Weekly Databricks

What shipped

• Genie and AI/BI experiences: Share chats with account users : You can now share Genie One chats with all users in your account as read-only. (25 Jun)
• Genie and AI/BI experiences: Genie Code space authoring skills : Genie Code now includes dedicated skills for authoring and maintaining Genie Spaces. (25 Jun)
• Dashboard enhancements and bug fixes: Dynamic annotation lines : Annotation lines can now be driven by data or a calculation instead of a fixed value, letting you show running averages, variable thresholds, or anomaly markers that update with… (25 Jun)
• Genie and AI/BI experiences: Genie Spaces is being renamed to Genie Agents. In early July 2026, Genie Spaces is renamed to Genie Agents to better reflect the full capabilities of this feature. (24 Jun)
• Genie and AI/BI experiences: In July 2026, Unity AI Gateway budgets will be generally available for all accounts on AWS, Azure, and Google Cloud. (23 Jun)
• Change the owner of standalone pipeline streaming tables and materialized views: You can now use ALTER STREAMING TABLE and ALTER MATERIALIZED VIEW with SET OWNER TO to change the owner of streaming tables and materialized views backed by standalone pipelines created in Databricks SQL. (23 Jun)
• Standalone pipeline materialized views support expectations: You can now add data quality expectations to materialized views created in Databricks SQL using the CONSTRAINT expectation_name EXPECT (expectation_expr) clause. (23 Jun)
• Governance and compliance controls: Data Classification is now available by default for workspaces with the compliance security profile enabled, and either HIPAA controls or no specific compliance standard selected. (23 Jun)
• Block specific internet destinations in network policies: You can now block internet destinations from serverless workloads through the network policies REST API. (23 Jun)
• Lakeflow pipeline operations: The Square connector in Lakeflow Connect is now available in Beta. The connector ingests point-of-sale data such as payments, orders, customers, catalog items, and inventory from Square into Azure Databricks. (22 Jun)
• Lakeflow pipeline operations: The Wiz Audit Logs connector in Lakeflow Connect is now available in Beta. The connector allows you to ingest audit log entries, issues, and vulnerability findings from Wiz into Azure Databricks. (22 Jun)
• Genie and AI/BI experiences: The Genie Code system table ( system.access.assistant_events ) now records only user-submitted Genie Code interactions, such as side-panel chat, agent mode, and the inline assistant ( %assistant ). (22 Jun)

Why it matters

• Genie and AI/BI experiences: Databricks is expanding conversational analytics and workspace-native AI experiences for business users.
• Genie and AI/BI experiences: Databricks is expanding conversational analytics and workspace-native AI experiences for business users.
• Dashboard enhancements and bug fixes: Dynamic annotation lines : Annotation lines can now be driven by data or a calculation instead of a fixed value, letting you show running averages, variable thresholds, or anomaly markers that update with your data.
• Genie and AI/BI experiences: Databricks is expanding conversational analytics and workspace-native AI experiences for business users.
• Genie and AI/BI experiences: Databricks is expanding conversational analytics and workspace-native AI experiences for business users.
• Change the owner of standalone pipeline streaming tables and materialized views: You can now use ALTER STREAMING TABLE and ALTER MATERIALIZED VIEW with SET OWNER TO to change the owner of streaming tables and materialized views backed by standalone pipelines created in Databricks SQL.
• Standalone pipeline materialized views support expectations: You can now add data quality expectations to materialized views created in Databricks SQL using the CONSTRAINT expectation_name EXPECT (expectation_expr) clause.
• Governance and compliance controls: The platform is tightening controls around sensitive metadata, audit trails and compliance-profile behaviour.
• Block specific internet destinations in network policies: You can now block internet destinations from serverless workloads through the network policies REST API. Blocked destinations are enforced regardless of the policy's network access mode. See Block internet destinations .
• Lakeflow pipeline operations: Lakeflow updates continue the push toward lower-friction data engineering and managed pipeline design.
• Lakeflow pipeline operations: Lakeflow updates continue the push toward lower-friction data engineering and managed pipeline design.
• Genie and AI/BI experiences: Databricks is expanding conversational analytics and workspace-native AI experiences for business users.

How data teams could use it

• Genie and AI/BI experiences: Analytics teams can test where Genie reduces ad hoc report queues while keeping governed metrics and permissions in place.
• Genie and AI/BI experiences: Analytics teams can test where Genie reduces ad hoc report queues while keeping governed metrics and permissions in place.
• Dashboard enhancements and bug fixes: Assess whether it affects platform governance, data engineering productivity, AI/BI adoption, sharing controls or workspace operations.
• Genie and AI/BI experiences: Analytics teams can test where Genie reduces ad hoc report queues while keeping governed metrics and permissions in place.
• Genie and AI/BI experiences: Analytics teams can test where Genie reduces ad hoc report queues while keeping governed metrics and permissions in place.
• Change the owner of standalone pipeline streaming tables and materialized views: Assess whether it affects platform governance, data engineering productivity, AI/BI adoption, sharing controls or workspace operations.
• Standalone pipeline materialized views support expectations: Assess whether it affects platform governance, data engineering productivity, AI/BI adoption, sharing controls or workspace operations.
• Governance and compliance controls: Security teams should check whether monitoring, troubleshooting or audit workflows need adjusting as redaction and compliance defaults change.
• Block specific internet destinations in network policies: Assess whether it affects platform governance, data engineering productivity, AI/BI adoption, sharing controls or workspace operations.
• Lakeflow pipeline operations: Data teams can assess whether visual design, compliance-profile support or GA readiness changes the build-vs-code path for new pipelines.
• Lakeflow pipeline operations: Data teams can assess whether visual design, compliance-profile support or GA readiness changes the build-vs-code path for new pipelines.
• Genie and AI/BI experiences: Analytics teams can test where Genie reduces ad hoc report queues while keeping governed metrics and permissions in place.

Editorial read

Databricks is continuing to package the lakehouse as an operating layer for data products: more AI/BI entry points for business users, more managed pipeline tooling for engineers, and more governance around sharing, audit data and external access. The practical theme is adoption with controls: turn on the useful productivity features, but pair them with app governance, metric ownership and security review.