Before data can be analyzed, modeled, or reported reliably, it often must be made consistent and usable, and Data Preparation & Feature Transformation is the agentic skill that performs this work. It enables an AI agent to clean, normalize, join, reshape, deduplicate, encode, scale, and derive features from raw or partially structured inputs so that the resulting dataset is ready for analysis, machine learning, visualization, or downstream processing. Its value lies in speed, repeatability, and scalability, especially when large or heterogeneous datasets require standardized preprocessing steps that would be time-consuming to perform manually. ...