December 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.