What process is involved in data triangulation?

Data triangulation is a crucial process in research that involves utilizing multiple data sources or methods to enhance the credibility and validity of findings. By integrating diverse perspectives and approaches, researchers can gain a more comprehensive understanding of a phenomenon. This approach minimizes the limitations and biases that might be present when relying solely on one method or source, thus providing a richer and more reliable insight into the subject being studied.

Using multiple data sources can include qualitative and quantitative data, surveys, interviews, observations, and existing data. This combination allows researchers to cross-verify information, leading to more robust conclusions and deeper insights. Furthermore, triangulation can help identify patterns and inconsistencies that may not be evident when only one method is employed.