How do you handle missing and inconsistent data in a large dataset?
You can handle missing and inconsistent data in a large dataset by using techniques like imputation, removal, or transformation to ensure accuracy. An Online course data analyticscan teach you advanced cleaning methods, including handling outliers, validating formats, and using tools like Python or SQL to streamline preprocessing for better insights.
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