Skip to main contentDecember 21, 2022: v0.6.3 Python, v0.6.6 dbt package
🔥 What’s new?
-
Slack alerts V2 2️⃣
- Elementary now supports customizing alerts, so you could notify data producers and consumers 🧑🔧
- Instead of sending detailed technical alerts, you can select fields. Learn more here how to configure it.
- Email owners will be translated to Slack handles in the alerts. Thanks Josh Elston-Green for contributing.
- Alerts also underwent layout improvements 🎨
-
New data tests 🩺
- Advanced schema tests, useful for source monitoring and enforcing data contracts: ✅
schema_changes_from_baseline - Define a schema in your models/<properties.yml> and ensure its validity.
json_schema - Validate the schema of JSON columns. 😱
- To ease configuration and implementation - both tests include operations to auto-generate the schema.
- New and improved table anomalies tests, including
where_expression: 📉
volume_anomalies - Monitor your row count over time.
freshness_anomalies - Monitor the freshness of you data over time.
-
Report UI new features 🆕
- Filter your report by Tags & Owners sidebars #️⃣🤵🏻
- dbt-expectations integration in the UI, including test descriptions.
- Custom test descriptions were added to the UI.
-
Monitor job results ⚛️
- Added job-related columns to
dbt_invocations and created job_run_results table.
- Keep track of your dbt jobs in dbt Cloud, GitHub Actions, Airflow, etc.
- The new columns can be viewed here.
-
Sensitive data / PII 🤫
- Have sensitive data that contains PII? x
- Use the new flag (
-disable-samples) to disable sampling of data in the report and alerts
💫 More changes
- Added support for
dbt-utils 1.0.0 - Thanks Jumpei Chikamori for contributing.
- Elementary’s tables are not full-refreshed by default - This can be changed using the
elementary_full_refresh var.
- The report doesn’t auto-open when using WSL - Thanks Ivan Toriya for contributing.