DATA OPS
Daily Pipeline Freshness Scorecard
Each morning it computes the prior day's freshness SLA compliance across all tracked tables and posts a scorecard to Slack ranking the worst offenders.
How it runs
The automated pipeline, trigger to output.
- TriggerSchedule: daily each morning
- ActionQuery 24h of load events + SLA windowsSnowflake
- LogicCompute hit rate, worst lag, trend per table
- LogicSort worst-first into scorecard
- OutputPost freshness scorecard to SlackSlack
What it does
Instead of alerting on individual breaches, this run rolls up a full day of freshness measurements into a single scorecard. For each tracked table it reports how many load windows it hit versus missed over the last 24 hours, the worst single lag, and a trend arrow versus the prior day. The result is a ranked digest highlighting chronic underperformers.
When to use it
Use it when you want to manage freshness as a metric, not just firefight it. Real-time alerts catch today's outage; this catches the table that is quietly late three days a week and never quite triggers a page.
How it works
- 1A daily schedule fires each morning.
- 2It queries Snowflake for the last 24 hours of load events and SLA windows per table.
- 3It computes hit rate, worst lag, and day-over-day trend for each table.
- 4It sorts tables worst-first and formats a compact scorecard.
- 5It posts the scorecard to the data Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect SnowflakeWarehouses, queries, shares.
- 2Connect SlackChannels, DMs, threads, mentions.
- 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.
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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.
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