Today, we are excited to announce support for scheduling Data Wrangler processing jobs in Amazon SageMaker Data Wrangler. Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes. 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. Previously, scheduling a data processing job would involve integrating with a serverless compute capability and an event bus service. This process would also involve writing code to schedule the data processing job in a production environment. Integrating these various capabilities together and writing the code to orchestrate this workflow can be a laborious, time-consuming task for data scientists, data engineers and ML engineers.
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