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Boosting data literacy: essential skills for early career researchers

Data literacy is increasingly important for researchers and allows for optimal data management and valuable conclusion generation. Understanding different data formats, such as CSV, JSON and XML, choosing the right analytical tool and data cleaning are all crucial skills. Good data management also involves data protection measures. Advanced data analysis using software like R, Python or SPSS is essential, as is effective data visualisation and communication. It’s also important to collaborate with fellow researchers. Boosting data literacy can be achieved through various methods like online courses, finding a mentor and joining data science communities.

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