CompTIA Data+ DA0-002 (V2) Practice Question

A data explainability report is specifically designed to translate complex model behavior into business-friendly language. It usually contains feature-impact or attribution scores (for example, "Impact scores" or SHAP values), narrative text that describes the model's assumptions and limitations, and visuals that illustrate how each variable affects the output. This level of insight allows auditors and executives to understand why the model arrived at particular forecasts and to defend the results if challenged. A data dictionary only defines column names, a data-flow diagram shows pipeline movement, and a model performance report focuses on accuracy metrics-none of these directly explain the decision logic itself.