What is

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Elementary?

The data observability platform built for data & analytics engineers and trusted by 5000+ data professionals. Prevent, detect, and resolve data quality issues, in your dbt pipelines and beyond.

Automated monitors

Freshness, volume and schema changes for all production tables

Out-of-the-box monitors activated automatically, without manual configuration.
Monitors leverage metadata such as information schema and query history, for monitoring with low compute cost
Automated adjustments based on frequency of updates, seasonality, and trends.

Anomaly Detection

Add monitors to detect unexpected changes

Add tests as you develop in code, or from the Elementary UI.
Detect anomalies in nullness, distribution, dimensions, completeness and more
Highly configurable for better accuracy: seasonality, where expressions, sensitivity and more.

data TESTS

One solution for all your data tests - dbt, elementary & custom

No need to reconfigure or duplicate logic, your existing tests are part of your Elementary coverage.
Leverage the dbt ecosystem with tests from packages like dbt-expectations, dbt-utils, and more.
Extend coverage with your custom tests.

End-to-end lineage

Column-level lineage, automated across your stack

Column-level lineage from your code, data warehouse, sources and BI tools.
Elementary’s lineage is enriched with test results, to show incidents across the DAG.
Quickly understand the origin of issues, and which assets are impacted.

Alerts

Actionable alerts to different systems, channels and recipients

Route alerts to different recipients and owners and avoid alert fatigue.
Alert on failures of Elementary monitors, dbt tests, model runs, and source freshness issues.
Enrich your alerts with additional properties and custom formats.

Code-first

Configuration as Code built for data & analytics engineers

All configurations are managed in your dbt code, enabling version control, code review, and CI/CD.
Observability configuration becomes part of the development process.
Escape vendor lock-in and onboarding hassle, utilize existing configurations and own new additions.

Data quality dashboard

Understand and communicate overall data health

Get an overview of your data health in a user-friendly dashboard.
Filters and drill-down options to allow users to focus on specific data subsets and investigate issues.
Quality dimensions scores (coming soon).

Data catalog

For your assets, maintained in code

Explore data sets, including underlying code, overall health, dependencies, ownership, and descriptions.
All descriptions, tags, and owners are managed and maintained in your code.
Easily navigate from catalog to test results, lineage, and runs history.