Encord Active's Bulk Classification feature is a valuable tool for Data Operations and Machine Learning teams dealing with large volumes of unstructured data, offering a streamlined approach to data classification and labeling. By allowing users to apply uniform classifications to extensive datasets efficiently, the feature transforms the traditionally labor-intensive task of individual data labeling into a more manageable and precise process. This is particularly useful in projects like weather analysis, where specific patterns need to be identified and classified consistently. The Bulk Classification process involves four straightforward steps: importing and exploring the project, filtering and selecting data, creating a collection, and applying classifications, with support for nested ontologies to enhance classification granularity. Encord Active's Bulk Classification aims to improve data enrichment and pre-labeling, significantly speeding up workflows and ensuring accuracy, making it an essential component for teams looking to optimize their data management strategies.