DATA OPS

Weekly reverse-ETL freshness scorecard to Notion

Each week, an agent profiles every reverse-ETL synced object, scores its freshness and drift against the Snowflake source.

CategoryData Ops
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule before the data-ops review
  • ActionQuery source-of-truth values per object from SnowflakeSnowflakeSnowflake
  • LogicScore freshness and drift per object and rank offenders
  • ActionWrite the ranked freshness scorecard to NotionNotionNotion
  • OutputPost a linked summary to the data-ops Slack channelSlack

What it does

Daily alerts catch fires; this workflow builds the weekly narrative. An agent walks each object your reverse-ETL pipeline syncs (accounts, contacts, opportunities), samples the synced CRM values against the Snowflake source of truth, and computes per-object freshness and drift scores. It then writes a structured Notion scorecard that ranks objects from healthiest to worst, calls out the fields most prone to drift, and recommends where to focus sync fixes. A short Slack summary links the page so the data-ops review meeting starts from evidence rather than anecdote.

When to use it

Use it for recurring data-quality reviews where you want trends and prioritization, not raw row-level alerts. It complements real-time monitors by giving leadership a readable weekly health view.

How it works

  1. 1A weekly schedule triggers the agent ahead of the review meeting.
  2. 2The agent enumerates synced objects and queries source values from Snowflake.
  3. 3It samples the synced values across CRM objects for comparison.
  4. 4It scores freshness and drift per object and ranks the offenders.
  5. 5It writes the ranked scorecard as a Notion page.
  6. 6It posts a linked summary to the data-ops Slack channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SnowflakeWarehouses, queries, shares.
  2. 2
    Connect NotionPages, databases, comments.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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.

Run this workflow in your colony.

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