RLS not working in Fabric Plan, but works in the Power BI report
Hi, I have a semantic model in a Premium Capacity Workspace in Fabric where I'm just starting practicing how to build a Plan in Fabric. I created roles and assigned to users - I'm using my developer account and assigning to the users provided there -. The user Alex Wilber has Viewer role in the Workspace, is a member of the role for NA for RLS, and still can see all regions in the Plan, eventhough cannot see them in the Power BI report, there the RLS works just fine. Thanks in advance for your help! Cheers, FernandoFabric Plan writeback where dates and values have NULL
Hello, I finished my first exercise with Fabric Plan with a Planning Sheet where I forcasted 2026 based on the historical data from previous year in the semantic model with fake data, actually the semantic model demo provided by Lumel, called "transaction-dataset". I created a Fabric SQL Database and the corresponding connections to writeback the final Forecast. I clicked the Writeback button, finished, then went to the SQL Database and found the new table with data from the Forecast except for Year, Quarter, Month and Value, they all have NULL. Am I missing any configuration? Any help is greatly appreciated. Thanks, Fernando
Fabric Data Agent chat error: “The natural language query could not be processed” (Ontology source)
Hi all, I’m having a persistent issue with Fabric Data Agent when using an Ontology as the data source. In the chat, even very simple natural language questions fail with: “The request is invalid. The natural language query could not be processed. Please rephrase your query and try again.” RAID examples: db24d651-d4f8-4dd9-8fcb-bab105ee68eb, bfb8cd2a-676a-40a0-9c91-f36ca250ff07. What I already validated: Ontology and graph are created correctly. Relationships exist and are active. Manual graph queries execute successfully. The issue happens in chat NL queries (NL-to-GQL translation), even with minimal prompts. I recreated the Data Agent from scratch, same behavior. So this looks like a chat/NL parser issue rather than a data or graph execution issue. Has anyone found a reliable workaround, or is this a known service-side issue in preview? Any guidance from Microsoft team would be very helpful. Thanks!data agent can't get data from ontology data source
Hello! I created an entity type in an ontology and successfully added a binding. The data is visible on the entity’s Instances page. However, when I use “Build agent with AI” to ask very simple questions about this ontology, it consistently returns a response similar to the one shown in the attached screenshot, referring to a “table” or "schema" As far as I understand, an ontology does not have the concept of tables. Is my understanding incorrect? Do I need to select or configure an ontology table somewhere before the agent can query the data? In addition, when I use "Test data agent" to query the ontology data, the request hangs for several minutes and then returns an error.
Fabric Plan PowerTable sheet unable to connect to SQL DB
Hello, I'm having an issue with the new Plan item in Fabric. When I create a PowerTable and click on "Create a New App" I get this popup where I can select the connection and DB. The connection field is automatically populated and it is definitely an existing connection. Clicking "Connect" loads for a while but then throws an error saying "DTMS connection is deleted or not found". In the Stack Trace there is a mention about the tenant ID not matching the tid claim. I have tried this with multiple different browsers and accounts (accounts with just a single tenant) but the error remains the same. Any ideas what could be causing this? I checked the prerequisites for Plan and those are all OK. Thanks, Veikko
How should I organize a BI project using SharePoint lists and Sage sales files?
Hello , I'm a beginner in Power BI, and I would like to start a project using SharePoint list sources and Sage sales files. However, I’m not sure how to structure the project as it would be done in a company. For example, do you create a folder for each data source, a folder for reports, etc.? I would like to know the overall structure of a BI project and the best practices for implementing it.
Multi-Dimensional Planning Cube: "Pivot error: Hierarchy error: Input row hierarchy has no root node
Hi folks, I’m seeking for help to create a Multi-Dimensional Planning Cube. This is my setup: Adventure Works sample data storge in a Direct Lake Semantic Model Rows: 2 Dimensions from the Customer table Columns: Year, Quarter, Month column from the Calendar table Valus >measure „Gross Profit“ Please, take a look at my submitted screenshots to get a better idea of my setup. Anyway, I follow the instructions provided on https://learn.microsoft.com/en-us/fabric/iq/plan/planning-how-to-create-cube . Thus, I click: Insert Column > Number >Insert a new empty series Submit the title „Plan 2027“ Inserted as „Visual Measure“ Add a breakdown >make sure all dimensions are added >in this case market_en_name as well as product_en Click Create In every case I tried I also get the error "Pivot error: Hierarchy error: Input row hierarchy has no root node". Even though the message seems clear I don’t understand what I need to do with the row hierarchy. I tested: several dimensions a mix of dimensions Added [Driver Measure] !== BLANK in the Formular field >[Gross Profit] !== BLANK However, I always hit the same error. What’s wrong here? Can you help me? Thank you in advanced. Cheers, DomExcessive CU usage in Fabric IQ
I’m running a tiny PoC with Fabric IQ and hitting a bottleneck with capacity consumption. The setup is super simple: Capacity: F4 Data: 2 tables from Lakehouse. A "Sale" fact table with 2k rows and a "Salesperson" dimension with 25 records. Ontology: 2 nodes (Sale and Salesperson) and 1 property. Data agent: connected exclusively to the ontology. I asked the Data Agent exactly 10 questions, and my capacity went straight into background throttling. Looking at the metrics, 90% of the CUs were swallowed by GraphIndex (Graph General Operations). Is it normal for such a small dataset to trigger this much usage? Has anyone else seen this or found a way to optimize it? Attached the screenshot of the spike. Before: After 10 prompts: Any tips?
