In information quality, which principle is described by data being well-structured and including all intended elements?

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Multiple Choice

In information quality, which principle is described by data being well-structured and including all intended elements?

Explanation:
Data completeness means information is fully present and usable: data is well-structured and includes all intended elements. When a dataset is complete, every required field exists and is populated, and all necessary records are present, following a consistent schema. This makes analyses reliable because there are no gaps that could lead to misinterpretation or missed insights. For example, a customer table should include fields like ID, name, address, and contact details with no missing values for active customers. If any of these elements are missing, analyses may be biased or incomplete. Encryption protects confidentiality, not completeness; duplicates add unnecessary redundancy and archiving governs long-term storage, not whether the data contains all needed items.

Data completeness means information is fully present and usable: data is well-structured and includes all intended elements. When a dataset is complete, every required field exists and is populated, and all necessary records are present, following a consistent schema. This makes analyses reliable because there are no gaps that could lead to misinterpretation or missed insights. For example, a customer table should include fields like ID, name, address, and contact details with no missing values for active customers. If any of these elements are missing, analyses may be biased or incomplete. Encryption protects confidentiality, not completeness; duplicates add unnecessary redundancy and archiving governs long-term storage, not whether the data contains all needed items.

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