Launch Announcement: Amazon SageMaker Data Wrangler now supports Databricks as a data source

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio, the first fully integrated development environment (IDE) for ML. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from a single visual interface. You can import data from multiple data sources such as Amazon S3, Amazon Athena, Amazon Redshift, Snowflake. Starting today, you can now use Databricks as a data source in Amazon SageMaker Data Wrangler to easily prepare data in Databricks for machine learning. Databricks, an AWS Partner, helps organizations prepare their data for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning (ML).

To learn more about Databricks integration with Amazon SageMaker Data Wrangler, view our blog or AWS document. To get started with Amazon SageMaker Data Wrangler, visit our AWS documentation and pricing page.