Explanation:
When designing a data pipeline for reliability and fault tolerance, it is important to consider implementing data validation and error handling mechanisms, ensuring data redundancy and backup mechanisms, and using a distributed processing architecture. This ensures that the pipeline can handle failures and continue processing data without significant disruptions. Option A is correct because data validation and error handling help detect and handle errors in the data. Option B is correct because data redundancy and backup mechanisms help ensure that data is not lost in case of failures. Option C is correct because a distributed processing architecture helps distribute the workload and provides fault tolerance in case of node failures.
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You are working on a project that requires creating data pipelines to move and process data. You have been asked to ensure the reliability and fault tolerance of the data pipeline. What measures should you consider when designing a data pipeline for reliability and fault tolerance?
A
Implementing data validation and error handling mechanisms.
B
Ensuring data redundancy and backup mechanisms.
C
Using a distributed processing architecture.
D
All of the above.