DATA OPS

Weekly Stale-Model Owner Digest by Team

Each Monday morning it groups all BigQuery models breaching freshness by owning team and emails each owner a single ranked digest.

CategoryData Ops
Enginesim
Difficultybeginner
Triggerschedule
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly Monday schedule
  • ActionQuery week of breach historyGoogle BigQueryBigQuery
  • LogicGroup + rank by owning team
  • ActionEmail per-team digestGmailGmail
  • OutputPublish rollup to NotionNotionNotion

What it does

Instead of one ticket per stale table, this rolls up a full week of freshness breaches into a per-team digest. It ranks each team's models by how often and how badly they went stale, then emails each owning team one summary so they can decide what to fix in their next sprint.

When to use it

Use it when per-incident tickets create too much noise and you'd rather drive a weekly prioritization conversation. It complements the real-time sentinel: pages handle emergencies, this handles chronic decay.

How it works

  1. 1A weekly Monday-morning schedule fires.
  2. 2It queries BigQuery for the past week's freshness-breach history across all dbt models.
  3. 3A logic step groups breaches by owning team and ranks each model by breach frequency and worst lag.
  4. 4It composes one ranked Markdown digest per team from the grouped results.
  5. 5It emails each team's distribution list its own digest via Gmail.
  6. 6It writes the full cross-team rollup to a Notion data-health page for leadership review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect GmailRead, draft, send, label.
  3. 3
    Connect NotionPages, databases, comments.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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