CHATBOTS
Slack metric lineage tracer for BigQuery dashboards
Ask the bot how a metric is calculated and it traces the BigQuery lineage back to source tables, returning the SQL definition and every upstream dependency in the thread.
How it runs
The automated pipeline, trigger to output.
- TriggerSlack mention asking how a metric is calculatedSlack
- ActionMatch metric name against BigQuery views and routinesBigQuery
- ActionFetch view SQL and read INFORMATION_SCHEMA lineageBigQuery
- LogicRank upstream dependencies by depth to source tables
- ActionNarrate the calculation in business termsOpenAI
- OutputPost lineage chain, SQL, and source tables in SlackSlack
What it does
Answers 'where does this metric come from?' by walking BigQuery lineage. When someone asks about a dashboard number, the bot returns the view's SQL, the columns it reads, and the chain of upstream tables that feed it.
When to use it
When stakeholders distrust a KPI and the data team burns hours screen-sharing query editors to prove the math. Use it when your metrics are defined as BigQuery views or scheduled queries and lineage is the real question, not just a one-line description.
How it works
- 1A Slack mention asks about a named metric or view.
- 2The metric name is matched against the BigQuery information schema and routines.
- 3The bot fetches the view definition and reads INFORMATION_SCHEMA lineage and column references to assemble the upstream dependency tree.
- 4A logic step ranks dependencies by depth so the source-of-truth tables surface first.
- 5An OpenAI step narrates the calculation in business terms alongside the raw SQL.
- 6The reply posts the lineage chain, the SQL, and the source tables back in Slack.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect BigQueryDatasets, queries, schemas.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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