Elementary Key Features
Data anomaly detection
Monitor data quality metrics, freshness, volume and schema changes.
dbt artifacts and run results
Upload metadata, run and test results to tables as part of your jobs.
Alerts
Send informative alerts to different channels and users.
Data observability dashboard
Inspect your data health overview, test results, models performance and data lineage.
End-to-end data lineage
Inspect dependencies including Column Level Lineage and integration with BI tools.
Automated monitors
Out of the box freshness, volume and schema monitoring.
Configuration as code
All the Elementary configuration is managed in your dbt code.
Data Catalog
Explore and discover data sets, manage your documentation in code.
Anomaly Detection
Automated Volume & Freshness Monitors
Out-of-the-box ML-powered monitoring for freshness and volume issues on all production tables.
The monitors track updates to tables, and will detect data delays, incomplete updates, and significant volume changes.
By qurying only metadata (e.g. information schema, query history), the monitors don’t add compute costs.
Opt-in Anomaly Detection Monitors
ML-powered anomaly detection on data quality metrics such as null rate, empty values, string length, numeric metrics (sum, max, min, avg), etc. Elementary also supports monitoring for anomalies by dimensions. The monitors are activated for specific data sets, and require minimal configuration (e.g. timestamp column, dimensions).
Schema Validation
Schema Tests
Elementary offers a set of schema tests for validating there are no breaking changes. The tests support detecting any schema changes, only detecting changes from a configured baseline, JSON schema validation, and schema changes that break downstream exposures such as dashboards.
Automated Schema Monitors
Coming soon!
Data Tests
Custom SQL Tests
dbt tests
Python tests