Release: Domain-Based Access Control, Automated Field-Level Lineage: Coverage Improvement on Bigquery and Snowflake, Get a More Granular Understanding of Your Data Pipelines Health With Tag-Based Dashboard Filtering, Data Quality As Code Supporting Continuous Scan

✨ Feature Highlights

Domain-Based Access Control

We are introducing domain-based access control to offer more flexibility when defining users permissions associated to multiple domains. For example, a user can now be a viewer (with a viewer role permissions) in Domain A, and editor (with an editor role permissions) in Domain B.
Learn more about it in the Access Control documentation page.

Automated Field-Level Lineage: Coverage Improvement on Bigquery and Snowflake

Sifflet’s automated field-level lineage supports temporary tables and incremental pipelines on Snowflake. We have also extended the support for BigQuery-specific SQL dialect, resulting in a higher coverage for all the transformations happening within BigQuery.

Get a More Granular Understanding of Your Data Pipelines Health With Tag-Based Dashboard Filtering

You can now filter the entire content of your dashboard (data assets, monitors, incidents, etc.) by any of your tags. This makes it easy for you to tailor this bird's eye view of your Sifflet account to specific data products, teams, and more.

Thanks to dashboard filtering, you can now:

Get a high level understanding of the monitoring coverage and overall health of data pipelines associated with a specific data product
Check out configuration improvement suggestions for your team's monitors
Analyse the incidents that occurred on a specific environment over the past months

Data Quality As Code Supporting Continuous Scan

We've added support for continuous scan in Data Quality as code monitors.

continuousScan: Boolean       # (optional - default false) Enable continuous scan

App version: v207