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AWS Machine Learning Specialty

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Data Engineering

A machine learning team needs to prepare a large dataset stored in Amazon S3 for training. The dataset contains millions of records with missing values, categorical variables that need encoding, and numerical features requiring normalization. The team wants a serverless, scalable solution that can handle this ETL workload efficiently. Which approach should they use?

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