Copy job for SAP with ABAP Add-On in Microsoft Fabric (Preview)
SAP systems sit at the center of many enterprises’ core business operations, powering processes across finance, supply chain, manufacturing, procurement, and HR. That makes SAP data some of the most business-critical data in the enterprise. As organizations modernize their analytics and AI platforms, bringing SAP data together with the rest of the enterprise data estate has become increasingly important. But moving SAP data at enterprise scale has historically been difficult. SAP landscapes are complex, data volumes are large, and extraction architectures often require specialized frameworks, custom code, and additional operational layers. For many organizations, this creates friction between where their most important operational data lives and where they want to analyze, enrich, and activate it. We are delivering the next step of our SAP roadmap: Copy job for SAP with ABAP Add-On in Microsoft, this new capability complements offerings like: SAP Business Data Cloud Connect was announced in SAP and Microsoft accelerate business insights and AI innovation with SAP Business Data Cloud Connect for Microsoft Fabric and will be available over the coming months). It will enable bi-directional zero-copy sharing between SAP Business Data Cloud and Microsoft Fabric without the need for data movement. Mirroring via SAP Datasphere, a turnkey data replication capability providing scalable near real-time data movement from SAP sources into Fabric OneLake (Generally Available). To learn more, refer to the Fabric mirroring documentation. Now, organizations can extract large volumes of SAP data through Copy job, reduce the need for external extraction frameworks, and build a scalable path from initial ingestion to ongoing incremental updates. Copy job provides a configuration driven experience for moving data across clouds, applications and on-premises systems – designed to support high-scale, multi-cloud data movement for petabyte-scale ingestion scenarios. Copy job helps bring data into OneLake as part of a unified, governed foundation for analytics and AI. High-performance SAP extraction with Copy job and Microsoft ABAP add-on integration This new integration option enables scalable, high-throughput extraction from SAP systems, making it easier than ever to bring large volumes of SAP data into Microsoft Fabric for analytics, reporting, and AI. Figure: High-level architecture diagram of Copy job with ABAP Add-on. Broad data coverage across SAP Systems Extracting data from SAP systems at scale can be complex and resource intensive. This new capability simplifies the process while delivering high performance. The solution runs directly inside SAP using a Microsoft-provided ABAP Add-On. Data is extracted at the application layer and transferred efficiently through Copy Job in Fabric Data Factory. This removes the need for complex external extraction frameworks and reduces operational overhead. It supports a wide range of SAP data sources. You can extract from SAP tables, views, and ABAP CDS views, including semantically rich models used for analytics. The capability works across both SAP ECC and SAP S/4HANA, whether deployed on-premises or in the cloud. Providing consistent access to both raw operational data and business-ready data models. Flexible data delivery styles for real-world SAP scenarios Through the integration with Copy Job, the solution handles data movement at scale. The integration is designed for high throughput and efficient processing of large datasets. Parallel execution capabilities help accelerate ingestion and reduce data transfer times. The solution supports different loading strategies depending on your needs. You can perform full snapshots for initial ingestion or bulk replication scenarios. For ongoing updates, incremental loads can be configured using watermark-based extraction. This allows you to process only the data that has changed. Together, these capabilities make it easier to design efficient pipelines. You can start with a large initial load and then transition seamlessly to incremental updates, without changing the overall architecture. SAP data in OneLake, ready for analytics and AI After ingestion, SAP data is immediately available in Microsoft OneLake. From there, it can be used across the entire Fabric platform. You can build Power BI reports directly on SAP data and operational datasets. You can run large-scale analytics workloads or combine SAP data with non-SAP sources from across your organization creating a unified data foundation without silos. With all data in one place, it also becomes easier to enable AI-driven scenarios. Applications and data agents can access consistent, trusted business data to generate insights and drive automation. Get started For more information, refer to the ABAP Add-On for SAP data extraction with Copy Job in Microsoft Fabric documentation. You can start exploring this capability today to: Accelerate SAP data ingestion Simplify data extraction architectures Enable scalable analytics and AI scenarios Looking ahead Copy job for SAP with Microsoft ABAP Add-On is another step in our continued investment in SAP data integration for Microsoft Fabric. SAP is one of the most important enterprise data sources for our customers, and Data Factory in Fabric is designed to help organizations bring SAP and non-SAP data together through scalable, flexible data movement experiences. With Copy job, customers can move data across clouds, applications, and on-premises systems into OneLake. With the Microsoft provided ABAP Add-On, that same Copy job experience now extends more deeply into SAP, helping customers bring business-critical SAP data into Fabric for analytics, reporting, and AI. We will continue expanding SAP data integration capabilities across Microsoft Fabric so customers can simplify their data architectures, reduce silos, and build a unified, governed foundation for enterprise analytics and AI.
Ability to delete system restore points in the data warehouse
Since the restore points count towards consumed (and billable) storage: "The creation of both system-created and user-defined restore points consume storage. The storage cost of restore points in OneLake includes the data files stored in parquet format. There are no storage charges incurred during the process of restore." we would like to be able to delete restore points. The current reasoning behind this option not being available is to meet the SLAs. I don't see it as valid reason as by deleting a restore point we acknowledge that meeting the recovery SLA is affected. We would like to be able to choose between paying for storage or having ability to restore a state from the past.Allow Custom URLs for Fabric Apps
Fabric Apps are awesome, but I can't see many executives clicking a link that lives at: moist-sausage-a47cb6849-webapp.fabricapps.net Please allow custom domains / friendly URLs for Fabric Apps. A polished option would go a long way towards improving trust, adoption, and making apps feel production-ready
Improve Fabric Trial Eligibility Transparency and Learning Access
Show the exact reason why a Fabric trial is blocked. Clearly document all eligibility requirements (including any tenant-age restrictions for new tenants ). Provide a retry date or condition when a user becomes eligible. Add a free Microsoft Learn/Fabric sandbox for DP-700 hands-on labs. Enable independent learners to practice Fabric without requiring an organization or paid capacity.
Improve Connection Discovery and Reuse Across Fabric Experiences
Description: Enhance the Fabric user experience by displaying all available and accessible connections in a consistent drop-down list across Dataflow Gen2, Notebooks, and other Fabric workloads. This would allow users to easily discover and reuse existing connections instead of recreating them, resulting in a more intuitive and streamlined onboarding experience. Benefits: Simplifies connection management and improves user experience. Reduces duplicate connection creation and accelerates onboarding to Fabric.
Keep Fabric SQL Endpoint Up to Date
When data is updated in a Fabric Data Warehouse or Lakehouse, it's not always up to date immediately when querying the SQL Endpoint. The same thing happens in a Fabric SQL Database but this is even more noticeable - on the SQL Database object, the data is always up to date, but on the SQL Endpoint object of the same database, the data can lag. It is possible to refresh this as part of a pipeline by including the refresh SQL endpoint activity, but in my view the data should always be up to date through the endpoint as this can lead to discrepancies.Support Microsoft Customer Agreement (MCA) Accounts in the Power BI Cost Management Template App
Many customers are now migrating from Enterprise Agreements (EA) to Microsoft Customer Agreements (MCA). While the Azure Cost Management connector in Power BI Desktop supports MCA accounts, the Power BI Cost Management Template App currently supports only EA accounts and cannot be used after an MCA migration. As a result, customers must manually recreate the data model, schema, reports, and dashboards that were previously available through the template app. This adds significant effort and reduces the out-of-the-box reporting experience that customers have come to rely on. It would be highly valuable if support for MCA accounts could be added to the Power BI Cost Management Template App in a future release. Enabling MCA compatibility would provide a more seamless transition for customers migrating from EA to MCA and help preserve the reporting capabilities and user experience currently offered by the template app. We appreciate your consideration of this enhancement request and believe it would benefit many customers adopting MCA billing agreements.Allow per-user/per-session control over Copilot Complete in Fabric Notebooks and SQL Endpoints
When reviewing or making systematic changes across large SQL scripts, I often pause while reading code, verifying logic, or planning the next edit. With Copilot Completions enabled in Fabric SQL Endpoints (and similarly in Notebooks), these pauses are frequently interpreted as uncertainty, causing Copilot to inject suggested code completions. The suggestion overlay changes the visual layout of the editor, interrupts reading flow, and requires manual dismissal (for example, pressing Esc). For coding sessions this can be helpful, but during code review, proof-reading, refactoring, or bulk editing activities it becomes disruptive. Each interruption breaks concentration, causes me to lose my place in the code, and increases the likelihood of mistakes. Tasks that are straightforward in other tools such as SQL Server Management Studio can therefore take significantly longer. Currently, Copilot Completions can be enabled or disabled at the tenant or warehouse level. While it is possible to disable the feature entirely for a warehouse, that affects every user and removes the benefit for colleagues who want to keep it enabled. Suggested enhancement Allow Copilot Completions to be disabled at a more granular level, for example: Per user (personal preference) Per session Per notebook / editor window This would allow users to choose the most appropriate experience for the task at hand without impacting other users in the same workspace or warehouse. The default state would still be inherited from tenant settings, but overridable by the user as needed. Benefits Improved focus for code review and refactoring tasks Reduced interruption during deep work Lower risk of editing mistakes caused by loss of context Greater flexibility without removing Copilot value for users who want suggestions enabled
