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Visual Data Preparation with AWS Glue DataBrew

Explore how to use AWS Glue DataBrew to visually prepare and transform data without coding. Understand key tasks like scaling, encoding, missing data imputation, and bias detection, helping you build clean, reliable datasets for machine learning on AWS.

AWS Glue DataBrew occupies a specific position in the ML data engineering pipeline as a visual, no-code data preparation service. For the AWS Certified Machine Learning Engineer  Associate exam, understanding when and how to use DataBrew for data exploration, transformation, and quality validation is a testable skill. DataBrew is purpose-built for analysts and data engineers who need to clean and normalize data without writing ETL code, and it connects directly to Amazon S3, Amazon Redshift, Amazon RDS, and the AWS Glue Data Catalog as source and target endpoints. The service provides more than 250 built-in transformations organized as recipe stepsOrdered, versioned sequences of data transformations that DataBrew applies to a dataset, analogous to a saved list of instructions that can be replayed on any compatible dataset.. It also includes a data-profiling engine and project-based workflows that make iterative data ...