![]() This involves dealing with missing values, outliers, and data inconsistencies. Data Manipulation and Cleaning: Learn how to clean, preprocess, and transform data to ensure it's ready for analysis.Database Skills: Gain familiarity with databases and SQL (Structured Query Language), as data analysts often work with large datasets stored in databases. ![]() Python is particularly popular due to its adaptablity and extensive libraries for data manipulation and analysis.
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