Data profiling refers to a systematic process of reviewing a dataset's structure, content, and quality to identify unusual patterns, missing values, or inconsistencies that could negatively impact analysis. It is a critical step in ensuring data reliability before proceeding with modeling or reporting. Misunderstanding this concept or skipping it entirely can lead to flawed insights and downstream inefficiencies.
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What are the main goals of data profiling?
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What tools are commonly used for data profiling?
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How can data profiling improve data analysis outcomes?