Microsoft Fabric

What shipped

• OneLake + ServiceNow zero-copy querying: OneLake in Microsoft Fabric makes a simple promise: provide a single, unified data foundation for analytics, AI, and BI. (17 Jun)
• AI-assisted Spark failure diagnosis: An AI-powered skill that turns Spark troubleshooting from a multi-tab investigation into a single natural-language command. (17 Jun)
• Faster Spark History Server loading: As Spark workloads scale in size and complexity, fast access to Spark application execution metrics and logs is essential for debugging, performance analysis, and operational confidence. (16 Jun)
• Fabric service-issue notifications: Fabric uses several message types to communicate service issues, depending on how an issue is detected and where the information is surfaced. (16 Jun)
• Faster Spark History Server loading: SAP systems sit at the center of many enterprises’ core business operations, powering processes across finance, supply chain, manufacturing, procurement, and HR. (16 Jun)
• SAP Copy job with Microsoft ABAP Add-On: As organizations scale their data and AI investments, many are adopting a multi-platform approach so teams can use the tools that best fit each project. (16 Jun)
• Azure Databricks and OneLake interoperability: As organizations scale their data and AI investments, they increasingly adopt a multi-platform approach, enabling teams to use the tools that best fit their needs. (16 Jun)
• Real-Time Dashboard upgrades: Discover a new way to build visuals in Real-Time Dashboards. The redesigned tile editing experience in Real-Time Dashboards brings AI-assisted authoring, a larger preview area, and more flexible workflows to… (11 Jun)
• Real-Time Dashboard upgrades: Time series analysis is at the heart of understanding how data behaves over time. (11 Jun)
• Real-Time Dashboard upgrades: Real-Time Dashboards in Microsoft Fabric help you monitor live data and react to changes as they happen. (11 Jun)
• Rayfin shareable sites: If you work alongside AI tools, your screen is probably full of markdown files. They’re fast to write, easy for an agent to read, and great for keeping a record. (11 Jun)

Why it matters

• OneLake + ServiceNow zero-copy querying: Operational workflow teams can query governed OneLake data in place rather than copying it into a separate ServiceNow store.
• AI-assisted Spark failure diagnosis: Spark debugging moves from manual log chasing to a natural-language troubleshooting flow.
• Faster Spark History Server loading: Snapshot-based loading makes large Spark job metrics usable much faster, especially for high-volume batch and streaming workloads.
• Fabric service-issue notifications: Better service-status surfacing gives admins earlier context when Fabric incidents affect workloads.
• Faster Spark History Server loading: Snapshot-based loading makes large Spark job metrics usable much faster, especially for high-volume batch and streaming workloads.
• SAP Copy job with Microsoft ABAP Add-On: Fabric Data Factory can extract large SAP datasets through a Microsoft ABAP add-on with less custom extraction infrastructure.
• Azure Databricks and OneLake interoperability: Databricks customers can work with OneLake as a shared data foundation, including Unity Catalog managed-table scenarios.
• Real-Time Dashboard upgrades: Dashboard creation and monitoring are getting more interactive, including AI-assisted tile editing, time-series visuals and live refresh.
• Real-Time Dashboard upgrades: Dashboard creation and monitoring are getting more interactive, including AI-assisted tile editing, time-series visuals and live refresh.
• Real-Time Dashboard upgrades: Dashboard creation and monitoring are getting more interactive, including AI-assisted tile editing, time-series visuals and live refresh.
• Rayfin shareable sites: Fabric-adjacent AI/markdown workflows gain a more shareable presentation layer.

How analytics teams could use it

• OneLake + ServiceNow zero-copy querying: Incident, field-service, supply-chain and AI-agent workflows can be enriched with analytics context while OneLake remains the shared foundation.
• AI-assisted Spark failure diagnosis: Data engineering teams can shorten triage loops for failed notebooks, pipelines and production Spark jobs.
• Faster Spark History Server loading: Platform teams can inspect executions, tune performance and support long-running jobs without waiting on huge event logs to render.
• Fabric service-issue notifications: Analytics teams can distinguish platform disruption from pipeline or model defects and communicate impact faster.
• Faster Spark History Server loading: Platform teams can inspect executions, tune performance and support long-running jobs without waiting on huge event logs to render.
• SAP Copy job with Microsoft ABAP Add-On: Finance, supply-chain, procurement and HR analytics can land SAP operational data into OneLake for reporting, enrichment and AI use cases.
• Azure Databricks and OneLake interoperability: Mixed Fabric/Databricks estates can reduce duplicated data and let teams use preferred engines against a more consistent governed layer.
• Real-Time Dashboard upgrades: Product and operations teams can build live monitoring surfaces for telemetry, customer behaviour and business KPIs with less hand-coded UI work.
• Real-Time Dashboard upgrades: Product and operations teams can build live monitoring surfaces for telemetry, customer behaviour and business KPIs with less hand-coded UI work.
• Real-Time Dashboard upgrades: Product and operations teams can build live monitoring surfaces for telemetry, customer behaviour and business KPIs with less hand-coded UI work.
• Rayfin shareable sites: Teams can package analysis outputs for stakeholders without turning every insight into a custom app or slide deck.

Editorial read

Fabric is continuing to push OneLake as the connective tissue: less copy-and-paste data engineering, more open-table interoperability, and more operational workflows that can consume governed analytical data directly. For teams building analytics products, the practical angle is to look for places where Fabric now removes a separate platform, manual troubleshooting step, or bespoke dashboard layer.