A city bus-ridership table still fails Glue Data Quality checks, an…

Question

A city bus-ridership table still fails Glue Data Quality checks, and SageMaker Clarify has not reported pre-training bias. The lead wants to launch the SageMaker training job tonight and clean the table later. What should the team do first?

Accepted Answer

Finish quality validation and a pre-training bias review, then publish the training set before any training job starts. — Think of a ridership table still failing Glue Data Quality, and Clarify has not reported pre-training bias. Finish those gates and publish the training set first. Launching tonight and cleaning later skips Domain 1.

Answer

Start training now and treat quality and bias as a post-training cleanup.

Answer

Amazon Rekognition, because a vision API is a quality-and-bias gate.

Answer

Skip Glue Data Quality and Clarify because a SageMaker training job validates the table on its own.

A city bus-ridership table still fails Glue Data Quality checks, and SageMaker Clarify has not reported pre-training bias. The lead wants to launch the SageMaker training job tonight and clean the table later. What should the team do first?

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