What data preprocessing activity does not fall under data cleaning?

What data preprocessing activity does not fall under data cleaning?

• A. Removing duplicates
• B. Filling missing values
• C. Deriving a new variable
• D. Correcting data entry errors

Answer: (C)

Deriving a new variable is not considered a part of data cleaning, as it primarily focuses on creating additional features from existing data rather than correcting or refining the quality of the data itself. Data cleaning typically involves activities aimed at improving the accuracy and reliability of the data, such as removing duplicates, filling in missing values, and correcting any data entry errors. These actions help ensure that the dataset is free from inconsistencies and errors, thereby preparing it for analysis. In contrast, deriving a new variable expands the dataset with additional information and may involve transformations or calculations based on the original data, placing it outside the scope of data cleaning activities.

Deriving a new variable is not considered a part of data cleaning, as it primarily focuses on creating additional features from existing data rather than correcting or refining the quality of the data itself. Data cleaning typically involves activities aimed at improving the accuracy and reliability of the data, such as removing duplicates, filling in missing values, and correcting any data entry errors. These actions help ensure that the dataset is free from inconsistencies and errors, thereby preparing it for analysis. In contrast, deriving a new variable expands the dataset with additional information and may involve transformations or calculations based on the original data, placing it outside the scope of data cleaning activities.