Homework Help: Questions and Answers: Which of the following would NOT be considered an accurate characteristic of high-quality data?
A. Is the name spelled correctly?
B. Is the email address invalid?
C. Do the name and phone values have the exact same data?
D. Is aggregate data in agreement with detailed data?
Answer
First, let’s understand what high-quality data is:
High-quality data typically has the following characteristics:
- Accuracy: Data should be correct and free of errors.
- Consistency: Data should be consistent across different systems and datasets.
- Completeness: No data is missing.
- Validity: Data follows the correct format and meets predefined rules.
- Integrity: Data should be complete, consistent, and properly linked across systems.
Given Options: Step by Step Answering
a) Is the name spelled correctly?
- This checks the accuracy of the data. Accurate data is a key characteristic of high-quality data.
- This is a valid characteristic of high-quality data.
b) Is the email address invalid?
- This checks the validity of the email format. Validity is also a key aspect of high-quality data.
- This is a valid characteristic of high-quality data.
c) Do the name and phone values have the exact same data?
- Having the name and phone values contain the same data would likely indicate an error, as these fields should contain different types of information (a name and a phone number).
- This checks for errors or inconsistencies. If the name and phone number fields have the exact same data, it would indicate poor data quality.
- This is not a valid characteristic of high-quality data. In fact, it indicates low-quality data.
d) Is aggregate data in agreement with detailed data?
- This checks the consistency between aggregate and detailed data, which is an important characteristic of high-quality data.
- This is a valid characteristic of high-quality data.
Final Answer
Based on the analysis above, the correct answer is:
C. Do the name and phone values have the exact same data?
This would indicate a data error, not a characteristic of high-quality data.
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