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  3. Introduction to Data Pipelines

Exercise

Running a data pipeline end-to-end

It's important to monitor the performance of a pipeline when running in production. Earlier in the course, you explored tools such as exception handling and logging. In this last exercise, we'll practice running a pipeline end-to-end, while monitoring for exceptions and logging performance.

Instructions 1/3

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  • From the pipeline_utils.py file, import the extract(), transform(), and load() functions.