Lineage-aware AI with the Fabric item relations API (Preview)

PreviewSep 10, 2026VerifiedAdded Sep 22, 2026

With two new REST operations, you can retrieve the upstream and downstream relations of any Fabric item directly from your own code , the dependency graph behind the portal's lineage view, now available as a supported, programmable surface.

AI agents Streaming Governance Observability Developer tools

Read Microsoft's release notes

https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Lineage-aware-AI-with-the-Fabric-item-relations-API-Preview/ba-p/5366064

Summaries of vendors' own notes. Product names and logos belong to their owners; logos via logo.dev.

More Microsoft Fabric releases

Microsoft FabricSep 10, 2026

Accelerate JSON workloads with the Native Execution Engine in Microsoft Fabric

JSON is one of the most common formats in modern data platforms. It carries application events, API payloads, operational telemetry, configuration data, and the metadata that coordinates data-driven processes. For many organizations, JSON is not an edge case. It is part of the critical path from ingestion through transformation and analytics.

UpdateVector searchSQLStreamingSource

Microsoft FabricSep 9, 2026

Get ready for table discovery in OneLake Catalog search (Preview)

In late September, OneLake Catalog will begin surfacing tables as searchable objects in Microsoft Fabric. This change expands which table metadata users can discover based on their existing item permissions, so administrators may want to review the related tenant setting before rollout.

PreviewGovernanceSecurityPricingSource

Microsoft FabricSep 8, 2026

Advancing the Microsoft Fabric SQL Query Editor

The Microsoft Fabric SQL Query Editor is the home for web-based SQL development in Fabric. It gives developers a workspace to explore warehouse data, write and run SQL, among many more capabilities. That work rarely starts and ends with a single query.

UpdateSQLStreamingPerformanceSource

Microsoft FabricSep 14, 2026

Diagnose Fabric Data Warehouse workloads with the SQL DW operations skill (Generally Available)

When a warehouse slows down, the investigation usually starts with more questions than answers. Was there a capacity spike? Did a specific query suddenly become expensive? Are requests failing, being canceled, or simply taking longer than usual?

GASQLPricingObservabilitySource

Microsoft FabricSep 15, 2026

Moving off ODBC , A self-serve scanner for your ADBC migration

If your Fabric workspace connects to an ODBC driver, and you haven’t already moved to the ADBC driver, you’re on the ODBC → ADBC migration path. The migration window is already open , the sooner you start, the more room you have to validate.

UpdateSQLData integrationBISource

Microsoft FabricSep 17, 2026

Upcoming changes to legacy Teams and Outlook activities in Fabric Data Factory pipelines

Beginning October 30, 2026, users will no longer be able to add new legacy Teams or legacy Outlook activities to pipelines. These legacy activities will no longer appear as options when users add new activities to a pipeline. Existing legacy activity instances can still be edited and used in existing pipelines.

DeprecationData integrationSource

Microsoft FabricSep 17, 2026

Soft delete for On-premises data gateways in Microsoft Fabric (Preview)

Deleting a gateway is currently permanent, so administrators must recreate it if it is removed accidentally. With soft delete, supported gateways are retained for 30 days after deletion, giving authorized administrators time to restore them before permanent deletion.

PreviewSource

Microsoft FabricSep 17, 2026

Mirroring for Google BigQuery in Microsoft Fabric (Generally Available)

Mirroring for Google BigQuery in Microsoft Fabric is now generally available. For organizations running critical workloads on BigQuery, this means a simpler, faster, and lower-cost path to bringing your data into the rest of your analytics estate , with production support, an enterprise SLA, and no pipelines to build or maintain.

GASQLPricingData integrationSource

Also shipped on Sep 10, 2026

Google Cloud BigQuerySep 10, 2026

BigQuery conversational analytics adds ML.CORRELATION in preview

Conversational analytics can now use ML.CORRELATION to calculate statistical correlations between a target column and one or more metric columns in a table.

PreviewSQLSource

Google Cloud BigQuerySep 10, 2026

BigQuery ML.METRICS evaluates predictions without a stored model

The preview ML.METRICS function computes classification or regression evaluation metrics on any table or query with actual and predicted values, with no need to create or reference a stored model.

PreviewSQLGovernanceObservabilitySource

Google Cloud BigQuerySep 10, 2026

You can use the AI.CAUSAL_EFFECT function to quantify the impact of specific interventions on time series data

You can use the AI.CAUSAL_EFFECT function to quantify the impact of specific interventions on time series data. This feature is in Preview .

PreviewSource

Google Cloud BigQuerySep 10, 2026

BigQuery Data Engineering Agent integrates with BigQuery Graph

The Data Engineering Agent now uses BigQuery Graph for extra context between source and destination schemas, improving schema mapping accuracy in data engineering pipelines. It is generally available.

GAAI agentsSQLData integrationSource

Snowflake SnowflakeSep 10, 2026

Using dbt artifacts for Slim CI and defer to production in dbt Projects on Snowflake (General availability)

Slim CI, defer to production, failed-execution recovery, and concurrent execution are now generally available for dbt Projects on Snowflake. Reuse dbt artifacts from recent production executions to accelerate development, streamline CI/CD workflows, and recover from failed production runs without maintaining a separate artifact store.

GAStreamingSource

Snowflake SnowflakeSep 10, 2026

External secret providers (Preview)

External secret providers are now in preview. If your organization already keeps API keys, database passwords, and similar values in AWS Secrets Manager, Azure Key Vault, or Google Cloud Secret Manager, Snowflake can read those values when a query needs them, so you don't have to maintain a second copy in a Snowflake secret .

PreviewSQLSecurityDeveloper toolsSource