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You have a complex data pipeline implemented using Snow park Python. The pipeline involves multiple Data Frame transformations, joins, aggregations, and window functions. To enhance the maintainability and readability of the code, you want to modularize the pipeline into reusable functions. You also need to handle potential errors and exceptions gracefully. Consider the following code snippet:
Correct Answer: B,D
Options B and D represent robust approaches to modularizing and handling errors in Snowpark pipelines. Option B demonstrates reusability by parameterizing the session and table name and returning a DataFrame. A: try except is good but lacks session and table name parameters for resuablity Option D demonstrates logging error details to a dedicated table to provide insights for auditing.