Working with Microsoft Dataverse Connector in Power BI is usually straightforward—until you encounter a table that simply refuses to load any rows, even though the data clearly exists in the environment. This happens especially with hidden, virtual, or system-driven tables (e.g. msdyn_businessclosure, msdyn_scheduleboardsetting) which are commonly used in Field Service and Scheduling scenarios. Before jumping to a workaround, it’s important to understand why certain Dataverse tables don’t load in Power BI, what causes this behavior, and why the standard Dataverse connector may legitimately return zero rows. Causes – 1] The Table Is a Virtual or System Table with Restricted AccessSystem-managed Dataverse tables like msdyn_businessclosure are not exposed to the Dataverse connector because they support internal scheduling and platform functions. 2] No Records Exist in the Root Business Unit Data owned by child business units is not visible to Power BI accounts associated with a different BU, resulting in zero rows returned. 3] The Table Is Not Included in the Standard Dataverse Connector Some solution-driven or non-standard tables are omitted from the Dataverse connector’s supported list, so Power BI cannot load them. Solution: Export Dataverse Data Using Power Automate + Excel Sync Since Power BI can read:-> OneDrive-hosted files-> Excel files-> SharePoint-hosted spreadsheets …a suitable workaround is to extract the restricted Dataverse table into Excel using a scheduled (When the records are few) / Dataverse triggered (When there are many records and you only want a single one, to avoid pagination) Power Automate flow. What it can do –-> Power Automate can access system-driven tables.-> Excel files in SharePoint can be refreshed by Power BI Service.-> we can bypass connector restrictions entirely.-> The method works even if entities have hidden metadata or internal platform logic. This ensures:-> Consistent refresh cycles-> Full visibility of all table rows-> No dependency on Dataverse connector limitations Use case I needed to use the Business Closures table (Dataverse entity: msdyn_businessclosure) for a few calculations and visuals in a Power BI report. However, when I imported it through the Dataverse Connector, the table consistently showed zero records, even though the data was clearly present inside Dynamics 365. There are 2 reasons possible for this –1] It is a System/Platform Tablemsdyn_businessclosure is a system-managed scheduling table, and system tables are often hidden from external connectors, causing Power BI to return no data. 2] The Table Is Not Included in “Standard Tables” Exposed to Power BIMany internal Field Service and scheduling entities are excluded from the Dataverse connector’s metadata, so Power BI cannot retrieve their rows even if they exist. So here, we would fetch the records via “Listing” in Power automate and write to an excel file to bypass the limitations that hinder the exposure of that data; without compromising on user privileges, or system roles; we can also control or filter the rows being referred directly at source before reaching PBI Report. Automation steps – 1] Select a suitable trigger to fetch the rows of that entity (Recurring or Dataverse, whichever is suitable). 2] List the rows from the entity (Sort/Filter/Select/Expand as necessary). 3] Perform a specific logic (e.g. clearing the existing rows, etc.) on the excel file where the data would be written to. 4] For each row in the Dataverse entity, select a primary key (e.g. the GUID), provide the path to the particular excel file (e.g. SharePoint -> Location -> Document Library -> File Name -> Sheet or Table in the Excel File), & assign the dynamic values of each row to the columns in the excel file. 5] Once this is done, import it to the PBI Report by using suitable Power Query Logic in the Advanced Editor as follows – -> a) Loading an Excel File from SharePoint Using Web.Contents() – Source = Excel.Workbook(Web.Contents(“https://<domain>.sharepoint.com/sites/<Location>/Business%20Closures/msdyn_businessclosures.xlsx”),null,true), What this step does: -> Uses Web.Contents() to access an Excel file stored in SharePoint Online.-> The URL points directly to the Excel file msdyn_businessclosures.xlsx inside the SharePoint site.-> Excel.Workbook() then reads the file and returns a structured object containing:All sheets, Tables, Named ranges Parameters used: null → No custom options (e.g., column detection rules)true → Indicates the file has headers (first row contains column names) -> b) Extracting a Table Named “Table1” from the Workbook – msdyn_businessclosures_Sheet = Source{[Item=”Table1″, Kind=”Table”]}[Data], This would search inside the Source object (which includes all workbook elements), and look specifically for an element where: Item = “Table1” → the name of the table in the Excel fileKind = “Table” → ensures it selects a table, not a sheet with the same name & would extract only the Data portion of that table. As a result, we get Power Query table containing the exact contents of Table1 inside the Excel workbook, to which we can further apply our logic filter, clean, etc. To conclude, when Dataverse tables refuse to load through the Power BI Dataverse Connector—especially system-driven entities like msdyn_businessclosure—the issue is usually rooted in platform-level restrictions, connector limitations, or hidden metadata. Instead of modifying these constraints, offloading the data through Power Automate → Excel → Power BI provides a controlled, reliable, and connector-independent integration path. By automating the extraction of Dataverse rows into an Excel file stored in SharePoint or OneDrive, you ensure: This method is simple to build, stable to maintain, and flexible enough to adapt to any Dataverse table -whether standard, custom, or system-managed. For scenarios where Power BI needs insights from hidden or restricted Dataverse tables, this approach remains one of the most practical and dependable solutions. I Hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudFronts.com.

In modern enterprises, documents stored across platforms like SharePoint often remain underutilized due to the lack of intelligent search capabilities. What if your organization could automatically extract meaning from those documents—turning them into searchable vectors for advanced retrieval systems? That’s exactly what we’ve achieved by integrating Azure Logic Apps with Azure AI Search. Workflow Overview Whenever a user uploads a file to a designated SharePoint folder, a scheduled Azure Logic App is triggered to: Once stored, a scheduled Azure Cognitive Search Indexer kicks in. This indexer: Technologies / resources used: –-> SharePoint: A common document repository for enterprise users, ideal for collaborative uploads. -> Azure Logic Apps: Provides low-code automation to monitor SharePoint for changes and sync files to Blob Storage. It ensures a reliable, scheduled trigger mechanism with minimal overhead. -> Blob Storage: Serves as the staging ground where documents are centrally stored for indexing—cheaper and more scalable than relying solely on SharePoint connectors. -> Azure AI Search (Cognitive Search): The intelligence layer that runs a skillset pipeline to extract, transform, and vectorize the content, enabling semantic search, multimodal RAG (Retrieval Augmented Generation), and other AI-enhanced scenarios. Why Not Vectorize Directly from SharePoint? Reference:-1. https://learn.microsoft.com/en-us/azure/search/search-howto-index-sharepoint-online2. https://learn.microsoft.com/en-us/azure/search/search-howto-indexing-azure-blob-storage How to achieve this? Stage 1: – Logic App to sync Sharepoint files to blob Firstly, create a designated Sharepoint directory to upload the required documents for vectorization. Then create the logic app to replicate the files along with it’s format and properties to the associated blob storage – 1] Assign the site address and the directory name where the documents are uploaded in Sharepoint – In the trigger action “When an item is created or modified”. 2] Assign a recurrence frequency, start time and time zone to check/verify for new documents and keep the blob container updated. 3] Add an action component – “Get file content using path”; and dynamically provide the full path (includes file extension), from the trigger 4] Finally, add an action to create blobs in the designated container that would be vectorized – provide the storage acc. name, directory path, the name of blob (Select to dynamically get the file name with extension for the trigger), blob content (from the get file content action). 5] On successfully saving & running this logic app, either manually or on trigger, the files are replicated in it’s exact form to the blob storage. Stage 2 :- Azure AI Search resource to vectorize the files in blob storage In Azure Portal (Home – Microsoft Azure), search for Azure AI Search service, and provide the necessary details, based on your requirement select a pricing tier. Once resource is successfully created, select “Import & vectorize data” From the 2 options – RAG and Multimodal RAG Index, select the latter one.RAG combines a retriever (to fetch relevant documents) with a generative language model (to generate answers) using text-only data. Multimodal RAG extends the RAG architecture to include multiple data types such as text, images, tables, PDFs, diagrams, audio, or video. Workflow: Now follow the steps and provide the necessary details for the index creation Enable deletion tracking, to remove the records of deleted documents from the index Provide a document intelligence resource to enable OCR, and to get location metadata for multiple document types. Select image verbalization (to verbalize text in images) or multimodal embedding to vectorize the whole image. Assign the LLM model for generating the embeddings for the text/images provide an image output location, to store images extracted from the files Assign a schedule to refresh the indexer and to keep the search index up to date with new documents. Once successfully created, search keywords in the search explorer of the index, to verify the vectorization, the results are provided based on it’s relevance and score/distance, to the user’s search query. Let us test this index in Custom Copilot Agent , by importing this index as an azure ai search knowledge source. On fetching details of certain document specific information, the index is searched for the most appropriate information, and the result is rendered in readable format by generative AI.  We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

What is a SharePoint site? Sharepoint site is an application which is provided by Microsoft which can be used to store information and content. This may include documents, images videos, tasks, and so many things. For more details please follow the link Steps to create a site and integrate your SharePoint with D365 CRM Step 1: Log in to Office 365 login and open SharePoint. Step 2: Once you click on Sharepoint, go onto the Home icon and click on +Create site. Step 3: Click on Team site. My requirement is to track my project status and to share team resources and co-author content. So that’s why I select the Team site. Step 4: Enter your details for your new site and once done, click on Next. Step 5: You can also add specific members for your site(not necessary). Once done click on Finish. Step 6: Once you click on Finish, it will redirect it to your site which you created. Just copy the above link of your site which I highlighted. Just copy the link to your site. It will be used later. Step 7: Go into Dynamics 365 CRM and login in with your credentials OR mention your URL for e.g. abcde.crm.dynamics.com and then login. Once done, click on the ellipses(3 dots) and select Advanced Settings. Step 8: Drop down the Settings icon and click on Document Management. Step 9: Click on Enable Server-Based Sharepoint Integration. Step 10: In simple terms, what we are doing is integrating and validating the configuration of SharePoint. Click on Next. Step 11:  Select Online and then click on Next. Step 12: Enter the URL I previously asked to copy and paste(In Step 6). Paste that link here and click on Next. In the Next Step, it will validate that site. After that click on Finish and wait for 3-4 mins. Step 13: After Refreshing you will observe that Enable Server-Based Sharepoint Integration section has changed to One Note Integration. This means that your SharePoint has been enabled and what’s remaining is to add the entities which need to be stored in Sharepoint. Step 14: In Order to do that, click on Document Management Settings. Step 15: Select the entities which you want to enable for the Document Management System. Step 16: If you want a folder structure based on a certain entity you can check the option Based on entity and select the entity you want. Step 17: Click OK to continue. Step 18: FYI the status is showing me cancelled since I have already created the document management system for these selected entities previously. In your case, the status will show completed if you are doing it for the first time. Step 19: Go onto your SharePoint site and click on Site contents Step 20: Here you can view all the entities which were selected for the Document Management System. Hope this Helps!!!

I created a SharePoint site and was working on user permissions for a document library, I wanted to assign the Restricted View permission to a group but the permission was not visible. Below is the screenshot of the document library I created in my SharePoint and as you can see the Restricted View Permission is not available in the permission list. So how to make the permission available, the catch here is that it is only visible if there is a document uploaded in the document library (So you can upload a dummy document to your library and later delete it).  Hope this helps!

In this blog we’ll see how to integrate SharePoint with Dynamics 365. Step 1- Configure SharePoint Option in Dynamics 365 Document Management option. Go to Advanced settings -> Document Management. Step 2- In Document Management select “Enable Server-based SharePoint Integration” Step 3- Now in the pop-up screen provide SharePoint site location as “Online” then proceed to next. Step 4- Now provide a valid SharePoint URL and click on finish. Step 5- Enable Share point Document setting for Entities using Document Management Settings. Step 6- Now in the Pop-up screen select the entities that you want to use to manage SharePoint documents. You will find some entities like Account are already Enabled and if you want you can enable other entities. We can also add custom entities if required. Step 7- Check Based on entity, document libraries and folders that are based on Account entity are automatically created on SharePoint site. Step 8- We can store a document for an Account or for any other entity in SharePoint. Open an Account and click on Related tab to choose Document option. Hope this helps!!

Use case – we wanted to retrieve attachment when new email arrives in outlook and create same file in SharePoint Let see how we can achieve this! Step 1 – Flow triggers on when a new email arrives trigger from Outlook connection. Step 2 – Retrieve attachments and Create file in SharePoint. Add step create file from SharePoint connection. In Create file, Add site address, Folder path, File name, File Content. Here file Content is the Attachment content from Trigger and File Name should be Attachment name. Save the flow and try. Hope this helps!