data-goblin Lineage Analysis
Trace downstream dependencies from a semantic model to all connected reports across the tenant. No admin permissions required -- workspace contributor access is sufficient.
When to Use
- Before modifying or deleting a semantic model, to understand impact
- Auditing which reports are connected to a model and where they live
- Identifying orphaned or test reports connected to production models
- Cross-workspace dependency mapping
Downstream Reports
Run scripts/get-downstream-reports.py to find all reports bound to a semantic model.
# By workspace and model name
python3 scripts/get-downstream-reports.py "Workspace Name" "Model Name"
# By dataset GUID directly
python3 scripts/get-downstream-reports.py --dataset-id <guid>
# JSON output for further processing
python3 scripts/get-downstream-reports.py "Workspace" "Model" --json
Requirements: azure-identity, requests (pip install azure-identity requests). Authenticated via DefaultAzureCredential (works with az login, managed identity, or environment variables).
How it works: Lists all workspaces the user can access, then queries each workspace's reports in parallel (8 workers) checking datasetId. Groups results by workspace. Typically completes in under 10 seconds for ~100 workspaces.
Permissions: Workspace contributor or higher on any workspace to be scanned. Reports in workspaces without access will not appear. For full tenant coverage, use the --dataset-id flag with a tenant admin token and the admin/reports API instead.
Limitations
Reports are not the only consumers. A semantic model can also be consumed by:
- Analyze in Excel workbooks (.xlsx live connections)
- Composite models (other semantic models chaining via DirectQuery)
- Explorations (ad-hoc visual explorations in the Power BI service)
- Fabric notebooks (connecting via Spark or sempy)
- Fabric data agents
- Paginated reports (.rdl)
- Dataflows referencing the model
- Third-party tools connecting via XMLA
The script only discovers Power BI reports. For full dependency mapping including these other item types, use the Fabric lineage APIs (fab api "admin/groups/{id}/lineage") or the lineage view in the Power BI service UI.
Not appropriate for many models at once. The script scans all accessible workspaces per invocation. Running it in a loop over dozens of semantic models will generate excessive API calls and risk throttling. For bulk inventory across many models, use the admin scan API (fab api "admin/workspaces/getInfo") when tenant-admin access is available, or the cross-workspace catalog via fab find ... -P type=SemanticModel for a quick non-admin list. Neither alternative resolves report-to-model dependency edges; fab find and the OneLake catalog do not expose lineage. For that you still need either a per-workspace scan (this script's approach) or the official Power BI lineage admin API at fab api "admin/groups/{ws-id}/lineage".
Interpreting Results
| Field | Meaning |
|---|---|
Report format PBIR |
Modern format, editable as JSON |
Report format PBIRLegacy |
Legacy format, needs conversion to PBIR for direct editing |
| Reports in unexpected workspaces | May indicate copies, forks, or thin reports pointing at a shared model |
| Many downstream reports | High-impact model -- changes require coordination |
Related Skills
semantic-model-- Design, build, refresh, and review models (quality, memory, DAX, design)refreshing-semantic-model-- Trigger and monitor model refreshesfabric-cli(fabric-cli plugin) -- Workspace and item management viafabCLI
Source: data-goblin/power-bi-agentic-development → plugins/semantic-models/skills/lineage-analysis/SKILL.md