For statistical analysis, data analysts employ a variety of tools, each of which serves a distinct purpose. Because of their versatility and libraries like R's ggplot2 and Python's Pandas, NumPy, and SciPy, R and Python are widely used. Excel is still frequently used for simple visualisation, pivot tables, and fast computations. Analysts use Tableau or Power BI for visualisations, SAS for sophisticated analytics, and SQL for database querying when dealing with larger or more complicated data sets. Additionally, the social sciences and academia use programs like Stata and SPSS. Consider signing up for a data analyst school that goes over these tools in detail if you want to become an expert.
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