Capacity Template v2 with Microsoft Fabric
1. Capacity Scenario One of the most common scenarios for Microsoft Graph Data Connect (MGDC) for SharePoint is Capacity. This scenario focuses on identifying which sites and files are using the most storage, along with understanding the distribution of these large sites and files by properties like type and age. The MGDC datasets for this scenario are SharePoint Sites and SharePoint Files. If you’re not familiar with these datasets, you can find details in the schema definitions at https://aka.ms/SharePointDatasets. To assist you in using these datasets, the team has developed a Capacity Template. Initially published as a template for Azure Synapse, we now have a new Microsoft Fabric template that is simpler and offers more features. This SharePoint Capacity v2 Template, based on Microsoft Fabric, is now publicly available. 2. Instructions The template comes with a set of detailed instructions at https://aka.ms/fabriccapacitytemplatesteps. These instructions include: How to install the Microsoft Fabric and Microsoft Graph Data Connect prerequisites How to import the pipeline template from the Microsoft Fabric gallery and set it up How to import the Power BI template and configure the data source settings See below some additional details about the template. 3. Microsoft Fabric Pipeline After you import the pipeline template, it will look like this: 4. Pipeline in Microsoft Fabric The Capacity template for Microsoft Fabric includes a few key improvements: The new template uses delta datasets to update the SharePoint Sites and SharePoint Files datasets. It keeps track of the last time the datasets were pulled by this pipeline, requesting just what changed since then. The new template uses views to do calculations and create new properties like size bands or date bands. In our previous template, this was done in Power Query, when importing into Power BI. The new template also uses a view to aggregate file data, grouping the data by file extension. You can find details on how to find and deploy the Microsoft Fabric template in the instructions (see item 3). 5. Microsoft Fabric Report The typical result from this solution is a set of Power BI dashboards pulled from the Microsoft Fabric data source. Here are some examples: These dashboards serve as examples or starting points and can be modified as necessary for various visualizations of the data within these datasets. The instructions (see item 3) include details on how to find and deploy a few sample Power BI Capacity templates. 6. Conclusion I hope this provides a good overview of the Capacity template for Microsoft Fabric. You can read more about the Microsoft Graph Data Connect for SharePoint at https://aka.ms/SharePointData. There you will find many details, including a list of datasets available, other common scenarios and frequently asked questions.MGDC for SharePoint FAQ: How to Run a PoC without Pulling Your Entire Tenant
Overview When getting started with SharePoint data in Microsoft Graph Data Connect (MGDC) for SharePoint, many teams want to validate scenarios - such as reporting or analytics before committing to a full production deployment. A common first instinct is to pull a complete dataset from a production tenant. While this delivers the most comprehensive view of SharePoint usage, it also: Requires broad administrative authorization Consumes the most Azure compute and storage resources Increases MGDC extraction and processing costs Adds complexity to early experimentation Fortunately, MGDC for SharePoint provides multiple ways to run low‑cost experiments or proof‑of‑concept (POC) deployments using partial or scoped datasets. This guide presents these options using a uniform comparison model, helping you choose the right approach based on: Cost Representativeness of production behavior Implementation effort Dataset completeness Supported datasets Option 1: Use a Dev or Test Tenant Description Use an existing development or test tenant (or create a new trial tenant) to enable MGDC and run initial experiments. Pros Smaller datasets reduce MGDC and Azure costs Easier to obtain administrative permissions Lower operational impact Cons May not reflect production‑scale usage patterns Some SharePoint features or integrations may be missing Requires simulated user activity to generate meaningful data Trial tenants are time‑limited Learn More Microsoft 365 Trial Options Azure Trial Options Option 2: Start with the SharePoint Sites Dataset Description The Sites dataset is typically the smallest MGDC dataset for SharePoint and provides tenant‑wide metadata for all site collections. Pros Lower cost compared to Files or Permissions datasets Provides organization‑wide coverage Minimal MGDC configuration beyond standard onboarding Small dataset can be handled directly by a variety of analysis tools Cons Does not include permission or file details Limited insight compared to full datasets Learn More How can I estimate my Azure bill? Updated! Gather a detailed dataset on SharePoint Sites Option 3: Sample a Limited Number of Rows Description Some MGDC SharePoint datasets support returning only a subset of rows in query results. This is supported across the top 5 SharePoint datasets in MGDC (Sites, Permissions, Groups, Files and File Actions). Pros Minimal and predictable extraction cost Enables rapid schema inspection Provides total dataset row count in request metadata Cons Rows are not returned in a predictable order Sample is not randomized. It is not reproducible and could be biased Results should not be used to draw tenant‑level conclusions Learn More How can I sample or estimate the number of objects in a dataset? Option 4: Filter by SiteId Description Because SharePoint data is partitioned by site collection, MGDC filtering allows you to extract data from a single site or a small group of representative sites. This supports Sites, Permissions, Groups, Files and File Actions datasets. Pros Enables realistic workload simulation Reduces total extraction volume Simplifies downstream reporting Cons May introduce sampling bias Not suitable for tenant‑wide reporting Learn More How can I filter rows on a dataset? Option 5: Filter by TemplateId Description Instead of selecting individual sites, filter by site template to isolate specific workloads. For example, you could filter for OneDrives or SharePoint Embedded. Pros Consistent dataset scope Useful for workload‑specific analysis Cons Limited dataset support (supported only for Sites, Files and File Actions) May not reflect cross‑workload usage patterns Learn More How can I filter rows on a dataset? Option 6: Use Delta State Datasets Description Delta datasets allow you to retrieve only changes since your last data transfer for supported SharePoint State datasets. Pros Enables recurring analytics with lower extraction costs Supports daily or weekly trend analysis Reduces data movement after initial ingestion Cons Requires an initial full dataset pull Adds complexity to downstream merge processing Learn More How can I use Delta State Datasets? How do I process Deltas? Summary MGDC for SharePoint provides multiple approaches to extract targeted subsets of tenant data, allowing teams to: Run proof‑of‑concept deployments Validate analytics pipelines Test governance or migration scenarios Estimate ongoing MGDC and Azure costs By selecting the right combination of dataset scope, filtering strategy, sampling method or delta tracking, you can balance cost, representativeness, and implementation effort before scaling to a full production deployment. For additional guidance on MGDC for SharePoint, visit SharePoint Data in MGDC.
