Solutions

Cost attribution

Every query finding names who ran it (person or service account), which tool sent it (dbt, Looker, Sheets, Airflow…) and which environment it hit, so each fix reaches the team that owns it.

On BigQuery

Available

Job-id prefixes, job labels and SQL comment headers classify dbt, Looker, Dataform, Airflow, Connected Sheets, scheduled queries, and the console. Dataset name tokens infer prod / staging / qa / dev.

BigQuery product

On Snowflake

Waitlist

Coming soon: QUERY_HISTORY user_name, client application, and warehouse labels mapped onto the same attribution dimensions so a Snowflake finding names a team too.

Snowflake product

On Databricks

Waitlist

Coming soon: query.history executed_by, client, and warehouse id mapped onto the same user / tool / environment dimensions.

Databricks product
How it works

A finding without a name never gets fixed

  1. 01

    Classify at fetch time

    No extra vendor APIs. The job record already has the signal.

  2. 02

    Roll up by person and tool

    Top users, workload mix, and environment share on every finding.

  3. 03

    Hand the list to the owner

    The dashboard is a conversation starter, not a mystery score.

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