DATABRICKS-MLP Question 57

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• Chose A0

  ,B,D - Correct answer s : A, B, D — Integration testing in staging is meant to confirm that feature engineering, training, and inference work correctly together, not just individually.; For Python code, storing functions outside notebooks in modules improves both reusability and compatibility with standard test frameworks.; Staging is designed to closely mirror production so that the full test suite can run under representative conditions before promotion. A . This matches documented guidance on integration testing: it exists to validate that pipelines including feature engineering, training, and inference function correctly together, beyond what testing each in isolation would show. B . This matches documented guidance for Python: moving functions into modules outside notebooks makes them usable both inside and outside notebooks and lets standard test frameworks run against them more directly than against notebook cells. C . This is not accurate; passing unit tests for every individual function does not guarantee that the functions work correctly together as a connected pipeline, which is exactly why integration testing exists as a distinct, necessary stage. D . This matches documented guidance: staging is built to mirror production as closely as feasible and is where the complete testing suite runs before code or artifacts are promoted further. E . This contradicts documented guidance for SQL, which recommends organizing SQL logic as SQL user-defined functions stored within a schema, not by embedding SQL inside Python notebook cells.