warehouse
301 TopicsFabric Warehouse as source in MS Access
Hi All, I have a client that is still using an Access application for some very specific modules. We recently migrated the on-prem database to Fabric & now some of the connections of that Access application needs to change to the Fabric Warehouse. Using the ODBC driver, this seems to work, the only issue is that it looks like the user that is using the application has to have "VIEWER" access on the workspace, otherwise the connection cannot be successfully performed. We've tried by removing the viewer access, and giving granualar connect + readData permission on the specific warehouse, but this throws a connection error (even before we can select a warehouse). It seems like it needs to have "connect" permissions on the "server". Does anyone have experience with this set-up? Best practices? Service principal,... doesn't seem an option at first sight. Thanks !64Views0likes5CommentsHow to know Warehouse name on Query Window (SMSS)
Hi, I am using SSMS to connect Fabric WH. I have created server registrations to have friendly names, but even with that I have a problem when opening multiple query windows against different WH. Every window is connected to a different WH but the only way to distinguish it is checking the wonderful String ID shown on the right bottom bar. Unfortunately the friendly name used to regisyter the server does not appear here. Any idea about how to distinguish easily which WH corresponds to every opened query window? Thx105Views1like7CommentsHow are you detecting drift between Fabric environments?
How do you know that what’s running in PROD is actually the same version that passed through DEV and UAT? That’s a problem I’ve been exploring recently in Microsoft Fabric. I built a Warehouse Drift Detection solution that compares SQL objects and their definitions across: DEV → UAT → PREPROD → PROD It identifies scenarios such as: objects that haven’t been promoted; objects missing from an environment; definitions that differ between environments; PROD differing from DEV/UAT; potential direct changes in an individual environment. It also maintains comparison history and, where definitions differ, shows the actual SQL differences. The idea is simple: Make it easy to see where Fabric Warehouse environments have diverged and understand exactly what changed. I thought I’d share the approach here as this is probably a challenge other teams working with multiple Fabric environments encounter as well. How are you currently handling environment drift in Microsoft Fabric?32Views2likes2CommentsTrasaction deadlocked on lock resources
Hi, I created a Dataflow Gen2 in Microsoft Fabric that loads multiple tables into a warehouse. Every time I run the dataflow, I receive the following error message: Couldn't refresh the entity because of an issue with the mashup document MashupException.Error: Microsoft SQL: Transaction (Process ID 206) was deadlocked on lock resources with another process and has been chosen as the deadlock victim. Rerun the transaction. Details: Reason = DataSource.Error;ErrorCode = 10478;DataSourceKind = Warehouse;DataSourcePath = Warehouse;DataSourceKind.2 = SQL;DataSourcePath.2 = qenzxdde3pdenc5pgrl56uss44-3nktrgkfckbedi5tclkxsvoogi.datawarehouse.fabric.microsoft.com;WH_Bronce;Message = Transaction (Process ID 206) was deadlocked on lock resources with another process and has been chosen as the deadlock victim. Rerun the transaction.;ErrorCode = -2146232060;Number = 1205;Class = 13;State = 51;ConnectionId = 090e3c20-db6d-492b-b2a6-48814400d26f;Microsoft.Data.Mashup.Error.Context = User GatewayObjectId: 714e5a6b-cca0-4a5a-bb6b-7c891e9991ba". Código de error: 104100. (Id. de solicitud: 4926601a-0aa6-4cdf-86d4-e84f3cbd1767). Any idea what it might be? Thank you in advance.73Views0likes6CommentsLakeHouse SQL Endpoint connection disruptions
Hello, Since a couple of weeks, we are constantly experiencing the connection issue to the SQL Endpoint our Lakehouses whenever we try to run the Python code on a local computer. we always have to try to establish the connection to the SQL Endpoint by running a query in Fabric or trying to connect to another on-premisses database, before being able to running any code (multiple times a day), but still the issue persist and we would have to do this multiple times for it to start working. Are there any disruptions on the SQL Endpoint connections? Regards, Benjamin T70Views0likes4CommentsWarehouse SCD Type 2 loads: MERGE or INSERT/UPDATE pattern for large dimensions?
Hi everyone, I am designing a Type 2 slowly changing dimension load in a Fabric Warehouse for a dimension with a few million rows. Two options on the table: A single MERGE that closes changed rows and inserts new versions. Two statements: an UPDATE that closes the current row for changed keys, followed by an INSERT of the new versions. A sketch of the two-statement version: UPDATE d SET d.valid_to = SYSUTCDATETIME(), d.is_current = 0 FROM dbo.dim_customer AS d JOIN stg.customer AS s ON s.customer_id = d.customer_id WHERE d.is_current = 1 AND s.row_hash <> d.row_hash; INSERT INTO dbo.dim_customer (customer_id, name, row_hash, valid_from, valid_to, is_current) SELECT s.customer_id, s.name, s.row_hash, SYSUTCDATETIME(), NULL, 1 FROM stg.customer AS s LEFT JOIN dbo.dim_customer AS d ON d.customer_id = s.customer_id AND d.is_current = 1 WHERE d.customer_id IS NULL OR d.row_hash <> s.row_hash; Questions: Is MERGE considered reliable enough in the Warehouse for SCD2, or do people prefer the explicit two-step approach? How do you wrap the two statements so a failure between them does not leave the dimension half updated? Any guidance on small file and compaction concerns when the table is updated frequently? Thanks in advance.Solved26Views0likes3CommentsMicrosoft Fabric – Unifying Data: The Lakehouse Revolution NDAC Event
NextGen Data Aspirants Community (NDAC) is excited to bring you another knowledge-packed session exploring the evolution of modern data platforms and how Microsoft Fabric is transforming the way organizations unify, manage, and analyze data. 🎯 Session Topic: Microsoft Fabric – Unifying Data: The Lakehouse Revolution 👨🏫 Speaker: Maureen Direro, Cloud, Data and AI Specialist Technical Trainer 📅 Date: 7 November 2026 (Saturday) ⏰ Time: 06:00 PM IST 🌐 Mode: Online ⏱ Duration: 1 Hour 🔗 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰: • Meetup: https://www.meetup.com/nextgen-data-aspirants-community/events/317201597/?utm_medium=referral&utm_campaign=share-btn_savedevents_share_modal&utm_source=link&utm_version=v2&member_id=471647775 • YoutTube Live: https://www.youtube.com/live/OZroGX48KC0?si=ACQrcKQyBBdEIFqv In this session, you’ll learn how to: ✅ Understand the evolution of modern data architectures and the Lakehouse concept ✅ Explore the fundamentals of Lakehouse architecture in Microsoft Fabric ✅ Understand how OneLake brings data together through a unified storage layer ✅ Explore how Delta Lake enables reliable and scalable data management ✅ Compare Lakehouse and Data Warehouse architectures in Microsoft Fabric ✅ Understand how different Fabric workloads work together with the LakehouseFabric Community Engineering Call - November 2026
🚀 We're invited: Fabric Community Engineering Call Our user group has been invited to join the Fabric community engineering call, and we'd love to have you there with us. It's a chance to hear what's happening, ask questions, and connect with the wider Fabric community. 📅 When: Thursday, November 19, 2026 - 9:00 AM to 10:00 AM PDT 📍 Where: Online 🎤 Speakers: Yoav Dobrin & Sandeep Pawar ✨Topic: Deployment Plans: Control What Happens and When, including sequencing deployment and actions consistently across Git, APIs, and deployment pipelines, plus configuring Fabric data agents for conversational analytics 🔗 RSVP on Meetup: https://www.meetup.com/microsoft-fabric-credit-unions-group/ Not on Meetup yet? We're using it to share the details and keep track of who's joining. Click the link, create a free account, join our group, and RSVP. It takes about a minute, and you'll get invites to our future sessions too. Hope to (virtually) see you there! 👋27Views0likes0CommentsItem Reference variable not saved on Lakehouse shortcut Target Item
Hello everyone, I have a workspace with a Lakehouse called Test_LH. Test_LH contains a schema shortcut to a warehouse called TEST_WH which is in a different workspace. I have a library variable that contains an Item Reference to TEST_WH. When i press manage shortcut on my schema shortcut inside Test_LH, and then press 'Edit Target' -> 'Target Item', and then select my library varialbe that contains an item Reference to TEST_WH, the selection does not save. Now, if i press manage shortcut again, it will show that the Target Item is TEST_WH, rather than the library variable. I have pressed "Update all variables" but this has not fixed the issue. Here are some things I have tried Logging out of Fabric, closing all my tabs and logging in again. Double checked to ensure that my item reference was correct I am not sure why It will not show the Target Item to be my variable after selecting it. Thanks, ASolved89Views0likes4CommentsNear-real-time CDC into Fabric Warehouse: MERGE vs Mirroring vs Lakehouse?
Hi all, I need operational data from an Azure SQL Database available in Fabric for reporting with roughly 5 to 15 minutes of latency. There are about 30 tables, mostly updates, with some deletes. Business users will query it in T-SQL and Power BI. I see three main approaches and would like to understand the trade-offs: Mirroring the source database into Fabric, then building curated tables in a Warehouse on top of it Incremental MERGE into Warehouse tables from a pipeline or copy job that reads changed rows (CDC or a watermark column) Eventstream CDC → Lakehouse Delta tables, queried through the SQL analytics endpoint Questions: Which approach is recommended at this latency and scale, and where does each one break down? How are deletes handled in each? Mirroring is the most direct, but what about MERGE-based loads? How much does running MERGE frequently cost on a Warehouse (capacity usage, small-file or fragmentation effects)? If you mirror, is it better to build curated tables in a Warehouse or use views over the mirrored database? Thanks!Solved146Views1like8Comments