What does Amazon SageMaker Data Wrangler primarily assist with in data tasks?

Amazon SageMaker Data Wrangler is designed specifically to facilitate data exploration, cleaning, and transformation. It provides an intuitive interface that allows data scientists and analysts to easily perform data preparation tasks without needing extensive coding skills. Users can import data from various sources, conduct exploratory data analysis, visualize the data, and apply various transformation techniques to preprocess the data for machine learning models.

This tool streamlines the data preparation process, which is often one of the most time-consuming steps in the machine learning workflow. With SageMaker Data Wrangler, users can efficiently tackle issues such as missing values, outliers, and feature engineering, which are critical for building effective and accurate machine learning models.

The other options pertain to functions that are either outside the scope of what Data Wrangler offers or are more general tasks that SageMaker accomplishes through different components. For example, while SageMaker does provide various features for automating workflows or cloud storage, these do not specifically align with the core functionality of Data Wrangler, which is centered on data preparation.