The Elastic Common Schema (ECS) is introduced as a new open-source specification designed to standardize data structuring in Elasticsearch, enhancing both interactive and automated data analysis across diverse sources. ECS aims to resolve formatting inconsistencies by providing a uniform set of document fields, enabling seamless data integration from various environments and vendors. This facilitates more efficient search, visualization, and machine learning-driven anomaly detection. ECS's taxonomy, organized into core, extended, and custom fields, allows for predictable data modeling while supporting custom use cases. By adopting ECS, users can streamline data correlation, reduce duplication, and ease the development of analytics content, thus improving interoperability and efficiency in data management. Despite its benefits, implementing ECS requires effort, particularly for those familiar with Elasticsearch index templates and Logstash. The schema, available on GitHub and licensed under Apache 2.0, is in Beta2 and expected to become generally available, with future updates aimed at expanding use case support.