Evaluation within CRISP-DM is intended to ensure that ______.

• A. the data is clean
• B. the business goals are aligned
• C. the model is fastest
• D. data mining results are reliable and useful

Answer: (D)

In CRISP-DM, the evaluation step checks whether the data mining results are reliable and useful for decision making. After building a model or extracting patterns, you need to verify that the findings hold up on new data, are robust to reasonable changes, and actually address the business question at hand. This involves assessing performance on appropriate validation data, considering uncertainties and risks, and judging whether the results are interpretable and feasible to deploy in practice. Early steps like cleaning data or ensuring the business goals were considered are important, but evaluation focuses on trustworthiness and practical value of the mining results themselves.