DATA OPS
BigQuery-Backed Looker Decay Tracker into a Coda Retirement Registry
Monthly pulls Looker dashboard view counts from BigQuery audit logs, scores each by recency and reach, and upserts decay candidates into a Coda retirement registry for review.
How it runs
The automated pipeline, trigger to output.
- TriggerMonthly schedule starts the decay tracker
- ActionQuery BigQuery Looker audit logs for view metricsBigQuery
- LogicScore dashboards Healthy / Watch / Decay
- LogicFilter to Watch and Decay candidates
- OutputUpsert candidates into the Coda retirement registryCoda
What it does
Once a month it reads Looker usage from BigQuery's audit log exports, computes a decay score per dashboard from how recently and how widely it was viewed, and maintains a single Coda registry that the data team works down.
When to use it
Use this when you want a durable, browsable record of dashboard health rather than ephemeral alerts. Coda becomes the system of record where owners annotate, defer, or approve retirements over time.
How it works
- 1A monthly schedule starts the run.
- 2BigQuery is queried against Looker audit log tables for views, distinct viewers, and last-view date per dashboard.
- 3A scoring step classifies each dashboard as Healthy, Watch, or Decay using recency and unique-viewer thresholds.
- 4Only Watch and Decay rows pass the filter.
- 5Each row is upserted into a Coda table keyed by dashboard ID, preserving prior owner notes and status.
- 6The Coda row carries the score, idle days, and last viewer so reviewers can act in one place.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect CodaDocs, packs, automations.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Data Ops workflows
Weekly BigQuery Cost Trend Sheet and Exec Digest
Compiles week-over-week BigQuery scheduled-query cost by owner and dataset into a Google Sheet with trend columns.
Daily BigQuery Scheduled-Query Cost Attribution to Owners
Each morning, totals the prior day's on-demand bytes-billed per scheduled query, maps each query to its owner from a label, and posts a per-owner cost leaderboard to Slack.
BigQuery Per-Team Budget Breach Alert to PagerDuty
Tracks month-to-date BigQuery scheduled-query spend per team and, when a team crosses its monthly budget, pages the team's on-call in PagerDuty and snapshots the spend breakdown…
dbt source freshness watcher with severity-routed alerts
Checks Snowflake loaded-at timestamps against each dbt source's freshness SLA, then routes warnings to Slack and hard breaches to a PagerDuty incident so stale data never…
dbt orphan model detector with Linear cleanup tickets
Scans your dbt manifest for models that no other model, exposure, or BI tool consumes.
Raw Sensor Telemetry Archive to BigQuery
Captures every incoming building sensor reading via webhook, normalizes the payload into a consistent schema.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.