# elementary

**Repository Path**: orientMoon/elementary

## Basic Information

- **Project Name**: elementary
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-10-09
- **Last Updated**: 2026-10-09

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

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<h2 align="center">
Elementary OSS: dbt-native data observability
</h2>

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[Docs »](https://docs.elementary-data.com/) | [Join the Elementary Community »](https://www.elementary-data.com/community)

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  ⭐️ Star the repo <a href="https://github.com/elementary-data/elementary/stargazers"><img src="static/star_github.png" width="45"/></a> 
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**Built by the [Elementary](https://www.elementary-data.com) team, helping you deliver trusted data in the AI era.**

Elementary OSS is the open-source CLI for dbt-native data observability. It works with the [Elementary dbt package](https://github.com/elementary-data/dbt-data-reliability) to generate the basic Elementary observability report and send alerts to Slack and Microsoft Teams.

For teams that need data reliability at scale, we offer **[Elementary Cloud](https://www.elementary-data.com/)**, a full Data & AI Control Plane with automated ML monitoring, column-level lineage from source to BI, a built-in catalog, and AI agents that scale reliability workflows for both engineers and business users.

![Demo](static/newreadmedemo.gif)

## How It Works

Elementary OSS connects to your warehouse and reads the metadata, artifacts, and test results collected by the Elementary dbt package.  
With this information, it can:

- Generate a data observability report
- Surface anomalies and failed tests
- Send alerts to Slack and Teams
- Track model and test performance trends

## Quickstart

Follow the quickstart guide to install and configure the Elementary dbt package and CLI:

👉 https://docs.elementary-data.com/oss/quickstart

## Features

- **Anomaly detection tests** - Collect data quality metrics and detect anomalies, as native dbt tests.
- **Automated monitors** - Out-of-the-box cloud monitors to detect freshness, volume and schema issues.
- **End-to-End Data Lineage** - Enriched with the latest test results, for impact and root cause analysis of data issues. Elementary Cloud offers **Column-Level-Lineage from ingestion to BI**.
- **Data quality dashboard** - Single interface for all your data monitoring and test results.
- **Models performance** - Monitor models and jobs run results and performance over time.
- **Configuration-as-code** - Elementary configuration is managed in your dbt code.
- **Alerts** - Actionable alerts including custom channels and tagging of owners.
- **Data catalog** - Explore your datasets information - descriptions, columns, datasets health, etc.
- **dbt artifacts uploader** - Save metadata and run results as part of your dbt runs.
- **AI-Powered Data Tests & Unstructured Data Validations** - Validate and monitor data using AI powered tests to validate both structured and unstructured data

## Support

For additional information and help:

- [Join thousands of users in the Slack community](https://www.elementary-data.com/community) \(Release announcements, community and AI support, discussions, etc.\)
- [Open a GitHub issue](https://github.com/elementary-data/elementary/issues) \(Bug reports, feature requests)
- Check out the [contributions guide](./CONTRIBUTING.md) and [open issues](https://github.com/elementary-data/elementary/issues).

##

**Elementary contributors: ✨**

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