datalineage-bigquery-asset-impact-analysis

Original：🇺🇸 English

Translated

Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset. - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset. Don't use for: - General BigQuery querying or data analysis (use BigQuery-related tools instead). - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage. - Creating or modifying lineage links directly.

6installs

Sourcegoogle/skills

Added on2026-07-04

NPX Install

npx skill4agent add google/skills datalineage-bigquery-asset-impact-analysis

SKILL.md Content

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BigQuery Asset Impact Analysis

This skill guides the agent in performing a downstream impact analysis (blast radius assessment) when a BigQuery table or view is reported as broken, stale, missing, or when a user is planning maintenance and wants to know the consequences of modifying or pausing updates to an asset.

It relies primarily on the Google Cloud Data Lineage (Knowledge Catalog) MCP Server to discover relationships between assets.

Prerequisites

This skill requires access to the Google Cloud Data Lineage API and an active client connection to the Data Lineage MCP Server. For detailed connection configurations and tool schemas, refer to MCP Usage.

Analysis Workflow

1. Resolve the Asset's Fully Qualified Name (FQN)

Ensure you have the correct FQN format for the BigQuery asset:

Format:

bigquery:{project_id}.{dataset_id}.{table_or_view_id}

Example:

bigquery:my-prod-project.analytics.orders

2. Determine Locations and Parent Path

Identify the locations to search and construct the Data Lineage API request:

Discover Asset Location: Run the command
```
bq show --format=json {project_id}:{dataset_id}
```
and extract the
```
location
```
field (e.g.,
```
us-central1
```
or
```
us
```
). If location discovery fails due to permissions or missing tools, prompt the user for the dataset's location.
Set Parent Path: Set the
```
parent
```
path using the project ID and the MCP server's location. Consult the
```
DataLineageServer
```
tool definition to find the configured region or location (e.g.,
```
us
```
). The format is:
```
projects/{project_id}/locations/{mcp_server_location}
```
.
Configure Search Scope: Include the discovered asset location in the
```
locations
```
array of the payload (e.g.,
```
["us-central1"]
```
or
```
["us", "us-central1"]
```
).

3. Retrieve the Downstream Lineage Graph

Call the

DataLineageServer:search_lineage

tool to fetch downstream relationships.

Direction: Set to
```
DOWNSTREAM
```
.
Search Parameters: Use
```
max_depth = 10
```
and
```
max_process_per_link = 5
```
as robust defaults.

4. Identify the Blast Radius

Traverse the returned lineage links to build the impact graph:

Affected Assets: The
```
target
```
of each link represents a downstream asset that depends on your source asset.
Transform Processes: Inspect the
```
processes
```
field on each link. This identifies the ETL pipelines, BigQuery Views, or Scheduled Queries that propagate the data.
Direct vs. Indirect Impact:
- Direct Impact (Depth 1): Assets directly consuming the source asset. If a link has
```
dependency_type: EXACT_COPY
```
  , mark the target as "Directly Stale / Identical Copy".
- Indirect Impact (Depth > 1): Assets further down the stream that will experience cascading stale data or failures.

5. Summarize and Format the Output

Present your findings clearly to the user using the following structure:

Executive Summary: State the total number of downstream assets affected and the maximum depth of the impact.
Critical Path: Highlight high-priority downstream assets (e.g., assets containing "prod", "dashboard", "reporting", or "master" in their names).
Blast Radius Table: A clean Markdown table listing the dependencies. You MUST include all columns:
Downstream Asset Transform Process Depth Impact Type
bigquery:project.dataset.table
projects/p/locations/l/processes/proc
1 Direct
bigquery:project.dataset.view
projects/p/locations/l/processes/view
2 Indirect
Analysis Metadata: Provide transparency on the parameters and boundaries of your search so the user can choose to expand them:
- Locations Searched:
```
{list_of_locations_queried}
```
- Parent Location:
```
{parent_path}
```
- Depth Limit:
```
{max_depth}
```
- Process per Link Limit:
```
{max_process_per_link}
```
- Tip for User: Let the user know they can request to rerun the analysis with expanded locations or larger depth limits.

Downstream Asset	Transform Process	Depth	Impact Type
`bigquery:project.dataset.table`	`projects/p/locations/l/processes/proc`	1	Direct
`bigquery:project.dataset.view`	`projects/p/locations/l/processes/view`	2	Indirect

Crucial Constraints & Guardrails

Interpret Empty Responses Correctly:
- If the lineage response is empty, immediately assume that no dependencies exist in the queried locations and report this to the user.
Strictly Banned Bypasses:
- Exclusively retrieve downstream relationships using the
```
DataLineageServer:search_lineage
```
  tool.
Verify Asset Existence First:
- If
```
bq show
```
  indicates the source table does not exist, stop and report this directly to the user. Do not attempt to guess alternative table names unless the user explicitly instructs you to do so.
No Output Shortcutting or Hallucinated Artifacts:
- Present the complete downstream blast radius table directly in your final response. Avoid telling the user you have created a separate Markdown file or artifact containing the details unless you have explicitly executed file-writing tools to create it.

Reference Directory

MCP Usage: Using the Google Cloud Data Lineage remote MCP server and tool preferences.