Elementary Data

Elementary Data provides a unified data and AI control plane designed to bring together metadata, lineage, logs, validations, and health signals. It aims to accelerate data and AI product development by ensuring reliable data for every workflow and AI agent. The platform helps data engineers and business users manage data quality, discover data assets, enforce governance policies, and observe data pipelines to detect and resolve issues proactively. Built on a context engine, Elementary Data integrates with various parts of the data stack, from ingestion to BI and AI, providing end-to-end reliability. It leverages AI to manage, monitor, validate, and triage data at scale, addressing the complexity that outgrows human capacity. The tool offers both an open-source dbt package for basic observability and a Cloud platform with enterprise-grade features for scaling data observability, catering to modern data teams looking to build trust and maximize the value of their data investments. Elementary Data is particularly beneficial for organizations using dbt, as it offers dbt-native integration, allowing teams to manage tests, rules, and metadata in code. It helps prevent breaking changes, optimize query performance, and provides a conversational catalog for easy data discovery. The platform also focuses on incident management, automated monitoring, and health scoring to ensure data reliability and reduce alert fatigue.