Researchers in many disciplines work with data that can become difficult to manage in spreadsheets or isolated files alone. This may be due to the size of the data, but also to their complexity, structure, and the need to organize, link, document, and query related information in a consistent and reproducible way. Relational database management systems (RDBMS) and SQL offer one way to address these challenges and to manage data for further analysis. Yet for many researchers, databases remain a technical topic that seems distant from everyday research practice. This Data Snack provides a low-threshold overview of relational databases and SQL for researchers across domains. It outlines why databases can become relevant in research, presents typical use cases, and gives a first orientation on how relational databases, SQL, and common analysis tools such as R and Python can fit together in a research workflow.
Nolte et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: