Data scrubbing allows us to handle anomalies that are present in the data set.

• A. False
• B. True
• C. Sometimes
• D. Not at all

Answer: (B)

Data scrubbing is the process of cleaning data by finding and correcting errors, inconsistencies, and inaccuracies. It targets anomalies such as misspellings, inconsistent formats, duplicate records, missing values, and outliers. By applying validation rules, standardizing formats, deduplicating records, imputing or removing missing values, and flagging or adjusting outliers, data scrubbing makes the dataset more consistent and trustworthy for analysis. Therefore, it enables us to handle anomalies present in the data set. However, some complex anomalies may require more advanced techniques or domain knowledge beyond automated cleaning.