Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for ML from weeks to minutes With 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, visualization, cleansing, and preparation from a low-code visual interface. Many ML practitioners want to explore datasets directly in notebooks to spot potential data-quality issues, like missing information, extreme values, skewed datasets, or biases, so they can correct those issues to prepare data for training ML model faster. ML practitioners can spend weeks writing boilerplate code to visualize and examine different parts of their dataset to identify and fix potential issues.