What are the most common mistakes beginners make in data cleaning and preprocessing?
One of the most common mistakes beginners make in data cleaning and preprocessing is ignoring missing values, duplicate records, or inconsistent formats. They also tend to overlook normalization and outlier handling. Through Data analytics training, learners can gain hands-on skills to systematically clean, preprocess, and prepare datasets for accurate analysis.
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