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In the context of developing a scalable and efficient machine learning (ML) pipeline for a data-driven project, which of the following best describes the impact of automating and orchestrating ML pipelines? Consider the need to minimize manual errors, ensure consistency across tasks, and optimize the speed of execution. Choose the two most accurate options.
A
It eliminates the need for manual data preprocessing by automating all steps.
B
It significantly slows down the data collection phase due to the overhead of automation scripts.
C
It reduces manual errors, speeds up repetitive tasks, and ensures consistency across the pipeline execution.
D
It introduces unnecessary complexity, making the pipeline harder to manage and scale.
E
Both A and C are correct.