✨ New & Improved

• Monitoring filters: users can now filter rules based on the data source, table name, monitoring type, or any tag added to the rules.
• Several UX enhancements across the UI, such as the lineage exploration experience on an incident report or pagination in data sources' historical runs.

🛠 Fixes

• Fixed a bug in the integrations page preventing from showing the next runs timestamps.

✨ New & Improved

• Incident report: Users can now efficiently troubleshoot data quality issues by having all the necessary context on the same page: Upstream and downstream dependencies of the asset impacted by the incident, Users assigned with the troubleshooting, incident mitigation updates ...

• Dynamic monitoring: define data quality rules on numerical values with dynamic thresholds, using ML models and fields historics.

• dbt Cloud: Sifflet integrates with dbt Cloud and extends all our dbt-specific features to users relying on dbt Cloud.
• Improved search engine performance by cutting the search time by up to 80%.
• Improved the connection testing for Snowflake when connecting a new data source.
• Improved the UI to ensure a smoother user experience

✨ New & Improved

• Introducing data assets SQL: Users can now preview SQL queries behind supported data assets directly on the UI with the Show SQL button. In the case of data tables, this will be the create/edit/update SQL query. In the case of dbt models, this will be the SQL queries the models are running.

🛠 Fixes

• Fixed an issue preventing users sometimes from expanding the upstream dependencies on the Lineage graph.

✨ New & Improved

• Improved MySQL integration by supporting several TLS versions.

✨ New & Improved

• Improved our reverse engineering capabilities on Snowflake, by including additional Snowflake-specific functions.
• dbt integration: increased the maximum dbt files size from 1MB to 100 MB.
• Improved the dbt integration by surfacing the mapping between tables and dbt models on the lineage graph.

• Improved the Slack connection experience and enabled the users to test it from our UI.

• Catalog: Improved the data preview feature by enabling the users to select all the fields to preview easily.

• Minor UX improvement on the connection page.

🛠 Fixes

• Fixed an issue on the search pagination where users needed to go back sometimes to the first page to preview the search results.

✨ New and Improved

• Sifflet is now integrated with dbt. More details here.
  You can now:
  • Centralise all your dbt tests run results with your Sifflet rules. You can also add ML-based rules to your monitoring coverage
  • Centralise all your catalog data in one place: search, description, tags etc.
  • Provide a full stack lineage view instead of the datawarehouse only
  • Leverage Sifflet alerting system to send notifications in case of run failure (via Slack, emails etc.)

• The table status is now visible on both the Catalog and Lineage views. Here to learn more about the table status.

✨ New and Improved

• The automatic rules can now predict on a more granular level, at the hourly level. More details here
• Added Refresh and Disconnect Button for Slack. More details here
• Added the possibility to customize your alert message in Slack/mail with a form, for each rule. It can be found in the rule creation page, for both automatic and custom rules.
• In the Integration page, you will now see new information for your datasources, such as the last time it was refreshed.

✨ New and Improved

• Improved Stability and Performance of Auto-Coverage: when there is a timeout, the loading button no longer loads indefinitely. The timeout limit has been increased to 5 min.
• Field-level lineage: more SQL queries are now supported to automatically map the field-level lineage
• Sifflet now supports Firebolt

🛠 Fixes

• Some minor bugs on some Automatic Rules for Snowflake and MSSQL