The particular tasks and properties of the data determine whether SQL or R is more efficient for data analysis. SQL offers speed and scalability, making it perfect for organizing and querying huge datasets, particularly in databases. R is an excellent tool for modelling, data visualization, and statistical analysis. It offers several packages for sophisticated analytics. I’ve used R for in-depth analysis, predictive modelling, and the creation of visualizations for insights that can be put into practice. I’ve also used SQL for data extraction and preprocessing in business analytics. By combining the strengths of both technologies—SQL’s data handling skills and R’s analytical strength—efficiency is maximized, and complete business analytics solutions are produced.
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