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google/datalineage-bigquery-asset-impact-analysis

google

datalineage-bigquery-asset-impact-analysis

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.

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v1.0Saved Jul 1, 2026

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:

  1. Executive Summary: State the total number of downstream assets affected and the maximum depth of the impact.

  2. Critical Path: Highlight high-priority downstream assets (e.g., assets containing "prod", "dashboard", "reporting", or "master" in their names).

  3. 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
  4. 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.

Crucial Constraints & Guardrails

  1. 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.
  2. Strictly Banned Bypasses:
    • Exclusively retrieve downstream relationships using the DataLineageServer:search_lineage tool.
  3. 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.
  4. 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.

External Documentation

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Overall Score

87/100

Grade

A

Excellent

Safety

88

Quality

89

Clarity

88

Completeness

83

Summary

This skill guides agents through performing downstream impact analysis (blast radius assessment) for broken, stale, or modified BigQuery tables and views. It provides a structured workflow to identify all downstream dependencies using the Google Cloud Data Lineage MCP server, then synthesizes findings into a clear impact report with executive summary, critical paths, and a comprehensive dependency table.

Detected Capabilities

Google Cloud API calls via MCPAsset metadata discovery (bq CLI)Lineage graph traversalExternal dependency resolutionJSON data transformation and reporting

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

bigquery impact analysisdownstream dependency checkblast radius assessmentdata lineage tracetable modification impact

Risk Signals

INFO

Calls to Google Cloud Data Lineage API via MCP server

Section 3: Retrieve the Downstream Lineage Graph
INFO

Requires GCP project credentials for MCP authentication

references/mcp-usage.md: MCP configuration block
INFO

Uses bq CLI to discover asset location

Section 2: Determine Locations and Parent Path
INFO

Traverses lineage graph structure without modifying data

Section 4: Identify the Blast Radius

Referenced Domains

External domains referenced in skill content, detected by static analysis.

cloud.google.comdatalineage.googleapis.comdocs.cloud.google.comwww.apache.org

Use Cases

  • Assess impact of BigQuery table modification or deletion
  • Identify downstream dashboards and processes affected by stale data
  • Analyze cascading failure consequences in data pipelines
  • Plan maintenance windows with full blast radius visibility
  • Understand column-level lineage for impact analysis

Quality Notes

  • Excellent workflow structure with clear numbered steps and prerequisites
  • Well-defined constraints and guardrails section prevents common pitfalls
  • Comprehensive output format requirements with exact table schema and metadata fields
  • Strong documentation of FQN format and location discovery process
  • Provides concrete examples (e.g., bigquery:my-prod-project.analytics.orders) for clarity
  • MCP configuration example reduces setup friction
  • Properly addresses edge cases (empty responses, missing assets, hallucinated artifacts)
  • References external documentation for deeper understanding
  • Clear distinction between direct impact (depth 1) and indirect impact (depth > 1)
  • Transparency note empowers users to request expanded searches
Model: claude-haiku-4-5-20251001Analyzed: Jul 1, 2026

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