DA0-001 · Question #52
While reviewing survey data, a research analyst notices data is missing from all the responses to a single question. Which of the following methods would BEST address this issue?
The correct answer is D. Remove invalid data. When an entire question's responses are missing from survey data, it indicates invalid or non-existent data for that field, and the best approach is to identify and address this invalidity, often by removing or marking those specific invalid entries or the question itself.
Question
While reviewing survey data, a research analyst notices data is missing from all the responses to a single question. Which of the following methods would BEST address this issue?
Options
- AReplace missing data.
- BRemove duplicate data.
- CReplace redundant data.
- DRemove invalid data.
How the community answered
(52 responses)- A15% (8)
- B4% (2)
- C8% (4)
- D73% (38)
Why each option
When an entire question's responses are missing from survey data, it indicates invalid or non-existent data for that field, and the best approach is to identify and address this invalidity, often by removing or marking those specific invalid entries or the question itself.
Replacing missing data, or imputation, is suitable for scattered missing values, but not when an entire field is consistently missing across all responses, which suggests a more fundamental problem.
Removing duplicate data addresses redundant entries, which is a different data quality issue than consistently missing responses for a specific question.
Replacing redundant data addresses information stored multiple times, which is unrelated to the issue of entirely missing responses for a question.
When an entire question's responses are missing, it indicates a significant data quality issue making that specific data invalid or unusable; therefore, removing or appropriately handling this invalid data is the best approach to ensure reliable analysis.
Concept tested: Data quality remediation - missing data
Source: https://learn.microsoft.com/en-us/azure/data-factory/concepts-data-quality
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