lineage-analysis

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 refreshes
• fabric-cli (fabric-cli plugin) -- Workspace and item management via fab CLI