When working with large datasets it is important that the right tools and methods are selected in order to effectively, it is important that the right tools and methods are selected in order to effectively analyze the data. This thesis presents a comparative evaluation of data management tools in the categories of validation, profiling, and feature extraction. The tools, Pandera, Ydata Profiling, SweetViz, and Tsfel, were selected and integrated into a data processing system for the WARA--Ops portal in order to validate, profile, and analyze new operational datasets uploaded to the portal. Finally, the system extracts statistical information from the dataset and uses a machine learning classification algorithm to apply a general label to the data based on the extracted information.