Consistent data asks if there is a value missing from the data.

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Restating the prompt helps focus attention on what is being asked: whether the statement about consistent data is true or false.
Option 1: 'True' — If we claimed that consistent data asks if there is a value missing from the data, we would be conflating consistency with completeness. Consistency generally refers to uniformity, validity across records, and adherence to rules, whereas missing values pertain to completeness. Therefore, describing consistency as specifically asking about missing values mischaracterizes what consistency typically entails.
Option 2: 'False' — This option aligns with the distinction between consistency and completeness. While missing values relate to whether all required data is present (completeness), consistency concerns whether data conforms to the same formats, standards, and inter-field relationships across the dataset. In that sense, a statement that consistent data asks about missing values is inaccurate, making this option a more fitting characterization of the concept.
Option 1 revisits common misconceptions, emphasizing that a claim equating consistency with checking for missing data conflates two separate data quality dimensions, which can lead to incorrect conclusions about data health.
Option 2 reinforces the idea that completeness and consistency are related but distinct concepts in data quality, clarifying why the statement in Option 1 is not an accurate description of what consistent data entails.

MANAGEMENT INFORMATION SYSTEMS CIS 3010-16 (93684) Exam Two

Consistent data asks if there is a value missing from the data.

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