DATA OPS

Audit dashboard queries against a changed BigQuery column

When a specific BigQuery column is dropped or retyped, scan logged dashboard and BI query history to list every query that still uses it.

CategoryData Ops
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerColumn-change webhookHTTP webhook
  • ActionConfirm change via BigQuery INFORMATION_SCHEMAGoogle BigQueryBigQuery
  • ActionSearch query history in Axiom for column referencesAxiom
  • LogicGroup affected queries by dashboard and resolve owners
  • OutputNotify dashboard owners in Microsoft TeamsMicrosoft Teams

What it does

Focuses the blast radius on the BI layer rather than dbt. When a tracked column changes, it searches your queried-from logs in Axiom (where you ship BigQuery job and dashboard query metadata) to find every saved query, scheduled report, or dashboard tile that referenced the column, and warns the people who own those dashboards.

When to use it

Use it when schema changes don't break pipelines but silently break charts — a renamed column makes a tile go blank or a filter stop working, and nobody notices until an exec asks why a number is gone. This catches the BI fallout that dbt-only checks miss.

How it works

  1. 1A webhook fires from your schema-tracking step when a column is dropped or retyped in BigQuery.
  2. 2The workflow confirms the change against BigQuery `INFORMATION_SCHEMA`.
  3. 3It queries Axiom for recent query logs that referenced the table and column.
  4. 4A logic step groups matching queries by dashboard and resolves each dashboard's owner.
  5. 5It sends each owner a Microsoft Teams message listing their affected dashboards and the column that moved.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect AxiomLog streams, queries, dashboards.
  3. 3
    Connect Microsoft TeamsChannels, chats, files.
  4. 4
    Connect HTTP webhookTrigger any URL on agent actions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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