What is a suitable approach when encountering missing data sources in the data collection process?

Acquiring missing data sources after obtaining intermediate results is a practical approach because it allows for a more informed decision-making process. This strategy recognizes that while some data may initially be unavailable, there may be opportunities to fill those gaps through further data collection or alternative methods. By analyzing the data that is currently available, you can gain insights and understand the implications of the missing data, which can guide efforts to acquire the necessary information.

This approach supports iterative refinement in your analysis, as it allows you to adapt as more data comes in, ultimately leading to a more robust and informed analysis. It acknowledges the dynamic nature of data collection, especially in environments where data availability can change, rather than forcing a premature conclusion based on incomplete datasets.