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
Archimedes planning...
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
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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
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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
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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
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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
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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
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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.
Microsoft