Could you explain how you would structure a test case to validate data transformations? For example, what data inputs would you use?

When structuring a test case for data transformations, you should start by defining the input data, the expected output, and the validation logic. Use representative data that covers typical values, edge cases, and boundary conditions. For example, if you are normalizing user names, you might use inputs like "John Doe", "john doe", and "JOHN DOE" and expect the output to be "John Doe". Include preconditions, steps, expected results, and cleanup steps. Store test data in CSV or JSON files and load it with a library such as pandas. Use a test framework like PyTest or unittest and write assertions to compare the actual output to the expected output. Also consider performance by testing with larger data volumes. Finally, integrate the tests into a CI pipeline so they run automatically on each commit.