Which of the following is NOT a classification of errors?

Which of the following is NOT a classification of errors?

• A. Value
• B. Missing
• C. Physical
• D. Duplicate

Answer: (C)

The classification of errors typically refers to how errors in data or processes can be categorized in order to identify and address them effectively. In the context of data integrity and processing, common classifications include errors that relate directly to the data itself or its completeness—specifically, value errors (where the data is incorrect), missing errors (when data is absent), and duplicate errors (where data entries are repeated). Physical errors, however, are generally not categorized in the same way as the others mentioned. They could refer to issues related to hardware or external factors rather than errors directly related to the data itself. This makes "Physical" not a classification of errors within the usual framework used for data integrity errors, such as those seen in data processing systems or integrations where Celigo operates. Understanding these distinctions is crucial because accurately classifying errors helps in diagnosing and rectifying issues effectively, ensuring smoother data operations and better system performance.

The classification of errors typically refers to how errors in data or processes can be categorized in order to identify and address them effectively. In the context of data integrity and processing, common classifications include errors that relate directly to the data itself or its completeness—specifically, value errors (where the data is incorrect), missing errors (when data is absent), and duplicate errors (where data entries are repeated).

Physical errors, however, are generally not categorized in the same way as the others mentioned. They could refer to issues related to hardware or external factors rather than errors directly related to the data itself. This makes "Physical" not a classification of errors within the usual framework used for data integrity errors, such as those seen in data processing systems or integrations where Celigo operates.

Understanding these distinctions is crucial because accurately classifying errors helps in diagnosing and rectifying issues effectively, ensuring smoother data operations and better system performance.