Difficulty: Easy
Correct Answer: Correct
Explanation:
Introduction / Context:
Derived attributes help reduce redundancy and keep stored data minimal by computing values from existing data when needed. This question evaluates whether a derived attribute can be computed from related entities or relationship data, not only from attributes within the same entity.
Given Data / Assumptions:
Concept / Approach:
A derived attribute is any attribute whose value can be calculated from other data in the model. This includes values based on attributes of the same entity (e.g., age from date_of_birth and today), on related entities (e.g., total_order_value from order_line amounts), or on relationship-level facts (e.g., price_at_time on a participation that stores negotiated price). The key property is computability, not storage location.
Step-by-Step Solution:
Identify the target attribute (e.g., customer_age).Locate source data that deterministically yields the value (date_of_birth and current_date).If the source resides in a related entity or the relationship, ensure a well-defined join/association exists.Express the derivation rule clearly for implementation (view, computed column, or application logic).
Verification / Alternative check:
Prototype a query or view showing the computed value. If the same value can be reproduced consistently from source data, the attribute is legitimately derived.
Why Other Options Are Wrong:
Restricting derivations to the same entity ignores common cross-entity calculations. Claiming derivations exist only in dimensional modeling is false; derivations are fundamental to ER modeling as well.
Common Pitfalls:
Persisting derived data without governance leads to inconsistencies. Not documenting derivation logic creates ambiguity.
Final Answer:
Correct
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