✨ New & Improved

• Roles permissions update: We have restricted the access to the sources secrets to Admin roles only. As of now, accounts with the Editor role can no longer see the secrets.
• Lineage improvement: We have improved our field-level lineage engines on Snowflake and BigQuery to cover additional use cases.
• ML-based monitoring sensitivity: we have improved the behaviour of our ML models when setting the sensitivity parameter to low

🛠 Fixes

• Fixed Redshift memory ingestion issues
• Fixed a bug on some rules running on Snowflake

✨ New & Improved

• New monitoring page: We have redesigned our monitoring page to surface more insights from the list view of the existing data quality rules and improve the user experience when interacting with them.

🛠 Fixes

• Fixed ingestion issues that can be encountered with BigQuery and Looker integrations.

✨ New & Improved

• New navigation bar: Sub-menu will replace the existing tabs for a better UX
• Redshift's ingestion limitation: ingestion time reduced by at least 5 times

🛠 Fixes

• Fixed several bugs around ingestion jobs for BigQuery, dbt

✨ New & Improved

• QuickSight integration: you can now integrate and visualise your dashboards on Quicksight
• Datasource Timezone 🕛: you can now precise the timezone of your datasources
• Display Timezone 🕛: you can now choose which timezone you wish to see all data on Sifflet's UI
• Improved dbt integration: Sifflet can now ingest dbt artifacts when not generated in the right order
• Incidents:
  • Page loading time optimised
  • Timeline tab has been moved to the Overview tab
• Catalog: added a Reset button to clear more easily your filter

🛠 Fixes

• Fixed a bug where data assets with long names will not display properly on some cases
• Fixed a bug where data were not pulled correctly from BigQuery on some cases
• Fixed a bug where a Completeness rule could not run on some edge cases (with qualifications)

✨ New & Improved

• LookML repository SSH and token connection. You can now connect to your LookML repository using both SSH or a token
• New Rule status "Requires your attention": this new status will appear when there is an issue in your rule setup that requires your attention. For instance, running a rule requiring a date column on a table that doesn't have one will result in this status.
• Freshness rule new graph: Freshness graph is now different than the completeness graph and provides clearer information

🛠 Fixes

• Fixed a bug where the graph will not show while using the multi dimension analysis (group by) in some edge cases

✨ New & Improved

• Dashboard page revamp: Our dashboard page comes now with deeper insights and a more personalized experience for the user.
• Pinning: Users can now pin their most useful data assets, data quality rules, or incidents and easily navigate to them from the My summary page on the dashboard.
• "Assigned to" Filter in Incidents page: Users have an additional filter "Assigned to" which allow to filter your incidents on certain users
• 7 latest rule run Status: you can now see the 7 latest run status for each rule instead of the last one

🛠 Fixes

• Fixed a bug where rules will result in a technical error in few instances
• Fixed an issue where the role 'Viewer' was missing some access rights (e.g. access to the failing rows of a rule)

✨ New & Improved

• ML-rules data querying optimisation: Sifflet now optimises the data sources querying for the models training in your datasource by querying only the new data ingested since the last rule execution

🛠 Fixes

• Fixed an issue where rules ran with technical errors in a few instances
• Fixed an issue where the rule schedule will sometimes not update

✨ New & Improved

• Power BI integration (Beta): Supporting Microsoft Power BI as a bi integration. Sifflet will be able to catalog dashboards, tiles, and datasets as well as full lineage to the actual datasources.

• Bigquery integration test : advanced testing to make sure that Sifflet and Bigquery are properly configured.

• Dataset selector optimization : improved user experience for the dataset selector used in both filters and quality rule creation stepper.

• Metadata pulling optimization: performance optimization for the jobs pulling metadata from sources.

🛠 Fixes

• Graph misinterpretation when min, max, and predicted value are the same.
• Fixing the preview issue when trying to sample a Snowflake table.
• Display a comprehensive message when a multi-dimension rule fails because of a high dimension cardinality.

✨ New & Improved

• Multi-dimensional monitoring (Beta): Users can now monitor their data assets at a more granular level by breaking down the monitoring based on any dimensional/low-cardinality fields.
  This type of monitoring can be applied to any data quality template.
• Multiple UX improvements: including a better UX when deploying new versions of the product and a redesign of notifications cards and an improvement of the data quality rules monitoring page.

🛠 Fixes

• Fixed a bug on the catalog search preventing from considering the tags filter.

✨ New & Improved

• Multi-schema/datasets integration: Users can simultaneously integrate Sifflet to multiple schemas (and datasets in the case of BigQuery) of the same data source.
• Data quality rules batch editing users can simultaneously batch edit schedules, descriptions, tags, and alert destinations for multiple rules.
• Auto-coverage rules frequency: Users can now schedule Auto-coverage suggested rules with cron expressions.

🛠 Fixes

• Fixed bugs preventing the run of ML-based rules in some specific circumstances.