Amazon SageMaker Data Wrangler reduces the time that 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 Simple Storage Service (Amazon S3), Amazon Athena, Amazon Redshift, and Snowflake. Starting today, you can now use Databricks as a data source in 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 ML.
Source:: Amazon AWS