Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code.
SageMaker Data Wrangler supports Snowflake, a popular data source for users who want to perform ML. We launch the Snowflake direct connection from the SageMaker Data Wrangler in order to improve the customer experience. Before the launch of this feature, administrators were required to set up the initial storage integration to connect with Snowflake to create features for ML in Data Wrangler. This includes provisioning Amazon Simple Storage Service (Amazon S3) buckets, AWS Identity and Access Management (IAM) access permissions, Snowflake storage integration for individual users, and an ongoing mechanism to manage or clean up data copies in Amazon S3. This process

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