Visual Data Preparation with AWS Glue DataBrew
Explore how AWS Glue DataBrew facilitates visual, no-code data preparation including transformations, missing data imputation, and encoding. Understand how to create reusable recipes for scalable ML workflows while ensuring data quality and bias detection through profiling. This lesson equips you to prepare clean, consistent datasets for AWS SageMaker training and production deployment.
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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