An analyst is working to identify trends in a study and finds the data set has a lot of missing values. Which of the following best describes the data quality issue?

The correct answer is D. Completeness. Completeness refers to whether all required data is present in a dataset. When there are missing values, it indicates a lack of completeness, which can hinder the ability to analyze data accurately and effectively. This aligns with the scenario where the analyst encounters a…

Data Governance, Quality, and Controls

Question

Options

AAccuracy
BRedundancy
CDuplication
DCompleteness

How the community answered

(54 responses)

A
4% (2)
B
2% (1)
C
7% (4)
D
87% (47)

Explanation

Completeness refers to whether all required data is present in a dataset. When there are missing values, it indicates a lack of completeness, which can hinder the ability to analyze data accurately and effectively. This aligns with the scenario where the analyst encounters a dataset with many

Topics

#Data quality#Missing values#Data completeness#Data quality dimensions

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