Elementary is a dbt-native data observability command-line tool for analytics and data engineering teams.
It works with the Elementary dbt package to read warehouse metadata, dbt artifacts, and test results, then uses that information to help monitor pipeline health, investigate data issues, generate observability reports, and send alerts to collaboration tools.
This is free and open source software.
Key Features
- Generates data observability reports from metadata, artifacts, and test results collected by the Elementary dbt package.
- Surfaces anomalies, failed tests, freshness issues, volume changes, and schema problems.
- Sends alerts to Slack and Microsoft Teams so teams can respond to data issues quickly.
- Tracks model, job, and test performance trends over time.
- Uses configuration as code so monitoring rules live alongside dbt project code.
- Includes support for data lineage, data quality dashboards, data catalog information, and dbt artifact uploads.
Website: github.com/elementary-data/elementary
Support:
Developer: Elementary
License: Apache License 2.0
Elementary is written in Python. Learn Python with our recommended free books and free tutorials.
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