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Data Concepts and EnvironmentseasyMultiple ChoiceObjective-mapped

DA0-002 Data Concepts and Environments Practice Question

A data analyst needs to ensure that a customer's address is stored in a consistent format across multiple databases. Which data quality dimension is the analyst primarily concerned with?

⚠ Common exam trap

A common mix-up: candidates confuse consistency with accuracy, thinking that if the address is correct (accurate), it must be consistent, but consistency is about format uniformity across systems, not the truthfulness of the data.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Consistency

The data analyst is primarily concerned with consistency, which ensures that the same data values are represented uniformly across different systems or databases. In this scenario, the customer's address must follow the same format (e.g., street, city, state, ZIP code) in every database to enable reliable merging and querying. Consistency is a key data quality dimension that focuses on cross-system uniformity, distinct from accuracy (correctness of values) or completeness (presence of all required fields).

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Consistency

    Why this is correct

    Consistency ensures data is uniform across systems.

  • Completeness

    Why it's wrong here

    Completeness checks for missing data, not format.

  • Accuracy

    Why it's wrong here

    Accuracy measures correctness of data, not format consistency.

  • Timeliness

    Why it's wrong here

    Timeliness refers to data being current, not format.

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