnwithmike.eu.